Mobile robot localization with gyroscope and constrained Kalman filter

Autor:	Ki-Wan Choi, Hyun Myung, Hyoung-Ki Lee, Seok-Won Bang
Rok vydání:	2010
Předmět:	Engineering business.industry Monte Carlo localization Kalman filter Invariant extended Kalman filter Computer Science Applications Extended Kalman filter Odometry Control and Systems Engineering Control theory Fast Kalman filter Observability business Alpha beta filter
Zdroj:	International Journal of Control, Automation and Systems. 8:667-676
ISSN:	2005-4092 1598-6446
DOI:	10.1007/s12555-010-0321-6
Popis:	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.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::4a22683ee5dcc5b3a3af38c06f0c8849 https://doi.org/10.1007/s12555-010-0321-6 Zobrazit plný text záznamu Full text from SpringerLink