• Journal of Institute of Control, Robotics and Systems
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• v.21 no.6
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• pp.565-570
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• 2015

Supervised machine learning has become popular in discovering context descriptions from sensor data. However, collecting a large amount of labeled training data in order to guarantee good performance requires a great deal of expense and time. For this reason, semi-supervised learning has recently been developed due to its superior performance despite using only a small number of labeled data. In the existing semi-supervised learning algorithms, unlabeled data are used to build a graph Laplacian in order to represent an intrinsic data geometry. In this paper, we represent the unlabeled data as the spatial-temporal dataset by considering smoothly moving objects over time and space. The developed algorithm is evaluated for position estimation of a smartphone-based robot. In comparison with other state-of-art semi-supervised learning, our algorithm performs more accurate location estimates.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.48 no.2
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• pp.1-8
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• 2011

An underwater robot S/W framework consists of various sub-modules such as sensory data processing module, thruster control module, cognition module and behavior control module. Performance of a robot is determined by not only the efficiency of algorithms used but also effectiveness of their implementations. One most important factor of the effective implementation is the efficiency of data sharing module, as it transmits signals and data between the sub-modules and thus is directly related to the cycles of sensing and control The ideal data sharing module enables immediate access to any data source irrespective of system configurations. In reality, however, there are lots of obstacles including limitation of processing capacity of source modules, delay over network, and scheduling latency of operating systems. The paper proposes a new data sharing architecture and programming models to effectively handle such obstacles in implementation of underwater S/W framework on a small scale distributed computing system.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10a
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• pp.1042-1046
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• 1993

This paper describes a control scheme for a robot manipulator system which uses visual information to position and orientate the end-effector. In this scheme, the position and orientation of the target workpiece with respect to the base frame of the robot are assumed to be unknown, but the desired relative position and orientation of the end-effector to the target workpiece are given in advance. The control scheme directly integrates visual data into the servoing process without subdividing the process into determination of the position and orientation of the workpiece and inverse kinematics calculation. A neural network system is used for determining the change in joint angles required in order to achieve the desired position and orientation. The proposed system can be control the robot so that it approach the desired position and orientation from arbitrary initial ones. Simulation for the robot manipulator with six degrees of freedom will be done. The validity and the effectiveness of the proposed control scheme will be verified by computer simulations.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2003.10a
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• pp.320-324
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• 2003

Recently, Virtual reality parts is applied in various fields of industry. In this paper we got under control motion of reality robot from interface manipulation in the virtual world. This paper created virtual robot using of 3D Graphic Tool. And we reappeared a similar image with reality robot put on texture the use of components of Direct 3D Graphic. Also a reality robot and a virtual robot is controlled by joystick. The developed robot consists of robot controller with vision system and host PC program. The robot and camera can move with 2 degree of freedom by independent remote controlling a user friendly designed joystick. An environment is recognized by the vision system and ultra sonic sensors. The visual mage and command data translated through 900MHz and 447MHz RF controller, respectively. If user send robot control command the use of simulator to control the reality robot, the transmitter/recever got under control until 500miter outdoor at the rate of 4800bps a second in Hlaf Duplex method via radio frequency module useing 447MHz frequency.

• Journal of Sensor Science and Technology
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• v.33 no.1
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• pp.18-23
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• 2024

Humanoid robots, designed to interact in human environments, require stable mobility to ensure safety. When a humanoid robot falls, it causes damage, breakdown, and potential harm to the robot. Therefore, fall detection is critical to preventing the robot from falling. Prevention of falling of a humanoid robot requires an operator controlling a crane. For efficient and safe walking control experiments, a system that can replace a crane operator is needed. To replace such a crane operator, it is essential to detect the falling conditions of humanoid robots. In this study, we propose falling detection methods using Convolution Neural Network (CNN) model. The image data of a humanoid robot are collected from various angles and environments. A large amount of data is collected by dividing video data into frames per second, and data augmentation techniques are used. The effectiveness of the proposed CNN model is verified by the experiments with the humanoid robot MAX-E1.

• Journal of Advanced Marine Engineering and Technology
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• v.17 no.3
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• pp.60-69
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• 1993

The speed control associated with dc servo motors for direct-drive applications of mobile robot is considered in this study. Robot is moved by power wheeled steering of two dc servo motors mounted to it. In order to cooperate with micro-computer and to achieve the high-performance operation of dc servo motor, speed control system is composed of a digital Phase Locked Loop and H-type drive circuit. And the motor is driven by Pulse Width Modulations. In controlling PWM, it is modified to compose of H-type drive circuit with feedback diodes and switching transistor and design of control sequence so that it may show linear characteristics. As a result, speed characteristics of motor showed linear features. In order to get data on design of PLL control system, the parameters of 80[W[ motor & robot device is measured by simple software control. The PLL speed control system is schemed and designed by leaner drive circuit and measured parameters. A complete speed control system applied to 80[W] dc servo motor showed good linearity, stability and high response. Also, it is verified that the PLL speed control system has good compatibility as a mobile robot driver.

• Journal of Institute of Control, Robotics and Systems
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• v.17 no.12
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• pp.1219-1226
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• 2011

This paper proposes a novel approach to building an occupancy grid map using sonar data. It is very important for a mobile robot to recognize and construct its surrounding environments for navigation. However, the grid map constructed by ultrasonic sensors cannot represent a realistic shape of given environments due to incorrect sonar measurements caused by specular reflection. To overcome this problem, we propose an advanced sonar sensor model which consists of distance and shape factors used to determine the reliability of sensor data. Through this sensor model, a robot can build a high-quality grid map. The proposed method was verified by various experiments and showed that the robot could build an accurate map with sonar data in various indoor environments.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.61.6-61
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• 2001

In this paper, we propose a method to analyze measured data from 3D Laser tracking system and to enhance precision performance of a Cartesian robot. Position data are obtained over the stroke of a Cartesian robot with variable speeds. The measured data is need to model errors with several different sources. In general, the error is a function of part accuracy, assembly accuracy, temperature, and control etc. After the sources of errors are identified, they are used to enhance precision performance. The proposed method is more complete than others because we use very accurate 3D Laser tracking system.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.10a
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• pp.566-569
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• 2022

In this paper, the algorithm was developed to recognize hand golve gesture and implemented a system to remotely control the robot. The system consists of a camera and a controller that controls robot motion by hand position gesture. The camera recognizes the specific color of the glove and outputs the recognized range and position by including the color area of the glove. We recognize the velocity vector of robot motion and control the robot by the output data of the position and the detected rectangle. Through the several experiments, it was confirmed that the robot motion control was successfully performed.

• Journal of Institute of Control, Robotics and Systems
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• v.10 no.3
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• pp.273-279
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• 2004

This research is concerned with the development of an Internet-based robot system, which is insensitive to the unpredictable internet time delay. For this purpose, a simple mobile robot system that moves in response to the user s direct control on the internet has been developed. The time delay in data transmission is an important problem for the construction of this kind of system. Therefore, the PPS (Position Prediction Simulator) is suggested and implemented to compensate for the time delay problem of the internet. The simulation and experimental results show that the distance error can be reduced using the developed PPS.