Paper Info
Title
Target Measurement Method Based on Sparse Disparity for Live Power Lines Maintaining Robot
Abstract
3D perception has been an indispensable part of the research on many manipulator robots. In this paper, we propose a the new kind of target measurement method to perceive the surrounding environment of robots based on binocular stereo vision theory, which can effectively improves the 3D reconstruction accuracy and effectiveness of the target recognition. The sparse disparity method we apply is different from the dense binocular stereo vision method in common. At the beginning of the article, a series of effective methods of image processing we use to identify and extract target images will be introduce. A novel operator-matching algorithm is proposed to improve the extraction and recognition. The contour-center stereo matching theory is expounded to lay a foundation to the calculation of sparse disparity estimation. To give accurate 3D reconstruction model information, a calibration system with low measurement error is proposed based on dual manipulators of our robot. After coordinate transformation implementation, robots obtain point cloud data of the target and able to perform interactive actions. A wiring experiment is set to test this method by judging work efficiency and success rate.
Year
DOI
Venue
2020
10.1109/RCAR49640.2020.9303329
2020 IEEE International Conference on Real-time Computing and Robotics (RCAR)
Keywords
DocType
ISBN
target measurement method,live power lines maintaining robot,manipulator robots,binocular stereo vision theory,target recognition,sparse disparity method,dense binocular stereo vision method,target images,contour-center stereo matching theory,sparse disparity estimation,accurate 3D reconstruction model information,low measurement error
Conference
978-1-7281-7294-1
Citations 
PageRank 
References 
0
0.34
4
Authors
7
Name
Order
Citations
PageRank
Jing Zhu100.34
Yutao Chen201.01
Yahao Wang300.34
Hao Zhang400.34
Xuming Tang500.34
Ming Xu600.34
Erbao Dong767.32