Global dynamic path‐planning algorithm in gravity‐aided inertial navigation system
Abstract Signals from gyros and accelerometers in an inertial navigation system (INS) can be processed to obtain navigation information while its errors accumulate with time. A path with long‐term characteristics is more likely to encounter unpredictable dynamic conditions. To deal with such problem...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Hindawi-IET
2021-10-01
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| Series: | IET Signal Processing |
| Subjects: | |
| Online Access: | https://doi.org/10.1049/sil2.12056 |
| _version_ | 1797421775042117632 |
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| author | Shengwu Zhao Lei Shi Wenzhe Zhang Zhihong Deng |
| author_facet | Shengwu Zhao Lei Shi Wenzhe Zhang Zhihong Deng |
| author_sort | Shengwu Zhao |
| collection | DOAJ |
| description | Abstract Signals from gyros and accelerometers in an inertial navigation system (INS) can be processed to obtain navigation information while its errors accumulate with time. A path with long‐term characteristics is more likely to encounter unpredictable dynamic conditions. To deal with such problems, this work improves the global static path‐planning algorithm based on the A* algorithm, and the local dynamic path‐planning algorithm based on dynamic window approach (DWA). In the global planning algorithm, the gravity index and the heading index are incorporated into the cost function of the A* algorithm to consider the mismatches and the deflection of the path. Furthermore, the search method of the A* algorithm is also improved. In the local planning algorithm, the motion model of the DWA algorithm is improved to a high‐precision model and expressed in a geographic coordinate system. Finally, the improved global static planning and local dynamic planning are combined as the global dynamic path‐planning algorithm of an underwater vehicle. The simulation results show that the global dynamic path‐planning algorithm proposed can realise obstacle‐free navigation of the underwater vehicle. |
| first_indexed | 2024-03-09T07:22:15Z |
| format | Article |
| id | doaj.art-c9705846e8cc4af892abc1c2045c7264 |
| institution | Directory Open Access Journal |
| issn | 1751-9675 1751-9683 |
| language | English |
| last_indexed | 2024-03-09T07:22:15Z |
| publishDate | 2021-10-01 |
| publisher | Hindawi-IET |
| record_format | Article |
| series | IET Signal Processing |
| spelling | doaj.art-c9705846e8cc4af892abc1c2045c72642023-12-03T07:19:47ZengHindawi-IETIET Signal Processing1751-96751751-96832021-10-0115851052010.1049/sil2.12056Global dynamic path‐planning algorithm in gravity‐aided inertial navigation systemShengwu Zhao0Lei Shi1Wenzhe Zhang2Zhihong Deng3School of Automation Beijing Institute of Technology Beijing ChinaSchool of Automation Beijing Institute of Technology Beijing ChinaSchool of Automation Beijing Institute of Technology Beijing ChinaSchool of Automation Beijing Institute of Technology Beijing ChinaAbstract Signals from gyros and accelerometers in an inertial navigation system (INS) can be processed to obtain navigation information while its errors accumulate with time. A path with long‐term characteristics is more likely to encounter unpredictable dynamic conditions. To deal with such problems, this work improves the global static path‐planning algorithm based on the A* algorithm, and the local dynamic path‐planning algorithm based on dynamic window approach (DWA). In the global planning algorithm, the gravity index and the heading index are incorporated into the cost function of the A* algorithm to consider the mismatches and the deflection of the path. Furthermore, the search method of the A* algorithm is also improved. In the local planning algorithm, the motion model of the DWA algorithm is improved to a high‐precision model and expressed in a geographic coordinate system. Finally, the improved global static planning and local dynamic planning are combined as the global dynamic path‐planning algorithm of an underwater vehicle. The simulation results show that the global dynamic path‐planning algorithm proposed can realise obstacle‐free navigation of the underwater vehicle.https://doi.org/10.1049/sil2.12056accelerometersautonomous underwater vehiclescollision avoidanceinertial navigationmobile robotsmotion control |
| spellingShingle | Shengwu Zhao Lei Shi Wenzhe Zhang Zhihong Deng Global dynamic path‐planning algorithm in gravity‐aided inertial navigation system IET Signal Processing accelerometers autonomous underwater vehicles collision avoidance inertial navigation mobile robots motion control |
| title | Global dynamic path‐planning algorithm in gravity‐aided inertial navigation system |
| title_full | Global dynamic path‐planning algorithm in gravity‐aided inertial navigation system |
| title_fullStr | Global dynamic path‐planning algorithm in gravity‐aided inertial navigation system |
| title_full_unstemmed | Global dynamic path‐planning algorithm in gravity‐aided inertial navigation system |
| title_short | Global dynamic path‐planning algorithm in gravity‐aided inertial navigation system |
| title_sort | global dynamic path planning algorithm in gravity aided inertial navigation system |
| topic | accelerometers autonomous underwater vehicles collision avoidance inertial navigation mobile robots motion control |
| url | https://doi.org/10.1049/sil2.12056 |
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