In this article, a network of central pattern generators is used for the motion planning of a hexapod robot. There are many parameters in the planning network, which determine the motion performance of the hexapod robot. On the other hand, the network is a highly nonlinear coupling network, which is difficult to obtain optimal parameters by an analytical method. Optimizing these parameters to make the robot walk well is a multi-objective optimization process. There is a certain mutual exclusion relationship among …