Trajectory planning for unmanned aerial vehicles in complicated urban environments: A control network approach. (July 2021)

• Record Type: Journal Article
• Authors: Lin, Xi; Wang, Chengzhang; Wang, Kaiping; Li, Meng; Yu, Xiangqian
• Is Part Of: Transportation research. Volume 128(2021)
• Publication Date: 2021-07
• Subjects: Unmanned aerial vehicles -- Trajectory planning -- Control network -- Urban environment; Transportation -- Periodicals; Transportation -- Technological innovations -- Periodicals; 388.011
• DOI: 10.1016/j.trc.2021.103120
• Languages: English
• ISSNs: 0968-090X

Abstract

Highlights: A two-stage control network approach for trajectory planning in large-scale complicated urban environment. Discrete control network for minimum-time path finding considering collision avoidance and kinetic properties. Both virtual and real-world urban maps are created to evaluate trajectory planning frameworks. Abstract: Trajectory planning is crucial for Unmanned Aerial Vehicles (UAVs) applications. It is still a challenge to plan UAV trajectories in large-scale complicated three-dimensional urban environments, mainly due to the complexities associated with handling a tremendous number of obstacles. To relieve this difficulty, this study proposes a two-stage control network approach. The first stage is an offline planning stage, aiming at constructing a discrete control network in the working environment achieving collision avoidance and meanwhile considering UAV kinetic properties. The second stage is an online planning stage, where a feasible corridor is generated based on the shortest path in the control network, and the obtained route is smoothed by a three-dimensional Dubins curve algorithm; then, a time-optimal trajectory generation algorithm is applied to trace the designed spatial path. Numerical studies based on a virtual city as well as a large-scale real-world urban area are conducted. The results show that the proposed approach is able to identify reasonable UAV trajectories within negligible computational time.