Multi-objective 3D UAV motion planning in WSN based on particle swarm optimization

LU Xiuli; AN Juanhua; JI Song; ZHENG Ying

Chinese

您当前的位置：

首页 >

文章列表页 >

Multi-objective 3D UAV motion planning in WSN based on particle swarm optimization

Calculation & Test | 更新时间：2025-12-30

- Multi-objective 3D UAV motion planning in WSN based on particle swarm optimization
- Vol. 44, Issue 11, Pages: 153-158(2025)
- 作者机构：
  
  保定理工学院信息科学与工程学院,河北,保定,071000
- 作者简介：
- 基金信息：
- DOI：
  CLC： TP212;TP391
- Published：2025
- 稿件说明：
移动端阅览
LU Xiuli, AN Juanhua, JI Song, et al. Multi-objective 3D UAV motion planning in WSN based on particle swarm optimization[J]. 2025, 44(11): 153-158.
DOI：

LU Xiuli, AN Juanhua, JI Song, et al. Multi-objective 3D UAV motion planning in WSN based on particle swarm optimization[J]. 2025, 44(11): 153-158. DOI：

摘要

为解决无线传感器网络(WSN)多目标无人机(UAV)路径规划问题，提出了一种基于粒子群优化的多目标无人机路径规划策略。首先，引入基于网格的传感器场和信息采集模型定义了无人机覆盖区域，实现目标区域内无人机与传感器之间的视距通信。其次，提出了一种多用途适应度函数，反映无人机覆盖范围内每种传感器类型的传感器密度，以及感知信息价值随时间的变化情况。最后，提出了一种基于粒子群优化的生物启发式算法，有效推导无人机的最优位置。实验结果表明，所提方法能够最大化目标函数的效用，并在寻找最优解方面相较于其他对比方法能够实现快速收敛且具有显著优势。

Abstract

To address the multi-objective unmanned aerial vehicle(UAV) path planning problem in a wireless sensor network(WSN)

a multi-objective unmanned aerial vehicle path planning strategy based on particle swarm optimization is proposed.First

a grid-based sensor field and an information collection model are introduced to define the unmanned aerial vehicle coverage area and achieve line-of-sight communication between unmanned aerial vehicle and sensors in the target area.Second

a multi-purpose fitness function is proposed

reflecting the sensor density of each type of sensor in the unmanned aerial vehicle coverage area

as well as the changing situation of the value of sensed information over time.Finally

a biologically inspired algorithm based on particle swarm optimization is proposed to effectively derive the optimal positions of the unmanned aerial vehicle.The experimental results show that the proposed method can maximize the utility of the objective function and achieve rapid convergence and significant advantages in finding the optimal solution compared with other methods.

关键词

Keywords

references

Views

下载量

CSCD

Alert me when the article has been cited

提交

Tools

Publicity Resources

Resilience multi-sensor UAV localization based on a hybrid joint fusion architecture

Enhanced egret swarm optimization algorithm for robot path planning

Highway image crack detection based on U-Net architecture and UAV aerial sensor

Clustering routing algorithm for wireless sensor networks based on chaotic particle swarm optimization

Path planning for guide robot based on improved bitterling fish optimization algorithm

Related Author

ZHANG Wenjuan

HU Haizhou

YANG Congmin

ZHAO Zhengjun

HU Likun

CHEN Wei

CHEN Ken

ZHU Wenyao

Related Institution

School of Mechanical and Electrical Engineering,Henan Vocational University of Science and Technology

School of Electrical and Information Engineering,Zhengzhou University

College of Information and Management Science,Henan Agricultural University

School of Electrical Engineering,Guangxi University

Zhejiang Communications Investment Expressway Operation and Management Co Ltd

⁰