Chapter
Jun 29, 2020
13th Asia Pacific Transportation Development Conference

Inertial Measurement System for Track Alignment Inspection Based on Machine Vision

Publication: Resilience and Sustainable Transportation Systems

ABSTRACT

Track alignment inspection is one of the most important methods to ensure safe transportation. Due to the cumulative error of the gyroscope and the accelerometer, the conventional inertial measurement has lower accuracy under the low speed. In order to solve this problem, a novel inspected method for railway space curve based on multi-sensors fusion of machine vision and inertial measurement is proposed. By using extended Kalman filter, the fusion of the machine vision and inertia information is obtained. Moreover, the inspected performance of the proposed method is investigated by experiment. Compared with the method of conventional inertial measurement, the result demonstrate that the new method has higher accuracy. Furthermore, it is found that the measurement accuracy of the proposed method has improved nearly 10 times.

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ACKNOWLEDGEMENT

This research was funded by National Natural Science Foundation of China [Grant No.: 51907117,51975347], and the Shanghai Committee of Science and Technology [Grant No.: 18030501300].

REFERENCES

Chen, P., Peng, Z., Li, D., Yang, L. (2016), An improved augmented reality system based on andar. J. Vis. Commun. Image Represent., 37, 63–69.
Chesneau, C. I., Hillion, M., Prieur, C. (2016), Motion Estimation of a Rigid Body with an EKFU sing Magneto-Inertial Measurements. In Proceedings of the IEEE 2016 International Conference on Indoor Positioning and Indoor Navigation (IPIN), Alcala de Henares, pp. 1–6.
Cui, G., Wang, J., Li, J. (2014), Robust multilane detection and tracking in urban scenarios based on LIDAR and mono-vision. IET Image Process. 8, 269–279.
Daponte, P., De Vito, L., Picariello, F., Riccio, M. (2014), State of the art and future developments of the augmented reality for measurement applications. Measurement 57, 53–70
El-Sheimy, N., Hou, H., Niu, X. (2008), Analysis and modeling of inertial sensors using Allan variance. IEEE Trans. Instrum. Meas. 57, 140–149.
Erdem, A.T., Ercan, A.O. (2015), Fusing inertial sensor data in an extended kalman filter for 3D camera tracking. IEEE Trans. Image Process. 2015, 24, 538–548
Fang, Y., Chen, L., Zheng, S. B., Zhang, G. F. (2013), Condition monitoring of rail vehicle suspension system based on parameter estimation. Journal of the China Railway Society, Vol. 35, Issue 5, p. 15-20.
Forster, C., Carlone, L., Dellaert, F., Scaramuzza, D. (2015), On-Manifold Preintegration Theory for Fast and Accurate Visual-Inertial Navigation. arXiv:1512.02363.
Guo, C.; Roumeliotis, S.I. (2013), IMU-RGBD Camera Navigation Using Point and Plane Features. In Proceedings of the 2013 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Tokyo, Japan, pp. 3164–3171.
Kumar, K., Reddy, P.K., Narendra, N., Swamy, P., Varghese, A., Chandra, M.G., Balamuralidhar, P. (2014), An improved tracking using IMU and vision fusion for mobile augmented reality applications. Int. J. Multimed. 6, 13–29.
Lele Peng, Shubin Zheng, Xiaodong Chai, Liming Li. (2018), A novel tangent error maximum power point tracking algorithm for photovoltaic system under fast multi-changing solar irradiances[J]. Applied Energy, 210.
Leutenegger, S., Lynen, S., Bosse, M. Siegwart, R, Furgale, P. (2015), Keyframe-Based Visual—Inertial Odometry Using Nonlinear Optimization. Int. J. Robot. Res. 34, 314–334.
Li, M., Mourikis, A.I. (2013), High-Precision, Consistent EKF-Based Visual—Inertial Odometry. Int. J. Robot. Res. 32, 690–711.
Li, Q., Ren, S. A real-time visual inspection system for discrete surface defects of rail heads. IEEE Trans. Instrum. Meas. 2012, 61, 2189–2199.
Lyrio, L.J., Oliveira-Santos, T., Badue, C., De Souza, A. F. Image-based mapping, global localization and position tracking using VG-RAM weightless neural networks. In Proceedings of the 2015 IEEE International Conference on Robotics and Automation (ICRA), Seattle, WA, USA, 26–30 May 2015; pp. 3603–3610.
Molodova Marija, Li, Z.L., Dollevoet Rolf Axle box acceleration: measurement and simulation for detection of short track defects. Wear, Vol. 271, 2011, p. 349-356.
Tian, Y., Jie, Z., Tan, J. Adaptive-frame-rate monocular vision and imu fusion for robust indoor positioning. In Proceedings of the 2013 IEEE International Conference on Robotics and Automation (ICRA), Karlsruhe, Germany, 6–10 May 2013; pp. 2257–2262.
Triepaischajonsak, N., Thompson, D. J.A hybrid modeling approach for predicting ground vibration from trains. Journal of Sound and Vibration, Vol. 335, 2015, p. 147-173.
Usenko, V., Engel, J., âckler, J., Cremers, D. Direct Visual-Inertial Odometry with Stereo Cameras. In Proceedings of the 2016 IEEE International Conference on Robotics and Automation (ICRA), Stockholm, Sweden, 16–21 May 2016; pp. 1885–1892.
Weng, E.N.G., Khan, R.U., Adruce, S.A.Z., Bee, O.Y. Objects tracking from natural features in mobile augmented reality. Procedia Soc. Behav. Sci. 2013, 97, 753–760
Wu, K.; Ahmed, A., Georgiou, G.A., Roumeliotis, S.I. A Square Root Inverse Filter for Efficient Vision-Aided Inertial Navigation on Mobile Devices. In Proceedings of the 2015 Robotics: Science and Systems Conference, Rome, Italy, 13–17 July 2015.
Yang, Z., Shen, S. Monocular Visual-Inertial State Estimation with Online Initialization and Camera-IMU Extrinsic Calibration. IEEE Trans. Autom. Sci. Eng. 2017, 14, 39–51.

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Published In

Go to Resilience and Sustainable Transportation Systems
Resilience and Sustainable Transportation Systems
Pages: 530 - 537
Editors: Fengxiang Qiao, Ph.D., Texas Southern University, Yong Bai, Ph.D., Marquette University, Pei-Sung Lin, Ph.D., University of South Florida, Steven I Jy Chien, Ph.D., New Jersey Institute of Technology, Yongping Zhang, Ph.D., California State Polytechnic University, and Lin Zhu, Ph.D., Shanghai University of Engineering Science
ISBN (Online): 978-0-7844-8290-2

History

Published online: Jun 29, 2020
Published in print: Jun 29, 2020

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Authors

Affiliations

College of Urban Railway Transportation, Shanghai Univ. of Engineering Science, Songjiang, Shanghai, China. E-mail: [email protected]
Huiling Zhang [email protected]
College of Urban Railway Transportation, Shanghai Univ. of Engineering Science, Songjiang, Shanghai, China. E-mail: [email protected]
College of Urban Railway Transportation, Shanghai Univ. of Engineering Science, Songjiang, Shanghai, China. E-mail: [email protected]
Shubin Zheng [email protected]
College of Urban Railway Transportation, Shanghai Univ. of Engineering Science, Songjiang, Shanghai, China. E-mail: [email protected]

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