International Journal of Fuzzy Logic and Intelligent Systems

Korean Institute of Intelligent Systems (한국지능시스템학회)
권호 표지
DOI QR코드

DOI QR Code

3D Global Dynamic Window Approach for Navigation of Autonomous Underwater Vehicles

  • Tusseyeva, Inara (Department of Computer Science and Engineering Research Institute (ERI), Gyeongsang National University) ;
  • Kim, Seong-Gon (Research Institute, LG Electronics) ;
  • Kim, Yong-Gi (Department of Computer Science and Engineering Research Institute (ERI), Gyeongsang National University)
  • Received : 2013.01.09
  • Accepted : 2013.06.07
  • Published : 2013.06.25
Download PDF
⟨ Previous Next ⟩

Abstract

An autonomous unmanned underwater vehicle is a type of marine self-propelled robot that executes some specific mission and returns to base on completion of the task. In order to successfully execute the requested operations, the vehicle must be guided by an effective navigation algorithm that enables it to avoid obstacles and follow the best path. Architectures and principles for intelligent dynamic systems are being developed, not only in the underwater arena but also in related areas where the work does not fully justify the name. The problem of increasing the capacity of systems management is highly relevant based on the development of new methods for dynamic analysis, pattern recognition, artificial intelligence, and adaptation. Among the large variety of navigation methods that presently exist, the dynamic window approach is worth noting. It was originally presented by Fox et al. and has been implemented in indoor office robots. In this paper, the dynamic window approach is applied to the marine world by developing and extending it to manipulate vehicles in 3D marine environments. This algorithm is provided to enable efficient avoidance of obstacles and attainment of targets. Experiments conducted using the algorithm in MATLAB indicate that it is an effective obstacle avoidance approach for marine vehicles.

Keywords

References

  1. A. Naik, "Arc path collision avoidance algorithm for autonomous ground vehicles," M.S. thesis, Department of Mechanical Engineering, Virginia Polytechnic Institute and State University, Blacksburg, VA, 2005.
  2. A. R. Anwary, Y. I. Lee, H. Jung, and Y. G. Kim, "Unsupervised real-time obstacle avoidance technique based on a hybrid fuzzy method for AUVs,"International Journal of Fuzzy Logic and Intelligent Systems, vol. 8, no. 1, pp. 82-86, Mar. 2008. http://dx.doi.org/10.5391/IJFIS.2008.8.1.082
  3. A. C. Bukhari, I. Tusseyeva, B. G. Lee, and Y. G. Kim, " An intelligent real-time multi-vessel collision risk assessment system from VTS view point based on fuzzy inference system," Expert Systems with Applications, vol. 40, no. 4, pp. 1220-1230, Mar. 2013. http://dx.doi.org/10.1016/j.eswa.2012.08.016
  4. D. Fox, W. Burgard, and S. Thrun, "The dynamic window approach to collision avoidance," IEEE Robotics & Automation Magazine, vol. 4, no. 1, pp. 23-33, Mar. 1997. http://dx.doi.org/10.1109/100.580977
  5. R. Simmons, "The curvature-velocity method for local obstacle avoidance," in Proceedings of 1996 IEEE International Conference on Robotics and Automation, Minneapolis, MN, 1996, pp. 3375-3382. http://dx.doi.org/10.1109/ROBOT.1996.511023
  6. N. Kim, G. H. Yoon, and D. Lee, "Intelligent navigation and control of an autonomous underwater vehicle based on Q-learning and self-organizing control," in Proceedings of 2009 ICCAS-SICE, Fukuoka, 2009, pp. 630-634.
  7. V. M. Kureichik, Genetic algorithm and its application, Taganrog TRTU, 2002. http://www.twirpx.com/file/601002/
  8. O. Brock and O. Khatib, "High-speed navigation using the global dynamic window approach," in Proceedings of 1999 IEEE International Conference on Robotics and Automation, Detroit, MI, 1999, pp. 341-346. http://dx.doi.org/10.1109/ROBOT.1999.770002
  9. D. Fox, W. Burgard, and S. Thrun, "Controlling synchrodrive robots with the dynamic window approach to collision avoidance," in Proceedings of 1996 IEEE/RSJ International Conference on Intelligent Robots and Systems, Osaka, 1996, pp. 1280-1287. http://dx.doi.org/10.1109/IROS.1996.568982
  10. D. Fox, W. Burgard, S. Thrun, and A. B. Cremers, "A hybrid collision avoidance method for mobile robots," in Proceedings of 1998 IEEE International Conference on Robotics and Automation, Leuven, 1998, pp. 1238-1243. http://dx.doi.org/10.1109/ROBOT.1998.677270
  11. C. Stachniss and W. Burgard, "An integrated approach to goal-directed obstacle avoidance under dynamic constraints for dynamic environments," in Proceedings of IEEE/RSJ International Conference on Intelligent Robots and Systems, Lausanne, 2002, pp. 508-513. http://dx.doi.org/10.1109/IRDS.2002.1041441
  12. M. Seder and I. Petrovic, "Dynamic window based approach to mobile robot motion control in the presence of moving obstacles," in Proceedings of 2007 IEEE International Conference on Robotics and Automation, Roma, 2007, pp. 1986-1991. http://dx.doi.org/10.1109/ROBOT.2007.363613
  13. M. Seder, K. Macek, and I. Petrovic, "An integrated approach to real-time mobile robot control in partially known indoor environments," in Proceedings of 31st Annual Conference of IEEE Industrial Electronics Society, Raleigh, NC, 2005, pp. 1785-1790. http://dx.doi.org/10.1109/IECON.2005.1569176
  14. C. Schroter, M. Hochemer, and H. M. Gross, "A particle filter for the dynamic window approach to mobile robot control," in Proceedings of the 25nd International Scientific Colloquium (IWK), Ilmenau, 2007, pp. 425-430.
  15. K. Y. Kwon, J. Cho, and J. Joh, "Collision avoidance of moving obstacles for underwater robots," Journal of Systemics, Cybernetics and Informatics, vol. 4, no. 5, pp. 86-91, 2006.
  16. L. D. Bui and Y. G. Kim, "A new approach of BK products of fuzzy relations for obstacle avoidance of autonomous underwater vehicles," International Journal of Fuzzy Logic and Intelligent Systems, vol. 4, no. 2, pp. 135-141, Sep. 2004. http://dx.doi.org/10.5391/IJFIS.2004.4.2.135
  17. H. S. Kim, T. S. Jin, and J. N. Sur, "Intelligent 3-D obstacle avoidance algorithm for autonomous control of underwater flight vehicle," Journal of Korean Institute of Intelligent Systems, vol. 21, no. 3, pp. 323-328, Jun. 2011. http://dx.doi.org/10.5391/JKIIS.2011.21.3.323
  18. Z. S. Mi and Y. G. Kim, "Intelligent 3D obstacles recognition technique based on support vector machines for autonomous underwater vehicles," International Journal of Fuzzy Logic and Intelligent Systems, vol. 9, no. 3, pp. 213-218, Sep. 2009. http://dx.doi.org/10.5391/IJFIS.2009.9.3.213
  19. H. S. Kim, H. J. Kang, Y. J. Ham, and S. S. Park, "Development of underwater-type autonomous marine robot-kit," Journal of Korean Institute of Intelligent Systems, vol. 22, no. 3, pp. 312-318, Jun. 2012. http://dx.doi.org/10.5391/JKIIS.2012.22.3.312
  20. J. S. Joh, K. Y. Kwon, and S. M. Lee, "Collision avoiding navigation of marine vehicles using fuzzy logic," International Journal of Fuzzy Logic and Intelligent Systems, vol. 2, no. 2, pp. 100-108, Jun. 2002. http://dx.doi.org/10.5391/IJFIS.2002.2.2.100
  21. T. S. Jin, "Obstacle avoidance of mobile robot based on behavior hierarchy by fuzzy logic," International Journal of Fuzzy Logic and Intelligent Systems, vol. 12, no. 3, pp. 245-249, Sep. 2012. http://dx.doi.org/10.5391/IJFIS.2012.12.3.245
  22. O. Khatib, "Real-time obstacle avoidance for manipulators and mobile robots," International Journal of Robotics Research, vol. 5, no. 1, pp. 90-98, Mar. 1986. http://dx.doi.org/10.1177/027836498600500106
  23. J. Y. Bouguet and P. Perona, "Visual navigation using a single camera," in Proceedings of 5th International Conference on Computer Vision, Cambridge, MA, 1995, pp. 645-652. http://dx.doi.org/10.1109/ICCV.1995.466877
  24. J. C. Latombe, Robot Motion Planning, Boston: Kluwer Academic Publishers, 1991.

Cited by

  1. Design, Control, and Implementation of Small Quad-Rotor System Under Practical Limitation of Cost Effectiveness vol.13, pp.4, 2013, https://doi.org/10.5391/IJFIS.2013.13.4.324
  2. Dynamic Obstacle Avoidance for Unmanned Underwater Vehicles Based on an Improved Velocity Obstacle Method vol.17, pp.12, 2017, https://doi.org/10.3390/s17122742