Author:
Yasukawa Shinsuke,Ahn Jonghyun,Nishida Yuya,Sonoda Takashi,Ishii Kazuo,Ura Tamaki, , ,
Abstract
We developed a vision system for an autonomous underwater robot with a benthos sampling function, specifically sampling-autonomous underwater vehicle (AUV). The sampling-AUV includes the following five modes: preparation mode (PM), observation mode (OM), return mode (RM), tracking mode (TM), and sampling mode (SM). To accomplish the mission objective, the proposed vision system comprises software modules for image acquisition, image enhancement, object detection, image selection, and object tracking. The camera in the proposed system acquires images in intervals of five seconds during OM and RM, and in intervals of one second during TM. The system completes all processing stages in the time required for image acquisition by employing high-speed algorithms. We verified the effective operation of the proposed system in a pool.
Publisher
Fuji Technology Press Ltd.
Subject
Electrical and Electronic Engineering,General Computer Science
Reference21 articles.
1. Y. Nishida, K. Nagahashi, T. Sato, A. Bodenmann, B. Thornton, A. Asada, and T. Ura, “Autonomous Underwater, Vehicle ‘BOSS-A’ for Acoustic and Visual Survey of Manganese Crusts,” J. of Robotics and Mechatronics, Vol.28, No.1, pp. 91-94, 2016.
2. L. L. Whitcomb, “Underwater robotics: Out of the research laboratory and into the field. In Robotics and Automation,” Proc. ICRA’00. IEEE Int. Conf., Vol.1, pp. 709-716, 2000.
3. M. Grasmueck, G. P. Eberli, D. A. Viggiano, T. Correa, G. Rathwell, and J. Luo, “Autonomous underwater vehicle (AUV) mapping reveals coral mound distribution, morphology, and oceanography in deep water of the Straits of Florida,” Geophysical Research Letters, Vol.33, Issue 23, L23616, 2006.
4. M. Johnson-Roverson, O. Pizarro, S. B. Williams, and I. Mahon, “Generation and visualization of large-scale three-dimensional reconstructions from underwater robotics surveys,” J. of Field Robotics, Vol.27, Issue 1, pp. 21-51, 2009.
5. B. Thorton, A. Bodenmann, O. Pizarro, S. B. Williams, A. Friedman, R. Nakajima, K. Takai, K. Motoki, T. Watsuji, H. Hirayama, Y. Matsui, H. Watanabe, and T. Ura, “Biometric assessment of deep-sea vent megabenthic communities using multi-resolution 3D image reconstructions,” Deep Sea Research Part I: Oceanographic Research Papers, Vol.116, pp. 200-219, 2016.
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