Abstract:

With the rapid growth of urban airspace applications for unmanned aerial vehicles (UAVs), the need for safe and coordinated multi-UAV flight in complex three-dimensional environments has become increasingly urgent. However, traditional path-planning methods typically optimize for the shortest distance and fail to adequately account for risks arising from building obstacles and dynamic interactions among UAVs, making it difficult to ensure safety and feasibility when multiple vehicles operate simultaneously. To address these challenges, this paper proposes a risk-aware three-dimensional path-planning algorithm. Building upon a voxelized urban environment with obstacle inflation, the algorithm incorporates a building risk field and an inter-UAV risk field to characterize static environmental risks and dynamic multi-UAV risks. A first-come-first-served strategy is adopted to determine the planning order and generate UAV paths sequentially. During path planning, the algorithm jointly constrains the current UAV's trajectory using the global static risk field and the accumulated dynamic risk field. After each path is generated, the corresponding time-indexed UAV risk distribution is integrated into the global risk map, forming a time-varying composite risk field that guides subsequent UAVs to avoid high-risk regions. Simulation results demonstrate that the proposed algorithm effectively suppresses potential collision risks between UAVs and buildings as well as among UAVs themselves, while maintaining competitive path length. The method significantly improves the safety and efficiency of coordinated multi-UAV flight in urban 3D environments.

Key words: UAM, UAV, path planning, A* algorithm, risk model