Paper
1 January 1998 Design and highly accurate 3D displacement characterization of monolithic SMA microgripper using computer vision
Yves Bellouard, Armin Sulzmann, Jacques Jacot, Reymond Clavel
Author Affiliations +
Proceedings Volume 3202, Microrobotics and Microsystem Fabrication; (1998) https://doi.org/10.1117/12.298026
Event: Intelligent Systems and Advanced Manufacturing, 1997, Pittsburgh, PA, United States
Abstract
In the robotics field, several grippers have been developed using SMA technologies, but, so far, SMA is only used as the actuating part of the mechanical device. However mechanical device requires assembly and in some cases this means friction. In the case of micro-grippers, this becomes a major problem due to the small size of the components. In this paper, a new monolithic concept of micro-gripper is presented. This concept is applied to the grasping of sub- millimeter optical elements such as Selfoc lenses and the fastening of optical fibers. Measurements are performed using a newly developed high precision 3D-computer vision tracking system to characterize the spatial positions of the micro-gripper in action. To characterize relative motion of the micro-gripper the natural texture of the micro-gripper is used to compute 3D displacement. The microscope image CCD receivers high frequency changes in light intensity from the surface of the ripper. Using high resolution camera calibration, passive auto focus algorithms and 2D object recognition, the position of the micro-gripper can be characterized in the 3D workspace and can be guided in future micro assembly tasks.
© (1998) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Yves Bellouard, Armin Sulzmann, Jacques Jacot, and Reymond Clavel "Design and highly accurate 3D displacement characterization of monolithic SMA microgripper using computer vision", Proc. SPIE 3202, Microrobotics and Microsystem Fabrication, (1 January 1998); https://doi.org/10.1117/12.298026
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Cited by 2 scholarly publications.
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KEYWORDS
Shape memory alloys

3D vision

Computer vision technology

Machine vision

Actuators

Assembly equipment

Lenses

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