Local Trajectory Planning of Unmanned Aerial Vehicle Formation Based on Time Cooperative Strategy

In this paper, we address the problem of rapid generation of trajectories with time coordination in unmanned aerial vehicle (UAV) formations in complex urban environments. Aiming at the phenomenon that large-scale UAV system trajectory planning is computationally burdensome and fails to generate high time-optimal cooperative trajectories, we propose a time cooperative trajectory planning algorithm based on distributed model predictive control (DMPC). Firstly, a multi-UAV dynamics model based on predictive horizon is established, and a rolling iterative optimization strategy is proposed to ensure the real-time and rapidity of trajectory planning. Furthermore, the time cooperative strategy is proposed so that the UAV formation can arrive at the target position and complete the formation flight mission at the same time to ensure the feasibility of macroscopic task allocation. The simulation results show that the UAV can reach the target location smoothly in the complex environment with random assignment of obstacles, and there is no collision during the flight process, which verifies the reliability of the algorithm.

I. Introduction

In the face of complex tasks in the urban environment, there are bottlenecks in the detection distance and penetration ability of a single UAV, while the cooperative work of multiple UAVs has the advantages of stronger robustness, more comprehensive functions, and better adaptability, which is more suitable for real-time tasks [1]. Therefore, the large-scale UAV formation system has a better application prospect [2, 3]. In the dynamic environment, the UAV usually needs to identify the information in the field of view, locate own position, receive the transmission signal [4, 5] of adjacent UAVs, complete the trajectory planning with the shortest path or optimal time, and transfer the state and input function to the controller to complete stable and efficient flight.