Mobile robot localization with gyroscope and constrained Kalman filter

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

DOI: 10.1007/s12555-010-0321-6

Cite this article as:
Myung, H., Lee, HK., Choi, K. et al. Int. J. Control Autom. Syst. (2010) 8: 667. doi:10.1007/s12555-010-0321-6
  • 377 Downloads

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 

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

Personalised recommendations