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Test method for measuring station-keeping with unmanned marine vehicles using sonar or optical sensors

Published: 20 March 2012 Publication History

Abstract

This paper proposes a test method for measuring the ability of a USV or ROV to fixate on an underwater object, i.e., station-keeping. Station-keeping is needed to permit an operator or domain expert to stay focused on an area in an image long enough to identify objects, such as submerged cars and debris, or a condition, such as scour eroding the underwater footing of a bridge. This problem is different from traditional robot control, as the point is not to measure the positions of the robot and sensor payload but rather how well the system maintains the position of the object in the image. The test method uses the Lucas-Kanade optical flow algorithm in OpenCV to track an inexpensive raised plywood and wire fiducial. The rotational, translational, and root mean square (RMS) error is measured over a 3 minute period as well as number of image frames in which the fiducial was not visible. The method was demonstrated using a DIDSON acoustic camera, but is generalizable to other types of sonars and underwater video cameras.

References

[1]
X. Cufi, R. Garcia, and P. Ridao. An approach to vision-based station keeping for an unmanned underwater vehicle. In Intelligent Robots and Systems, 2002. IEEE/RSJ International Conference on, volume 1, pages 799--804 vol. 1, 2002.
[2]
R. Marks, H. Wang, M. Lee, and S. Rock. Automatic Visual Station Keeping of an Underwater Robot. In Proc. IEEE Oceans 94 Osates, Brest, France, 1994.
[3]
S. van der Zwaan and J. Santos-Victor. Real-time vision-based station keeping for underwater robots. In OCEANS, 2001. MTS/IEEE Conference and Exhibition, volume 2, pages 1058--1065 vol. 2, 2001.
[4]
Q. Wu, S. Li, Y. Hao, and F. Zhu. A model-based monocular vision system for station keeping of an underwater vehicle. In Robotics and Biomimetics (ROBIO). 2005 IEEE International Conference on, pages 450--454, 2005.
[5]
X. Xu and S. Negahdaripour. Automatic optical station keeping and navigation of an rov; sea trial experiments. In OCEANS '99 MTS/IEEE. Riding the Crest into the 21st Century, volume 1, pages 71--76 vol. 1, 1999.
[6]
S.-C. Yu, T.-W. Kim, A. Asada, S. Weatherwax, B. Collins, and J. Yuh. Development of high-resolution acoustic camera based real-time object recognition system by using autonomous underwater vehicles. In OCEANS 2006, pages 1--6, 2006.

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  • (2016)Embedded multibeam sonar feature extraction for online AUV controlOCEANS 2016 - Shanghai10.1109/OCEANSAP.2016.7485466(1-4)Online publication date: Apr-2016

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  1. Test method for measuring station-keeping with unmanned marine vehicles using sonar or optical sensors

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      PerMIS '12: Proceedings of the Workshop on Performance Metrics for Intelligent Systems
      March 2012
      243 pages
      ISBN:9781450311267
      DOI:10.1145/2393091
      Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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      • University of Maryland: University of Maryland
      • NIST: National Institute of Standards & Technology

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      New York, NY, United States

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      Published: 20 March 2012

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      Author Tags

      1. ROV
      2. sonar
      3. unmanned marine vehicles

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      PerMIS'12
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      • University of Maryland
      • NIST
      PerMIS'12: Performance Metrics for Intelligent Systems
      March 20 - 22, 2012
      Maryland, College Park

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      • (2016)Embedded multibeam sonar feature extraction for online AUV controlOCEANS 2016 - Shanghai10.1109/OCEANSAP.2016.7485466(1-4)Online publication date: Apr-2016

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