Obstacle Avoidance using a Capacitive Skin for Safe Human-Robot Interaction
Kamal-Eddine M’Colo, Bruno Luong, André Crosnier, Christian Néel, Philippe Fraisse
Abstract
The paper describes a control framework using a capacitive skin for advanced and safe human-robot interactions. The skin consists of high density capacitive sensors which are able to detect objects at close distance. We propose a multitask kinematic control scheme which manages at once the control task of the end-effector and the obstacle avoidance task by using the capacitive skin measurements. To solve the multiobjective problem, a Weight-Prioritized solution based on a QP formalism is adopted. The robustness of the kinematic controller is enhanced by adding a local joint reconfiguration when the robot moves close to a singularity. Experimental results on manipulator arm equipped with the capacitive sensors are presented in realistic situations of human-robot interactions.
BibTeX
@inproceedings{iros2019_obstacleavoidanc,
title = {Obstacle Avoidance using a Capacitive Skin for Safe Human-Robot Interaction},
author = {Kamal-Eddine M’Colo and Bruno Luong and André Crosnier and Christian Néel and Philippe Fraisse},
booktitle = {IROS 2019},
year = {2019}
}