Robot Obstacle Recognition and Target Tracking Based on Binocular Vision. (18th August 2022)
- Record Type:
- Journal Article
- Title:
- Robot Obstacle Recognition and Target Tracking Based on Binocular Vision. (18th August 2022)
- Main Title:
- Robot Obstacle Recognition and Target Tracking Based on Binocular Vision
- Authors:
- Sun, Wencheng
- Other Names:
- Li Qiangyi Academic Editor.
- Abstract:
- Abstract : To further improve the perception ability of binocular vision sensor in getting rich environment information and scene depth information, a research method of a robot obstacle recognition and target tracking based on binocular vision was proposed. The method focused on target recognition and obstacle recognition of binocular stereo vision. The system based on obstacles of visual identification was set up. Through the analysis of the Bouguet mathematical model algorithm based on OpenCV, the binocular stereo correction was carried out and the obstacle recognition system was calibrated and corrected. Through the experimental data, it was found that the average error of the obstacle recognition and target tracking algorithm based on binocular vision could be controlled within 50 mm within the range of 2100 mm. The average time of obstacle recognition was 0.096 s and the average time consumption of the whole system was 0.466 s, indicating that the robot obstacle recognition and target tracking system based on binocular vision could meet the accuracy and real-timeness requirements of obstacle recognition and detection.
- Is Part Of:
- Advances in multimedia. Volume 2022(2022)
- Journal:
- Advances in multimedia
- Issue:
- Volume 2022(2022)
- Issue Display:
- Volume 2022, Issue 2022 (2022)
- Year:
- 2022
- Volume:
- 2022
- Issue:
- 2022
- Issue Sort Value:
- 2022-2022-2022-0000
- Page Start:
- Page End:
- Publication Date:
- 2022-08-18
- Subjects:
- Multimedia systems -- Periodicals
Computer networks -- Periodicals
Multimédia
Réseaux d'ordinateurs
Computer networks
Multimedia systems
Periodicals
006.7 - Journal URLs:
- https://www.hindawi.com/journals/am/ ↗
http://bibpurl.oclc.org/web/22854 ↗ - DOI:
- 10.1155/2022/9022038 ↗
- Languages:
- English
- ISSNs:
- 1687-5680
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library HMNTS - ELD Digital store
- Ingest File:
- 23059.xml