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Mathilde Legrand

dblp:225/8942 · DBLP profile ↗
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2ranked-venue papers
1as first author
1since 2021 · last 2021
0000-0002-6873-2975ORCID · corroborated

Domains — the database's venue-derived domains; a paper can count in several

Artificial intelligence and machine learning · 2 · 1 first-author · 1 since 2021Systems, architecture and hardware · 2 · 1 first-author · 1 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Artificial intelligence
2 papers
Motion planning and robot control · 100%
Human-computer interaction and pervasive computing
2 papers
Human-robot interaction · 50% Accessibility and assistive technology · 35% Wearable and physiological sensing · 15%

Topics — the 6 heaviest of 7, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Robotics › Motion planning and robot control
robot control
0.512021
Computing the positioning error of an upper-arm robotic prosthesis from the observation of its wearer's posture · ICRA 2021
Robotics › Motion planning and robot control › robot control
feedback control
0.412020
A closed-loop and ergonomic control for prosthetic wrist rotation · ICRA 2020
Human-robot interaction › physical human-robot interaction
prosthetic control
0.412020
A closed-loop and ergonomic control for prosthetic wrist rotation · ICRA 2020
Robotics › Motion planning and robot control › redundancy resolution
posture optimization
0.112021
Computing the positioning error of an upper-arm robotic prosthesis from the observation of its wearer's posture · ICRA 2021
Accessibility and assistive technology
assistive technology
0.112021
Computing the positioning error of an upper-arm robotic prosthesis from the observation of its wearer's posture · ICRA 2021
Accessibility and assistive technology › assistive technology
robotic prosthesis
0.112021
Computing the positioning error of an upper-arm robotic prosthesis from the observation of its wearer's posture · ICRA 2021

Methods — techniques the papers use, named apart from their topics

postural score optimization · 1.0null-space optimization · 1.0compensatory movement measurement · 0.9
YearPublicationVenuePosition
2021 Computing the positioning error of an upper-arm robotic prosthesis from the observation of its wearer's posture
abstract
When the arm prosthesis worn by an amputated Human being is not adequately configured with respect to the end-effector task, body compensations are often observed. Namely, to compensate for a wrong joint positioning on the robotic distal side, a subject trying to reach a desired position/orientation of his/her hand mobilizes his/her proximal joints, thus exploiting the redundancy of the human+robot kinematic chain.In this paper, we explore the possibility of exploiting this well-known behavior to reverse the causality: if we observe the posture of an amputated subject wearing a prosthesis during a hand positioning task, to what extent can we infer the positioning error of the prosthesis?To answer this question, we make the assumption that the adequate, or natural posture for a given task is one that optimizes a postural score. The proposed approach then consists in i) measuring the joint posture of the subject fitted with the prosthesis; ii) search for an alternative posture that optimizes a postural score within the null space of the human+robot kinematic chain and iii) compute the position error for the robot joints between the initial and the optimized posture.An experimental evaluation is provided with non amputated subjects who emulate erratic positioning of their distal joints during hand positioning tasks. Results show that joint errors are estimated with a precision that seems compatible with the implementation of a real time control algorithm.
Alexis Poignant, Mathilde Legrand, Nathanaël Jarrassé, Guillaume Morel
ICRA2
2020 A closed-loop and ergonomic control for prosthetic wrist rotation
abstract
Beyond the ultimate goal of prosthetics, repairing all the capabilities of amputees, the development line of upper-limb prostheses control mainly relies on three aspects: the robustness, the intuitiveness and the reduction of mental fatigue. Many complex structures and algorithms are proposed but no one question a common open-loop nature, where the user is the one in charge of correcting errors. Yet, closing the control loop at the prosthetic level may help to improve the three main lines of research cited above. One major issue to build a closed-loop control is the definition of a reliable error signal; this paper proposes to use body compensations, naturally exhibited by prostheses users when the motion of their device is inaccurate, as such. The described control scheme measures these compensatory movements and makes the prosthesis move in order to bring back the user into an ergonomic posture. The function of the prosthesis is no longer to perform a given motion but rather to correct the posture of its user while s/he focus on performing an endpoint task. This concept was validated and compared to a standard open-loop scheme, for the control of a prosthetic wrist, with five healthy subjects completing a dedicated task with a customized transradial prosthesis. Results show that the presented closed-loop control allows for more intuitiveness and less mental burden without enhancing body compensation.
Mathilde Legrand, Nathanaël Jarrassé, Florian Richer, Guillaume Morel
ICRA1