Autonomous Driving of Trackless Transport Vehicles: A Case Study in Underground Mines

The introduction of autonomous vehicles in underground mine trackless transportation systems can significantly reduce safety risks for personnel in production operations and improve transportation efficiency. Current autonomous mining vehicle technology is characterized by complex algorithms and high deployment costs, which limit its widespread application in underground mines. This paper proposes a light-band-guided autonomous driving method for trackless mining vehicles, where a continuous, digitally controllable light band is installed at the tunnel ceiling to provide uninterrupted vehicle guidance. The light band is controlled by an independent hardware system and uses different colors to indicate vehicle movement status, enabling vehicles to navigate simply by following the designated light trajectory. We designed the necessary hardware and software systems and built a physical model for validation. The system enabled multiple vehicles to be guided simultaneously within the same area to perform diverse transportation tasks according to operational requirements. The model vehicles maintained a safe distance from tunnel walls. In GPS-denied environments, positioning was achieved using dead reckoning and periodic location updates at designated points based on the known light-band trajectory. The proposed method demonstrates high potential for practical applications.

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Publication Details

Journal
Sensors
Published
2025-05-19
DOI
https://doi.org/10.3390/s25103189
Citations
1
Primary Topic
Robotic Path Planning Algorithms
Type
article
Field-Weighted Citation Impact
1.28

Funders

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article

Autonomous Driving of Trackless Transport Vehicles: A Case Study in Underground Mines

Yunjie Sun, Xiaoquan Li, Ying Xu, Linxin Zhang et al.
1 citations
Sensors
Robotic Path Planning Algorithms
1.28
article

Autonomous Driving of Trackless Transport Vehicles: A Case Study in Underground Mines

Yunjie Sun, Xiaoquan Li, Ying Xu, Linxin Zhang, Junhong Liu
article en
1 citations

Abstract

The introduction of autonomous vehicles in underground mine trackless transportation systems can significantly reduce safety risks for personnel in production operations and improve transportation efficiency. Current autonomous mining vehicle technology is characterized by complex algorithms and high deployment costs, which limit its widespread application in underground mines. This paper proposes a light-band-guided autonomous driving method for trackless mining vehicles, where a continuous, digitally controllable light band is installed at the tunnel ceiling to provide uninterrupted vehicle guidance. The light band is controlled by an independent hardware system and uses different colors to indicate vehicle movement status, enabling vehicles to navigate simply by following the designated light trajectory. We designed the necessary hardware and software systems and built a physical model for validation. The system enabled multiple vehicles to be guided simultaneously within the same area to perform diverse transportation tasks according to operational requirements. The model vehicles maintained a safe distance from tunnel walls. In GPS-denied environments, positioning was achieved using dead reckoning and periodic location updates at designated points based on the known light-band trajectory. The proposed method demonstrates high potential for practical applications.

SensorsVol. 25(10)
Guangxi University (CN)
University of Technology Sydney, National Natural Science Foundation of China
Openalex Percentile: Top 20%
Robotic Path Planning Algorithms
1.28
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