Vision‐based navigation through urban canyons

Abstract We address the problem of navigating unmanned vehicles safely through urban canyons in two dimensions using only vision‐based techniques. Two commonly used vision‐based obstacle avoidance techniques (namely stereo vision and optic flow) are implemented on an aerial and a ground‐based robotic platform and evaluated for urban canyon navigation. Optic flow is evaluated for its ability to produce a centering response between obstacles, and stereo vision is evaluated for detecting obstacles to the front. We also evaluate a combination of these two techniques, which allows a vehicle to detect obstacles to the front while remaining centered between obstacles to the side. Through experiments on an unmanned ground vehicle and in simulation, this combination is shown to be beneficial for navigating urban canyons, including T‐junctions and 90‐deg bends. Experiments on a rotorcraft unmanned aerial vehicle, which was constrained to two‐dimensional flight, demonstrate that stereo vision allowed it to detect an obstacle to the front, and optic flow allowed it to turn away from obstacles to the side. We discuss the theory behind these techniques, our experience in implementing them on the robotic platforms, and their suitability to the urban canyon navigation problem. © 2009 Wiley Periodicals, Inc.