Fast-Tracker: A Robust Aerial System for Tracking Agile Target in Cluttered Environments
This addresses the challenge of autonomous aerial tracking in dense, unpredictable settings, which is incremental as it builds on existing hierarchical planning methods.
The paper tackles the problem of using a UAV to aggressively and safely track an agile target in unknown, cluttered environments by proposing a systematic solution with target motion prediction and tracking trajectory planning, achieving superior time efficiency and tracking effectiveness compared to state-of-the-art methods.
This paper proposes a systematic solution that uses an unmanned aerial vehicle (UAV) to aggressively and safely track an agile target. The solution properly handles the challenging situations where the intent of the target and the dense environments are unknown to the UAV. Our work is divided into two parts: target motion prediction and tracking trajectory planning. The target motion prediction method utilizes target observations to reliably predict the future motion of the target considering dynamic constraints. The tracking trajectory planner follows the traditional hierarchical workflow.A target informed kinodynamic searching method is adopted as the front-end, which heuristically searches for a safe tracking trajectory. The back-end optimizer then refines it into a spatial-temporal optimal and collision-free trajectory. The proposed solution is integrated into an onboard quadrotor system. We fully test the system in challenging real-world tracking missions.Moreover, benchmark comparisons validate that the proposed method surpasses the cutting-edge methods on time efficiency and tracking effectiveness.