Evolvable Reactive Execution System using Recon gurable Hardware: a Robot Navigation System Case Study

Recently there has been great interest in the design and study of evolvable systems in order to control the behavior of physically embedded systems. Due to the complexity of their architecture and their interaction with the environment, a Model-based Autonomous System approach was proposed by Williams to integrate a priori knowledge and reasoning methods of di erent kinds (Williams & Nayak 1996a). But the di culty of precomputing all possible interactions obliges also the autonomous system to self con gure itself by modifying its own structure as well as self modeling by adapting or even building a model using for example sensor information. This paper examines the architecture of a self con guration component of a model-based autonomous system using a evolvable hardware (EHW). The self con gure component is applied to a navigation system for a mobile robot. It uses a Boolean function approach implemented on gate-level recon gurable hardware. The task of the mobile robot is to reach a goal represented by a colored ball 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 recon gurable hardware is su cient. We demonstrate the e ectiveness of the generalization ability of the Boolean function approach using EHW by creating o -line the robot behavior and the advantage of the hardware implementation to speed up the on-line adaptation. The results show that the evolvable hardware system is able to create a robust robot behavior insensitive to the gap between the real and simulated world.