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Structural analysis of built-in sensor frame in jaws with linear type gripper

Title
Structural analysis of built-in sensor frame in jaws with linear type gripper
Author(s)
Shin, Dong HwanPark, Tae SangKim, Yoon GuAn, Jin Ung
DGIST Authors
Shin, Dong HwanPark, Tae SangKim, Yoon GuAn, Jin Ung
Issued Date
2012
Type
Conference
Article Type
Conference Paper
ISBN
9780000000000
ISSN
2161-8070
Abstract
It is important to design gripper jaws and tips which contact with the handled part, for a proper conduction of a given mission of robot systems. Especially, it should be also considered to use what kind of sensors and degree of freedoms in gripper systems. If the tip of gripper has the force and torque sensor, it is possible to measure the value of reaction forces and torques from sensors on gripping. Further this leads to enhance the intelligence of gripper system such as the prevention of slip occurrence and the estimation of mass center position of handled parts. On the other hand, the smallest force and torque sensor among commercial ones has 17mm as a diameter and 15mm as a height. It is not compact to adapt even this smallest sensor in jaws of gripper. Therefore, it is necessary to develop the sensor equipped in jaws with smaller sizes, as not a package type but a separated built-in type (sensor frame and data acquisition board is separated). In this paper, as a part of embodiment of built-in type force and torque sensor, we describe the required DOF of sensor for pick-and-place tasks and the structural analysis of sensor frame built-in jaw with linear type gripper. © 2012 IEEE.
URI
http://hdl.handle.net/20.500.11750/1788
DOI
10.1109/CoASE.2012.6386512
Publisher
Institute of Electrical and Electronics Engineers
Related Researcher
  • 신동환 Shin, Dong-Hwan 미래자동차연구부
  • Research Interests Multi-body dynamic simulation;다물체 동역학 해석; Structural Analsys;구조해석
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Appears in Collections:
Convergence Research Center for Future Automotive Technology 2. Conference Papers
Division of Intelligent Robotics Brain Robot Augmented InteractioN(BRAIN) Laboratory 2. Conference Papers

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