Mobile Robot Localization Based on Vision and Multisensor
To deal with the low accuracy of positioning for mobile robots when only using visual sensors and an IMU, a method based on tight coupling and nonlinear optimization is proposed to obtain a high-precision visual positioning scheme by combining measured value of the preintegrated inertial measurement...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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Wiley
2020-01-01
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| Series: | Journal of Robotics |
| Online Access: | http://dx.doi.org/10.1155/2020/8701619 |
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| _version_ | 1832566302826299392 |
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| author | Lina Yao Fengzhe Li |
| author_facet | Lina Yao Fengzhe Li |
| author_sort | Lina Yao |
| collection | DOAJ |
| description | To deal with the low accuracy of positioning for mobile robots when only using visual sensors and an IMU, a method based on tight coupling and nonlinear optimization is proposed to obtain a high-precision visual positioning scheme by combining measured value of the preintegrated inertial measurement unit (IMU) and values of the odometer and characteristic observations. First, the preprocessing part of the observation data includes tracking of the image data and the odometer data, and preintegration of IMU data. Second, the initialization part of the above three sensors includes IMU preintegration, odometer preintegration, and gyroscope bias calculation. It also includes the alignment of speed, gravity, and scale. Finally, a local BA (bundle adjustment) joint optimization and global graph optimization are established, so as to obtain more accurate positioning results. |
| format | Article |
| id | doaj-art-cfa6d807a27a4cdd93212a7163531216 |
| institution | Kabale University |
| issn | 1687-9600 1687-9619 |
| language | English |
| publishDate | 2020-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Journal of Robotics |
| spelling | doaj-art-cfa6d807a27a4cdd93212a71635312162025-02-03T01:04:30ZengWileyJournal of Robotics1687-96001687-96192020-01-01202010.1155/2020/87016198701619Mobile Robot Localization Based on Vision and MultisensorLina Yao0Fengzhe Li1School of Electrial Engineering, Zhengzhou University, Zhengzhou 450001, ChinaSchool of Electrial Engineering, Zhengzhou University, Zhengzhou 450001, ChinaTo deal with the low accuracy of positioning for mobile robots when only using visual sensors and an IMU, a method based on tight coupling and nonlinear optimization is proposed to obtain a high-precision visual positioning scheme by combining measured value of the preintegrated inertial measurement unit (IMU) and values of the odometer and characteristic observations. First, the preprocessing part of the observation data includes tracking of the image data and the odometer data, and preintegration of IMU data. Second, the initialization part of the above three sensors includes IMU preintegration, odometer preintegration, and gyroscope bias calculation. It also includes the alignment of speed, gravity, and scale. Finally, a local BA (bundle adjustment) joint optimization and global graph optimization are established, so as to obtain more accurate positioning results.http://dx.doi.org/10.1155/2020/8701619 |
| spellingShingle | Lina Yao Fengzhe Li Mobile Robot Localization Based on Vision and Multisensor Journal of Robotics |
| title | Mobile Robot Localization Based on Vision and Multisensor |
| title_full | Mobile Robot Localization Based on Vision and Multisensor |
| title_fullStr | Mobile Robot Localization Based on Vision and Multisensor |
| title_full_unstemmed | Mobile Robot Localization Based on Vision and Multisensor |
| title_short | Mobile Robot Localization Based on Vision and Multisensor |
| title_sort | mobile robot localization based on vision and multisensor |
| url | http://dx.doi.org/10.1155/2020/8701619 |
| work_keys_str_mv | AT linayao mobilerobotlocalizationbasedonvisionandmultisensor AT fengzheli mobilerobotlocalizationbasedonvisionandmultisensor |