Automatic Tracking Control of Autonomous-rail Rapid Tram Based on Camera Vision, Inertial Measurement Unit and GPS Data
Visual recognition is easily affected by broken ground identification, reflection of strong light and narrow field of view, while GPS (global positioning system) location is susceptible to occlusion and electromagnetic interference. Using any single positioning method will cause the problem of low t...
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| Format: | Article |
| Language: | zho |
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Editorial Office of Control and Information Technology
2022-04-01
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| Series: | Kongzhi Yu Xinxi Jishu |
| Subjects: | |
| Online Access: | http://ctet.csrzic.com/thesisDetails#10.13889/j.issn.2096-5427.2022.02.400 |
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| _version_ | 1849224945615241216 |
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| author | YUAN Xiwen ZHANG Xinrui HU Yunqing GAO Xinpeng HUANG Ruipeng |
| author_facet | YUAN Xiwen ZHANG Xinrui HU Yunqing GAO Xinpeng HUANG Ruipeng |
| author_sort | YUAN Xiwen |
| collection | DOAJ |
| description | Visual recognition is easily affected by broken ground identification, reflection of strong light and narrow field of view, while GPS (global positioning system) location is susceptible to occlusion and electromagnetic interference. Using any single positioning method will cause the problem of low tracking availability. Therefore, a fault-tolerant control method of combined vision and GPS combined inertial navigation is proposed in this paper. Firstly, lane line recognition is carried out based on image recognition method, geometric relationship parameters between vehicle and road are obtained, and PID controller is designed for steering control. Secondly, layered electronic map is constructed by RTK-GPS (real-time kinematic GPS), smooth reference track is output, and then Stanley controller is designed for steering control. Finally, vision and GPS tracking control are fused. Through real vehicle verification, the results show that the proposed fusion control strategy effectively improves the small radius turning passing rate of autonomous-rail rapid tram, the maximum passing speed can reach 25 km/h, which is increased by 66.7%, the number of one-way takeovers is reduced by 83.8%, the operation time is reduced by 24.4%, and the system availability is effectively improved. |
| format | Article |
| id | doaj-art-4d7886dfd9da42c6957439a5aa60fbea |
| institution | Kabale University |
| issn | 2096-5427 |
| language | zho |
| publishDate | 2022-04-01 |
| publisher | Editorial Office of Control and Information Technology |
| record_format | Article |
| series | Kongzhi Yu Xinxi Jishu |
| spelling | doaj-art-4d7886dfd9da42c6957439a5aa60fbea2025-08-25T06:48:02ZzhoEditorial Office of Control and Information TechnologyKongzhi Yu Xinxi Jishu2096-54272022-04-01626824170378Automatic Tracking Control of Autonomous-rail Rapid Tram Based on Camera Vision, Inertial Measurement Unit and GPS DataYUAN XiwenZHANG XinruiHU YunqingGAO XinpengHUANG RuipengVisual recognition is easily affected by broken ground identification, reflection of strong light and narrow field of view, while GPS (global positioning system) location is susceptible to occlusion and electromagnetic interference. Using any single positioning method will cause the problem of low tracking availability. Therefore, a fault-tolerant control method of combined vision and GPS combined inertial navigation is proposed in this paper. Firstly, lane line recognition is carried out based on image recognition method, geometric relationship parameters between vehicle and road are obtained, and PID controller is designed for steering control. Secondly, layered electronic map is constructed by RTK-GPS (real-time kinematic GPS), smooth reference track is output, and then Stanley controller is designed for steering control. Finally, vision and GPS tracking control are fused. Through real vehicle verification, the results show that the proposed fusion control strategy effectively improves the small radius turning passing rate of autonomous-rail rapid tram, the maximum passing speed can reach 25 km/h, which is increased by 66.7%, the number of one-way takeovers is reduced by 83.8%, the operation time is reduced by 24.4%, and the system availability is effectively improved.http://ctet.csrzic.com/thesisDetails#10.13889/j.issn.2096-5427.2022.02.400autonomous-rail rapid tramautomatic trackingvisionGPSIMU (inertial measurement unit)fusion control |
| spellingShingle | YUAN Xiwen ZHANG Xinrui HU Yunqing GAO Xinpeng HUANG Ruipeng Automatic Tracking Control of Autonomous-rail Rapid Tram Based on Camera Vision, Inertial Measurement Unit and GPS Data Kongzhi Yu Xinxi Jishu autonomous-rail rapid tram automatic tracking vision GPS IMU (inertial measurement unit) fusion control |
| title | Automatic Tracking Control of Autonomous-rail Rapid Tram Based on Camera Vision, Inertial Measurement Unit and GPS Data |
| title_full | Automatic Tracking Control of Autonomous-rail Rapid Tram Based on Camera Vision, Inertial Measurement Unit and GPS Data |
| title_fullStr | Automatic Tracking Control of Autonomous-rail Rapid Tram Based on Camera Vision, Inertial Measurement Unit and GPS Data |
| title_full_unstemmed | Automatic Tracking Control of Autonomous-rail Rapid Tram Based on Camera Vision, Inertial Measurement Unit and GPS Data |
| title_short | Automatic Tracking Control of Autonomous-rail Rapid Tram Based on Camera Vision, Inertial Measurement Unit and GPS Data |
| title_sort | automatic tracking control of autonomous rail rapid tram based on camera vision inertial measurement unit and gps data |
| topic | autonomous-rail rapid tram automatic tracking vision GPS IMU (inertial measurement unit) fusion control |
| url | http://ctet.csrzic.com/thesisDetails#10.13889/j.issn.2096-5427.2022.02.400 |
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