International Journal of Control, Automation and Systems

, Volume 8, Issue 3, pp 667–676

Mobile robot localization with gyroscope and constrained Kalman filter


    • Dept. of Civil & Environmental EngineeringKAIST
  • Hyoung-Ki Lee
    • Samsung Advanced Institute of TechnologySamsung Electronics Co., Ltd.
  • Kiwan Choi
    • Samsung Advanced Institute of TechnologySamsung Electronics Co., Ltd.
  • Seokwon Bang
    • Robotics InstituteCMU
Technical Notes and Correspondence

DOI: 10.1007/s12555-010-0321-6

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


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.


ConstraintsgyroscopeKalman filteringlocalizationmobile robotobservability

Copyright information

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