Technical Notes and Correspondence

International Journal of Control, Automation and Systems

, Volume 8, Issue 3, pp 667-676

First online:

Mobile robot localization with gyroscope and constrained Kalman filter

  • Hyun MyungAffiliated withDept. of Civil & Environmental Engineering, KAIST Email author 
  • , Hyoung-Ki LeeAffiliated withSamsung Advanced Institute of Technology, Samsung Electronics Co., Ltd.
  • , Kiwan ChoiAffiliated withSamsung Advanced Institute of Technology, Samsung Electronics Co., Ltd.
  • , Seokwon BangAffiliated withRobotics Institute, CMU

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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.


Constraints gyroscope Kalman filtering localization mobile robot observability