基于动态障碍物可达包络分析的无人机编队路径规划

doi:10.12305/j.issn.1001-506X.2025.04.24

摘要/Abstract

摘要：

针对无人机编队对行为未知动态障碍物的规避问题, 提出一种基于动态障碍物可达包络分析的无人机编队路径规划方法。首先, 建立无人机编队运动模型, 并利用领航-跟随法维持期望的编队构形。其次, 考虑到动态障碍物运动状态的不确定性, 建立含有不确定因素的非线性运动模型, 并通过状态转移张量法得到不确定因素的协方差传递方程, 进而计算出预测时域内障碍物的可达包络。最后, 对障碍物可达包络建立势场模型, 利用人工势场法实现无人机编队避障飞行。对比仿真实验结果表明, 所提方法能够在线一次性给出行为未知动态障碍物的可达包络, 并有效解决无人机编队在避开动态障碍物时出现的路径绕远等问题。

关键词: 无人机编队, 动态障碍物, 不确定性, 状态转移张量法, 可达包络分析

Abstract:

To solve the problem of unmanned aerial vehicle (UAV) formation to avoid dynamic obstacles with unknown behaviors, a UAVs formation path planning method based on the reachable envelope analysis of dynamic obstacles is proposed. Firstly, the model of the UAVs formation motion is established and the desired formation configuration is formed using the leader-follower method. Secondly, considering the uncertainty of the motion dynamic states of dynamic obstacles, a nonlinear motion model containing uncertainties is established, and the covariance propagation equation of the uncertainties is obtained by the state transfer tensor method, which generates the reachable envelope of the obstacle in the predicted time domain. Finally, the potential field model is established for the reachable envelope of the obstacle, and the artificial potential field method is applied to realize the UAVs formation obstacle avoidance flight. The results of comparative simulation experiments show that the proposed method can generate the reachable envelope of dynamic obstacles with unknown behaviors at one time online, and effectively solve problems such as path bypassing when the UAV formation avoids dynamic obstacles.

Key words: unmanned aerial vehicle (UAV) formation, dynamic obstacle, uncertainty, state transfer tensor method, reachable envelope analysis

中图分类号:

殷泽阳, 梁浩, 廖宇新, 陈晓方, 谢永芳. 基于动态障碍物可达包络分析的无人机编队路径规划[J]. 系统工程与电子技术, 2025, 47(4): 1275-1284.

Zeyang YIN, Hao LIANG, Yuxin LIAO, Xiaofang CHEN, Yongfang XIE. UAV formation path planning based on reachable envelope analysis of dynamic obstacle[J]. Systems Engineering and Electronics, 2025, 47(4): 1275-1284.

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变量名称	数值
σ_η/(m·s^－2)	[0.01, 0.1, 0.06]^T
τ_η/s	[0.01, 0.2, 0.3]^T
动态障碍物初始状态	[7, 10, 1, 0.35, 0, 0]^T

变量名称	数值
最大线速度/(m·s^-1)	1
最小线速度/(m·s^-1)	0.1
俯仰角最大变化值/rad	1.047 2
偏航角最大变化值/rad	1.047 2
领航者初始状态	[－5, －5, 1, 0.5, 0, 0.78]^T
跟随者1初始状态	[－8.48, －5.65, 1, 0.5, 0, 0.78]^T
跟随者2初始状态	[－5.65, －8.84, 1, 0.5, 0, 0.78]^T
领航者目标位置/m	[35, 35, 1]^T
机间相对期望距离/m	4
机间相对期望夹角/rad	[2.618 0, 3.665 2]^T

变量名称	本文方法	传统人工势场法	减少百分比/%
领航者飞行路径长度/m	58.01	65.7	11.7
跟随者1飞行路径长度/m	60.9	78.9	22.8
跟随者2飞行路径长度/m	59.4	75.2	20.2
平均编队误差/m	22.6	69.5	67.5
飞行总时间/s	118	139	15.1

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