An Intelligent Locomotion Control Architecture for Hexapod Robot

Abstract

This paper presents an intelligent locomotion control architecture for a hexapod robot. The proposed architecture provides a hexapod robot abilities to perceive different terrains and adjust gait accordingly by utilizing CPG-network, torque sensing, and radial basis function neural network. The architecture is suitable for implementing in an embedded system for on-board small hexapod robots. The effectiveness of the proposed intelligent control architecture is demonstrated through real robot experiments.