A New CPG Model for the Generation of Modular Trajectories for Hexapod Robots

Abstract

Legged robots are often used in a large variety of tasks, in different environments. Nevertheless, due to the large number of degrees-of-freedom to be controlled, online generation of trajectories in these robots is very complex. In this paper, we consider a modular approach to online generation of trajectories, based on biological concepts, namely Central Pattern Generators (CPGs). We introduce a new CPG model for hexapod robots' rhythms, based in the work of Golubitsky et al (1998). Each neuron/oscillator in the CPG consists of two modules/primitives: rhythmic and discrete. We study the effect on the robots' gaits of superimposing the two motor primitives, considering two distinct types of coupling. We conclude, from the simulation results, that the amplitude and frequency of periodic solutions, identified with hexapods' tripod and metachronal gaits, remain constant for the two couplings, after insertion of the discrete part.