Evolution of central pattern generators for the control of a five-link planar bipedal walking mechanism

With the aim of producing a stable human-like bipedal gait, a five-link planar walking mechanism was coupled with a central pattern generator (CPG) network, consisting of units based on Matsuoka's half-center oscillator model. As a minimalistic approach to bipedal walking, this type of walking mechanism contains only four actuators, and is lacking feet and ankles. Firstly, the mechanism was designed and built as a physical simulation, providing a platform for heuristic tests and the creation of a CPG controller by genetic algorithms (GA). The oscillatory characteristics of the CPG network, its internal connectivity, and the external feedback pathways were subject to GA optimization. The approach proved successful and the results were transferred to a hardware realization of the mechanism, to test their performance under real-world dynamics. Results suggest that the biologically inspired CPG model is very well suited for controlling legged locomotion, since a diverse manifestation of CPG networks (both with and without external feedback) have been observed to succeed during the course of GA evaluations. Observations also imply that while the CPG mechanism is inherently able to sustain a stable gait, the utilization of feedback pathways makes the gait more human-like and is needed to provide a means to adapt to irregularities in the environment.