Applying Genetic Programming to Evolve Behavior Primitives and Arbitrators for Mobile Robots

|Behavior-based approach has been successfully applied to design the control system of a robot. This paper presents our approach, based on evolutionary algorithms , to program behavior-based robots automatically. Instead of handcoding all the behavior controllers or evolving an entire control system for an overall task, we suggest our approach at the intermediate level: it includes evolving behavior primitives and behavior arbitrators for a mobile robot to achieve the speciied tasks. To examine the developed approach, we evolve a control system for a moderate complicated box-pushing task as an example. We rst evolved the controllers in simulation and then transferred them to the Khepera miniature robot. Experimental results show the promise of our approach and the evolved controllers are transferred to the real robot without loss of performance.