• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 한국공작기계학회 2003년도 추계학술대회
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• pp.201-206
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• 2003

In this paper, it is presented a new technique to the design and real-time implementation of fuzzy control system based-on digital signal processors in order to improve the precision and robustness for system of industrial robot. Fuzzy control has emerged as one of the most active and fruitful areas for research in the applications of fuzzy set theory, especially in the real of industrial processes. In this thesis, a self-organizing fuzzy controller for the industrial robot manipulator with a actuator located at the base is studied. A fuzzy logic composed of linguistic conditional statements is employed by defining the relations of input-output variable of the controller, In the synthesis of a FLC, one of the most difficult problems is the determination of linguistic control rules from the human operators. To overcome this difficult, SOFC is proposed fir a hierarchical control structure consisting of basic level and high level that modify control rules. The proposed SOFC scheme is simple in structure, fast in computation and suitable for implementation of real-time control. Performance of the SOFC is illustrated by simulation and experimental results for robot with eight joints.

• Journal of Institute of Control, Robotics and Systems
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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.

• Journal of Institute of Control, Robotics and Systems
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• 제14권7호
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• pp.672-678
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• 2008

This paper proposes a new rehabilitation robot with upper and lower limb connections for gait training. As humans change a walking speed, their nervous systems adapt muscle activation patterns to modify arm swing for the appropriate frequency. By analyzing this property, we can find a relation between arm swinging and lower limb motions. Thus, the lower limb motion can be controlled by the arm swing for walking speed adaptation according to a patent's intension. This paper deals with the design aspects of the suggested gait rehabilitation robot, including a trajectory planning and a control strategy. The suggested robot is mainly composed of upper limb and lower limb devices, a body support system. The lower limb device consists of a slider device and two 2-dof footpads to allow walking training at uneven and various terrains. The upper limb device consists of an arm swing handle and switches to use as a user input device for walking. The body support system will partially support a patient's weight to allow the upper limb motions. Finally, we showed simulation results for the designed trajectory and controller using a dynamic simulation tool.

• The Transactions of the Korean Institute of Electrical Engineers
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• 제40권8호
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• pp.816-824
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• 1991

It is well known that dynamic control is needed for fast and accurate control. Neural networks are ideal for representing the strongly nonlinear relationship in the dynamic equations including complex unmodeled effects. It thus creates many advantages over conventional methods such as simple, fast and accurate control through neural network's inherent learning and massive parallelism. In this paper, dynamic control of the full six degrees of freedom of an industrial robot arm will be presented using neural networks. Moreover, through application to a real robot the usefulness of neurocontrol is demonstrated. The back propagation and feedback-error learning is used to train the neurocontroller. Simulated control of a PUMA 560 arm demonstrates that it moves at high speed with good accuracy and generalizes over untrained trajectories as well as adapt to unforseen load changes and sensor noise.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2005년도 ICCAS
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• pp.969-972
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• 2005

This paper presents a GA-fuzzy $P^2ID$ control system for the flexible-joint robot arm. This controller is designed based on the parameter adjustment using fuzzy logic and genetic algorithms. According to the simulations, the better performance has been achieved acquired that the robot moved smoothly and met its required objectives. The results of comparison between 8 parameters and 10 parameters can be conclusion that the 10 parameters have setting time little than 8 parameters. In usability can be use 8 or 10 parameters these one.

• The Journal of the Korea institute of electronic communication sciences
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• 제12권6호
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• pp.1127-1134
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• 2017

In this study, the robot arm control system was implemented that is operated by human hands, which can be used in environments that are inaccessible to humans. This function has to be sent to the robot's arms after extracting coordinates of human hands. Through mapping and bluetooth communication we use a leap motion sensor with infrared light and Image recognition sensor.

• The Journal of the Korea institute of electronic communication sciences
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• 제16권6호
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• pp.1205-1212
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• 2021

Robots that can actually help people a lot by dealing with dangerous tasks that are difficult for people to do, such as disaster situations, lifesaving, handling dangerous goods, and reconnaissance of dangerous areas, continue to become an issue. Therefore, in this paper, we intend to implement a mobile robot arm that can implement a human motion will on the robot arm to enable active response according to the situation and control the vehicle according to hand movements to give mobility. A controller is manufactured using a flex sensor and agyro sensor, and the roll and pitch values of the two gyro sensors are adjusted to control the angle of the robot arm and specify the vehicle direction. In addition, by designating the levels of the three flex sensors, the motor is operated according to hand movements, and a robot arm is implemented so that objects can be picked up and moved.

• Journal of Biomedical Engineering Research
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• 제35권3호
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• pp.50-54
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• 2014

It is being tried to control robot arm using brain signal in the field of brain-machine interface (BMI). This study is focused on applying guidance laws for efficient robot arm control using 3D coordinates obtained from Magnetoencephalography (MEG) signal which represents movement of upper limb. The 3D coordinates obtained from brain signal is inappropriate to be used directly because of the spatial difference between human upper limb and robot arm's end-effector. The spatial difference makes the robot arm to be controlled from a third-person point of view with assist of visual feedback. To resolve this inconvenience, guidance laws which are frequently used for tactical ballistic missile are applied. It could be applied for the users to control robot arm from a first-person point of view which is expected to be more comfortable. The algorithm which enables robot arm to trace MEG signal is provided in this study. The algorithm is simulated and applied to 6-DOF robot arm for verification. The result was satisfactory and demonstrated a possibility in decreasing the training period and increasing the rate of success for certain tasks such as gripping object.

• Journal of Power System Engineering
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• 제21권1호
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• pp.30-36
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• 2017

In robot industries, the request to obtain a high efficiency and accurately controlled electric actuator has been growing. Nevertheless, the effectiveness of electric actuators is significantly affected by the presence of factors such as nonlinearity, uncertain disturbance and unknown dynamics. Therefore, it makes difficult to derive an exact mathematical model of the controlled system. In this paper, a new method for easily recognizing and regenerating robot motions used in small size industries such as painting and welding parts is proposed. Instead of modeling the entire dynamic motion of the robot system, this method is based on the procedure of modeling and controller design for every arm individually. The proposed method does not require complex model and control system such that it gives easy working process to the small size industries. Based on this fact, in this research, the model and PID controller for every arm of the 3 DOF robot system are obtained separately. Some experimental results are implemented to validate the effectiveness of the proposed method.

• Journal of Institute of Control, Robotics and Systems
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• 제3권5호
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• pp.461-468
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• 1997

A real-time collision-free trajectory control method for dual arm robot system is proposed. The proposed method is composed of two stages; one is to calculate the minimum distance between two robot arms and the other is to control the trajectories of the robots to ensure collision-free motions. The calculation of minimum distance between two robots is, also, composed of two steps. To reduce the calculation time, we, first, apply a simple modeling technique to the robots arms and determine the interested part of the robot arms. Next, we apply more precise modeling techniques for the part to calculate the minimum distance. Simulation results show that the whole algorithm runs within 0.05 second using Pentium 100MHz PC.