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Visual-Inertial Fusion Localization Algorithm for Escort Inspection Robots
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Kaile WANG1, Yangrui CHENG2
Mining and Metallurgical Engineering | 2026, 46(3) : 54 - 60
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Mining and Metallurgical Engineering | 2026, 46(3): 54-60
• SPECIAL TOPIC ON BREAKTHROUGHS IN KEY TECHNOLOGIES AND COORDINATED DEVELOPMENT OF INDUSTRIAL CHAINS FOR DEEP-SEA MINERAL RESOURCE EXPLOITATION •
Visual-Inertial Fusion Localization Algorithm for Escort Inspection Robots
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Kaile WANG1, Yangrui CHENG2
Affiliations
  • 1.School of Mechanical and Electrical Engineering, Central South University, Changsha 410083, Hunan, China
  • 2.Changsha Research Institute of Mining and Metallurgy Co., Ltd., Changsha 410012, Hunan, China
doi: 10.3969/j.issn.0253-6099.2026.03.006
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A loosely coupled visual-inertial fusion positioning algorithm based on Extended Kalman Filter (EKF) is proposed, which adopts a visual algorithm for relative pose estimation. It takes a mining vehicle as an observation target to acquire low-frequency and high-precision global coordinates, and then fuses these data with high-frequency global coordinate information from the inertial navigation system (INS). Simulation results show that compared with the INS, the proposed fusion algorithm leads to the average position error reduced from 1.309 m to 0.026 m for rectangular trajectory and from 1.749 m to 0.028 m for serpentine trajectory, indicating a remarkable improvement. Further experiments have verified the feasibility of the proposed algorithm, which provides technical support for cooperative operation of robots under complex deep-sea working conditions.

inertial navigation  /  visual sensor  /  deep-sea positioning  /  visual-inertial fusion  /  Extended Kalman Filter  /  relative pose estimation  /  underwater robot positioning
王凯乐, 程阳锐. 基于视觉-惯导融合的伴随式巡检机器人定位方法研究. 矿冶工程杂志, 2026 , 46 (3) : 54 -60 . DOI: 10.3969/j.issn.0253-6099.2026.03.006
Kaile WANG, Yangrui CHENG. Visual-Inertial Fusion Localization Algorithm for Escort Inspection Robots[J]. Mining and Metallurgical Engineering, 2026 , 46 (3) : 54 -60 . DOI: 10.3969/j.issn.0253-6099.2026.03.006
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Year 2026 volume 46 Issue 3
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doi: 10.3969/j.issn.0253-6099.2026.03.006
  • Receive Date：2026-03-13
  • Online Date：2026-10-08
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  • Received：2026-03-13
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Affiliations
    1.School of Mechanical and Electrical Engineering, Central South University, Changsha 410083, Hunan, China
    2.Changsha Research Institute of Mining and Metallurgy Co., Ltd., Changsha 410012, Hunan, China
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表12种不同金属材料的力学参数
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Family		 属数
Number of
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Number of
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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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