Online Trajectory Generation of a MAV for Chasing a Moving Target in 3D Dense Environments
This addresses the challenge of simultaneous collision avoidance and occlusion handling for micro aerial vehicles in dense environments, representing an incremental improvement in target chasing missions.
The paper tackles the problem of an aerial vehicle chasing a moving target in cluttered 3D environments by developing a real-time replanning algorithm that ensures safety and optimizes visibility, achieving successful tests in multiple dense environments with a provided simulator.
This work deals with a moving target chasing mission of an aerial vehicle equipped with a vision sensor in a cluttered environment. In contrast to obstacle-free or sparse environments, the chaser should be able to handle collision and occlusion simultaneously with flight efficiency. In order to tackle these challenges with real-time replanning, we introduce a metric for target visibility and propose a cascaded chasing planner. By means of the graph-search methods, we first generate a sequence of chasing corridors and waypoints which ensure safety and optimize visibility. In the following phase, the corridors and waypoints are utilized as constraints and objective in quadratic programming from which we complete a dynamically feasible trajectory for chasing. The proposed algorithm is tested in multiple dense environments. The simulator AutoChaser with full code implementation and GUI can be found in https://github.com/icsl-Jeon/traj_gen_vis