• Journal of the Korean Society of Industry Convergence
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• v.18 no.4
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• pp.216-223
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• 2015

Recently Manipulation capability is important for a robot. Interaction between a robot hand and objects can be properly controlled only is suitable sensors are available. Recently the tendency is to create robot hands more compact and high integrated sensors system, in order to increase the grasping capability and in order to reduce cabling through the finger, the palm and the arm. As a matter of fact, miniaturization and cabling harness represents a significant limitation to the design of small sized embedded sensor. Ongoing work is focusing on a flexible manipulation system, which consists of a dual flexible multi-fingered hand-arm system, and a dual active vision system.

• Journal of the Korean Institute of Intelligent Systems
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• v.8 no.3
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• pp.95-103
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• 1998

This paper deals with a problem occuring in recognition of tactile images due to the effects of imposed force at a me urement moment. Tactile image of a contact surface, used for recognition of the surface type, varies depending on the forces imposed so that a false recognition may result in. This paper fuzzifies two parameters of the contour of a tactile image with the membership function formed by considering the imposed force. Two fuzzifed paramenters are fused by the average Minkowski's dist; lnce. The proposed algorithm was implemented on the multisensor system cnmposed of an optical tact le sensor and a 6 axes forceltorque sensor. By the experiments, the proposed algorithm has shown average recognition ratio greater than 869% over all imposed force ranges and object models which is about 14% enhancement comparing to the case where only the contour information is used. The pro- ~oseda lgorithm can be used for end-effectors manipulating a deformable or fragile objects or for recognition of 3D objects by implementing on multi-fingered robot hand.