Parameter Optimization Of CPG And Its Application In Robot

Abstract

The central pattern generator (CPG) has been identified in the spinal cords as responsible for locomotion movements. It is difficult to select the appropriate values of parameters in CPG model. In this paper, the Matsuoka oscillator is selected as the rhythm-generation model and the bat algorithm is chosen to search the parameters of CPG model. The paper shows the details of the parameters optimization and the diagram of the convergence performance. In the paper, the CPG includes the main rhythm-generation neuron and the minor pattern-formation neuron, and Rowat's neural model is chosen as the pattern-formation neuron. Then the CPG model is applied to the three-link biped robot and the result shows that the method of parameter optimization is effective.

Adaptive Walking Control for a Quadruped Robot on Irregular Terrain Using the Complex-Valued CPG Network

“…However, the effective dynamics model of a legged robot for movement control in an unknown environment is difficult to compute. This is not only because the efficient mechanical dynamics arithmetic for evaluation of the robot joint torque is difficult to compute, but also because an adaptive walking control system for a legged robot to climb up and down a slope is complex [4,5].…”