HOJO-brain for motion control of robots and biological systems

Abstract

The purpose of this research was to propose and develop a control method in the robotic and biomedical fields which is configured by a robotic/biological simulator, an analytical control frame which has phase sequences, sensory feedback, and an artificial central pattern generator (CPG) which is constructed by a recurrent neural network (RNN) and a genetic algorithm (GA). We call such a controller a “HOJO-brain”, which means a supplementary brain for motion control. We applied this method in the robotic and biomedical fields. In the robotic field, the HOJO-brain was applied to a 5-DOF legged-locomotion robot and a 32-DOF humanoid simulation model consisting of antagonistic muscles. In the biomedical field, it was applied to animals as the FES (functional electrical stimulation) controller. This FES control system with a HOJO-brain has the potential to give more effective and emergent motion control to severely physically handicapped people such as quadraplegics. With computer simulations and simple experiments using animals, we abtained performance indices which confirmed the fine adaptability and emergence for motion control.