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RISS 인기검색어
- 검색키워드
- 저자 : 안두성(D. S. Ahn) (검색결과 27 건)
- 무료
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D. S. Ahn(안두성),I. Y. Lee(이일영),H. Y. Kim(김현호) 유공압건설기계학회 2015 유공압건설기계학회 학술대회논문집 Vol.2015 No.10
Hydraulic manipulators have been widely used in many different fields due to a high force/torque to inertia ratio. The speedup of hydraulic manipulators requires the solution of problems concerning various aspects, from the mechanical design to the necessity of determining a robot model suitable for control, and of experimentally testing the control performances. For one solution, integration of SolidWorks with Simscape for designing and controlling hydraulic manipulators is presented in this paper. The integration provides a flatform for rapid control prototyping of hydraulic robot without the need for building real prototypes. Mechanical drawings of a manipulator are first created using Solidworks and imported into the Simscape, where the manipulator is represented by connected block diagrams based on the principle of physical modeling. Simulation examples for 3D manipulator made by KNR SYSTEM INC. are testified to show effectiveness of the presented platform.
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안두성(D. S. Ahn),김성율(S. Y. Kim),조형석(H. S. Cho) Korean Society for Precision Engineering 1993 한국정밀공학회지 Vol.10 No.3
In this paper, a practical method to generate task strategies applicable to chamferless and high-precision assembly, is proposed. The difficulties in devising reliable assembly strategies result from various forms of uncertainty such as imperfect knowledge on the parts being assembled and functional limitations of the assembly devices. In approach to cope with these problems, the robot is provided with the capability of learning the corrective motion in response to the force signal through iterative task execution. The strategy is realized by adopting a learning algorithm and represented in a binary tree type database. To verify the effectiveness of the proposed algorithm, a series of simulations and experiments are carried out under assimilated real production environments. The results show that the sensory signal-to-robot action mapping can be acquired effectively and, consequently, the chamferless assembly can be performed successfully.
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신상운(S. W. Shin),안두성(D. S. Ahn) Korean Society for Precision Engineering 1998 한국정밀공학회지 Vol.15 No.9
This study presents the new method which can transfer the expert's skill to deburring robot through neural network. The expert's skill is expressed as association mapping between the characteristics of the burr and human expert's action. Under the fundamental idea that the state of the deburring process can be extracted via the visual sense of the human, we employ vision system for the perception and identification of the changing burr. From the demonstration of human experts, force data are measured. Finally the characteristics of the burr and corresponding force are associated by the neural network which is trained through many demonstrations. The proposed method is verified in the deburring process of welding burr.
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