NDLI: Mobile robot localization with gyroscope and constrained Kalman filter

Content Provider	Springer Nature Link
Author	Myung, Hyun Lee, Hyoung Ki Choi, Kiwan Bang, Seokwon
Copyright Year	2010
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.
Starting Page	667
Ending Page	676
Page Count	10
File Format	PDF
ISSN	15986446
Journal	International Journal of Control, Automation and Systems
Volume Number	8
Issue Number	3
e-ISSN	20054092
Language	English
Publisher	Institute of Control, Robotics and Systems and The Korean Institute of Electrical Engineers
Publisher Date	2010-06-05
Publisher Place	Heidelberg
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Constraints gyroscope Kalman filtering localization mobile robot observability Control Robotics Mechatronics
Content Type	Text
Resource Type	Article
Subject	Control and Systems Engineering Computer Science Applications

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