Low-Dimensional User Control of Autonomously Planned Whole-Body Humanoid Locomotion Motion Towards Brain-Computer Interface Applications

Karim Bouyarmane 1 Joris Vaillant 2, 3 Jun Morimoto 1
2 IDH - Interactive Digital Humans
LIRMM - Laboratoire d'Informatique de Robotique et de Microélectronique de Montpellier
Abstract : The goal of the presented work is to use a low-dimensional control interface to control the high-DOF whole-body locomotion motion of a humanoid robot, for instance using a 2D keyboard or joystick interface (up-down, left-right) to control a 30 DOF acyclic locomotion task (reaching a goal position by climbing on a stair). This work is motivated by the use of non-invasive BCI, which offers only such low-dimensional control signals, for low-level motion control of humanoids or exoskeletons in the assistive robotics domain of applications. The methodology is the following: given the target complex locomotion task, the humanoid autonomously plans the high-DOF motion and then executes it allowing the user to control on-line some low-dimensional features of the motion, namely way-points of the moving end-links. The approach is based on the two-stage contact-before-motion planning paradigm, which autonomously plans a sequence of transition contacts in its first stage, then executes the collision-free dynamics-consistent motion in the second stage, keeping dynamics balance of the motion. Example of this control approach is demonstrated in dynamic simulation.
Type de document :
Communication dans un congrès
CLAWAR: International Conference on Climbing and Walking Robots, Jul 2013, Sydney, Australia. 2013, 〈http://clawar2013.feit.uts.edu.au/〉
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https://hal-lirmm.ccsd.cnrs.fr/lirmm-00863928
Contributeur : François Keith <>
Soumis le : jeudi 19 septembre 2013 - 22:33:52
Dernière modification le : jeudi 11 janvier 2018 - 06:27:07

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  • HAL Id : lirmm-00863928, version 1

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Karim Bouyarmane, Joris Vaillant, Jun Morimoto. Low-Dimensional User Control of Autonomously Planned Whole-Body Humanoid Locomotion Motion Towards Brain-Computer Interface Applications. CLAWAR: International Conference on Climbing and Walking Robots, Jul 2013, Sydney, Australia. 2013, 〈http://clawar2013.feit.uts.edu.au/〉. 〈lirmm-00863928〉

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