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Algorithm for Automatic Rod Feeding and Positioning Error Compensation for Underground Drilling Robots in Coal Mines

In the pursuit of automating the entire underground drilling process in coal mines, the automatic rod feeding technology of drilling robots plays a crucial role. However, the current lack of positional accuracy in automatic rod feeding leads to frequent accidents. To address this issue, this paper p...

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Detalles Bibliográficos
Autores principales: Lu, Qianhai, Kong, Lingfei, Peng, Guangyu, Jia, Wang, Jin, Sun, Dai, Chenyu, Zhu, Qianxiang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10490727/
https://www.ncbi.nlm.nih.gov/pubmed/37687984
http://dx.doi.org/10.3390/s23177530
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author Lu, Qianhai
Kong, Lingfei
Peng, Guangyu
Jia, Wang
Jin, Sun
Dai, Chenyu
Zhu, Qianxiang
author_facet Lu, Qianhai
Kong, Lingfei
Peng, Guangyu
Jia, Wang
Jin, Sun
Dai, Chenyu
Zhu, Qianxiang
author_sort Lu, Qianhai
collection PubMed
description In the pursuit of automating the entire underground drilling process in coal mines, the automatic rod feeding technology of drilling robots plays a crucial role. However, the current lack of positional accuracy in automatic rod feeding leads to frequent accidents. To address this issue, this paper presents an algorithm for compensating positioning errors in automatic rod feeding. The algorithm is based on a theoretical mathematical model and manual teaching methods. To enhance the positioning accuracy, we first calibrate the pull rope sensor to correct its measurement precision. Subsequently, we establish a theoretical mathematical model for rod feeding positions by employing spatial coordinate system transformations. We determine the target rod feeding position using a manual teaching-based approach. Furthermore, we analyze the relationship between the theoretical rod delivery position and the target rod delivery position and propose an anisotropic spatial difference compensation technique that considers both distance and direction. Finally, we validate the feasibility of our proposed algorithm through automatic rod feeding tests conducted on a coal mine underground drilling robot. The results demonstrate that our algorithm significantly improves the accuracy of rod feeding positions for coal mine underground drilling robots.
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spelling pubmed-104907272023-09-09 Algorithm for Automatic Rod Feeding and Positioning Error Compensation for Underground Drilling Robots in Coal Mines Lu, Qianhai Kong, Lingfei Peng, Guangyu Jia, Wang Jin, Sun Dai, Chenyu Zhu, Qianxiang Sensors (Basel) Article In the pursuit of automating the entire underground drilling process in coal mines, the automatic rod feeding technology of drilling robots plays a crucial role. However, the current lack of positional accuracy in automatic rod feeding leads to frequent accidents. To address this issue, this paper presents an algorithm for compensating positioning errors in automatic rod feeding. The algorithm is based on a theoretical mathematical model and manual teaching methods. To enhance the positioning accuracy, we first calibrate the pull rope sensor to correct its measurement precision. Subsequently, we establish a theoretical mathematical model for rod feeding positions by employing spatial coordinate system transformations. We determine the target rod feeding position using a manual teaching-based approach. Furthermore, we analyze the relationship between the theoretical rod delivery position and the target rod delivery position and propose an anisotropic spatial difference compensation technique that considers both distance and direction. Finally, we validate the feasibility of our proposed algorithm through automatic rod feeding tests conducted on a coal mine underground drilling robot. The results demonstrate that our algorithm significantly improves the accuracy of rod feeding positions for coal mine underground drilling robots. MDPI 2023-08-30 /pmc/articles/PMC10490727/ /pubmed/37687984 http://dx.doi.org/10.3390/s23177530 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Lu, Qianhai
Kong, Lingfei
Peng, Guangyu
Jia, Wang
Jin, Sun
Dai, Chenyu
Zhu, Qianxiang
Algorithm for Automatic Rod Feeding and Positioning Error Compensation for Underground Drilling Robots in Coal Mines
title Algorithm for Automatic Rod Feeding and Positioning Error Compensation for Underground Drilling Robots in Coal Mines
title_full Algorithm for Automatic Rod Feeding and Positioning Error Compensation for Underground Drilling Robots in Coal Mines
title_fullStr Algorithm for Automatic Rod Feeding and Positioning Error Compensation for Underground Drilling Robots in Coal Mines
title_full_unstemmed Algorithm for Automatic Rod Feeding and Positioning Error Compensation for Underground Drilling Robots in Coal Mines
title_short Algorithm for Automatic Rod Feeding and Positioning Error Compensation for Underground Drilling Robots in Coal Mines
title_sort algorithm for automatic rod feeding and positioning error compensation for underground drilling robots in coal mines
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10490727/
https://www.ncbi.nlm.nih.gov/pubmed/37687984
http://dx.doi.org/10.3390/s23177530
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