Technology of AUV High-Precision Referencing to Inspected Object

Pleiades Publishing Ltd - Tập 10 - Trang 322-329 - 2020
V. A. Bobkov1, A. P. Kudryashov1, A. V. Inzartsev2
1Institute for Automation and Control Processes, Far Eastern Branch of the Russian Academy of Sciences, Vladivostok, Russia
2Institute of Marine Technology Problems, Far Eastern Branch of the Russian Academy of Sciences, Vladivostok, Russia

Tóm tắt

A new algorithm and a method of coordinate referencing of an unmanned autonomous underwater vehicle (AUV) to underwater objects using stereo images are proposed for automated inspection of bottom industrial infrastructure facilities. Computational experiments have been carried out using a modeling simulator based on a hybrid multiprocessor computing architecture. The proposed solutions have been estimated in terms of efficiency.

Tài liệu tham khảo

García-Valdovinos, L.G., Salgado-Jiménez, T., Bandala-Sánchez, M. et al., Modelling, design and robust control of a remotely operated underwater vehicle, International Journal of Advanced Robotic Systems, 2014, vol. 11, no. 1, pp. 1–16. Jacobi, M. and Karimanzira, D., Multi sensor underwater pipeline tracking with AUVs, Oceans—St. John’s 2014, 2014, pp. 1–6. Jacobi, M. and Karimanzira, D., Guidance of AUVs for autonomous underwater inspection, Automatisierungstechnik, 2015, vol. 63, no. 5, pp. 380–388. Cheramie, J., Patent WO2015134473A2, 2015. Wu, D., Chatzigeorgiou, D., Youcef-Toumi, K. and Ben-Mansour, R., Node localization in robotic sensor networks for pipeline inspection, IEEE Transactions on Industrial Informatics, 2016, vol. 12, no. 2, pp. 809–819. Yu, C., Xiang, X., Zuo, M. and Liu, H., Underwater cable tracking control of under-actuated AUV, 2016 IEEE/OES Autonomous Underwater Vehicles(AUV), 2016, pp. 324–329. Zhang, J., Zhang, Q. and Xiang, X., Automatic inspection of subsea optical cable by an autonomous underwater vehicle, 2017 OCEANS, 2017, pp. 1–6. Zhang, J. and Xiang, X., Subsea cable tracking by a 5–DOF AUV, 36th Chinese Control Conference, 2017, pp. 4796–4800. Zhang, J., Ila, V., and Kneip, L., Robust visual odometry in underwater environment, 2018 OCEANS— MTS/IEEE Kobe Techno-Ocean(OTO), 2018, pp. 1–9. Subsea Production System. URL: http://sahalin-shelf-dobycha.gazprom.ru/about/technologies/pdk/. Bobkov, V.A., Kudryashov, A.P., Mel’man, S.V. and Shcherbatyuk, A.F., Autonomous underwater navigation with 3D environment modeling using stereo images, Gyroscopy and Navigation, 2018, vol. 9, no. 1, pp. 67–75. Mel’man, S., Bobkov, V., Inzartsev, A. and Pavin, A., Distributed simulation framework for investigation of autonomous underwater vehicles' real-time behavior, Proceedings of the OCEANS'15 MTS/IEEE Washington DC, October 19−22, 2015, ISBN DVD: 978-0-933957-43-5. Chen, Y. and Medioni, G., Object modeling by registration of multiple range images, IEEE International Conference on Robotics and Automation, 1991, vol. 3, pp. 2724–2729. Besl, P. J. and McKay, N. D., A method for registration of 3-D shapes, IEEE Transactions on Pattern Analysis and Machine Intelligence, 1992, vol. 14, no. 2, pp. 239–256. Bobkov, V.A., Mel’man, S.V., and Kudryashov, A.P., Fast computation of local displacement by stereo pairs, Pattern Recognition and Image Analysis, 2017, vol. 27, no. 3, pp. 458–465.