A Planar Multi-Inertial Navigation Strategy for Autonomous Systems for Signal-Variable Environments
The challenge of precise dynamic positioning for mobile robots is addressed through the development of a multi-inertial navigation system (M-INSs). The inherent cumulative sensor errors prevalent in traditional single inertial navigation systems (INSs) under dynamic conditions are mitigated by a nov...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2024-02-01
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| Series: | Sensors |
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| Online Access: | https://www.mdpi.com/1424-8220/24/4/1064 |
| _version_ | 1797297101428752384 |
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| author | Wenbin Dong Cheng Lu Le Bao Wenqi Li Kyoosik Shin Changsoo Han |
| author_facet | Wenbin Dong Cheng Lu Le Bao Wenqi Li Kyoosik Shin Changsoo Han |
| author_sort | Wenbin Dong |
| collection | DOAJ |
| description | The challenge of precise dynamic positioning for mobile robots is addressed through the development of a multi-inertial navigation system (M-INSs). The inherent cumulative sensor errors prevalent in traditional single inertial navigation systems (INSs) under dynamic conditions are mitigated by a novel algorithm, integrating multiple INS units in a predefined planar configuration, utilizing fixed distances between the units as invariant constraints. An extended Kalman filter (EKF) is employed to significantly enhance the positioning accuracy. Dynamic experimental validation of the proposed 3INS EKF algorithm reveals a marked improvement over individual INS units, with the positioning errors reduced and stability increased, resulting in an average accuracy enhancement rate exceeding 60%. This advancement is particularly critical for mobile robot applications that demand high precision, such as autonomous driving and disaster search and rescue. The findings from this study not only demonstrate the potential of M-INSs to improve dynamic positioning accuracy but also to provide a new research direction for future advancements in robotic navigation systems. |
| first_indexed | 2024-03-07T22:15:23Z |
| format | Article |
| id | doaj.art-dbeccdade0474c18b48ca5680d85de39 |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-03-07T22:15:23Z |
| publishDate | 2024-02-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-dbeccdade0474c18b48ca5680d85de392024-02-23T15:33:28ZengMDPI AGSensors1424-82202024-02-01244106410.3390/s24041064A Planar Multi-Inertial Navigation Strategy for Autonomous Systems for Signal-Variable EnvironmentsWenbin Dong0Cheng Lu1Le Bao2Wenqi Li3Kyoosik Shin4Changsoo Han5Department of Mechatronics Engineering, Hanyang University, Ansan 15588, Republic of KoreaSchool of Mechanical Engineering, Anhui Science and Technology University, Chuzhou 233100, ChinaDepartment of Mechatronics Engineering, Hanyang University, Ansan 15588, Republic of KoreaDepartment of Mechatronics Engineering, Hanyang University, Ansan 15588, Republic of KoreaDepartment of Mechatronics Engineering, Hanyang University, Ansan 15588, Republic of KoreaDepartment of Mechatronics Engineering, Hanyang University, Ansan 15588, Republic of KoreaThe challenge of precise dynamic positioning for mobile robots is addressed through the development of a multi-inertial navigation system (M-INSs). The inherent cumulative sensor errors prevalent in traditional single inertial navigation systems (INSs) under dynamic conditions are mitigated by a novel algorithm, integrating multiple INS units in a predefined planar configuration, utilizing fixed distances between the units as invariant constraints. An extended Kalman filter (EKF) is employed to significantly enhance the positioning accuracy. Dynamic experimental validation of the proposed 3INS EKF algorithm reveals a marked improvement over individual INS units, with the positioning errors reduced and stability increased, resulting in an average accuracy enhancement rate exceeding 60%. This advancement is particularly critical for mobile robot applications that demand high precision, such as autonomous driving and disaster search and rescue. The findings from this study not only demonstrate the potential of M-INSs to improve dynamic positioning accuracy but also to provide a new research direction for future advancements in robotic navigation systems.https://www.mdpi.com/1424-8220/24/4/1064mobile robotEKFINSlocalizationautonomous navigation |
| spellingShingle | Wenbin Dong Cheng Lu Le Bao Wenqi Li Kyoosik Shin Changsoo Han A Planar Multi-Inertial Navigation Strategy for Autonomous Systems for Signal-Variable Environments Sensors mobile robot EKF INS localization autonomous navigation |
| title | A Planar Multi-Inertial Navigation Strategy for Autonomous Systems for Signal-Variable Environments |
| title_full | A Planar Multi-Inertial Navigation Strategy for Autonomous Systems for Signal-Variable Environments |
| title_fullStr | A Planar Multi-Inertial Navigation Strategy for Autonomous Systems for Signal-Variable Environments |
| title_full_unstemmed | A Planar Multi-Inertial Navigation Strategy for Autonomous Systems for Signal-Variable Environments |
| title_short | A Planar Multi-Inertial Navigation Strategy for Autonomous Systems for Signal-Variable Environments |
| title_sort | planar multi inertial navigation strategy for autonomous systems for signal variable environments |
| topic | mobile robot EKF INS localization autonomous navigation |
| url | https://www.mdpi.com/1424-8220/24/4/1064 |
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