• Transactions of the Korean Society of Mechanical Engineers A
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• v.21 no.8
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• pp.1209-1217
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• 1997

This paper proposes the modeling of the dynamics of two cooperating robot manipulators performing the assembly job such as peg-in-hole while coordinating the payload along the desired path. The mass and moment of inertia of the manipulators and the payload are assumed to be unknown. To control the uncertain system, a robust control algorithm based on the computed torque control is proposed. Usually, the robust controller requires high input torques such that it may face input saturation in actual application. In this reason, the robust control algorithm includes fuzzy logic such that the magnitude of the input torque of the manipulators is controlled not to go over the hardware saturation while keeping path tracking errors bounded. A numerical example using dual three degree-of-freedom manipulators is shown.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.24 no.12
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• pp.3072-3079
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• 2000

Assembly tasks are often performed by one robot with fixtures. This type of assembly system has low flexibility in terms of the variety of parts and the part-presentation the system can handle. This paper addresses assembly without fixtures using two-manipulator robot. An active method using force feedback is proposed for the peg-in-hole assembly in highly uncertain environment. Assembly states are defined as status having unique motion constraints and events are modeled as variation of the environmental force. The states are recognized through identification of the events using two 6-d. o. f. force/moment sensors. The proposed method is verified and evaluated by experiments with round peg-in-hole assembly.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1996.04a
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• pp.427-431
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• 1996

A modeling of the dynamics of two cooperating robot manipulators doing assembly job such as peg-in-hole while coordinating the payload along the desired path is proposed. The system is uncertain due to the unknown mass and moment of inertia of the manipulators and the payload. To control the system, a robust control algorithm is proposed. The control algorithm includes fuzzylogic. By the fuzzy logic, the magnitude of the input torque of the manipulators is controlled not to go over the hardware saturation with keeping path tracking errors bounded.