A Fast Binocular Localisation Method for AUV Docking

• Published in: Sensors (Basel, Switzerland) Vol. 19; no. 7; p. 1735
• Main Authors: Zhong, Lijia, Li, Dejun, Lin, Mingwei, Lin, Ri, Yang, Canjun
• Format: Journal Article
• Language: English
• Published: Switzerland MDPI AG 11.04.2019; MDPI
• Subjects: Algorithms; Autonomous underwater vehicles; binocular vision; Digital cameras; docking guidance technology; Laboratories; Lamps; Localization; Vehicles; United States > US; China; autonomous underwater vehicles; binocular vision; docking guidance technology
• ISSN: 1424-8220; 1424-8220
• DOI: 10.3390/s19071735

Docking technology plays a critical role in realising the long-time operation of autonomous underwater vehicles (AUVs). In this study, a binocular localisation method for AUV docking is presented. An adaptively weighted OTSU method is developed for feature extraction. The foreground object is extracted precisely without mixing or missing lamps, which is independent of the position of the AUV relative to the station. Moreover, this extraction process is more precise compared to other segmentation methods with a low computational load. The mass centre of each lamp on the binary image is used as matching feature for binocular vision. Using this fast feature matching method, the operation frequency of the binocular localisation method exceeds 10 Hz. Meanwhile, a relative pose estimation method is suggested for instances when the two cameras cannot capture all the lamps. The localisation accuracy of the distance in the heading direction as measured by the proposed binocular vision algorithm was tested at fixed points underwater. A simulation experiment using a ship model has been conducted in a laboratory pool to evaluate the feasibility of the algorithm. The test result demonstrates that the average localisation error is approximately 5 cm and the average relative location error is approximately 2% in the range of 3.6 m. As such, the ship model was successfully guided to the docking station for different lateral deviations.