Abstract
A vision-based extended Kalman filter is proposed to estimate the state of a remotely operated vehicle (ROV) used for inspection of a nuclear reactor pressure vessel. The state estimation framework employs an overhead, pan-tilt-zoom (PTZ) camera as the primary sensing modality. In addition to the camera state, a map of the nuclear reactor vessel is also estimated from a prior. We conduct experiments to validate the framework in terms of accuracy and robustness to environmental image degradation due to speckling and color attenuation. Subscale mockup experiments highlight estimate consistency as compared to ground truth despite visually degraded operating conditions. Full-scale platform experiments are conducted using the actual inspection system in a dry setting. In this case, the ROV achieves a lower state uncertainty as compared to subscale mockup evaluation. For both subscale and full-scale experiments, the state uncertainty was robust to environmental image degradation effects.
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Arthur, D., Vassilvitskii, S.: K-means++: the advantages of careful seeding. In: Proceedings of the ACM-SIAM Symposium on Discrete Algorithms, pp. 1027–1035 (2007)
Bartoli, A., Sturm, P.: The 3d line motion matrix and alignment of line reconstructions. Int. J. Comput. Vis. 57, 159–178 (2004)
Canny, J.: A computational approach to edge detection. IEEE Trans. Pattern Anal. Mach. Intell. 6, 679–698 (1986)
Carreras, M., Ridao, P., García, R., Nicosevici, T.: Vision-based localization of an underwater robot in a structured environment. In: Proceedings of the IEEE International Conference on Robot and Automation, vol. 1, pp. 971–976 (2003)
Cho, B.H., Byun, S.H., Shin, C.H., Yang, J.B., Song, S.I., Oh, J.M.: Keprovt: Underwater robotic system for visual inspection of nuclear reactor internals. Nucl. Eng. des. 231(3), 327–335 (2004)
Collins, R.T., Tsin, Y.: Calibration of an outdoor active camera system. In: IEEE Computer Society Conference on Computer Vision and Pattern Recognition, vol. 1 (1999)
Corke, P., Detweiler, C., Dunbabin, M., Hamilton, M., Rus, D., Vasilescu, I.: Experiments with underwater robot localization and tracking. In: Proceedings of the IEEE International Conference on Robot and Automation, pp. 4556–4561 (2007)
Doyle, D.D., Jennings, A.L., Black, J.T.: Optical flow background estimation for real-time pan/tilt camera object tracking. Measurement 48, 195–207 (2014)
Furgale, P., Rehder, J., Siegwart, R.: Unified temporal and spatial calibration for multi-sensor systems. In: Proceedings of the IEEE/RSJ InternationaL Conference on Intelligence Robots and Systems, pp. 1280–1286 (2013)
Hartley, R., Zisserman, A.: Multiple View Geometry in Computer Vision. Cambridge University Press (2003)
Hover, F.S., Eustice, R.M., Kim, A., Englot, B., Johannsson, H., Kaess, M., Leonard, J.J.: Advanced perception, navigation and planning for autonomous in-water ship hull inspection. Int. J. Robot. Res. 31(12), 1445–1464 (2012)
Jain, S., Neumann, U.: Real-time camera pose and focal length estimation. IEEE International Conference on Pattern Recognition, vol. 1, pp. 551–555 (2006)
Kelly, J., Sukhatme, G.S.: Visual-inertial sensor fusion: localization, mapping and sensor-to-sensor self-calibration. Intl. J. Robot. Res. 30(1), 56–79 (2011)
Kim, A., Eustice, R.: Pose-graph visual slam with geometric model selection for autonomous underwater ship hull inspection. In: Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, pp. 1559–1565 (2009)
Kinsey, J.C., Eustice, R.M., Whitcomb, L.L.: A survey of underwater vehicle navigation: recent advances and new challenges. In: IFAC Conference of Manoeuvering and Ctrl of Marine Craft, vol. 88 (2006)
LaViola, J.J.: A comparison of unscented and extended kalman filtering for estimating quaternion motion. In: Proceedings of the American Control Conference, vol. 3, pp. 2435–2440. IEEE (2003)
Matas, J., Galambos, C., Kittler, J.: Robust detection of lines using the progressive probabilistic hough transform. Comput. Vis. Image Underst. 78(1), 119–137 (2000)
Mazumdar, A., Lozano, M., Fittery, A., Asada, H.H.: A compact, maneuverable, underwater robot for direct inspection of nuclear power piping systems. In: Proceedings of the IEEE Internatinal Conference on Robot and Automation, pp. 2818–2823 (2012)
Murphy, R.R., Steimle, E., Hall, M., Lindemuth, M., Trejo, D., Hurlebaus, S., Medina-Cetina, Z., Slocum, D.: Robot-assisted bridge inspection. J. Intell. Robot. Syst. 64(1), 77–95 (2011)
Odakura, M., Kometani, Y., Koike, M., Tooma, M., Nagashima, Y.: Advanced inspection technologies for nuclear power plants. Hitachi Rev. 58(2), 82–87 (2009)
Shea, H.R.: Effects of radiation on mems. In: Proceedings of SPIE, vol. 7928, pp. 79,280E–1–79,280E–13 (2011)
Shkurti, F., Rekleitis, I., Scaccia, M., Dudek, G.: State estimation of an underwater robot using visual and inertial information. In: Proceedings of the IEEE/RSJ International Conference on Intelligence Robots and Systems, pp. 5054–5060 (2011)
Sinha, S.N., Pollefeys, M.: Pan-tilt-zoom camera calibration and high-resolution mosaic generation. Comput. Vis. Image Underst. 103(3), 170–183 (2006)
Sola, J., Vidal-Calleja, T., Civera, J., Montiel, J.M.M.: Impact of landmark parametrization on monocular ekf-slam with points and lines. Int. J. Comput. Vis. 97(3), 339–368 (2012)
Tsui, C.L., Schipf, D., Lin, K.R., Leang, J., Hsieh, F.J., Wang, W.C.: Using a time of flight method for underwater 3-dimensional depth measurements and point cloud imaging. In: IEEE OCEANS Conference, pp. 1–6 (2014)
Yuen, H., Princen, J., Illingworth, J., Kittler, J.: Comparative study of hough transform methods for circle finding. Image Vis. Comput. 8(1), 71–77 (1990)
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We gratefully acknowledge support from Westinghouse Electric Company, LLC.
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Lee, T.E., Michael, N. (2018). State Estimation and Localization for ROV-Based Reactor Pressure Vessel Inspection. In: Hutter, M., Siegwart, R. (eds) Field and Service Robotics. Springer Proceedings in Advanced Robotics, vol 5. Springer, Cham. https://doi.org/10.1007/978-3-319-67361-5_45
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DOI: https://doi.org/10.1007/978-3-319-67361-5_45
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