Application of OpenCV multi video mosaic fusion in group robot control
Swarm robot control technology shows great potential in improving production eficiency and optimizing resource allocation. However, how to obtain comprehensive environmental information has become a major challenge. Therefore, this study proposes a real-time mosaic fusion algorithm of multi video images based on OpenCV, which aims to provide global vision for swarm robot. video mosaic technology has been widely used in the fields of monitoring, navigation and scene understanding. It provides more comprehensive environmental information for the observer by seamlessly splicing multiple video images together to form a wide viewing angle or panoramic image. In the control of swarm robots, this technology can significantly improve the perception ability of robots to the environment. In this study, the real-time mosaic and fusion of multiple video images are realized by using the modules of feature point detection, feature matching, image transformation and image fusion in OpenCV. Among them, multi band fusion, image smoothing and other technologies are used to reduce the stitching gap and image distortion, and improve the stitching quality. The experimental results show that the multi video image real-time mosaic fusion algorithm proposed in this study can efectively provide global vision for swarm robots.
Authors
- Chunlai Guo (ORCID: https://orcid.org/0009-0001-4848-9621)
- Jianmin Wang (ORCID: https://orcid.org/0000-0001-6841-7943)
- Yang Cao (ORCID: https://orcid.org/0000-0001-7787-8506)
- Zhen Zhang (ORCID: https://orcid.org/0000-0002-2905-8578)
- Shuo Liang Lin (ORCID: https://orcid.org/0000-0002-9303-1310)
- Wei Zhao (ORCID: https://orcid.org/0009-0004-1001-7866)
- G. Leng
Institutions
- Harbin University (CN)
- China Mobile (China) (CN)
- Belarusian National Technical University (BY)
Publication Details
- Published
- 2025-03-14
- DOI
- https://doi.org/10.1109/itoec63606.2025.10968398
- Primary Topic
- Simulation and Modeling Applications
- Type
- article
- Field-Weighted Citation Impact
- 0.00