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Behavior Based Robotics Using Hybrid Automata

  • Magnus Egerstedt
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1790)

Abstract

In this article, we show how a behavior based control system for autonomous robots can be modeled as a hybrid automaton, where each node corresponds to a distinct robot behavior. This type of construction gives rise to chattering executions, but we show how regularized automata suggest a solution to this problem. We also discuss some design and implementation issues.

Keywords

Mobile Robot Path Planning Obstacle Avoidance Autonomous Robot Discrete Transition 
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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References

  1. 1.
    J. Ackermann. Robust Control. Springer-Verlag, London, 1993.zbMATHGoogle Scholar
  2. 2.
    M. Andersson, A. Orebäck, M. Lindström, and H.I. Christensen. Intelligent Sensor Based Robotics. Ch. ISR: An Intelligent Service Robot, Lecture Notes in Artificial Intelligence, Heidelberg: Springer Verlag, 1999.Google Scholar
  3. 3.
    R.C. Arkin. Behavior-Based Robotics. The MIT Press, Cambridge, Massachusetts, 1998.Google Scholar
  4. 4.
    M. Egerstedt, X. Hu, and A. Stotsky. Control of a Car-Like Robot Using a Virtual Vehicle Approach. Proceedings of the 37th IEEE Conference on Decision and Control, pp. 1502–1507, Tampa, Florida, USA, Dec. 1998.Google Scholar
  5. 5.
    M. Egerstedt, X. Hu, and A. Stotsky. A Hybrid Control Approach to Action Coordination for Mobile Robots. Proceedings of IFAC’99:14th World Congress, Beijing, China, Jul., 1999.Google Scholar
  6. 6.
    M. Egerstedt, K. Johansson, J. Lygeros, and S. Sastry. Behavior Based Robotics Using Regularized Hybrid Automata. Proceedings of CDC’99, Phoenix, Arizona, Dec, 1999.Google Scholar
  7. 7.
    A.F. Filippov. Differential Equations with Discontinuous Righthand Sides. Kluwer Academic Publishers, 1988.Google Scholar
  8. 8.
    K. Johansson, M. Egerstedt, J. Lygeros, and S. Sastry. Regularization of Zeno Hybrid Automata. Systems and Control Letters, 1999. Accepted for publication in 1999 Special Issue on Hybrid Systems.Google Scholar
  9. 9.
    O. Khatib, K. Yokoi, K. Chang, D. Ruspini, R. Holmberg, A. Casal and A. Baader: Force Strategies for Cooperative Tasks in Multiple Mobile Manipulation Systems. International Symposium of Robotics Research, Munich, October 1995.Google Scholar
  10. 10.
    D. Kortenkamp, R.P. Bonasso, and R. Murphy, Eds. Artificial Intelligence and Mobile Robots. The MIT Press, Cambridge, Massachusetts, 1998.Google Scholar
  11. 11.
    J. Košecká: A Framework for Modeling and Verifying Visually Guided Agents: Design, Analysis and Experiments. Dissertation, Grasp Lab, March 1996.Google Scholar
  12. 12.
    B. Krogh and C. Thorpe. Integrated Path Planning and Dynamic Steering Control for Autonomous Vehicles, Proceedings of the 1986 IEEE International Conference on Robotics and Automation, San Francisco, CA, pp. 1664–1669, 1986.Google Scholar
  13. 13.
    J.C. Latombe. Robot Motion Planning, Kluwer Academic Publishers, 1991.Google Scholar
  14. 14.
    J. Lygeros, C. Tomlin, and S. Sastry. Controllers for Reachability Specifications for Hybrid Systems. Automatica, Vol. 35, No. 3, March 1999.Google Scholar
  15. 15.
    J. Malmborg. Analysis and Design of Hybrid Control Systems. PhD thesis, Department of Automatic Control, Lund Institute of Technology, Lund, Sweden, May 1998.Google Scholar
  16. 16.
    L. Petersson, M. Egerstedt, and H.I. Christensen. A Hybrid Control Architecture for Mobile Manipulation. Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, Kyongju, Korea, Oct. 1999.Google Scholar
  17. 17.
    N. Sarkar, X. Yun, and V. Kumar. Dynamic Path Following: A New Control Algorithm for Mobile Robots. Proceedings of the 32nd Conference on Decision and Control, San Antonio, Texas, Dec. 1993.Google Scholar
  18. 18.
    A. Stenz. Optimal and Efficient Path Planning for Partially Known Environments, Proceedings of the 1994 IEEE International Conference on Robotics and Automation, 1994.Google Scholar
  19. 19.
    C. Tomlin, G. Papas, J. Košecká, J. Lygeros, and S.S. Sastry. Advanced Air Traffic Automation: A Case Study in Distributed Decentralized Control, Control Problems in Robotics, Lecture Notes in Control and Information Sciences 230, Springer-Verlag, London, 1998.CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2000

Authors and Affiliations

  • Magnus Egerstedt
    • 1
  1. 1.Division of Optimization and Systems TheoryRoyal Institute of TechnologyStockholmSweden

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