Precision Data-Driven Collision Localization with a Dedicated Matrix Template for Electric Vehicle Automatic Charging
With the increasing maturity of autonomous driving technology and automated valet parking, public awareness of robot-based automatic charging for electric vehicles has gradually increased. The positioning of the charging port for electric vehicles is a prerequisite for achieving automatic charging....
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2024-02-01
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| Series: | Electronics |
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| Online Access: | https://www.mdpi.com/2079-9292/13/3/638 |
| _version_ | 1797318863501656064 |
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| author | Haoyu Lin Pengkun Quan Zhuo Liang Ya’nan Lou Dongbo Wei Shichun Di |
| author_facet | Haoyu Lin Pengkun Quan Zhuo Liang Ya’nan Lou Dongbo Wei Shichun Di |
| author_sort | Haoyu Lin |
| collection | DOAJ |
| description | With the increasing maturity of autonomous driving technology and automated valet parking, public awareness of robot-based automatic charging for electric vehicles has gradually increased. The positioning of the charging port for electric vehicles is a prerequisite for achieving automatic charging. The common approach is to use visual methods for charging port positioning. However, due to factors such as external light conditions, humidity, and temperature, the visual system may experience insufficient positioning accuracy, leading to difficulties in executing the charging plug-in task. To address this issue, this paper proposes a data-driven collision localization method based on the vibration signal generated by the contact. During the data collection process, we first introduce a collision point matrix template suitable for automatic charging plug-in. This template covers the entire charging port and supports the acquisition of dense collision vibration data. Using this collision point matrix template, the collision localization problem can be transformed into a classification problem of collision vibration information corresponding to different collision points. Then, the collision vibration data obtained, based on this template, are used to train the collision localization model, which mainly consists of an echo state network (ESN) and support vector machine (SVM). The AUBO-i5 6-DOF articulated robot is employed to test the proposed collision localization method under different joint configurations. The simulated experimental results demonstrate the effectiveness of the proposed collision localization method, showcasing a promising localization accuracy and root mean square error (RMSE). |
| first_indexed | 2024-03-08T03:58:34Z |
| format | Article |
| id | doaj.art-53bebe0e54ed4c72b49be6f56a8cd1ec |
| institution | Directory Open Access Journal |
| issn | 2079-9292 |
| language | English |
| last_indexed | 2024-03-08T03:58:34Z |
| publishDate | 2024-02-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Electronics |
| spelling | doaj.art-53bebe0e54ed4c72b49be6f56a8cd1ec2024-02-09T15:10:55ZengMDPI AGElectronics2079-92922024-02-0113363810.3390/electronics13030638Precision Data-Driven Collision Localization with a Dedicated Matrix Template for Electric Vehicle Automatic ChargingHaoyu Lin0Pengkun Quan1Zhuo Liang2Ya’nan Lou3Dongbo Wei4Shichun Di5School of Mechatronics Engineering, Harbin Institute of Technology, Harbin 150001, ChinaSchool of Mechatronics Engineering, Harbin Institute of Technology, Harbin 150001, ChinaSchool of Mechatronics Engineering, Harbin Institute of Technology, Harbin 150001, ChinaBeijing Institute of Astronautical Systems Engineering, Beijing 100076, ChinaSchool of Mechatronics Engineering, Harbin Institute of Technology, Harbin 150001, ChinaSchool of Mechatronics Engineering, Harbin Institute of Technology, Harbin 150001, ChinaWith the increasing maturity of autonomous driving technology and automated valet parking, public awareness of robot-based automatic charging for electric vehicles has gradually increased. The positioning of the charging port for electric vehicles is a prerequisite for achieving automatic charging. The common approach is to use visual methods for charging port positioning. However, due to factors such as external light conditions, humidity, and temperature, the visual system may experience insufficient positioning accuracy, leading to difficulties in executing the charging plug-in task. To address this issue, this paper proposes a data-driven collision localization method based on the vibration signal generated by the contact. During the data collection process, we first introduce a collision point matrix template suitable for automatic charging plug-in. This template covers the entire charging port and supports the acquisition of dense collision vibration data. Using this collision point matrix template, the collision localization problem can be transformed into a classification problem of collision vibration information corresponding to different collision points. Then, the collision vibration data obtained, based on this template, are used to train the collision localization model, which mainly consists of an echo state network (ESN) and support vector machine (SVM). The AUBO-i5 6-DOF articulated robot is employed to test the proposed collision localization method under different joint configurations. The simulated experimental results demonstrate the effectiveness of the proposed collision localization method, showcasing a promising localization accuracy and root mean square error (RMSE).https://www.mdpi.com/2079-9292/13/3/638robot-based automatic chargingcollision localizationcollision point matrix templateautomatic feature extraction methodecho state networksupport vector machine |
| spellingShingle | Haoyu Lin Pengkun Quan Zhuo Liang Ya’nan Lou Dongbo Wei Shichun Di Precision Data-Driven Collision Localization with a Dedicated Matrix Template for Electric Vehicle Automatic Charging Electronics robot-based automatic charging collision localization collision point matrix template automatic feature extraction method echo state network support vector machine |
| title | Precision Data-Driven Collision Localization with a Dedicated Matrix Template for Electric Vehicle Automatic Charging |
| title_full | Precision Data-Driven Collision Localization with a Dedicated Matrix Template for Electric Vehicle Automatic Charging |
| title_fullStr | Precision Data-Driven Collision Localization with a Dedicated Matrix Template for Electric Vehicle Automatic Charging |
| title_full_unstemmed | Precision Data-Driven Collision Localization with a Dedicated Matrix Template for Electric Vehicle Automatic Charging |
| title_short | Precision Data-Driven Collision Localization with a Dedicated Matrix Template for Electric Vehicle Automatic Charging |
| title_sort | precision data driven collision localization with a dedicated matrix template for electric vehicle automatic charging |
| topic | robot-based automatic charging collision localization collision point matrix template automatic feature extraction method echo state network support vector machine |
| url | https://www.mdpi.com/2079-9292/13/3/638 |
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