UAV Path Planning Algorithm Based on Improved A* and Dynamic Window Approach

贺勇; 侯体成; 曾子望

doi:10.13433/j.cnki.1003-8728.20230322

Chinese

您当前的位置：

首页 >

文章列表页 >

UAV Path Planning Algorithm Based on Improved A* and Dynamic Window Approach

更新时间：2026-04-23

- UAV Path Planning Algorithm Based on Improved A* and Dynamic Window Approach
- Mechanical Science and Technology for Aerospace Engineering Vol. 44, Issue 9, Pages: 1668-1676(2025)
- 作者机构：
  
  长沙理工大学机构电气与信息工程学院,长沙,410114
- 作者简介：
- 基金信息：
- DOI：10.13433/j.cnki.1003-8728.20230322
  CLC：
- Published：2025
- 稿件说明：
移动端阅览
贺勇, 侯体成, 曾子望. UAV Path Planning Algorithm Based on Improved A* and Dynamic Window Approach[J]. Mechanical Science and Technology for Aerospace Engineering, 2025, 44(9): 1668-1676.
DOI：

贺勇, 侯体成, 曾子望. UAV Path Planning Algorithm Based on Improved A* and Dynamic Window Approach[J]. Mechanical Science and Technology for Aerospace Engineering, 2025, 44(9): 1668-1676. DOI： 10.13433/j.cnki.1003-8728.20230322.

摘要

为了解决传统A*算法搜索效率低、路径不平滑、不具备避障能力等问题，结合A*和动态窗口法，提出具有全局引导的双层规划G-DWA*算法。首先，定义障碍物覆盖率模型，动态调整A*算法启发函数的权重系数，设计视线算法提取路径关键点。然后，引入折扣因子改进动态窗口法的原始评价子函数，并提出新的速度平滑和轨迹相似度评价指标。最后，将改进A*算法提取的关键路径节点作为改进动态窗口法的中间引导点，同时计算每个引导点的作用范围，为局部规划提供全局引导。实验结果表明，G-DWA*算法可以明显提升无人机自主路径规划的快速性、平滑性，能在全局最优的基础上，规避未知障碍物，能更好地满足军事等复杂规划任务的要求。

Abstract

To address the challenges of poor search efficiency

non-fluid pathways

and inadequate obstacle evasion in conventional A* algorithms

an innovative globally-guided dual-layer planning algorithm known as G-DWA* is proposed in this study

which combines the A* algorithm with the dynamic window approach (DWA). Initially

a model for obstacle coverage is formulated

the weight coefficient for the A* heuristic function is adjusted dynamically

and a line-of-sight algorithm is implemented to extract pivotal path points. Then

a discount factor is employed to enhance the original sub-function evaluation of DWA

introducing novel assessment metrics for velocity smoothness and trajectory likeness. Finally

the essential path nodes obtained from the refined A* algorithm serve as intermediate waypoints for the augmented DWA. The impact radius of each waypoint is computed

providing comprehensive guidance for localized planning. Experimental results indicate that the G-DWA* algorithm considerably improves the velocity and fluidity of autonomous path planning for drones. It is proficient in evading unidentified obstacles based on global optimization

thereby effectively fulfilling the requirements of intricate planning tasks

inclusive of military operations.

关键词

Keywords

references

Views

下载量

CSCD

Alert me when the article has been cited

提交

Tools

Publicity Resources

Robot Path Planning by Integrating Improved A* Algorithm and Dynamic Window Approach

A* Algorithm of Path Planning Combining with Dual Neighborhood Selection Expansion

Research on Path Planning and Tracking Control of Four-wheeled Independently Driven Electric Vehicles

Improved RRT* Algorithm for Mobile Robot Path Planning

Robotic Arm Path Planning Combined Artificial Fish Swarming and RRT Algorithms

Related Author

滕景佳

毛建中

杨秀建

袁志豪

白永瑞

敖鹏

刘瀚蔚

高银

Related Institution

College of Mechanical and Vehicle Engineering, Hu'nan University

Faculty of Transportation Engineering, Kunming University of Science and Technology

Chongqing Key Laboratory of Manufacturing Equipment Mechanism Design and Control, Chongqing Technology and Business University

School of Mechanical Engineering, Chongqing Technology and Business University

School of information Engineering, Nanchang Hangkong University

AI问答

Postal code：100079
Tel：（010）53879206 Email：tmw@bjxintong.com.cn
Technical support is provided by Beijing Founder electronics co., LTD 京ICP备09082226号-64 京公网安备11010602201714号
It is recommended to read the content of this site in Chrome&IE9+. Please switch to extreme mode in browser 360.
Cookies We use cookies to help provide and enhance our service and tailor content. By continuing, you agree to the use of cookies.

⁰