An Evolutionary Robot Navigation System Using a Gate-Level Evolvable Hardware

Recently there has been a great interest in the design and study of evolvable systems based on Arti cial Life principles in order to control the behavior of physically embedded systems such as a mobile robot. This paper studies an evolutionary navigation system for a mobile robot using a Boolean function approach implemented on gate-level evolvable hardware (EHW). The task of the mobile robot is to reach a goal represented by a colored light while avoiding obstacles during its motion. Using the evolution principles to build the desired behaviors, we show that the Boolean function approach using gate-level evolvable hardware is su cient. We demonstrate the e ectiveness of the generalization ability of EHW by comparing the method with a Boolean function approach implemented on a random access memory (RAM). The results show that the evolvable hardware system obtains the desired behaviors in twice fast time and that the EHW generates a robust robot behavior insensitive to the robot position and the obstacles con gurations.