Mapping and Navigating in Time-Varying Obstacle Fields

  • Ray Jarvis
Part of the International Series on Microprocessor-Based and Intelligent Systems Engineering book series (ISCA, volume 18)


Navigation schemes for autonomous mobile robots are critically dependent, in terms of functionality and robustness, on appropriately engineered and managed tight couplings between localisation, environmental mapping and path planning/execution sub-system components [ See Figure 1]. Various modalities of this scenario require more complex instrumentation and algorithmic considerations according to the degree of uncertainty which must be accommodated.


Mobile Robot Path Planning Robot Navigation Autonomous Mobile Robot Navigation Problem 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Kleeman, L. Ultrasonic Autonomous Robot Localisation System, IEEE International Conference — Intelligent Robotics and Systems ′89, Tsukuba, Japan, Sept. 1989, pp 212–219.Google Scholar
  2. 2.
    Jarvis, R.A. A Selective Survey of Localisation Methodology for Autonomous Mobile Robot Navigation, Proc. Robots for Competitive Industry Conference, July 14-16, 1993, Brisbane Australia, pp.310–317.Google Scholar
  3. 3.
    Clark, S. and Durrant-Whyte, H. The Design of a High Performance MMW Radar System for Autonomous Land Vehicle Navigation, Proc. International Conference on Field and Service Robots, Canberra, Australia, 8-10 Dec. 1997, pp.292–299.Google Scholar
  4. 4.
    Kong, X., Nebot, E., Durrant-Whyte, H. Use of Quaternions in a Low Cost Strapdown INS Unit, Proc. International Conference on Field and Service Robots, Canberra, Australia, 8-10 Dec. 1997, pp.286–291.Google Scholar
  5. 5.
    Brooks, R.A. Elephants Don't Play Chess, Journal of Robotics and Autonomous Systems, Vol. 6, 1990, pp.3–15.CrossRefGoogle Scholar
  6. 6.
    Chatila, R. and Lacroix, S. Adaptive Navigation for Autonomous Mobile Robots, Proc. The Seventh International Symposium on Robotics Research (edited by G. Giralt and G. Hirzinger), 1996, pp.450–458.Google Scholar
  7. 7.
    Jarvis, R.A. A Perspective on Range Finding Techniques for Computer Vision, IEEE Transactions on Pattern Analysis and Machine Intelligence. Vol. PAMI-5, No. 2, March 1983, pp.122–139.CrossRefGoogle Scholar
  8. 8.
    Moravec, H.P. Visual Mapping by a Robot Rover, Proc. 6th Int. Joint Conf. Artificial Intell., 1979, pp.598–620.Google Scholar
  9. 9.
    Faugeras, O.D. How Can Vision Make Mobile Robots Come True, Proc. International Symposium and Exposition on Robots, 6-10 Nov, 1988, Sydney, Australia, pp.1430–1461.Google Scholar
  10. 10.
    Braunstein, M.L. Depth Perception Through Motion, Academic Press, Inc. 1976.Google Scholar
  11. 11.
    Bolles, R.C. and Woodfill, J. Spatiotemporal Consistency Checking of Passive Range Data, Proc. 6th International Symposium on Robotics Research, Pittsburg, Pensylvania, Oct. 2-5, 1994, pp.165–183.Google Scholar
  12. 12.
    Prazdny, K. Motion and structure from optical flow. In Proc. 6th Int. Joint Conf. Artificial Intell., Tokyo, Japan, November 8-11, 1979, pp.702–704.Google Scholar
  13. 13.
    Kanade, T. Very Fast 3-D Sensing Hardware, Proc. The Sixth International Symposium on Robotics Research, Pitsburgh, Pennsylvania, Oct. 2-5, 1993, pp.185–198.Google Scholar
  14. 14.
    Chong, K.S. and Kleeman, L. Large Scale Sonarray Mapping using Multiple Connected Local Maps, Proc. International Conference on Field and Service Robotics, Canberra, Dec. 8-10, 1997, pp.538–545.Google Scholar
  15. 15.
    Jarvis, R.A. and Lipton, A.J. GO-2: — An Autonomous Mobile Robot for a Science Museum, Proc. 4th International Conference on Control, Automation, Robotics and Vision, Westin Stamford, Singapore, 3-6 December, 1996, pp.260–266.Google Scholar
  16. 16.
    Nillson, N.J. Problem-Solving Methods in Artificial Intelligence, McGraw-Hill, 1971.Google Scholar
  17. 17.
    Lozano-Perez, L. and Wesley, M.A. (1979): An Algorithm for Planning Collision-free Paths Among Polyhedral Obstacles, Commun. ACM, 22, 10 Oct 1979, pp.560–570.Google Scholar
  18. 18.
    Jarvis, R.A. Growing Polyhedral Obstacles for Planning Collision-Free Paths, The Australian Computer Journal, vol. 15, No. 3, August 1983, pp.103–111.Google Scholar
  19. 19.
    Rosenfeld, A. and Pfaltz, J.L. Sequential Operations in Digital Image Processing, J.A.C.M., Vol. 13, No. 4, Oct. 1966, pp.471–494.zbMATHGoogle Scholar
  20. 20.
    Jarvis, R.A. On Distance Transform Based Collision-Free Path Planning for Robot Navigation in Known, Unknown and Time-Varying Environments, invited chapter for a book entitled‘Advanced Mobile Robots’ edited by Professor Yuan F. Zang. World Scientific Publishing Co. Pty. Ltd. 1994, pp.3–31.Google Scholar
  21. 21.
    Jarvis, R.A. Configuration Space Collision-Free Path Planning for Robotic Manipulators, Proc. 10th Australian Computer Science Conference, Deakin University, Victoria, 4-6 Feb. 1987, pp.193–204.Google Scholar
  22. 22.
    Tang, K.W. and Jarvis, R.A. Collision-Free Path Finding amongst Polygonal Obstacles using Efficient Free Space Triangulation, Proc. Second International Conference on Automation, Robotics and Computer Vision, 15-18 Sept. 1992, Singapore, pp. RO-11.1.1-RO-11.1.5.Google Scholar
  23. 23.
    Zelinsky. A. Robot Navigation with Learning, The Australian Computer Journal, Vol. 20, No. 2, May 1988, pp.85–93.Google Scholar
  24. 24.
    Udupa, S.M. (1977): Collision Detection and Avoidance in Computer Controlled Manipulators, Proceedings of 5th International Joint Conference on Artificial Intelligence, August 1977, pp.737–748.Google Scholar
  25. 25.
    Brooks, R.A. (1983): Solving the Find-Path Problem by a Good Representation of Free Space, IEEE Trans. on Systems, Man and Cybernetics, SMC-13, No. 3, March 1983, pp.190–197.Google Scholar
  26. 26.
    Chatila, R. (1982): Path Planning and Environment Learning, European Conference on Artificial Intelligence, July 1982, pp.211–215.Google Scholar
  27. 27.
    Jarvis, R.A. Collision-Free Path Planning in Time Varying Environments, Proc. I.E.E.E./R.S.J. International Workshop on Intelligent Robots and Systems, ′89, Tsukuba, Japan, Sept. 4-6 ′89, pp.99–106.Google Scholar
  28. 28.
    Jarvis, R.A. Collision-Free Path Planning in Time-Varying Obstacle Fields Without Perfect Prediction, Proc. ′93 ICAR, International Conference on Advanced Robotics, No. 1-2 1993, Tokyo, Japan, pp.701–706.Google Scholar
  29. 29.
    Jarvis, R.A. Video Plane Robot Swarms, Robotics and Computer Integrated Manufacturing, Vol. 11, No. 4, 1994, pp.249–258.Google Scholar
  30. 30.
    Jarvis, R.A. Natural Landmark Based Robot Navigation in Distance Transform Space, Proc. AI′95, Canberra, 1995, pp.323–330.Google Scholar
  31. 31.
    Jarvis, R.A. Etherbot — An Autonomous Mobile Robot on a Local Area Network Radio Tether, Proc. Fifth International Symposium on Experimental Robotics, Barcelona, Catalonia, June 15-18, 1997, pp.151–163.Google Scholar
  32. 32.
    Jarvis, R.A. An Autonomous Heavy Duty Outdoor Robotic Tracked Vehicle, Proc. International Conference on Intelligent Robots and Systems, Grenoble, France, Sept. 8-12, 1997, pp.352–359.Google Scholar

Copyright information

© Springer Science+Business Media Dordrecht 1999

Authors and Affiliations

  • Ray Jarvis
    • 1
  1. 1.Intelligent Robotics Research CentreMonash UniversityClaytonAustralia

Personalised recommendations