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Development of the Intelligent Gripper Using Two 3-axis Force Sensor  

Kim, Gab-Soon (경상대학교 제어계측공학과)
Publication Information
Journal of the Korean Society for Precision Engineering / v.24, no.3, 2007 , pp. 47-54 More about this Journal
Abstract
This paper describes the development of the intelligent gripper with two 3-axis force sensor that can measure forces Fx, Fy, Fz simultaneously, for stably grasping an unknown object. In order to grasp an unknown object using an intelligent gripper softly, it should measure the force in the gripping direction and the force in the gravity direction, and perform the force control using the measured farces. Thus, the intelligent gripper should be composed of 3-axis force sensor that can measure forces Fx, Fy, Fz at the same time. In this paper, the intelligent gripper with two 3-axis force sensor was manufactured and its characteristic test was carried out. The fabricated gripper could grasp an unknown object stably. Also, the sensing element of 3-axis force sensor was modeled and designed with five parallel-plate beams, and 3-axis force sensor for the intelligent gripper was fabricated. The characteristic test of the made sensor was carried out.
Keywords
Intelligent gripper; 3-axis force sensor; Parallel-plate beam; Rated strain; Interference error;
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1 Yin, X., Guo, D. and Xie, M., 'Hand image segmentation using color and RCE neural network,' Robotics and Autonomous Systems, Vol.34, No.4, pp.235-250, 2001   DOI   ScienceOn
2 Lee, J., 'Apply Force/Torque Sensors to Robotic Applications,' North-Holland Robotics2, pp. 139-­148, 1987
3 Kim, G. S., 'design of 3-component force/moment sensor with force/moment ratio of wide range,' Korean Society for Precision Engineering, Vol. 18, No. 2, pp. 214-221, 2001
4 Yabuki, A., 'Six-Axis ForcelTorque Sensor for Assembly Robots,' FUJTSU Science Technology, Vol. 26, No. 1, pp. 41-47, 1990
5 Joseph, C. and Yunhui, 'Dynamic simulation of multi-fingered robot hands based on a unified model,' Robotics and Autonomous Systems, Vol.32, No. 2-3, pp.185-201, 2000   DOI   ScienceOn
6 Steil, J. J., Rthling, F., Haschke, R. and Ritter, H. 'Situated robot learning for multi-modal instruction and imitation of grasping,' Robotics and Autonomous Systems, Vol.47, No. 2-3, pp.129-141, 2004   DOI   ScienceOn
7 ATI INDUSTRIAL AUTOMATION, 'Multi-Axis Force/Torque Sensor,' ATI INDUSTRIAL AUTOMATION, pp.4-45, 2005
8 Domnguez-Lpez, J. A., Damper, R. I., Crowder, R. M. and Harris, C. J., 'Adaptive neurofuzzy control of a robotic gripper with on-line machine learning,' Robotics and Autonomous Systems, Vol.48, No. 2-3, pp.93-110, 2004   DOI