On Chaotic Oscillator-Based Central Pattern Generator for Motion Control of Hexapod Walking Robot

In this paper, we address a problem of motion control of a real hexapod walking robot along a trajectory of the prescribed curvature and desired motion gait. The proposed approach is based on a chaotic neural oscillator that is employed as the central pattern generator (CPG). The CPG allows to generate various motion gaits according to the specified period of the chaotic oscillator. The output signal of the oscillator is processed by the proposed trajectory generator that allows to specify a curvature of the trajectory the robot is requested to traverse. Such a signal is then considered as an input for the inverse kinematic task which provides particular trajectories of individual legs that are directly send to the robot actuators. Thus, the main benefit of the proposed approach is that only two natural parameters are necessary to control the gait type and the robot motion. The proposed approach has been verified in real experiments. The experimental results support feasibility of the proposed concept and the robot is able to crawl desired trajectories with the tripod, ripple, low gear, and wave motion gaits.