skip to main content
10.1145/1174429.1174470acmconferencesArticle/Chapter ViewAbstractPublication PagesgraphiteConference Proceedingsconference-collections
Article

Methodologies for immersive robot programming in an augmented reality environment

Published:29 November 2006Publication History

ABSTRACT

Advancements in robotics have gained much momentum in recent years. Industrial robotic systems are increasingly being used outside the factory floor, evident by the growing presence of service robots in personal environments. In light of these trends, there is currently a pressing need of identifying new ways of programming robots safely, quickly and more intuitively. These methods should focus on service robots and address long outstanding Human-Robot Interaction issues in industrial robotics simultaneously. In this paper, the potential of using an Augmented Reality (AR) environment to facilitate immersive robot programming in unknown environments is explored. The benefits of an AR environment over conventional robot programming approaches are discussed, followed by a description of the Robot Programming using AR (RPAR) system developed in this research. New methodologies for programming two classes of robotic tasks using RPAR are proposed. A number of case studies are presented and the results discussed.

References

  1. Aleoti, J., Caselli, S., and Reggiani, M. 2004. Leveraging on a Virtual Environment for Robot Programming by Demonstration. Robotics and Autonomous Systems 47, 2--3, 153--161.Google ScholarGoogle Scholar
  2. Azuma, R. T. 1997. A Survey of Augmented Reality. Presence: Teleoperators and Virtual Environments 6, 4, 355--385.Google ScholarGoogle ScholarDigital LibraryDigital Library
  3. Besl, P. J. 1992. A Method for Registration of 3D Shapes. IEEE Transactions on Pattern Analysis and Machine Intelligence 14, 2, 239--256. Google ScholarGoogle ScholarDigital LibraryDigital Library
  4. Bobrow, J. E., Dubowsky, S., and Gibson, J. S. 1985. Time-Optimal Control of Robotic Manipulators along Specified Paths. International Journal of Robotics Research 4, 3, 3--17.Google ScholarGoogle ScholarCross RefCross Ref
  5. Craig, J. J. 1989. Introduction to Robotics, Mechanics and Control. Addison-Wesley. Google ScholarGoogle ScholarDigital LibraryDigital Library
  6. Delson, N., and West, H. 1994a. Robot Programming by Human Demonstration: The Use of Human Variation in Identifying Obstacle Free Trajectories. In Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), vol. 1, 564--571.Google ScholarGoogle Scholar
  7. Delson, N., and West, H. 1994b. Robot Programming by Human Demonstration: The Use of Human Variation in Improving 3D Robot Trajectories. In Proceedings of the IEEE/RSJ/GI International Conference on Intelligent Robots and Systems (IROS), vol. 2, 1248--1255.Google ScholarGoogle Scholar
  8. Farin, G. 2002. Curves and Surfaces for CAGD: A Practical Guide, 5th Ed. Morgan-Kaufman. Google ScholarGoogle ScholarDigital LibraryDigital Library
  9. Friedrich, H., Munch, S., Dillmann, R., Bocionek, S., and Sassin, M. 1996. Robot Programming by Demonstration (RPD): Supporting the Induction by Human Interaction. Machine Learning 23, 2--3, 163--189. Google ScholarGoogle ScholarDigital LibraryDigital Library
  10. Furcy, D. 2004. Speeding Up the Convergence of Online Heuristic Search and Scaling Up Offline Heuristic Search. PhD thesis, Georgia Institute of Technology. Google ScholarGoogle ScholarDigital LibraryDigital Library
  11. Hoschek, J. 1988. Intrinsic Parametrization for Approximation. Computer Aided Geometric Design 5, 1, 27--31. Google ScholarGoogle ScholarDigital LibraryDigital Library
  12. Kaiser, M., Retey, A., and Dillmann, R. 1995. Robot Skill Acquisition via Human Demonstration. In Proceedings of the 7th International Conference on Advanced Robotics (ICAR), 763--768.Google ScholarGoogle Scholar
  13. Kato, H., and Billinghurst, M. 1999. Marker Tracking and HMD Calibration for a Video-based Augmented Reality Conferencing System. In Proceedings of the 2nd IEEE and ACM International Workshop on Augmented Reality, San Francisco, 85--94. Google ScholarGoogle ScholarDigital LibraryDigital Library
  14. Mackay, D. J. C. 1995. Bayesian Methods for Neural Networks: Theory and Applications. Lecture Notes, University of Cambridge Programme for Industry, July.Google ScholarGoogle Scholar
  15. Nanotek, E., Zimmerman, T., and Fluckiger, L. 1995. Model Based Vision as Feedback for Virtual Reality Robotics Environment. In Proceedings of the IEEE Virtual Reality Annual International Symposium (VRAIS), 110--117. Google ScholarGoogle ScholarDigital LibraryDigital Library
  16. Pettersen, T., Pretlove, J., Skourup, C., Engedal, T., and Lokstad, T. 2003. Augmented Reality for Programming Industrial Robots. In Proceedings of the International Symposium on Mixed and Augmented Reality (ISMAR), 319--320. Google ScholarGoogle ScholarDigital LibraryDigital Library
  17. Rastogi, A., and Milgram, P. 1995. Augmented Telerobotic Control: A Visual Interface for Unstructured Environments. In Proceedings of the KBS/Robotics Conference, 16--18.Google ScholarGoogle Scholar
  18. Schwald, B., and Laval, B. 2003. An Augmented Reality System for Training and Assistance to Maintenance in the Industrial Context. Journal of WSCG 11, 1, 425--432.Google ScholarGoogle Scholar
  19. Sung, J. A. 2004. Least Squares Orthogonal Distance Fitting of Curves and Surfaces in Space. Springer-Verlag.Google ScholarGoogle Scholar
  20. U.S. Department Of Labor, 2006. OSHA Technical Manual, Industrial Robots and Robot System Safety, Section IV: Chapter 4. Available: http://www.osha.gov/dts/osta/otm/otm iv/otm iv 4.html, last accessed on 10 Sept. 2006.Google ScholarGoogle Scholar

Index Terms

  1. Methodologies for immersive robot programming in an augmented reality environment

            Recommendations

            Comments

            Login options

            Check if you have access through your login credentials or your institution to get full access on this article.

            Sign in
            • Published in

              cover image ACM Conferences
              GRAPHITE '06: Proceedings of the 4th international conference on Computer graphics and interactive techniques in Australasia and Southeast Asia
              November 2006
              489 pages
              ISBN:1595935649
              DOI:10.1145/1174429

              Copyright © 2006 ACM

              Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

              Publisher

              Association for Computing Machinery

              New York, NY, United States

              Publication History

              • Published: 29 November 2006

              Permissions

              Request permissions about this article.

              Request Permissions

              Check for updates

              Qualifiers

              • Article

              Acceptance Rates

              GRAPHITE '06 Paper Acceptance Rate47of83submissions,57%Overall Acceptance Rate124of241submissions,51%

            PDF Format

            View or Download as a PDF file.

            PDF

            eReader

            View online with eReader.

            eReader