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Automated 3-D Micrograsping Tasks Performed by Vision-Based Control

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4 Author(s)
Lidai Wang ; Dept. of Mech. & Ind. Eng., Univ. of Toronto, Toronto, ON, Canada ; Lu Ren ; Mills, J.K. ; Cleghorn, W.L.

We present a fully automated micrograsping methodology that uses a micro-robot and a microgripper to automatically grasp a micropart in three-dimensional (3-D) space. To accurately grasp a micropart in 3-D space, we propose a three-stage micrograsping strategy: (i) coarse alignment of a micropart with a microgripper in the image plane of a video camera system; (ii) alignment of the micropart with the microgripper in the direction normal to the image plane; (iii) fine alignment of the micropart with the microgripper in the image plane, until the micropart is completely grasped. Two different vision-based feedback controllers are employed to perform the coarse and fine alignment in the image plane. The vision-based feedback controller used for the fine alignment employs position feedback signals obtained from two special patterns, which can achieve submicron alignment accuracy. Fully automated micrograsping experiments are conducted on a microassembly robot. The experimental results show that the average alignment accuracy achieved during automated grasping is approximately ± 0.07 μm; the time to complete an automated micrograsping task is as short as 7.9 seconds; and the success rate is as high as 94%.

Published in:

Automation Science and Engineering, IEEE Transactions on  (Volume:7 ,  Issue: 3 )