ICUAS 2020 Paper Abstract


Paper ThB1.2

Zheng, Zhaoliang (University of California Los Angeles), Bewley, Thomas R. (University of California San Diego), Kuester, Falko (University of California San Diego)

Point Cloud-Based Target-Oriented 3D Path Planning for UAVs

Scheduled for presentation during the Regular Session "See and Avoid Systems II" (ThB1), Thursday, September 3, 2020, 15:20−15:40, Macedonia Hall

2020 International Conference on Unmanned Aircraft Systems (ICUAS), September 1-4, 2020 (Postponed from June 9-12, 2020), Athens, Greece

This information is tentative and subject to change. Compiled on September 25, 2020

Keywords Path Planning, UAS Applications, Autonomy


This paper explores 3D path planning for unmanned aerial vehicles (UAVs) in 3D point cloud environments. Derivative maps such as dense point clouds, mesh maps, octomaps, etc. are frequently used for path planning purposes. A target-oriented 3D path planning algorithm, directly using point clouds to compute optimized trajectories for a UAV, is presented in this article. This approach searches for obstacle-free, low computational cost, smooth, and dynamically feasible paths by analyzing a point cloud of the target environment, using a modified connect RRT-based path planning algorithm, with a k-d tree-based obstacle avoidance strategy and three-step optimization. This presented approach bypasses the common 3D map discretization, directly leveraging point cloud data. Following trajectory generation, the algorithm creates way-point based, closed-loop quadrotor controls for pitch, roll, and yaw attitude angle as well as dynamics commands for the UAV. Simulations of UAV 3D path planning based on different target points in the point cloud map are presented, showing the effectiveness and feasibility of this approach.



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