A Novel Double-Layered Central Pattern Generator-Based Motion Controller for the Hexapod Robot

To implement the various movement control of the hexapod robot, a motion controller based on the double-layered central pattern generator (CPG) is proposed in this paper. The novel CPG network is composed of a rhythm layer and a pattern layer. The CPG neurons are constructed based on Kuramoto nonlinear oscillator. The parameters including the frequency, coupling strength, and phase difference matrix of the CPG network for four typical gaits are planned. The mapping relationship between the signals of the CPG network and the joint trajectories of the hexapod robot is designed. The co-simulations and experiments have been conducted to verify the feasibility of the proposed CPG-based controller. The actual average velocities of the wave gait, the tetrapod gait, the tripod gait, and the self-turning gait are 10.8 mm/s, 25.5 mm/s, 37.8 mm/s and 26 degrees/s, respectively. The results verify that the hexapod robot with the proposed double-layered CPG-based controller can perform stable and various movements.

Automated summary

A motion controller based on double-layered central pattern generator (CPG) is proposed to implement various movement controls of the hexapod robot in this paper. The CPG network consists of a rhythm layer and a pattern layer, with CPG neurons constructed based on Kuramoto nonlinear oscillator. Parameters for four typical gaits are planned, and the mapping relationship between CPG network signals and hexapod robot's joint trajectories is designed. Co-simulations and experiments verify the feasibility of the proposed CPG-based controller. The hexapod robot with the double-layered CPG-based controller demonstrates stable and various movements, with actual average velocities of the wave gait, tetrapod gait, tripod gait, and self-turning gait being 10.8 mm/s, 25.5 mm/s, 37.8 mm/s, and 26 degrees/s, respectively.