Scientific context

So far, only a few autonomous robots have been deployed for a long time (weeks, months, or years) outside of factories and laboratories. They are mostly mobile robots that simply “move around” (e.g., vacuum cleaners or museum “guides”) and data collecting robots (e.g., boats or underwater “gliders” that collect data about the water of the ocean).

A large part of the long-term autonomy community is focused on simultaneous localization and mapping (SLAM), with a recent emphasis on changing and outdoor environments 49, 57. A more recent theme is life-long learning: during long-term deployment, we cannot hope to equip robots with everything they need to know, therefore some things will have to be learned along the way. Most of the work on this topic leverages machine learning and/or evolutionary algorithms to improve the ability of robots to react to unforeseen changes 49, 54.

Main challenges

The first major challenge is to endow robots with a stable situation awareness in open and dynamic environments. This covers both the state estimation of the robot by itself as well as the perception/representation of the environment. Both problems have been claimed to be solved but it is only the case for static environments 53.

In the Larsen team, we aim at deployment in environments shared with humans which imply dynamic objects that degrade both the mapping and localization of a robot, especially in cluttered spaces. Moreover, when robots stay longer in the environment than for the acquisition of a snapshot map, they have to face structural changes, such as the displacement of a piece of furniture or the opening or closing of a door. The current approach is to simply update an implicitly static map with all observations but without attempt at distinguishing the suitable changes. For localization in not-too-cluttered or not-too-empty environments, this is generally sufficient since a significant fraction of the environment should remain stable. But for life-long autonomy, and in particular for navigation, the quality of the map, and especially the knowledge of the stable parts, is primordial.

A second major obstacle to moving robots outside of labs and factories is their fragility: Current robots often break in a few hours, if not a few minutes. This fragility mainly stems from the overall complexity of robotic systems, which involve many actuators, many sensors, and complex decisions, and from the diversity of situations that robots can encounter. Low-cost robots exacerbate this issue because they can be broken in many ways (high-quality material is expensive), because they have low self-sensing abilities (sensors are expensive and increase the overall complexity), and because they are typically targeted towards non-controlled environments (e.g., houses rather than factories, in which robots are protected from most unexpected events). More generally, this fragility is a symptom of the lack of adaptive abilities in current robots.

Angle of attack

To solve the state estimation problem, our approach is to combine classical estimation filters (Extended Kalman Filters, Unscented Kalman Filters, or particle filters) with a Bayesian reasoning model in order to internally simulate various configurations of the robot in its environment. This should allow for adaptive estimation that can be used as one aspect of long-term adaptation. To handle dynamic and structural changes in an environment, we aim at assessing, for each piece of observation, whether it is static or not.

We also plan to address active sensing to improve the situation awareness of robots. Literally, active sensing is the ability of an interacting agent to act so as to control what it senses from its environment with the typical objective of acquiring information about this environment. A formalism for representing and solving active sensing problems has already been proposed by members of the team 48 and we aim to use it to formalize decision-making problems for improving situation awareness.

Situation awareness of robots can also be tackled by cooperation, whether it be between robots or between robots and sensors in the environment (deployed in sensorized environments) or between robots and humans. This is in rupture with classical robotics, in which robots are conceived as self-contained. But, in order to cope with as diverse environments as possible, these classical robots use precise, expensive, and specialized sensors, whose cost prohibits their use in large-scale deployments for service or assistance applications. Furthermore, when all sensors are on the robot, they share the same point of view on the environment, which is a limit for perception. Therefore, we propose to complement a cheaper robot with sensors distributed in a target environment. This is an emerging research direction that shares some of the problematics of multi-robot operation and we are therefore collaborating with other teams at Inria that address the issue of communication and interoperability.

To address the fragility problem, the traditional approach is to first diagnose the situation, then use a planning algorithm to create/select a contingency plan. But, again, this calls for both expensive sensors on the robot for the diagnosis and extensive work to predict and plan for all the possible faults that, in an open and dynamic environment, are almost infinite. An alternative approach is then to skip the diagnosis and let the robot discover by trial and error a behavior that works in spite of the damage with a reinforcement learning algorithm 62, 54. However, current reinforcement learning algorithms require hundreds of trials/episodes to learn a single, often simplified, task 54, which makes them impossible to use for real robots and more ambitious tasks. We therefore need to design new trial-and-error algorithms that will allow robots to learn with a much smaller number of trials (typically, a dozen). We think the key idea is to guide online learning on the physical robot with dynamic simulations. For instance, in our recent work, we successfully mixed evolutionary search in simulation, physical tests on the robot, and machine learning to allow a robot to recover from physical damage 55, 1.

A final approach to address fragility is to deploy several robots or a swarm of robots or to make robots evolve in an active environment. We will consider several paradigms such as (1) those inspired from collective natural phenomena in which the environment plays an active role for coordinating the activity of a huge number of biological entities such as ants and (2) those based on online learning 52. We envision to transfer our knowledge of such phenomenon to engineer new artificial devices such as an intelligent floor (which is in fact a spatially distributed network in which each node can sense, compute and communicate with contiguous nodes and can interact with moving entities on top of it) in order to assist people and robots (see the principle in 60, 52, 47).

Scientific context

Interaction with the environment is a primordial requirement for an autonomous robot. When the environment is sensorized, the interaction can include localizing, tracking, and recognizing the behavior of robots and humans. One specific issue lies in the lack of predictive models for human behavior and a critical constraint arises from the incomplete knowledge of the environment and the other agents.

On the other hand, when working in the proximity of or directly with humans, robots must be capable of safely interacting with them, which calls upon a mixture of physical and social skills. Currently, robot operators are usually trained and specialized but potential end-users of robots for service or personal assistance are not skilled robotics experts, which means that the robot needs to be accepted as reliable, trustworthy and efficient 65. Most Human-Robot Interaction (HRI) studies focus on verbal communication 61 but applications such as assistance robotics require a deeper knowledge of the intertwined exchange of social and physical signals to provide suitable robot controllers.

Main challenges

We are here interested in building the bricks for a situated HRI addressing both the physical and social dimension of the close interaction, and the cognitive aspects related to the analysis and interpretation of human movement and activity.

The combination of physical and social signals into robot control is a crucial investigation for assistance robots 63 and robotic co-workers 59. A major obstacle is the control of physical interaction (precisely, the control of contact forces) between the robot and the human while both partners are moving. In mobile robots, this problem is usually addressed by planning the robot movement taking into account the human as an obstacle or as a target, then delegating the execution of this “high-level” motion to whole-body controllers, where a mixture of weighted tasks is used to account for the robot balance, constraints, and desired end-effector trajectories 46.

The first challenge is to make these controllers easier to deploy in real robotics systems, as currently they require a lot of tuning and can become very complex to handle the interaction with unknown dynamical systems such as humans. Here, the key is to combine machine learning techniques with such controllers.

The second challenge is to make the robot react and adapt online to the human feedback, exploiting the whole set of measurable verbal and non-verbal signals that humans naturally produce during a physical or social interaction. Technically, this means finding the optimal policy that adapts the robot controllers online, taking into account feedback from the human. Here, we need to carefully identify the significant feedback signals or some metrics of human feedback. In real-world conditions (i.e., outside the research laboratory environment) the set of signals is technologically limited by the robot's and environmental sensors and the onboard processing capabilities.

The third challenge is for a robot to be able to identify and track people on board. The motivation is to be able to estimate online either the position, the posture, or even moods and intentions of persons surrounding the robot. The main challenge is to be able to do that online, in real-time and in cluttered environments.

Angle of attack

Our key idea is to exploit the physical and social signals produced by the human during the interaction with the robot and the environment in controlled conditions, to learn simple models of human behavior and consequently to use these models to optimize the robot movements and actions. In a first phase, we will exploit human physical signals (e.g., posture and force measurements) to identify the elementary posture tasks during balance and physical interaction. The identified model will be used to optimize the robot whole-body control as prior knowledge to improve both the robot balance and the control of the interaction forces. Technically, we will combine weighted and prioritized controllers with stochastic optimization techniques. To adapt online the control of physical interaction and make it possible with human partners that are not robotics experts, we will exploit verbal and non-verbal signals (e.g., gaze, touch, prosody). The idea here is to estimate online from these signals the human intent along with some inter-individual factors that the robot can exploit to adapt its behavior, maximizing the engagement and acceptability during the interaction.

Another promising approach already investigated in the Larsen team is the capability for a robot and/or an intelligent space to localize humans in its surrounding environment and to understand their activities. This is an important issue to handle both for safe and efficient human-robot interaction.

Simultaneous Tracking and Activity Recognition (STAR) 64 is an approach we want to develop. The activity of a person is highly correlated with his position, and this approach aims at combining tracking and activity recognition to make one benefit from the other. By tracking the individual, the system may help infer its possible activity, while by estimating the activity of the individual, the system may make a better prediction of his/her possible future positions (especially in the case of occlusions). This direction has been tested with simulator and particle filters 51, and one promising direction would be to couple STAR with decision making formalisms like partially observable Markov decision processes (POMDPs). This would allow us to formalize problems such as deciding which action to take given an estimate of the human location and activity. This could also formalize other problems linked to the active sensing direction of the team: how should the robotic system choose its actions in order to better estimate the human location and activity (for instance by moving in the environment or by changing the orientation of its cameras)?

Another issue we want to address is robotic human body pose estimation. Human body pose estimation consists of tracking body parts by analyzing a sequence of input images from single or multiple cameras.

Human posture analysis is of high value for human robot interaction and activity recognition. However, even though the arrival of new sensors like RGB-D cameras has simplified the problem, it still poses a great challenge, especially if we want to do it online, on a robot and in realistic world conditions (cluttered environment). This is even more difficult for a robot to bring together different capabilities both at the perception and navigation level 50. This will be tackled through different techniques, going from Bayesian state estimation (particle filtering), to learning, active and distributed sensing.

7.1.1 Prescyent

• Name:
  Prescyent
• Keywords:
  Machine learning, Robotics, Telerobotics, Timeseries Prediction
• Functional Description:

  PreScyent is a trajectory forecasting library, built upon pytorch_lightning. It comes with datasets such as:

  • AndyData-lab-onePerson
  • AndyData-lab-onePersonTeleoperatingICub
  • Human3.6M
  • And synthetics dataset to test simple properties of our predictors.

  It come also with baselines to run over theses datasets, referred in the code as Predictors, such as:

  • SiMLPe a MultiLayer Perceptron (MLP) with Discrete Cosine Transform (DCT), shown as a strong baseline achieving SOTA results against bigger and more complicated models.
  • Seq2Seq, an architecture mapping an input sequence to an output sequence, that originated from NLP and grew in popularity for time series predictions. Here we implemented an RNN Encoder and RNN Decoder.
  • Probabilistic Movement Primitives (ProMPs), an approach commonly used in robotics to model movements by learning from demonstrations and generating smooth, adaptable trajectories under uncertainty.
  • Some simple ML Baselines such as a Fully Connected MultiLayer Perceptron and an auto-regressive predictor with LSTMs.
  • Non machine learning baselines, maintaining the velocity or positions of the inputs, or simply delaying it.
• News of the Year:
  - First public release - Support for many datasets - Support for many baselines - Full documentation, including tutorials
• URL:
  https://­hucebot.­github.­io/­prescyent/
• Contact:
  Jean-Baptiste Mouret
• Participants:
  Jean-Baptiste Mouret, Alexis Biver

8.1.1 Planning, decision, and control

8.1.2 Learning and optimization

8.2.1 Planning for Human-Robot collaboration

8.2.2 Exoskeleton and ergonomics

PhD grant with SAFRAN

Participants: François Charpillet, Pauline Maurice, Serena Ivaldi, Alexandre Oliveira Souza.

Collaboration with Jordane Grenier (Safran) and Christophe Guettier (Safran).

The thesis is funded by Safran to develop the AI-based control of their hybrid exoskeleton, based on the one developed in the DGA-Rapid project ASMOA. It consists in developing methods to predict the amount of assistance that is needed by the human in tasks invovling payload manipulation.

PhD work co-advised with CEA-LIST

Participants: Jacques Zhong, Francis Colas, Pauline Maurice.

Collaboration with Vincent Weistroffer (CEA-LIST) and Claude Andriot (CEA-LIST)

This PhD work started in October, 2020. The objective is to develop a software tool that allows taking into account the diversity of workers' morphology when designing an industrial workstation. The developed tool will enable us to test the feasibility and ergonomics of a task for any morphology of workers, based on a few demonstrations of the task in virtual reality by one single worker. The two underlying scientific questions are i) the automatic identification of the task features from a few virtual reality (VR) demonstrations, and ii) the transfer of the identified task to digital human models of various morphologies.

PhD work co-advised with CEA-LIST

Participants: Quentin Rolland, Jean-Baptiste Mouret.

Collaboration with Fabrice Mayran de Chamisso (CEA-LIST) and Claude Andriot (CEA-LIST)

This PhD work started in October, 2024. The objective is to leverage anomaly detection “one-class” learning algorithms to improve imitation learning in robotics.

10.1.1 Visits of international scientists

10.2.1 Horizon Europe

10.3.1 PEPR O2R: AS3

Participants: Serena Ivaldi, Jean-Baptiste Mouret, Enrico Mingo Hoffman, Pauline Maurice.

• Program:
  PEPR
• Project acronym:
  AS3
• Project title:
  Decision, Apprentissage et Interaction Sociale
• Duration:
  Janvier 2024 – Decembre 2031
• Coordinator:
  Serena Ivaldi
• Local coordinator:
  Serena Ivaldi
• Abstract:
  Le défi scientifique majeur de cette action structurante est de jeter les bases de nouveaux algorithmes de décision, d’apprentissage et d’interaction centrés sur la société. Nous avons identifié 4 défis clés qui seront au cœur du développement scientifique de ce projet : l’anticipation et la prédiction humaine, l’interaction multimodale, l’apprentissage au cours des interactions et la confiance. Notre approche pour relever ces défis consiste à concevoir et à mener des études d’observation conjointes sur le terrain, par des experts en robotique et en sciences sociales. L’analyse conjointe des études de terrain aura un impact sur la conception de nouvelles théories, de nouveaux modèles et de nouveaux algorithmes, en tenant compte des aspects humains et sociétaux de ces défis. Dans la première partie du projet, le consortium se concentrera sur les manipulateurs mobiles, en utilisant des plateformes facilement disponibles dans le consortium pour mener des expériences avec des humains en public et sur les lieux de travail. Dans la seconde partie du projet, le consortium élargira son champ d’investigation aux robots portables, avec un degré plus élevé d’incarnation et d’interaction physique. L’objectif est d’informer le développement des plateformes dans les PI1, PI2 et PI3 et d’identifier les liens bidirectionnels avec AS1, AS2 et AS4.

10.3.2 PEPR O2R: PI3

Participants: Serena Ivaldi, Pauline Maurice.

• Program:
  PEPR
• Project acronym:
  PI3
• Project title:
  ASSISTMOV
• Duration:
  Janvier 2024 – Decembre 2031
• Coordinator:
  Franck Geffard (CEA)
• Local coordinator:
  Serena Ivaldi
• Abstract:
  Le projet intégré PI3 “ASSISTMOV”, composé d’une équipe pluridisciplinaire ingénierie et de Sciences Humaines et Sociales (SHS), cible le cas d’usage de l’utilisation de la robotique d’assistance au mouvement de personnes en situation de handicap (PSH). A travers le développement d’une gamme d’exosquelettes (membres inférieurs et supérieurs), ce projet vise une technologie de rupture pour une interaction fluide et robuste à la variété d’environnements et d’usages (de la rééducation à la vie quotidienne). Le projet suivra la philosophie proposée dans ce PEPR dont le but est de repenser la conception des robots depuis le matériel jusqu’au logiciel, de manière à favoriser l’adaptation sociale et l’inclusion. Centrée sur une vision globale de l’usage dans son écosystème, cette approche innovante intégrant les SHS, questionnera la pertinence des orientations technologiques existantes et projetées que ce soit par rapport au membre supérieur (MS) ou inférieur (MI). Les objectifs sont de proposer des démonstrateurs robotiques socialement adaptés (Challenge 1) en garantissant une interaction fluide(Challenge 3) basée sur une architecture matérielle et logicielle robuste à une variété d’environnements et d’usages (Challenge 2).

10.3.3 ANR : OSTENSIVE

Participants: Serena Ivaldi, Jean-Baptiste Mouret.

• Program:
  ANR
• Project acronym:
  OSTENSIVE
• Project title:
  Ostensive Human-Robot Interaction
• Duration:
  April 2025 – April 2028
• Coordinator:
  Mohamed Chetouani (Sorbonne Université)
• Local coordinator:
  Serena Ivaldi
• Abstract:
  When humans demonstrate a task to another human or agent, they go beyond merely manipulating the targeted object (instrumental action) to add to their actions ostensive communicative cues such as eye gaze and/or modulations of the demonstrations in the space–-time dimensions (belief–directed action). This modulation results in behaviors that might appear to be sub–optimal, such as pause, repetition and exaggeration, but they are provided to communicate additional information. Recent research in Cognitive Science addressed this challenge of communication in action. Similarly, when robots have to perform actions, there is a need for mechanisms of communication in action allowing to combine instrumental and belief-directed actions. In robotics, this is known as the instantiation of legible robot motion (transparency through motion) by which a robot communicates its intent to a human observer. OSTENSIVE will provide novel solutions to study and develop human-robot interaction systems that are conceptually human centric by explicitly combining instrumental and belief-directed dimensions at key stages such as human behavior perception, human/robot motion representations, robot motion synthesis and simulation to real transfer. We will consider several approaches for (de)coupling instrumental and belief-directed actions by leveraging research in cognitive science and exploiting multi-task learning in order to explicitly consider dual components of human and robot actions.

10.3.4 ANR : MeRLin: Multi-limbed Robots empowered by whole-body Loco-manipulation.

Participants: Enrico Mingo Hoffman, Ioannis Tsikelis, Serena Ivaldi, Jean-Baptiste Mouret.

• Program:
  ANR
• Project title:
  MeRLin
• Duration:
  April 2025 – September 2028
• Coordinator:
  Enrico Mingo Hoffman (INRIA, Nancy)
• Abstract:

  The MeRLin project addresses the limitations of current robotics in performing hazardous and strenuous tasks, which are still predominantly carried out by human workers in industries like construction and heavy manufacturing. Such tasks often expose workers to significant safety and health risks, including long-term musculoskeletal disorders. Motivated by the need to create safer working environments and enhance productivity, the project focuses on developing advanced robotics capable of operating in unstructured and dynamic environments.

  The project targets the development of a robot-agnostic framework that enables multi-limbed robots to perform complex loco-manipulation tasks by coordinating their entire bodies.

10.3.5 ANR: ROOIBOS

Participants: Pauline Maurice, Francis Colas, Vincent Thomas.

• Program:
  ANR JCJC
• Project acronym:
  ROOIBOS
• Project title:
  User-Specific Adaptation of Collaborative Robot Motion for Improved Ergonomics
• Duration:
  March 2021 – August 2025
• Coordinator:
  Pauline Maurice (CNRS)
• Summary:
  Collaborative robots have the potential to reduce work-related musculoskeletal disorders not only by decreasing the workers' physical load, but also by modifying and improving their postures. Imposing a sudden modification of one's movement can however be detrimental to the acceptance and efficacy of the human-robot collaboration. In ROOIBOS, we will develop a framework to plan user-specific trajectories for collaborative robots, to gradually optimize the efficacy of the collaboration and the long-term occupational health of the user. We will use machine learning and probabilistic methods to perform user-specific prediction of whole-body movements. We will define dedicated metrics to evaluate the movement ergonomic performance and intuitiveness. We will integrate those elements in a digital human simulation to plan a progressive adaptation of the robot motion accounting for the user's motor preferences. We will then use probabilistic decision-making to adapt the plan on-line to the user's motor adaptation capabilities. This will enable a smooth deployment of collaborative robots at work.

10.3.6 ANR : EpiRL

Participants: Olivier Buffet.

• Program:
  ANR
• Project title:
  Apprentissage par renforcement épistémique
• Duration:
  February 2023 – February 2027
• Coordinator:
  François Schwarzentruber (IRISA, École normale supérieure de Rennes)
• Abstract:

  EpiRL project aims at investigating the combination of epistemic planning and reinforcement learning (RL), by proposing new algorithms that are efficient, adaptive, and capable of computing decisions relying on theory of knowledge and belief. We expect from this approach an efficiency in the generation of epistemic plans, while decisions made by RL algorithms will be explainable. Moreover, the algorithms of EpiRL will be tested and evaluated within a real application that exploits autonomous agents.

  The project will address the weaknesses of both epistemic planning and RL: on the one hand, existing epistemic planning algorithms are costly, do not adapt to the environment, and concepts are hand-crafted and are not learned; on the other hand, in reinforcement learning, agents adapt to their environments but are unable to reason about beliefs of other agents. The newly developed algorithms will combine the strengths of both fields.

  We propose four workpackages:

  1. Study representations of states
  2. Develop RL algorithms
  3. Study representations of policies
  4. Validating our algorithms with our industrial partner DAVI. In particular, we aim at developing a debunking chatbot whose use case will apply to raising awareness about environmental issues.

10.3.7 ANR: BUCOLYC

Participants: Jean-Baptiste Mouret, Thomas Martin.

• Program:
  ANR
• Project acronym:
  BUCOLYC
• Project title:
  Papillons et drones en conditions de vol confiné : aérodynamique, biomimétisme et IA au service du contrôle et de la stabilisation
• Duration:
  Sept. 2023 – Aug. 2027
• Coordinator:
  Mickaël Bourgoin (Laboratoire de Physique de l'ENS Lyon)
• Local coordinator:
  Jean-Baptiste Mouret
• Abstract:

  While drone technology has matured for open-air flight, confined flight remains a major challenge, due to the aerodynamic interference induced by the complex couplings between the drone itself and the surrounding walls, which cause severe flight disturbances. This renders the usual UAV stabilization controls inoperative, and considerably reduces maneuverability. Our project aims to address this challenge by combining aerodynamic, biomimetic and machine learning approaches to improve UAV control and stability in confined, near-wall environments.

  To achieve this ambitious goal, our multidisciplinary consortium brings together experts in robotics and biorobotics, fluid mechanics and entomologists, as well as an industrial partner (XTim) recognized for its leadership in the market for biomimetic flapping-wing drones.

10.3.8 COMS@N: EXOCODESIM

Participants: Serena Ivaldi, Pauline Maurice.

• Program:
  COMS@N Appel à Pre-Maturation
• Project acronym:
  EXOCODESIM
• Project title:
  Exoskeleton Co-design by Simulation
• Duration:
  Octobre 2024 – Septembre 2025
• Coordinator:
  Serena Ivaldi
• Local coordinator:
  Serena Ivaldi
• Abstract:
  Suite aux projet ExoTurn et ExoSim, nous souhiatons developper nos propres solutions exosquelettes à destination du CHRU de Nancy/ Cette demande de co-financement permettra de financer le co-développement de prototypes d'exosquelettes, validés par les outils de simulation devéloppées dans l'équipe, ainsi que par des tests utilisateurs sur site répondant aux objectifs d’une médecine 5P. Les résultats de ce projet ont vocation a être transferés vers une startup liée à l'équipe, qui serait porté par Raphael Bousigues et Raphael Lartot .

10.3.9 AID: ATOR (Assisted TeleOeration of Robots)

Participants: Jean-Baptiste Mouret, Serena Ivaldi.

• Program:
  Inria-AID convention (Agence Innovation Defense)
• Project acronym:
  ATOR
• Project title:
  Assisted TeleOeration of Robots
• Duration:
  01/01/2024 – 31/12/2028
• Coordinator:
  Jean-Baptiste Mouret
• Local coordinator:
  Jean-Baptiste Mouret
• Abstract:
  The ATOR project aims at leveraging artificial intelligence algorithms to make it easier to teleoperate robots (typically mobile manipualtors). The main idea is to exploit a dataset of expert demonstrations to guide the hand of a non-expert, helping to understand in real-time “what would an expert do in that situation”. The project will propose novel, uncertainty-aware trajectory prediction algorithms, as well as demonstrations with the robots of the team.

10.4.1 LUE: EXOSIM

Participants: Serena Ivaldi, Pauline Maurice.

• Program:
  LUE
• Project acronym:
  EXOSIM
• Project title:
  Simulation de tâches pénibles couramment réalisées en milieu hospitalier pour guider la recherche automatique de solutions exosquelettes pour assister les soignants
• Duration:
  July 2024 – June 2026
• Coordinator:
  Serena Ivaldi
• Local coordinator:
  Serena Ivaldi
• Abstract:
  Suite aux projet ExoTurn et ExoCare coordonnés par les deux porteuses de ce projet, nous souhaitons pérenniser la collaboration entre Loria et CHRU de Nancy sur l’utilisation d’outils numériques pour aider l’introduction, expérimentation et mise en œuvre d’exosquelettes dans le milieu sanitaire. Dans ce projet, nous souhaitons développer un nouveau pro- gramme de développement d’outils numériques pour 1) aider l’hôpital à identifier les exos- quelettes existants qui seraient potentiellement pertinents pour aider les soignants , et à défaut déterminer le cahier de charge d’un nouveau exosquelette à acquérir , à travers un logiciel de simulation physique de l’humain virtuel et d’évaluation ergonomique développé par le Loria ; 2) faire valider le logiciel par les ergonomes du CHRU de Nancy, ainsi que le choix du dispositif ; 3) doter l’hôpital d’instruments numériques intégrant évaluation subjec- tive (par questionnaires) et objective (par capteurs portés) pour suivre la campagne expéri- mentale de test des exosquelettes sur le court/moyen/longue terme, en utilisant ces don- nées pour guider le processus d’adoption de l’exosquelette.

General chair, scientific chair

• Serena Ivaldi was general chair of the IEEE-RAS Conference on Humanoid Robots (Humanoids) – more than 700 individual registrations
• Serena Ivaldi was the main Organizer of the euROBIN “Coopetition” – about 150 participants from all Europe, in 3 competition leagues
• Jean-Baptiste Mouret was co-chair of the Evolutionary Machine Learning track of the ACM Genetic and Evolutionary Conference (GECCO) – about 100 submissions to the track

11.1.1 Scientific events: organisation

11.1.2 Scientific events: selection

11.1.3 Invited talks

• Jean-Baptiste Mouret was invited to the French-German-Japanese symposium “Generative AI: Pathways to democratization, transparency and sustainability” (Tokyo, Japan)
• Pauline Maurice gave an invited talk in 2 French laboratories: LAAS-CNRS (robotics, Toulouse) and LBMC (biomechanics, Lyon)
• Enrico Mingo Hoffman was invited to the Workshop on Real World Physical and Social Human-Robot Interaction held at IEEE-RAS HUMANOIDS 2024 (Nancy, France), JNRH 2024 (Nancy, France), Workshop on Human Movement Understanding, Whole-Body Control, and Human-Robot Interfaces held at IEEE CASE 2024 (Bari, Italy, online), Workshop Advancements in High Performance Humanoid & Legged Robot Functionalities held at ERF 2024 (Rimini, Italy)
• Serena Ivaldi was invited to give presentations at the Club ORION of University of Lorraine, the ICRA 2024 Workshops on Human Modeling and PHRI, the ICRA 2024 Workshop on Teleoperation, the CORL 2024 Workshop on Whole-body Control and Bimanual Manipulation.

11.1.4 Leadership within the scientific community

• Enrico Mingo Hoffman is serving as Corresponding Chair and representative for the primary region of Europe for the IEEE Technical Committee on Whole-Body Control (TC-WBC), with responsibility for the TC-WBC funds' management.
• Pauline Maurice is a co-chair of the technical committee on “Humans and Robots” of the French GdR Robotique.
• Serena Ivaldi is Vice-President of the Members Activities Board of the IEEE Robotics & Automation Society and member of the IEEE RAS HUMANOIDS Steering Committee.
• Serena Ivaldi participated to the writing of the SRA (Strategic Research Agenda) of the euROBIN Network of Excellence in Robotics & AI, a strategic document for research in robotics and AI for the European Commission.

11.1.5 Research administration

• Jean-Baptiste Mouret is Head of Science (Délégué Scientifique) of the Inria Center at Université de Lorraine (since March 1st, 2024)
• Amine Boumaza is member of the Comité de Centre of Inria Centre at Université de Lorraine.
• Francis Colas is member of the Comité de Centre and Comipers committees of Inria Centre at Université de Lorraine as well as the ComiDoc PhD hiring commission of the Loria laboratory.
• Serena Ivaldi was Member of Bureau de Comité de Projets of the Inria Center at Université de Lorraine until 03/2024.

11.2.1 Teaching

• Master: Vincent Thomas is co-responsible for the parcours “Intelligence Artificielle et ses Applications en Vision et Robotique” of the Computer Science Master, Univ. Lorraine and co-conducted the evolution of this parcours for the new training offer of Univ. Lorraine.

• Master: Amine Boumaza , “Méta-heuristiques et recherche locale stochastique”, 30h eq. TD, M1 informatique, Univ. Lorraine, France.
• Master: Amine Boumaza , “Modélisation de Phénomènes Biologiques ”, 12h eq. TD, M2 Sciences Cognitives IACH, Univ. Lorraine, France.
• Master: Amine Boumaza , “Robotique collective”, 24h eq. TD, M2 Informatique IA²VR, Univ. Lorraine.
• Tutorial: Olivier Buffet , “Planification dans l'incertain”, 2h CM, CNRS Formation Entreprise.
• Master: Francis Colas , “Planification de trajectoires”, 17h eq. TD, M2 Informatique “Intelligence Artificielle et ses Applications en Vision et Robotique”, Univ. Lorraine, France.
• Master: Francis Colas , “Ingénierie Logicielle pour l'Intelligence Artificielle et la Robotique”, 15h eq. TD, M2 Informatique “Intelligence Artificielle et ses Applications en Vision et Robotique”, Univ. Lorraine, France.
• Master: Francis Colas , “Situation Intégratrice”, 36h eq. TD, M2 Informatique “Intelligence Artificielle et ses Applications en Vision et Robotique”, Univ. Lorraine, France.
• Master: Serena Ivaldi , “Analyse Comportementale”, 16h CM/TD, M2 “Sciences Cognitives”, Univ. Lorraine, France.
• Master: Pauline Maurice , “Analyse Comportementale”, 16h CM/TP, M2 “Sciences Cognitives”, Univ. Lorraine, France.
• Master: Pauline Maurice , “Robotic assistive devices for occupational applications: From research to deployment”, 6h CM/TP, 3rd year (M2) in “Control Engineering”, Centrale-Supelec, France.
• Master: Pauline Maurice , “Human motion analysis for human-robot interaction”, 6h CM, M2 Robotics and Biomechanics (joint class), Univ. of Lyon, France.
• Master: Jean-Baptiste Mouret , “Quality Diversity and Creative Design”, 3h (M2 Innovation, Mines Paristech)
• Master: Alexis Scheuer , “Introduction à la robotique autonome”, 30h eq. TD, M1 informatique, Univ. Lorraine, France.
• Master: Alexis Scheuer , “Modélisation et commande en robotique”, 16h eq. TD, M2 “Apprentissage, Vision, Robotique”, Univ. Lorraine, France.
• Master: Alexis Scheuer , “Éléments de robotique”, 4h eq. TD, Master MEEF 2d degré, INSPÉ, Univ. Lorraine, France.
• Master: Vincent Thomas , “Apprentissage et raisonnement dans l'incertain”, 15h eq. TD, M2 M2 “Apprentissage, Vision, Robotique”, Univ. Lorraine, France.
• Master: Vincent Thomas , “Planification Apprentissage et Controle pour la Robotique”, 15h eq. TD, M2 M2 “Intelligence Artificielle et ses Applications en Vision et Robotique”, Univ. Lorraine, France.
• Master: Vincent Thomas , “Game Design”, 30h eq. TD, M1 Sciences Cognitives, Univ. Lorraine, France.
• Master: Vincent Thomas , “Agent intelligent”, 15h eq. TD, M1 Sciences Cognitives, Univ. Lorraine, France.

11.2.2 Supervision

• PhD: Timothée Anne , “L'optimisation multi-tâche et ses applications à la robotique : d'abord résoudre, ensuite généraliser', started in September 2020, defended 2024-06-06, Jean-Baptiste Mouret (advisor) 32.
• PhD: Jacques Zhong , “Prise en compte de la variabilité morphologique d'opérateurs sur des chaines de montage en réalité virtuelle”', started in October 2020, defended 2024-06-25, Francis Colas (advisor), Pauline Maurice (co-advisor), and Vincent Weistroffer (co-advisor, CEA-LIST) 34.
• PhD: Abir Bouaouda , “Apprentissage par renforcement pour le contrôle des robots parallèles à câbles”', started in October 2020, defended on 2024-12-13, Mohamed Boutayeb (advisor, CRAN), Dominique Martinez (co-advisor).
• PhD: Nima Mehdi , “Approches probabilistes pour la perception et l'interprétation de l'activité humaine”', started in May 2020, defended on 2024-12-17, Francis Colas (advisor), Serena Ivaldi (co-advisor), and Vincent Thomas (co-advisor).
• PhD in progress: Aya Yaacoub , “User-specific planning of a collaborative robot behavior to help prevent musculoskeletal disorders”, started in December 2021, Francis Colas (advisor), Pauline Maurice (co-advisor), Vincent Thomas (co-advisor), ROOIBOS project.
• PhD in progress: Alexandre Oliveira Souza , “Intelligence Artificielle et contrôle de systèmes interactifs : Application aux exosquelettes”, started in May 2022, François Charpillet ( advisor), Pauline Maurice (co-advisor), Serena Ivaldi (co-advisor), CIFRE with Safran.
• PhD in progress Salomé Lepers , “Explicabilité et interprétabilité en planification probabiliste”, started in October 2022, Olivier Buffet (advisor), Vincent Thomas (co-advisor).
• PhD in progress: Dionis Totsila , “Learning Bimanual robot skills from human demonstrations and natural language”', started in November 2023, Serena Ivaldi (advisor) and Jean-Baptiste Mouret (co-advisor), euROBIN project.
• PhD in progress: Thomas Martin , “Utilisation de l'apprentissage automatique pour le vol de drones en milieu très confiné”, started in January 2024, Jean-Baptiste Mouret (advisor) and Thibaut Rahajiraona (co-avisor)
• PhD in progress: Konstantinos Tsakonas , “Intelligence artificielle pour la prédiction de trajectoires en robotique téléopérée”, started in October 2024, Serena Ivaldi (advisor) and Jean-Baptiste Mouret (co-advisor)
• PhD in progress: Ioannis Tsikelis , “Model-base and learning methods for whole-body motion planning and control” (tentative) started in October 2024, Serena Ivaldi (advisor) and Enrico Mingo Hoffman (co-advisor)
• PhD in progress: Raphael Lorenzo , “Multimodal prediction of human intention for human-robot collaboration”, started in October 2024, Serena Ivaldi (advisor) and Bertrand Luvison (co-advisor)
• PhD in progress: Raphaël Boige , "Algorithmes de recherche dans les arbres : au-delà de Monte-Carlo Tree Search", started in November 2024, Bruno Scherrer (advisor) and Amine Boumaza (co-advisor)
• PhD in progress: Mathis Antonetti , “Diffusion pour l'apprentissage de politiques de manipulation en robotique”, started in December 2024, Serena Ivaldi (advisor) and Jean-Baptiste Mouret (co-advisor)

11.2.3 Juries

• Jean-Baptiste Mouret was :
  • President of the jury of the PhD of Quentin Le Lidec (Paris Sciences Lettres / Willow)
  • Reviewer of the PhD of Côme Perrot (INSA Toulouse / LAAS)
  • Reviewer of the Phd of Valetin Macé (Sorbonne Université / ISIR)
• Pauline Maurice was :
  • Examinator of the PhD of Océane Dubois (ISIR / Sorbonne Université)
  • Examinator of the PhD of Arthur Favennec (DevAH / Université de Lorraine)
  • Examinator of the PhD of Erwan Landais (Inria Bordeaux / Université de Bordeaux)
  • Examinator of the PhD of Bianca Lento (INCIA / Université de Bordeaux)
  • Examinator of the PhD of Anna Bucchieri (Politecnico di Milano, Italy)
• Serena Ivaldi was:
  • President of the jury of PhD of Sewade Olaolu Ogun (Université de Lorraine)
  • Reviewer of the PhD of Jianling Zou (Université Paris 8)
  • Examiner of the PhD of Lucas Quesada (Université Paris Saclay)
  • Examiner of the PhD of Anand Ballou (Université Grenoble Alpes)
  • Examiner of the HDR of Stéphane Caron (ENS & Sorbonne Université)
  • Member of the Jury of Selection of Chargé de Recherche & ISFP at Centre Inria de l'Université de Lorraine (jury NGE-CRCN-2024)
  • Examiner for the Academic Senate of Scuola Superiore Sant'Anna for the Promotion to Associate Professor of Assistant Professor Dr. Marco Controzzi
  • Member of Comité de Suivi de Thèse of Clelie Amiot (Université de Lorraine), Augustin Chartouny (Sorbonne Université), Alessia Fusco (Université Paul Sabatier III), Sebastien Muraccioli (Université de Montpellier)

11.3.1 Specific official responsibilities in science outreach structures

• Amine Boumaza is a member of the editorial board of Interstices.

11.3.2 Productions (articles, videos, podcasts, serious games, ...)

• As a phd student, Aya Yaacoub participated in a formation on popularization and, in particular, fiction. This led to a publication in a book collection 45.
• Serena Ivaldi and Jean-Baptiste Mouret produced a leaflet (4 pages) about robotics for the general public, distributed at the Semaine de la Robotique 44.
• Serena Ivaldi , Jean-Baptiste Mouret and Anna Bucchieri translated the robotics activities sheets of IEEE Robots Guide from English to Italian and French.

11.3.3 Participation in Live events

• Serena Ivaldi organized (with the help of the communication service) the outreach program of IEEE Humanoids (Friday-Sunday, November 22nd-24th 2024):
  • robotics workshop for 6-12 year old kids (building and programming a robot)
  • childcare program for the children of the conference's attendees (about 10 children, 3-12 year old)
  • robotics workshop for high-school students (robot soccer / robocup)
  • robotics workshop for university students (Nao humanoid robots with ChatGPT)
  • visit of the exhibition part of the conference (robot demonstrations, humanoid competition, ...)
  • general audience conference by Christian Duriez (Inria, Lille) about soft robot
  • also involved: Jean-Baptiste Mouret , Anna Bucchieri , Ioannis Tsikelis , Alexandre Oliveira Souza , Fabio Amadio , Clemente Donoso , Raphael Lorenzo , Raphael Lartot , Raphael Bousigues , Nima Mehdi , Alexis Biver , Dionis Totsila , Konstantinos Tsakonas , Olivier Rochel , Manon Cordone
  • Total: about 900 visitors
• Serena Ivaldi organized (with the help of the communication service) the outreach program of the euROBIN coopetition (Monday-Thursday, November 25nd-28th 2024), focused on schools (6-12 year old):
  • visit of the competition area, with the robots of the euROBIN coopetition
  • robotic workshops
  • scientific play about artificial intelligence for high-school students
  • Total: about 700 visitors
  • also involved: Jean-Baptiste Mouret
• Serena Ivaldi presented at the Féru des Sciences (Nancy) on September 21 in the context of the Journées du Matrimoine/Patrimoine.
• Alexis Scheuer participated at the "fêtes de la science" by organizing and co-animating an introductory robotics workshop for pupils.
• Vincent Thomas and Olivier Buffet participated at the "fêtes de la science" by co-animating an introductory robotics workshop for pupils.
• Vincent Thomas was a member of the organizing comittee of a Game Jam event at Université de Lorraine (June 26th-27th 2024), aimed to assist professors in designing serious games enhancing the students' learning experience.
• Vincent Thomas is a member of the organizing comittee of the pedagogy seminar "Apprendre et enseigner à l'Université de Lorraine " (planned in 2025).
• Serena Ivaldi appeared on the Italian television PrimoCanale with a "live" from the lab; she was on TF1 news on automated factories; she was live on France 3 during the news from the Centre Prouvé in Nancy during the euROBIN coopetition.

11.3.4 Other science outreach relevant activities

• Pauline Maurice gave a short conference and lab visit on occupational exoskeletons within the context of the Université de Lorraine outreach program “A votre santé” (about 15 persons).
• Enrico Mingo Hoffman was interviewed by the Science & Vie newspaper for an article entitled “Le mécha : un robot géant vite encombrant”
• Serena Ivaldi was interviewed and appeared in articles by: L'Express, Les Tablettes Lorraine, Sciences et Avenir, L'Est Republicain, La Semaine, 20 Minutes, L'Usine Nouvelle, Reuters (the interview and Reuter's article appeared then on many other media, such as Rainews – the full list is here). She was on the radio France Inter (La Tech la Premiere), Direct FM and France Bleue.

International journals

• 3 articleK.K Bouillet, S.S Lemonnier Cd, F.F Clanche and G.G Gauchard. Effects of pace on productivity and physical and mental workloads in a Human-Cobot Collaboration.International Journal of Occupational Safety and ErgonomicsJanuary 2025HALDOI
• 4 articleJ. A.Juan A. Castano, E. M.Eugenio Manuel Espuela, J. R.Jaime Ramos Rojas, E. M.Enrico Mingo Hoffman and C.Chengxu Zhou. Benchmarking Standing Stability for Bipedal Robots.IEEE Access2025, 1-1HALDOI
• 5 articleJ.Jessica Colombel, V.Vincent Thomas, F.Francis Colas and P.Pauline Maurice. Identifying human movement strategies for human-robot collaboration.Multidisciplinary Biomechanics Journal49th congress of the Société de BiomécaniqueJanuary 2025HALDOIback to text
• 6 articleK.Kris Hauser, E.Eleanor Nell Watson, J.Joonbum Bae, J.Josh Bankston, S.Sven Behnke, B.Bill Borgia, M.Manuel Catalano, S.Stefano Dafarra, J.Jan van Erp, T.Thomas Ferris, J.Jeremy Fishel, G.Guy Hoffman, S.Serena Ivaldi, F.Fumio Kanehiro, A.Abderrahmane Kheddar, G.Gaëlle Lannuzel, J. F.Jacquelyn Ford Morie, P.Patrick Naughton, S.Steve Nguyen, P.Paul Oh, T.Taskin Padir, J.Jim Pippine, J.Jaeheung Park, J.Jean Vaz, D.Daniele Pucci, P.Peter Whitney, P.Peggy Wu and D.David Locke. Analysis and Perspectives on the ANA Avatar XPRIZE Competition.International Journal of Social RoboticsJanuary 2024. In press. HALDOI
• 7 articleE. M.E. Mingo Hoffman, D.Daniel Costanzi, G.Gabriele Fadini, N.Narcis Miguel, A. D.A. Del Prete and L.Luca Marchionni. Addressing Reachability and Discrete Component Selection in Robotic Manipulator Design through Kineto-Static Bi-Level Optimization.IEEE Robotics and Automation Letters2025, 1-8HALDOIback to text
• 8 articleE. M.Enrico Mingo Hoffman, A.Arturo Laurenzi and N. G.Nikos G. Tsagarakis. The Open Stack of Tasks Library: OpenSoT: A Software Dedicated to Hierarchical Whole-Body Control of Robots Subject to Constraints.IEEE Robotics and Automation Magazine2024, 2-12HALDOIback to text
• 9 articleP.Paul Kent, A.Adam Gaier, J.-B.Jean-Baptiste Mouret and J.Juergen Branke. Bayesian Optimisation for Quality Diversity Search With Coupled Descriptor Functions.IEEE Transactions on Evolutionary Computation2024, 1-1HALDOIback to text
• 10 articleE.Enrico Mingo Hoffman, A.Andrea Curti, N.Narcis Miguel, S. K.Sai Kishor Kothakota, A.Alberto Molina, A.Adria Roig and L.Luca Marchionni. Modeling and Numerical Analysis of Kangaroo Lower Body based on Constrained Dynamics of Hybrid Serial-Parallel Floating-Base Systems.Robotics and Autonomous Systems182December 2024, 104827HALDOIback to text
• 11 articleJ.-B.Jean-Baptiste Mouret. Large language models help computer programs to evolve.Nature6257995January 2024, 452-453HALDOI
• 12 articleQ.Quentin Rouxel, S.Serena Ivaldi and J.-B.Jean-Baptiste Mouret. Multi-Contact Whole-Body Force Control for Position-Controlled Robots.IEEE Robotics and Automation Letters96May 2024, 5639-5646HALDOIback to text
• 13 articleF.Francesco Ruscelli, L.Luca Rossini, E.Enrico Mingo Hoffman, L.Lorenzo Baccelliere, A.Arturo Laurenzi, L.Luca Muratore, D.Davide Antonucci, S.Stefano Cordasco and N. G.Nikos G. Tsagarakis. Design and Control of the Humanoid Robot COMAN+: Hardware Capabilities and Software Implementations.IEEE Robotics and Automation Magazine2024, 2-13HALDOI
• 14 articleA.Andrea Testa, M.Marco Laghi, E. D.Edoardo Del Bianco, G.Gennaro Raiola, E. M.Enrico Mingo Hoffman and A.Arash Ajoudani. A Stable Method for Task Priority Adaptation in Quadratic Programming via Reinforcement Learning.Robotics and Computer-Integrated Manufacturing91February 2025, 102857HALDOI
• 15 articleD.Dionis Totsila, K.Konstantinos Chatzilygeroudis, V.Valerio Modugno, D.Denis Hadjivelichkov and D.Dimitrios Kanoulas. Sensorimotor Learning With Stability Guarantees via Autonomous Neural Dynamic Policies.IEEE Robotics and Automation Letters102February 2025, 1760-1767HALDOI
• 16 articleL.Lorenzo Vianello, S.Serena Ivaldi, A.Alexis Aubry and L.Luka Peternel. The effects of role transitions and adaptation in human-cobot collaboration.Journal of Intelligent Manufacturing35June 2024, 2005-2019HALDOI

International peer-reviewed conferences

• 17 inproceedingsT.Timothée Anne and J.-B.Jean-Baptiste Mouret. Parametric-Task MAP-Elites.Proceedings of the Genetic and Evolutionary Computation Conference (GECCO)GECCO 2024Melbourne, AustraliaACM2024HALDOIback to text
• 18 inproceedingsA.Amine Boumaza. Exploring Affordances in Open-Ended Online Collective Robotics.Proceedings of the 2024 Artificial Life ConferenceCopenhagen, DenmarkMIT PressJuly 2024, 317-325HALDOIback to text
• 19 inproceedingsJ.Jessica Colombel, V.Vincent Thomas, F.Francis Colas and P.Pauline Maurice. Identifying human movement strategies for human-robot collaboration.Multidisciplinary Biomechanics Journal49ème congrès de la Société de BiomécaniqueCompiègne, FranceOctober 2024HALback to text
• 20 inproceedingsV.Véronique Cortier, P.Pierrick Gaudry, A.Anselme Goetschmann and S.Sophie Lemonnier. Belenios with cast-as-intended: towards a usable interface.SpringerEVote-ID 2024 - 9th International Joint Conference on Electronic VotingTerragona, SpainSpringerOctober 2024HAL
• 21 inproceedingsT.Thomas Martin, J. R.Jefferson Roman Blanco, J.-B.Jean-Baptiste Mouret and T.Thibaut Raharijaona. Compact docking station for sub-150g UAV indoor precise landing.2024 International Conference on Unmanned Aircraft Systems (ICUAS) : 4-7 June 20242024 International Conference on Unmanned Aircraft Systems (ICUAS 2024)Chania - Crete, GreeceIEEEJune 2024, 1267-1274HALDOI
• 22 inproceedingsS.Shuwa Miura, O.Olivier Buffet and S.Shlomo Zilberstein. Approximation Algorithms for Observer Aware MDPs.Proceedings of the 40th Conference on Uncertainty in Artificial Intelligence (UAI)40th Conference on Uncertainty in Artificial Intelligence (UAI)Barcelone, SpainJuly 2024HALback to text
• 23 inproceedingsA.Alexandre Oliveira Souza, J.Jordane Grenier, F.François Charpillet, S.Serena Ivaldi and P.Pauline Maurice. Enhancing Exoskeleton Transparency with Motion Prediction: An Experimental Study.IEEE-RAS International Conference on Humanoid RobotsNancy, FranceNovember 2024HALback to text
• 24 inproceedingsJ.Johan Peralez, A.Aurélien Delage, O.Olivier Buffet and J.Jilles Dibangoye. Solving Hierarchical Information-Sharing Dec-POMDPs: An Extensive-Form Game Approach.Proceedings of the 41st International Conference on Machine LearningICML 2024 - 41st International Conference on Machine Learning235Proceedings of Machine Learning ResearchVienne, Austria2024, 63010HALback to text
• 25 inproceedingsQ.Quentin Rouxel, A.Andrea Ferrari, S.Serena Ivaldi and J.-B.Jean-Baptiste Mouret. Flow Matching Imitation Learning for Multi-Support Manipulation.2024 IEEE-RAS 23rd International Conference on Humanoid Robots (Humanoids)Nancy, FranceJuly 2024HALback to text
• 26 inproceedingsD.Dionis Totsila, Q.Quentin Rouxel, J.-B.Jean-Baptiste Mouret and S.Serena Ivaldi. Words2Contact: Identifying Support Contacts from Verbal Instructions Using Foundation Models.2024 IEEE-RAS 23rd International Conference on Humanoid Robots (Humanoids)Nancy, FranceIEEENovember 2024, 9-16HALDOIback to text
• 27 inproceedingsA.Aya Yaacoub, V.Vincent Thomas, F.Francis Colas and P.Pauline Maurice. Fatigue Mitigation through Planning in Human-Robot Repetitive Co-Manipulation: Automatic Extraction of Relevant Action Sets.2024 IEEE-RAS 23rd International Conference on Humanoid Robots (Humanoids)2024 IEEE-RAS 23rd International Conference on Humanoid Robots (Humanoids)Nancy, FranceIEEENovember 2024, 795-802HALDOIback to text
• 28 inproceedingsY.Yang You, V.Vincent Thomas, F.Francis Colas, R.Robert Skilton and O.Olivier Buffet. Online Robust Robot Planning for Human-Robot Collaboration.Lecture Notes in Artificial IntelligenceTAROS 2024 - 25th Toward Autonomous Robotic Systems Conference15052Lecture Notes in Computer ScienceLondres, United KingdomSpringer Nature SwitzerlandDecember 2025, 11HALDOIback to text

National peer-reviewed Conferences

• 29 inproceedingsS.Salomé Lepers, V.Vincent Thomas and O.Olivier Buffet. Un cadre pour la planification consciente d'un observateur sous observabilité partielle.Actes des 18es Journées d’Intelligence Artificielle Fondamentale et des 19es Journées Francophones sur laPlanification, la Décision et l’Apprentissage pour la conduite de systèmes18es Journées d’Intelligence Artificielle Fondamentale et 19es Journées Francophones sur la Planification, la Décision et l’Apprentissage pour la conduite de systèmesLa Rochelle, FranceJune 2024HALback to text

Conferences without proceedings

• 30 inproceedings S.Sophie Lemonnier, K.Kévin Bouillet, E.Elissa El Khalil, P.Pauline Maurice and G.Guillaume Mornieux. Travailler avec un robot collaboratif ou un exosquelette : Comment évaluer l'impact sur la santé physique et cognitive ? Journée Technique Mesures Physiologiques et Études Utilisateurs Toulouse, France September 2024 HAL
• 31 inproceedingsJ.Jonathan Savin, R.Raphaël Bousigues, P.Pauline Maurice, V.Vincent Padois, N.Nasser Rezzoug and D.David Daney. Motor variability in human-robot interaction during an assisted trajectory-tracking task: preliminary results from the MOVER experiment.Humanoids 2024 workshop - Human movement modeling for Human-Robot interactionNancy, FranceNovember 2024HAL

Doctoral dissertations and habilitation theses

• 32 thesisT.Timothee Anne. Multi-task optimization and its application to robotics : first solve, then generalize.Université de LorraineJune 2024HALback to text
• 33 thesisA.Aurélien Delage. Theoretical foundations for planning in partially observable stochastic games.INSA de LyonJune 2024HALback to text
• 34 thesisJ.Jacques Zhong. Assessing the variability of operators' morphology for assembly tasks using virtual reality.Université de LorraineJune 2024HALback to text

Reports & preprints

• 35 miscF.Fabio Amadio, C.Clemente Donoso, D.Dionis Totsila, R.Raphael Lorenzo, Q.Quentin Rouxel, O.Olivier Rochel, E.Enrico Mingo Hoffman, J.-B.Jean-Baptiste Mouret and S.Serena Ivaldi. From Vocal Instructions to Household Tasks: The Inria Tiago++ in the euROBIN Service Robots Coopetition.2024HALDOI
• 36 miscJ.Jonathan Ferrer-Mestres, T.Thomas Dietterich, O.Olivier Buffet and I.Iadine Chadès. Interpretable Solutions for Stochastic Dynamic Programming.August 2024HALDOIback to text
• 37 miscS.Salomé Lepers, S.Sophie Lemonnier, V.Vincent Thomas and O.Olivier Buffet. How to Exhibit More Predictable Behaviors.October 2024HALback to text
• 38 miscT.Thomas Martin, A.Adrien Guénard, V.Vladislav Tempez, L.Lucien Renaud, T.Thibaut Raharijaona, F.Franck Ruffier and J.- . B.Jean- Baptiste Mouret. Flying in air ducts.October 2024HAL
• 39 miscE.Enrico Mingo Hoffman, A.Antonio Paolillo, J.-B.Jean-Baptiste Mouret and S.Serena Ivaldi. Whole-Body Motion Control in Orbital Scenarios through Centroidal Momentum Conservation.June 2024HAL

Other scientific publications

• 40 inproceedingsE.Elissa El Khalil, S.Sophie Lemonnier and P.Pauline Maurice. Effect of Induced Postural Changes on Cognitive Load.European Conference on Cognitive ErgonomicsParis, France2024HALback to text
• 41 miscE.Enrico Mingo Hoffman. OpenSoT: a Software Tool for Advanced Whole-Body Control.September 2024HAL
• 42 miscQ.Quentin Rouxel, S.Serena Ivaldi and J.-B.Jean-Baptiste Mouret. Supplementary Material: Multi-Contact Whole-Body Force Control for Position-Controlled Robots.INRIA Nancy, équipe LARSENApril 2024HAL
• 43 inproceedingsA.Aya Yaacoub, V.Vincent Thomas, F.Francis Colas and P.Pauline Maurice. Fatigue Mitigation in Human-Robot Repetitive Co-Manipulation: A Planning-Friendly Discretization of The Continuous Action Space.IEEE ICRA 2024 Workshop on Innovations and Applications of Human Modelling in Physical Human-Robot InteractionYokohama, JapanMay 2024HALback to text

Scientific popularization

• 44 miscJ.-B.Jean-Baptiste Mouret and S.Serena Ivaldi. La robotique.Nancy, FranceNovember 2025HALback to text
• 45 inbookA.Athénaïs Vaginay, A.Aya Yaacoub, P.Philippe Flores and A.Aman Sinha. THESEUS WRECK.THINK BEFORE LOADING2024HALback to text