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Section: New Results
Shared Control Architectures
Shared Control for Remote Manipulation
Participants : Firas Abi Farraj, Paolo Robuffo Giordano, Claudio Pacchierotti, Rahaf Rahal, Mario Selvaggio.
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. For this reason, researchers started to devise innovative approaches to make the control of such systems more effective and intuitive. In this respect, shared control algorithms have been investigated as one the main tools to design complex but intuitive robotic teleoperation system, helping operators in carrying out several increasingly difficult robotic applications, such as assisted vehicle navigation, surgical robotics, brain-computer interface manipulation, rehabilitation. This approach makes it possible to share the available degrees of freedom of the robotic system between the operator and an autonomous controller. The human operator is in charge of imparting high level, intuitive goals to the robotic system; while the autonomous controller translates them into inputs the robotic system can understand. How to implement such division of roles between the human operator and the autonomous controller highly depends on the task, robotic system, and application. Haptic feedback and guidance have been shown to play a significant and promising role in shared control applications. For example, haptic cues can provide the user with information about what the autonomous controller is doing or is planning to do; or haptic force can be used to gradually limit the degrees of freedom available to the human operator, according to the difficulty of the task or the experience of the user. The dynamic nature of haptic guidance enables us to design very flexible robotic system, which can easily and rapidly change the division of roles between the user and autonomous controller.
Along this general line of research, we worked at different approaches:
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We proposed novel haptic guidance methods for a dual-arm telerobotic manipulation system [36] which are able to deal with several different constraints, such as collisions, joint limits, and singularities. We combined the haptic guidance with shared-control algorithms for autonomous orientation control and collision avoidance meant to further simplify the execution of grasping tasks. In addition, a human subject study was carried out to assess the effectiveness and applicability of the proposed control approaches both in simulated and real scenarios. Results showed that the proposed haptic-enabled shared-control methods significantly improve the performance of grasping tasks with respect to the use of classic teleoperation with neither haptic guidance nor shared control. Live demos of some of these approaches have been shown to the general public at the Maker Faire 2018 in Rome.
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In the framework of the RoMANS H2020 project, we worked together with CEA to implement an intuitive and effective shared-control teleoperation system with haptic feedback using the CEA robotic hand at the slave side and the Haption glove at the master side. The system was tested at CEA in an object grasping, manipulation, and sorting scenario. A video of the experiment is available at: https://youtu.be/M-tpVP9Fakc.
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Finally, in [38] we reported the results of a collaborative project involving LAAS-CNRS as leader, where we implemented an aerial-ground comanipulator system, denoted Tele-MAGMaS, where a fixed-based manipulator arm cooperates with a UAV equipped with an onboard gripper for carrying together (and manipulating) a long bar. The system has been demonstrated live during the Hannover Fair in 2017.
Shared Control for Mobile Robot Navigation
Participant : Paolo Robuffo Giordano.
Besides manipulators, we also considered shared control algorithms for mobile robot navigation. In [25], we have presented (and experimentally validated) an online trajectory planning approach that allows a human operator to act on the trajectory to be tracked by a mobile robot (a quadrotor UAV in the experiments) in conjunction with the robot autonomy which can locally modify the planned trajectory for avoiding obstacles of staying close to points of interest. This “shared planning approach” is quite general and its application to other robotic systems is under investigation.
Shared Control of a Wheelchair for Navigation Assistance
Participants : Louise Devigne, Marie Babel.
Power wheelchairs allow people with motor disabilities to have more mobility and independence. However, driving safely such a vehicle is a daily challenge particularly in urban environments while encountering negative obstacles, dealing with uneven grounds, etc. Indeed, differences of elevation have been reported to be one of the most challenging environmental barrier to negotiate while driving a wheelchair with tipping and falling being is the most common accidents power wheelchair users encounter. It is thus our actual challenge to design assistive solutions for power wheelchair navigation in order to improve safety while navigating in such environments. To this aim, we proposed a first shared-control algorithm which provides assistance while navigating with a wheelchair in an environment consisting of negative obstacles [80].
Wheelchair Kinematics and Dynamics Modeling for Shared Control
Participants : Aline Baudry, Marie Babel.
The driving experience of an electric powered wheelchair can be disturbed by the dynamic and kinematic effects of the passive caster wheels, particularly during maneuvers in narrow rooms and direction changes. In order to prevent their nasty behaviour, we proposed a caster wheel behavior model based on experimental measurements. The study has been realised for the three existing types of wheelchair, which present different kinematic behaviors, i.e. front caster type, rear caster type and mid-wheel drive. The orientation of the caster wheels has been measured experimentally for different initial orientations, velocities and user mass, according to a predefined experimental design. The repeatability of the motions has been studied, and from these measurements, their behavior has been modeled. By using this model with the wheelchair kinematic expressions, we were able to calculate the real trajectory of the wheelchair to enhance an existing driving assistance for powered wheelchair [79].
Wheelchair Autonomous Navigation for Fall Prevention
Participants : Solenne Fortun, Marie Babel.
The Prisme project (see Section 9.1.7) is devoted to fall prevention and detection of inpatients with disabilities. For wheelchair users, falls typically occur during transfer between the bed and the wheelchair and are mainly due to a bad positioning of the wheelchair. In this context, the Prisme project addresses both fall prevention and detection issues by means of a collaborative sensing framework. Ultrasonic sensors are embedded onto both a robotized wheelchair and a medical bed. The measured signals are used to detect fall and to automatically drive the wheelchair near the bed at an optimal position determined by occupational therapists. This year, we designed the related control framework based on sensor-based servoing principles and validated it in simulation. Next step will consist in realizing tests within the Rehabilitation Center of Pôle Saint Hélier.
Robot-Human Interactions during Locomotion
Participants : Julien Legros, Javad Amirian, Fabien Grzeskowiak, Ceilidh Hoffmann, Marie Babel, Jean Bernard Hayet, Julien Pettré.
This research activity is dedicated to the design of robot navigation techniques to make them capable of safely moving through a crowd of people. We are following two main research paths. The first one is dedicated to the prediction of crowd motion based on the state of the crowd as sensed by a robot. The second one is dedicated to the creation of a virtual reality platform that enables robots and humans to share a common virtual space where robot control techniques can be tested with no physical risk of harming people, as they remain separated in the physical space. We are currently developing these ideas, which should bring good results in the near future.