Algorithm for Determining the Position of a Ship Hull-Cleaning Robot
The paper explores the development and evaluation of algorithms for the positioning of ship hull cleaning robots, focusing on machine learning and sensor fusion techniques. The research employs Gradient Boosting, Kalman filters, and deep learning to enhance the accuracy of robot positioning. Gradien...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2025-05-01
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| Series: | Applied Sciences |
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| Online Access: | https://www.mdpi.com/2076-3417/15/10/5705 |
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| author | Konrad Chwełatiuk Anna Kubina Marcin Michalak Marek Sikora Piotr Ściegienka Łukasz Wróbel |
| author_facet | Konrad Chwełatiuk Anna Kubina Marcin Michalak Marek Sikora Piotr Ściegienka Łukasz Wróbel |
| author_sort | Konrad Chwełatiuk |
| collection | DOAJ |
| description | The paper explores the development and evaluation of algorithms for the positioning of ship hull cleaning robots, focusing on machine learning and sensor fusion techniques. The research employs Gradient Boosting, Kalman filters, and deep learning to enhance the accuracy of robot positioning. Gradient Boosting is used to predict displacement vectors and rotation angles, while the Kalman filter is applied to refine position estimates by integrating odometry and GPS data. Deep learning models are utilized to predict robot trajectories based on sensor inputs. Experiments conducted on the Rosario dataset and simulated environments demonstrate the effectiveness of these methods. |
| format | Article |
| id | doaj-art-ba1a609c8b5f4d51ab76f42948526bcb |
| institution | OA Journals |
| issn | 2076-3417 |
| language | English |
| publishDate | 2025-05-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj-art-ba1a609c8b5f4d51ab76f42948526bcb2025-08-20T02:33:39ZengMDPI AGApplied Sciences2076-34172025-05-011510570510.3390/app15105705Algorithm for Determining the Position of a Ship Hull-Cleaning RobotKonrad Chwełatiuk0Anna Kubina1Marcin Michalak2Marek Sikora3Piotr Ściegienka4Łukasz Wróbel5Łukasiewicz Research Network–Institute of Innovative Technologies EMAG, ul. Leopolda 31, 40-189 Katowice, PolandŁukasiewicz Research Network–Institute of Innovative Technologies EMAG, ul. Leopolda 31, 40-189 Katowice, PolandŁukasiewicz Research Network–Institute of Innovative Technologies EMAG, ul. Leopolda 31, 40-189 Katowice, PolandŁukasiewicz Research Network–Institute of Innovative Technologies EMAG, ul. Leopolda 31, 40-189 Katowice, PolandJoint Doctoral School, Silesian University of Technology, ul. Akademicka 2A, 44-100 Gliwice, PolandŁukasiewicz Research Network–Institute of Innovative Technologies EMAG, ul. Leopolda 31, 40-189 Katowice, PolandThe paper explores the development and evaluation of algorithms for the positioning of ship hull cleaning robots, focusing on machine learning and sensor fusion techniques. The research employs Gradient Boosting, Kalman filters, and deep learning to enhance the accuracy of robot positioning. Gradient Boosting is used to predict displacement vectors and rotation angles, while the Kalman filter is applied to refine position estimates by integrating odometry and GPS data. Deep learning models are utilized to predict robot trajectories based on sensor inputs. Experiments conducted on the Rosario dataset and simulated environments demonstrate the effectiveness of these methods.https://www.mdpi.com/2076-3417/15/10/5705ship hull cleaningpositioningKalman filterodometry dataIMU data |
| spellingShingle | Konrad Chwełatiuk Anna Kubina Marcin Michalak Marek Sikora Piotr Ściegienka Łukasz Wróbel Algorithm for Determining the Position of a Ship Hull-Cleaning Robot Applied Sciences ship hull cleaning positioning Kalman filter odometry data IMU data |
| title | Algorithm for Determining the Position of a Ship Hull-Cleaning Robot |
| title_full | Algorithm for Determining the Position of a Ship Hull-Cleaning Robot |
| title_fullStr | Algorithm for Determining the Position of a Ship Hull-Cleaning Robot |
| title_full_unstemmed | Algorithm for Determining the Position of a Ship Hull-Cleaning Robot |
| title_short | Algorithm for Determining the Position of a Ship Hull-Cleaning Robot |
| title_sort | algorithm for determining the position of a ship hull cleaning robot |
| topic | ship hull cleaning positioning Kalman filter odometry data IMU data |
| url | https://www.mdpi.com/2076-3417/15/10/5705 |
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