Cooperative Localization Algorithm for Multiple Mobile Robot System in Indoor Environment Based on Variance Component Estimation
The Multiple Mobile Robot (MMR) cooperative system is becoming a focus of study in various fields due to its advantages, such as high efficiency and good fault tolerance. However, the uncertainty and nonlinearity problems severely limit the cooperative localization accuracy of the MMR system. Thus,...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2017-06-01
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| Series: | Symmetry |
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| Online Access: | http://www.mdpi.com/2073-8994/9/6/94 |
| _version_ | 1798042443215536128 |
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| author | Qian Sun Ming Diao Ya Zhang Yibing Li |
| author_facet | Qian Sun Ming Diao Ya Zhang Yibing Li |
| author_sort | Qian Sun |
| collection | DOAJ |
| description | The Multiple Mobile Robot (MMR) cooperative system is becoming a focus of study in various fields due to its advantages, such as high efficiency and good fault tolerance. However, the uncertainty and nonlinearity problems severely limit the cooperative localization accuracy of the MMR system. Thus, to solve the problems mentioned above, this manuscript presents a cooperative localization algorithm for MMR systems based on Cubature Kalman Filter (CKF) and adaptive Variance Component Estimation (VCE) methods. In this novel algorithm, a nonlinear filter named CKF is used to enhance the cooperative localization accuracy and reduce the computational load. On the other hand, the adaptive VCE method is introduced to eliminate the effects of unknown system noise. Furthermore, the performance of the proposed algorithm is compared with that of the cooperative localization algorithm based on normal CKF by utilizing the real experiment data. In addition, the results demonstrate that the proposed algorithm outperforms the CKF cooperative localization algorithm both in accuracy and consistency. |
| first_indexed | 2024-04-11T22:35:35Z |
| format | Article |
| id | doaj.art-20ce024f1609496d92cf9609aba30998 |
| institution | Directory Open Access Journal |
| issn | 2073-8994 |
| language | English |
| last_indexed | 2024-04-11T22:35:35Z |
| publishDate | 2017-06-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Symmetry |
| spelling | doaj.art-20ce024f1609496d92cf9609aba309982022-12-22T03:59:13ZengMDPI AGSymmetry2073-89942017-06-01969410.3390/sym9060094sym9060094Cooperative Localization Algorithm for Multiple Mobile Robot System in Indoor Environment Based on Variance Component EstimationQian Sun0Ming Diao1Ya Zhang2Yibing Li3College of Information and Communication Engineering, Harbin Engineering University, Harbin, 150001, ChinaCollege of Information and Communication Engineering, Harbin Engineering University, Harbin, 150001, ChinaSchool of Electrical Engineering and Automation, Harbin Institute of Technology, Harbin, 150001, ChinaCollege of Information and Communication Engineering, Harbin Engineering University, Harbin, 150001, ChinaThe Multiple Mobile Robot (MMR) cooperative system is becoming a focus of study in various fields due to its advantages, such as high efficiency and good fault tolerance. However, the uncertainty and nonlinearity problems severely limit the cooperative localization accuracy of the MMR system. Thus, to solve the problems mentioned above, this manuscript presents a cooperative localization algorithm for MMR systems based on Cubature Kalman Filter (CKF) and adaptive Variance Component Estimation (VCE) methods. In this novel algorithm, a nonlinear filter named CKF is used to enhance the cooperative localization accuracy and reduce the computational load. On the other hand, the adaptive VCE method is introduced to eliminate the effects of unknown system noise. Furthermore, the performance of the proposed algorithm is compared with that of the cooperative localization algorithm based on normal CKF by utilizing the real experiment data. In addition, the results demonstrate that the proposed algorithm outperforms the CKF cooperative localization algorithm both in accuracy and consistency.http://www.mdpi.com/2073-8994/9/6/94multi-mobile robot systemcooperative localizationvariance component estimationcubature Kalman filter |
| spellingShingle | Qian Sun Ming Diao Ya Zhang Yibing Li Cooperative Localization Algorithm for Multiple Mobile Robot System in Indoor Environment Based on Variance Component Estimation Symmetry multi-mobile robot system cooperative localization variance component estimation cubature Kalman filter |
| title | Cooperative Localization Algorithm for Multiple Mobile Robot System in Indoor Environment Based on Variance Component Estimation |
| title_full | Cooperative Localization Algorithm for Multiple Mobile Robot System in Indoor Environment Based on Variance Component Estimation |
| title_fullStr | Cooperative Localization Algorithm for Multiple Mobile Robot System in Indoor Environment Based on Variance Component Estimation |
| title_full_unstemmed | Cooperative Localization Algorithm for Multiple Mobile Robot System in Indoor Environment Based on Variance Component Estimation |
| title_short | Cooperative Localization Algorithm for Multiple Mobile Robot System in Indoor Environment Based on Variance Component Estimation |
| title_sort | cooperative localization algorithm for multiple mobile robot system in indoor environment based on variance component estimation |
| topic | multi-mobile robot system cooperative localization variance component estimation cubature Kalman filter |
| url | http://www.mdpi.com/2073-8994/9/6/94 |
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