Advertisement

Integration and control of reactive visual processes

  • James L. Crowley
  • Jean Marc Bedrune
  • Morten Bekker
  • Michael Schneider
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 801)

Abstract

This paper describes a new approach to the integration and control of continuously operating visual processes. Visual processes are expressed as transformations which map signals from virtual sensors into commands for devices. These transformations define reactive processes which tightly couple perception and action. Such transformations may be used to control robotic devices, including fixation an active binocular head, as well as the to select and control the processes which interpret visual data.

This method takes inspiration from so-called “behavioural” approaches to mobility and manipulation. However, unlike most previous work, we define reactive transformations at the level of virtual sensors and device controllers. This permits a system to integrate a large number of perceptual processes and to dynamically compose sequences of such processes to perform visual tasks. The transition between visual processes is mediated by signals from a supervisory controller as well as signals obtained from perception. This method offers the possibility of constructing vision systems with large numbers of visual abilities in a manner which is both scalable and learnable.

Keywords

Tilt Angle Visual Process Action Space Face Detection Perceptual Space 
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.

Bibliography

  1. [1]
    J. Aloimonos, I. Weiss and A. Bandopadhay, “Active Vision”, International Journal on Computer Vision, pp. 333–356, 1987.Google Scholar
  2. [2]
    R. Bajcsy, “Active Perception”, Proceedings of the IEEE, Vol 76, No 8, Aug. 1988.Google Scholar
  3. [3]
    D. Ballard, “Animate Vision”, Artificial Intelligence, Vol 48, No. 1, February 1991.Google Scholar
  4. [4]
    A. G. Barto, “An approach to Learning Control Surfaces by Connectionist Systems”, in M. Arbib and A. Hanson, Vision, Brain and Cooperative Computation, MIT Press, Cambridge MA 1987.Google Scholar
  5. [5]
    R. A. Brooks, “A Robust Layered Control System for a Mobile Robot, IEEE Journal of Robotics and Automation, RA-2(1) March 1986.Google Scholar
  6. [6]
    C. Brown, “Prediction and Cooperation in Gaze Control”, Biological Cyber 63, 90.Google Scholar
  7. [7]
    K. Brunnström, “Active Exploration of Static Scenes”, Doctoral Dissertation, KTH — Royal School of Technology, Stockholm Sweden, 1993.Google Scholar
  8. [8]
    Carpenter G. A. “Neural network models for pattern recognition and associate memory”, Neural Networks, Vol 2, 1989.Google Scholar
  9. [9]
    D. Chapman and L. P. Kaelbling, “Learning from Delayed Reinforcement in a Complex Domain”, Proc. of the IJCAI, 1991.Google Scholar
  10. [10]
    A. Chehikian and J. L. Crowley, “Fast Computation of Optimal Semi-Octave Pyramids”, 7th S.C.I.A., Aalborg, August 1991.Google Scholar
  11. [11]
    Robot Learning, Edited by J. Connell and S. Mahadevan, Kluwer Academic Publishers, Boston, 1993.Google Scholar
  12. [12]
    Crowley, J. L., “Coordination of Action and Perception in a Surveillance Robot”, IEEE Expert, Vol 2(4), pp 32–43 Winter 1987, (Also appeared in IJCAI-87).Google Scholar
  13. [13]
    Crowley, J. L. “Towards Continuously Operating Integrated Vision Systems for Robotics Applications”, SCIA-91, Seventh Scandinavian Conference on Image Analysis, Aalborg, August 91.Google Scholar
  14. [14]
    Crowley, J. L., P. Bobet and M. Mesrabi, “Camera Control for a Active Camera Head”, Pattern Recognition and Artificial Intelligence, Vol 7, No. 1, January 1993.Google Scholar
  15. [15]
    Crowley, J. L.and H. I. Christensen, Vision as Process. Springer Verlag Basic Research Series, to appear 1993.Google Scholar
  16. [16]
    Crowley, J. L. and P. Reignier, “Asynchronous Control of Rotation and Translation for a Robot Vehicle”, Robotics and Autonmous Systems, Vol 10, No. 1, Jan. 1993.Google Scholar
  17. [17]
    Eklundh, J. O. and K. Pahlavan, “A head-eye system: Analysis and Design.”, CVGIP, 56:1. 1993.Google Scholar
  18. [18]
    J. A. Coelho and R. A. Grupen, “Constructing Effective Multifingered Grasp Controllers”, 1994 IEEE Conf. on Robotics and Automation, 1994.Google Scholar
  19. [19]
    L. P. Kaelbling Learning in Embedded Systems, MIT Press, Cambridge Mass, 93.Google Scholar
  20. [20]
    J. Kosecka and R. Bajcsy, “Discrete Event Systems for Autonomous Mobile Agents”, Intelligent Robotic Systems, '93, Zakopane, 1993 (also to appear in Robotics and Autonomous Systems, 12(3) March 94.Google Scholar
  21. [21]
    Krotkov, E., “Focusing”, International Journal of Computer Vision, 1, 1987.Google Scholar
  22. [22]
    Krotkov, E., Henriksen, K. and Kories, R., “Stereo Ranging from Verging Cameras”. IEEE Trans on PAMI, Vol 12, No. 12, pp. 1200–1205, December 1990.Google Scholar
  23. [23]
    D. A. Pomerlau, “Neural Network Based Autonomous Navigation”, in Vision and Navigation, C. Thorpe (ed)., Kluwer Academic Publishers, Boston, 1990.Google Scholar
  24. [24]
    P. J. Ramadge and W. M Wonham, “The Control of Discrete Event Systems”, Proceedings of the IEEE, 77(1), January 1989.Google Scholar
  25. [25]
    P. Reignier, “Fuzzy Logic Techniques for Mobile Robot Obstacle Avoidance”, Intelligent Robotic Systems, '93, Zakopane, 1993 (also in Robotics and Autonomous Systems, 12(3) March 94.Google Scholar
  26. [26]
    K. Souccar, M. Huber, and J. A. Coelho, “Sequencing Contollers — Experiments in Auronomous Reaching and Grasping”, 1994 IEEE Conference on Robotics and Automation, May 1994.Google Scholar
  27. [27]
    R. S. Sutton, “Integrated Architectures for Learning, Planning and Reacting Based on Approximating Dynamic Programming”, in Proceedings of the 7th Int. Conf. on Machine Learning, June 1990.Google Scholar
  28. [28]
    J.K. Tsotsos, “Representational Axes and Temporal Co-operative Processes”, In: Vision, Brain and Co-operative Computation, (Eds.) M.A. Arbib & A.R. Hanson, MIT Press, Cambridge, Mass, pp. 361–418, 1987.Google Scholar
  29. [29]
    Westelius, C. J., H. Knutsson, and G. H. Granlund, “Focus of Attention Control”, SCIA-91, Seventh Scandinavian Conference on Image Analysis, Aalborg, Aug. 91.Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 1994

Authors and Affiliations

  • James L. Crowley
    • 1
  • Jean Marc Bedrune
    • 1
  • Morten Bekker
    • 2
  • Michael Schneider
    • 2
  1. 1.IMAG - LIFIA, I.N.P. GrenobleGrenobleFrance
  2. 2.L.I.A. Aalborg UniversityAalborgDenmark

Personalised recommendations