Obstacle Magnification for 2-D Collision and Occlusion Avoidance of Autonomous Multirotor Aerial Vehicles

Collision or occlusion avoidance is one of the most important functions of autonomous unmanned vehicles when maneuvering or conducting missions, including monitoring or following targets in environments with various obstacles such as trees and buildings. While considering the minimum distance to obstacles or approximating the shape of obstacles is convenient, incorporating the shape of the original obstacles, sometimes, can provide more effective strategies for collision and occlusion avoidance of obstacles with complex shapes or arrangements. This article presents an obstacle magnification algorithm that magnifies but retains the original shape of the detected obstacles. Two simple parameters can adjust the position and magnification of the virtual obstacles. The simulation and outdoor experimental results for the obstacle magnification, implemented on an onboard embedded system, demonstrate the effectiveness of this concept, which should be useful in various applications for small autonomous multirotor aircrafts.