Image-based visual servoing control of remotely operated vehicle for underwater pipeline inspection
Author:
Funder
Texas Commission on Environmental Quality
Publisher
Springer Science and Business Media LLC
Subject
Artificial Intelligence,Computer Science Applications
Link
https://link.springer.com/content/pdf/10.1007/s41315-023-00301-2.pdf
Reference24 articles.
1. Aripin, M.K., Aras, M.S.M., Sulaiman, M., Zainal, M.I.M., Harun, M.H., Zambri, M.K.M.: Low cost expansion of unmanned underwater remotely operated crawler (roc) for pipeline inspection. In 2017 IEEE 7th International Conference on Underwater System Technology: Theory and Applications (USYS), pages 1–5. IEEE (2017)
2. Bharti, V., Lane, D., Wang, S.: A semi-heuristic approach for tracking buried subsea pipelines using fluxgate magnetometers. In: 2020 IEEE 16th International Conference on Automation Science and Engineering (CASE), pages 469–475. IEEE (2020)
3. Chu, Z., Zhu, D., Luo, C.: Adaptive neural sliding mode trajectory tracking control for autonomous underwater vehicle without thrust model. In: 2017 13th IEEE Conference on Automation Science and Engineering (CASE), pages 1639–1644. IEEE (2017)
4. Duda, R.O., Hart, P.E.: Use of the hough transformation to detect lines and curves in pictures. Commun. ACM 15(1), 11–15 (1972)
5. Duran, O., Althoefer, K., Seneviratne, L.D.: Automated pipe defect detection and categorization using camera/laser-based profiler and artificial neural network. IEEE Trans. Autom. Sci. Eng. 4(1), 118–126 (2007). https://doi.org/10.1109/TASE.2006.873225
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