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Outdoor Localization of a Mobile Robot Using Weighted GPS Data and Map Information

가중화된 GPS 정보와 지도정보를 활용한 실외 이동로봇의 위치추정

  • Received : 2011.03.17
  • Accepted : 2011.08.26
  • Published : 2011.08.31

Abstract

Global positioning system (GPS) is widely used to measure the position of a vehicle. However, the accuracy of the GPS can be severely affected by surrounding environmental conditions. To deal with this problem, the GPS and odometry data can be combined using an extended Kalman filter. For stable navigation of an outdoor mobile robot using the GPS, this paper proposes two methods to evaluate the reliability of the GPS data. The first method is to calculate the standard deviation of the GPS data and reflect it to deal with the uncertainty of the GPS data. The second method is to match the GPS data to the traversability map which can be obtained by classifying outdoor terrain data. By matching of the GPS data with the traversability map, we can determine whether to use the GPS data or not. The experimental results show that the proposed methods can enhance the performance of the GPS-based outdoor localization.

Keywords

References

  1. Da, DIIa, Ren, "Investigation of a low‐cost and high‐accuracy GPS/IMU system", Proc. of the ION National Technical Meeting, Santa Monica, pp.955-963, 1997.
  2. S. Sukkarieh, E. M. Nebot and H. F. Durrant‐ Whyte, "A high integrity IMU/GPS navigation loop for autonomous land vehicle applications", IEEE Trans. Robotics and Automation, Vvol.15, No.3, pp.572-578, 1999. https://doi.org/10.1109/70.768189
  3. Rainer Kümmerlem, Rudolph Triebel, Patrick Pfaff, Wolfram Burgard, "Monte Carlo localization in outdoor terrains using multilevel surface maps", Journal of Field Robotics, Vol.25, Issue6‐ 7, pp.346-359, 2008. https://doi.org/10.1002/rob.20245
  4. Keith Yu Kit Leung, Christopher M. Clark, Jan P. Huissoon, "Localization in urban environments by matching ground level video images with an aerial image," IEEE International Conference on Robotics and Automation, Pasadena, pp.551-556, 2008.
  5. K. Ohno, T. Tsubouchi and B. Shigematsu, "Differential GPS and odometry‐based outdoor navigation of a mobile robot," Advanced Robotics, Vol.18, No.6, pp.611-635, 2004. https://doi.org/10.1163/1568553041257431
  6. 노치원, 김승훈, 김문준, 강성철, 홍석교, "DGPS와 연석추출을 이용한 순찰용 로봇의 개발," 제어자동화시스템공학 논문지, 13권, 2호, pp.140-146, 2007.
  7. Luka Teslic, Igor Skrjanc and Gregor Klancar, "Using a LRF sensor in the Kalman‐filteringbased localization of a mobile robot," ISA Trans., Vol.49, No.1, pp.145-153, 2010. https://doi.org/10.1016/j.isatra.2009.09.009
  8. Luka Teslić, Igor Škrjanc and Gregor Klančar, "Using a LRF sensor in the Kalman‐filteringbased localization of a mobile robot," ISA Trans., Vol.49, No.1, pp.145-153, 2010. https://doi.org/10.1016/j.isatra.2009.09.009

Cited by

  1. Unscented Kalman Filter based Outdoor Localization of a Mobile Robot vol.36, pp.2, 2011, https://doi.org/10.7736/kspe.2019.36.2.183