Mobile robot localization with gyroscope and constrained Kalman filter

  • Hyun Myung
  • Hyoung-Ki Lee
  • Kiwan Choi
  • Seokwon Bang
Technical Notes and Correspondence

Abstract

The odometry information used in mobile robot localization can contain a significant number of errors when robot experiences slippage. To offset the presence of these errors, the use of a low-cost gyroscope in conjunction with Kalman filtering methods has been considered by many researchers. However, results from conventional Kalman filtering methods that use a gyroscope with odometry can unfeasible because the parameters are estimated regardless of the physical constraints of the robot. In this paper, a novel constrained Kalman filtering method is proposed that estimates the parameters under the physical constraints using a general constrained optimization technique. The state observability is improved by additional state variables and the accuracy is also improved through the use of a nonapproximated Kalman filter design. Experimental results show that the proposed method effectively offsets the localization error while yielding feasible parameter estimation.

Keywords

Constraints gyroscope Kalman filtering localization mobile robot observability 

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Copyright information

© Institute of Control, Robotics and Systems and The Korean Institute of Electrical Engineers and Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Hyun Myung
    • 1
  • Hyoung-Ki Lee
    • 2
  • Kiwan Choi
    • 2
  • Seokwon Bang
    • 3
  1. 1.Dept. of Civil & Environmental EngineeringKAISTDaejeonKorea
  2. 2.Samsung Advanced Institute of TechnologySamsung Electronics Co., Ltd.YonginKorea
  3. 3.Robotics InstituteCMUPittsburghUSA

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