Recognition and Localization of Target Images for Robot Vision Navigation Control
This paper focuses on a visual navigation control system for mobile robots, recognizing target images and intelligent algorithms for the navigation system’s path tracking and localization techniques. This paper examines the recognition and localization of target images based on the visual navigation...
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2022-01-01
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| Series: | Journal of Robotics |
| Online Access: | http://dx.doi.org/10.1155/2022/8565913 |
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| _version_ | 1832564867064659968 |
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| author | Muji Chen |
| author_facet | Muji Chen |
| author_sort | Muji Chen |
| collection | DOAJ |
| description | This paper focuses on a visual navigation control system for mobile robots, recognizing target images and intelligent algorithms for the navigation system’s path tracking and localization techniques. This paper examines the recognition and localization of target images based on the visual navigation control of mobile robots. It proposes an efficient marking line method for recognizing and localization target images. Meanwhile, a fuzzy control method with smooth filtering and high efficiency is designed to improve the stability of robot operation, and the feasibility is verified in different scenarios. The corresponding image acquisition system is developed according to the characteristics of the experimental environment, and the acquired images are preprocessed to obtain corrected grayscale images. Then, target image recognition and linear fitting are performed to obtain target image positioning. The system calculates the angle and distance of the mobile robot, offsetting the target image in real time, adjusting the output signal, and controlling the mobile robot to realize path tracking. The comparison of sensor data and path tracking algorithm results during the experiment shows that the path tracking algorithm achieves good results with an angular deviation of ±1.5°. The application of RANSAC algorithm and improved Hough algorithm was analyzed in visual navigation control, and the two navigation line detection algorithms based on the image characteristics of the target image were improved in the optical detection area of the navigation line for the shortcomings of the two algorithms in visual navigation control, and the algorithms before and after the improvement were compared. |
| format | Article |
| id | doaj-art-0b5800e6a1dc4161b0e5de5e1ec3dfe5 |
| institution | Kabale University |
| issn | 1687-9619 |
| language | English |
| publishDate | 2022-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Journal of Robotics |
| spelling | doaj-art-0b5800e6a1dc4161b0e5de5e1ec3dfe52025-02-03T01:09:59ZengWileyJournal of Robotics1687-96192022-01-01202210.1155/2022/8565913Recognition and Localization of Target Images for Robot Vision Navigation ControlMuji Chen0College of Information EngineeringThis paper focuses on a visual navigation control system for mobile robots, recognizing target images and intelligent algorithms for the navigation system’s path tracking and localization techniques. This paper examines the recognition and localization of target images based on the visual navigation control of mobile robots. It proposes an efficient marking line method for recognizing and localization target images. Meanwhile, a fuzzy control method with smooth filtering and high efficiency is designed to improve the stability of robot operation, and the feasibility is verified in different scenarios. The corresponding image acquisition system is developed according to the characteristics of the experimental environment, and the acquired images are preprocessed to obtain corrected grayscale images. Then, target image recognition and linear fitting are performed to obtain target image positioning. The system calculates the angle and distance of the mobile robot, offsetting the target image in real time, adjusting the output signal, and controlling the mobile robot to realize path tracking. The comparison of sensor data and path tracking algorithm results during the experiment shows that the path tracking algorithm achieves good results with an angular deviation of ±1.5°. The application of RANSAC algorithm and improved Hough algorithm was analyzed in visual navigation control, and the two navigation line detection algorithms based on the image characteristics of the target image were improved in the optical detection area of the navigation line for the shortcomings of the two algorithms in visual navigation control, and the algorithms before and after the improvement were compared.http://dx.doi.org/10.1155/2022/8565913 |
| spellingShingle | Muji Chen Recognition and Localization of Target Images for Robot Vision Navigation Control Journal of Robotics |
| title | Recognition and Localization of Target Images for Robot Vision Navigation Control |
| title_full | Recognition and Localization of Target Images for Robot Vision Navigation Control |
| title_fullStr | Recognition and Localization of Target Images for Robot Vision Navigation Control |
| title_full_unstemmed | Recognition and Localization of Target Images for Robot Vision Navigation Control |
| title_short | Recognition and Localization of Target Images for Robot Vision Navigation Control |
| title_sort | recognition and localization of target images for robot vision navigation control |
| url | http://dx.doi.org/10.1155/2022/8565913 |
| work_keys_str_mv | AT mujichen recognitionandlocalizationoftargetimagesforrobotvisionnavigationcontrol |