Abstract
Underwater docking technology enables autonomous underwater vehicles (AUVs) to execute long-term observation missions by periodically recovering and recharging AUVs. The conventional AUV homing and docking operations utilize acoustic and optical sensors at different ranges relative to the docking station. However, this method cannot perform perfectly in confined water regions because of the acoustic reflection and multipath effect. Thus, this paper proposes a novel navigation system, which fuses downward-looking visual odometry and model-based velocity for homing, and recognizes and tracks the light marker for terminal docking, in order to overcome the defects of the conventional navigation method. The reservoir experiment result verifies the effectiveness of the proposed method and shows good potential to extended applications in underwater routine cruise.
Article PDF
Similar content being viewed by others
Explore related subjects
Discover the latest articles, news and stories from top researchers in related subjects.Avoid common mistakes on your manuscript.
References
Yang, C., Lin, M., Li, D.: Improving Steady and Starting Characteristics of Wireless Charging for an AUV Docking System. IEEE Journal of Oceanic Engineering. 1–12 (2018)
Lin, M., Li, D., Yang, C.: Design of an ICPT system for battery charging applied to underwater docking systems. Ocean Engineering. 145, 373–381 (2017)
Palomeras, N., Vallicrosa, G., Mallios, A., Bosch, J., Vidal, E., Hurtos, N., Carreras, M., Ridao, P.: AUV homing and docking for remote operations. Ocean Engineering. 154, 106–120 (2018)
Eren, F., Pe'Eri, S., Rzhanov, Y., Thein, M., Celikkol, B.: Optical Detector Array Design for Navigational Feedback Between Unmanned Underwater Vehicles (UUVs). IEEE Journal of Oceanic Engineering. 41, 18–26 (2016)
R. P Rez-Alcocer, L. A. Torres-M Ndez, E. Olgu N-D Az, and A. A. Maldonado-Ram Rez, "Vision-Based Autonomous Underwater Vehicle Navigation in Poor Visibility Conditions Using a Model-Free Robust Control," Journal of Sensors, pp. 1–16, 2016
D. Park, J. Jung, K. Kwak, W. K. Chung, and J. Kim, "3D Underwater Localization using EM Waves Attenuation for UUV Docking," IEEE Conference on Underwater Technology (UT), 2017
Mur-Artal, R., Tardos, J.D.: ORB-SLAM2: An Open-Source SLAM System for Monocular, Stereo, and RGB-D Cameras. IEEE Transactions on Robotics. 33, 1255–1262 (2017)
Nawaf, M.M., Merad, D., Royer, J., Boï, J., Saccone, M., Ellefi, M.B., Drap, P.: Fast Visual Odometry for a Low-Cost Underwater Embedded Stereo System. Sensors. 18, 2313 (2018)
Bellavia, F., Fanfani, M., Colombo, C.: Selective visual odometry for accurate AUV localization. Autonomous Robots. 41, 133–143 (2017)
D. Li, Ship motion and modeling: Chinese Defense Industry Press, 2008
J. Kennedy and R. Eberhart, "Particle Swarm Optimization," Proceedings of International Conference on Neural Networks, 1995
Zhang, T., Li, D., Yang, C.: Study on impact process of AUV underwater docking with a cone-shaped dock. Ocean Engineering. 130, 176–187 (2017)
Dormand, J.R., Prince, P.J.: A family of embedded Runge-Kutta formulae. Journal of Computational and Applied Mathematics. 6, 19–26 (1980)
P. Lluis Negre, F. Bonin-Font and G. Oliver, "Cluster-Based Loop Closing Detection for Underwater SLAM in Feature-Poor Regions," in IEEE International Conference on Robotics and Automation ICRA, A. Okamura, A. Menciassi, A. Ude, D. Burschka, D. Lee, F. Arrichiello, H. Liu, H. Moon, J. Neira, K. Sycara, K. Yokoi, P. Martinet, P. Oh, P. Valdastri, and V. Krovi, Eds., 2016, pp. 2589–2595
J. Bouguet, "Pyramidal Implementation of the Lucas Kanade Feature Tracker Description of the algorithm. intel corporation microprocessor research labs," OpenCV documents, 2000
W. Hou, A. D. Weidemann, D. J. Gray, and G. R. Fournier, "Imagery-derived modulation transfer function and its applications for underwater imaging,", 2007, pp. 22–28
Kim, A., Eustice, R.M.: Real-Time Visual SLAM for Autonomous Underwater Hull Inspection Using Visual Saliency. IEEE Transactions on Robotics. 29, 719–733 (2013)
Chong-Yi, L., Ji-Chang, G., Run-Min, C., Yan-Wei, P., Bo, W.: Underwater Image Enhancement by Dehazing With Minimum Information Loss and Histogram Distribution Prior. IEEE Transactions on Image Processing. 25, 5664–5677 (2016)
Zhang, Z.: A flexible new technique for camera calibration. IEEE Transactions on Pattern Analysis and Machine Intelligence. 22, 1330–1334 (2000)
Scaramuzza, D., Fraundorfer, F.: Visual Odometry Part I: The First 30 Years and Fundamentals. IEEE Robotics & Automation Magazine. 18, 80–92 (2011)
"The KITTI Vision Benchmark Suite,", 2012
Lin, M., Yang, C., Li, D.: An Improved Transformed Unscented FastSLAM With Adaptive Genetic Resampling. IEEE Transactions on Industrial Electronics. 66, 3583–3594 (2019)
Liu, D., Duan, J., Shi, H.: A Strong Tracking Square Root Central Difference FastSLAM for Unmanned Intelligent Vehicle with Adaptive Partial Systematic Resampling. IEEE Transactions on Intelligent Transportation Systems. 11, 3110–3120 (2016)
Acknowledgements
This work was supported by the Marine S&T Fund of Shandong Province under Grant 2018SDKJ0211.
Author information
Authors and Affiliations
Corresponding author
Additional information
Publisher’s Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
About this article
Cite this article
Lin, M., Yang, C. AUV Docking Method in a Confined Reservoir with Good Visibility. J Intell Robot Syst 100, 349–361 (2020). https://doi.org/10.1007/s10846-020-01175-3
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s10846-020-01175-3