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Research and Application of Positioning Technology for Mine Inspection Robot Based on UWB and IMU Fusion
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Wenbo KUAI1, 2, Hongwei ZHANG1, 2, Zhonghui PU3, Wei XIAO3
Mining Research and Development | 2025, 45(8) : 200 - 208
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Mining Research and Development | 2025, 45(8): 200-208
Research and Application of Positioning Technology for Mine Inspection Robot Based on UWB and IMU Fusion
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Wenbo KUAI1, 2, Hongwei ZHANG1, 2, Zhonghui PU3, Wei XIAO3
Affiliations
  • 1.School of Electrical Engineering and Automation, Henan Polytechnic University, Jiaozuo, Henan 454003, China
  • 2.Henan Key Laboratory of Intelligent Detection and Control of Coal Mine Equipment, Jiaozuo, Henan 454003, China
  • 3.Henan Longyu Energy Co., Ltd., Shangqiu, Henan 476600, China
Published: 2025-08-25
Outline
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A fusion positioning method based on UWB (Ultra Wideband) and IMU (Inertial Measurement Unit) was proposed to address the issues of low positioning accuracy and poor real-time performance of underground inspection robots in mines due to environmental influences. Firstly, the UWB ranging module was used to measure the distance between the inspection robot and the UWB base station. Secondly, a GRU (Gated Recurrent Unit) neural network model was constructed, and the UWB measurement distance and real distance were input into the neural network model for training, resulting in a GRU correction model. Then, the GRU neural network was used to correct the model for the measured distance, suppressing NLOS (Non-Line of Sight) distance errors in complex environments and obtaining more accurate distances than before. Finally, the corrected distance information was combined with the data provided by the IMU through ESKF (Error State Kalman Filter) to construct the error state equation and measurement equation, respectively, to evolve and update the system's error state and calculate more accurate position coordinates. The experimental results show that under three different NLOS environments, the corrected static experimental positioning accuracy is improved by 6.09%, 16.56% and 18.89% respectively, and the positioning accuracy in the composite scene is improved by 11.36% compared to before. In the dynamic experiment, the corrected average positioning accuracy is improved by 11.10% compared to before. By correcting the pseudo range measured under non line of sight, the impact of non line of sight can be reduced and the positioning accuracy can be improved.

Inspection robot  /  Fusion positioning method  /  Inertial measurement unit  /  GRU neural network  /  Non-line of sight
蒯文博, 张宏伟, 蒲忠辉, 肖卫. 基于UWB和IMU融合的矿井巡检机器人定位技术研究与应用. 矿业研究与开发, 2025 , 45 (8) : 200 -208 .
Wenbo KUAI, Hongwei ZHANG, Zhonghui PU, Wei XIAO. Research and Application of Positioning Technology for Mine Inspection Robot Based on UWB and IMU Fusion[J]. Mining Research and Development, 2025 , 45 (8) : 200 -208 .
Year 2025 volume 45 Issue 8
82
36
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Article Info
  • Receive Date:2024-09-09
  • Online Date:2026-10-28
  • Published:2025-08-25
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  • Received:2024-09-09
Funding
Affiliations
    1.School of Electrical Engineering and Automation, Henan Polytechnic University, Jiaozuo, Henan 454003, China
    2.Henan Key Laboratory of Intelligent Detection and Control of Coal Mine Equipment, Jiaozuo, Henan 454003, China
    3.Henan Longyu Energy Co., Ltd., Shangqiu, Henan 476600, China
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表12种不同金属材料的力学参数
科
Family
属数
Number of
genus
种数
Number of
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Percentage of
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Number of
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Percentage of total
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鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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