• Journal of the Korean Society for Precision Engineering
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• v.16 no.1 s.94
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• pp.211-218
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• 1999

The traditional robot manipulators are actuated by continuous range of motion actuators such as motors or hydraulic cylinders. However, there are many applications of mechanisms and robotic manipulators where only a finite number of locations need to be reached, and the robot’s trajectory is not important as long as it is bounded. Binary manipulator uses actuators which have only two stable states. As a result, binary manipulators have a finite number of states. The number of states of a binary manipulator grows exponentially with the number of actuators. This kind of robot manipulator has some advantage compared to a traditional one. Feedback control is not required, task repeatability can be very high, and finite state actuators are generally inexpensive. And this kind of robot manipulator has a fault tolerant mechanism because of kinematic redundancy. In this paper, we solve the inverse kinematic problem of a binary parallel robot manipulator using neural network and test the validity of this structure using some arbitrary points m the workspace of the robot manipulator. As a result, we can show that the neural network can find the nearest feasible points and corresponding binary states of the joints of the robot manipulator

• Journal of the Korea Academia-Industrial cooperation Society
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• v.9 no.6
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• pp.1574-1580
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• 2008

In this paper, to bring under robust and accurate control of auto-equipment systems which disturbance, parameter alteration of system, uncertainty and so forth exist, neural network controller called dynamic neural processor(DNP) is designed In order to perform a elaborate task like as assembly, manufacturing and so forth of components, tracking control on the trajectory of power coming in contact with a target as well as tracking control on the movement course trajectory of end-effector is indispensable. Also, the learning architecture to compute inverse kinematic coordinates transformations in the Plants of auto-equipment systems is developed and the example that DNP can be used is explained. The architecture and learning algorithm of the proposed dynamic neural network, the DNP, are described and computer simulations are provided to demonstrate the effectiveness of the proposed learning method using the DNP.

• Journal of KIISE:Software and Applications
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• v.36 no.2
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• pp.131-143
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• 2009

Based on the fact that a human being walks naturally and stably with consuming a minimum energy, this paper proposes a new method of generating a natural gait of 5-link biped robot like human by analyzing a COG (Center Of Gravity) trajectory of human's gait. In order to generate a natural gait pattern for 5-link biped robot, it considers the COG trajectory measured from human's gait images on the sagittal and frontal plane. Although the human and 5-link biped robot are similar in the side of the kinematical structure, numbers of their DOFs(Degree Of Freedom) are different. Therefore, torques of the human's joints cannot are applied to robot's ones directly. In this paper, the proposed method generates the gait pattern of the 5-link biped robot from the GA algorithm which utilize human's ZMP trajectory and torques of all joints. Since the gait pattern of the 5-link biped robot model is generated from human's ones, the proposed method creates the natural gait pattern of the biped robot that minimizes an energy consumption like human. In the side of visuality and energy efficiency, the superiority of the proposed method have been improved by comparative experiments with a general method that uses a inverse kinematics.

• Journal of the Society of Naval Architects of Korea
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• v.35 no.2
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• pp.51-62
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• 1998

In this paper, a CAD/CAM system for 5-axis machining of model propeller is introduced. This system has been developed under the environment of personal computer and Windows NT. In order to enhance the productivity, existing text-based design S/W was integrated into this graphic-based system. Non-Uniform Rational B-Spline method is used to represent the sculptured surface of propeller blades and hub using point data, and surface blending between blade and hub is realized in this system. For 5-axis machining of sculptured surface, tool/work collision and interference are checked and inverse kinematic analysis is performed to make NC data. In addition, tool and workpiece are animated on the PC monitor by preparing NC verification module. Finally, optimal cutting conditions are determined empirically and those cutting conditions are integrated into this S/W so that the whole process from design to machining can be done automatically.