A multiple UAVs path planning method based on model predictive control and improved artificial potential field

被引：0
|
作者：
Xian B. [1 ]
Song N. [1 ]
机构：
[1] School of Electrical and Information Engineering, Tianjin University, Tianjin
来源：
Kongzhi yu Juece/Control and Decision | 2024年 / 39卷 / 07期
关键词：
dynamic obstacles; event trigger; model predictive control; modified artificial potential field; multiple unmanned aerial vehicles; path planning;
D O I：
10.13195/j.kzyjc.2023.0892
中图分类号：
学科分类号：
摘要：
The model predictive control (MPC) method has been applied in the path planning for unmanned aerial vehicle (UAV) swarm. However, it has some disadvantages, such as high computation consumption, long time single-step execution, et al. These disadvantages make the MPC method difficult for real-time implementation which requires high control updating frequency. The offline MPC method requires accurate map information and struggles with handling unpredictable dynamic obstacles. In this paper, a path planning strategy is proposed which combines offline MPC for the global planning with the online improved artificial potential field (APF) for the UAVs’ local planning. This approach enhances the UAV’s obstacle avoidance capability while ensuring safe and smooth trajectories generated by the MPC. This paper introduces an adjustment force to solve the local minimum problem in the traditional APF method. A repulsive function based on the relative distance between the target and UAVs, and an attractive function are designed to alleviate the UAVs’ low speed problem near the target point. An event-triggered UAV trajectory modification and recovery strategy is also designed, enabling the UAV to perform dynamic obstacle avoidance behaviors only when it is necessary, thus maximizing the utilization of the original planned trajectory. Simulation results demonstrate that the proposed method can make the UAVs reach the target point with excellent dynamic obstacle avoidance capabilities. © 2024 Northeast University. All rights reserved.
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页码：2133 / 2141
页数：8
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