• Title/Summary/Keyword: deformable robot

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A Review: All Solid-state Electroactive Polymer-based Tunable Lens (고체 전기활성 고분자 기반 가변 렌즈의 연구동향)

  • Shin, Eun-Jae;Ko, Hyun-U;Kim, Sang-Youn
    • The Journal of Korea Robotics Society
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    • v.16 no.1
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    • pp.41-48
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    • 2021
  • In this paper, we review papers which report to the all solid-state electroactive polymer-based tunable lens. Since electroactive polymer-based tunable lenses change their focal length by responding to electric stimuli, it can be minimized the size and weight of optical modules. Thus, it has been received attention in the robot, mobile device and display industry. The all solid-state electroactive polymer-based tunable lenses can be classified into two categories depending on the classification of materials: ionic electroactive polymer-based lenses and non-ionic electroactive polymer-based lenses. Most of the ionic electroactive polymer-based tunable lenses are fabricated with ionic polymer-metal composite. So, the ionic electroactive polymer-based tunable lenses can be operated under low electric voltage. But small force, slow recovery time and environmental limitation for operation has been pointed to the disadvantage of the lenses. The non-ionic electroactive polymer-based tunable lenses are classified again into two categories: dielectric polymer-based tunable lenses and polyvinylchloride gel-based tunable lenses. The advantage of the dielectric polymer-based tunable lenses is fast response to electric stimuli. But the essential flexible electrodes degrade performance of the lens. Polyvinylchloride gel-based tunable lens has reported impressive performance without flexible electrodes.

Recognition of Tactilie Image Dependent on Imposed Force Using Fuzzy Fusion Algorithm (접촉력에 따라 변하는 Tactile 영상의 퍼지 융합을 통한 인식기법)

  • 고동환;한헌수
    • 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.

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