• 제어로봇시스템학회논문지
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• 제14권7호
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• pp.656-662
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• 2008

A cost-function based on manipulability and compatibility is designed to determine assembly motions of two cooperating manipulators. Assembly motions are planned along the direction maximizing performance indices to improve control performance of the two manipulators. This paper proposes bimanual task compatibility by defining cost functions. The proposed cost functions are applied and compared to the bimanual assembly task. The problem is formulated as a constrained optimization considering assembly constraints, position of the workpieces, and kinematics and redundancy of the bimanual robot. The proposed approach is evaluated with simulation of a peg-in-hole assembly with an L-shaped peg and two 3-dof manipulators.

• 제어로봇시스템학회논문지
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• 제21권10호
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• pp.972-976
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• 2015

The objective of this research is to verify the quantitative efficiency of a bimanual robotic task. Bimanual robots can realize dexterous and complicated motions using two cooperating arms. However, its motion planning and control method are not simple for implementing flexible tasks such as assembly. In this paper, the proposed motion planning method is used to find an optimal solution satisfying a designed cost function and constraints with regard to the kinematics and redundancy of the bimanual robot. The simulation results show that the lifetime of the manipulator can be changed by the proposed cost function consisting of angular velocity and angular acceleration of each joint in the same assembly task.

• 로봇학회논문지
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• 제8권1호
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• pp.20-28
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• 2013

Large workspace and strong grasping force are required when a robot manipulates big and/or heavy objects. In that situation, bimanual manipulation is more useful than unimanual manipulation. However, the control of both hands to manipulate an object requires a more complex model compared to unimanual manipulation. Learning by human demonstration is a useful technique for a robot to learn a model. In this paper, we propose an imitation learning method of bimanual object manipulation by human demonstrations. For robust imitation of bimanual object manipulation, movement trajectories of two hands are encoded as a movement trajectory of the object and a force trajectory to grasp the object. The movement trajectory of the object is modeled by using the framework of dynamic movement primitives, which represent demonstrated movements with a set of goal-directed dynamic equations. The force trajectory to grasp an object is also modeled as a dynamic equation with an adjustable force term. These equations have an adjustable force term, where locally weighted regression and multiple linear regression methods are employed, to imitate complex non-linear movements of human demonstrations. In order to show the effectiveness our proposed method, a movement skill of pick-and-place in simulation environment is shown.

• 제어로봇시스템학회논문지
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• 제22권8호
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• pp.656-664
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• 2016

While anthropomorphic robots are gaining interest, dual-arm robots are widely used in the industrial environment. Many methods exist in order to implement bimanual tasks by dual-arm robot. However, kinesthetic teaching is used in this paper. This paper suggests three different kinesthetic teaching methods that can implement most of the human task by the robot. The three kinesthetic teaching methods are joint level, task level, and contact level teaching. The task introduced in this paper is box packing, which is a popular and complex task in industrial environment. The task is programmed into the dual-arm robot by utilizing the suggested kinesthetic teaching method, and this paper claims that most tasks can be implemented by using the suggesting kinesthetic teaching methods.