WiPlan: Waypoint Planning for UAVs with Multiple Pan-Zoom Adjustable Cameras

Yanlong Huang, Weijun Wang, Tingting Yuan, Xiaoming Fu

Abstract: Waypoint planning is critical for Unmanned Aerial Vehicle (UAV) operations, particularly for surveillance and monitoring applications. With the rapid development and deployment of UAVs, an increasing number of industrial UAVs are equipped with multiple cameras to enhance monitoring capabilities and operational efficiency. Meanwhile, a new type of camera supporting adjustable pan and zoom is emerging and rapidly being deployed. While UAVs equipped with multi-adjustable cameras enhance flexibility and precision in capturing dynamic scenes, they also introduce new challenges in optimizing waypoints to ensure efficient coverage and accurate data collection. In this paper, we propose WiPlan, which aims to determine the optimal UAV waypoints while dynamically adjusting the pan (horizontal rotation) and zoom (focal length) of cameras to maximize overall monitoring utility. This problem involves two coupled NP-hard problems, making it significantly more complex to solve compared to previous work. In tackling this challenge, we construct WiPlan as a two-level optimization problem. The results show that our algorithm improves monitoring utility by at least $1.73 \times$ compared to state-of-the-art algorithms. Moreover, we test WiPlan using a real-world outdoor field, which includes 23 objects and a two-camera UAV with 7 waypoints. The results demonstrate that our algorithm successfully monitors 65 % of the maximum possible monitored targets, outperforming the baselines by factors of $4.25 \times$ and $15 \times$, respectively.

External IDs:dblp:conf/iwqos/HuangWYF25