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실내외 환경에서 휠 오도메트리와 비주얼 오도메트리 정보의 퍼지 융합에 기반한 궤도로봇의 위치추정

Localization of a Tracked Robot Based on Fuzzy Fusion of Wheel Odometry and Visual Odometry in Indoor and Outdoor Environments

  • 투고 : 2012.01.03
  • 심사 : 2012.03.20
  • 발행 : 2012.06.01

초록

궤도로봇은 궤도의 미끄럼 때문에 위치추정의 신뢰도가 낮다. 본 논문은 엔코더 기반의 휠오도메트리와 비주얼 오도메트리의 퍼지 융합을 이용하여 궤도로봇을 위한 새로운 위치추정 방법을 제안한다. 비주얼 오도메트리는 충분한 수의 영상 특징점이 없을 경우 정확성이 저하된다. 두 방법을 융합하기 위한 각각의 가중치는 주위 환경에 따른 퍼지 결정을 통해 제어된다. 실험 결과는 제안한 방법으로 강화된 궤도 로봇의 위치추정 성능을 보인다.

Tracked robots usually have poor localization performance because of slippage of their tracks. This study proposes a new localization method for tracked robots that uses fuzzy fusion of stereo-camera-based visual odometry and encoder-based wheel odometry. Visual odometry can be inaccurate when an insufficient number of visual features are available, while the encoder is prone to accumulating errors when large slips occur. To combine these two methods, the weight of each method was controlled by a fuzzy decision depending on the surrounding environment. The experimental results show that the proposed scheme improved the localization performance of a tracked robot.

키워드

참고문헌

  1. Micire, M. J., 2007, "Evolution and Field Performance of A Rescue Robot," Journal of Field Robotics, Vol. 25, No. 1-2, pp.17-30.
  2. Le, A. T., Rye, D.C. and Durrant-Whyte, H.F., 1997, "Estimation of Track-soil Interactions for Autonomous Tracked Vehicles," Proc. of IEEE Intl. Conf. on Robotics and Automation, Vol.2, pp. 1388-1393.
  3. Nister, D., Naroditsky, O. and Bergen, J., 2006, "Visual Odometry for Ground Vehicle Applications," Journal of Field Robotics, Vol. 23, No. 1, pp. 3-20. https://doi.org/10.1002/rob.20103
  4. Piasecki, M., 1994, "Mobile Robot Localization by Fuzzy Logic Fusion of Multisensory Data," Robotics and Autonomous Systems, Vol. 12, No. 3-4, pp. 155-162. https://doi.org/10.1016/0921-8890(94)90022-1
  5. Liu, Y. and Liu, G., 2009, "Modeling of Tracked Mobile Manipulators with Consideration of Track-terrain and Vehicle-manipulator Interactions," Robotics and Autonomous Systems, Vol. 57, No. 11, pp. 1065-1074. https://doi.org/10.1016/j.robot.2009.07.007
  6. Jung, S. J., Song, J. B. and Kang, S. C., 2008, "Stereo Vision-based Visual Odometry Using Robust Visual Feature in Dynamic Environment," The Journal of Korea Robotics Society, Vol.10, No.4, pp.263-269.
  7. Harris, C. and Stephens, M., 1988, "A Combined Corner and Edge Detector," Alvey vision Conference, United Kingdom, pp. 147-152.
  8. Medioni, G. and Yasumoto, Y., 1985, "Corner Detection and Curve Representation using Cubic Bsplines," Computer Vision, Graphics, and Image Processing, Vol.39, No 3, pp. 267-278.
  9. Bouguet, J. Y., 1999, Pyramidal Implementation of the Lucas Kanade Feature Tracker Description of the algorithm, Intel Corporation, Microprocessor Research Labs, 1999.
  10. Bradski, G. and Kaehler, A., 2008, Learning OpenCV: Computer Vision with the OpenCV Library, O'Reilly Media, California, pp. 551-606.
  11. Fischler, M. A. and Bolles, R. C., 1981, "Random Sample Consensus: A Paradigm for Model Fitting with Applications to Image Analysis and Automated Cartography," Comm. Of the ACM 24, pp. 381-385. https://doi.org/10.1145/358669.358692
  12. Horn, B. K. P., 1987, "Closed-form Solution of Absolute Orientation using Unit Quaternions," Journal of the Optical Society of America A, Vol. 4, No. 4, pp. 629-642.
  13. Niku, S. B., 2001, An Introduction to Robotics Analysis, Systems, Applications, Upper Saddle River, New Jersey, pp. 351-370.
  14. Nam, S.K., Kim, J.S. and Yoo, W.S., 1992, "Systematic Design Method of Fuzzy Logic Controllers by Using Fuzzy Control Cell," Trans. of the KSME, Vol. 16, No. 7, pp. 1234-1243.