Real-Time Obstacle Avoidance for Mobile Robots via Stereoscopic Vision Using Reconfigurable Hardware (Abstract Only)

Abstract

An embedded, real-time, and low power obstacle avoidance system is a critical component towards fully autonomous robots that can be used in safety missions, space exploration, and transportation systems among others. In this paper a complete prototyping platform for the evaluation of obstacle avoidance systems and autonomous robots is realized on reconfigurable hardware. An efficient stereo vision algorithm for producing the necessary 3D and an obstacle avoidance subsystem were both implemented on an ATLYS Spartan-6 FPGA board equipped with a VmodCam stereo camera module. A modified FDX Vantage 1/10 electric car platform was used for testing the proposed architecture in indoor and outdoor real-world scenes. The system receives stereo image data from the VmodCam module and a decision-making algorithm is applied on a specified Region of Interest (RoI) on the produced disparity map. The algorithm outputs the direction that the robot should move to in order to avoid any obstacles present. Experimental evaluation results indicate that the FPGA-based robotic platform can avoid obstacles in real-time (i.e. can process and identify obstacles within a 1/30th of a second that a stereo image takes to be processed) in both indoor and outdoor environments, with 91.7% accuracy, equivalent to software implementations. The overall power consumption of the proposed architecture, excluding the electronic car platform, is 6 W, making it ideal for use on mobile robots, without becoming a significant drain on its battery life.