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

Institute of Control, Robotics and Systems (제어로봇시스템학회)
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Online Dynamic Modeling of Ubiquitous Sensor based Embedded Robot Systems using Kalman Filter Algorithm

칼만 필터 알고리즘을 이용한 유비쿼터스 센서 기반 임베디드 로봇시스템의 온라인 동적 모델링

  • 조현철 (동아대학교 전기공학과 포닥연구원) ;
  • 이진우 (동아대학교 전기공학과 포닥연구원) ;
  • 이영진 (한국폴리텍 항공대학 항공전기과) ;
  • 이권순 (동아대학교 전기공학과)
  • Published : 2008.08.01
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Abstract

This paper presents Kalman filter based system modeling algorithm for autonomous robot systems. State of the robot system is measured using embedded sensor systems and then carried to a host computer via ubiquitous sensor network (USN). We settle a linear state-space motion equation for unknown robot system dynamics and modify a popular Kalman filter algorithm in deriving suitable parameter estimation mechanism. To represent time-delay nature due to network media in system modeling, we construct an augmented state-space model which is mainly composed of original state and estimated parameter vectors. We conduct real-time experiment to test our proposed estimation algorithm where speed state of the constructed robot is used as system observation.

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References

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