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An efficient underwater coverage method for multi-AUV with sea current disturbances

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  • Robotics and Automation
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Abstract

This paper presents an online coverage method for the exploration of unknown oceanic terrains using multiple autonomous underwater vehicles (AUVs). Working from the concept of planar algorithm developed by Hert, this study attempts to develop an improved method. Instead of theoretical research, it focuses on the practical aspects of exploration by considering the equations of motion for AUVs that are actually used in oceanic exploration as well as on the characteristics of complex oceanic topography and other realistic variables, such as sea current. These elements are used to calculate cross track error (CTE) and path width for AUV movement. The validity of the improved algorithm for terrain coverage is first verified mathematically and then by a simulation of the real underwater environment that analyzes the path length and time taken for the coverage as well as the missed areas, which is the key element of efficiency. In order to apply the improved method to the multi-AUV operation, each AUV was assigned a covering or a scanning role by means of a dynamic role-changing mechanism. The results showed that the multi-AUV operation has an advantage over a single-AUV operation in many ways. The method proposed in this study will be useful not only for commercial applications but also for mine counter-measures (MCMs) and rapid environmental assessments (REAs) as part of naval military operations as well. We also believe that it will be ideal for use in variable oceanic environment, particularly in shallow water terrains. For the purposes of this study, we assume that the communication between AUVs is problem-free.

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References

  1. E. U. Acar, H. Choset, and P. N. Atkar, “Complete sensor-based coverage with extended-range detectors: a hierarchical decomposition in terms of critical points and voronoi diagrams,” Proc. of IEEE Int. Conf. on Intelligent Robots and Systems, pp. 1305–1311, 2001.

  2. E. U. Acar, H. Choset, A. A. Rizzi, P. N. Atkar, and D. Hull “Morse decompositions for coverage tasks,” International Journal of Robotics Research, vol. 21, no. 4, pp. 331–344, 2002.

    Article  Google Scholar 

  3. H. Choset, “Coverage for robotics — a survey of recent results,” Annals of Mathematics and Artificial Intelligence, vol. 31, no. 1–4, pp. 113–126, 2001.

    Article  Google Scholar 

  4. L. Chaimowicz, M. FM. Campos, and V. Kumar, “Dynamic role assignment for cooperative robots,” Proc. of IEEE Int. Conf. on Robotics and Automation, pp. 293–298, 2002.

  5. T. I. Fossen, Guidance and Control of Ocean Vehicles, Wiely, New York, NY, 1994.

    Google Scholar 

  6. Y. Gabriely and E. Rimon, “Spanning-tree based coverage of continuous areas by a mobile robot,” Annals of Mathematics and Artificial Intelligence, vol. 31, no. 1–4, pp. 77–98, 2001.

    Article  Google Scholar 

  7. Y. Gabriely and E. Rimon, “Competitive on-line coverage of grid environments by a mobile robot. computational geometry,” Theory and Applications, vol. 24, pp. 197–224, 2003.

    MATH  MathSciNet  Google Scholar 

  8. S. S. Ge and C.-H, Fua, “Complete multi — robot formation coverage of unknown environment with minimum repeated coverage,” Proc. of IEEE Int. Conf. on Robotics and Automation, Barcelona, Spain, pp. 715–720, 2005.

  9. S. S. Ge and F. L. Lewis, Autonomous Mobile Robots, Taylor and Francis, Boca Raton, FL, 2006.

    MATH  Google Scholar 

  10. N. Hazon and G. A. Kaminka, “Redundancy, efficiency and robustness in multi-robot coverage,” Proc. of IEEE Int. Conf. on Robotics and Automation, Barcelona, Spain, 2005.

  11. A. J. Healey and D. Liendrd, “Multivariable sliding mode control for autonomous diving and steering of manned underwater vehicles,” IEEE Journal of Oceanic Engineering, vol. 18, no. 3, pp. 327–339, 1993.

    Article  Google Scholar 

  12. S. Hert, S. Tiwari, and V. Lumelsky, “A terrain-covering algorithm for an AUV,” Journal of Autonomous Robots, vol. 3, no. 2–3, pp. 91–119, 1996.

    Article  Google Scholar 

  13. S. Hert and V. Lumelsky, “Polygon area decomposition for multiple-robot workspace division,” International Journal of Computational Geometry and Applications on Applied Computational Geometry, vol. 8, no. 4. pp. 437–466, 1998.

    Article  MATH  MathSciNet  Google Scholar 

  14. V. Lumelsky, S. Mukhopadhyay, and K. Sun, “Dynamic path planning in sensor-based terrain acquisition,” IEEE Trans. on Robotics and Automation, vol. 6, no. 4, pp. 464–472, 1990.

    Article  Google Scholar 

  15. T. Prestero, Verification of a Six-degree of Freedom Simulation Model for the REMUS Autonomous Underwater Vehicles, Master thesis, Department of Ocean Engineering and Mechanical Engineering, MIT, USA, 2001.

    Google Scholar 

  16. I. A. Wagner, M. Lindenbaum, and A. M. Bruckstei, “Distributed covering by ant-robots using evaporating traces,” IEEE Trans. on Robotics and Automation, vol. 15, no. 5, pp. 918–933, 1999.

    Article  Google Scholar 

  17. I. A. Wagner, M. Lindenbaum, and A. M. Bruckstei, “MAC vs. PC-determinism and randomness as complementary approaches to robotic exploration of continuous unknown domain,” International Journal of Robotics Research, vol. 19, no. 1, pp. 12–31, 2000.

    Article  Google Scholar 

  18. B. Yamauchi, A. Schultz, and W. Adams, “Mobile robot exploration and map-building with continuous localization,” Proc. of Int. Conf. on Robotics and Automation, Leuven, Belgium, pp. 3715–3720, 1998.

  19. S. X. Yang and Luo, “A neural network approach to complete coverage path planning,” IEEE Trans. on Systems, Man and Cybernetics-Part B, vol. 34, no. 1, pp. 718–725, 2004.

    Article  Google Scholar 

  20. R. Zlot and A. Stentz, “Market-based Multi-robot coordination for complex tasks,” International Journal of Robotics Research, vol. 25, no. 1, pp. 73–101, 2006.

    Article  Google Scholar 

  21. D. H. Kim, “Self-organization of swarm systems by association,” International Journal of Control, Automation, and Systems, vol. 6, no. 2, pp. 253–262, 2008.

    Google Scholar 

  22. D.-W. Lee, S.-W. Seo, and K.-B. Sim, “Online evolution for cooperative behavior in group robot systems,” International Journal of Control, Automation, and Systems, vol. 6, no. 2, pp. 282–287, 2008.

    Google Scholar 

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Correspondence to Kong-Woo Lee.

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Recommended by Editorial Board member Sooyong Lee under the direction of Editor Jae-Bok Song. This work was supported in part by MOCIE Industrial Technology Development Program, the ASRI, and BK21 Information Technology at Seoul National University.

Yeun-Soo Jung received the Ph.D. degree in Electrical Engineering from Seoul National University in 2008. His research interests include autonomous underwater vehicles and multi-agent control.

Kong-Woo Lee received the M.S. degree in Electrical Engineering from Seoul National University in 2007. His research interests include multi-agent control, autonomous mobile robot navigation and SLAM.

Seong-Yong Lee received the M.S. degree in Electrical Engineering from Seoul National University in 2007. His research interests include intelligent robots, embedded systems, operating systems, and multi-agent control.

Myoung Hwan Choi received the Ph.D. degree in Control and Instrumentation Engineering from Seoul National University in 1992. His research interests include ultrasonic Imaging, biomedical signal processing and biomedical imaging.

Beom-Hee Lee received the Ph.D. degree in Computer, Information & Control Engineering from University of Michigan in 1985. His research interests include multi-agent system coordination, control, and application.

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Jung, YS., Lee, KW., Lee, SY. et al. An efficient underwater coverage method for multi-AUV with sea current disturbances. Int. J. Control Autom. Syst. 7, 615–629 (2009). https://doi.org/10.1007/s12555-009-0412-4

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