TY - JOUR
T1 - Automated 3-D micrograsping tasks performed by vision-based control
AU - Wang, Lidai
AU - Ren, Lu
AU - Mills, James K.
AU - Cleghorn, William L.
PY - 2010/7
Y1 - 2010/7
N2 - 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%. © 2010 IEEE.
AB - 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%. © 2010 IEEE.
KW - microassembly
KW - Microelectromechanical systems
KW - micrograsping
KW - vision-based control
UR - http://www.scopus.com/inward/record.url?scp=77954386842&partnerID=8YFLogxK
UR - https://www.scopus.com/record/pubmetrics.uri?eid=2-s2.0-77954386842&origin=recordpage
U2 - 10.1109/TASE.2009.2036246
DO - 10.1109/TASE.2009.2036246
M3 - RGC 21 - Publication in refereed journal
SN - 1545-5955
VL - 7
SP - 417
EP - 426
JO - IEEE Transactions on Automation Science and Engineering
JF - IEEE Transactions on Automation Science and Engineering
IS - 3
M1 - 5411942
ER -