Morphology and Gait Control Evolution of Legged Robots

Abstract

This paper describes our research and experiments with autonomous robots, in which were used genetic algorithms to evolve stable gaits of simulated legged robots in a physically based simulation environment. In our approach, the gait is defined using a finite state machine based on the joint angles of the robot legs, and the parameters are optimized using genetic algorithms. The proposed model also allows the evolution of the robot body morphology. The model validation was performed by several experiments and a valid statistical analysis, and the results show that it is possible to generate fast and stable gaits using genetic algorithms in an efficient manner.