2025​‌Activity reportProject-TeamRAINBOW​​

3.2.1 Optimal and‌​‌ Uncertainty-Aware Sensing

Future robots​​ will need to have​​​‌ a large degree of‌ autonomy for, e.g., interpreting‌​‌ the sensory data for​​ accurate estimation of the​​​‌ robot and world state‌ (which can possibly include‌​‌ the human users), and​​ for devising motion plans​​​‌ able to take into‌ account many constraints (actuation,‌​‌ sensor limitations, environment), including​​ also the state estimation​​​‌ accuracy (i.e., how well‌ the robot/environment state can‌​‌ be reconstructed from the​​ sensed data). In this​​​‌ context, we will be‌ particularly interested in $(‌‌i)$ devising trajectory​​​‌ optimization strategies able to​ maximize some norm of​‌ the information gain gathered​​ along the trajectory (and​​​‌ with the available sensors).​ This can be seen​‌ as an instance of​​ Active Sensing, with the​​​‌ main focus on online/reactive​ trajectory optimization strategies able​‌ to take into account​​ several requirements/constraints (sensing/actuation limitations,​​​‌ noise characteristics). We will​ also be interested in​‌ the coupling between optimal​​ sensing and concurrent execution​​​‌ of additional tasks (e.g.,​ navigation, manipulation). $\left(\mathrm{i‌}i\right)$ Formal methods​​ for guaranteeing the accuracy​​​‌ of localization/state estimation in​ mobile robotics, mainly exploiting​‌ tools from interval analysis.​​ The interest of these​​​‌ methods is their ability​ to provide possibly conservative​‌ but guaranteed accuracy bounds​​ on the best accuracy​​​‌ one can obtain with​ the given robot/sensor pair,​‌ and can thus be​​ used for planning purposes​​​‌ or for system design​ (choice of the best​‌ sensors for a given​​ robot/task). $\left(i\mathrm{i‌}i\right)$ Localization/tracking of​ objects with poor/unknown or​‌ deformable shape, which will​​ be of paramount importance​​​‌ for allowing robots to​ estimate the state of​‌ “complex objects” (e.g., human​​ tissues in medical robotics,​​​‌ elastic materials in manipulation)​ for controlling its pose/interaction​‌ with the objects of​​ interest.

3.2.2 Advanced Sensor-based​​​‌ Control

One of the​ main competences of the​‌ previous Lagadic team has​​ been, generally speaking, the​​​‌ topic of sensor-based control​, i.e., how to​‌ exploit (typically onboard) sensors​​ for controlling the motion​​​‌ of fixed/ground robots. The​ main emphasis has been​‌ in devising ways to​​ directly couple the robot​​​‌ motion with the sensor​ outputs in order to​‌ invert this mapping for​​ driving the robots towards​​​‌ a configuration specified as​ a desired sensor reading​‌ (thus, directly in sensor​​ space). This general idea​​​‌ has been applied to​ very different contexts: mainly​‌ standard vision (from which​​ the Visual Servoing keyword),​​​‌ but also audio, ultrasound​ imaging, and RGB-D.

Use​‌ of sensors for controlling​​ the robot motion will​​​‌ also clearly be a​ central topic of the​‌ Rainbow team too, since​​ the use of (especially​​​‌ onboard) sensing is a​ main characteristic of any​‌ future robotics application (which​​ should typically operate in​​​‌ unstructured environments, and thus​ mainly rely on its​‌ own ability to sense​​ the world). We then​​​‌ naturally aim at making​ the best out of​‌ the previous Lagadic experience​​ in sensor-based control to​​​‌ propose new advanced ways​ of exploiting sensed data​‌ for, roughly speaking, controlling​​ the motion of a​​​‌ robot. In this respect,​ we plan to work​‌ on the following topics:​​ $\left(i\right)$ “direct/dense​​​‌ methods” which try to​ directly exploit the raw​‌ sensory data in computing​​ the control law for​​​‌ positioning/navigation tasks. The advantages​ of these methods is​‌ the little need for​​ data pre-processing which can​​​‌ minimize feature extraction errors​ and, in general, improve​‌ the overall robustness/accuracy (since​​ all the available data​​​‌ is used by the​ motion controller); $\left(\mathrm{i‌}i\right)$ sensor-based interaction​​ with objects of unknown/deformable​​​‌ shapes, for gaining the​ ability to manipulate, e.g.,​‌ flexible objects from the​​ acquired sensed data (e.g.,​​ controlling online a needle​​​‌ being inserted in a‌ flexible tissue); $\left(\mathrm{i‌‌}ii\right)$ sensor-based​​ model predictive control, by​​​‌ developing online/reactive trajectory optimization‌ methods able to plan‌​‌ feasible trajectories for robots​​ subject to sensing/actuation constraints​​​‌ with the possibility of‌ (onboard) sensing for continuously‌​‌ replanning (over some future​​ time horizon) the optimal​​​‌ trajectory. These methods will‌ play an important role‌​‌ when dealing with complex​​ robots affected by complex​​​‌ sensing/actuation constraints, for which‌ pure reactive strategies (as‌​‌ in most of the​​ previous Lagadic works) are​​​‌ not effective. Furthermore, the‌ coupling with the aforementioned‌​‌ optimal sensing will also​​ be considered; $\left(\mathrm{i‌}v\right)$ multi-robot decentralised‌ estimation and control, with‌​‌ the aim of devising​​ again sensor-based strategies for​​​‌ groups of multiple robots‌ needing to maintain a‌​‌ formation or perform navigation/manipulation​​ tasks. Here, the challenges​​​‌ come from the need‌ of devising “simple” decentralized‌​‌ and scalable control strategies​​ under the presence of​​​‌ complex sensing constraints (e.g.,‌ when using onboard cameras,‌​‌ limited fov, occlusions). Also,​​ the need of locally​​​‌ estimating global quantities (e.g.,‌ common frame of reference,‌​‌ global property of the​​ formation such as connectivity​​​‌ or rigidity) will also‌ be a line of‌​‌ active research.

3.2.3 Haptics​​ for Robotics Applications

In​​​‌ the envisaged shared cooperation‌ between human users and‌​‌ robots, the typical sensory​​ channel (besides vision) exploited​​​‌ to inform the human‌ users is most often‌​‌ the force/kinesthetic one (in​​ general, the sense of​​​‌ touch and of applied‌ forces to the human‌​‌ hand or limbs). Therefore,​​ a part of our​​​‌ activities will be devoted‌ to study and advance‌​‌ the use of haptic​​ cueing algorithms and interfaces​​​‌ for providing a feedback‌ to the users during‌​‌ the execution of some​​ shared task. We will​​​‌ consider: $(i)‌$ multi-modal haptic cueing for‌​‌ general teleoperation applications, by​​ studying how to convey​​​‌ information through the kinesthetic‌ and cutaneous channels. Indeed,‌​‌ most haptic-enabled applications typically​​ only involve kinesthetic cues,​​​‌ e.g., the forces/torques that‌ can be felt by‌​‌ grasping a force-feedback joystick/device.​​ These cues are very​​​‌ informative about, e.g., preferred/forbidden‌ motion directions, but are‌​‌ also inherently limited in​​ their resolution since the​​​‌ kinesthetic channel can easily‌ become overloaded (when too‌​‌ much information is compressed​​ in a single cue).​​​‌ In recent years, the‌ arise of novel cutaneous‌​‌ devices able to, e.g.,​​ provide vibro-tactile feedback on​​​‌ the fingertips or skin,‌ has proven to be‌​‌ a viable solution to​​ complement the classical kinesthetic​​​‌ channel. We will then‌ study how to combine‌​‌ these two sensory modalities​​ for different prototypical application​​​‌ scenarios, e.g., 6-dof teleoperation‌ of manipulator arms, virtual‌​‌ fixtures approaches, and remote​​ manipulation of (possibly deformable)​​​‌ objects; $\left(i\mathrm{i‌}\right)$ in the particular‌​‌ context of medical robotics,​​ we plan to address​​​‌ the problem of providing‌ haptic cues for typical‌​‌ medical robotics tasks, such​​ as semi-autonomous needle insertion​​​‌ and robot surgery by‌ exploring the use of‌​‌ kinesthetic feedback for rendering​​ the mechanical properties of​​​‌ the tissues, and vibrotactile‌ feedback for providing with‌​‌ guiding information about pre-planned​​​‌ paths (with the aim​ of increasing the usability/acceptability​‌ of this technology in​​ the medical domain); $(‌iii)$ finally, in the context​‌ of multi-robot control we​​ would like to explore​​​‌ how to use the​ haptic channel for providing​‌ information about the status​​ of multiple robots executing​​​‌ a navigation or manipulation​ task. In this case,​‌ the problem is (even​​ more) how to map​​​‌ (or compress) information about​ many robots into a​‌ few haptic cues. We​​ plan to use specialized​​​‌ devices, such as actuated​ exoskeleton gloves able to​‌ provide cues to each​​ fingertip of a human​​​‌ hand, or to resort​ to “compression” methods inspired​‌ by the hand postural​​ synergies for providing coordinated​​​‌ cues representative of a​ few (but complex) motions​‌ of the multi-robot group,​​ e.g., coordinated motions (translations/expansions/rotations)​​​‌ or collective grasping/transporting.

3.2.4​ Shared Control of Complex​‌ Robotics Systems

This final​​ and main research axis​​​‌ will exploit the methods,​ algorithms and technologies developed​‌ in the previous axes​​ for realizing applications involving​​​‌ complex semi-autonomous robots operating​ in complex environments together​‌ with human users. The​​ leitmotiv is to realize​​​‌ advanced shared control paradigms,​ which essentially aim at​‌ blending robot autonomy and​​ user's intervention in an​​​‌ optimal way for exploiting​ the best of both​‌ worlds (robot accuracy/sensing/mobility/strength and​​ human's cognitive capabilities). A​​​‌ common theme will be​ the issue of where​‌ to “draw the line”​​ between robot autonomy and​​​‌ human intervention: obviously, there​ is no general answer,​‌ and any design choice​​ will depend on the​​​‌ particular task at hand​ and/or on the technological/algorithmic​‌ possibilities of the robotic​​ system under consideration.

A​​​‌ prototypical envisaged application, exploiting​ and combining the previous​‌ three research axes, is​​ as follows: a complex​​​‌ robot (e.g., a two-arm​ system, a humanoid robot,​‌ a multi-UAV group) needs​​ to operate in an​​​‌ environment exploiting its onboard​ sensors (in general, vision​‌ as the main exteroceptive​​ one) and deal with​​​‌ many constraints (limited actuation,​ limited sensing, complex kinematics/dynamics,​‌ obstacle avoidance, interaction with​​ difficult-to-model entities such as​​​‌ surrounding people, and so​ on). The robot must​‌ then possess a quite​​ large autonomy for interpreting​​​‌ and exploiting the sensed​ data in order to​‌ estimate its own state​​ and the environmental one​​​‌ (“Optimal and Uncertainty-Aware​ Sensing” axis), and​‌ for planning its motion​​ in order to fulfil​​​‌ the task (e.g., navigation,​ manipulation) by coping with​‌ all the robot/environment constraints.​​ Therefore, advanced control methods​​​‌ able to exploit the​ sensory data at its​‌ most, and able to​​ cope online with constraints​​​‌ in an optimal way​ (by, e.g., continuously replanning​‌ and predicting over a​​ future time horizon) will​​​‌ be needed (“Advanced​ Sensor-based Control” axis),​‌ with a possible (and​​ interesting) coupling with the​​​‌ sensing part for optimizing,​ at the same time,​‌ the state estimation process.​​ Finally, a human operator​​​‌ will typically be in​ charge of providing high-level​‌ commands (e.g., where to​​ go, what to look​​​‌ at, what to grasp​ and where) that will​‌ then be autonomously executed​​ by the robot, with​​ possible local modifications because​​​‌ of the various (local)‌ constraints. At the same‌​‌ time, the operator will​​ also receive online visual-force​​​‌ cues informative of, in‌ general, how well her/his‌​‌ commands are executed and​​ if the robot would​​​‌ prefer or suggest other‌ plans (because of the‌​‌ local constraints that are​​ not of the operator's​​​‌ concern). This information will‌ have to be visually‌​‌ and haptically rendered with​​ an optimal combination of​​​‌ cues that will depend‌ on the particular application‌​‌ (“Haptics for Robotics​​ Applications” axis).

7.1.1 HandiViz

• Name:​​
  Driving assistance of a​​​‌ wheelchair
• Keywords:
  Health, Persons‌ attendant, Handicap
• Functional Description:‌​‌

  Preserving the autonomy and​​ the mobility is essential​​​‌ for disabled people well-being.‌ The HandiViz software proposes‌​‌ a semi-autonomous navigation framework​​ of a wheelchair relying​​​‌ on visual servoing along‌ corridors. This control system‌​‌ relies on the combination​​ of two tasks: first​​​‌ the manual steering and‌ second wall avoidance task‌​‌ obtained by a dedicated​​ visual based servoing approach.​​​‌ The idea is then‌ to correct the trajectory‌​‌ indicated by the patient​​ by servoing only the​​​‌ necessary degrees of freedom.‌ This visual servoing process‌​‌ is based on both​​ the vanishing point and​​​‌ wall plane detection. A‌ smooth transition from manual‌​‌ driving to assisted naviga-​​ tion is obtained thanks​​​‌ to an adapted weighting‌ function, thus avoiding discontinuities‌​‌ that can lead to​​ unpleasant experience.

  It has​​​‌ been registered to the‌ APP (“Agence de Protection‌​‌ des Programmes”) as an​​ INSA software (IDDN.FR.001.440021.000.S.P.2013.000.10000) and​​​‌ is under GPL license.‌

• Contact:
  Marie Babel
• Participants:‌​‌
  François Pasteau, Marie Babel​​
• Partner:
  INSA Rennes

7.1.2​​​‌ ViSP

• Name:
  Visual servoing‌ platform
• Keywords:
  Computer vision,‌​‌ Robotics, Visual servoing (VS),​​ Visual tracking
• Scientific Description:​​​‌

  Since 2004, we develop‌ and release ViSP [1],‌​‌ an open source library​​ available from https://­visp.­inria.­fr.​​​‌ ViSP standing for Visual‌ Servoing Platform allows prototyping‌​‌ and developing applications using​​ visual tracking and visual​​​‌ servoing techniques at the‌ heart of the Rainbow‌​‌ research. ViSP was designed​​ to be independent from​​​‌ the hardware, to be‌ simple to use, expandable‌​‌ and cross-platform. ViSP allows​​ designing vision-based tasks for​​​‌ eye-in-hand and eye-to-hand systems‌ from the most classical‌​‌ visual features that are​​ used in practice. It​​​‌ involves a large set‌ of elementary positioning tasks‌​‌ with respect to various​​ visual features (points, segments,​​​‌ straight lines, circles, spheres,‌ cylinders, image moments, pose...)‌​‌ that can be combined​​ together, and image processing​​​‌ algorithms that allow tracking‌ of visual cues (dots,‌​‌ segments, ellipses...), or 3D​​ model-based tracking of known​​​‌ objects or template tracking.‌ Simulation capabilities are also‌​‌ available.

  ViSP also provides​​ an open-source dynamic simulator​​​‌ called FrankaSim based on‌ CoppeliaSim and ROS for‌​‌ the Panda robot from​​ Franka Robotics [2]. The​​​‌ simulator fully integrated in‌ the ViSP ecosystem features‌​‌ a dynamic model that​​ has been accurately identified​​​‌ from a real robot,‌ leading to more realistic‌​‌ simulations. Conceived as a​​ multipurpose research simulation platform,​​​‌ it is well suited‌ for visual servoing applications‌​‌ as well as, in​​ general, for any pedagogical​​​‌ purpose in robotics. All‌ the software, models and‌​‌ CoppeliaSim scenes presented in​​ this work are publicly​​​‌ available under free GPL-2.0‌ license.

  A module dedicated‌​‌ to deep neural networks​​​‌ (DNN) is also available​ to facilitate image classification​‌ and object detection. This​​ module can infer the​​​‌ convolutional networks Faster-RCNN, SSD-MobileNet,​ ResNet 10, Yolo v3,​‌ Yolo v4, Yolo v5,​​ Yolo v7, Yolo v8​​​‌ and Yolo v11, which​ simultaneously predict object boundaries​‌ and prediction scores at​​ each position.

  A new​​​‌ module dedicated to the​ visual tracking of an​‌ object using its model​​ has been introduced. Called​​​‌ RBT for Render-Based-Tracker, it​ enables complex objects to​‌ be localized in real​​ time by robustly combining​​​‌ geometric features, colour-based features​ and depth map features​‌ in the minimisation process.​​ We also introduced Python​​​‌ bindings to populate ViSP​ into the vision and​‌ robotics community.

  [1] E.​​ Marchand, F. Spindler, F.​​​‌ Chaumette. ViSP for visual​ servoing: a generic software​‌ platform with a wide​​ class of robot control​​​‌ skills. IEEE Robotics and​ Automation Magazine, Special Issue​‌ on "Software Packages for​​ Vision-Based Control of Motion",​​​‌ P. Oh, D. Burschka​ (Eds.), 12(4):40-52, December 2005.​‌ URL: https://hal.inria.fr/inria-00351899v1

  [2] A.​​ A. Oliva, F. Spindler,​​​‌ P. Robuffo Giordano and​ F. Chaumette. ‘FrankaSim: A​‌ Dynamic Simulator for the​​ Franka Emika Robot with​​​‌ Visual-Servoing Enabled Capabilities’. In:​ ICARCV 2022 - 17th​‌ International Conference on Control,​​ Automation, Robotics and Vision.​​​‌ Singapore, Singapore, 11th Dec.​ 2022, pp. 1–7. URL:​‌ https://hal.inria.fr/hal-03794415.

• Functional Description:
  ViSP​​ provides simple ways to​​​‌ integrate and validate new​ algorithms with already existing​‌ tools. It follows a​​ module-based software engineering design​​​‌ where data types, algorithms,​ sensors, viewers and user​‌ interaction are made available.​​ Written in C++, ViSP​​​‌ is based on open-source​ cross-platform libraries (such as​‌ OpenCV) and builds with​​ CMake. Several platforms are​​​‌ supported, including OSX, iOS,​ Windows and Linux. ViSP​‌ online documentation allows to​​ ease learning. More than​​​‌ 307 fully documented classes​ organized in 18 different​‌ modules, with more than​​ 475 examples and 114​​​‌ tutorials are proposed to​ the user. ViSP is​‌ released under a dual​​ licensing model. It is​​​‌ open-source with a GNU​ GPLv2 or GPLv3 license.​‌ A professional edition license​​ that replaces GNU GPL​​​‌ is also available.
• URL:​
  https://­visp.­inria.­fr
• Contact:
  Fabien Spindler​‌
• Participant:
  5 anonymous participants​​

7.1.3 DIARBENN

• Name:
  Obstacle​​​‌ avoidance through sensor-based servoing​
• Keywords:
  Servoing, Shared control,​‌ Navigation
• Functional Description:

  Diarbenn​​ is a semi-autonomous robotic​​​‌ assistance module for elec-​ tric wheelchairs (EW), i.e.,​‌ a control system shared​​ with the user. This​​​‌ module is designed to​ accessorize Powered wheelchair (PWC)​‌ to improve safety conditions​​ when driving. The device​​​‌ consists of several sensor​ boxes and a control​‌ box. The sensor boxes​​ measure the distances around​​​‌ the PWC. The measurements​ from the sensor boxes​‌ are then processed by​​ the control box to​​​‌ ensure safe operation of​ the PWC.

  Speed Constraint​‌ of the PWC are​​ calculated based on distances​​​‌ measured around the wheelchair.​ These constraints, derived from​‌ the environment, are then​​ merged with the user’s​​​‌ command (data from the​ control box) in order​‌ to recalculate the speed​​ to be applied to​​​‌ the wheelchair to gradually​ modify its trajectory and​‌ avoid collisions with the​​ environment, while respecting the​​ user’s intention as closely​​​‌ as possible. With the‌ module activated, the PWC‌​‌ will stop when it​​ approaches an obstacle at​​​‌ a desired distance. In‌ the event of an‌​‌ oblique approach, the PWC​​ will autonomously bypass the​​​‌ obstacle by running alongside‌ it. At any time,‌​‌ the user can interrupt​​ the assisted maneuver by​​​‌ releasing the control, as‌ with a traditional PWC.‌​‌ In addition, these sensors​​ have been designed and​​​‌ positioned to be protected‌ or resistant to collisions‌​‌ with the environment. Their​​ robustness has been proven​​​‌ in laboratory tests.

• Contact:‌
  Marie Babel
• Participant:
  3‌​‌ anonymous participants
• Partner:
  INSA​​ Rennes

7.1.4 telekyb3

• Name:​​​‌
  Free and open source‌ collection of software for‌​‌ Unmanned Aerial Vehicles (UAVs)​​
• Keyword:
  Robot system
• Functional​​​‌ Description:

  The main features‌ of telekyb3 include access‌​‌ to all low-level components​​ and closed-loop control of​​​‌ each robot actuator—critical elements‌ for research in aerial‌​‌ physical interaction and manipulation.​​

  Moreover, it is designed​​​‌ with a strong focus‌ on modularity and code‌​‌ reusability. Components use and​​ provide common interfaces, which​​​‌ makes it possible to‌ easily swap between interface-compatible‌​‌ modules. Additionally, the framework​​ is designed to be​​​‌ middleware-independent: users need only‌ focus on writing the‌​‌ code related to their​​ chosen algorithm, while the​​​‌ remaining boilerplate required to‌ run it is automatically‌​‌ generated for the target​​ middleware (e.g., ROS, YARP,​​​‌ pocolibs).

  Lastly, it can‌ support a wide variety‌​‌ of aerial robots: it​​ allows controlling not only​​​‌ one or multiple platforms,‌ but also robots with‌​‌ different actuator configurations.

  The​​ project originally started at​​​‌ LAAS–CNRS in Toulouse in‌ 2015. Over the years,‌​‌ the framework has been​​ extensively used within the​​​‌ laboratory, and several researchers‌ who moved to other‌​‌ institutions chose to continue​​ using it for its​​​‌ features, strong modularity, and‌ its ability to adapt‌​‌ easily to evolving research​​ needs.

  Today, IRISA–Inria counts​​​‌ roughly a dozen users‌ and contributors. Since 2023,‌​‌ it has been supporting​​ LAAS in maintaining the​​​‌ software, developing new modules,‌ and adding new features.‌​‌ The framework is now​​ also used by international​​​‌ partners, including the University‌ of Twente and Saxion‌​‌ University of Applied Sciences​​ in the Netherlands, and​​​‌ University College London in‌ the United Kingdom.

• URL:‌​‌
  https://­git.­openrobots.­org/­projects/­telekyb3
• Contact:
  Gianluca Corsini​​
• Partner:
  CNRS

7.2.1 Robot Vision Platform‌

Participants: François Chaumette,‌​‌ Eric Marchand, Fabien​​ Spindler [contact].

We​​​‌ are using an industrial‌ robot built by Afma‌​‌ Robots in the nineties​​ to validate our research​​​‌ in visual servoing and‌ active vision. This robot‌​‌ is a 6 DoF​​ Gantry on which it​​​‌ is possible to mount‌ a gripper and an‌​‌ RGB-D camera on its​​ end effector (see Fig.​​​‌ 2). This equipment‌ is mainly used to‌​‌ validate vision-based visual servoing​​ and real-time tracking algorithms.​​​‌

In 2025, this platform‌ has been used to‌​‌ validate experimental results in​​​‌ 1 accepted publication 23​.

In this image​‌ we can see our​​ Gantry robot.

7.2.2​‌ Mobile Robots

Participants: Marie​​ Babel, François Pasteau​​​‌, Fabien Spindler [contact]​.

To validate our​‌ research in personally assisted​​ living topic (see Sect.​​​‌ 8.3.2), we have​ now five electric wheelchairs​‌ (see Fig. 3.a).​​ The control of the​​​‌ wheelchair is performed using​ a plug and play​‌ system between the joystick​​ and the low level​​​‌ control of the wheelchair.​ Such a system lets​‌ us acquire the user​​ intention through the joystick​​​‌ position and control the​ wheelchair by applying corrections​‌ to its motion. The​​ wheelchairs have been fitted​​​‌ with cameras, ultrasound and​ time of flight sensors​‌ to perform the required​​ servoing for assisting handicapped​​​‌ people. A wheelchair haptic​ simulator completes this platform​‌ to develop new human​​ interaction strategies in a​​​‌ virtual reality environment (see​ Fig. 3.b). Moreover,​‌ for fast prototyping of​​ multi-robot control algorithms, since​​​‌ end of 2025 the​ platform provides about ten​‌ DJI RoboMaster S1 mobile​​ ground robots (see Fig.​​​‌ 3.c).

In 2025,​ these robots were used​‌ to obtain experimental results​​ presented in 1 PhD​​​‌ thesis 75 and in​ multiple papers 17,​‌ 19, 31,​​ 59, 62,​​​‌ 63.

(a)	(b)​	(c)

In the left​‌ image, our wheelchairs from​​ Permobil, Sunrise and YouQ.​​​‌ In the middle image​ our wheelchair simulator. In​‌ the next image, one​​ of our DJI RoboMaster​​​‌ S1 ground mobile robot.​

7.2.3 Advanced​​ Manipulation Platform

Participants: Alexandre​​​‌ Krupa, Claudio Pacchierotti​, Paolo Robuffo Giordano​‌, François Chaumette,​​ Fabien Spindler [contact].​​​‌

This platform consists of​ by 2 Panda lightweight​‌ 7 DoF arms from​​ Franka Emika and 1​​​‌ from Franka Robotics acquired​ end of 2025. They​‌ are equipped with torque​​ sensors in all seven​​​‌ axes. The following end​ effectors can be mounted​‌ on the robot: an​​ electric gripper, a camera,​​​‌ a soft hand from​ qbrobotics (see Fig. 4​‌.a) and a Reflex​​ TakkTile 2 gripper from​​​‌ RightHand Labs. A​ force-torque sensor from Alberobotics​‌ is also attached to​​ one of the robots​​​‌ end effector to provide​ greater accuracy in torque-controlled​‌ tasks.

Two Adept 6-DoFs​​ arms (one Viper 650​​​‌ robot and one Viper​ 850 robot) and a​‌ 6-DoFs Universal Robots UR5​​ complete this platform category.​​​‌

Moreover, since June 2025,​ the platform has been​‌ supplemented by the acquisition​​ of a new TRIAGo​​​‌ robot from the company​ PAL Robotics (see Fig.​‌ 4.b). This robot​​ is unique in the​​​‌ world. It was funded​ by the TIRREX Equipex​‌ and by Inria. It​​ consists of a holonomic​​​‌ mobile base, on top​ of which sits a​‌ motorized torso, to which​​ three 7-degree-of-freedom arms are​​​‌ attached. The end-effectors of​ these arms are modular​‌ and can be equipped​​ with ATI force sensors​​ and Allegro hands whose​​​‌ phalanges are fitted with‌ Xela tactile sensors. This‌​‌ platform category is mainly​​ used to validate our​​​‌ research in coupling force‌ and vision control when‌​‌ attempting to manipulate deformable​​ and soft objects. Other​​​‌ haptic devices can also‌ be paired to any‌​‌ robot in this category.​​

This platform (see Fig.​​​‌ 4.c) is mainly‌ used to manipulate deformable‌​‌ objects and to validate​​ our activities in coupling​​​‌ force and vision for‌ controlling robot manipulators (see‌​‌ Section 8.3.1) and​​ in controlling the deformation​​​‌ of soft objects (Sect.‌ 8.1.8). Other haptic‌​‌ devices (see Section 8.2​​) can also be​​​‌ coupled to this platform.‌

In 2025, 1 paper‌​‌ 58 and 1 PhD​​ thesis 71 were published​​​‌ including experimental results obtained‌ with this platform.

(a)‌​‌		(b)		(c)

In the​​ left image our Franka​​​‌ robot equipped with the‌ Pisa SoftHand grasping a‌​‌ box. In the middle​​ image the TRIAGo robot​​​‌ from PAL Robotics. In‌ the right image the‌​‌ 5 arms composing the​​ platform with in the​​​‌ foreground a Franka, in‌ the second plan our‌​‌ two Viper robots, then​​ in the background, a​​​‌ UR 5 arm and‌ our second Franka robot.‌​‌

7.2.4 Unmanned Aerial Vehicles​​ (UAVs)

Participants: Gianluca Corsini​​​‌ [contact], Paolo Robuffo‌ Giordano, Marco Tognon‌​‌, Claudio Pacchierotti,​​ Fabien Spindler, Esteban​​​‌ Restrepo.

Rainbow is‌ involved in several activities‌​‌ concerning conception, modelling, control​​ and perception for single​​​‌ and multiple aerial robots‌ (ARs). Two indoor flying‌​‌ arenas are used to​​ carry out the related​​​‌ experimental activities. The first‌ arena is relatively small‌​‌ (3m x 5m x​​ H1.8m) and is equipped​​​‌ with 11 Vicon cameras‌ for motion capture. The‌​‌ second one, spanning a​​ larger volume (about 9m​​​‌ x 9m x H2.5m),‌ is equipped with 14‌​‌ Qualisys cameras. However, the​​ latter room is only​​​‌ available within the period‌ from January to August.‌​‌ Compared to the former,​​ the larger arena grants​​​‌ us with the possibility‌ to fly multiple drones‌​‌ at the same time​​ thanks to the larger​​​‌ volume and the great‌ coverage offered by the‌​‌ larger number of cameras.​​

In these flying arenas,​​​‌ we operate several customized‌ ARs which have been‌​‌ heavily customised by: reprogramming​​ from scratch the low-level​​​‌ firmwares running on the‌ onboard electronics (comprising flight‌​‌ and motor controllers), equipping​​ each robot with an​​​‌ onboard computer (for instance‌ a Jetson or a‌​‌ NUC board) running Linux​​ Ubuntu and the telekyb3​​​‌ software framework, and adding‌ Realsense RGB-D cameras for‌​‌ onboard visual odometry and​​ visual servoing.

The framework​​​‌ telekyb3 is an open-source‌ architecture based on the‌​‌ Genom3 software tool which​​​‌ has been developed at​ LAAS in Toulouse. It​‌ features a modular and​​ formal structure tailored to​​​‌ code reusability, high performance​ and middleware abstraction. It​‌ comprises a set of​​ algorithms dedicated to localization,​​​‌ navigation and low-level control​ of aerial robots in​‌ maneuvering and physical-interaction-based tasks.​​

The aerial robotic platform​​​‌ of the team includes​ quadrotors and hexarotors (see​‌ Fig. 5.a and​​ 5.b, respectively) which​​​‌ have been internally designed​ both at the mechanical​‌ and the electronic level.​​ While the quadrotors have​​​‌ a standard (in jargon,​ collinear) propeller orientation, the​‌ hexarotors have the motors​​ tilted w.r.t. the main​​​‌ body. This property grants​ them with maneuvering capabilities​‌ that cannot be replicated​​ by conventional and commercial​​​‌ drones with collinear rotors.​

For most of the​‌ mechanical components, we rely​​ on custom parts which​​​‌ are then realized by​ exploiting 3D printing technology​‌ and water-jet and milling​​ processes of carbon-fiber material.​​​‌ From the electronic standpoint,​ our robots feature a​‌ Mikrokopter-based flight controller running​​ custom firmware. However, due​​​‌ to the unavailability and​ aging of the latter​‌ board, a newer flight​​ controller named Paparazzi, has​​​‌ been adopted and consequently​ the firmware adapted to​‌ the new board. The​​ Paparazzi flight controller is​​​‌ part of an open-source​ and open-hardware project started​‌ at ENAC in Toulouse.​​ This board has been​​​‌ chosen as it fits​ well our needs: it​‌ comprises more precise onboard​​ sensors and sufficient programmable​​​‌ peripherals used to communicate​ with the other electronic​‌ modules and sensors.

Smaller​​ commercial drones, namely the​​​‌ BitCraze Crazyflie, have been​ added to this robotic​‌ platform. Thanks to the​​ tiny dimensions of these​​​‌ drones and considering the​ limited available space for​‌ experiments, these robots are​​ perfect candidates to carry​​​‌ out research related to​ the control and perception​‌ of a team of​​ multiple robots.

Among the​​​‌ different successful experiments, we​ can annoverate a visual​‌ servoing using ViSP to​​ position the drone w.r.t.​​​‌ a target and to​ manipulate deformable objects (e.g.​‌ a cable), accurate positioning​​ of a swarm of​​​‌ (more than 5) robots,​ contact-based interaction with flat​‌ surfaces (for instance, drawing​​ on a whiteboard) by​​​‌ means of a hexarotor​ equipped with a rigid​‌ end-effector.

In 2025, multiple​​ papers 33, 37​​​‌, 43, 44​, 18, 65​‌, 22, 34​​, 20 contain experimental​​​‌ results obtained with this​ platform.

(a)		(b)

In​‌ the left image, one​​ of our quadrotors. In​​​‌ the right image, our​ hexarotor with tilted propellers.​‌

7.2.5​​ Interactive interfaces and systems​​​‌

Participants: Claudio Pacchierotti,​ Paolo Robuffo Giordano,​‌ Maud Marchal, Marie​​ Babel, Fabien Spindler​​​‌ [contact].

Interactive technologies​ enables the communication between​‌ artificial systems and human​​ users. Examples of such​​​‌ technologies are haptic interfaces​ and virtual reality headsets.​‌

Various haptic devices are​​ used to validate our​​​‌ research in, e.g., shared​ control and extended reality.​‌ We design some wearable​​ haptics devices to enhance​​ the user robotic interaction​​​‌ with sensorial feedback, while‌ some other devices are‌​‌ bought from off-the-shelf products,​​ such as a Virtuose​​​‌ 6D device and Desktop‌ 6D device acquired fall‌​‌ 2025 from Haption (see​​ Fig. 6.a). For​​​‌ instance, the latter equipment‌ is used as the‌​‌ master device in many​​ of our shared control​​​‌ activities. An Omega 6‌ (see Fig. 6.b)‌​‌ from Force Dimension and​​ devices from Ultrahaptics (see​​​‌ Fig. 6.c) complete‌ this platform that could‌​‌ be coupled to the​​ other robotic systems.

Similarly,​​​‌ in order to augment‌ the immersiveness of virtual‌​‌ scenarios, we make use​​ of virtual and augmented​​​‌ reality headsets, namely HTC‌ Vive headsets for VR‌​‌ tasks and Microsoft Hololens​​ for Augmented Reality interactions.​​​‌ (see Fig. 6.d).‌

In 2025, this platform‌​‌ was used to obtain​​ experimental results presented in​​​‌ multiple papers 24,‌ 34, 46,‌​‌ 47, 64,​​ 53, 66,​​​‌ 56, 57,‌ 54, 55.‌​‌

(a)		(b)		(c)		(d)​​

Left image, our Virtuose​​​‌ 6D haptic device, in‌ the middle-left our Omega6‌​‌ haptic device, in the​​ middle-right image the Ultraleap​​​‌ STRATOS device, and in‌ the right our Microsoft‌​‌ Hololens 2 AR headset​​

8.1.1 Integrated Robust​​​‌ Planning and Control for‌ Uncertain Robots

Participants: Tommaso‌​‌ Belvedere, Paolo Robuffo​​ Giordano.

The goal​​​‌ of this research activity‌ is to propose an‌​‌ integrated approach for robust​​ planning and control of​​​‌ robots whose models are‌ affected by uncertainty in‌​‌ some of their parameters.​​ The results are based​​​‌ on the notion of‌ closed-loop state sensitivity developed‌​‌ in our group since​​ several years, and are​​​‌ also related to the‌ ANR project CAMP (Sect.‌​‌ 10.4.8) and of​​ the recent Cluster SequoIA​​​‌ HARMONY (Sect. 10.4.16).‌

Over the past years,‌​‌ we have developed several​​ trajectory optimization algorithms leveraging​​​‌ the notion of closed-loop‌ “state sensitivity”, “input sensitivity”‌​‌ and derived quantities. In​​ particular, exploiting these metrics​​​‌ we were able to‌ construct tubes enveloping the‌​‌ bundle of perturbed trajectories​​ given an uncertainty model​​​‌ (a range of variation‌ for the parameters around‌​‌ a nominal value). During​​ this year we have​​​‌ continued working on this‌ subject with the following‌​‌ contributions:

• in 40,​​ we experimentally validated the​​​‌ sensitivity framework in the‌ context of robust manipulation‌​‌ control for a robot​​ manipulator. Our objective was​​​‌ to assess how to‌ enhance the closed-loop robustness‌​‌ against payload variations during​​ precise manipulation tasks. We​​​‌ conducted a series of‌ experiments to validate our‌​‌ optimization approach across different​​ trajectories, focusing primarily on​​​‌ evaluating the precision of‌ the manipulator’s end-effector at‌​‌ critical moments where high​​ accuracy is essential like,​​​‌ for example, while tossing‌ objects. The experimental campaign‌​‌ confirmed the validity of​​​‌ the approach.
• in 38​, we performed a​‌ principled study on the​​ “sensitivity tubes”. Indeed, these​​​‌ tubes are traditionally built​ from ellipsoidal uncertainty sets​‌ and used to robustify​​ system constraints. These ellipsoids,​​​‌ however, are themselves smooth​ approximations of underlying hyperboxes​‌ in the parameter space,​​ leading to an inaccurate​​​‌ estimation of the parameter​ set. We then extended​‌ our framework by proposing​​ two new formulations that​​​‌ more precisely represent the​ real closed-loop behavior of​‌ the system through improved​​ computation of the sensitivity​​​‌ tubes. The first constructs​ tubes directly from hyperboxes,​‌ exactly preserving the original​​ parameter bounds but producing​​​‌ a non-differentiable description. The​ second employs superquadrics, which​‌ smoothly approximate the hyperbox​​ with user-tunable fidelity while​​​‌ preserving differentiability, as in​ the ellipsoidal case. Both​‌ methods were extensively validated​​ in a simulation campaign.​​​‌
• in 20, 50​ we proposed an `online'​‌ reactive trajectory optimization based​​ on sensitivity metrics for​​​‌ increasing the robustness against​ model uncertainties. In particular,​‌ in 20 we developed​​ a MPC scheme leveraging​​​‌ the sensitivity formulation: one​ key contribution lied in​‌ the introduction of a​​ computationally efficient robust MPC​​​‌ formulation with a comparable​ computational complexityto a standard​‌ MPC (i.e., an MPC​​ not explicitly dealing with​​​‌ parametric uncertainty). An extensive​ simulation campaign was presented​‌ to demonstrate the effectiveness​​ of the proposed approach​​​‌ in handling parametric uncertainties​ and enhancing task performance,​‌ safety, and overall robustness,​​ complemented by an experimental​​​‌ validation of the approach​ in real-world conditions. In​‌ 50, we instead​​ proposed a MPPI scheme​​​‌ based on sensitivity for​ generating online robust trajectory​‌ by exploiting the parallelizability​​ of the MPPI scheme​​​‌ on a GPU hardware​
• in 45 we proposed​‌ a review paper where​​ we summarized the various​​​‌ main contributions of sensitivity-based​ robust planning achieved over​‌ the last years
• in​​ 21, we developed​​​‌ Feedback-MPPI (F-MPPI), a framework​ that augments standard MPPI​‌ by computing local linear​​ feedback gains, enabling high-frequency​​​‌ closed-loop corrections without full​ re-optimization at each timestep.​‌ The key innovation lies​​ in recognizing that MPPI,​​​‌ despite being sampling-based, implicitly​ defines a smooth policy​‌ through the weighted average​​ in parameter space. Compared​​​‌ to prior work on​ Feedback MPC (which extracts​‌ Riccati gains from Differential​​ Dynamic Programming or NLP​​​‌ solvers), the key contribution​ is the extension of​‌ this concept to gradient-free,​​ sampling-based controllers. The gain​​​‌ computation leverages automatic differentiation​ to evaluate cost gradients​‌ for each rollout in​​ parallel alongside trajectory evaluation,​​​‌ maintaining GPU-accelerated efficiency. The​ method was validated on​‌ multiple robotic platforms in​​ simulation and experiments on​​​‌ a quadcopter, involving GPU-accelerated​ onboard computation. The code​‌ was released as an​​ open-source Python library
• To​​​‌ handle generic constraints in​ the sampling-based MPPI setting,​‌ in 49 we developed​​ BC-MPPI (Bayesian-Constraints MPPI), which​​​‌ uses probabilistic surrogates to​ reshape the MPPI sampling​‌ distribution toward constraint satisfaction.​​ The fundamental limitation of​​​‌ penalty-based constraint handling is​ that if no feasible​‌ samples are drawn, violations​​ become inevitable. Inspired by​​​‌ Constrained Bayesian Optimization, BC-MPPI​ attaches a Bayesian Neural​‌ Network (BNN) surrogate to​​ each constraint, predicting both​​ the mean constraint value​​​‌ and its variance for‌ the sampled inputs. The‌​‌ feasibility probability is then​​ multiplied across constraints and​​​‌ incorporated into the MPPI‌ weights. This automatically down-weights‌​‌ unsafe rollouts without explicit​​ rejection, pushing the sampling​​​‌ distribution toward the safe‌ subset while preserving useful‌​‌ exploration. The approach was​​ validated in simulation with​​​‌ an aerial robot navigating‌ around obstacles. Compared to‌​‌ classic MPPI with hard​​ rejection, BC-MPPI achieved larger​​​‌ obstacle clearances, closer target‌ tracking, fewer collisions in‌​‌ complex scenarios, and lower​​ rejection rates (indicating more​​​‌ efficient sample use).

8.1.2‌ UWB navigation of assisted‌​‌ power wheelchair

Participants: Vincent​​ Drevelle, Marie Babel​​​‌, François Pasteau,‌ Theo Le Terrier.‌​‌

Ultra-wideband (UWB) radio technology​​ is a promising solution​​​‌ for indoor localization and‌ object tracking. Unlike vision-based‌​‌ systems, UWB provides a​​ low-cost, non-intrusive, and easy-to-install​​​‌ alternative for wheelchairs. By‌ measuring time-of-flight between fixed‌​‌ beacons and a mobile​​ tag, UWB yields accurate​​​‌ distance estimates. However, in‌ cluttered indoor environments, multipath‌​‌ or non-line-of-sight (NLOS) propagation​​ can introduce large positive​​​‌ errors in these measurements.‌

To address this, we‌​‌ developed a robust set-membership​​ positioning approach for a​​​‌ smart wheelchair equipped with‌ UWB beacons 31.‌​‌ The method employs interval​​ constraint propagation to explicitly​​​‌ account for multipath and‌ NLOS effects, which may‌​‌ cause measured ranges to​​ exceed the true distance​​​‌ 62. This produces‌ a reliable feasible pose‌​‌ set for the wheelchair​​ at each measurement epoch,​​​‌ ensuring conservative but trustworthy‌ localization.

We also investigate‌​‌ Model Predictive Control (MPC)​​ for autonomous navigation of​​​‌ the wheelchair toward a‌ learned target pose using‌​‌ UWB range measurements 63​​, 59. The​​​‌ MPC framework incorporates nonholonomic‌ and user-comfort constraints and‌​‌ can ensure obstacle avoidance​​ via time-of-flight infrared sensors.​​​‌ This integrated approach enables‌ safe and efficient navigation,‌​‌ paving the way for​​ enhanced user mobility and​​​‌ independence.

8.1.3 Visual field‌ for parts assembly

Participant:‌​‌ François Chaumette.

This​​ study was done in​​​‌ collaboration with IRT Jules‌ Verne in Nantes (see‌​‌ Section 9.1.1). Its​​ goal was to accurately​​​‌ control the complete trajectory‌ of a robot during‌​‌ the assembly of two​​ parts 48.

8.1.4​​​‌ Visual servoing with respect‌ to a cylinder

Participants:‌​‌ Alessandro Colotti, François​​ Chaumette.

We developed​​​‌ a new method able‌ to position an eye-in‌​‌ hand camera with respect​​ to a cylinder. We​​​‌ proposed new visual features‌ and a new control‌​‌ scheme enabling to demonstrate​​ the global stability of​​​‌ the system even in‌ the presence of a‌​‌ very bad estimation or​​ approximation of the cylinder​​​‌ radius: the value injected‌ in the control scheme‌​‌ has just to be​​ positive 23.

8.1.5​​​‌ Proximetry-based control with respect‌ to a cylinder

Participants:‌​‌ François Chaumette.

This​​ study was done in​​​‌ the scope of the‌ BPI Lichie project (see‌​‌ 10.4.7) as part​​ of John Thomas's PhD,​​​‌ which was defended last‌ year. Its goal was‌​‌ to design sensor-based control​​ strategies based on proximetry​​​‌ data for positioning a‌ robot inside or outside‌​‌ of a cylinder 58​​​‌

8.1.6 Visual Exploration of​ an Indoor Environment

Participants:​‌ Eric Marchand, François​​ Chaumette.

This study​​​‌ was done in collaboration​ with the Creative company​‌ in Rennes (see Section​​ 8.1.6). It was​​​‌ devoted to the exploration​ of indoor environments by​‌ a mobile robot for​​ a complete and accurate​​​‌ reconstruction of the environment​ through Thibault Noël's PhD​‌ 75.

8.1.7 Active​​ vision for 3D object​​​‌ reconstruction

Participant: François Chaumette​.

This study takes​‌ place in the context​​ of the BIFROST project​​​‌ (see Section 10.1.2).​ Its goal was to​‌ design an active vision​​ system based on visual​​​‌ servoing for enabling the​ complete reconstruction of an​‌ object observed by an​​ RGB-D camera 35.​​​‌

8.1.8 Shape servoing of​ soft objects using Finite​‌ Element Model

Participants: Mandela​​ Ouafo Fonkoua, Alexandre​​​‌ Krupa, François Chaumette​.

This study takes​‌ also place in the​​ context of the BIFROST​​​‌ project (see Section 10.1.2​). We proposed a​‌ fast visual servoing approach​​ using a RGB-D camera​​​‌ that relies on a​ coarse Finite Element Model​‌ (FEM) to autonomously guide​​ a volumetric soft object​​​‌ towards a target shape​ represented by its projection​‌ in a reduced latent​​ space. This latent space​​​‌ is defined by a​ mapping which can be​‌ obtained through various techniques,​​ including learning-based methods (e.g.,​​​‌ PCA or auto-encoders) or​ non-learning approaches (Laplacian spectral​‌ descriptors) 71. This​​ framework considers the dynamic​​​‌ behavior of the object​ deformation without assuming that​‌ the object is in​​ static equilibrium during the​​​‌ manipulation. We have successfully​ formulated the analytical relationship​‌ expressing the variation of​​ the reduced representation of​​​‌ the object shape to​ the 6 degrees of​‌ freedom motion of a​​ robot gripper. Experimental results​​​‌ have demonstrated that our​ approach can deform the​‌ soft object to a​​ desired shape very rapidly.​​​‌

8.1.9 Multi-Robot Control Localization​ and Estimation

Participant: Paolo​‌ Robuffo Giordano, Claudio​​ Pacchierotti, Esteban Restrepo​​​‌, Antonio Marino.​

Systems composed by multiple​‌ robots are useful in​​ several applications where complex​​​‌ tasks need to be​ performed. Examples range from​‌ target tracking, to search​​ and rescue operations and​​​‌ to load transportation. We​ have been very active​‌ over the last years​​ on the topics of​​​‌ coordination, estimation, localization and​ control of multiple robots​‌ under the possible guidance​​ of a human operator​​​‌ (see, e.g., Sect. 10.4.9​ and Sect. 10.4.16),​‌ and we recently started​​ to explore the use​​​‌ of machine learning for​ replicating, or replacing, more​‌ analytical control/estimation strategies (with​​ benefits in terms of​​​‌ reduced computational power and​ communication load).

During this​‌ year we have produced​​ the the following contributions:​​​‌

• in 39 we address​ the problem of managing​‌ the arbitrary addition and​​ removal of agents in​​​‌ open multi-robot systems in​ an autonomous energy-aware and​‌ passive way. For this​​ purpose we propose a​​​‌ passivity-preserving energy-tank-based framework for​ the analysis and control​‌ design of multi-mode multidimensional​​ switched systems. A new​​​‌ design of hybrid energy​ tank is proposed, modeled​‌ as an impulsive switched​​ system and that allows​​ to account for the​​​‌ sudden (and possibly non-passive)‌ jumps in energy of‌​‌ the system due to​​ the change of dimension​​​‌ of the state at‌ the switching instants. Under‌​‌ this framework we establish​​ passivity of the plant-plus-tank​​​‌ system via an energy-based‌ condition for the switching‌​‌ signal.
• In 33,​​ we address the challenge​​​‌ of allocating heterogeneous resources‌ among multiple agents using‌​‌ a decentralized method called​​ Liquid-Graph-Time Clustering-IPPO. This approach​​​‌ integrates dynamic cluster consensus‌ with Independent Proximal Policy‌​‌ Optimization, allowing agents to​​ form local sub-teams based​​​‌ on resource demands. We‌ demonstrate that this strategy‌​‌ improves coordination and scalability​​ compared to standard baselines​​​‌ and a centralized expert‌ solution, enabling efficient resource‌​‌ reallocation even with dynamic​​ resources. Extensive experiments demonstrate​​​‌ that this proposed approach‌ achieves more stable rewards,‌​‌ better coordination, and robust​​ performance in a scalable​​​‌ way. Additionally, the experimental‌ campaign illustrates how dynamic‌​‌ clustering enables agents to​​ reallocate resources efficiently in​​​‌ dynamic scenarios.
• in 32‌ we considered the problem‌​‌ of “dynamic average estimation”:​​ this is a critical​​​‌ problem in multi-agent systems,‌ enabling agents to collaboratively‌​‌ estimate time-varying signals using​​ only local information exchange.​​​‌ Traditional model-based approaches often‌ face challenges related to‌​‌ convergence speed and sensitivity​​ to network topology changes.​​​‌ In this work we‌ introduced a novel learning-based‌​‌ solution leveraging Gated Graph​​ Neural Networks (GGNNs) for​​​‌ fast convergent dynamic average‌ estimation in a fully‌​‌ distributed manner. Taking advantage​​ of the inherent structure​​​‌ of GGNNs, the proposed‌ method models the estimation‌​‌ process as a distributed​​ autoregressor, ensuring rapid convergence​​​‌ while maintaining stability. Extensive‌ numerical experiments demonstrate that‌​‌ our approach significantly outperforms​​ conventional model-based estimators in​​​‌ terms of both convergence‌ speed and precision, making‌​‌ it a promising alternative​​ for multi-agent applications that​​​‌ require dynamic average estimation.‌
• in 37 we considered‌​‌ the problem of coordinating​​ a group of mobile​​​‌ robots for distributedly estimating‌ the parameters of a‌​‌ diffusion model that generates​​ a time-varying spatial field.​​​‌ To this end, we‌ developed a decentralized online‌​‌ motion strategy aimed at​​ minimizing a Gramian-based information​​​‌ metric that improves the‌ estimation convergence. Additional constraints,‌​‌ among which collision avoidance,​​ are integrated as Control​​​‌ Barrier Functions (CBFs) in‌ a Quadratic Program (QP).‌​‌ A set of statistical​​ comparisons against three baselines​​​‌ showed the improved performance‌ of the proposed method‌​‌ in a range of​​ simulated scenarios, and we​​​‌ also performed experiments carried‌ out with the drones‌​‌ in our group to​​ demonstrate the actual implementability​​​‌ of the approach and‌ its effectiveness in generating‌​‌ online, collision-free, and informative​​ motions.

8.2.1 Wearable haptics for​​ human-centered robotics, Virtual Reality​​​‌ (VR), and Augmented Reality‌ (AR)

Participants: Claudio Pacchierotti‌​‌, Maud Marchal,​​​‌ Eric Marchand, Lisheng​ Kuang.

We have​‌ been working on wearable​​ haptics since few years​​​‌ now, both from the​ hardware (design of interfaces)​‌ and software (rendering and​​ interaction techniques) points of​​​‌ view. This line of​ research has continued also​‌ in this year.

In​​ 25, we review​​​‌ the state of the​ art in wearable multi-sensory​‌ haptic devices. These devices​​ communicate complex information by​​​‌ delivering multiple types of​ haptic stimuli simultaneously, such​‌ as vibration, skin stretch,​​ and pressure. We discuss​​​‌ the engineering challenges in​ packaging these mechanisms and​‌ the perceptual issues related​​ to cue masking and​​​‌ human acuity. We provide​ guidelines for designing future​‌ multi-sensory devices to enhance​​ human-machine interaction.

In 36​​​‌, we discuss recent​ advancements in wearable haptics,​‌ highlighting a new 18-gram​​ haptic ring capable of​​​‌ delivering strong force feedback​ while detecting multi-directional touch​‌ inputs. This device addresses​​ the common trade-off between​​​‌ portability and performance in​ haptic technology, offering potential​‌ applications in interacting with​​ virtual environments.

In 46​​​‌, we propose "Flexible​ Reality," a concept to​‌ enhance haptic feedback intensity​​ in co-located Augmented Reality​​​‌ (AR) using pseudo-haptics. We​ conducted a user study​‌ comparing vibration intensity perception​​ in AR versus VR.​​​‌ The results show that​ pseudo-haptics can effectively modulate​‌ perceived intensity. We also​​ found that user agency​​​‌ and self-causality significantly increase​ interaction believability.

In 47​‌, as part of​​ the DORNELL project (see​​​‌ Sect. 10.4.6), we​ propose a multi-actuator haptic​‌ handle that acts as​​ a physical representation of​​​‌ the user's surroundings in​ VR. The device displays​‌ directional haptic patterns to​​ inform the user about​​​‌ obstacles. Our user studies​ demonstrate that this in-hand​‌ feedback enables users to​​ avoid dynamic obstacles effectively​​​‌ and intuitively understand the​ spatial location of threats​‌ relative to their avatar.​​

In 77, we​​​‌ investigate the use of​ passive finger movements for​‌ calibrating Brain-Computer Interfaces (BCIs)​​ as an alternative to​​​‌ motor imagery. We recorded​ EEG activity from participants​‌ performing both tasks. We​​ observed significantly stronger brain​​​‌ activity in the α​ and β bands during​‌ passive movements. These findings​​ suggest passive movements could​​​‌ improve BCI accessibility for​ applications like extended reality.​‌

In 53, 78​​, we study whether​​​‌ vibrations applied to the​ hands can support the​‌ sensation of walking in​​ VR, serving as an​​​‌ alternative to foot vibrations.​ We compared hand vibrations,​‌ foot vibrations, and no​​ vibrations during a passive​​​‌ walking simulation. Results indicate​ that hand vibrations significantly​‌ increase the walking sensation​​ and embodiment compared to​​​‌ no vibrations, offering a​ cost-effective solution for immersive​‌ VR locomotion.

In 57​​, we investigate vibrotactile​​​‌ perception on the arm​ using a modular wearable​‌ sleeve. We examined localization,​​ apparent haptic motion, and​​​‌ two-point discrimination across the​ wrist, forearm, upper arm,​‌ and shoulder. Users could​​ identify stimulus locations with​​​‌ high accuracy. We found​ that spatial acuity decreases​‌ from the wrist to​​ the upper arm, though​​​‌ the shoulder shows better​ discrimination than expected.

In​‌ 54, we investigate​​ the manipulation of fingertip​​ contact plane tilt to​​​‌ enhance the visuo-haptic coherency‌ of virtual objects. We‌​‌ designed a compact device​​ capable of adjusting the​​​‌ tilt of the contact‌ plane to simulate diverse‌​‌ 3D shapes. User studies​​ demonstrated that this approach​​​‌ yields significant improvements in‌ haptic realism, enjoyment, and‌​‌ operability compared to conventional​​ methods.

In 55,​​​‌ we present FresnelDeformable, a‌ technique conveying the softness‌​‌ of virtual objects by​​ combining pseudo-stiffness with dynamic​​​‌ fingertip plane tilt manipulation.‌ The method uses a‌​‌ custom device that tilts​​ the fingertip contact surface​​​‌ according to the applied‌ force to align tactile‌​‌ feedback with visual deformation.​​ Results from a user​​​‌ study indicated that tilt‌ manipulation significantly increases the‌​‌ coherence between visual and​​ tactile cues and expands​​​‌ the range of perceived‌ softness in virtual environments.‌​‌

8.2.2 Encounter-Type Haptic Devices​​

Participants: Claudio Pacchierotti,​​​‌ Lisheng Kuang, Elodie‌ Bouzbib.

Encounter-Type Haptic‌​‌ Displays (ETHDs) provide haptic​​ feedback by positioning a​​​‌ tangible surface for the‌ user to encounter. This‌​‌ allows users to freely​​ elicit haptic feedback with​​​‌ a surface during a‌ virtual simulation. ETHDs differ‌​‌ from most of current​​ haptic devices which rely​​​‌ on an actuator always‌ in contact with the‌​‌ user.

In 64,​​ we analyze an origami-inspired​​​‌ wearable haptic device designed‌ for cutaneous interaction with‌​‌ the palm. The device​​ uses a structured mechanism​​​‌ to render edges, tips,‌ and surfaces by adjusting‌​‌ force and velocity. We​​ evaluate the device's reachable​​​‌ configurations and trajectory execution‌ through inverse kinematics analysis,‌​‌ contributing to the design​​ of adaptable wearable haptic​​​‌ systems.

8.3.1 Shared Control‌​‌ for Remote Manipulation

Participants:​​ Paolo Robuffo Giordano,​​​‌ Claudio Pacchierotti, Marco‌ Ferro, Leon Raphalen‌​‌, Paul Mefflet.​​

As teleoperation systems become​​​‌ more sophisticated and flexible,‌ the environments and applications‌​‌ where they can be​​ employed become less structured​​​‌ and predictable. This desirable‌ evolution toward more challenging‌​‌ robotic tasks requires an​​ increasing degree of training,​​​‌ skills, and concentration from‌ the human operator. In‌​‌ this respect, shared control​​ algorithms have been investigated​​​‌ as one of the‌ main tools to design‌​‌ complex but intuitive robotic​​ teleoperation systems, helping operators​​​‌ in carrying out several‌ increasingly difficult robotic applications‌​‌ such as assisted vehicle​​ navigation, surgical robotics, brain-computer​​​‌ interface manipulation, rehabilitation. Indeed,‌ this approach makes it‌​‌ possible to share the​​ available degrees of freedom​​​‌ of the robotic system‌ between the operator and‌​‌ an autonomous controller.

Along​​ this line of research,​​​‌ in the context of‌ the Horizon Europe Rego‌​‌ project (Sect. 10.3.1),​​ we are starting to​​​‌ investigate how to employ‌ shared control strategies for‌​‌ allowing a human operator​​ to control a group​​​‌ of micro-robots for drug‌ delivery and micro-assembly.

In‌​‌ 24, we presented​​ the experimental evaluation of​​​‌ a haptic shared control‌ teleoperation framework for the‌​‌ locomotion of multiple microrobots,​​ relying on a kinesthetic​​​‌ haptic interface and a‌ custom electromagnetic system. Six‌​‌ combinations of haptic and​​ shared control strategies are​​​‌ evaluated during a safe‌ 3D navigation scenario in‌​‌ a cluttered environment. 18​​​‌ participants are asked to​ steer two spherical magnetic​‌ microrobots among obstacles to​​ reach a predefined goal,​​​‌ under different conditions. For​ each condition, participants are​‌ provided with different obstacle​​ avoidance and navigation guidance​​​‌ cues. Results show that​ providing assistance in avoiding​‌ obstacles guarantees safer performance,​​ regardless if the assistance​​​‌ is autonomous or delivered​ through a haptic repulsive​‌ force.

In 52,​​ we introduce a “Stiffness​​​‌ Regulation Co-pilot" to assist​ operators in bilateral teleimpedance​‌ control. This virtual agent​​ infers optimal stiffness actions​​​‌ based on task performance​ and communicates them to​‌ the operator via feedback.​​ A preliminary study suggests​​​‌ that cutaneous feedback, possibly​ combined with other modalities,​‌ improves task performance and​​ reduces the cognitive load​​​‌ required to regulate stiffness​ manually.

In 66,​‌ we present a haptic​​ shared control system for​​​‌ teleoperating a pair of​ magnetic microrobots. We formulate​‌ a Quadratic Programming approach​​ with Control Lyapunov and​​​‌ Barrier Functions to ensure​ safe navigation. We combine​‌ this with a shared​​ control architecture that provides​​​‌ visuo-haptic cues. The system​ improves navigation accuracy and​‌ stability compared to unassisted​​ teleoperation.

In 56,​​​‌ we address the problem​ of occlusions in vision-constrained​‌ teleoperation. We propose an​​ occlusion-safe shared control framework​​​‌ using High-Order Control Barrier​ Functions to prevent robots​‌ from entering unobserved regions.​​ The system provides haptic​​​‌ feedback to signal proximity​ to occlusion zones, helping​‌ the operator maintain visibility​​ and control safety.

8.3.2​​​‌ Shared Control of a​ Wheelchair for Navigation Assistance​‌

Participants: Louise Devigne,​​ François Pasteau, Emilie​​​‌ Leblong, Marie Babel​.

Power wheelchairs allow​‌ people with motor disabilities​​ to have more mobility​​​‌ and independence. In order​ to improve the access​‌ to mobility for people​​ with disabilities, we carefully​​​‌ designed a semi-autonomous assistive​ wheelchair system which progressively​‌ corrects the trajectory as​​ the user manually drives​​​‌ the wheelchair and smoothly​ avoids obstacles. During the​‌ past 5 years, we​​ successfully conducted several clinical​​​‌ trials with more than​ 300 users 17.​‌

The Cirris laboratory at​​ Univeristy of Laval (Canada)​​​‌ has acquired and set​ up our collision avoidance​‌ wheelchair kit composed of​​ 48 sensors and a​​​‌ control board running the​ shared control algorithm. With​‌ the help of the​​ Fondation Saint Hélier (Emilie​​​‌ Leblong), we designed an​ experimental protocol to conduct​‌ international multicentric clinical trials​​ and find new use​​​‌ cases for this solution​ inside the rehabilitation process.​‌

A cooperation with Clinatec​​ / CEA Leti led​​​‌ us to defined assist-as-needed​ sensor-based shared control (SC)​‌ methods relying on the​​ blending of BCI and​​​‌ depth-sensor-based control. The proposed​ assistance targets the BCI-teleoperation​‌ of effectors for tasks​​ that answer mobility and​​​‌ manipulation needs in a​ at-home context. We demonstrated​‌ the ability of the​​ proposed method to provide​​​‌ effective assistance for wheelchair​ mobility and reach-and-grasp tasks​‌ through a clinical trial​​ with a quadriplegic patient​​​‌ implanted with a wireless​ 64-channel ElectroCorticoGram recording implant​‌ named WIMAGINE. The time​​ to perform the tasks​​​‌ and the number of​ changes of mental tasks​‌ were reduced. Unwanted actions,​​ such as wheelchair collisions​​ with the environment, and​​​‌ gripper opening that could‌ result in the fall‌​‌ of the object were​​ avoided 19.

8.3.3​​​‌ Integrating social interaction in‌ a VR power wheelchair‌​‌ driving simulator

Participants: Emilie​​ Leblong, Fabien Grzeskowiak​​​‌, Sebastien Thomas,‌ François Pasteau, Anne-Hélène‌​‌ Olivier, Marie Babel​​.

Navigating in the​​​‌ city while driving a‌ powered wheelchair, in a‌​‌ complex and dynamic environment​​ made of various interactions​​​‌ with other humans, can‌ be challenging for a‌​‌ person with disabilities. Learning​​ how to drive a​​​‌ powered wheelchair remains then‌ a major issue. Immersive‌​‌ environments provide solutions to​​ learn and transfer skills​​​‌ to real life. This‌ opens up new areas‌​‌ of application, such as​​ rehabilitation, where people with​​​‌ neurological disabilities can learn‌ to drive a power‌​‌ wheelchair through immersive simulators.​​ In this context, we​​​‌ collaborated with clinicians to‌ design a Virtual Reality‌​‌ based power wheelchair simulator.​​ We received in 2025​​​‌ an award for the‌ best research demo (honorable‌​‌ mention). This multisensory power​​ wheelchair simulator has been​​​‌ duplicated and set up‌ at the Cirris Laboratory‌​‌ at University of Laval​​ (Canada) to develop new​​​‌ usage scenarios and perform‌ multicentric clinical studies (SocNav‌​‌ project 10.1.1). To​​ promote the transfer of​​​‌ skills from virtual to‌ real, the use of‌​‌ such a platform requires​​ the deployment of environmentally​​​‌ friendly interactive populated virtual‌ environments. However, these are‌​‌ currently empty of any​​ pedestrians, even though the​​​‌ question of social interaction‌ in the framework of‌​‌ an inclusive urban mobility​​ is fundamental. Hence, to​​​‌ expose these users to‌ daily-life study interaction situations,‌​‌ it is important to​​ ensure realistic interactions with​​​‌ the virtual humans that‌ populate the simulated environment.‌​‌ We then investigate the​​ regulation of interpersonal distance​​​‌ (i.e., proxemics) between a‌ pedestrian and a PWC‌​‌ user in real and​​ virtual situations, and proposed​​​‌ a model to regulate‌ the virtual agent behavior‌​‌ while sharing the same​​ virtual environment. We conducted​​​‌ clinical trials (March to‌ June 2025) to evaluate‌​‌ the performances of our​​ system. Results indicated high​​​‌ potential for learning and‌ safety, with users feeling‌​‌ secure and better understanding​​ urban risks. Professionals saw​​​‌ it as a tool‌ for progressive training and‌​‌ detailed observation. Further studies​​ are required to validate​​​‌ its clinical efficacy and‌ integration into care pathways.‌​‌

8.3.4 Upper-limb exoskeleton for​​ reach-to-grasp assistance for power​​​‌ wheelchair users

Participants: Marie‌ Babel, Maxime Manzano‌​‌, Mael Gallois,​​ Sylvain Guégan, Elise​​​‌ Larribeau, Charles Pontonnier‌.

Wearable Upper-Limb (UL)‌​‌ assistive robots are designed​​ to increase autonomy and​​​‌ social participation for people‌ with UL impairments as‌​‌ they assist tasks involved​​ in Activities of Daily​​​‌ Living (ADLs). When an‌ active device is coupled‌​‌ with a power wheelchair,​​ it is usually controlled​​​‌ through push-buttons located near‌ the wheelchair joystick, thus‌​‌ preventing bimanual tasks and​​ requiring a large mental​​​‌ load to perform complex‌ UL trajectories. Therefore, there‌​‌ is a need for​​ strategies to detect user​​​‌ intent and get rid‌ of manual control, allowing‌​‌ a distinctive, intuitive control​​​‌ of devices with multiple​ active degrees of freedom.​‌

Assistive devices are then​​ to be designed with​​​‌ the objective of use​ in daily-life as well​‌ as broad adoption by​​ end users. In this​​​‌ context, it is necessary​ to tackle usability challenges​‌ by properly detecting and​​ acting in accordance to​​​‌ user intents while minimizing​ the device installation complexity​‌ as well.

We designed​​ an exoskeleton prototype with​​​‌ a control interface leveraging​ human–exoskeleton interaction forces relying​‌ on intent detection methods.​​ We then developed a​​​‌ shared control strategy exploiting​ user force impulses to​‌ mitigate physical effort required​​ to use the exoskeleton​​​‌ through a variable admittance​ controller with adjustable parameters​‌ 60, allowing to​​ avoid instabilities or overly​​​‌ conservative settings that compromises​ user experience. This work​‌ is supported by models​​ of users' force generation​​​‌ capabilities to personalize the​ assistance 61, 51​‌, 26. Indeed,​​ exoskeletons are challenging to​​​‌ use because of the​ multiple degrees of freedom​‌ one needs to control,​​ in addition to their​​​‌ exposure to misalignments which​ cause discomfort due to​‌ kinematic incompatibilities with the​​ human upper-limb. We then​​​‌ explored the possibility to​ assess joint torque capacities​‌ of patients presenting post-stroke​​ sequels or multiple sclerosis​​​‌ impairment to use it​ as guidance in a​‌ shared control scheme 67​​.

8.4.1 Controlled Shaking​ of Trees With an​‌ Aerial Manipulator

Participants: Marco​​ Tognon.

Aerial shaking​​​‌ of flexible structures, and​ in particular trees, has​‌ recently emerged as a​​ promising application of aerial​​​‌ manipulators for agriculture and​ environmental monitoring. By inducing​‌ controlled vibrations, UAVs can​​ enable tasks such as​​​‌ fruit detachment or structural​ assessment while avoiding heavy,​‌ ground-based machinery. The main​​ challenge lies in understanding​​​‌ and exploiting the coupled​ dynamics between the aerial​‌ platform and the flexible​​ structure to achieve effective​​​‌ vibration generation in a​ controlled and robust manner.​‌

In 28, the​​ authors take a first​​​‌ step in this direction​ by proposing a self-excited​‌ oscillation strategy for shaking​​ flexible systems with an​​​‌ aerial manipulator. The method​ exploits the natural dynamics​‌ of the coupled UAV–tree​​ system to automatically excite​​​‌ vibrations at the structure’s​ resonant frequency, without requiring​‌ prior knowledge of the​​ tree parameters. A simplified​​​‌ one-degree-of-freedom model, derived using​ the Rayleigh–Ritz method, is​‌ used to analyze the​​ interaction dynamics and predict​​​‌ vibration characteristics. Indoor experiments​ validate the approach, showing​‌ accurate prediction of oscillation​​ frequency and amplitude, and​​​‌ demonstrating the feasibility of​ autonomous vibration-based interaction with​‌ flexible structures.

Building on​​ this modeling foundation, the​​​‌ more recent work 27​ extends the problem formulation​‌ by explicitly exploiting the​​ full actuation capabilities of​​​‌ aerial manipulators. Instead of​ limiting interaction to translational​‌ push–pull motions, the paper​​ introduces two complementary shaking​​​‌ strategies: a translation strategy​ based on force-induced linear​‌ motions, and a rotation​​ strategy based on torque-induced​​​‌ rotational motions. By integrating​ both strategies into a​‌ Rayleigh–Ritz model of the​​ tree, the closed-loop dynamics​​​‌ of the coupled system​ are derived and analyzed.​‌ This analysis addresses a​​ previously unexplored question: which​​ interaction strategy is more​​​‌ effective for a given‌ contact point on the‌​‌ tree. The results show​​ that the optimal choice​​​‌ depends solely on the‌ aerial platform’s physical properties,‌​‌ such as mass and​​ inertia, rather than on​​​‌ the tree itself. Indoor‌ experiments with a fully‌​‌ actuated platform and a​​ hand-made bamboo tree validate​​​‌ the theoretical findings.

Together,‌ these two works establish‌​‌ a coherent research direction​​ on aerial shaking of​​​‌ flexible structures: from exploiting‌ self-excited oscillations to induce‌​‌ vibrations without prior knowledge,​​ to systematically comparing force-​​​‌ and torque-based interaction strategies‌ through unified modeling and‌​‌ experimental validation.

8.4.2 Design​​ and Control of Aerial​​​‌ Manipulators for Physical Interaction‌ Tasks

Participants: Marco Tognon‌​‌, Paolo Robuffo Giordano​​, Lorenzo Balandi,​​​‌ Phillip Maximilian Mehl,‌ Lluis Prior, Giulio‌​‌ Franchi, Igor Angelini​​, Alessandro Borgherini,​​​‌ Emanuele Bua Odetti,‌ Luigi Graziosi.

The‌​‌ design and control of​​ novel aerial manipulators aim​​​‌ to improve precision, stability,‌ and efficiency in mobile‌​‌ robotic applications, particularly for​​ aerial manipulation tasks. Aerial​​​‌ manipulators often face challenges‌ due to reaction forces‌​‌ and torques induced by​​ motion, impacting performance and​​​‌ control complexity.

The work‌ in 42 presents a‌​‌ design methodology for the​​ high-level analysis of inherently​​​‌ force-balanced robotic manipulators and‌ applies it to three‌​‌ closed-chain, two-degree-of-freedom planar concepts​​ based on four-bar and​​​‌ five-bar linkages. The manipulators‌ are modeled at an‌​‌ abstract component level, explicitly​​ accounting for link mass​​​‌ distribution, counter-masses, and attachment‌ constraints.

An optimization-based approach‌​‌ is used to determine​​ suitable counter-mass configurations while​​​‌ exploring tradeoffs between workspace,‌ total mass, and balancing‌​‌ effectiveness. Multibody simulations comparing​​ balanced and unbalanced designs​​​‌ along representative trajectories quantify‌ reaction forces, moments, and‌​‌ joint torques. The results​​ highlight how inherent force​​​‌ balancing can substantially reduce‌ dynamic reactions, while also‌​‌ exposing key design tradeoffs​​ that influence manipulator performance.​​​‌

A series of works‌ have progressively addressed the‌​‌ challenge of achieving accurate​​ and robust control of​​​‌ aerial robots in the‌ presence of model uncertainties,‌​‌ disturbances, and hardware limitations,​​ all converging toward architectures​​​‌ that tightly couple high-level‌ optimal control with robust,‌​‌ high-rate inner-loop strategies.

In​​ 43, the authors​​​‌ investigate the combination of‌ Nonlinear Model Predictive Control‌​‌ (NMPC) with a fast​​ acceleration-based inner loop to​​​‌ improve trajectory tracking under‌ disturbances and modeling errors.‌​‌ By studying Incremental Nonlinear​​ Dynamic Inversion (INDI) and​​​‌ Time Delay Control (TDC),‌ the paper clarifies their‌​‌ close relationship and proposes​​ a TDC-based inner loop​​​‌ running at 1 kHz.‌ Extensive simulations on a‌​‌ fully actuated hexarotor show​​ significant performance improvements, while​​​‌ also highlighting fundamental limitations‌ arising from input saturation,‌​‌ thereby motivating more constraint-aware​​ inner-loop designs.

Complementing the​​​‌ control-side robustness, 44 focuses‌ on improving the quality‌​‌ of inertial feedback by​​ addressing mechanical vibrations affecting​​​‌ IMUs on multirotor aerial‌ vehicles. Through analysis of‌​‌ real flight data and​​ vibration theory, the work​​​‌ identifies motor–propeller units as‌ the dominant vibration source‌​‌ and develops theoretical models​​ to guide effective damping​​​‌ strategies. A redesigned, low-cost‌ damping configuration significantly reduces‌​‌ vibration levels in both​​​‌ acceleration and angular velocity​ measurements, directly benefiting high-bandwidth​‌ control architectures that rely​​ on accurate inertial sensing.​​​‌

Building on these insights,​ 18 proposes a constraint-aware,​‌ optimization-based inner-loop controller inspired​​ by TDC and formulated​​​‌ as a Quadratic Program​ (QP). Unlike classical feedback​‌ inner loops, this approach​​ explicitly handles actuation limits​​​‌ and preserves stability under​ saturation and model mismatches.​‌ The controller uses acceleration​​ feedback and does not​​​‌ require precise inertial parameters,​ further enhancing robustness. Experiments​‌ on a fully actuated​​ hexarotor demonstrate that the​​​‌ proposed QP-based inner loop​ substantially improves NMPC tracking​‌ performance in aggressive scenarios​​ where traditional inner-loop strategies​​​‌ fail.

Finally, 65 extends​ the pursuit of robustness​‌ beyond classical control by​​ introducing a model-based reinforcement​​​‌ learning framework for end-to-end​ UAV control. To overcome​‌ the sim-to-real gap and​​ the impracticality of unsafe​​​‌ real-world training, the authors​ encapsulate a high-fidelity simulator​‌ into a Gaussian Process​​ model, enabling efficient policy​​​‌ learning with reduced computational​ cost. The learned policies​‌ are successfully transferred to​​ a real quadrotor, with​​​‌ experimental results showing close​ agreement between simulation, learned​‌ models, and real flight​​ data. This work demonstrates​​​‌ the feasibility of combining​ model-based learning and optimal​‌ control principles to achieve​​ robust performance on real​​​‌ aerial platforms.

Together, these​ contributions outline a coherent​‌ research direction toward robust,​​ high-performance aerial robot control,​​​‌ combining accurate sensing, fast​ and constraint-aware inner loops,​‌ optimal outer-loop control, and​​ learning-based methods to bridge​​​‌ modeling gaps between simulation​ and reality.

8.4.3 Cooperative​‌ Multi-Aerial Robot Manipulation

Participants:​​ Marco Tognon, Paolo​​​‌ Robuffo Giordano, Szymon​ Bielenin, Nicola De​‌ Carli, Valeria Braglia​​.

Cooperative transportation of​​​‌ cable-suspended loads with UAVs​ is a key problem​‌ in cooperative aerial manipulation,​​ motivated by applications such​​​‌ as search and rescue,​ construction, and logistics in​‌ cluttered or hard-to-reach environments.​​ By distributing the payload​​​‌ across multiple aerial robots,​ these systems can overcome​‌ the payload and actuation​​ limits of a single​​​‌ UAV while enabling full-pose​ control of large or​‌ heavy objects. However, the​​ strong dynamic coupling introduced​​​‌ by the cables and​ the load makes control​‌ particularly challenging, often forcing​​ existing approaches to operate​​​‌ at low speeds and​ accelerations or to rely​‌ on centralized solutions that​​ limit scalability.

In 41​​​‌, the focus is​ placed on agility. The​‌ paper proposes a centralized,​​ trajectory-based Model Predictive Control​​​‌ framework that explicitly accounts​ for the coupled quadrotor–cable–load​‌ dynamics and constraints in​​ a whole-body kinodynamic planning​​​‌ problem solved online. The​ resulting trajectories are tracked​‌ in a receding-horizon fashion​​ by onboard controllers that​​​‌ estimate and compensate for​ cable tension, without requiring​‌ sensors on the load.​​ Real-world experiments show dramatic​​​‌ performance gains, achieving accelerations​ up to eight times​‌ higher than state-of-the-art methods​​ and enabling aggressive maneuvers​​​‌ such as high-speed flight​ through narrow passages, while​‌ remaining robust to load​​ uncertainty and wind disturbances.​​​‌

Complementarily, 22 addresses the​ challenge of scalability in​‌ cooperative aerial manipulation. Instead​​ of a centralized controller,​​​‌ the authors introduce a​ Distributed Nonlinear Model Predictive​‌ Control (DNMPC) architecture in​​ which each UAV solves​​ a local optimization problem​​​‌ and exchanges only a‌ reduced set of variables‌​‌ with its neighbors over​​ a peer-to-peer network. This​​​‌ distributed scheme preserves the‌ benefits of NMPC while‌​‌ significantly reducing computational and​​ communication burdens. The approach​​​‌ is validated in simulation‌ and through real-world experiments‌​‌ on the Fly-Crane platform,​​ demonstrating effective cooperative manipulation​​​‌ of a cable-suspended load‌ with improved scalability and‌​‌ robustness.

Together, these two​​ works advance cooperative aerial​​​‌ transportation by tackling complementary‌ aspects of the same‌​‌ problem: one pushing the​​ limits of agility through​​​‌ centralized, whole-body MPC, and‌ the other enabling scalable‌​‌ deployment through distributed predictive​​ control.

8.4.4 Physical Human–Aerial​​​‌ Robot Interaction and Shared‌ Control

Participants: Marco Tognon‌​‌, Marco Cognetti.​​

Physical interaction between humans​​​‌ and aerial robots represents‌ a critical step toward‌​‌ deploying UAVs in collaborative​​ and assistive tasks, where​​​‌ safety, intuitiveness, and robustness‌ are paramount. Unlike ground‌​‌ robots, aerial platforms are​​ inherently underactuated, dynamically unstable,​​​‌ and subject to strict‌ safety constraints, making direct‌​‌ physical human–robot interaction particularly​​ challenging. Recent works have​​​‌ begun to address these‌ challenges by combining predictive‌​‌ control, compliance, and human-centered​​ interface design to enable​​​‌ effective collaboration between humans‌ and aerial robots.

In‌​‌ 29, the authors​​ propose a control framework​​​‌ that enables an aerial‌ robot to physically collaborate‌​‌ with a human in​​ a shared transportation task.​​​‌ The approach is based‌ on a nonlinear Model‌​‌ Predictive Control (NMPC) formulation​​ that explicitly incorporates the​​​‌ coupled dynamics of the‌ human, the aerial robot,‌​‌ and the manipulated object.​​ To ensure safe interaction,​​​‌ the NMPC is complemented‌ with a compliant control‌​‌ layer and a motion​​ preference strategy that favors​​​‌ forward motion, aligning the‌ robot’s behavior with the‌​‌ human’s natural movement. Indoor​​ experiments with a fully​​​‌ actuated hexarotor demonstrate stable‌ and effective human–robot cooperation,‌​‌ highlighting the aerial robot’s​​ ability to assist the​​​‌ human while improving comfort‌ and efficiency during physical‌​‌ manipulation.

Complementing physical collaboration,​​ 34 addresses the human-in-the-loop​​​‌ aspect of aerial manipulation‌ through teleoperation. The paper‌​‌ investigates how richer feedback​​ modalities can enhance operator​​​‌ awareness and task performance‌ compared to conventional 2D‌​‌ visual interfaces. A human–robot​​ interface providing immersive 3D​​​‌ mixed-reality visual feedback and‌ 3D haptic feedback is‌​‌ developed and evaluated. Through​​ real-world manipulation experiments and​​​‌ a controlled human-subjects study,‌ the results show that‌​‌ both mixed-reality vision and​​ haptic feedback significantly improve​​​‌ dexterity and reduce cognitive‌ workload in teleoperated aerial‌​‌ manipulation tasks, while also​​ revealing that operator experience​​​‌ remains a dominant factor.‌

Together, these works advance‌​‌ human–aerial robot interaction from​​ both physical collaboration and​​​‌ interface design perspectives, contributing‌ toward safer, more intuitive,‌​‌ and more effective shared-control​​ paradigms for aerial robots​​​‌ operating in close proximity‌ to humans.

8.5.1​​​‌ Capacitive and pressure sensor‌ through one-shot 3D printing‌​‌

Participants: Marie Babel,​​ José Eduardo Aguilar-Segovia,​​​‌ Sylvain Lefebvre.

Measuring‌ interaction forces between robots‌​‌ and humans is a​​ major challenge in physical​​​‌ human-robot interactions. Nowadays, conventional‌ force/torque sensors suffer from‌​‌ bulkiness, high cost, and​​​‌ stiffness, which limit their​ use in soft robotics.​‌

Additive manufacturing (AM) enables​​ the fabrication of multi-material​​​‌ 3D structures with sensing​ capabilities by integrating conductive​‌ materials alongside flexible or​​ rigid parts. Recent research​​​‌ focuses on embedding sensing​ elements into 3D structures​‌ using complex algorithms or​​ intricate design approaches to​​​‌ create interactive or monitoring​ devices. A challenge in​‌ manufacturing bespoke devices is​​ performing user-specific ergonomic and​​​‌ anthropomorphic adjustments to multi-material​ 3D models. We proposed​‌ a novel computational fabrication​​ method that operates directly​​​‌ within the layered fabrication​ space. The method transforms​‌ simple sensing structures into​​ complex designs through layer​​​‌ transformations – rotation, translation,​ and scaling – while​‌ addressing constraints from design​​ for additive manufacturing (DfAM).​​​‌ These constraints include ensuring​ electrical conductivity in conductive​‌ parts and preventing unintended​​ electrical connections during fabrication.​​​‌ A custom-fit handle with​ embedded capacitive sensors is​‌ manufactured as a one-shot​​ multi-material print and forces​​​‌ applied to the embedded​ sensors by the user's​‌ fingertips and palm are​​ measured. A user study​​​‌ validates that our method​ successfully adjusts the handle​‌ to a set of​​ users, ensuring ergonomic comfort.​​​‌ Our results demonstrate the​ potential of our method​‌ for fabricating personalized sensing​​ devices, enabling designers to​​​‌ explore diverse structures by​ transforming a single template​‌ design 1516.​​

9.1.1 IRT JV Happy2​​

Participant: Romain Lagneau,​​​‌ Fabien Spindler, François​ Chaumette.

No Inria​‌ Rennes 13521, duration: 72​​ months.

F. Chaumette is​​​‌ in secondment (at 20%)​ at IRT Jules Verne​‌ in Nantes since 2018.​​ This year, he was​​​‌ involved the Happy 2​ project with Airbus &​‌ Naval Group to give​​ his expertise in visual​​​‌ servoing. Based on ViSP,​ a model-based tracking algorithm​‌ was transfered and integrated​​ in a demonstrator at​​​‌ IRT to assemble two​ airplane parts.

9.1.2 Trasys/NRB​‌

Participants: Romain Lagneau,​​ Fabien Spindler, François​​​‌ Chaumette.

No Inria​ Rennes 2023000390, duration: 19​‌ months.

This project started​​ in May 2023. It​​​‌ was in collaboration with​ the Trasys/NRB company in​‌ Belgium. Its goal was​​ to develop an embedded​​​‌ vision-based localization system with​ respect to satellite parts.​‌

9.1.3 Sopra-Steria

Participants: François​​ Pasteau, Marie Babel​​​‌, Sylvain Guegan,​ Fabien Grzeskowiak.

INSA​‌ Rennes, duration: 72 months.​​

This project funded by​​​‌ Sopra Steria aimed to​ design new assistive robotics​‌ and to support clinical​​ trials activities.

9.2.1​ IRT JV Perform

Participant:​‌ François Chaumette.

No​​ Inria Rennes 16107, duration:​​​‌ 42 months.

This project​ funded by IRT Jules​‌ Verne started in November​​ 2021. It was achieved​​​‌ in cooperation with Stéphane​ Caro from LS2N in​‌ Nantes to support Sophie​​ Rousseau's PhD at IRT​​​‌ Jules Verne about sensor-based​ control and vibration reduction​‌ of cable-driven parallel robots.​​ Sophie Rousseau defended her​​​‌ PhD entitled "Sensor-Based Control​ and Vibration Reduction of​‌ Cable-Driven Parallel Robots" in​​ May 2025 at Ecole​​​‌ Centrale de Nantes.

9.2.2​ Commande partagée centrée sur​‌ l'humain pour la télémanipulation​​ robotique à différentes échelles​​

Participant: Claudio Pacchierotti,​​​‌ Paolo Robuffo Giordano.‌

Convention cifre 2023/1119. Duration:‌​‌ 36 months.

This project​​ is funded by Haption,​​​‌ Laval, and funds the‌ PhD of Paul Mefflet‌​‌ on shared control for​​ tele-manipulation

10.1.1 Inria associate team‌​‌ not involved in an​​ IIL or an international​​​‌ program

10.1.2​​ Participation in other International​​​‌ Programs

10.2.1 Visits‌​‌ of international scientists

10.3.1 Horizon Europe‌​‌

REGO project on cordis.europa.eu​​

• Title:
  Cognitive robotic tools​​​‌ for human-centered small-scale multi-robot‌ operations
• Duration:
  From October‌​‌ 1, 2022 to September​​ 30, 2026
• Partners:
  • INSTITUT​​​‌ NATIONAL DE RECHERCHE EN‌ INFORMATIQUE ET AUTOMATIQUE (INRIA),‌​‌ France
  • CENTRE HOSPITALIER UNIVERSITAIRE​​ DE RENNES (CHU RENNES),​​​‌ France
  • UNIVERSITEIT TWENTE (UNIVERSITEIT‌ TWENTE), Netherlands
  • SCUOLA SUPERIORE‌​‌ DI STUDI UNIVERSITARI E​​ DI PERFEZIONAMENTO S ANNA​​​‌ (SSSA), Italy
  • FONDAZIONE ISTITUTO‌ ITALIANO DI TECNOLOGIA (IIT),‌​‌ Italy
  • HAPTION SA (HAPTION),​​ France
  • CENTRE NATIONAL DE​​​‌ LA RECHERCHE SCIENTIFIQUE CNRS‌ (CNRS), France
  • HELMHOLTZ-ZENTRUM DRESDEN-ROSSENDORF‌​‌ EV (HZDR), Germany
• Inria​​ contact:
  Claudio Pacchierotti
• Coordinator:​​​‌
  Claudio Pacchierotti
• Summary:
  Robots‌ are still often regarded‌​‌ as large machines with​​ links, gears, and electric​​​‌ motors, autonomously interacting with‌ the surrounding environment. Despite‌​‌ the great research efforts​​ in robotics and human-robot​​​‌ interaction (HRI), the way‌ we design, use, and‌​‌ control robots has not​​​‌ fundamentally changed in the​ past 20 years. We​‌ see in small-scale wireless​​ multi-robot systems and cognitive​​​‌ HRI a revolutionary answer​ to nowadays robots limitations.​‌ Instead of large, tethered​​ machines, that are difficult​​​‌ for the human user​ to control, REGO proposes​‌ an innovative set of​​ AI-powered, modular, microsized swarms​​​‌ of robots. They are​ wirelessly steered by electromagnetic​‌ fields as well as​​ able to react to​​​‌ other external stimuli, and​ then naturally controlled by​‌ humans through intuitive dexterous​​ interfaces and interaction techniques.​​​‌ Taking advantage of AI​ multi-robot control strategies, these​‌ robots can team up​​ and collaborate to fulfill​​​‌ complex tasks in a​ robust and unprecedented flexible​‌ way. By exploiting multisensory​​ interaction techniques and cognitive​​​‌ shared control, the operator​ will achieve an unparalleled​‌ level of seamless interaction​​ and continuous collaboration with​​​‌ the robotic team. According​ to the application at​‌ hand, the robotic team​​ will feature different task-specific​​​‌ characteristics (e.g., biocompatibility for​ medical procedures, biodenitrification for​‌ cleaning water, ability to​​ carry drugs to fight​​​‌ infections) and be dispatched​ through various delivery systems,​‌ including a stimuli-responsive milli-scale​​ wireless robotic carrier developed​​​‌ within the project. To​ achieve this revolution, REGO​‌ will develop magnetic multi-robot​​ motion control systems, autonomous​​​‌ swarm control techniques for​ micro-sized robots, human-robot haptic-centered​‌ interfaces, and cognitive shared-control​​ techniques. REGO enables the​​​‌ next generation of AI-powered​ interactive small-size multi-robots systems,​‌ with increased capabilities to​​ work with each other​​​‌ and their human operators.​

10.3.2 H2020 projects‌

10.4.1 Equipex+​ Tirrex

Participants: Fabien Spindler​‌, François Chaumette,​​ Alexandre Krupa.

no​​​‌ Inria Rennes OIP 03-22-01,​ duration: 8 years.

This​‌ large national project devoted​​ to open robotics platforms​​​‌ started in December 2021.​ Rainbow is responsible of​‌ the manipulation axis for​​ which a new TRIAGo​​​‌ platform (Multi-arm Multi-sensor Mobile​ Manipulator) was designed by​‌ PAL Robotics and installed​​ in our lab in​​​‌ April 2025.

10.4.2 PEPR​ O2R

Participants: Maud Marchal​‌, Marie Babel.​​

duration: 8 years.

The​​​‌ Organic Robotics program proposes​ to implement a responsible​‌ and socially acceptable robotics.​​ This PEPR will intensify​​​‌ the multidisciplinary approach of​ the community (digital, life​‌ sciences, engineering, environmental, social​​ sciences) in a strategy​​​‌ that radically differs from​ the current vision of​‌ robotics and its limitations.​​ The Organic Robotics program​​​‌ therefore aims to initiate​ a shift in robotics​‌ allowing to create a​​ new generation of robots​​​‌ capable of interacting and​ working in symbiosis with​‌ humans. We propose to​​ consider the robot, no​​​‌ longer as an automation​ machine, but as a​‌ tool, in line with​​ those that humans have​​​‌ created, used and optimized​ in order to explore​‌ and act on their​​ environment. More efficient, modular,​​​‌ reconfigurable and adaptive, organic​ robots will become an​‌ extension of humans. The​​ PEPR O2R started in​​​‌ September 2023. M. Marchal​ has contributed to the​‌ proposal writing and is​​ a member of the​​​‌ executive committee.

Marie Babel​ participates to the ASSISTMOV​‌ project that aims to​​ design innovative robotic assistance​​​‌ through upper-limb exoskeleton. She​ is a member of​‌ the steering committee of​​ ASSISTMOV project.

Maud Marchal​​​‌ participates to the REINVENT​ and AS4 projects.  

10.4.3​‌ PEPR O2R - AS2​​ structuring action

Participants: Alexandre​​​‌ Krupa, Fabien Spindler​.

• Title:
  PEPR O2R​‌ - AS2 structuring action​​ “Robot motion with physical​​ interactions and social adaptation”​​​‌
• Duration:
  January 2024 -‌ December 2031
• Coordinator:
  LASS-CNRS‌​‌ (Toulouse)
• Partners:
  • Gepeto (LAAS),​​ IDH (LIRMM), Willow (Inria),​​​‌ Auctus (Inria), Rainbow (Inria),‌ Robioss (PPRIME), CERCA (CNRS),‌​‌ ICNA (ONERA), Habiter le​​ Monde (UPJV)
• Summary:
  In​​​‌ the context of the‌ national PEPR O2R robotic‌​‌ exploration program, Alexandre Krupa​​ is involved in the​​​‌ AS2 structuring action. This‌ structuring action aims to‌​‌ rethink the problem of​​ motion generation in robotic​​​‌ systems, taking a global‌ approach and redefining research‌​‌ objectives in conjunction with​​ the Human and Social​​​‌ Sciences. Within this AS2‌ action, the Rainbow group‌​‌ is involved on the​​ development of multi-sensor control​​​‌ strategies for the control‌ of physically interacting robotic‌​‌ systems. Since January 2024,​​ Alexandre Krupa has been​​​‌ co-supervising a PhD student‌ based at LIRMM with‌​‌ Philippe Fraisse (LIRMM) and​​ Andrea Cherubini (LS2N), whose​​​‌ thesis focuses on the‌ robotic manipulation of deformable‌​‌ objects using the LIRMM​​ dual-arm robot BAZAR.

10.4.4​​​‌ PEPR eNSEMBLE

Participant: Maud‌ Marchal.

duration: 8‌​‌ years.

The purpose of​​ eNSEMBLE (Future of Digital​​​‌ Collaboration) is to fundamentally‌ redefine digital tools for‌​‌ collaboration. To address this​​ challenge, a paradigm shift​​​‌ in the design of‌ collaborative systems is needed,‌​‌ comparable to the one​​ that saw the advent​​​‌ of personal computing. To‌ collaborate in a fluid‌​‌ and natural way while​​ taking advantage of computer​​​‌ capabilities, collaboration and sharing‌ must become native features‌​‌ of computer systems, in​​ the same way that​​​‌ files or applications are‌ today. To achieve this‌​‌ goal, we need to​​ invent mixed (i.e. physical​​​‌ and digital) collaboration spaces‌ that do not simply‌​‌ replicate the physical world​​ in virtual environments, enabling​​​‌ co-located and/or geographically distributed‌ teams to work together‌​‌ smoothly and efficiently. The​​ PEPR eNSEMBLE started in​​​‌ September 2023. M. Marchal‌ has contributed to the‌​‌ writing of the proposal​​ and is one of​​​‌ PC1 project leaders.

10.4.5‌ ANR Marsurg

Participants: Eric‌​‌ Marchand, François Chaumette​​, Fabien Spindler.​​​‌

no Inria 16162, duration:‌ 48 months.

This project‌​‌ started in September 2021.​​ It involves a consortium​​​‌ managed by ISIR (Paris)‌ with Pixee Medical and‌​‌ Rainbow group. It aims​​ at researching markerless augmented​​​‌ reality solution for orthopedic‌ surgery

10.4.6 Inria Challenge‌​‌ DORNELL

Participants: Marie Babel​​, Claudio Pacchierotti,​​​‌ Maud Marchal, François‌ Pasteau, Sylvain Guegan‌​‌, Louise Devigne,​​ Marco Aggravi, Inès​​​‌ Lacôte, Pierre-Antoine Cabaret‌, Lisheng Kuang.‌​‌

• Title:
  DORNELL: A multimodal,​​ shapeable haptic handle for​​​‌ mobility assistance of people‌ with disabilities
• Duration:
  November‌​‌ 2020 - December 2024​​
• Coordinators:
  Marie Babel, Claudio​​​‌ Pacchierotti
• Partners:
  • Potioc Inria‌ team
  • MFX Inria team‌​‌
  • LGCGM (Rennes)
  • Centre de​​ rééducation Pôle Saint Hélier​​​‌ (Rennes)
  • ISIR (Paris)
  • Institut‌ des jeunes aveugles (Yzeure)‌​‌
• Inria contact:
  Marie Babel,​​ Claudio Pacchierotti
• Summary:
  While​​​‌ technology helps people to‌ compensate for a broad‌​‌ set of mobility impairments,​​ visual perception and/or cognitive​​​‌ deficiencies still significantly affect‌ their ability to move‌​‌ safely and easily. We​​ propose an innovative multisensory,​​​‌ multimodal, smart haptic handle‌ that can be easily‌​‌ plugged onto a wide​​​‌ range of mobility aids,​ including white canes, precanes,​‌ walkers, and power wheelchairs.​​ Specifically fabricated to fit​​​‌ the needs of a​ person, it provides a​‌ wide set of ungrounded​​ tactile sensations (e.g., pressure,​​​‌ skin stretch, vibrations) in​ a portable and plug-and-play​‌ format – bringing haptics​​ in assistive technologies all​​​‌ at once. The project​ will address important scientific​‌ and technological challenges, including​​ the study of multisensory​​​‌ perception, the use of​ new materials for multimodal​‌ haptic feedback, and the​​ development of a haptic​​​‌ rendering API to adapt​ the feedback to different​‌ assistive scenarios and user’s​​ wishes. We will co-design​​​‌ DORNELL with users and​ therapists, driving our development​‌ by their expectations and​​ needs.

10.4.7 BPI Lichie​​​‌

Participants: François Chaumette.​

no Inria 14876, duration:​‌ 72 months.

This project​​ started in March 2020.​​​‌ It involves a consortium​ managed by Airbus Defense​‌ and Space (Toulouse) with​​ many companies, Onera and​​​‌ Inria. It aims at​ designing a new constellation​‌ of satellites with on-board​​ imaging facilities. Robotics for​​​‌ the assembly of the​ satellites is also studied.​‌ François Chaumette is the​​ Inria scientific coordinator of​​​‌ this project who funded​ 9 PhD and 9​‌ post-doc for the Rainbow,​​ Sairpico, and Sirocco groups​​​‌ in Rennes, Auctus in​ Bordeaux and Ayana in​‌ Sophia-Antipolis.

10.4.8 ANR CAMP​​

Participants: Paolo Robuffo Giordano​​​‌, Fabien Spindler,​ Ali Srour, Tommaso​‌ Belvedere, Salvatore Marcellini​​.

• Title:
  Intrinsically-Robust and​​​‌ Control-Aware Motion Planning for​ Robots in Real-World Conditions​‌
• Duration:
  October 2020 -​​ June 2026
• Coordinator:
  P.​​​‌ Robuffo Giordano
• Partners:
  • LAAS​ (Toulouse)
  • Univ. Twente (Netherlands)​‌
• Inria contact:
  P. Robuffo​​ Giordano
• Summary:
  An effective​​​‌ way of dealing with​ the complexity of robots​‌ operating in real (uncertain)​​ environments is the paradigm​​​‌ of “feedforward/feedback” or “planning/control”:​ in a first step​‌ a suitable nominal trajectory​​ (feedforward) for the robot​​​‌ states/controls is planned exploiting​ the available information (e.g.,​‌ a model of the​​ robot and of the​​​‌ environment). While there has​ been an effort in​‌ proposing “robust planners” or​​ more “global controllers” (e.g.,​​​‌ Model Predictive Control (MPC)),​ a truly unified approach​‌ that fully exploits the​​ techniques of the motion​​​‌ planning and control/estimation communities​ is still missing and​‌ the existing state-of-the-art has​​ several important limitations, namely​​​‌ (1) lack of generality,​ (2) lack of computational​‌ efficiency, and (3) poor​​ robustness. In this respect,​​​‌ the ambition of CAMP​ is to (1) develop​‌ a general and unified​​ “intrinsically-robust and control-aware motion​​​‌ planning framework” able to​ address all the above-mentioned​‌ issues, and to (2)​​ demonstrate the applicability of​​​‌ this new framework to​ real robots in real-world​‌ challenging tasks. In particular​​ we envisage two robotics​​​‌ demonstrators for showing at​ best the effectiveness and​‌ generality of our methodology:​​ (1) an indoor pick-​​​‌ and-place/assembly task involving a​ 7-dof torque-controlled arm for​‌ a first validation in​​ “controlled conditions” and (2)​​​‌ an outdoor cooperative mobile​ manipulation task involving an​‌ aerial manipulator (a quadrotor​​ UAV equipped with an​​​‌ onboard arm) and a​ skid-steering mobile robot with​‌ an onboard arm for​​ a final validation in​​ much less favorable experimental​​​‌ conditions (see Sect. 8.1.1‌)

10.4.9 ANR MULTISHARED‌​‌

Participants: Paolo Robuffo Giordano​​, Claudio Pacchierotti,​​​‌ Vincent Drevelle, Nicola‌ De Carli, Maxime‌​‌ Bernard, Esteban Restrepo​​.

• Title:
  Shared-Control Algorithms​​​‌ for Human/Multi-Robot Cooperation
• Duration:‌
  September 2020 - October‌​‌ 2025
• Coordinator:
  P. Robuffo​​ Giordano
• Inria contact:
  P.​​​‌ Robuffo Giordano
• Summary:
  The‌ goal of the Chaire‌​‌ AI MULTISHARED is to​​ significantly advance the state-of-the-art​​​‌ in multi-robot autonomy and‌ human-multi-robot interaction for allowing‌​‌ a human operator to​​ intuitively control the coordinated​​​‌ motion of a multi-UAV‌ group navigating in remote‌​‌ environments, with a strong​​ emphasis on the division​​​‌ of roles between multi-robot‌ autonomy (in controlling its‌​‌ motion/configuration and online decision-making)​​ and human intervention/guidance for​​​‌ providing high-level commands to‌ the group while being‌​‌ most aware of the​​ group status via VR​​​‌ and haptics technology (see‌ Sect. 8.1.9).

10.4.10‌​‌ ANR MATES

Participants: Claudio​​ Pacchierotti, Paolo Robuffo​​​‌ Giordano, Marco Tognon‌, Valeria Braglia,‌​‌ Francesco Russo, Esteban​​ Restrepo.

• Title:
  Multi-drone-human​​​‌ collaboration teams for high-risk‌ assembling and handling tasks‌​‌
• Duration:
  March 2025 -​​ February 2029
• Coordinator:
  Claudio​​​‌ Pacchierotti
• Partners:
  • LAAS (Toulouse)‌
• Inria contact:
  Claudio Pacchierotti‌​‌
• Summary:
  Despite the great​​ recent progress in automation,​​​‌ computer science, and machine‌ learning, robots still have‌​‌ many limitations (e.g., limited​​ cognitive/manipulation capabilities) and they​​​‌ cannot fulfill alone the‌ wide range of tasks‌​‌ that humans can perform.​​ Achieving an effective collaboration​​​‌ between robots and humans‌ could clearly enlarge the‌​‌ nature of tasks that​​ can be addressed together.​​​‌ The aim of this‌ project is to propose‌​‌ a multi-robot system that​​ allows humans to remotely​​​‌ perform tasks at high‌ locations eliminating any potential‌​‌ risk for the operator.​​ Since ground robots cannot​​​‌ be employed in such‌ conditions, we propose a‌​‌ human-multi-drone team in which​​ a human user remotely​​​‌ controls a group of‌ drones in completing a‌​‌ complex task that requires​​ advanced coordination and manipulation​​​‌ capabilities. To achieve such‌ an ambitious goal, it‌​‌ is essential that drones​​ acquire manipulation capabilities as​​​‌ well as improve their‌ interaction and coordination with‌​‌ humans. Moreover, several advancements​​ in the theory, control,​​​‌ and interaction of coordinated‌ human-drone teams should be‌​‌ accomplished. As a representative​​ example of a high-impact​​​‌ scenario, we plan to‌ carry out a peg-in-hole‌​‌ task at a high​​ location: A group of​​​‌ drones collaboratively transports an‌ object, i.e., a peg,‌​‌ to a target location,​​ i.e., a hole. Once​​​‌ it has been reached,‌ an aerial manipulator grasps‌​‌ the lower part of​​ the peg and inserts​​​‌ it into the hole,‌ coordinating its motion with‌​‌ the one of the​​ transport team. These actions​​​‌ are remotely imparted by‌ a human operator, who‌​‌ controls the synergistic motion​​ of the aerial team​​​‌ using a grounded haptic‌ interface and shared-control techniques.‌​‌ At the same time,​​ the operator receives information​​​‌ about the task, the‌ team, and the interaction‌​‌ with the environment, through​​ a combination of grounded​​​‌ and wearable haptic feedback.‌ A view of the‌​‌ remote environment is provided​​​‌ to the operator through​ a VR headset thanks​‌ to a group of​​ supporting drones equipped with​​​‌ cameras.

10.4.11 ANR JCJC​ AirHandyBot

Participants: Marco Tognon​‌, Paolo Robuffo Giordano​​, Lorenzo Balandi,​​​‌ Maximilian Mehl, Gianluca​ Corsini, Fabien Spindler​‌.

• Title:
  Aerial Robots​​ for True Manipulation of​​​‌ Dynamic and Uncertain Environments​
• Duration:
  November 2023 -​‌ October 2026
• Coordinator:
  Marco​​ Tognon
• Inria contact:
  Marco​​​‌ Tognon
• Summary:
  One of​ the main goals of​‌ robotics is to realize​​ autonomous systems that can​​​‌ help human operators in​ tasks that are hard​‌ and dangerous (e.g., in​​ elevated areas). It is​​​‌ therefore important to conceive​ robots that can perform​‌ physical work executing complex​​ tasks requiring the interaction​​​‌ with the environment and​ the manipulation of objects.​‌ In particular, having aerial​​ robots able to interact​​​‌ with the environment, would​ open the door new​‌ applications in dangerous and​​ hardly accessible area, like​​​‌ manipulation of objects, contact-based​ inspection, and construction. Aiming​‌ to show the feasibility​​ of Aerial Physical Interaction​​​‌ (APhI), previous works focused​ on the design and​‌ control of aerial manipulators.​​ However, current investigations and​​​‌ applications are still limited​ to simple interaction tasks,​‌ involving limited contact behaviors​​ with static and rigid​​​‌ surfaces, moreover performed in​ known and structured environments.​‌ To deploy aerial manipulators​​ in real scenarios, they​​​‌ must be able to​ perform more complex manipulation​‌ tasks in less structured​​ situations. Because of the​​​‌ application, scientific interest, and​ possible future impact of​‌ APhI, FlyHandyBot aims to​​ enhance APhI capabilities of​​​‌ highly dynamical aerial manipulators​ by considering: - manipulations​‌ tasks of movable and​​ articulated objects, relying on​​​‌ onboard sensors only; -​ real scenarios characterized by​‌ disturbances and uncertainties due​​ to system modeling errors,​​​‌ noisy and imprecise measurements​ coming from lightweight onboard​‌ sensors, imprecise actuation models​​ due to complex aerodynamic​​​‌ effects, and partially unknown​ environments. The investigation, including​‌ fundamental theoretical results, real​​ experiments and practical demonstrations,​​​‌ will focus on the​ design of new conception,​‌ modeling and control methods​​ to make aerial robots​​​‌ much more precise, robust​ and safe while performing​‌ physical interaction tasks in​​ real environments. This will​​​‌ allow aerial robots to​ be in the future​‌ valid companions of human​​ operators.

10.4.12 ANR DyNNAMo​​​‌

Participants: Marie Babel,​ François Pasteau, Louise​‌ Devigne.

• Title:
  Shared-Control​​ Algorithms for Human/Multi-Robot Cooperation​​​‌
• Duration:
  April 2025 -​ October 2029
• Coordinator:
  S.​‌ Le Nours
• Inria contact:​​
  Marie Babel
• Summary:
  The​​​‌ DyNNAMO project aims to​ define and validate a​‌ modeling and analysis workflow​​ for the design and​​​‌ optimization of an innovative​ hardware-software architecture, specifically tailored​‌ to enhance detection capabilities​​ in power wheelchairs. The​​​‌ proposed architecture leverages dynamic​ neural networks (DNNs), which​‌ autonomously adjust their computational​​ workload in response to​​​‌ real-time operating conditions.

10.4.13​ AeX AEROTouch

Participants: Marco​‌ Tognon, Tommaso Belvedere​​, Lluis Prior,​​​‌ Gianluca Corsini, Fabien​ Spindler.

• Title:
  Aerial​‌ Robots with the Sense​​ of Touch
• Duration:
  November​​​‌ 2023 - October 2029​
• Coordinator:
  Marco Tognon
• Inria​‌ contact:
  Marco Tognon
• Summary:​​
  Researchers are trying to​​ make aerial robots perform​​​‌ physical work. Current methodologies‌ show promising results, but‌​‌ they fail in real​​ scenarios, mostly because of​​​‌ inaccurate visual perception. Inspired‌ by nature, this project‌​‌ investigates how to also​​ provide aerial robots with​​​‌ the sense of touch‌ and how to use‌​‌ it for improving their​​ manipulation capabilities.

10.4.14 AeX​​​‌ RobotiCore

Participants: Marco Tognon‌, Tommaso Belvedere,‌​‌ Gianluca Corsini.

• Title:​​
  Integrated Hardware Acceleration: the​​​‌ Brain and Heart Behind‌ Next-Generation Robots
• Duration:
  November‌​‌ 2025 - October 2028​​
• Coordinator:
  Marco Tognon and​​​‌ Marcello Traiola (team TARAN)‌
• Inria contact:
  Marco Tognon‌​‌ and Marcello Traiola (team​​ TARAN)
• Summary:
  RobotiCore proposes​​​‌ a methodology to accelerate‌ robotic algorithms on a‌​‌ unified hardware accelerator, to​​ improve performance and energy​​​‌ efficiency for small-scale robotic‌ systems. By efficiently accelerating‌​‌ fundamental robotic operations, RobotiCore​​ addresses the limitations of​​​‌ traditional power-hungry hardware platforms,‌ which currently limit scalability‌​‌ and affordability in robotics.​​

10.4.15 Inria AeX MusMaps​​​‌

Participants: Marie Babel,‌ Mael Gallois, Louise‌​‌ Devigne.

• Title:
  Muscle​​ Mapping for Shared-Control assistance​​​‌ of people with disabilities‌
• Duration:
  2024 - 2028‌​‌
• Coordinator:
  Charles Pontonnier (Combo​​ team) and Marie Babel​​​‌
• Inria contact:
  Charles Pontonnier‌ and Marie Babel
• Partner:‌​‌
  Fondation Saint Hélier
• Summary:​​
  The Inria Exploratory Action​​​‌ MusMapS uses effort measurements‌ (mapping of physical capacities)‌​‌ from disabled patients to​​ personalize the assistance of​​​‌ an upper-limb exoskeleton using‌ shared control to help‌​‌ these patients with their​​ everyday movements. The coupling​​​‌ of a musculoskeletal model‌ representative of the patient's‌​‌ physical capabilities with a​​ shared control system for​​​‌ pathologies such as multiple‌ sclerosis or the after-effects‌​‌ of a stroke is​​ innovative and forms the​​​‌ core of the approach.‌

10.4.16 SequoIA Chair HARMONY‌​‌

Participants: Paolo Robuffo Giordano​​, Esteban Restrepo,​​​‌ Claudio Pacchierotti, Andrea‌ Perna.

• Title:
  Human-AI‌​‌ Robotic Merging for Optimal​​ cooperatioN and efficiency
• Duration:​​​‌
  September 2025 - August‌ 2029
• Coordinator:
  Paolo Robuffo‌​‌ Giordano
• Inria contact:
  Paolo​​ Robuffo Giordano
• Summary:
  Robots​​​‌ embody Artificial Intelligence (AI)‌ through physical interaction with‌​‌ the environment, yet achieving​​ full autonomy in unstructured​​​‌ settings remains challenging due‌ to limitations in perception,‌​‌ decision-making, and actuation. Human–robot​​ cooperation, and in particular​​​‌ shared control, offers a‌ promising way to enhance‌​‌ autonomy by combining robotic​​ precision with human cognitive​​​‌ capabilities. While shared control‌ has shown success in‌​‌ domains such as telemanipulation,​​ navigation, and medical robotics,​​​‌ current approaches rely on‌ static role allocation between‌​‌ AI and human operators,​​ lack robustness to uncertainty,​​​‌ and often increase human‌ cognitive load. Moreover, the‌​‌ design of intuitive multi-sensory​​ interfaces remains an open​​​‌ challenge. The HARMONY project‌ addresses these limitations through‌​‌ three research axes: (A1)​​ real-time adaptive role allocation​​​‌ based on confidence metrics,‌ (A2) robust AI algorithms‌​‌ resilient to perception uncertainty​​ and dynamic environments, and​​​‌ (A3) advanced multi-sensory and‌ VR-based interfaces to improve‌​‌ human situational awareness. These​​ contributions will be validated​​​‌ on two demonstrators: (D1)‌ shared control of heterogeneous‌​‌ aerial–ground robot teams for​​ cooperative manipulation in a​​​‌ Phygital Twin environment with‌ haptic feedback, and (D2)‌​‌ shared control of an​​​‌ anthropomorphic mobile manipulator for​ human–robot collaborative object transport​‌ with dynamic role adaptation.​​

10.5.1​​​‌ Academic Chair IH2A

Participants:​ Marie Babel, François​‌ Pasteau, Louise Devigne​​, Vincent Drevelle,​​​‌ Maud Marchal, Emilie​ Leblong, Anne-Hélène Olivier​‌, Charles Pontonnier,​​ Thomas Voisin, Sebastien​​​‌ Thomas, Fabien Grzeskowiak​, Claudio Pacchierotti,​‌ Maxime Manzano, Mael​​ Gallois, Theo Le​​​‌ Terrier, Elyse Larribau​.

• Title:
  Academic Chair​‌ on Innovations, Handicap, Autonomy​​ and Accessibility (IH2A)
• Duration:​​​‌
  2020-...
• Coordinator:
  Marie Babel​
• Inria contact:
  Marie Babel​‌
• Partners:
  INSA Rennes, Université​​ Rennes, Université Rennes 2,​​​‌ Centre de médecine physique​ et de réadaptation Fondation​‌ Saint Hélier (Rennes), CHU​​ Pontchaillou Rennes, M2S
• Summary:​​​‌
  This research chair (Innovations,​ Handicap, Autonomy and Accessibility​‌ - IH2A) aims to​​ propose the most appropriate​​​‌ technological solutions to compensate​ for sensorimotor impairments that​‌ limit people's mobility and​​ autonomy in everyday tasks​​​‌ and leisure activities. The​ IH2A Chair aims to​‌ structure these activities from​​ a social, scientific and​​​‌ clinical point of view​ and to be an​‌ effective and innovative tool​​ for the development of​​​‌ large-scale research in this​ field. This multidisciplinary research​‌ and innovative collaborative experiments​​ allow the clinical and​​​‌ scientific validation of the​ technical assistance offered, while​‌ ensuring the accessibility of​​ the solutions deployed.

10.5.2​​​‌ AAP PME HUBERT

Participants:​ Marie Babel, François​‌ Pasteau, Vincent Drevelle​​, Emilie Leblong,​​​‌ Fabien Grzeskowiak.

• Title:​
  HUBERT
• Duration:
  January 2023​‌ - June 2026
• Coordinator:​​
  BA Healthcare
• Inria contact:​​​‌
  Marie Babel
• Partners:
  INSA​ Rennes, BA Healthcare, Centre​‌ de médecine physique et​​ de réadaptation Fondation Saint​​​‌ Hélier (Rennes)
• Summary:
  The​ aim of this project​‌ is to create a​​ range of robotized walkers​​​‌ for geriatric use in​ health and social care​‌ establishments, to give residents​​ or patients greater independence.​​​‌

10.5.3 AAP PME ARDEB​

Participants: Marie Babel,​‌ François Pasteau, Fabien​​ Grzeskowiak.

• Title:
  ARDEB​​​‌
• Duration:
  January 2024 -​ December 2027
• Coordinator:
  BA​‌ Healthcare
• Inria contact:
  Marie​​ Babel
• Partners:
  INSA Rennes,​​​‌ BA Healthcare, DK Innovation​
• Summary:
  The ARDEB project​‌ aims to develop an​​ innovative inclusive mobility solution​​​‌ based on a combination​ of a Segway and​‌ a robotic system that​​ is verticalized, stabilized, and​​​‌ secure. This alternative to​ wheelchairs is designed to​‌ be both compact and​​ versatile, promoting independence and​​​‌ social interaction while minimizing​ the physiological risks associated​‌ with sitting.

11.1.1 Scientific events: organisation​

11.1.2 Scientific events:​​​‌ selection

11.1.3 Journal

11.1.4​ Invited talks

• Marco Tognon​‌ . “Advancements in aerial​​ physical interaction: design control​​​‌ and collaborations”. LAAS-CNRS, Toulouse,​ France. March 2025.
• Marco​‌ Tognon . “Advancements in​​ aerial physical interaction: design​​​‌ control and collaborations”. University​ of La Reunion, Saint​‌ Denis, La Reunion. September​​ 2025.
• Paolo Robuffo Giordano​​​‌ . “Intrinsic Robust Planning​ for Uncertain Robots”. Sapienza​‌ Univ Rome, Italy, January​​ 2025
• Paolo Robuffo Giordano​​​‌ . “Shared Control for​ Tele-manipulation and Tele-navigation at​‌ the Macro and Micro​​ scale”'. GdR Thematic day​​​‌ on “Shared Control”, Paris,​ France, January 2025
• Paolo​‌ Robuffo Giordano . “Introduction​​ to Sensitivity-Based Robust Planning”.​​​‌ ICRA 2025 Workshop on​ Beyond the Lab: Robust​‌ Planning and Control in​​ Real World Scenarios, May​​​‌ 2025
• Paolo Robuffo Giordano​ . “Introduction to Sensitivity-Based​‌ Robust Planning”. JNRR 2025​​ Workshop on Introduction to​​​‌ Sensitivity-Based Robust Planning, October​ 2025
• Paolo Robuffo Giordano​‌ . “Shared Control for​​ Tele-manipulation and Tele-navigation at​​​‌ the Macro and Micro​ scale”'. European Cyber Week​‌ 2025, November 2025
• Claudio​​ Pacchierotti . “Haptique: la​​​‌ science du toucher.” Visites​ insolites du CNRS, Rennes,​‌ France, 2025.
• Claudio Pacchierotti​​ . “Haptique: la science​​​‌ du toucher.” Visites insolites​ du CNRS, Rennes, France,​‌ 2025.
• Claudio Pacchierotti .​​ “Haptic shared control for​​​‌ telerobotics.” Journées Nationales de​ la Recherche en Robotique​‌ (JNRR), Rennes, France, 2025.​​
• Claudio Pacchierotti . “Cutaneous​​​‌ Haptic Feedback for Human-Centered​ Robotics: a 10-years retrospective.”​‌ Eindhoven University of Technology​​ (TU/e), Eindhoven, The Netherlands,​​​‌ 2025.
• Claudio Pacchierotti .​ “Cutaneous Haptic Feedback for​‌ Improving Telepresence.” Workshop on​​ “The Importance of Haptics​​​‌ in Telepresence” at IEEE​ World Haptics Conference (WHC),​‌ Suwon, Republic of Korea,​​ 2025.
• Claudio Pacchierotti .​​​‌ “Wearable cutaneous haptics: an​ historical overview.” Workshop on​‌ “Emerging Challenges in Wearable​​ Haptics” at IEEE World​​​‌ Haptics Conference (WHC), Suwon,​ Republic of Korea, 2025.​‌
• Claudio Pacchierotti . “Haptics:​​ the science of touch.”​​​‌ Introduction for the keynote​ session on Haptics at​‌ the IEEE International Conference​​ on Robotics and Automation​​​‌ (ICRA), Atlanta, USA, 2025.​
• Claudio Pacchierotti . “Haptics​‌ for small-scale robotics” Workshop​​ on “Empowering Humans with​​​‌ Miniaturized Sensing and Control:​ Shared Autonomy for Small-Scale​‌ Robots (SASSR)” at the​​ IEEE International Conference on​​​‌ Robotics and Automation (ICRA),​ Atlanta, USA, 2025.
• Claudio​‌ Pacchierotti . “Haptics for​​ biomedical applications.” Seminar for​​​‌ the M2 course on​ Biomedical Engineering, University of​‌ Twente, Enschede, The Netherlands,​​ 2025.
• François Chaumette .​​​‌ "Geometric and end-to-end robot​ vision-based control". Plenary talk​‌ at the IEEE International​​ Conference on Emerging Technologies​​​‌ and Computing (ICETC), Brest,​ June 2025
• Fabien Spindler​‌ presented the national 2RM​​ network of roboticists and​​​‌ mechatronics engineers at the​ National Robotics Research Days​‌ (JNRR 2025), October 2025.​​
• Gianluca Corsini , Romain​​​‌ Lagneau , Olivier Roussel​ , Fabien Spindler ,​‌ and Samuel Felton each​​ gave presentations on the​​​‌ ROBSTAR robotics platform and​ robotics-related software to promote​‌ ViSP and telekyb3 within​​ the community during the​​​‌ 2RM national meeting (June​ 2025) and at the​‌ first meeting of Inria’s​​ thematic robotics network (Sept.​​​‌ 2025).
• Esteban Restrepo .​ “Open Multi-Robot Systems for​‌ Resilient Teams.” GdR Robotique​​ TS3 & GICAT Workshop​​ on Multi-Robot Systems, Rennes,​​​‌ France, 2025.
• Esteban Restrepo‌ . “Towards Resilient and‌​‌ Autonomous Human-Multi-Robot Collaboration.” Seminar​​ for the École normale​​​‌ supérieure de Rennes, Rennes,‌ France, 2025.

11.1.5 Leadership‌​‌ within the scientific community​​

• Marco Tognon is the​​​‌ co-organizer (co-animateur) of the‌ scientific thematics 3 “Heterogeneity‌​‌ and Complexity” (TS3 “Hétérogénéité​​ et Complexité”, 2024 onwards)​​​‌ of GdR Robotique.
• Marco‌ Tognon is Co-Chair of‌​‌ the IEEE Technical Committee​​ Aerial Robotics and UAVs​​​‌ (2024 onwards).
• Paolo Robuffo‌ Giordano was member (elected)‌​‌ of the Section 07​​ of the Comité National​​​‌ de la Recherche Scientifique.‌
• Paolo Robuffo Giordano has‌​‌ started an appointment as​​ President of the EuRobotics​​​‌ Georges Giralt Award
• Paolo‌ Robuffo Giordano is co-Chair‌​‌ of the “IEEE​​ RAS Young Reviewers Program​​​‌”, which is part‌ of the IEEE RAS‌​‌ Member Activities Board (MAB)​​
• Paolo Robuffo Giordano is​​​‌ Distinguished Lecturer for the‌ IEEE RAS Technical Committee‌​‌ on Multi-robot Systems
• Claudio​​ Pacchierotti is Distinguished Lecturer​​​‌ of the IEEE Robotics‌ & Automation Society for‌​‌ the field of haptics​​ (Region 8: Europe, Middle​​​‌ East and Africa, 2025‌ onwards).
• Claudio Pacchierotti is‌​‌ Co-Chair, IEEE Technical Committee​​ on Telerobotics (2023 –​​​‌ 2026).
• Claudio Pacchierotti is‌ Scientific Advisory Board, “TOAST:‌​‌ Touch-enabled Tactile Internet Training​​ Network and Open Source​​​‌ Testbed,” Marie Skłodowska-Curie Action‌ (2025 – 2026).
• Claudio‌​‌ Pacchierotti is Secretary, Eurohaptics​​ Society (2018 – 2022,​​​‌ 2022 – 2026).
• Claudio‌ Pacchierotti is Responsible for‌​‌ the GdR Robotique at​​ IRISA (2025 onwards).
• Claudio​​​‌ Pacchierotti is Organization Committee,‌ Program Committee, and “Code‌​‌ of Conduct” Officer, Journées​​ Nationales de la Recherche​​​‌ en Robotique (JNRR), Rennes,‌ 2025.
• Claudio Pacchierotti is‌​‌ Co-organizer (co-animateur) of the​​ scientific thematics 4 “Human-centered​​​‌ robotics” (TS4 “Robotique centrée‌ sur l'humain”, 2024 onwards).‌​‌
• François Chaumette was president​​ of the jury for​​​‌ the 2024 best French‌ thesis in robotics organized‌​‌ by the the "GdR​​ Robotique".
• Fabien Spindler co-organized​​​‌ the first workshop of‌ Inria’s thematic network dedicated‌​‌ to robotics in sept.​​ 2025.
• Fabien Spindler was​​​‌ a member of the‌ HCERES evaluation committee of‌​‌ the LIRIS laboratory in​​ Lyon
• Marie Babel serves​​​‌ as the Deputy Director‌ of the GdR Robotique‌​‌ since 2024.
• Alexandre Krupa​​ was the organizer of​​​‌ the session “Robotic manipulation”‌ of the French National‌​‌ Robotics Research Days (JNRR​​ 2025).
• Alexandre Krupa is​​​‌ responsible (since November 2025)‌ of the “manipulation” axis‌​‌ of the national Equipex+​​ Tirrex project devoted to​​​‌ open robotic platforms.

11.1.6‌ Scientific expertise

• Paolo Robuffo‌​‌ Giordano served as expert/reviewer​​ for the euRobotics “George​​​‌ Giralt” award for the‌ best European PhD thesis‌​‌ in robotics. He was​​ reviewer for EU Consolidator​​​‌ and Advanced Grants. He‌ was member of the‌​‌ HCERES committee for evaluating​​ the LIRMM lab, and​​​‌ committee member of the‌ Chaire professeur junior (CPJ)‌​‌ CNRS “Véhicules autonomes et​​ transport”, Heudiasyc, France. Finally,​​​‌ he is member of‌ the Steering Committee (Comité‌​‌ de Pilotage) for the​​ PEPR “Accélération en Robotique”​​​‌
• Marie Babel is the‌ vice-president of the Comité‌​‌ d’évaluation of ANR (CE33​​ - Interaction, robotique -​​​‌ 2024, 2025). She leads‌ an Academic Chair on‌​‌ Innovations, Handicap, Autonomy and​​​‌ accessibility since 2020. She​ serves since 2017 as​‌ an expert for the​​ International Mission of the​​​‌ French Research Ministry (MEIRIES).​ She serves as a​‌ member of the Selection​​ and Validation Committee of​​​‌ the Pôle Images et​ Réseaux since 2022.

11.1.7​‌ Research administration

• Alexandre Krupa​​ is the president of​​​‌ the CUMIR (“Commission des​ Utilisateurs des Moyens Informatiques​‌ pour la Recherche”) of​​ Centre Inria de l'Université​​​‌ de Rennes since February​ 2023.
• Vincent Drevelle is​‌ an elected member of​​ the IRISA laboratory council​​​‌ since 2023.
• Eric Marchand​ is the head of​‌ the doctoral school Matisse​​

11.2.1 Supervision​​

• Ph.D. completed: Maxime Manzano,​​​‌ “Reach-to-grasp in activities of‌ daily living: shared control‌​‌ of a multisensory assistive​​ device to compensate for​​​‌ upper extremity neuromuscular disorders.”,‌ defended in December 2025,‌​‌ supervised by Marie Babel,​​ Ronan Le Breton, and​​​‌ Sylvain Guégan 73
• Ph.D.‌ completed: Emilie Leblong, “Taking‌​‌ into account social interactions​​ in a virtual reality​​​‌ power wheelchair driving simulator:‌ promoting learning for inclusive‌​‌ mobility”, defended in July​​ 2025, supervised by Marie​​​‌ Babel and Anne-Hélène Olivier‌ (Virtus team) 72
• Ph.D.‌​‌ completed: Thibault Noël, "Autonomous​​ Exploration of an Unknown​​​‌ 3D Environment" defended in‌ January 2025, supervised by‌​‌ François Chaumette and Eric​​ Marchand 75.
• Ph.D.​​​‌ completed: Erwan Normand, “Augmenting‌ the interaction with everyday‌​‌ objects with wearable haptics​​ and AR,” defended in​​​‌ January 2025, supervised by‌ Claudio Pacchierotti, Maud Marchal‌​‌ and Eric Marchand 76​​.
• Ph.D. completed: Maxime​​​‌ Bernard, “Shared control for‌ multi-robot systems”, defended in‌​‌ April 2025, supervised by​​ Paolo Robuffo Giordano and​​​‌ Claudio Pacchierotti 70
• Ph.D.‌ completed: Lendy Mulot, “Advancing‌​‌ Ultrasound Mid-Air Haptics: Perception​​ Studies, Rendering Methods, and​​​‌ Design of Virtual Reality‌ Interactions,” defended in November‌​‌ 2025, supervised by Claudio​​ Pacchierotti and M. Marchal.​​​‌
• Ph.D. completed: Antonio Marino,‌ “Learning-based Formation Control and‌​‌ Localizaton for Multiple Robots”,​​ defended in December 2025,​​​‌ supervised by Paolo Robuffo‌ Giordano and Claudio Pacchierotti‌​‌ 74
• Ph.D. completed: Mandela​​ Ouafo Fonkoua,“Vision-based shape servoing​​​‌ of soft objects using‌ finite element model”, defended‌​‌ in December 2025, supervised​​ by Alexandre Krupa and​​​‌ François Chaumette 71.‌
• Ph.D. in progress: Sylvain‌​‌ Jannin, “Collaboration and navigation​​ of multi-robot systems at​​​‌ the small-scale for clinical‌ applications,” started in October‌​‌ 2025, supervised by Claudio​​ Pacchierotti.
• Ph.D. in progress:​​​‌ Francesco Russo, “Shared autonomy‌ for intuitive collaboration between‌​‌ humans and multiple robots,”​​ started in December 2025,​​​‌ supervised by Claudio Pacchierotti‌ and E. Restrepo.
• Ph.D.‌​‌ in progress: Jessé De​​ Oliveira Santan Alves, “Human-robot​​​‌ interaction and shared control‌ for robotic telemanipulation,” started‌​‌ in November 2024, supervised​​ by Claudio Pacchierotti.
• Ph.D.​​​‌ in progress: Sara Rossi,‌ “Tactile haptic perception and‌​‌ rendering for robotic prosthesis,”​​ started in February 2024,​​​‌ supervised by Claudio Pacchierotti‌ and M. Marchal.
• Ph.D.‌​‌ in progress: Yuxin Jin,​​ “Detection and tracking of​​​‌ microagents using Artificial Intelligence,”‌ started in September 2023,‌​‌ supervised by Claudio Pacchierotti​​​‌ and S. Misra.
• Ph.D.​ in progress: Léon Raphalen,​‌ “Human-centered shared control of​​ multi-robot systems at the​​​‌ microscale,” started in September​ 2023, supervised by Claudio​‌ Pacchierotti.
• Ph.D. in progress:​​ Andrea Perna, “Coordination of​​​‌ Heterogeneous Multi-robot systems for​ Multi-objective Missions”, started in​‌ November 2025, supervised by​​ Esteban Restrepo and Paolo​​​‌ Robuffo Giordano
• Ph.D. in​ progress: Valeria Braglia, “Perception-Aware​‌ Cable Suspended Multi-Drone Transportation”,​​ started in February 2025,​​​‌ supervised by Marco Tognon​ and Paolo Robuffo Giordano​‌
• Ph.D. in progress: Lorenzo​​ Balandi, “Full-Body Design and​​​‌ Control of an Aerial​ Manipulator for Advance Physical​‌ Interaction”, started in October​​ 2023, supervised by Marco​​​‌ Tognon and Paolo Robuffo​ Giordano
• Ph.D. in progress:​‌ Szymon Bielenin, “Robust and​​ Agile Transportation of Cable​​​‌ Suspended-Loads with Multi-Drone Systems”,​ started in October 2024,​‌ supervised by Marco Tognon,​​ Paolo Robuffo Giordano and​​​‌ Claudio Pacchierotti
• Ph.D. in​ progress: Phillip Maximilian Mehl,​‌ “Learning-based Control of an​​ Aerial Manipulator for Complex​​​‌ Manipulation Tasks”, started in​ January 2024, supervised by​‌ Marco Tognon
• Ph.D. in​​ progress: Lluis Prior Sancho,​​​‌ “AEROTouch – AErial RObots​ with the sense of​‌ Touch”, started in November​​ 2024, supervised by Marco​​​‌ Tognon
• Ph.D. in progress:​ Johan Berrier-Gonzalez,“Forming carbon fiber​‌ fabrics by visual servoing”,​​ started in October 2025,​​​‌ supervised by Alexandre Krupa.​
• Ph.D. in progress: Simone​‌ Rotondi,“Shape visual servoing of​​ deformable objects robust to​​​‌ model uncertainties”, started in​ November 2025, supervised by​‌ Paolo Robuffo Giordano, Alexandre​​ Krupa and Tommaso Belvedere.​​​‌
• Ph.D. in progress: Jose​ Eduardo Aguilar Segovia, “Design​‌ of haptic feedback using​​ innovative shape-able materials”, started​​​‌ in October 2022, supervised​ by Marie Babel, Sylvain​‌ Lefebvre (MFXteam, Nancy) and​​ Sylvain Guégan
• Ph.D. in​​​‌ progress: Maël Gallois, “Shared​ control by muscle mapping​‌ for upper limb assistance​​ in neuromuscular and neurodegenerative​​​‌ pathologies”, started in September​ 2024, supervised by Marie​‌ Babel, Charles Pontonnier (Combo​​ team), Nicolas Vignais (Combo)​​​‌ and Sylvain Guégan (LGCGM)​
• Ph.D. in progress: Théo​‌ Le Terrier, “Sensor-based control​​ of a power wheelchair​​​‌ with interval set-membership methods”,​ started in October 2023,​‌ supervised by Marie Babel​​ and Vincent Drevelle.
• Ph.D​​​‌ in progress: Elyse Larribau,​ "Conception et commande d'un​‌ exosquelette de poignet-main basé​​ sur la modélisation de​​​‌ biomécanique personnalisée d'usagers en​ situation de handicap à​‌ mobilité résiduelle.", started in​​ October 2025, supervised by​​​‌ Marie Babel, Charles Pontonnier​ (Combo), Nolwenn Fougeron (Combo),​‌ Sylvain Guégan
• Ph.D. in​​ progress: Amine Ouasfi, "Apprentissage​​​‌ auto-supervisé pour la reconstruction​ de formes implicites", started​‌ in 2022, supervised by​​ Adnane Boukhayama and Eric​​​‌ Marchand

11.2.2 Juries

11.2.3‌ Educational and pedagogical outreach‌​‌

• Claudio Pacchierotti organized a​​ one-day educational workshop introducing​​​‌ 8 middle-school students to‌ mobile robotics, including robot‌​‌ control exercises, Rennes, France,​​ 2025.
• Claudio Pacchierotti organized​​​‌ a one-day educational workshop‌ introducing 20 high-school students‌​‌ to mechatronics and mobile​​ robotics, including hands-on assembly​​​‌ and robot control exercises,‌ Rennes, France, 2025.

11.3.1 Productions (articles,‌​‌ videos, podcasts, serious games,​​ ...)

• In 79,​​​‌ we present a perspective‌ on engineering human-cyberphysical synergy,‌​‌ exploring how machines can​​ evolve from tools into​​​‌ collaborative teammates that perceive‌ touch and context. We‌​‌ discuss the necessary convergence​​ of robotics, materials science,​​​‌ and neuroscience to realize‌ systems such as aerial‌​‌ manipulators and drone swarms​​ capable of physical interaction.​​​‌ The article highlights the‌ role of affective haptics‌​‌ and embodied AI in​​ achieving intuitive collaboration, while​​​‌ also addressing the ethical‌ and societal implications of‌​‌ these emerging technologies.

11.3.2​​ Participation in Live events​​​‌

• Claudio Pacchierotti organized the‌ Visites Insolites du CNRS‌​‌ à l'IRISA, “Toucher​​ le virtuel: les fascinantes​​​‌ interactions entre humains et‌ machines,” a public‌​‌ engagement event on human-computer​​ interaction and haptics, Rennes,​​​‌ France, 2025.

International​​​‌ journals

• 15 articleJ.‌ E.Jose Eduardo Aguilar-Segovia‌​‌, F.Fabien Grzeskowiak​​, S.Sylvain Lefebvre​​​‌, M.Marie Babel‌ and S.Sylvain Guégan‌​‌. Parametric Foam-Like Capacitive​​ Sensors for 3D Printing​​​‌ of Deformable Parts with‌ Sensing Capabilities.IEEE‌​‌ Sensors Journal253​​February 2025, 4261-4272​​​‌HALDOIback to‌ text
• 16 articleJ.‌​‌ E.José Eduardo Aguilar-Segovia​​, S.Salim Perchy​​​‌, P.-A.Pierre-Alexandre Hugron‌, S.Sylvain Guégan‌​‌, M.Marie Babel​​ and S.Sylvain Lefebvre​​​‌. Customization of 3D‌ printed sensing devices in‌​‌ the layered fabrication space​​.Computers and Graphics​​​‌133December 2025,‌ 104459HALDOIback‌​‌ to text
• 17 article​​M.Marie Babel,​​​‌ S.Sylvain Guégan and‌ L.Louise Devigne.‌​‌ Robotique d’assistance : conception​​ et commande pour l’autonomie​​​‌ en fauteuil roulant électrique‌.Les Techniques de‌​‌ l'IngenieurJune 2025,​​ 1-45HALDOIback​​​‌ to textback to‌ text
• 18 articleL.‌​‌Lorenzo Balandi, P.​​ R.Paolo Robuffo Giordano​​​‌ and M.Marco Tognon‌. QP-Based Inner-Loop Control‌​‌ for Constraint-Safe and Robust​​ Trajectory Tracking for Aerial​​​‌ Robots.IEEE Robotics‌ and Automation Letters10‌​‌7July 2025,​​ 6640-6647HALDOIback​​​‌ to textback to‌ text
• 19 articleA.‌​‌Angélina Bellicha, L.​​Lucas Struber, F.​​​‌François Pasteau, V.‌Violaine Juillard, L.‌​‌Louise Devigne, S.​​Serpil Karakas, S.​​​‌Stephan Chabardes, M.‌Marie Babel and G.‌​‌Guillaume Charvet. Depth-sensor-based​​ shared control assistance for​​​‌ mobility and object manipulation:‌ toward long-term home-use of‌​‌ BCI-controlled assistive robotic devices​​.Journal of Neural​​​‌ Engineering221February‌ 2025, 016045HAL‌​‌DOIback to text​​back to text
• 20​​​‌ articleT.Tommaso Belvedere‌, M.Marco Cognetti‌​‌, G.Giuseppe Oriolo​​ and P.Paolo Robuffo​​​‌ Giordano. Sensitivity-Aware Model‌ Predictive Control for Robots‌​‌ with Parametric Uncertainty.​​IEEE Transactions on Robotics​​​‌412025, 3039-3058‌HALDOIback to‌​‌ textback to text​​back to text
• 21​​​‌ articleT.Tommaso Belvedere‌, M.Michael Ziegltrum‌​‌, G.Giulio Turrisi​​ and V.Valerio Modugno​​​‌. Feedback-MPPI: Fast Sampling-Based‌ MPC via Rollout Differentiation‌​‌ – Adios low-level controllers​​​‌.IEEE Robotics and​ Automation Letters111​‌2026, 1 -​​ 8HALDOIback​​​‌ to text
• 22 article​N.Nicola de Carli​‌, R.Riccardo Belletti​​, E.Emanuele Buzzurro​​​‌, A.Andrea Testa​, G.Giuseppe Notarstefano​‌ and M.Marco Tognon​​. Distributed NMPC for​​​‌ Cooperative Aerial Manipulation of​ Cable-Suspended Loads.IEEE​‌ Robotics and Automation Letters​​10102025,​​​‌ 10546-10553HALDOIback​ to textback to​‌ text
• 23 articleA.​​Alessandro Colotti and F.​​​‌François Chaumette. Globally-stable​ and robust image-based visual​‌ servoing for positioning with​​ respect to a cylinder​​​‌.IEEE Robotics and​ Automation Letters1011​‌November 2025, 12071-12078​​HALDOIback to​​​‌ textback to text​
• 24 articleM.Marco​‌ Ferro, F.Franco​​ Piñan Basualdo, P.​​​‌Paolo Robuffo Giordano,​ S.Sarthak Misra and​‌ C.Claudio Pacchierotti.​​ Experimental Evaluation of Haptic​​​‌ Shared Control for Multiple​ Electromagnetic Untethered Microrobots.​‌IEEE Transactions on Automation​​ Science and Engineering22​​​‌2025, 8069-8080HAL​DOIback to text​‌back to text
• 25​​ articleJ.Joshua Fleck​​​‌, Z.Zane Zook​, J.Janelle Clark​‌, D.Daniel Preston​​, D.Darren Lipomi​​​‌, C.Claudio Pacchierotti​ and M.Marcia O'Malley​‌. Wearable multi-sensory haptic​​ devices.Nature Reviews​​​‌ Bioengineering34April​ 2025, 288–302HAL​‌DOIback to text​​
• 26 articleM.Maël​​​‌ Gallois, M.Mégane​ Millan, N.Nicolas​‌ Vignais, S.Sylvain​​ Guégan, M.Marie​​​‌ Babel, J.Justin​ Carpentier and C.Charles​‌ Pontonnier. Human-Robot Co-Simulation​​ method for upper limb​​​‌ assistive force calculation using​ polytopes.Multidisciplinary Biomechanics​‌ Journal22025,​​ 287–289HALDOIback​​​‌ to text
• 27 article​A.Antonio González-Morgado,​‌ E.Eugenio Cuniato,​​ G.Guillermo Heredia,​​​‌ A.Aníbal Ollero,​ R.Roland Siegwart and​‌ M.Marco Tognon.​​ How to Shake Trees​​​‌ With Aerial Manipulators? A​ Theoretical and Experimental Study​‌.IEEE Robotics and​​ Automation Letters108​​​‌2025, 8067-8074HAL​DOIback to text​‌
• 28 articleA.Antonio​​ González-Morgado, E.Eugenio​​​‌ Cuniato, M.Marco​ Tognon, G.Guillermo​‌ Heredia, R.Roland​​ Siegwart and A.Aníbal​​​‌ Ollero. Controlled Shaking​ of Trees With an​‌ Aerial Manipulator.IEEE/ASME​​ Transactions on Mechatronics30​​​‌2April 2025,​ 1026-1037HALDOIback​‌ to text
• 29 article​​A.Antonio Gonzalez-Morgado,​​​‌ J.Jonas Soueidan,​ G.Guillermo Heredia,​‌ A.Anibal Ollero,​​ P.Philippe Fraisse,​​​‌ M.Marco Tognon and​ M.Marco Cognetti.​‌ A Nonlinear MPC for​​ Physical Human-Aerial Robot Interaction​​​‌ in Collaborative Transportation Tasks​.IEEE Robotics and​‌ Automation Letters1010​​2025, 9670 -​​​‌ 9677HALDOIback​ to text
• 30 article​‌G.Glenn Kerbiriou,​​ Q.Quentin Avril and​​​‌ M.Maud Marchal.​ Data-driven modeling of subtle​‌ eye region deformations.​​Computers and Graphics133​​​‌December 2025, 104425​HALDOIback to​‌ text
• 31 articleT.​​Théo Le Terrier,​​ M.Marie Babel and​​​‌ V.Vincent Drevelle.‌ Ultra-Wideband Smart Wheelchair Pose‌​‌ Estimation Using Interval Analysis​​.Acta Cybernetica2025​​​‌, 1-20In press.‌ HALback to text‌​‌back to text
• 32​​ articleA.Antonio Marino​​​‌, C.Claudio Pacchierotti‌ and P.Paolo Robuffo‌​‌ Giordano. A Gated​​ Graph Neural Network Approach​​​‌ to Fast-Convergent Dynamic Average‌ Estimation.ACM Transactions‌​‌ on Intelligent Systems and​​ Technology163May​​​‌ 2025, 1-18HAL‌DOIback to text‌​‌
• 33 articleA.Antonio​​ Marino, E.Esteban​​​‌ Restrepo, C.Claudio‌ Pacchierotti and P. R.‌​‌Paolo Robuffo Giordano.​​ Decentralized Reinforcement Learning for​​​‌ Multi-Agent Multi-Resource Allocation via‌ Dynamic Cluster Agreements.‌​‌IEEE Robotics and Automation​​ Letters108August​​​‌ 2025, 8123-8130HAL‌DOIback to text‌​‌back to text
• 34​​ articleJ.Julien Mellet​​​‌, M.Mike Allenspach‌, E.Eugenio Cuniato‌​‌, C.Claudio Pacchierotti​​, R.Roland Siegwart​​​‌ and M.Marco Tognon‌. Evaluation of Human-Robot‌​‌ Interfaces based on 2D/3D​​ Visual and Haptic Feedback​​​‌ for Aerial Manipulation.‌Journal of Intelligent and‌​‌ Robotic Systems1113​​2025, 104HAL​​​‌DOIback to text‌back to textback‌​‌ to text
• 35 article​​E.Ekrem Misimi,​​​‌ S.Sverre Herland and‌ F.François Chaumette.‌​‌ Visual Servoing-Based Active Vision​​ for 3D Object Reconstruction​​​‌.IEEE Robotics and‌ Automation LettersNovember 2025‌​‌, 1-8HALback​​ to text
• 36 article​​​‌C.Claudio Pacchierotti.‌ Haptic feedback that rings‌​‌ true.Nature Electronics​​9December 2025,​​​‌ 1-4HALDOIback‌ to text
• 37 article‌​‌F.Francesca Pagano,​​ N.Nicola de Carli​​​‌, E.Esteban Restrepo‌, A.Antonio Marino‌​‌ and P. R.Paolo​​ Robuffo Giordano. Distributed​​​‌ Multi-Robot Active-Sensing of a‌ Diffusive Source.IEEE‌​‌ Robotics and Automation Letters​​10102025,​​​‌ 10807-10814HALDOIback‌ to textback to‌​‌ text
• 38 articleA.​​Andrea Pupa, T.​​​‌Tommaso Belvedere, C.‌Cristian Secchi and P.‌​‌ R.Paolo Robuffo Giordano​​. On the Computation​​​‌ of Sensitivity Tubes.‌IEEE Robotics and Automation‌​‌ Letters109July​​ 2025, 8802 -​​​‌ 8809HALDOIback‌ to text
• 39 article‌​‌E.Esteban Restrepo,​​ C.Cristian Secchi and​​​‌ P.Paolo Robuffo Giordano‌. Passivity Preserving Energy-Aware‌​‌ Design for Multi-Dimensional Switched​​ Systems: Application to Open​​​‌ Multi-Robot Systems.Automatica‌181November 2025,‌​‌ 112496HALDOIback​​ to text
• 40 article​​​‌A.Ali Srour,‌ A.Antonio Franchi,‌​‌ P.Paolo Robuffo Giordano​​ and M.Marco Cognetti​​​‌. Experimental Validation of‌ Sensitivity-Aware Trajectory Planning for‌​‌ a Redundant Robotic Manipulator​​ Under Payload Uncertainty.​​​‌IEEE Robotics and Automation‌ Letters102February‌​‌ 2025, 1561-1568HAL​​DOIback to text​​​‌
• 41 articleS.Sihao‌ Sun, X.Xuerui‌​‌ Wang, D.Dario​​ Sanalitro, A.Antonio​​​‌ Franchi, M.Marco‌ Tognon and J.Javier‌​‌ Alonso-Mora. Agile and​​ Cooperative Aerial Manipulation of​​​‌ a Cable-Suspended Load.‌Science Robotics10107‌​‌October 2025, 1-46​​​‌HALDOIback to​ textback to text​‌
• 42 articleY.Yash​​ Vyas, M.Matteo​​​‌ Bottin, M.Marco​ Tognon and S.Silvio​‌ Cocuzza. Design and​​ comparative analysis of force​​​‌ balanced 2 degree of​ freedom planar robot manipulator​‌ concepts.Journal of​​ Mechanisms and Robotics2025​​​‌, 1-17In press.​ HALDOIback to​‌ text

International peer-reviewed conferences​​

• 43 inproceedingsL.Lorenzo​​​‌ Balandi, P.Paolo​ Robuffo Giordano and M.​‌Marco Tognon. Acceleration-based​​ Inner-loop Control and MPC​​​‌ for Aerial Robots: Advantages​ and Drawbacks.European​‌ Robotics Forum 2025ERF​​ 2025 - European Robotics​​​‌ ForumStuttgart, Germany2025​, 1-6HALback​‌ to textback to​​ text
• 44 inproceedingsL.​​​‌Lorenzo Balandi, P.​Paolo Robuffo Giordano and​‌ M.Marco Tognon.​​ Enhancing IMU Accuracy in​​​‌ MRAVs: A Theoretical and​ Experimental Approach to Vibration​‌ Damping.ICUAS 2025​​ - International Conference on​​​‌ Unmanned Aircraft SystemsCharlotte​ (North Carolina), United States​‌2025, 1-7HAL​​DOIback to text​​​‌back to text
• 45​ inproceedingsT.Tommaso Belvedere​‌, A.Amr Afifi​​, S.Simon Wasiela​​​‌ and A.Andrea Pupa​. Planning under Uncertainties​‌ with Closed-Loop Sensitivity: Recent​​ Results and Perspectives.​​​‌ERF 2025 - European​ Robotics ForumStuttgart, Germany​‌March 2025, 1-5​​HALDOIback to​​​‌ text
• 46 inproceedings E.​Elodie Bouzbib, G.​‌Gauthier Gendreau, N.​​Noé Guillaumin, M.​​​‌Marc Teyssier, C.​Claudio Pacchierotti and A.​‌Anatole Lécuyer. Flexible​​ Reality: Can Pseudo-Haptics Enhance​​​‌ Vibration Intensity Perception in​ Co-Located AR Interaction? IHM​‌ 2025 - 36e Conférence​​ Internationale Francophone sur l'Interaction​​​‌ Humain-Machine IHM’25 : Articles​ Scientifiques de la 36ème​‌ conférence Francophone sur l’Interaction​​ Humain-Machine Toulouse, France November​​​‌ 2025 HAL DOI back​ to text back to​‌ text
• 47 inproceedingsP.-A.​​Pierre-Antoine Cabaret, C.​​​‌Claudio Pacchierotti, M.​Marie Babel and M.​‌Maud Marchal. In-Hand​​ Haptic Representation of User's​​​‌ Surroundings in Virtual Reality​.WHC 2025 -​‌ IEEE World Haptics Conference​​Suwon, South KoreaIEEE​​​‌2025, 1-7HAL​DOIback to text​‌back to text
• 48​​ inproceedingsG.Gilles Chabert​​​‌, F.François Chaumette​ and A. S.Adolfo​‌ Suarez Roos. Clevis​​ and Tenon Assembly Using​​​‌ Visual Guiding Fields.​IROS 2025 - IEEE/RSJ​‌ International Conference on Intelligent​​ Robots and SystemsHangzhou,​​​‌ ChinaIEEE2025,​ 1-8HALback to​‌ text
• 49 inproceedingsO.​​Odichimnma Ezeji, M.​​​‌Michael Ziegltrum, G.​Giulio Turrisi, T.​‌Tommaso Belvedere and V.​​Valerio Modugno. BC-MPPI:​​​‌ A Probabilistic Constraint Layer​ for Safe Model-Predictive Path-Integral​‌ Control.Communications in​​ Computer and Information Science​​​‌ (AREA 2025)AREA 2025​ - 5th Workshop on​‌ Agents and Robots for​​ reliable Engineered Autonomy2700​​​‌Communications in Computer and​ Information ScienceBologna, Italy​‌Springer Nature SwitzerlandOctober​​ 2025, 131-143HAL​​​‌DOIback to text​
• 50 inproceedingsF.Frederik​‌ Falk Nyboe, A.​​Amr Afifi, P.​​​‌Paolo Robuffo Giordano,​ E.Emad Ebeid and​‌ A.Antonio Franchi.​​ Embedded Robust Model Predictive​​ Path Integral Control using​​​‌ Sensitivity Tubes and GPU‌ Acceleration.ICRA 2025‌​‌ - IEEE International Conference​​ on Robotics & Automation​​​‌Altlanta, United StatesMay‌ 2025, 7174-7180HAL‌​‌DOIback to text​​back to text
• 51​​​‌ inproceedingsM.Mael Gallois‌, M.Maxime Manzano‌​‌, S.Sylvain Guégan​​, N.Nicolas Vignais​​​‌, M.Marie Babel‌ and C.Charles Pontonnier‌​‌. Effort generation capabilites​​ mapping for personalized robotic​​​‌ assistance of the elbow‌.ICORR 2025 -‌​‌ IEEE International Conference on​​ Rehabilitation RoboticsChicago, United​​​‌ StatesIEEE2025,‌ 1-6HALDOIback‌​‌ to text
• 52 inproceedings​​P.Pedro Gomez Hernandez​​​‌, J. M.Jonas‌ Mariager Jakobsen, C.‌​‌Claudio Pacchierotti, F.​​Francesco Chinello and C.​​​‌Cheng Fang. Stiffness‌ regulation co-pilot in bilateral‌​‌ teleimpedance control: a preliminary​​ user study.ICRA​​​‌ 2025 - IEEE International‌ Conference on Robotics and‌​‌ Automation,Atlanta (Georgia), United​​ StatesIEEE2025,​​​‌ 5622-5628HALDOIback‌ to text
• 53 inproceedings‌​‌J.Julien Manson,​​ A.Anatole Lécuyer,​​​‌ C.Claudio Pacchierotti and‌ J.Justine Saint-Aubert.‌​‌ Walk on Hands: Can​​ Vibrations in the Hands​​​‌ Support Walking Experience in‌ Virtual Reality?WHC 2025‌​‌ - IEEE World Haptics​​ ConferenceSuwon, South Korea​​​‌IEEE2025, 1-7‌HALDOIback to‌​‌ textback to text​​
• 54 inproceedingsH.Hiroki​​​‌ Ota, Y.Yutaro‌ Hirao, M.Monica‌​‌ Perusquía-Hernández, H.Hideaki​​ Uchiyama, K.Kiyoshi​​​‌ Kiyokawa and M.Maud‌ Marchal. Enhancing Visuo-Haptic‌​‌ Coherency by Manipulating Fingertip​​ Contact Tilt.2025​​​‌ IEEE Conference on Virtual‌ Reality and 3D User‌​‌ Interfaces Abstracts and Workshops​​ (VRW)Saint Malo, France​​​‌IEEEMarch 2025,‌ 1308-1309HALDOIback‌​‌ to textback to​​ text
• 55 inproceedingsH.​​​‌Hiroki Ota, M.‌Monica Perusquía-Hernández, K.‌​‌Kiyoshi Kiyokawa, Y.​​Yutaro Hirao, H.​​​‌Hideaki Uchiyama and M.‌Maud Marchal. FresnelDeformable:‌​‌ A Softness Presentation Technique​​ Combining Fingertip Plane Tilt​​​‌ Manipulation and Pseudo-Stiffness.‌CHI EA 2025 -‌​‌ Extended Abstracts of the​​ CHI Conference on Human​​​‌ Factors in Computing Systems‌Yokohama, JapanACMApril‌​‌ 2025, 1-6HAL​​DOIback to text​​​‌back to text
• 56‌ inproceedingsL.Leon Raphalen‌​‌, T.Tom Goalard​​, M.Marco Ferro​​​‌, P. R.Paolo‌ Robuffo Giordano and C.‌​‌Claudio Pacchierotti. Occlusion-Safe​​ Shared Micromanipulation in Vision-Constrained​​​‌ Environments.Telepresence 2025‌ - Second IEEE Conference‌​‌ on TelepresenceLeiden, Netherlands​​September 2025, 1-4​​​‌HALback to text‌back to text
• 57‌​‌ inproceedingsS.Sara Rossi​​, C.Claudio Pacchierotti​​​‌ and M.Maud Marchal‌. Studying the Perception‌​‌ of Vibrotactile Stimulation on​​ the Arm via a​​​‌ Modular Wearable Sleeve.‌WHC 2025 - IEEE‌​‌ World Haptics ConferenceSuwon,​​ South KoreaIEEE2025​​​‌, 499-505HALDOI‌back to textback‌​‌ to text
• 58 inproceedings​​J.John Thomas and​​​‌ F.François Chaumette.‌ Positioning with respect to‌​‌ a cylinder using proximity-based​​ control.IROS 2025​​​‌ - IEEE/RSJ Int. Conf.‌ on Intelligent Robots and‌​‌ SystemsHangzhou, China2025​​​‌, 1-8HALback​ to textback to​‌ text

National peer-reviewed Conferences​​

• 59 inproceedingsT.Théo​​​‌ Le Terrier, M.​Marie Babel and V.​‌Vincent Drevelle. Model​​ Predictive Control for Autonomous​​​‌ Navigation of Smart Wheelchairs​ Using Ultra-wideband Sensors.​‌Actes du Colloque Jeunes​​ Chercheurs, Jeunes Chercheuses 2025,​​​‌ Campus Condorcet, Aubervilliers, 10​ juin 2025.JCJC 2025​‌ - Colloque Jeunes Chercheurs,​​ Jeunes ChercheusesAubervilliers, France​​​‌June 2025, 33-38​HALback to text​‌back to text
• 60​​ inproceedingsM.Manzano Maxime​​​‌, G.Gallois Maël​, G.Guégan Sylvain​‌, L. B.Le​​ Breton Ronan, D.​​​‌Devigne Louise and B.​Babel Marie. Enhancing​‌ the Usability of Upper-Limb​​ Assistive Robots with a​​​‌ Variable Admittance Controller.​Actes du Colloque Jeunes​‌ Chercheurs, Jeunes Chercheuses 2025,​​ Campus Condorcet, Aubervilliers,10 juin​​​‌ 2025.JCJC 2025 -​ Colloque Jeunes Chercheurs, Jeunes​‌ Chercheuses 2025Aubervilliers (Campus​​ Condorcet), France2025,​​​‌ 14-19HALback to​ text

Conferences without proceedings​‌

• 61 inproceedingsM.Mael​​ Gallois, M.Maxime​​​‌ Manzano, S.Sylvain​ Guégan, N.Nicolas​‌ Vignais, M.Marie​​ Babel and C.Charles​​​‌ Pontonnier. Commande partagée​ par cartographie musculaire pour​‌ l’assistance du membre supérieur​​.SOFAMEA 2025 -​​​‌ XXIIIe Congrès de la​ Société Francophone d'Analyse du​‌ Mouvement chez l'Adulte et​​ l'EnfantParis, France2025​​​‌HALback to text​
• 62 inproceedingsT.Théo​‌ Le Terrier, M.​​Marie Babel and V.​​​‌Vincent Drevelle. Ultra-wideband​ Based Smart Wheelchair Static​‌ Pose Estimation using Interval​​ Analysis.SCAN 2025​​​‌ - 20th International Symposium​ on Scientific Computing, Computer​‌ Arithmetic, and Verified Numerical​​ ComputationsOldenburg, Germany2025​​​‌HALback to text​back to text
• 63​‌ inproceedingsT.Théo Le​​ Terrier, M.Marie​​​‌ Babel and V.Vincent​ Drevelle. Ultra-wideband Sensor​‌ Based Robust Model Predictive​​ Control.SWIM 2025​​​‌ - Summer Workshop on​ Interval MethodsRennes, France​‌2025, 1-4HAL​​back to textback​​​‌ to text
• 64 inproceedings​M.Monica Malvezzi,​‌ L.Lisheng Kuang,​​ C.Claudio Pacchierotti and​​​‌ F.Francesco Chinello.​ Model-Based Analysis and Evaluation​‌ of an Origami Encounter-type​​ Wearable Device.TELEPRESENCE​​​‌ 2025 - Second IEEE​ Conference on TelepresenceLeiden,​‌ Netherlands2025, 1-6​​HALback to text​​​‌back to text
• 65​ inproceedingsM.Maximilian Mehl​‌, A. D.Alberto​​ Dalla Libera, R.​​​‌Ruggero Carli and M.​Marco Tognon. Model-Based​‌ Reinforcement Learning for Robust​​ End-to-End UAV Control from​​​‌ Simulation to Real System​ Application.ERF 2025​‌ - European Robotics Forum​​Stuttgart, Germany2025,​​​‌ 1-6HALback to​ textback to text​‌back to text
• 66​​ inproceedingsL.Leon Raphalen​​​‌, M.Marco Ferro​, S.Sarthak Misra​‌, P.Paolo Robuffo​​ Giordano and C.Claudio​​​‌ Pacchierotti. Haptic Shared​ Control of a Pair​‌ of Microrobots for Telemanipulation​​ using Constrained Optimization.​​​‌IROS 2025Hangzhou, China​October 2025HALback​‌ to textback to​​ text
• 67 inproceedingsA.​​​‌Aurélie Tomezzoli, B.​Boris Cassard, E.​‌Elyse Larribau, M.​​Marie Babel, E.​​Emilie Leblong and C.​​​‌Charles Pontonnier. Développement‌ de modèles personnalisés de‌​‌ génération d'effort chez les​​ patients présentant un déficit​​​‌ neurologique : étude préliminaire‌.SOFAMEA 2025 -‌​‌ XXIIIè congrès de la​​ Société Francophone d’Analyse du​​​‌ Mouvement chez l’Adulte et‌ l’EnfantParis, France2025‌​‌, 1-2HALback​​ to text

Scientific book​​​‌ chapters

• 68 inbookF.‌François Chaumette. Visual‌​‌ Control.Robotics Goes​​ MOOCSpringer Nature Switzerland​​​‌June 2025, 135-164‌HALDOIback to‌​‌ text
• 69 inbookM.​​Maud Marchal and C.​​​‌Claudio Pacchierotti. Virtual‌ Reality and Haptics.‌​‌Robotics Goes MOOCSpringer​​ Nature SwitzerlandMay 2025​​​‌, 111-158HALDOI‌back to text

Doctoral‌​‌ dissertations and habilitation theses​​

• 70 thesisM.Maxime​​​‌ Bernard. Haptic shared‌ control for multi-robot systems‌​‌.Université de Rennes​​April 2025HALback​​​‌ to text
• 71 thesis‌M. O.Mandela Ouafo‌​‌ Fonkoua. Vision-based shape​​ servoing of soft objects​​​‌ using finite element model‌.Université de Rennes‌​‌December 2025HALback​​ to textback to​​​‌ textback to text‌
• 72 thesisÉ.Émilie‌​‌ Leblong. Social interaction​​ in virtual reality powered​​​‌ wheelchair driving simulation: Fostering‌ learning for inclusive mobility‌​‌.INSA RennesJuly​​ 2025HALback to​​​‌ text
• 73 thesisM.‌Maxime Manzano. Contributions‌​‌ to Ergonomics and Control​​ Methods for Upper-Limb Assistive​​​‌ Exoskeletons.Institut National‌ des Sciences Appliquées -‌​‌ RennesDecember 2025HAL​​back to text
• 74​​​‌ thesisA.Antonio Marino‌. Learning to Communicate‌​‌ and Coordinate: Distributed Learning-based​​ Control for Multi-Robot Systems​​​‌.Université de Rennes‌December 2025HALback‌​‌ to text
• 75 thesis​​T.Thibault Noël.​​​‌ Autonomous exploration of an‌ unknown 3D environment.‌​‌Université de RennesJanuary​​ 2025HALback to​​​‌ textback to text‌back to text
• 76‌​‌ thesisE.Erwan Normand​​. Study of the​​​‌ perception and manipulation of‌ virtual objects in augmented‌​‌ reality using wearable haptics​​.Université de Rennes​​​‌January 2025HALback‌ to text

Other scientific‌​‌ publications

• 77 inproceedingsT.​​Théo Lefeuvre, K.​​​‌Kyungho Won, M.‌Monica Malvezzi, M.‌​‌Mihai Dragusanu, C.​​Claudio Pacchierotti, A.​​​‌Anatole Lécuyer, M.-M.‌ J.Marc J.-M. Macé‌​‌ and L.Léa Pillette​​. Toward EEG discrimination​​​‌ of fingers movements during‌ motor imagery vs passive‌​‌ movement.2025 -​​ Doctoriales Laval VirtualLaval,​​​‌ France2025, 1-4‌HALback to text‌​‌
• 78 miscJ.Julien​​ Manson, A.Anatole​​​‌ Lécuyer, C.Claudio‌ Pacchierotti and J.Justine‌​‌ Saint-Aubert. Walk on​​ Hands: Experiencing Vibrations in​​​‌ the Hands to represent‌ Virtual Walking.2025‌​‌, 1-1HALback​​ to text
• 79 misc​​​‌C.Claudio Pacchierotti and‌ M.Marco Tognon.‌​‌ When Machines Feel and​​ Cooperate: Engineering Human-Cyberphysical Synergy​​​‌.July 2025,‌ 45-47HALback to‌​‌ text