A Dynamic Trajectory Planning Algorithm for Urban Ultra-Low Altitude UAVs Based on a Fusion Heuristic Algorithm

This paper presents a dynamic trajectory planning method for ultra-low altitude UAV flights in urban multi-building environments and conducts simulations of multiple UAVs dynamic trajectory planning in urban environments. The initial UAV trajectory is obtained by adding a time dimension to the traditional $\mathrm{A}^{\star}$ algorithm, and the environment is monitored during flight, and local path re-planning is carried out by an improved ant colony algorithm when unexpected obstacles are encountered. Simulation experiments show that the dynamic trajectory planning algorithm proposed in this paper improves the usability of the planned path compared with the traditional path planning method, and the combination of pre-planned path and dynamic corrected trajectory is beneficial to the UAVs efficient flight in the complex urban environment.

I. Introduction

Drones are in a period of rapid development as they integrate a variety of technological innovations, and their technology is becoming increasingly mature, with applications expanding towards the military, agriculture, logistics and transport [1–2]. Due to the online shopping, the impact of urban logistics and distribution on urban traffic has become more and more significant and has become a prominent conflict in large cities that already face a mismatch between traffic demand and traffic capacity. To solve this contradiction, the National Aeronautics and Space Administration (NASA) [3] and others have conducted studies on urban air traffic and airspace integration, and the Federal Aviation Administration [4] has stipulated that light and small drones can fly in urban ultra-low altitude airspace below 120 meters above ground level.