Object Detection and Avoidance Using Optical Techniques in Uninhabited Aerial Vehicles

Abstract

Uninhabited Aerial Vehicles will require autonomous collision detection and avoidance capabilities in order to gain wide acceptance and usage in the National Airspace System. The collision detection and avoidance problem is primarily a motion estimation problem, relying on the accuracy of the sensing, processing, actuation and control algorithms onboard the vehicle. Computer vision is a growing field in robotics and autonomous vehicles, and has made vision a feasible technology for object detection in different platforms. In this work, we investigate the feasibility of using optic flow techniques in order to design an altitude hold controller for a fixed wing aircraft flying a nap-of-the-earth trajectory in the presence of variable terrain. Simulated results yield an error of approximately 1.5 % in altitude variation for steady level flight (approximately 15 cm) for terrain disturbances of maximum amplitude 4 m. Experimental results obtained from flight data using the UIUC UAV platform are used to validate the controller, and sources of error along with potential improvements in equipment and procedures are cited. I.