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EKF based Mobile Robot Indoor Localization using Pattern Matching

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로봇학회논문지 (The Journal of Korea Robotics Society)
한국로봇학회 (Korea Robotics Society)
초록

This paper proposes how to improve the performance of CSS-based indoor localization system. CSS based localization utilizes signal flight time between anchors and tag to estimate distance. From the distances, the 3-dimensional position is calculated through trilateration. However the error in distance caused from multi-path effect transfers to the position error especially in indoor environment. This paper handles a problem of reducing error in raw distance information. And, we propose the new localization method by pattern matching instead of the conventional localization method based on trilateration that is affected heavily on multi-path error. The pattern matching method estimates the position by using the fact that the measured data of near positions possesses a high similarity. In order to gain better performance of localization, we use EKF(Extended Kalman Filter) to fuse the result of CSS based localization and robot model.

저자
  • 김석용(충남대학교 메카트로닉스 공학과) | Seokyoung Kim
  • 이지홍(충남대학교 메카트로닉스 공학과 교수) | Jihong Lee 교신저자