• Title/Summary/Keyword: IEKF SLAM

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Improvement of SLAM Using Invariant EKF for Autonomous Vehicles (Invariant EKF를 사용한 자율 이동체의 SLAM 개선)

  • Jeong, Da-Bin;Ko, Nak-Yong;Chung, Jun-Hyuk;Pyun, Jae-Young;Hwang, Suk-Seung;Kim, Tae-Woon
    • The Journal of the Korea institute of electronic communication sciences
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    • v.15 no.2
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    • pp.237-244
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    • 2020
  • This paper describes an implement of Simultaneous Localization and Mapping(SLAM) in two dimensional space. The method uses Invariant Extended Kalman Filter(IEKF), which transforms the state variables and measurement variables so that the transformed variables constitute a linear space when variables called the invariant quantities are kept constant. Therefore, the IEKF guarantees convergence provided in the invariant quantities are kept constant. The proposed IEKF approach uses Lie group matrix for the transformation. The method is tested through simulation, and the results show that the Kalman gain is constant as it is the case for the linear Kalman filter. The coherence between the estimated locations of the vehicle and the detected objects verifies the estimation performance of the method.