Work

Urban Air Mobility and Unmanned Aerial Vehicle Path Planning in Dynamic Urban Environments: A Review

Year: 2026

Type: article

Abstract: The complexity of three-dimensional (3D) dynamic urban environments poses new challenges to emerging unmanned aerial vehicle (UAV) path planning, especially in dense buildings, dynamic obstacles, and multi-UAV collaboration. This paper reviews mainstream 3D path planning algorithms (including RRT, PRM, the ant colony algorithm, the artificial potential field method, and A*) and analyzes their core principles, applicable scenarios, advantages, and disadvantages. The study finds that each algorithm has its disadvantages: RRT lacks optimality, PRM has high computational cost, the ant colony algorithm is poor in real-time performance, APF is prone to local optima, and A* performs well in static environments. Future research should explore hybrid strategies combining multiple algorithms to improve adaptability in dynamic complex environments, providing efficient solutions for urban low-altitude UAV operations.

Source: Electronics

DOI: 10.3390/electronics15101998

Authors: Yang Xu, Xiang Lu, Junru Yang, Chuan Sun, Shucai Xu, Zhixiong Li

Institutions: Ocean University of China, Nanjing University of Aeronautics and Astronautics, Tsinghua University

Language: English

Topic: Robotic Path Planning Algorithms

Subfield: Computer Vision and Pattern Recognition

Field: Computer Science

Domain: Physical Sciences

SDG: Sustainable cities and communities

Open Access status: gold

Estimated APC paid: $2,896