Brain-machine interfacing control of whole-body humanoid motion

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.
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Frontiers in Systems Neuroscience, Frontiers, 2014, 8 (138), pp.001-010. 〈http://journal.frontiersin.org/Journal/10.3389/fnsys.2014.00138/full〉. 〈10.3389/fnsys.2014.00138〉
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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. 〈http://journal.frontiersin.org/Journal/10.3389/fnsys.2014.00138/full〉. 〈10.3389/fnsys.2014.00138〉. 〈lirmm-01057294〉

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