Localization of Wheeled Mobile Robot Based on Extended Kalman Filtering
A mobile robot localization method which combines relative positioning with absolute orientation is presented. The code salver and gyroscope are used for relative positioning, and the laser radar is used to detect absolute orientation. In this paper, we established environmental map, multi-sensor in...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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EDP Sciences
2015-01-01
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| Series: | MATEC Web of Conferences |
| Subjects: | |
| Online Access: | http://dx.doi.org/10.1051/matecconf/20152201061 |
| _version_ | 1819295008580173824 |
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| author | Li Guangxu Qin Dongxing Ju Hui |
| author_facet | Li Guangxu Qin Dongxing Ju Hui |
| author_sort | Li Guangxu |
| collection | DOAJ |
| description | A mobile robot localization method which combines relative positioning with absolute orientation is presented. The code salver and gyroscope are used for relative positioning, and the laser radar is used to detect absolute orientation. In this paper, we established environmental map, multi-sensor information fusion model, sensors and robot motion model. The Extended Kalman Filtering (EKF) is adopted as multi-sensor data fusion technology to realize the precise localization of wheeled mobile robot. |
| first_indexed | 2024-12-24T04:35:23Z |
| format | Article |
| id | doaj.art-04db0e1ac4a84540b71f58f18fc3e081 |
| institution | Directory Open Access Journal |
| issn | 2261-236X |
| language | English |
| last_indexed | 2024-12-24T04:35:23Z |
| publishDate | 2015-01-01 |
| publisher | EDP Sciences |
| record_format | Article |
| series | MATEC Web of Conferences |
| spelling | doaj.art-04db0e1ac4a84540b71f58f18fc3e0812022-12-21T17:15:12ZengEDP SciencesMATEC Web of Conferences2261-236X2015-01-01220106110.1051/matecconf/20152201061matecconf_iceta2015_01061Localization of Wheeled Mobile Robot Based on Extended Kalman FilteringLi GuangxuQin DongxingJu HuiA mobile robot localization method which combines relative positioning with absolute orientation is presented. The code salver and gyroscope are used for relative positioning, and the laser radar is used to detect absolute orientation. In this paper, we established environmental map, multi-sensor information fusion model, sensors and robot motion model. The Extended Kalman Filtering (EKF) is adopted as multi-sensor data fusion technology to realize the precise localization of wheeled mobile robot.http://dx.doi.org/10.1051/matecconf/20152201061Wheeled mobile robotPositioningMulti-sensorEKF |
| spellingShingle | Li Guangxu Qin Dongxing Ju Hui Localization of Wheeled Mobile Robot Based on Extended Kalman Filtering MATEC Web of Conferences Wheeled mobile robot Positioning Multi-sensor EKF |
| title | Localization of Wheeled Mobile Robot Based on Extended Kalman Filtering |
| title_full | Localization of Wheeled Mobile Robot Based on Extended Kalman Filtering |
| title_fullStr | Localization of Wheeled Mobile Robot Based on Extended Kalman Filtering |
| title_full_unstemmed | Localization of Wheeled Mobile Robot Based on Extended Kalman Filtering |
| title_short | Localization of Wheeled Mobile Robot Based on Extended Kalman Filtering |
| title_sort | localization of wheeled mobile robot based on extended kalman filtering |
| topic | Wheeled mobile robot Positioning Multi-sensor EKF |
| url | http://dx.doi.org/10.1051/matecconf/20152201061 |
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