• Journal of Engineering Education Research
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• v.18 no.6
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• pp.3-10
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• 2015

The purpose of this study was to analyze STEAM learning/teaching program that relates robots and to develop and redesign STEAM teaching/learning program with a robot for elementary and secondary schools. 'Learning with a robot' is considered as one of the best candidates for STEAM education. This article mainly concerns a robot that can be helpful to improve students' interests in learning science and mathematics in schools. As the results of the STEAM learning/teaching program analyzing, the program for elementary schools contained more contents of liberal arts and fine arts, and the program for secondary schools contained more contents of science, technology, and math. In the middle school program, context for learning, class activities of creative design and emotional touch, evaluation, and job and career information were evenly implemented. In the elementary and high school program, there were few information about robotics career. We extracted all robot utilizable subjects and units from school curriculums, and redesigned contents which can be applicable to regular classes for schools. As the result of this study, we conclude that 'learning with a robot' can encourage students' interests in STEM area.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.552-555
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• 1997

Recently, increasing attention has been paid to the application of learning control method to robot manipulator control. Because the learning control method does not require an exact dynamic model, it is flexible and easy to implement. In this paper, we implement a learning control scheme which consists of a unique feedforward learning controller and a linear feedback controller. The learning control method does not require acceleration terms that are sensitive to noise and has the capability of rejecting unknown disturbances and adapting itself to time-varying system parameters. The feasibility of the learning control scheme is soon by implementing the control scheme to a commercial robot manipulator and the performance of which is also compared with the conventional linear PID control method.

• Journal of Mechanical Science and Technology
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• v.20 no.7
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• pp.917-928
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• 2006

In recent decades, Artificial Neural Networks (ANNs) have become the focus of considerable attention in many disciplines, including robot control, where they can be used to solve nonlinear control problems. One of these ANNs applications is that of the inverse kinematic problem, which is important in robot path planning. In this paper, a neural network is employed to analyse of inverse kinematics of PUMA 560 type robot. The neural network is designed to find exact kinematics of the robot. The neural network is a feedforward neural network (FNN). The FNN is trained with different types of learning algorithm for designing exact inverse model of the robot. The Unimation PUMA 560 is a robot with six degrees of freedom and rotational joints. Inverse neural network model of the robot is trained with different learning algorithms for finding exact model of the robot. From the simulation results, the proposed neural network has superior performance for modelling complex robot's kinematics.

• Journal of The Korean Association of Information Education
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• v.9 no.3
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• pp.501-510
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• 2005

To facilitate interaction between home robot and humans, it's urgently needed to make in-depth research in Human-Robot Interaction(HRI). The purpose of this study was to examine how children interacted with a newly developed home robot named 'iRobi' in a bid to identify how the home robot affected their psychology and the effectiveness of learning through the home robot. Concerning the psychological effects of the home robot, the children became familiar with the robot, and found it possible to interact with it, and their initial anxiety was removed. As to its learning effect, the group that studied by using the home robot outperformed the others utilizing the other types of learning media (books, WBI)in attention, learning interest and academic achievement. Accordingly, home robot could serve as one of successful vehicles to expedite the psychological and educational interaction of children.

• The Journal of Korea Robotics Society
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• v.14 no.2
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• pp.81-86
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• 2019

Robots are used in various industrial sites, but traditional methods of operating a robot are limited at some kind of tasks. In order for a robot to accomplish a task, it is needed to find and solve accurate formula between a robot and environment and that is complicated work. Accordingly, reinforcement learning of robots is actively studied to overcome this difficulties. This study describes the process and results of learning and solving which applied reinforcement learning. The mission that the robot is going to learn is bottle flipping. Bottle flipping is an activity that involves throwing a plastic bottle in an attempt to land it upright on its bottom. Complexity of movement of liquid in the bottle when it thrown in the air, makes this task difficult to solve in traditional ways. Reinforcement learning process makes it easier. After 3-DOF robotic arm being instructed how to throwing the bottle, the robot find the better motion that make successful with the task. Two reward functions are designed and compared the result of learning. Finite difference method is used to obtain policy gradient. This paper focuses on the process of designing an efficient reward function to improve bottle flipping motion.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.57 no.2
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• pp.109-114
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• 2008

In this paper, a dynamic learning controller for robot manipulator is implemented using real-time operating system with capabilities of multitasking, intertask communication and synchronization, event-driven, priority-driven scheduling, real-time clock control, etc. The controller hardware system with VME bus and related devices is developed and applied to implement a dynamic learning control scheme for robot manipulator. Real-time performance of the proposed dynamic learning controller is tested and evaluated for tracking of the desired trajectory and compared with the conventional servo controller.

• The Journal of Korean Association of Computer Education
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• v.8 no.6
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• pp.23-32
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• 2005

Dolittle is a educational programming language that helps students learning principles and concepts of computer science with programming. Learning programming with robot improve learning achievements robot motivate to be interest with programming. However, Dolittle robot programming is a different from Dolittle programming in process of interpretation and execution mechanism. Therefore, students have virtually to learn two languages to control robot and it would reduce the worth of Dolittle as educational programming language. In order to solve this problem, we tried to Unify Dolittle and robot control language using parser that Dolittle program with turtle object convert robot program. But this try couldn't overcome completely this problem because attributes of turtle object is different from robot. In this research we unified Dolittle programming and Dolittle robot programming as a way of adding new robot object in dolittle standard object group. it would improve educational effect of learning programming with robot in Dolittle.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.944-947
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• 1996

Realization of autonomous agents that organize their own internal structure in order to behave adequately with respect to their goals and the world is the ultimate goal of AI and Robotics. Reinforcement learning gas recently been receiving increased attention as a method for robot learning with little or no a priori knowledge and higher capability of reactive and adaptive behaviors. In this paper, we present a method of reinforcement learning by which a multi robots learn to move to goal. The results of computer simulations are given.

• Journal of the Korean Society of Industry Convergence
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• v.18 no.4
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• pp.259-266
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• 2015

This study presents new scheme for various walking pattern of biped robot under the limitted enviroments. We show that the neural network is significantly more attractive intelligent controller design than previous traditional forms of control systems. A multilayer backpropagation neural network identification is simulated to obtain a learning control solution of biped robot. Once the neural network has learned, the other neural network control is designed for various trajectory tracking control with same learning-base. The main advantage of our scheme is that we do not require any knowledge about the system dynamic and nonlinear characteristic, and can therefore treat the robot as a black box. It is also shown that the neural network is a powerful control theory for various trajectory tracking control of biped robot with same learning-vase. That is, we do net change the control parameter for various trajectory tracking control. Simulation and experimental result show that the neural network is practically feasible and realizable for iterative learning control of biped robot.

• Journal of the Korea Society of Computer and Information
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• v.24 no.1
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• pp.247-255
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• 2019

In this paper, we propose the effect of project-based robot education program on the interest toward robots and the computational thinking of elementary school students. Software education is being actively carried out around the world in order to cultivate software talents in accordance with the 4th industrial revolution. As a result, the importance of robots in education has increased, and education using robots has been actively introduced. However, the activities of simply assembling and repeating robots in schools were not effective in enhancing elementary school students' interest toward robots and computational thinking. Therefore, it is necessary to overcome traditional teaching-learning methods and to develop robot education. So, in this study, the robot education program that introduces project-based learning was developed for improvement of interest toward robots and computational thinking of elementary school students. In order to verify the developed education program, 114 elementary six grade students were selected as research subjects and the traditional teaching-learning method and project-based learning were applied to the experimental and control group. As a result, project-based learning was more effective for elementary school students' interest toward robot than traditional teaching-learning method. In computing thinking, the experimental group showed a significant improvement, but there was no statistically significant difference in the post-test.