Path planning of coal mine rescue robot based on blocked grid map

To address the issues of coal mine rescue robots’ path planning algorithms taking too long, producing too many redundant points, and easily falling into deadlock in complex underground environments, a grid map blocking algorithm based on type matching is proposed. This algorithm iteratively blocks p...

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Main Authors: Xiaoqiang SHAO, Mingqian LIU, Bo MA, Hao LI, Zhiyue LYU, Zehui HAN
Format: Article
Language:zho
Published: Editorial Department of Coal Science and Technology 2025-07-01
Series:Meitan kexue jishu
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Online Access:http://www.mtkxjs.com.cn/article/doi/10.12438/cst.2024-0650
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author Xiaoqiang SHAO
Mingqian LIU
Bo MA
Hao LI
Zhiyue LYU
Zehui HAN
author_facet Xiaoqiang SHAO
Mingqian LIU
Bo MA
Hao LI
Zhiyue LYU
Zehui HAN
author_sort Xiaoqiang SHAO
collection DOAJ
description To address the issues of coal mine rescue robots’ path planning algorithms taking too long, producing too many redundant points, and easily falling into deadlock in complex underground environments, a grid map blocking algorithm based on type matching is proposed. This algorithm iteratively blocks passable nodes that do not require exploration in the grid map. The blocking process matches the grid map with a subgraph type composed of defined grid nodes and their neighbors. Firstly, blockable and non-blockable grid types are defined based on the pathfinding characteristics of the path planning algorithm. Then, the model is built according to these types, assigning weight and bias to each type. Finally, each type of subgraph is matched with the initial grid map through a two-dimensional convolution operation to block nodes that do not require expansion. Blocking the input raster map before using the path planning algorithm. Blocking nodes does not disconnect the minimum cost path in the original raster map. Experimental results show that this algorithm can be applied to various grid environment maps. In real underground coal mine grid maps, compared to using the path planning algorithm alone, the proposed algorithm combined with the A* algorithm reduces total path planning time by 60.0% and the number of expansion nodes by 60.4%. When combined with the ant colony algorithm, total time is reduced by 55.8% and the number of iterations by 53.7%. The proposed algorithm significantly reduces path planning time, solves the deadlock issue, has clear advantages in complex environment maps, and ensures timely accident rescue.
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issn 0253-2336
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publisher Editorial Department of Coal Science and Technology
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spelling doaj-art-124d3e2dfe064baa8777a7add83a94eb2025-08-20T02:59:41ZzhoEditorial Department of Coal Science and TechnologyMeitan kexue jishu0253-23362025-07-0153724926110.12438/cst.2024-06502024-0650Path planning of coal mine rescue robot based on blocked grid mapXiaoqiang SHAO0Mingqian LIU1Bo MA2Hao LI3Zhiyue LYU4Zehui HAN5College of Electrical and Control Engineering, Xi’an University of Science and Technology, Xi’an 710054, ChinaCollege of Electrical and Control Engineering, Xi’an University of Science and Technology, Xi’an 710054, ChinaCollege of Electrical and Control Engineering, Xi’an University of Science and Technology, Xi’an 710054, ChinaCollege of Electrical and Control Engineering, Xi’an University of Science and Technology, Xi’an 710054, ChinaCollege of Electrical and Control Engineering, Xi’an University of Science and Technology, Xi’an 710054, ChinaCollege of Electrical and Control Engineering, Xi’an University of Science and Technology, Xi’an 710054, ChinaTo address the issues of coal mine rescue robots’ path planning algorithms taking too long, producing too many redundant points, and easily falling into deadlock in complex underground environments, a grid map blocking algorithm based on type matching is proposed. This algorithm iteratively blocks passable nodes that do not require exploration in the grid map. The blocking process matches the grid map with a subgraph type composed of defined grid nodes and their neighbors. Firstly, blockable and non-blockable grid types are defined based on the pathfinding characteristics of the path planning algorithm. Then, the model is built according to these types, assigning weight and bias to each type. Finally, each type of subgraph is matched with the initial grid map through a two-dimensional convolution operation to block nodes that do not require expansion. Blocking the input raster map before using the path planning algorithm. Blocking nodes does not disconnect the minimum cost path in the original raster map. Experimental results show that this algorithm can be applied to various grid environment maps. In real underground coal mine grid maps, compared to using the path planning algorithm alone, the proposed algorithm combined with the A* algorithm reduces total path planning time by 60.0% and the number of expansion nodes by 60.4%. When combined with the ant colony algorithm, total time is reduced by 55.8% and the number of iterations by 53.7%. The proposed algorithm significantly reduces path planning time, solves the deadlock issue, has clear advantages in complex environment maps, and ensures timely accident rescue.http://www.mtkxjs.com.cn/article/doi/10.12438/cst.2024-0650coal mine rescue robotgrid mapblocking grid mapa* algorithmant colony optimization
spellingShingle Xiaoqiang SHAO
Mingqian LIU
Bo MA
Hao LI
Zhiyue LYU
Zehui HAN
Path planning of coal mine rescue robot based on blocked grid map
Meitan kexue jishu
coal mine rescue robot
grid map
blocking grid map
a* algorithm
ant colony optimization
title Path planning of coal mine rescue robot based on blocked grid map
title_full Path planning of coal mine rescue robot based on blocked grid map
title_fullStr Path planning of coal mine rescue robot based on blocked grid map
title_full_unstemmed Path planning of coal mine rescue robot based on blocked grid map
title_short Path planning of coal mine rescue robot based on blocked grid map
title_sort path planning of coal mine rescue robot based on blocked grid map
topic coal mine rescue robot
grid map
blocking grid map
a* algorithm
ant colony optimization
url http://www.mtkxjs.com.cn/article/doi/10.12438/cst.2024-0650
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AT haoli pathplanningofcoalminerescuerobotbasedonblockedgridmap
AT zhiyuelyu pathplanningofcoalminerescuerobotbasedonblockedgridmap
AT zehuihan pathplanningofcoalminerescuerobotbasedonblockedgridmap