Brain-machine interfacing control of whole-body humanoid motion

Karim Bouyarmane 1 Joris Vaillant 2 Norikazu Sugimoto 3 François Keith 2 Jun-Ichiro Furukawa 1, 4 Jun Morimoto 1
1 ATR Computational Neuroscience Lab
2 IDH - Interactive Digital Humans
LIRMM - Laboratoire d'Informatique de Robotique et de Microélectronique de Montpellier
3 BMI - Department of Brain Machine Interface
4 Osaka University [Osaka]
Abstract : We propose to tackle in this paper the problem of controlling whole-body humanoid robot behavior through non-invasive brain-machine interfacing (BMI), motivated by the perspective of mapping human motor control strategies to human-like mechanical avatar. Our solution is based on the adequate reduction of the controllable dimensionality of a high-DOF humanoid motion in line with the state-of-the-art possibilities of non-invasive BMI technologies, leaving the complement subspace part of the motion to be planned and executed by an autonomous humanoid whole-body motion planning and control framework. The results are shown in full physics-based simulation of a 36-degree-of-freedom humanoid motion controlled by a user through EEG-extracted brain signals generated with motor imagery task.
Keywords : motion planning semi-autonomous humanoid contact support planning motor imagery brain-machine interfacing humanoid whole-body control
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Karim Bouyarmane, Joris Vaillant, Norikazu Sugimoto, François Keith, Jun-Ichiro Furukawa, et al.. Brain-machine interfacing control of whole-body humanoid motion. Frontiers in Systems Neuroscience, Frontiers, 2014, 8 (138), pp.001-010. ⟨10.3389/fnsys.2014.00138⟩. ⟨lirmm-01057294⟩

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