Moving Obstacle Avoidance for Unmanned Aerial Vehicles

摘要

We investigated moving obstacle avoidance for Unmanned Aerial Vehicles (UAVs). We propose a two-stage approachrnfor obstacle avoidance. Stage 1 involves a global path planner and Stage 2 uses a local potential field planner. Byrncombining them in a hierachical manner, we are going to develop a complete system for avoiding stationary as well asrnmoving obstacles for UAVs. The global planner uses Dubins curves (Ref. 1) coupled with a Kalman filter to predictrnthe collision point and plan paths that are obstacle free. We demonstrate the efficacy of the system using simulatedrnUAVs and real aircraft broadcasting their position using the ADS-B (Automatic Dependent Surveillance-Broadcastrn(ADS-B) (Ref. 2)) system. A local planner is also developed for avoiding obstacles that do not use ADS-B. This localrnplanner uses vision for obstacle detection and potential fields for obstacle avoidance. The effectiveness of the globalrnand local path planners are demonstrated in simulations.