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Paladyn, Journal of Behavioral Robotics

Editor-in-Chief: Schöner, Gregor

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Profile Following for Inspection of Underwater Structures

Enric Galceran
  • Underwater Robotics Research Center, University of Girona, Parc Científic i Tecnológic de la Universitat de Girona, Pic de Peguera, 13 17071 Girona, Catalonia, Spain
  • Email:
/ Narcís Palomeras
  • Underwater Robotics Research Center, University of Girona, Parc Científic i Tecnológic de la Universitat de Girona, Pic de Peguera, 13 17071 Girona, Catalonia, Spain
  • Email:
/ Marc Carreras
  • Underwater Robotics Research Center, University of Girona, Parc Científic i Tecnológic de la Universitat de Girona, Pic de Peguera, 13 17071 Girona, Catalonia, Spain
  • Email:
Published Online: 2013-12-27 | DOI: https://doi.org/10.2478/pjbr-2013-0019

Abstract

We present a seabed profile estimation and following method for close proximity inspection of 3D underwater structures using autonomous underwater vehicles (AUVs). The presented method is used to determine a path allowing the AUV to pass its sensors over all points of the target structure, which is known as coverage path planning. Our profile following method goes beyond traditional seabed following at a safe altitude and exploits hovering capabilities of recent AUV developments. A range sonar is used to incrementally construct a local probabilistic map representation of the environment and estimates of the local profile are obtained via linear regression. Two behavior-based controllers use these estimates to perform horizontal and vertical profile following. We build upon these tools to address coverage path planning for 3D underwater structures using a (potentially inaccurate) prior map and following cross-section profiles of the target structure. The feasibility of the proposed method is demonstrated using the GIRONA 500 AUV both in simulation using synthetic and real-world bathymetric data and in pool trials.

Keywords: Autonomous underwater vehicles; sensor-based planning; seabed profile following; coverage path planning; behavior-based control

  • [1] J. Escartin, R. Garcia, O. Delaunoy, J. Ferrer, N. Gracias, A. Elibol, X. Cufi, L. Neumann, D. J. Fornari, S. E. Humphris, and J. Renard, “Globally aligned photomosaic of the lucky strike hydrothermal vent field (mid-atlantic ridge, 37 deg 18.5 min n): Release of georeferenced data, mosaic construction, and viewing software,” Geochemistry, Geophysics, Geosystems, vol. 9, no. 12, pp. n/a–n/a, 2008. [Online]. Available: http: //dx.doi.org/10.1029/2008GC002204 [Crossref]

  • [2] D. R. Yoerger, D. S. Kelley, and J. R. Delaney, “Fine-scale three-dimensional mapping of a deep-sea hydrothermal vent site using the jason rov system,” The International Journal of Robotics Research, vol. 19, no. 11, pp. 1000–1014, 2000. [Online]. Available: http://ijr.sagepub.com/content/19/ 11/1000.abstract [Crossref]

  • [3] B. Bingham, B. Foley, H. Singh, R. Camilli, K. Delaporta, R. Eustice, A. Mallios, D. Mindell, C. N. Roman, and D. Sakellariou, “Robotic tools for deep water archaeology: Surveying an ancient shipwreck with an autonomous underwater vehicle,” J. Field Robotics, vol. 27, no. 6, pp. 702–717, 2010.

  • [4] P. Rigby, O. Pizarro, and S. B. Williams, “Toward adaptive benthic habitat mapping using gaussian process classification,” Journal of Field Robotics, vol. 27, no. 6, pp. 741–758, 2010. [Online]. Available: http://dx.doi.org/10.1002/rob.20372 [Crossref]

  • [5] D. P. Williams, “On optimal auv track-spacing for underwater mine detection,” ICRA, pp. 4755–4762, 2010.

  • [6] A. Bennet, J. Leonard, and J. Bellingham, “Bottom following for survey-class autonomous underwater vehicles,” in International Symposium on Unmanned Untethered Submersible Tech- nology, 1995, pp. 327–336.

  • [7] M. Caccia, G. Bruzzone, and G. Veruggio, “Active sonarbased bottom-following for unmanned underwater vehicles,” Control Engineering Practice, vol. 7, no. 4, pp. 459 – 468, 1999. [Online]. Available: http://www.sciencedirect.com/ science/article/pii/S0967066198001683

  • [8] M. Caccia, R. Bono, G. Bruzzone, and G. Veruggio, “Bottomfollowing for remotely operated vehicles,” Control Engineering Practice, vol. 11, no. 4, pp. 461 – 470, 2003. [Online]. Available: http://www.sciencedirect.com/science/article/pii/ S0967066101001423

  • [9] V. Creuze, B. Jouvencel, and P. Baccou, “Seabed following for small autonomous underwater vehicles,” in OCEANS, 2001. MTS/IEEE Conference and Exhibition, vol. 1, 2001, pp. 369 –374 vol.1.

  • [10] J. Melo and A. Matos, “Bottom estimation and following with the mares auv,” in Oceans, 2012, oct. 2012, pp. 1 –8.

  • [11] A. Adhami-Mihosseini, A. Aguiar, and M. Yazdanpanah, “Seabed tracking of an autonomous underwater vehicle with nonlinear output regulation,” in Decision and Control and European Con- trol Conference (CDC-ECC), 2011, pp. 3928 – 3933.

  • [12] S. Houts, S. Rock, and R. McEwen, “Aggressive terrain following for motion-constrained auvs,” in Autonomous Underwater Ve- hicles (AUV), 2012 IEEE/OES, 2012, pp. 1–7.

  • [13] G. Karras, C. Bechlioulis, H. Abdella, T. Lakworthy, K. Kyriakopoulos, and D. Lane, “A robust sonar servo control scheme for wallfollowing using an autonomous underwater vehicle,” in Intelli- gent Robots and Systems (IROS), 2013.

  • [14] H. Choset, “Coverage for robotics–a survey of recent results,” An- nals of Mathematics and Artificial Intelligence, vol. 31, pp. 113–126, 2001.

  • [15] 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. [Crossref]

  • [16] S. Hert, S. Tiwari, and V. Lumelsky, “A terrain-covering algorithm for an auv,” Autonomous Robots, vol. 3, pp. 91–119, 1996.

  • [17] P. Cheng, J. Keller, and V. Kumar, “Time-optimal uav trajectory planning for 3d urban structure coverage,” in Intelligent Robots and Systems, 2008. IROS 2008. IEEE/RSJ International Conference on, sept. 2008, pp. 2750 –2757.

  • [18] T.-S. Lee, J.-S. Choi, J.-H. Lee, and B.-H. Lee, “3-d terrain covering and map building algorithm for an auv,” in Proc. IEEE/RSJ Int. Conf. Intelligent Robots and Systems IROS 2009, 2009, pp. 4420–4425.

  • [19] P. N. Atkar, H. Choset, A. A. Rizzi, and E. U. Acar, “Exact cellular decomposition of closed orientable surfaces embedded in r3,” in Proc. Int. Conf. Robotics and Automation, vol. 1, 2001, pp. 699–704.

  • [20] P. Atkar, A. L. Greenfield, D. C. Conner, H. Choset, and A. Rizzi, “Uniform coverage of automotive surface patches,” The Interna- tional Journal of Robotics Research, vol. 24, no. 11, pp. 883 – 898, November 2005.

  • [21] T. Oksanen and A. Visala, “Coverage path planning algorithms for agricultural field machines,” Journal of Field Robotics, vol. 26, no. 8, pp. 651–668, 2009.

  • [22] A. Xu, P. Virie, and I. Rekleitis, “Optimal complete terrain coverage using an unmanned aerial vehicle,” in Proceedings of the 2011 IEEE International Conference on Robotics & Automation, 2011.

  • [23] A. Barrientos, J. Colorado, J. del Cerro, A. Martinez, C. Rossi, D. Sanz, and J. Valente, “Aerial remote sensing in agriculture: A practical approach to area coverage and path planning for fleets of mini aerial robots,” Journal of Field Robotics, vol. 28, no. 5, pp. 667–689, 2011.

  • [24] S. Guo and B. Gao, “Path-planning optimization of underwater microrobots in 3-d space by pso approach,” in Robotics and Biomimetics (ROBIO), 2009 IEEE International Conference on, dec. 2009, pp. 1655 –1620.

  • [25] J. Carsten, D. Ferguson, and A. Stentz, “3d field d: Improved path planning and replanning in three dimensions,” in Intelligent Robots and Systems, 2006 IEEE/RSJ International Confer- ence on, oct. 2006, pp. 3381 –3386.

  • [26] B. Englot and F. Hover, “Sampling-based coverage path planning for inspection of complex structures,” in International Con- ference on Automated Planning and Scheduling (ICAPS), 2012.

  • [27] J. Poppinga, A. Birk, K. Pathak, and N. Vaskevicius, “Fast 6-dof path planning for autonomous underwater vehicles (auv) based on 3d plane mapping,” in Safety, Security, and Rescue Robotics (SSRR), 2011 IEEE International Symposium on, nov. 2011, pp. 345 –350.

  • [28] A. Hornung, K. Wurm, M. Bennewitz, C. Stachniss, and W. Burgard, “Octomap: an efficient probabilistic 3d mapping framework based on octrees,” Autonomous Robots, vol. 34, no. 3, pp. 189–206, 2013.

  • [29] R. H. Bartels, J. C. Beatty, and B. A. Barsky, An Introduction to Splines for Use in Computer Graphics & Geometric Modeling. San Francisco, CA, USA: Morgan Kaufmann Publishers Inc., 1987.

  • [30] E. Galceran and M. Carreras, “Planning coverage paths on bathymetric maps for in-detail inspection of the ocean floor,” in Proc. International Conference on Robotics and Automation, 2013.

  • [31] D. Ribas, N. Palomeras, P. Ridao, M. Carreras, and A. Mallios, “Girona 500 auv, from survey to intervention,” IEEE/ASME Transactions on Mechatronics, vol. 17, no. 1, pp. 46–53, 2012.

  • [32] N. Palomeras, A. El-Fakdi, M. Carreras, and P. Ridao, “Cola2: A control architecture for auvs,” Oceanic Engineering, IEEE Journal of, vol. 37, no. 4, pp. 695–716, 2012.

  • [33] M. Prats, J. Perez, J. Fernandez, and P. Sanz, “An open source tool for simulation and supervision of underwater intervention missions,” in Intelligent Robots and Systems (IROS), 2012 IEEE/RSJ International Conference on, 2012, pp. 2577–2582.

About the article

Published Online: 2013-12-27

Published in Print: 2013-12-27



Citation Information: Paladyn, Journal of Behavioral Robotics, ISSN (Print) 2081-4836, DOI: https://doi.org/10.2478/pjbr-2013-0019. Export Citation

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