Evolutionary Behavior Acquisition for Humanoid Robots

This paper describes and analyzes a series of experiments to develop a general evolutionary behavior acquisition technique for humanoid robots. The robot’s behavior is defined by joint controllers evolved concurrently. Each joint controller consists of a series of primitive actions defined by a chromosome. By using genetic algorithms with specifically designed genetic operators and novel representations, complex behaviors are evolved from the primitive actions defined. Representations are specifically tailored to be useful in trajectory generation for humanoid robots. The effectiveness of the method is demonstrated by two experiments: a handstand and a limbo dance behavioral tasks (leaning the body backwards so as to pass under a fixed height bar).