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.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Siciliano, B., Khatib, O.: Springer Handbook of Robotics. Springer, Cham (2016). https://doi.org/10.1007/978-3-319-32552-1
Aghili, F., Salerno, A.: Driftless 3-D attitude determination and positioning of mobile robots by integration of IMU with two RTK GPSs. IEEE/ASME Trans. Mechatron. 18(1), 21–31 (2013)
Kushleyev, A., Mellinger, D., Powers, C., Kumar, V.: Towards a swarm of agile micro quadrotors. Auton. Robots 35(4), 287–300 (2013)
Kanellakis, C., Nikolakopoulos, G.: Evaluation of visual localization systems in underground mining. In: 2016 24th Mediterranean Conference on Control and Automation (MED), pp. 539–544. IEEE(2016)
Menggang, L., Hua, Z., Shaoze, Y., Lei, W., Chaoquan, T.: Efficient laser-based 3D SLAM for coal mine rescue robots. IEEE Access 7, 14124–14138 (2019). https://doi.org/10.1109/access.2018.2889304
Einicke, G.A., Ralston, J.C., Hargrave, C.O.: Longwall mining automation an application of minimum-variance smoothing [Applications of Control]. IEEE Control Syst. Mag. 28(6), 28–37 (2008)
Paraszczak, J., Gustafson, A., Schunnesson, H.: Technical and operational aspects of autonomous LHD application in metal mines. Int. J. Surf. Min. Reclam. Environ. 29(5), 391–403 (2015)
Liu, Z., Li, C., Wu, D.: A wireless sensor network based personnel positioning scheme in coal mines with blind areas. Sensors 10(11), 9891–9918 (2010)
Longkang, W., Baisheng, N., Ruming, Z.: ZigBee-based positioning system for coal miners. Proc. Eng. 26, 2406–2414 (2011)
Bulin, M. A., Fan, Y.: The design and implementation of WiFi localization GIS for mine. J. Xi’an Univ. Sci. Technol. 3 (2012)
Yang, H., Luo, T., Li, W., et al.: A stable SINS/UWB integrated positioning method of shearer based on the multi-model intelligent switching algorithm. IEEE Access 7, 29128–29138 (2019)
Fang, X., Wang, C., Nguyen, T.M., et al.: Model-free approach for sensor network localization with noisy distance measurement. In: 2018 15th International Conference on Control, Automation, Robotics and Vision (ICARCV), pp. 1973–1978. IEEE (2018)
Zhou, Y.: An efficient least-squares trilateration algorithm for mobile robot localization. In: IEEE International Conference on Intelligent Robots and Systems, IROS 2009, pp. 3474–3479. IEEE/RSJ (2009)
Agarwal, S., Mierle, K.: Ceres solver (2013). https://github.com/ceres-solver/ceres-solver
Moore, T., Stouch, D.: A generalized extended Kalman Filter implementation for the robot operating system. In: Menegatti, E., Michael, N., Berns, K., Yamaguchi, H. (eds.) Intelligent Autonomous Systems 13. AISC, vol. 302, pp. 335–348. Springer, Cham (2016). https://doi.org/10.1007/978-3-319-08338-4_25
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.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2019 Springer Nature Switzerland AG
About this paper
Cite this paper
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
Download citation
DOI: https://doi.org/10.1007/978-3-030-27526-6_23
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-27525-9
Online ISBN: 978-3-030-27526-6
eBook Packages: Computer ScienceComputer Science (R0)