Autonomous off-road navigation using stereo-vision and laser-rangefinder fusion for outdoor obstacles detection

During the last decade, ground mobile robots that are able to drive autonomously in off-road environments have received a great deal of attention. Autonomous navigation in unstructured environments faces many new challenges compared to structured urban environments, these challenges increase the complexity of the localization, obstacle detection, path planning and navigation commands. Accordingly this paper presents a fusion system for stereo-vision and laser-rangefinder outdoor obstacle detection, which is implemented as an application for autonomous off-road navigation. The test platform is an electric golf-cart that is modified mechanically and electrically to operate in driver-less mode. This vehicle is equipped with binocular camera, laser-rangefinder, electronic compass and on-board embedded computer, which operates using Robotic Operating System (ROS) architecture. The proposed architecture gathers the data from all different sensors, in order to make navigation decisions from one point to another, avoiding obstacles in the path. Experimental results indicate the high performance of the proposed approaches, they show that the perception from the stereo-vision detection enhances the laser-rangefinder detection, which consequently makes a better decision in maneuvering the obstacle and returns back to the original path.