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Accurate Map Building via Fusion of Laser and Ultrasonic Range Measures

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Fuzzy Logic Techniques for Autonomous Vehicle Navigation

Part of the book series: Studies in Fuzziness and Soft Computing ((STUDFUZZ,volume 61))

Abstract

Reactivity to workspace features and workspace changes is an essential capability for robotic systems performing motion tasks in unstructured environments [1,11,24]. A truly autonomous mobile robot should be able to discriminate between safe and dangerous areas, recognize free passages, as well as detect possibly moving obstacles. These goals can be achieved only if the robot is endowed with a fast, reliable, accurate sensory system.

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References

  1. R. C. Arkin, “Integrating behavioral, perceptual, and world knowledge in reactive navigation,” Robotics and Autonomous Systems, vol. 6, pp. 105–122, 1990.

    Article  Google Scholar 

  2. H. Bandemer and W. Näther, Fuzzy Data Analysis, Kluwer Academic Publishers, 1992.

    Book  MATH  Google Scholar 

  3. I. Bloch, “Information combination operators for data fusion: A comparative review with classification,” IEEE Trans. on Systems, Man, and Cybernetics, vol. 26, no. 1, part A, pp. 52–67, 1996.

    Article  Google Scholar 

  4. P. P. Bonissone, “Reasoning, plausible,” in The Encyclopedia of Artificial Intelligence (S. Shapiro, Ed.), John Wiley and Sons, 2nd Edition, pp. 1307–1322, 1991.

    Google Scholar 

  5. D. W. Cho, “Certainty grid representation for robot navigation by a Bayesian method”, Robotica, vol. 8, pp. 159–165, 1990.

    Article  Google Scholar 

  6. B. V. Dasarathy, Decision Fusion, IEEE Computer Society Press, 1994.

    Google Scholar 

  7. D. Dubois, N. P. Wellmann, B. D’Ambrosio, and Ph. Smets, “The nature of unnormalized beliefs encountered in the transferable belief model,” 8th Conf. on Uncertainty in Artificial Intelligence, pp. 292–297, 1992.

    Google Scholar 

  8. H. F. Durrant-Whyte, Integration, Coordination and Control of Multi-Sensor Robot Systems, Kluwer Academic Publishers, 1988.

    Google Scholar 

  9. H. F. Durrant Whyte, “Sensor models and multisensor integration,” Int. J. of Robotics Research, vol. 7, no. 6, pp. 97–113, 1988.

    Article  Google Scholar 

  10. A. Elfes, “Occupancy grids: A stochastic spatial representation for active robot perception,” in Autonomous Mobile Robots: Perception, Mapping, and Navigation (S. S. Iyengar and A. Elfes, Eds.), IEEE Computer Society Press, pp. 60–71, 1991.

    Google Scholar 

  11. E. Gat, “Integrating planning and reacting in a heterogeneous asynchronous architecture for mobile robot navigation,” SIGART Bulletin, vol. 2, pp. 70–74, 1991.

    Article  Google Scholar 

  12. F. Gambino, G. Oriolo, and G. Ulivi, “A comparison of three uncertainty calculus techniques for ultrasonic map building,” 1996 SPIE Int. Symp. on Aerospace/Defense Sensing and Control, pp. 249–260, 1996.

    Google Scholar 

  13. S. J. Henkind and M. C. Harrison, “An analysis of four uncertainty calculi,” IEEE Trans. on Systems, Man, and Cybernetics, vol. 18, no. 5, pp. 700–714, 1988.

    Article  MathSciNet  Google Scholar 

  14. T. L. Huntsberger and S. N. Jayaramamurthy, “A framework for multisensor fusion in the presence of uncertainty,” Workshop on Spatial Reasoning and Multisensor Fusion, pp. 345–350, 1987.

    Google Scholar 

  15. A. C. Kak, B. A. Roberts, K. M. Andress, and R. L. Cromwell, “Experiments in the integration of world knowledge with sensory information for mobile robots,” 1987 IEEE Int. Conf. on Robotics and Automation, pp. 734–740, 1987.

    Google Scholar 

  16. G. J. Klir and T. A. Folger, Fuzzy Sets, Uncertainty and Information, PrenticeHall, 1988.

    MATH  Google Scholar 

  17. R. C. Luo and M. G. Kay, “Multisensor integration and fusion in intelligent systems,” IEEE Trans. on Systems, Man, and Cybernetics, vol. 19, no. 5, pp. 901–931, 1989.

    Article  Google Scholar 

  18. H. P. Moravec, “Sensor fusion in certainty grids for mobile robots,” AI Magazine, vol. 9, no. 2, pp. 61–74, 1988.

    Google Scholar 

  19. Nomadic Technologies, Nomad 200 User’s Guide, 1993.

    Google Scholar 

  20. G. Oriolo, G. Ulivi, and M. Vendittelli, “Fuzzy maps: A new tool for mobile robot perception and planning,” Journal of Robotic Systems, vol. 14, no. 3, pp. 179–197, 1997.

    Article  Google Scholar 

  21. G. Oriolo, G. Ulivi, and M. Vendittelli, “Real-time map building and navigation for autonomous robots in unknown environments,” IEEE Trans. on Systems, Man, and Cybernetics, vol 28, no. 3, Part B, pp. 316–333, 1998.

    Article  Google Scholar 

  22. Polaroid Corporation, Ultrasonic Ranging System, 1987.

    Google Scholar 

  23. J. R. Quinlan, “Consistency and plausible reasoning,” 8th Int. Joint Conf. on Artificial Intelligence, pp. 137–144, 1983.

    Google Scholar 

  24. A. Saffiotti, “Some notes on the integration of planning and reactivity in autonomous mobile robots,” in AAAI Spring Symp. on Foundations of Automatic Planning, pp. 122–126, 1993.

    Google Scholar 

  25. L. A. Zadeh, “Outline of a new approach to the analysis of complex systems and decision process,” IEEE Trans. on Systems, Man, and Cybernetics, vol. 3, no. 1, pp. 28–44, 1973.

    Article  MathSciNet  MATH  Google Scholar 

  26. H.-J. Zimmermann, Fuzzy Set Theory—and its Applications, Kluwer Academic Publishers, 1991.

    MATH  Google Scholar 

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Fabrizi, E., Oriolo, G., Ulivi, G. (2001). Accurate Map Building via Fusion of Laser and Ultrasonic Range Measures. In: Driankov, D., Saffiotti, A. (eds) Fuzzy Logic Techniques for Autonomous Vehicle Navigation. Studies in Fuzziness and Soft Computing, vol 61. Physica, Heidelberg. https://doi.org/10.1007/978-3-7908-1835-2_11

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  • DOI: https://doi.org/10.1007/978-3-7908-1835-2_11

  • Publisher Name: Physica, Heidelberg

  • Print ISBN: 978-3-7908-2479-7

  • Online ISBN: 978-3-7908-1835-2

  • eBook Packages: Springer Book Archive

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