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arXiv · 1601.04862

Scalability in Neural Control of Musculoskeletal Robots

Christoph Richter·Sören Jentzsch·Rafael Hostettler·Jesús A. Garrido·Eduardo Ros·Alois C. Knoll·Florian Röhrbein·Patrick van der Smagt·Jörg Conradt
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Abstract

Anthropomimetic robots are robots that sense, behave, interact and feel like humans. By this definition, anthropomimetic robots require human-like physical hardware and actuation, but also brain-like control and sensing. The most self-evident realization to meet those requirements would be a human-like musculoskeletal robot with a brain-like neural controller. While both musculoskeletal robotic hardware and neural control software have existed for decades, a scalable approach that could be used to build and control an anthropomimetic human-scale robot has not been demonstrated yet. Combining Myorobotics, a framework for musculoskeletal robot development, with SpiNNaker, a neuromorphic computing platform, we present the proof-of-principle of a system that can scale to dozens of neurally-controlled, physically compliant joints. At its core, it implements a closed-loop cerebellar model which provides real-time low-level neural control at minimal power consumption and maximal extensibility: higher-order (e.g., cortical) neural networks and neuromorphic sensors like silicon-retinae or -cochleae can naturally be incorporated.

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BibTeXRIS

Christoph Richter, Sören Jentzsch, Rafael Hostettler, Jesús A. Garrido, Eduardo Ros, Alois C. Knoll, Florian Röhrbein, Patrick van der Smagt, Jörg Conradt. 2016-01-19. Scalability in Neural Control of Musculoskeletal Robots. https://doi.org/10.1109/mra.2016.2535081

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