Visual Techniques for the Controlled Movement of Docking

  • Robin R. Murphy
Part of the NATO ASI Series book series (volume 83)


This paper discusses ongoing research in developing vision strategies for the docking behavior of an autonomous mobile robot, concentrating on the needs of the controlled movement of docking in a manufacturing environment. In the controlled movement, a perceptual strategy must provide feedback to the motor behavior in order to make accurate corrections to the mobile robot’s approach trajectory. Two novel techniques have been developed: adaptive tracking of an artificial landmark through a sequence of images, and the use of texture to recover relative depth and orientation. Experimental results are presented. These techniques, in conjunction with an inverse perspective transform technique for the coarse recovery of depth and orientation, form the basis of the perceptual strategy for the controlled movement.


Control Region Mobile Robot Flexible Manufacturing System Automate Guide Vehicle Autonomous Mobile Robot 
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.


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  1. [1]
    Allen, D., “Craft - a small prototype AGV for parts transfer between machine tools,” Proceedings 3rd Internation Conference on Automated Guided Vehicle Systems, Stockholm, Oct. 1985, pp. 112–121.Google Scholar
  2. [2]
    Arkin, R. C., “Spatial Uncertainty Management for a Mobile Robot and Its Role in Expectation- Based Perception,” Robot Control 1988 (Syroco ’88), Pergamon Press, Karlsruhe, FRG, October 5–7, 1988, pp. 279–284.Google Scholar
  3. [3]
    Arkin, R. C., “Towards Cosmopolitan Robots: Intelligent Navigation in Extended Man-Made Environments”. Ph.D. Dissertation, COINS TR-87–80, University of Massachusetts, Amherst, Sept. 1987.Google Scholar
  4. [4]
    Arkin, R., Murphy, R., “Autonomous Navigation in a Manufacturing Environment”, to appear in IEEE Journal of Robotics and Automation.Google Scholar
  5. [5]
    Arkin, R., Murphy, R., Pearson, M., and Vaughn, D., “Mobile Robot Docking Operations in a Manufacturing Environment: Progress in Visual Perceptual Strategies”, to appear in the proceedings of IEEE International Workshop on Intelligent Robots and Systems, Tsukuba, Japan, Sept. 4–6, 1989.Google Scholar
  6. [6]
    Arkin, R., Riseman, E. and Hanson, A., “Visual Strategies for Mobile Robot Navigation”, Proceedings of the IEEE Computer Society Workshop on Computer Vision, Miami Beach, Florida, 1987, pp. 176–181.Google Scholar
  7. [7]
    Banta, L., Dickerson, S., Bohlander, R., and Holcombe, W., “Reduced-order, Extended Kalman Filter for AGV Navigation.” Proceedings Winter ASME Meeting, 1987.Google Scholar
  8. [8]
    Dickmanns, E. E., and Wünsche, H. J., “Satellite Rendezvous Maneuvers by Means of Computer Vision”, Jahrbuch 1986 I, DGLR-Jahrestagung, München, 8–10, 1986.Google Scholar
  9. [9]
    Bruce, V., and Green, P., Visual Perception: Physiology, Psychology and Ecology, Lawrence Erlbaum Ass., Hillsdale, NJ, 1985.Google Scholar
  10. [10]
    Courtney, J. W., Magee, M. J. and Aggarwal, J. K., “Robot Guidance Using Computer Vision.” Pattern Recognition, vol. 17, no. 6, 1984, pp. 585–592.CrossRefGoogle Scholar
  11. [11]
    Daniel, W. W., and Terrell, J. C., Business Statistics: Basic Concepts and Methodology, Fourth ed., Houghton Mifflin, Boston, 1986, pp. 30–31.Google Scholar
  12. [12]
    Drake, K. C., McVey, E. S., and Inigo, R. M., “Experimental Position and Ranging Results for a Mobile Robot.” IEEE Journal of Robotics and Automation, vol. RA-3, no.1, February, 1987, pp. 31–42.CrossRefGoogle Scholar
  13. [13]
    Erwin, J. O., “Laser Docking System.” Proceedings of the Seventh Annual Rocky Mountain Guidance and Control Conference, Keystone, CO. February 4–8, 1984, pp. 239–253.Google Scholar
  14. [14]
    Frommherz, B. “Robot Action Planning,” University of Karlsruhe, Institute for Informatics III. Research Group: Process Control Computer Technology and Robotics.Google Scholar
  15. [15]
    Fukui, I. “TV Image Processing to Determine the Position of a Robot Vehicle,” Pattern Recognition, vol. 14, no. 1–6, 1981, pp. 101–109.CrossRefGoogle Scholar
  16. [16]
    Giralt, G., Chatila, R., and Vaisset, M. “An Integrated Navigation and Motion Control System for Autonomous Multisensory Mobile Robots,” Robotics Research, The First International Symposium, MIT Press, 1984, pp. 191–214.Google Scholar
  17. [17]
    Hongo, T., Arakawa, H., Sugimoto, G., Tange, K, and Yamamoto, Y., “An Automatic Guidance System of a Self-Controlled Vehicle,” IEEE Transactions on Industrial Electronics, vol. IE-34, no. 1, February 1987, pp. 5–10.CrossRefGoogle Scholar
  18. [18]
    Inigo, R. M., Tkacik, T., and McVey, E. S., “The application of linear image arrays to movile robot guidance and navigation.” Proceedings of the 3rd International Conference on Automated Guided Vehicle Systems, 15–17 October 1985. Stockholm, Sweden, pp. 157–168.Google Scholar
  19. [19]
    Kahn, P., Kitchen, L., and Riseman, E.M., “Real-Time Feature Extraction: a Fast Line Finder for Vision-Guided Robot Navigation”, COINS TR-87–57, University of Massachusetts, Amherst, 1987.Google Scholar
  20. [20]
    Kabuka, M.R., and Arenas, A.E., “Position Verification of a Mobile Robot Using Standard Pattern”, IEEE Journal of Robotics and Automation, vol. RA-3, no. 6, Dec., 1987, pp. 505–516.CrossRefGoogle Scholar
  21. [21]
    Michael, J. D. “A Study of Autonomous Rendezvous and Docking Systems,” Government publication N82–18298. publication date March 1982.Google Scholar
  22. [22]
    Milberg, J. and Luts, P. “Integration of Autonomous Mobile Robots into the Industrial Production Environment,” Proceedings of the 1st International Conferenc on AGVS, Stratford-upon-Avon, England, 1981, pp. 219–214.Google Scholar
  23. [23]
    Miura, T., Kondo, Y., and Yamauchi, F., “Automated Guided Vehicle Using Magnetic Marker.” Proceedings of the 3rd International Conference on Automated Guided Vehicle Systems, Stockholm, Sweden, 15–17 October 1985, pp. 181–188.Google Scholar
  24. [24]
    Murphy, R. R., “Adaptive Tracking for a Mobile Robot”, Technical Report #GIT-ICS-89/10, School of Information and Computer Science, Georgia Institute of Technology, 1989.Google Scholar
  25. [25]
    Murphy, R. R., “Autonomous Mobile Robots in CIMS: Current Work on Intelligent Docking”, Proceedings of the Sixth National Conference on University Programs in Computer-Aided Engineering, Design and Manufacturing, June 27–29, 1988, pp. 202–210.Google Scholar
  26. [26]
    Northmore, D., Volkmann, F. C., and Yager, D., “Vision in Fishes: Color and Pattern”, Mostofsky, D. I. (ed.), The Behavior of Fish and Other Aquatic Animals, Academic Press, New York, 1978, pp. 79–137.Google Scholar
  27. [27]
    Ray, A. J., Ross, S. E., Demming, D. R. “Rendezvous and docking tracker.” Proceedings of the Ninth Annual Rocky Mountain Guidance and Control Conference, Keystone, CO. (AAS86–014) 1986, pp. 109–118.Google Scholar
  28. [28]
    Tsumura, T., Fujiwara, N., Shirakw, T., and Hashimoto, J., “Automatic Vehicle Guidance - Commanded Map Routing,” Proceedings of the IEEE 1982 Vehicular Technology Conference, 1982, pp. 62–70.Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 1992

Authors and Affiliations

  • Robin R. Murphy
    • 1
  1. 1.School of Information and Computer ScienceGeorgia Institute of TechnologyAtlantaUSA

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