Online Trajectory Generation of a MAV for Chasing a Moving Target in 3D Dense Environments
Not on the map. Why?
Abstract (arXiv)
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
Key facts. Cited by 1 paper in the map (data through 7 Oct 2026). First posted on arXiv 6 Apr 2019.
Builds on
No reference list yet.
Built on by
Citing papers per year: 2024: 1.
1 paper.
- 2024Active Human Pose Estimation via an Autonomous UAV Agentcited by 1
- 2024Active Human Pose Estimation via an Autonomous UAV Agent1 Jul 2024