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An Automatic Grabbing Method of Manipulator Based on Monocular Ranging
Author(s) -
Chenyu Zhang,
Mengxing Huang,
Di Wu,
Yiyin Ding,
Weizhe Chen,
Jin Xiao,
Rong Chen
Publication year - 2019
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1314/1/012132
Subject(s) - ranging , computer science , inverse kinematics , flexibility (engineering) , monocular vision , focus (optics) , object (grammar) , trajectory , kinematics , lens (geology) , artificial intelligence , computer vision , monocular , inverse , range (aeronautics) , control theory (sociology) , robot , engineering , control (management) , mathematics , telecommunications , statistics , physics , geometry , classical mechanics , astronomy , petroleum engineering , optics , aerospace engineering
Most existing studies on manipulator focus on the field of teaching and research. Other manipulators used for industrial production also have several disadvantages, including high cost, complicated control and low flexibility. Accordingly, in this paper, a simple automatic grabbing method of manipulator is proposed based on monocular ranging. The method is developed via the openmv vision platform. First, the target object is identified in the lens, the linear distance of the lens from the target object is calculated through monocular ranging, and then the inverse kinematics of the manipulator is exploited to calculate the rotation angle of each steering engine. Next, the contradiction between system speed and impact is balanced using the five-time curve trajectory optimization algorithm. The results of tests suggest that the method can achieve accurate capture of the target object in the grab range. The method, compared with the teaching and even the engineering manipulator system, is characterized by lower cost, simple and flexible control. Besides, it can be used to implement simple tasks in industry.

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