FPGA-BASED AUTONOMOUS ROBOT NAVIGATION VIA INTRINSIC EVOLUTION

Abstract

Artificial evolution has been applied in mobile robotics to achieve adaptive robotic behaviors in unstructured environments. Meanwhile, much attention has been paid to the evolvable hardware, which is a novel set of integrated circuits capable of reconfiguring its architectures using evolutionary computing techniques. This paper presents the design and implementation of an evolvable hardware-based autonomous robot navigation system using intrinsic evolution. Distinguished from traditional evolutionary approaches based on software simulation, an evolvable robot controller at the hardware gate-level that is capable of adapting to 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 robotic system is confirmed with physical implementation of robot navigation behaviors on light source following and obstacle avoidance using a robot with traction fault.