Reconfigurable On-Board Vision Processing for Small Autonomous Vehicles

This paper addresses the challenge of supporting real-time vision processing on-board small autonomous vehicles. Local vision gives increased autonomous capability, but it requires substantial computing power that is difficult to provide given the severe constraints of small size and battery-powered operation. The authors describe a custom FPGA-based circuit board designed to support research in the development of algorithms for image-directed navigation and control. They show that the FPGA approach supports real-time vision algorithms by describing the implementation of an algorithm to construct a Three-Dimensional (3D) map of the environment surrounding a small mobile robot.