A cyber-physical system based unmanned ground vehicles for safety inspection and rescue support in an underground mine

Purpose The unmanned ground vehicle (UGV) described in this manuscript is a robot designed by the authors to map the underground mine environments. The UGV works to develop a computational intelligence-based cyber-physical system (CPS)-based analytical framework for mining operations. The UGV demonstrated excellent semi-autonomous navigation capabilities in the absence of GNSS signals. The UGV has a suite that works in unison to provide relevant information. These sensors are integrated to form a robust sensor fusion-based architecture, creating a CPS with a wide range of capabilities such as data acquisition and navigation in challenging underground environments. UGVs can be used to enhance the efficacy of safety inspections, rescue during underground emergencies and assist miners in hazardous conditions. Design/methodology/approach In this research, an UGV was constructed whose operations are enabled by sensors including a D415i Red Blue Green (RGB) depth camera, a LiDAR, a FLIR C5 infrared camera and smart air quality sensors. This sensor fusion-based architecture forms a CPS. Data obtained remotely are processed by deep learning algorithms to achieve overall capabilities such as real-time image analysis for miner identification, object detection, posture analysis and identifying threats of roof falls and overhangs. Simultaneous localization and mapping (SLAM) algorithms create a 3D map, facilitate autonomous navigation and build a decision support system for delivering mine rescue support. Findings The aim of this study is to include this capacity in training situations when it has been validated and authorized by the Directorate General of Mines Safety (DGMS) Indian government regulatory agency for safety in mines and oil fields. The longwall demo mine, at IIT (ISM) is being used as the site of the first operations. Once approved by the respective enforcement agencies, this technology and the accompanying rescue and training process can be used in underground operations. Originality/value In fact, this paper is the first attempt at remotely operated UGVs based on CPSs, the CPS–UGV in Indian mine conditions, so as to revolutionize Indian mines based on the idea of Industry 4.0.

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Publication Details

Journal
International Journal of Intelligent Unmanned Systems
Published
2025-02-06
DOI
https://doi.org/10.1108/ijius-07-2024-0202
Citations
1
Primary Topic
Mineral Processing and Grinding
Type
article
Field-Weighted Citation Impact
0.71
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article

A cyber-physical system based unmanned ground vehicles for safety inspection and rescue support in an underground mine

Ayush Ranjan, Tushar Sandhan, Laxmidhar Behera, Pratibha Sharma et al.
1 citations
International Journal of Intelligent Unmanned Systems
Mineral Processing and Grinding
0.71
article

A cyber-physical system based unmanned ground vehicles for safety inspection and rescue support in an underground mine

Ayush Ranjan, Tushar Sandhan, Laxmidhar Behera, Pratibha Sharma, Sidhartha Watsa, Ashish Kumar, Atul Singh, Siddhartha Agarwal, Jyothi Swaroop Kasina
article en
1 citations

Abstract

Purpose The unmanned ground vehicle (UGV) described in this manuscript is a robot designed by the authors to map the underground mine environments. The UGV works to develop a computational intelligence-based cyber-physical system (CPS)-based analytical framework for mining operations. The UGV demonstrated excellent semi-autonomous navigation capabilities in the absence of GNSS signals. The UGV has a suite that works in unison to provide relevant information. These sensors are integrated to form a robust sensor fusion-based architecture, creating a CPS with a wide range of capabilities such as data acquisition and navigation in challenging underground environments. UGVs can be used to enhance the efficacy of safety inspections, rescue during underground emergencies and assist miners in hazardous conditions. Design/methodology/approach In this research, an UGV was constructed whose operations are enabled by sensors including a D415i Red Blue Green (RGB) depth camera, a LiDAR, a FLIR C5 infrared camera and smart air quality sensors. This sensor fusion-based architecture forms a CPS. Data obtained remotely are processed by deep learning algorithms to achieve overall capabilities such as real-time image analysis for miner identification, object detection, posture analysis and identifying threats of roof falls and overhangs. Simultaneous localization and mapping (SLAM) algorithms create a 3D map, facilitate autonomous navigation and build a decision support system for delivering mine rescue support. Findings The aim of this study is to include this capacity in training situations when it has been validated and authorized by the Directorate General of Mines Safety (DGMS) Indian government regulatory agency for safety in mines and oil fields. The longwall demo mine, at IIT (ISM) is being used as the site of the first operations. Once approved by the respective enforcement agencies, this technology and the accompanying rescue and training process can be used in underground operations. Originality/value In fact, this paper is the first attempt at remotely operated UGVs based on CPSs, the CPS–UGV in Indian mine conditions, so as to revolutionize Indian mines based on the idea of Industry 4.0.

International Journal of Intelligent Unmanned SystemsVol. 13(1)
Pennsylvania State University (US), Indian Institute of Technology Dhanbad (IN), Intelligent Systems Research (United States) (US), Indian Institute of Technology Kanpur (IN)
Openalex Percentile: Top 36%
Mineral Processing and Grinding
0.71
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