Skip to main content
SpringerLink
Log in

Integrating vision and spatial reasoning for assistive navigation

  • Chapter
  • First Online:
Book cover Assistive Technology and Artificial Intelligence

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 1458))

Abstract

This paper describes the goals and research directions of the University of Texas Artificial Intelligence Lab's Intelligent Wheelchair Project (IWP). The IWP is a work in progress. The authors are part of a collaborative effort to bring expertise from knowledge representation, control, planning, and machine vision to bear on this difficult and interesting problem domain. Our strategy uses knowledge about the semantic structure of space to focus processing power and sensing resources. The semi-autonomous assistive control of a wheelchair shares many sub-problems with mobile robotics, including those of sensor interpretation, spatial knowledge representation, and real-time control. By enabling the wheelchair with active vision and other sensing modes, and by application of our theories of spatial knowledge representation and reasoning, we hope to provide substantial assistance to people with severe mobility impairments.

This work has taken place in the Qualitative Reasoning Group at the Artificial Intelligence Laboratory, The University of Texas at Austin. Research of the Qualitative Reasoning Group is supported in part by NSF grants IRI-9504138 and CDA 9617327, by NASA grant NAG 9-898, and by the Texas Advanced Research Program under grants no. 003658-242 and 003658-347.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. J. R. Anderson. Spreading activation. In J. R Anderson and S. M. Kosslyn, editors, Tutorials in Learning and memory: Essays in honor of Gordon Bower. W.H. Freeman, 1984.

    Google Scholar 

  2. D.H. Ballard. Animate vision. Artificial Intelligence, 48:57–86, 1991.

    Article  Google Scholar 

  3. W.S. Gribble. Slow visual search in a fast-changing world. In Proceedings of the 1995 IEEE Intl. Symposium on Computer Vision (ISCV-95), 1995.

    Google Scholar 

  4. W.S. Gribble. ARGUS: a distributed environment for real-time vision. Master's thesis, University of Texas at Austin AI Lab, Austin, Texas, 1995.

    Google Scholar 

  5. W.S. Gribble, R.L. Browning, and B.J. Kuipers. Dynamic binding of visual percepts for robot control. Unpublished manuscript, 1997.

    Google Scholar 

  6. G.D. Hager. Task-directed sensor fusion and planning: a computational approach. Kluwer Academic Publishers, 1990.

    Google Scholar 

  7. A. Bandopadhay J. Aloimonos and I. Weiss. Active vision. Int. J. Computer Vision, 1:333–356, 1988.

    Article  Google Scholar 

  8. B. Kuipers. A hierarchy of qualitative representations for space. In Working papers of the Tenth International Workshop on Qualitative Reasoning about Physical Systems (QR-96). AAAI Press, 1996.

    Google Scholar 

  9. B. Kuipers and Y. T. Byun. A robot exploration and mapping strategy based on semantic hierarchy of spatial representations. Journal of Robotics and Autonomous Systems, 8:47–63, 1991.

    Article  Google Scholar 

  10. B. J. Kuipers and T. Levitt. Navigation and mapping in large scale space. AI Magazine, 9(2):25–43, 1988. Reprinted in Advances in Spatial Reasoning, Volume 2, Su-shing Chen (Ed.), Norwood NJ: Ablex Publishing, 1990.

    Google Scholar 

  11. D. McDermott and E. Davis. Planning routes through uncertain territory. Artificial Intelligence, 22:107–156, 1984.

    Article  Google Scholar 

  12. D.M. Pierce and B. Kuipers. Map learning with uninterpreted sensors and effectors. Artificial Intelligence, 92:169–227, 1997.

    Article  MATH  Google Scholar 

  13. C.E. Thorpe, editor. Vision and Navigation: the Carnegie-Mellon Navlab. Kluwer Academic Publishers, 1996.

    Google Scholar 

  14. A. Treisman. Features and objects. In A. Baddeley and L. Weiskrantz, editors, Attention: Selection, Awareness and Control. Clarendon Press, 1993.

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Dept. of Electrical and Computer Engineering, The University of Texas at Austin, 78712, Austin, TX, USA

    William S. Gribble

  2. Dept. of Computer Sciences, The University of Texas at Austin, 78712, Austin, TX, USA

    Robert L. Browning, Micheal Hewett, Emilio Remolina & Benjamin J. Kuipers

Authors
  1. William S. Gribble
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Robert L. Browning
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Micheal Hewett
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Emilio Remolina
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Benjamin J. Kuipers
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Vibhu O. Mittal Holly A. Yanco John Aronis Richard Simpson

Rights and permissions

Reprints and permissions

Copyright information

© 1998 Springer-Verlag Berlin Heidelberg

About this chapter

Cite this chapter

Gribble, W.S., Browning, R.L., Hewett, M., Remolina, E., Kuipers, B.J. (1998). Integrating vision and spatial reasoning for assistive navigation. In: Mittal, V.O., Yanco, H.A., Aronis, J., Simpson, R. (eds) Assistive Technology and Artificial Intelligence. Lecture Notes in Computer Science, vol 1458. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0055978

Download citation

  • DOI: https://doi.org/10.1007/BFb0055978

  • Published:

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-64790-4

  • Online ISBN: 978-3-540-68678-1

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics

Search

Navigation