Autonomous robot navigation via intrinsic evolution

Abstract

This paper presents the design and implementation of an evolvable hardware based autonomous robot navigation system using intrinsic evolution. Distinguished from the traditional evolutionary approaches based on software simulation, an evolvable robot controller at the hardware gate-level that is capable of adapting dynamic changes in the environments is implemented. In our approach, the concept of Boolean function is used to construct the evolvable controller implemented on an FPGA-based robot turret, and evolutionary computing is applied as a learning tool to guide the artificial evolution at the hardware level. The effectiveness of the proposed evolvable autonomous robotic system is confirmed with the physical real-time implementation of robot navigation behaviors on light source following and obstacle avoidance using a robot with traction fault.