Evolving a Sensory–Motor Interconnection Structure for Adaptive Biped Robot Locomotion

Abstract

We present an evolving neural oscillator-based bio-inspired biped robot locomotion for minimizing the constraints during the locomotion process. Sensory-motor coordination model is represented by the interconnection between motor neurons and sensory neurons. An evolutionary computation technique is applied for reconstructing the number of joints and the number of neurons in each joint depending on the environmental condition. In this system, either the number of joints, or the number of neurons, or the interconnection structure are dynamically changed depending on the conditions acquired from the sensors that equipped in the robot. Bacterial programming is inspired by the evolutionary process of bacteria, including bacterial mutation and gene transfer. This system is applied in computer simulation for realizing the optimization process and the optimized structure is applied in a small humanoid robot. In experiments, we run the robot in several different environmental conditions. Different neuron structures are resulted depending on the environmental conditions. The proposed tree structurebased optimization strategy can simplify the sensory-motor interconnection structure.