Detour-Straddle 3D-like path planning of unmanned mining truck in open pit mines based on optimized ant colony algorithm

With the continuous advancement of intelligent mine construction in China, the unmanned transportation link has developed into an important part of the intelligent mine system. Scenarios such as the loading and unloading area of open-pit mines are usually unstructured operating areas with complex te...

Full description

Saved in:
Bibliographic Details
Main Authors: Mingyu GAO, Jiusheng BAO, Yan YIN, Deping HU, Kekun ZHANG, Chenzhong ZHU, Maosen WANG, Kai WANG
Format: Article
Language:zho
Published: Editorial Department of Coal Science and Technology 2025-06-01
Series:Meitan kexue jishu
Subjects:
Online Access:http://www.mtkxjs.com.cn/article/doi/10.12438/cst.2024-0950
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1849431039743623168
author Mingyu GAO
Jiusheng BAO
Yan YIN
Deping HU
Kekun ZHANG
Chenzhong ZHU
Maosen WANG
Kai WANG
author_facet Mingyu GAO
Jiusheng BAO
Yan YIN
Deping HU
Kekun ZHANG
Chenzhong ZHU
Maosen WANG
Kai WANG
author_sort Mingyu GAO
collection DOAJ
description With the continuous advancement of intelligent mine construction in China, the unmanned transportation link has developed into an important part of the intelligent mine system. Scenarios such as the loading and unloading area of open-pit mines are usually unstructured operating areas with complex terrain environment and many obstacles. As the main tool for material transportation of open-pit mines, unmanned mining trucks are more difficult to plan paths in this scenario due to their size, heavy load and other characteristics. In order to solve the problem of low driving efficiency and poor path quality caused by excessive detour during path planning, a “3D-like” path planning method based on optimized ant colony algorithm was proposed, and its effectiveness was verified by simulation and experiment. Firstly, a 3D map construction method based on laser point cloud is designed, and the valid point cloud data after filtering and registration are rasterized and the grid height is calculated, and the 3D map containing obstacle height information is obtained. Secondly, taking unmanned mining truck as the research object, a 3D collision detection method is designed, which can judge the conflict relationship between obstacles and vehicle body in the horizontal and vertical aspects respectively, and according to the structural characteristics of mining truck and road conditions, a parallel crossing strategy is developed to directly cross over obstacles that are not threatening to vehicles, which can effectively improve the passing efficiency of mining truck under the premise of ensuring safety. Then, the initial pheromone distribution of ant colony algorithm is optimized to improve the goal orientation of the algorithm, and the optimal and worst path is considered in the improved pheromone updating strategy to improve the performance and efficiency of path search. Adaptive multi-step movement mode is introduced, and a multi-objective heuristic function is designed to introduce cross-obstacle evaluation. The simulation results show that: After optimization, the path length of the ant colony algorithm is shortened by 16.53% and 16.79% respectively in the scenario with fewer and more obstacles. Moreover, the path quality is effectively improved by reducing the path inflection point, making the path generated by the algorithm more in line with the actual demand. Finally, by setting up a multi-obstacle scenario to simulate the unstructured area of an open-pit mine, the real vehicle simulation test is carried out. The results show that the unmanned mining truck test vehicle equipped with the optimized ant colony algorithm can cross some obstacles, and the passing efficiency in the scene with fewer obstacles is increased by 20.53%, and the passing efficiency in the scene with more obstacles is increased by 31.62%, without any friction with obstacles. Therefore, the proposed parallel 3D path planning method based on optimized ant colony algorithm can effectively shorten the path length, improve the search efficiency and path quality, and give full play to the characteristics of wide body and high underbody of unmanned mining trucks under the premise of ensuring safety. The research results provide a theoretical reference for the development and application of open-pit truck unmanned driving technology.
format Article
id doaj-art-5823e61b5f68416cb03d2bd5bcf0c973
institution Kabale University
issn 0253-2336
language zho
publishDate 2025-06-01
publisher Editorial Department of Coal Science and Technology
record_format Article
series Meitan kexue jishu
spelling doaj-art-5823e61b5f68416cb03d2bd5bcf0c9732025-08-20T03:27:47ZzhoEditorial Department of Coal Science and TechnologyMeitan kexue jishu0253-23362025-06-0153S139941110.12438/cst.2024-09502024-0950Detour-Straddle 3D-like path planning of unmanned mining truck in open pit mines based on optimized ant colony algorithmMingyu GAO0Jiusheng BAO1Yan YIN2Deping HU3Kekun ZHANG4Chenzhong ZHU5Maosen WANG6Kai WANG7School of Mechanical and Electrical Engineering, China University of Mining and Technology, Xuzhou 221116, ChinaSchool of Mechanical and Electrical Engineering, China University of Mining and Technology, Xuzhou 221116, ChinaSchool of Mechanical and Electrical Engineering, China University of Mining and Technology, Xuzhou 221116, ChinaXuzhou XCMG Heavy Vehicle Co., Ltd., Xuzhou 221112, ChinaSchool of Mechanical and Electrical Engineering, China University of Mining and Technology, Xuzhou 221116, ChinaXuzhou XCMG Heavy Vehicle Co., Ltd., Xuzhou 221112, ChinaSchool of Mechanical and Electrical Engineering, China University of Mining and Technology, Xuzhou 221116, ChinaSchool of Mechanical and Electrical Engineering, China University of Mining and Technology, Xuzhou 221116, ChinaWith the continuous advancement of intelligent mine construction in China, the unmanned transportation link has developed into an important part of the intelligent mine system. Scenarios such as the loading and unloading area of open-pit mines are usually unstructured operating areas with complex terrain environment and many obstacles. As the main tool for material transportation of open-pit mines, unmanned mining trucks are more difficult to plan paths in this scenario due to their size, heavy load and other characteristics. In order to solve the problem of low driving efficiency and poor path quality caused by excessive detour during path planning, a “3D-like” path planning method based on optimized ant colony algorithm was proposed, and its effectiveness was verified by simulation and experiment. Firstly, a 3D map construction method based on laser point cloud is designed, and the valid point cloud data after filtering and registration are rasterized and the grid height is calculated, and the 3D map containing obstacle height information is obtained. Secondly, taking unmanned mining truck as the research object, a 3D collision detection method is designed, which can judge the conflict relationship between obstacles and vehicle body in the horizontal and vertical aspects respectively, and according to the structural characteristics of mining truck and road conditions, a parallel crossing strategy is developed to directly cross over obstacles that are not threatening to vehicles, which can effectively improve the passing efficiency of mining truck under the premise of ensuring safety. Then, the initial pheromone distribution of ant colony algorithm is optimized to improve the goal orientation of the algorithm, and the optimal and worst path is considered in the improved pheromone updating strategy to improve the performance and efficiency of path search. Adaptive multi-step movement mode is introduced, and a multi-objective heuristic function is designed to introduce cross-obstacle evaluation. The simulation results show that: After optimization, the path length of the ant colony algorithm is shortened by 16.53% and 16.79% respectively in the scenario with fewer and more obstacles. Moreover, the path quality is effectively improved by reducing the path inflection point, making the path generated by the algorithm more in line with the actual demand. Finally, by setting up a multi-obstacle scenario to simulate the unstructured area of an open-pit mine, the real vehicle simulation test is carried out. The results show that the unmanned mining truck test vehicle equipped with the optimized ant colony algorithm can cross some obstacles, and the passing efficiency in the scene with fewer obstacles is increased by 20.53%, and the passing efficiency in the scene with more obstacles is increased by 31.62%, without any friction with obstacles. Therefore, the proposed parallel 3D path planning method based on optimized ant colony algorithm can effectively shorten the path length, improve the search efficiency and path quality, and give full play to the characteristics of wide body and high underbody of unmanned mining trucks under the premise of ensuring safety. The research results provide a theoretical reference for the development and application of open-pit truck unmanned driving technology.http://www.mtkxjs.com.cn/article/doi/10.12438/cst.2024-0950open pit minesunmanned mining truckpath planning3d-like mapoptimized ant colony algorithm
spellingShingle Mingyu GAO
Jiusheng BAO
Yan YIN
Deping HU
Kekun ZHANG
Chenzhong ZHU
Maosen WANG
Kai WANG
Detour-Straddle 3D-like path planning of unmanned mining truck in open pit mines based on optimized ant colony algorithm
Meitan kexue jishu
open pit mines
unmanned mining truck
path planning
3d-like map
optimized ant colony algorithm
title Detour-Straddle 3D-like path planning of unmanned mining truck in open pit mines based on optimized ant colony algorithm
title_full Detour-Straddle 3D-like path planning of unmanned mining truck in open pit mines based on optimized ant colony algorithm
title_fullStr Detour-Straddle 3D-like path planning of unmanned mining truck in open pit mines based on optimized ant colony algorithm
title_full_unstemmed Detour-Straddle 3D-like path planning of unmanned mining truck in open pit mines based on optimized ant colony algorithm
title_short Detour-Straddle 3D-like path planning of unmanned mining truck in open pit mines based on optimized ant colony algorithm
title_sort detour straddle 3d like path planning of unmanned mining truck in open pit mines based on optimized ant colony algorithm
topic open pit mines
unmanned mining truck
path planning
3d-like map
optimized ant colony algorithm
url http://www.mtkxjs.com.cn/article/doi/10.12438/cst.2024-0950
work_keys_str_mv AT mingyugao detourstraddle3dlikepathplanningofunmannedminingtruckinopenpitminesbasedonoptimizedantcolonyalgorithm
AT jiushengbao detourstraddle3dlikepathplanningofunmannedminingtruckinopenpitminesbasedonoptimizedantcolonyalgorithm
AT yanyin detourstraddle3dlikepathplanningofunmannedminingtruckinopenpitminesbasedonoptimizedantcolonyalgorithm
AT depinghu detourstraddle3dlikepathplanningofunmannedminingtruckinopenpitminesbasedonoptimizedantcolonyalgorithm
AT kekunzhang detourstraddle3dlikepathplanningofunmannedminingtruckinopenpitminesbasedonoptimizedantcolonyalgorithm
AT chenzhongzhu detourstraddle3dlikepathplanningofunmannedminingtruckinopenpitminesbasedonoptimizedantcolonyalgorithm
AT maosenwang detourstraddle3dlikepathplanningofunmannedminingtruckinopenpitminesbasedonoptimizedantcolonyalgorithm
AT kaiwang detourstraddle3dlikepathplanningofunmannedminingtruckinopenpitminesbasedonoptimizedantcolonyalgorithm