A 3D Multipath Planning Method for Guided Vehicles Using Improved A  <sup>∗</sup> Algorithm Based on Multiple Avoidance Tactics and Terminal Attack Angles

Existing path planning methods have limitations such as random solutions, lack of sharing initial and terminal waypoints, and rare consideration of avoidance between multipaths in 3D. This paper presents a 3D multipath planning method for guided vehicles by employing an improved A ∗ algorithm based on multiple avoidance tactics and terminal attack angles, which searches for a unique solution in restricted waypoint quantities under real‐time conditions and solves four major problems. Intelligent optimization algorithms have the characteristics of random multiple solutions, whereas Classical A ∗ approaches show time consumption, insufficient smoothness, unsettable terminal attack direction, and collisions between multiple paths. To address these limitations, a terminal attack course orientation is achieved by solving the base unit vector, an engineering practical and implicit approach of node extension is built by extending the horizontal and vertical margin vectors, new tactics for terrain and threat zone avoidance are developed by filtering subnodes below the Earth’s surface with bilinear interpolation, and a detection tactic based on point‐in‐polygon checking is used to realize horizontal route avoidance with a better effect. The criteria used to measure multipath planning effectiveness include path length, path smoothness, avoidance capability, terminal attack angle settablity, and search time. Simulation results in two attack situations, three different degrees of freedom modes and 10 real‐world scenarios demonstrate that the improved A ∗ search algorithm has higher efficiency and better performance than classical algorithms. The 3D multipath planning method shortened the search time by 91.4%, reduced the number of path nodes by 96.9% for Mode 1, improved the direction smoothness by 100% for Mode 3, and improved the pitch smoothness by 99.6% for Mode 2. The research not only provides practical tools for antisurface target operations and simulations but also offers new perspectives and methodological references for researchers in related fields.

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Publication Details

Journal
International Journal of Aerospace Engineering
Published
2025-01-01
DOI
https://doi.org/10.1155/ijae/9944699
Citations
2
Primary Topic
Robotic Path Planning Algorithms
Type
article
Field-Weighted Citation Impact
2.55

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article

A 3D Multipath Planning Method for Guided Vehicles Using Improved A  ∗ Algorithm Based on Multiple Avoidance Tactics and Terminal Attack Angles

Pengfei Wu, Xiaobao Li, Yue Liu, Huang Jun
2 citations
International Journal of Aerospace Engineering
Robotic Path Planning Algorithms
2.55
article

A 3D Multipath Planning Method for Guided Vehicles Using Improved A  ∗ Algorithm Based on Multiple Avoidance Tactics and Terminal Attack Angles

Pengfei Wu, Xiaobao Li, Yue Liu, Huang Jun
article en
2 citations

Abstract

Existing path planning methods have limitations such as random solutions, lack of sharing initial and terminal waypoints, and rare consideration of avoidance between multipaths in 3D. This paper presents a 3D multipath planning method for guided vehicles by employing an improved A ∗ algorithm based on multiple avoidance tactics and terminal attack angles, which searches for a unique solution in restricted waypoint quantities under real‐time conditions and solves four major problems. Intelligent optimization algorithms have the characteristics of random multiple solutions, whereas Classical A ∗ approaches show time consumption, insufficient smoothness, unsettable terminal attack direction, and collisions between multiple paths. To address these limitations, a terminal attack course orientation is achieved by solving the base unit vector, an engineering practical and implicit approach of node extension is built by extending the horizontal and vertical margin vectors, new tactics for terrain and threat zone avoidance are developed by filtering subnodes below the Earth’s surface with bilinear interpolation, and a detection tactic based on point‐in‐polygon checking is used to realize horizontal route avoidance with a better effect. The criteria used to measure multipath planning effectiveness include path length, path smoothness, avoidance capability, terminal attack angle settablity, and search time. Simulation results in two attack situations, three different degrees of freedom modes and 10 real‐world scenarios demonstrate that the improved A ∗ search algorithm has higher efficiency and better performance than classical algorithms. The 3D multipath planning method shortened the search time by 91.4%, reduced the number of path nodes by 96.9% for Mode 1, improved the direction smoothness by 100% for Mode 3, and improved the pitch smoothness by 99.6% for Mode 2. The research not only provides practical tools for antisurface target operations and simulations but also offers new perspectives and methodological references for researchers in related fields.

International Journal of Aerospace EngineeringVol. 2025(1)
Naval University of Engineering (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 11%
Robotic Path Planning Algorithms
2.55
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