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arXiv · 2202.07064

Towards hardware Implementation of WTA for CPG-based control of a Spiking Robotic Arm

A. Linares-Barranco·E. Pinero-Fuentes·S. Canas-Moreno·A. Rios-Navarro·Maryada·Chenxi Wu·Jingyue Zhao·D. Zendrikov·G. Indiveri
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Abstract

Biological nervous systems typically perform the control of numerous degrees of freedom for example in animal limbs. Neuromorphic engineers study these systems by emulating them in hardware for a deeper understanding and its possible application to solve complex problems in engineering and robotics. Central-Pattern-Generators (CPGs) are part of neuro-controllers, typically used at their last steps to produce rhythmic patterns for limbs movement. Different patterns and gaits typically compete through winner-take-all (WTA) circuits to produce the right movements. In this work we present a WTA circuit implemented in a Spiking-Neural-Network (SNN) processor to produce such patterns for controlling a robotic arm in real-time. The robot uses spike-based proportional-integrativederivative (SPID) controllers to keep a commanded joint position from the winner population of neurons of the WTA circuit. Experiments demonstrate the feasibility of robotic control with spiking circuits following brain-inspiration.

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A. Linares-Barranco, E. Pinero-Fuentes, S. Canas-Moreno, A. Rios-Navarro, Maryada, Chenxi Wu, Jingyue Zhao, D. Zendrikov, G. Indiveri. 2022-02-14. Towards hardware Implementation of WTA for CPG-based control of a Spiking Robotic Arm. https://arxiv.org/abs/2202.07064

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