Evolving a Sensory-Motor Interconnection for Dynamic Quadruped Robot Locomotion Behavior

In this paper, we present a novel biologically inspired evolving neural oscillator for quadruped robot locomotion to minimize constraints during the locomotion process. The proposed sensory-motor coordination model is formed by the interconnection between motor and sensory neurons. The model utilizes Bacterial Programming to reconstruct the number of joints and neurons in each joint based on environmental conditions. Bacterial Programming is inspired by the evolutionary process of bacteria that includes bacterial mutation and gene transfer process. In this system, either the number of joints, the number of neurons, or the interconnection structure are changing dynamically depending on the sensory information from sensors equipped on the robot. The proposed model is simulated in computer for realizing the optimization process and the optimized structure is then applied to a real quadruped robot for locomotion process. The optimizing process is based on tree structure optimization to simplify the sensory-motor interconnection structure. The proposed model was validated by series of real robot experiments in different environmental conditions.