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IMU-Aided Ultra-wideband Based Localization for Coal Mine Robots

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 11740))

Abstract

Robotic mining equipment is playing an increasingly important role in coal mine operations. Due to the complexity of underground occlusion environment, the localization methods available are limited, which restricts the development of coal mine robots (CMRs). Ultra Wideband (UWB) is a promising positioning sensor with accurate ranging capacity, but it needs to overcome the transient signal loss caused by multipath effect and metal block in coal mine. Range measurements from UWB can only provide 3 degrees of freedom (DOF) position without orientation, which is not enough to operation for CMRs under space-constrained coal mine. In this paper, a pseudo-GPS positioning system composed by UWB range measurements is proposed to provide the position of CMRs. Additionally, an Error State Kalman Filter (ESKF) is used for fusing measurements from Inertial Measurement Unit (IMU) and UWB positioning system. The complete 6 DOF state estimation is established, and the biases of IMU and the calibration parameters of IMU w.r.t. the UWB mobile node are also estimated online to accommodate the long-term operation in underground harsh environment. Experiments in different motion conditions show that our approach can provide robust and precise 6 DOF state estimation for CMRs.

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Acknowledgment

This work is supported by the National Key Research and Development Program of China (No. 2018YFC0808000) and the Priority Academic Program Development of Jiangsu Higher Education Institutions (PAPD), China.

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Correspondence to Hua Zhu .

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Li, Mg., Zhu, H., You, Sz., Wang, L., Zhang, Z., Tang, Cq. (2019). IMU-Aided Ultra-wideband Based Localization for Coal Mine Robots. In: Yu, H., Liu, J., Liu, L., Ju, Z., Liu, Y., Zhou, D. (eds) Intelligent Robotics and Applications. ICIRA 2019. Lecture Notes in Computer Science(), vol 11740. Springer, Cham. https://doi.org/10.1007/978-3-030-27526-6_23

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  • DOI: https://doi.org/10.1007/978-3-030-27526-6_23

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-27525-9

  • Online ISBN: 978-3-030-27526-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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