Abstract
Legged animals exhibit adaptive locomotion by coordinating leg movements. Biological findings suggest that such locomotion is controlled in part by an intraspinal neural network called the Central Pattern Generator (CPG), which is capable of self-organizing movement patterns between legs. In our previous study, we have proposed an unconventional CPG model that fully exploits physical interaction between legs. Experiments with quadruped robots showed that the CPG model enables the robot to reproduce various gaits without any interlimb neural connections. The purpose of this study is to verify whether or not the same CPG model would also be valid for a hexapod. To this end, we constructed a hexapod robot and conducted verification. Experimental results show that our robot can successfully self-organize stable walking pattern called metachronal wave gait in hexapod locomotion.
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