Abstract
We have been trying to induce a quadruped robot to walk dynamically on irregular terrain by using a neural system model consisting of a CPG (central pattern generator) and reflexes. In this paper, we define adaptive walking using a neural system model as “coupled-dynamics-based motion generation”, in which a neural system and a mechanical system are coupled and generate motion by interacting with the environment emergently and adaptively. In order to clarify how a CPG is coupled to a mechanical system, we use simulations to investigate the relationship between the parameters of a CPG and the dynamics of the mechanical system. We propose the essential conditions for stable dynamic walking on irregular terrain in general, and we design a neural system by comparing biological knowledge with the essential conditions described in physical terms. We report our experimental results of dynamic walking on terrains of medium degrees of irregularity using a planar quadruped robot and a newly developed three-dimensional quadruped robot. MPEG footage of these experiments can be seen at: http://www.kimura.is.uec.ac.jp.
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Kimura, H., Fukuoka, Y., Hada, Y., Takase, K. (2003). Adaptive Dynamic Walking of a Quadruped Robot on Irregular Terrain Using a Neural System Model. In: Jarvis, R.A., Zelinsky, A. (eds) Robotics Research. Springer Tracts in Advanced Robotics, vol 6. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-36460-9_10
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DOI: https://doi.org/10.1007/3-540-36460-9_10
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