• Journal of Institute of Control, Robotics and Systems
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• v.20 no.9
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• pp.922-929
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• 2014

Wind turbines are in the limelight in the alternative energy industry. However, they face frequent and various problems during operation. We focused on the supervising of the blades of a wind turbine. In this paper, we present the design of a maintenance robot that takes the size of wind turbine blades into consideration, so the general form of the robot is a square with four wires fixed to its vertices and to the nacelle. After the robot is placed near the nacelle, it moves along the blades. We also designed an attitude control algorithm for the robot to maintain its balance. Our control algorithm for the robot consists of roll and pitch attitude controllers and a height controller. Each controller was designed independently and then superposed together. We used simulations to verify our control algorithm.

• Journal of the Korea Society for Simulation
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• v.17 no.4
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• pp.249-257
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• 2008

This paper shows the Applied Q-learning Algorithm which supports selecting the waiting position of a robot and the part serviced next in the Flexible Manufacturing Cell (FMC) that consists of one robot and various types of facilities. To verify the performance of the suggested algorithm, we design the general FMC made up of single transfer robot and multiple machines with a simulation method, and then compare the output with other control methods. As a result of the analysis, the algorithm we use improve the average processing time and total throughputs as well by increasing robot utilization, reversely, by decreasing robot waiting time. Furthermore, because of ease of use compared with other complex ways and its adoptability to real world, we expect that this method contribute to advance total FMC efficiency as well.

• Journal of IKEEE
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• v.25 no.2
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• pp.337-343
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• 2021

Deep reinforcement learning is an artificial intelligence algorithm that enables learners to select optimal behavior based on raw and, high-dimensional input data. A lot of research using this is being conducted to create an optimal movement path of a mobile robot in an environment in which obstacles exist. In this paper, we selected the Dueling Double DQN (D3QN) algorithm that uses the prioritized experience replay to create the moving path of mobile robot from the image of the complex surrounding environment. The virtual environment is implemented using Webots, a robot simulator, and through simulation, it is confirmed that the mobile robot grasped the position of the obstacle in real time and avoided it to reach the destination.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2002.04a
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• pp.561-566
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• 2002

This paper proposed trajectory tracking control of Mobile Robot. Trajectory tracking control scheme are Real coding Genetic-Algorithm and Back-propergation Algorithm. Control scheme ability experience proposed simulation.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2001.10a
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• pp.146-151
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• 2001

This paper proposed trajectory tracking control of Mobile Robot. Trajectory tracking control scheme are Real coding Genetic-Algorithm and Back-propergation Algorithm. Control scheme ability experience proposed simulation.

• Proceedings of the KIEE Conference
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• 1999.07g
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• pp.3095-3097
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• 1999

A New path planning using modified DT(distance transform) algorithm for a remote mobile robot is proposed. The weakness of DT algorithm is that the generated path is not the best path of all possible paths. Modified DT algorithm proposed can compensate for the weakness of DT algorithm, but the operating time of the proposed is longer than that of DT algorithm.

• The Journal of Korea Robotics Society
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• v.3 no.3
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• pp.237-244
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• 2008

Nowadays, research on human-robot interaction has been getting increasing attention. In the research field of human-robot interaction, speech signal processing in particular is the source of much interest. In this paper, we report a speaker localization system with six microphones for a humanoid robot called MAHRU from KIST and propose a time delay of arrival (TDOA)-based feature matrix with its algorithm based on the minimum sum of absolute errors (MSAE) for sound source localization. The TDOA-based feature matrix is defined as a simple database matrix calculated from pairs of microphones installed on a humanoid robot. The proposed method, using the TDOA-based feature matrix and its algorithm based on MSAE, effortlessly localizes a sound source without any requirement for calculating approximate nonlinear equations. To verify the solid performance of our speaker localization system for a humanoid robot, we present various experimental results for the speech sources at all directions within 5 m distance and the height divided into three parts.

• IEMEK Journal of Embedded Systems and Applications
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• v.3 no.2
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• pp.66-73
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• 2008

The pipes have been laid underground while the industry is developing. We have to take maintenance procedure when the pipes are cracked or ruptured. It is very difficult jop to check pipe's crack because the pipes are narrow and laid underground. Using in-pipe robot, we can check the conditions of inner section of pipes, therefore, we designed a crawler type robot to search cracked pipe. In this paper, we have made a special focus on the control of the robot using differential drive algorithm to move in curved section of pipes. The detailed design of the robot with experimental result show the effectiveness of the robot in pipe maintenance.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.256-261
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• 2005

In this research, we propose a path-planning algorithm for an autonomous mobile robot using geographical information, under the condition that the robot moves in unknown environment. All image inputted by camera at every sampling time are analyzed and geographical elements are recognized, and the geographical information is embedded in environmental map. The geographical information was transformed into 1-dimensional evaluation value that expressed the difficulty of movement for the robot. The robot goes toward the goal searching for path that minimizes the evaluation value at every sampling time. Then, the path is updated by integrating the exploited information and the prediction on unexploited environment. We used a sensor fusion method for improving the mobile robot dead reckoning accuracy. The experiment results that confirm the effectiveness of the proposed algorithm on the robot's reaching the goal successfully using geographical information are presented.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.130.1-130
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• 2001

In this paper, a motion control algorithm is developed using a fuzzy control and the optimization of performance function, which makes a robot arm avoid an unexpected obstacle when the end-effector of the robot arm is moving to the goal position. During the motion, if there exists no obstacle, the end-effector of the robot arm moves along the pre-defined path. But if there exists an obstacle and close to the robot arm, the fuzzy motion controller is activated to adjust the path of the end-effector of the robot arm. Then, the robot arm takes the optimal posture for collision avoidance with the obstacle. To show the feasibility of the developed algorithm, numerical simulations are carried out with changing both the positions and sizes of obstacles. It was concluded ...