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

Institute of Control, Robotics and Systems (제어로봇시스템학회)
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An Efficient Outdoor Localization Method Using Multi-Sensor Fusion for Car-Like Robots

다중 센서 융합을 사용한 자동차형 로봇의 효율적인 실외 지역 위치 추정 방법

  • Bae, Sang-Hoon (Korea Advanced Institute of Science and Technology (KAIST)) ;
  • Kim, Byung-Kook (Korea Advanced Institute of Science and Technology (KAIST))
  • 배상훈 (한국과학기술원 전기 및 전자 공학과) ;
  • 김병국 (한국과학기술원 전기 및 전자 공학과)
  • Received : 2011.02.10
  • Accepted : 2011.08.10
  • Published : 2011.10.01
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Abstract

An efficient outdoor local localization method is suggested using multi-sensor fusion with MU-EKF (Multi-Update Extended Kalman Filter) for car-like mobile robots. In outdoor environments, where mobile robots are used for explorations or military services, accurate localization with multiple sensors is indispensable. In this paper, multi-sensor fusion outdoor local localization algorithm is proposed, which fuses sensor data from LRF (Laser Range Finder), Encoder, and GPS. First, encoder data is used for the prediction stage of MU-EKF. Then the LRF data obtained by scanning the environment is used to extract objects, and estimates the robot position and orientation by mapping with map objects, as the first update stage of MU-EKF. This estimation is finally fused with GPS as the second update stage of MU-EKF. This MU-EKF algorithm can also fuse more than three sensor data efficiently even with different sensor data sampling periods, and ensures high accuracy in localization. The validity of the proposed algorithm is revealed via experiments.

Keywords

References

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