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Herve Audrerr

dblp:226/6280 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2018
—ORCID · none

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

Artificial intelligence and machine learning · 1Systems, architecture and hardware · 1

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
1 paper
Motion planning and robot control · 88% Legged, aerial and field robots · 12%

Topics — the 4 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Robotics › Motion planning and robot control › robot control
external force estimation
0.312018
Model-Based External Force/Moment Estimation for Humanoid Robots with no Torque Measurement · ICRA 2018
Robotics › Motion planning and robot control
robot control
0.312018
Model-Based External Force/Moment Estimation for Humanoid Robots with no Torque Measurement · ICRA 2018
Robotics › Legged, aerial and field robots
humanoid robot
0.112018
Model-Based External Force/Moment Estimation for Humanoid Robots with no Torque Measurement · ICRA 2018
Robotics › Motion planning and robot control › robot dynamics › contact dynamics
multicontact motion
0.112018
Model-Based External Force/Moment Estimation for Humanoid Robots with no Torque Measurement · ICRA 2018

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

sensor fusion · 0.3dynamics modeling · 0.3
YearPublicationVenuePosition
2018 Model-Based External Force/Moment Estimation for Humanoid Robots with no Torque Measurement
abstract
The dynamics of a humanoid robot cannot be correctly described independently from the external forces acting on it. These forces have to be reconstructed to enable the robot to control them or to compensate for them. Force sensors are usually used to measure these forces, but because of their cost, they are often put only on the ankle/feet and possibly the wrists. This paper addresses the issue of the estimation of external forces and moments that apply at any part of a robot without direct force measurements and without torque measurements. The sensors used are the regular force sensors and the IMUs of the robot. The method relies on a model-based estimator able to make the fusion between these sensors and the whole body dynamics. The estimator reconstructs a single state vector containing the floating-base kinematics, a filtered measurement of contact force and an additional estimation external force that we evaluate in this paper. Validation is performed on HRP-2 in a multi-contact motion.
Mehdi Benallegue, Pierre Gergondet, Herve Audrerr, Alexis Mifsud, Mitsuharu Morisawa, Florent Lamiraux, Abderrahmane Kheddar, Fumio Kanehiro
ICRA3