Vision-Based Detection and Tracking of Airborne Obstacles in a Cluttered Environment

Abstract

This paper proposes an image processing algorithm for 'sense-and-avoid' of aerial vehicles in short-range at low altitude and shows flight experiment results. Since it can suppress the negative effects cause cluttered environment in image sequence such as the ground seen or sensitivity of threshold value during low-altitude flight, proposed algorithm has better performance of collision avoidance. Furthermore, proposed algorithm can perform better than simple color-based detection and tracking methods because it takes the characteristics of vehicle dynamics into account in image plane. The performance of proposed algorithm is validated by post image processing using video clip taken from flight test and actual flight test with simple avoidance maneuver.