제어로봇시스템학회논문지 (Journal of Institute of Control, Robotics and Systems)

  • 제13권11호
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  • Pages.1092-1098
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  • 2007
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  • 1976-5622(pISSN)
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  • 2233-4335(eISSN)
제어로봇시스템학회 (Institute of Control, Robotics and Systems)
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실내용 이동로봇을 위한 위치추정 관측모델 설계 및 미끄러짐 오차 보상 기법 개발

Observation Likelihood Function Design and Slippage Error Compensation Scheme for Indoor Mobile Robots

  • 발행 : 2007.11.01
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초록

A mobile robot localization problem can be classified into following three sub-problems as an observation likelihood model, a motion model and a filtering technique. So far, we have developed the range sensor based, integrated localization scheme, which can be used in human-coexisting real environment such as a science museum and office buildings. From those experiences, we found out that there are several significant issues to be solved. In this paper, we focus on three key issues, and then illustrate our solutions to the presented problems. Three issues are listed as follows: (1) Investigation of design requirements of a desirable observation likelihood model, and performance analysis of our design (2) Performance evaluation of the localization result by computing the matching error (3) The semi-global localization scheme to deal with localization failure due to abrupt wheel slippage In this paper, we show the significance of each concept, developed solutions and the experimental results. Experiments were carried out in a typical modern building environment, and the results clearly show that the proposed solutions are useful to develop practical and integrated localization schemes.

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참고문헌

  1. D. H. Lee and W. J. Chung, 'Discrete status based localization for indoor service robots,' IEEE Transactions. on Industrial Electronics, vol. 53, no.5, October 2006, pp. 1737-1746 https://doi.org/10.1109/TIE.2006.881949
  2. D. H. Lee and W. J. Chung, 'Dependable localization strategy in dynamic real environments,' IEEF/RSJ International Conf. on Intelligent Robotics and System(IROS), 2005
  3. S. Thrun, D. Fox, W. Burgard, Probabilistic Robotics, The MIT Press, 2005, pp.153-169
  4. A. Doucet, Nando de Freitas, and Neil Gordon, Sequential Monte Carlo Methods in Practice, New York: Springer-Verlag, January 2001, pp.10-13
  5. F. Dellaert, D. Fox, W. Burgard, S. Thnm, 'Monte carlo localization for mobile robots,' IEEE Int. Conf. on robotics and Automation(ICRA), 1999
  6. J.-S. Gutmann, D. Fox, 'An experimental comparison of localization methods continued,' IEEE/RSJ International Conf. on Intelligent Robots and Systems(IROS), 2002
  7. S. Lensor and M. Veloso, 'Sensor resetting localization for poorly modeled mobile robots,' Proceedings of the IEEE International Conference on Robotics and Automation(ICRA), IEEE, San Francisco, CA, 2000
  8. V. Verma, G. Gordon, R. Simmons, S. Thrun, 'Particle filters for rover fault diagnosis,' Robotics & Automation Magazine, Special issue on Human Centered Robotics and Dependability, June 2004
  9. C. Plagemann, D. Fox, W. Burgard, 'Efficient failure detection on mobile robots using particle filters with gaussian process proposals,' IJCAI 2007, pp 2185-2190
  10. E. Olson, M. Walter, S. Teller and J. Leonard, 'Single-cluster spectral graph partitioning for robotics applications,' Proceedings of Robotics: Science and Systems, 2005