Vision-Based Object Recognition and Precise Localization for Space Body Control
The space motion control is an important issue on space robot, rendezvous and docking, small satellite formation, and some on-orbit services. The motion control needs robust object detection and high-precision object localization. Among many sensing systems such as laser radar, inertia sensors, and...
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| Format: | Article |
| Language: | English |
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Wiley
2019-01-01
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| Series: | International Journal of Aerospace Engineering |
| Online Access: | http://dx.doi.org/10.1155/2019/7050915 |
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| author | Zeyu Shangguan Lingyu Wang Jianquan Zhang Wenbo Dong |
| author_facet | Zeyu Shangguan Lingyu Wang Jianquan Zhang Wenbo Dong |
| author_sort | Zeyu Shangguan |
| collection | DOAJ |
| description | The space motion control is an important issue on space robot, rendezvous and docking, small satellite formation, and some on-orbit services. The motion control needs robust object detection and high-precision object localization. Among many sensing systems such as laser radar, inertia sensors, and GPS navigation, vision-based navigation is more adaptive to noncontact applications in the close distance and in high-dynamic environment. In this work, a vision-based system serving for a free-floating robot inside the spacecraft is introduced, and the method to measure space body 6-DOF position-attitude is presented. At first, the deep-learning method is applied for robust object detection in the complex background, and after the object is navigated at the close distance, the reference marker is used for more precise matching and edge detection. After the accurate coordinates are gotten in the image sequence, the object space position and attitude are calculated by the geometry method and used for fine control. The experimental results show that the recognition method based on deep-learning at a distance and marker matching in close range effectively eliminates the false target recognition and improves the precision of positioning at the same time. The testing result shows the recognition accuracy rate is 99.8% and the localization precision is far less than 1% in 1.5 meters. The high-speed camera and embedded electronic platform driven by GPU are applied for accelerating the image processing speed so that the system works at best by 70 frames per second. The contribution of this work is to introduce the deep-learning method for precision motion control and in the meanwhile ensure both the robustness and real time of the system. It aims at making such vision-based system more practicable in the real-space applications. |
| format | Article |
| id | doaj-art-3c47405814b14a6488b048ea29f157c2 |
| institution | Kabale University |
| issn | 1687-5966 1687-5974 |
| language | English |
| publishDate | 2019-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | International Journal of Aerospace Engineering |
| spelling | doaj-art-3c47405814b14a6488b048ea29f157c22025-02-03T01:22:22ZengWileyInternational Journal of Aerospace Engineering1687-59661687-59742019-01-01201910.1155/2019/70509157050915Vision-Based Object Recognition and Precise Localization for Space Body ControlZeyu Shangguan0Lingyu Wang1Jianquan Zhang2Wenbo Dong3Key Laboratory of Space Utilization, Chinese Academy of Sciences, Beijing 100094, ChinaKey Laboratory of Space Utilization, Chinese Academy of Sciences, Beijing 100094, ChinaKey Laboratory of Space Utilization, Chinese Academy of Sciences, Beijing 100094, ChinaKey Laboratory of Space Utilization, Chinese Academy of Sciences, Beijing 100094, ChinaThe space motion control is an important issue on space robot, rendezvous and docking, small satellite formation, and some on-orbit services. The motion control needs robust object detection and high-precision object localization. Among many sensing systems such as laser radar, inertia sensors, and GPS navigation, vision-based navigation is more adaptive to noncontact applications in the close distance and in high-dynamic environment. In this work, a vision-based system serving for a free-floating robot inside the spacecraft is introduced, and the method to measure space body 6-DOF position-attitude is presented. At first, the deep-learning method is applied for robust object detection in the complex background, and after the object is navigated at the close distance, the reference marker is used for more precise matching and edge detection. After the accurate coordinates are gotten in the image sequence, the object space position and attitude are calculated by the geometry method and used for fine control. The experimental results show that the recognition method based on deep-learning at a distance and marker matching in close range effectively eliminates the false target recognition and improves the precision of positioning at the same time. The testing result shows the recognition accuracy rate is 99.8% and the localization precision is far less than 1% in 1.5 meters. The high-speed camera and embedded electronic platform driven by GPU are applied for accelerating the image processing speed so that the system works at best by 70 frames per second. The contribution of this work is to introduce the deep-learning method for precision motion control and in the meanwhile ensure both the robustness and real time of the system. It aims at making such vision-based system more practicable in the real-space applications.http://dx.doi.org/10.1155/2019/7050915 |
| spellingShingle | Zeyu Shangguan Lingyu Wang Jianquan Zhang Wenbo Dong Vision-Based Object Recognition and Precise Localization for Space Body Control International Journal of Aerospace Engineering |
| title | Vision-Based Object Recognition and Precise Localization for Space Body Control |
| title_full | Vision-Based Object Recognition and Precise Localization for Space Body Control |
| title_fullStr | Vision-Based Object Recognition and Precise Localization for Space Body Control |
| title_full_unstemmed | Vision-Based Object Recognition and Precise Localization for Space Body Control |
| title_short | Vision-Based Object Recognition and Precise Localization for Space Body Control |
| title_sort | vision based object recognition and precise localization for space body control |
| url | http://dx.doi.org/10.1155/2019/7050915 |
| work_keys_str_mv | AT zeyushangguan visionbasedobjectrecognitionandpreciselocalizationforspacebodycontrol AT lingyuwang visionbasedobjectrecognitionandpreciselocalizationforspacebodycontrol AT jianquanzhang visionbasedobjectrecognitionandpreciselocalizationforspacebodycontrol AT wenbodong visionbasedobjectrecognitionandpreciselocalizationforspacebodycontrol |