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Localization for Mobile Robot by Selective Anchors in Indoor GPS and EKF
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 Title & Authors
Localization for Mobile Robot by Selective Anchors in Indoor GPS and EKF
Kang, Han-Goo; Yun, Jae-Oh; Lee, Ji-Hong;
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 Abstract
This paper proposes a technique of indoor localization for mobile robot by so called indoor GPS and EKF. Basically the concept of indoor GPS is similar outdoor GPS, and the indoor GPS gets distances between Anchors and Tag by a ranging method of CSS and then estimates the coordinate by distances and known Anchor positions. After we performed performance test of indoor GPS system in ideal and multipath environment, we configured that the indoor GPS has internal error factors and external error factors. This paper handled a multipath problem belonging to external error factors. At first various direct physical method are introduced to fix the multipath problems, and as expected we got errors corrected considerably. And then the method of selective anchors for indoor GPS is applied. With these two level improvement of indoor GPS performance, EKF(Extended Kalman Filter) is applied to mobile robot in indoor environment. The usefulness of the proposed methods are shown by a series of experiments in a environment giving contaminated data by multipath.
 Keywords
LBS;Localization;Indoor GPS;Multipath;EKF;
 Language
Korean
 Cited by
1.
위상학적 공간 인식을 위한 효과적인 초음파 격자 지도 매칭 기법 개발,최진우;최민용;정완균;

로봇학회논문지, 2011. vol.6. 3, pp.247-254 crossref(new window)
 References
1.
Jeffrey Hightower and Gaetano Borriello, "Location Systems for Ubiquitous Computing", University of Washington, August 2001.

2.
E. D. Kaplan, Understanding GPS: Principles and Applications, Boston, MA: Artech House, 1996

3.
Kim Jung Soo, "A Study on the Location Awareness System using TOA(Time of arrival) algorithm", M.S. Thesis, Kwangwoon University, 2007.

4.
Christof Rohrig, Marcel Muller, "Indoor Location Tracking in Non-line-of Sight Environments Using a IEEE 802.15.4a Wireless Network", Proceedings of the 2009 IEEE/RSJ international Conference on Intelligent Robots and Systems, pp.552-557, 2009.

5.
Kim, Eui Seok, "The Ranging Performance fo Chirp Spread Spectrum in Indoor Multipath Environment", M.S. Thesis, Seoul National University, 2008.

6.
진조철, "위치 인식 시스템 개발 동향 소개", 정보와 통신 : 한국통신학회지 Vol.25, No.4, pp.5-10, 2008.

7.
조현우, 이영훈, 김상우 "Chirp Spread Spectrum 거리 측정을 이용한 이동 로봇의 위치 추정" 제어.로봇.시스템학회 논문지, 제15권, 제10호, pp.994-1001, 2009.

8.
김정민, 김연태, 김성신 "확장 칼만 필터를 이용한 로봇의 실내위치측정" 한국지능시스템학회 논문지, Vol.18, No.5, pp.706-711, 2008.

9.
진태석, 이장명 "이동물제의 기하학적 위치정보 를 이용한 자율이동로봇의 위치추정" 퍼지 및 지능시스템학회 논문지, Vol.14, No.4, pp.438-444, 2004.

10.
IEEE 802.15.4a, "Part 15.4: Wireless Medium Assess Control (MAC) and Physical Layer (PHY) Specifications for Low-Rate Wireless Personal Area Networks (WPANs)", 31 Aug. 2007.

11.
E. Doukhnitch, M. Salamah, E. Ozen, "An efficient approach for trilateration in 3D positioning", Computer Communications 31, pp.4124-4129, Elsevier, 2008 crossref(new window)

12.
Hangoo Kang, Geon woong Seo, Jihong Lee, "Error Compensation for CSS-based Localization System", Proc. of Int. Con. on Intelligent Automation and Robotics, Vol.2, pp.696-701, 2009

13.
Greg Welch, Gary Bishop, "An Introduction to the Kalman Filter", University of North Carolina Chapel Hill, July 2006

14.
Howie Choset, Kevin Lynch, Seth Hutchinson, George Kantor, Wolfram Burgard, Lydia Kavraki, Sebastian Thrun, Principles of Robot Motion Theory, Algorithms, and Implementation, The MIT Press, Cambridge, Massachusetts, London, England, 2005