• Journal of the Korean Society for Precision Engineering
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• v.10 no.3
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• pp.175-181
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• 1993

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 trrough 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.

• Transactions of the Korean Society of Mechanical Engineers
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• v.18 no.1
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• pp.1-11
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• 1994

This paper presents an intelligent robotic control method for chamferless parts mating by integrating fuzzy control and neural network. The successful assembly task requires an extremely high position accuracy and a good knowledge of mating parts. However, conventional assembly method alone makes it difficult to achieve satisfactory assembly performance because of the complexity and the uncertainties of the process and its environments such as not only the limitation of the devices performing the assembly but also imperfect knowledge of the parts being assembled. To cope with these problems, an intelligent robotic assembly method is proposed, which is composed of fuzzy controller and learning mechanism based upon neural net. In this method, fuzzy controller copes with the complexity and the uncertainties of the assembly process, while neural network enhances the assembly scheme so as to learn fuzzy rules from experience and adapt to changes in environment of uncertainty and imprecision. The performance of the proposed assembly scheme is evaluted through a series of experiments using SCARA robot. The results show that the proposed control method can be effectively applied to chamferless precision parts mating.

• 제어로봇시스템학회:학술대회논문집
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• 1992.10a
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• pp.1072-1077
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• 1992

In ths paper a new active assembly algorithm for chamferless precision parts mating, is considered. The successful assembly task requires an extremely high position accuracy and a good knowledge of mating parts. However, conventional assembly mehtod alone makes it difficult to achieve satisfactory assembly performance because of the complexity and the uncertainties of the process and its environments such as imperfect knowledge of the parts being assembled as well as the limitation of the devices performing the assebled as well as the limitation of the devices performing the assembly. To cope with these problems, a self-learning rule-based assembly algorithm is proposed by intergaring fuzzy set theory and neural network. In this algortihm, fuzzy set theory copes with the complexity and the uncertainties of the assembly process, while neural network enhances the assembly schemen so as to learn fuzzy rules form experience and adapt to changes in environment of uncertainty and imprecision. The performance of the proposed assembly algorithm is evaluated through a series of experiments. The results show that the self-learning fuzzy assembly scheme can be effecitively applied to chamferless precision parts mating.

• Transactions of the Korean Society of Mechanical Engineers
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• v.16 no.12
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• pp.2315-2327
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• 1992

A robot assembly method which uses configuration and force/torque information of tactile sensor system and performs chamferless peg-in-hole tasks is suggested and experimentally studied. When the robot gripes the peg with random orientation, the realignment of the peg to the hole center line is successfully performed with the gripping configuration information of the tactile sensor and the inverse kinematics of the robot. The force/torque information of the tactile sensor makes it possible to control the contacting force between mating parts during hole search stage. The suggested algorithm employs a hybrid position/force control and the experiments show that the algorithm accomplishes well peg-in-hole tasks with permissible small contacting force. The chamferless peg-in-hole tasks with smaller clearance than the robot repeatibility can be excuted without any loss or deformation of mating parts. This study the possibility of precise and chamferless parts mating by robot and tactile sensor system.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1991.11a
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• pp.139-145
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• 1991

본 논문에서는 chamfer가 없는 경우에도 조립이 가능한 로봇 조립용 손목기구를 개발하였다. 손목기구에서는 chamfer있는 경우에 우수란 적응능력을 가지는 RCC(Remote Center Compliance) 구조가 이용되었으며 위치측정용 sensor와 공압 actuator를 이용하여 조립시 생기는 RCC 구조의 변형을 측정하여 이로부터 능동적으로 오차를 교정하도록 하였다. sensor signal로부터 적절한 오차교정방향을 찾아내는 algorithm 으로는 신경회로망을 이용하였으며 이 결과 손목기구의 비선형성에도 잘 적응함을 볼 수 있었다. 제작된 로봇 조립용 손목을 이용하여 chamferless part의 조립을 실험한 결과 clearance ratio가 0.02인 경우 eccentricity가 2mm 까지 오차교정이 가능함을 볼 수 있었다.

• Journal of the Korean Society for Precision Engineering
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• v.9 no.2
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• pp.36-43
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• 1992

In this paper, a robot assembly wrist, which is able to assemble chamferless parts, has been developed. The RCC (Remote Center Compliance) structure is used as a basic structure. 5 position sensors and 4 pneumatic actuators are installed additionally to measure the deformation of RCC structure and correct the errors actively. Due to the restricted direction of actuation, a decision rule which selects the suitable actuator according to the position sensor signals is needed. For this purpose, a neural network is used and it is experimentally shown that the nerual network overcomes system's nonlinearity. This paper presents fundamental experiment results for the insertion of parts with several clearance.

• 제어로봇시스템학회:학술대회논문집
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• 1991.10a
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• pp.693-698
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• 1991

This paper describes a fuzzy rule-based assembly algorithm for precision parts mating, The difficulties in devising reliable assembly strategies result from the complexity of the assembly process and the uncertainty such as imperfect knowledge of the parts being assembled as well as the limitations of the devices performing the assembly. To cope with above problems, we propose an assembly algorithm utilizing fuzzy set theory. The presented method allows us to represent the uncertainty by using fuzzy membership function and treat nonlinear sapping from measured force/torque to corrective motions using rules. Finally, the performance of this method is evaluated through a series of experiments. Experimental results show that the proposed method can be effectively used for chamferless and precision parts mating.

• 제어로봇시스템학회:학술대회논문집
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• 1991.10a
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• pp.1155-1160
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• 1991

Active part mating algorithm using 6-axis force sensor data for the assembly automation and/or teletobotics is presented and experimented. Parts to be mated are cylindrical and have no chamfers. There are basically two modes. One is the normal mode with only a positional error, the other is the tilted mode with an orientational error in addition to a positional error. The used algorithm distinguishes a contact external to the hole from that of internal to the hole in order to perform part-mating in spite of the relative tilt between the hole and the peg.