Paper
5 July 2024 Design of monocular vision field-assisted positioning for A Kid-sized humanoid soccer robot
Yu Zhao, Bixi Yan, Junfei Hu, Jun Wang
Author Affiliations +
Proceedings Volume 13184, Third International Conference on Electronic Information Engineering and Data Processing (EIEDP 2024); 131846Z (2024) https://doi.org/10.1117/12.3032893
Event: 3rd International Conference on Electronic Information Engineering and Data Processing (EIEDP 2024), 2024, Kuala Lumpur, Malaysia
Abstract
In order to improve the positioning accuracy of humanoid football robots on the playing field[1], this paper proposes a field-assisted positioning method based on monocular vision. By fixing a robot in a specific position and using its monocular camera to capture the key features of other robots and footballs on the field, the latest target detection algorithm YOLOv8 is used to accurately identify targets. Then, the distance measurement model established by the camera pose algorithm and the geometric relationship within the coordinate system are used to accurately calculate the relative coordinates of the robot on the football field. Through experimental verification, we found that among the five test algorithms, the ranging and auxiliary positioning model based on the EPNP algorithm performed best. Its ranging and positioning accuracy within 3 meters can reach a level of less than 10 centimeters, which fully proves confirm the effectiveness and accuracy of this method.
(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.
Yu Zhao, Bixi Yan, Junfei Hu, and Jun Wang "Design of monocular vision field-assisted positioning for A Kid-sized humanoid soccer robot", Proc. SPIE 13184, Third International Conference on Electronic Information Engineering and Data Processing (EIEDP 2024), 131846Z (5 July 2024); https://doi.org/10.1117/12.3032893
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KEYWORDS
Cameras

Ranging

Detection and tracking algorithms

Imaging systems

Visual process modeling

Distance measurement

Evolutionary algorithms

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