Gao, R.; Li, Y.; Liu, Z.; Zhang, S. Target Localization and Grasping of Parallel Robots with Multi-Vision Based on Improved RANSAC Algorithm. Appl. Sci.2023, 13, 11302.
Gao, R.; Li, Y.; Liu, Z.; Zhang, S. Target Localization and Grasping of Parallel Robots with Multi-Vision Based on Improved RANSAC Algorithm. Appl. Sci. 2023, 13, 11302.
Gao, R.; Li, Y.; Liu, Z.; Zhang, S. Target Localization and Grasping of Parallel Robots with Multi-Vision Based on Improved RANSAC Algorithm. Appl. Sci.2023, 13, 11302.
Gao, R.; Li, Y.; Liu, Z.; Zhang, S. Target Localization and Grasping of Parallel Robots with Multi-Vision Based on Improved RANSAC Algorithm. Appl. Sci. 2023, 13, 11302.
Abstract
Some traditional robots are based on offline programming reciprocal motion, and with the continuous upgrading of vision technology, more and more tasks are replaced by machine vision. For the current problem of insufficient accuracy of robot target localization based on binocular vision, and an improved random sampling consistency algorithm is proposed to complete parallel robot target localization and grasping under the guidance For the current problem of insufficient accuracy of robot target localization based on binocular vision, an improved random sampling consistency algorithm is proposed to complete parallel robot target localization and grasping under the guidance of multi Firstly, the RANSAC algorithm is improved based on the SURF algorithm; then the parallax gradient method is applied to iterate the matched point pairs several times to further optimize the data; then the 3D reconstruction is completed by the program technique; finally the obtained data is finally the obtained data is input into the robot arm and the camera internal and external parameters are obtained by the calibration method so that the robot can accurately locate and The experiments show that the improved algorithm has advantages in recognition accuracy and grasping success rate under multi- The experiments show that the improved algorithm has advantages in recognition accuracy and grasping success rate under multi-vision system.
Keywords
multiocular vision; random sampling consistency; 3D reconstruction; parallel robot; target localisation and grasping
Subject
Engineering, Control and Systems Engineering
Copyright:
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