• Journal of Institute of Control, Robotics and Systems
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• v.18 no.3
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• pp.181-187
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• 2012

Horse riding is widely recognized as a valuable form of education, exercise and therapy. But, the injuries observed in horse riding range from very minor injuries to fatalities. In order to reduce these injuries, the effective horseback riding simulator is required. In this paper, we proposed the implementation method of horse gait and riding aids for horseback riding robot simulator HRB-1. For implementation of horse gait to robot simulator, we gathered and modified real motion data of horse. We obtained two main frequencies of each gait by frequency analysis, and then simple sinusoidal functions are acquired by genetic algorithm. In addition, we developed riding aids system including hands, leg, and seat aids. With the help of a developed robotic system, beginners can learn the skill of real horse riding without the risk of injury.

• The KIPS Transactions:PartC
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• v.10C no.4
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• pp.509-518
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• 2003

A web robot is a program that downloads and stores web pages. Implementation issues for developing web robots have been studied widely and various web statistics are reported in the literature. First, this paper describes the overall architecture of our robot and implementation decisions on several important issues. Second, we show empirical statistics on approximately 74 million Korean web pages. Third, we monitored 1,424 Korean web sites to observe the changes of web pages. We identify what factors of web pages could affect the changes. The factors may be used for the selection of web pages to be updated incrementally.

• Journal of IKEEE
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• v.27 no.4
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• pp.610-616
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• 2023

In this paper, we implement an unmanned delivery robot system with Robot Operating System(ROS)-based mobile manipulator, and introduce the technologies employed for the system implementation. The robot consists of a mobile robot capable of autonomous navigation inside the building using an elevator and a Selective Compliance Assembly Robot Arm(SCARA)-Type manipulator equipped with a vacuum pump. The robot can determines the position and orientation for picking up a package through image segmentation and corner detection using the camera on the manipulator. The proposed system has a user interface implemented to check the delivery status and determine the real-time location of the robot through a web server linked to the application and ROS, and recognizes the shipment and address at the delivery station through You Only Look Once(YOLO) and Optical Character Recognition(OCR). The effectiveness of the system is validated through delivery experiments conducted within a 4-story building.

• Journal of the Korean Society of Industry Convergence
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• v.20 no.3
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• pp.245-256
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• 2017

In this study, we describe a new approach to real-time implementation of working path control for the forging and casting manufacturing process by vertical type articulated robot system. The proposed control scheme is simple in structure, fast in computation, and useful for real-time control of factory automation based on robot system. Moreover, this scheme does not require any accurate parameter information, nor values of the uncertain parameters and payload variations. Reliability of the proposed controller is proved by simulation and experimental results for robot manipulator consisting of arm with six degrees of freedom under the variation of payloads and tracking trajectories in Cartesian space and joint space. The vertical type articulated robot manipulator with six axes made in SMEC Co., Ltd. has been used for real-time implementation test to illustrate the enhanced working path control performance for unmanned automation of the forging and casting manufacturing process.

• Journal of the Korean Society of Industry Convergence
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• v.21 no.1
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• pp.17-27
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• 2018

We propose a new approach to control a biped robot motion based on iterative learning of voice command for the implementation of smart factory. The real-time processing of speech signal is very important for high-speed and precise automatic voice recognition technology. Recently, voice recognition is being used for intelligent robot control, artificial life, wireless communication and IoT application. In order to extract valuable information from the speech signal, make decisions on the process, and obtain results, the data needs to be manipulated and analyzed. Basic method used for extracting the features of the voice signal is to find the Mel frequency cepstral coefficients. Mel-frequency cepstral coefficients are the coefficients that collectively represent the short-term power spectrum of a sound, based on a linear cosine transform of a log power spectrum on a nonlinear mel scale of frequency. The reliability of voice command to control of the biped robot's motion is illustrated by computer simulation and experiment for biped walking robot with 24 joint.

• Journal of the Korean Society of Industry Convergence
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• v.18 no.4
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• pp.250-258
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• 2015

In this research, we proposed a new approach to implement the real-time motion control of biped robot based on voice command for unmanned FA. Voice is one of convenient methods to communicate between human and robots. To command a lot of robot task by voice, voice of the same number have to be able to be recognition voice is, the higher the time of recognition is. In this paper, a practical voice recognition system which can recognition a lot of task commands is proposed. The proposed system consists of a general purpose microprocessor and a useful voice recognition processor which can recognize a limited number of voice patterns. Given biped robots, each robot task is, classified and organized such that the number of robot tasks under each directory is net more than the maximum recognition number of the voice recognition processor so that robot tasks under each directory can be distinguished by the voice recognition command. By simulation and experiment, it was illustrated the reliability of voice recognition rates for application of the manufacturing process.

• Journal of Institute of Control, Robotics and Systems
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• v.12 no.5
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• pp.450-456
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• 2006

Monte Carlo localization is known to be one of the most reliable methods for pose estimation of a mobile robot. Although MCL is capable of estimating the robot pose even for a completely unknown initial pose in the known environment, it takes considerable time to give an initial pose estimate because the number of random samples is usually very large especially for a large-scale environment. For practical implementation of MCL, therefore, a reduction in sample size is desirable. This paper presents a novel approach to reducing the number of samples used in the particle filter for efficient implementation of MCL. To this end, the topological information generated through the thinning technique, which is commonly used in image processing, is employed. The global topological map is first created from the given grid map for the environment. The robot then scans the local environment using a laser rangefinder and generates a local topological map. The robot then navigates only on this local topological edge, which is likely to be similar to the one obtained off-line from the given grid map. Random samples are drawn near the topological edge instead of being taken with uniform distribution all over the environment, since the robot traverses along the edge. Experimental results using the proposed method show that the number of samples can be reduced considerably, and the time required for robot pose estimation can also be substantially decreased without adverse effects on the performance of MCL.

• Korean Journal of Artificial Intelligence
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• v.11 no.4
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• pp.15-20
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• 2023

Machine learning is comprised of supervised learning, unsupervised learning and reinforcement learning as the type of data and processing mechanism. In this paper, as input and output are unclear and it is difficult to apply the concrete modeling mathematically, reinforcement learning method are applied for crawling robot in this paper. Especially, Q-Learning is the most effective learning technique in model free reinforcement learning. This paper presents a method to implement a crawling robot that is operated by finding the most optimal crawling method through trial and error in a dynamic environment using a Q-learning algorithm. The goal is to perform reinforcement learning to find the optimal two motor angle for the best performance, and finally to maintain the most mature and stable motion about EV3 Crawling robot. In this paper, for the production of the crawling robot, it was produced using Lego Mindstorms with two motors, an ultrasonic sensor, a brick and switches, and EV3 Classroom SW are used for this implementation. By repeating 3 times learning, total 60 data are acquired, and two motor angles vs. crawling distance graph are plotted for the more understanding. Applying the Q-learning reinforcement learning algorithm, it was confirmed that the crawling robot found the optimal motor angle and operated with trained learning, and learn to know the direction for the future research.

• IEMEK Journal of Embedded Systems and Applications
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• v.13 no.1
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• pp.33-43
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• 2018

In this paper, we describe an sound tracking mobile robot suitable for areas where GPS is not available. Sound sensors are attached to four sides of the robot in order to locate the person in a danger, and the robot is supposed to move to the yelling person. The traveling distance of the mobile robot is calculated by the encoder attached to the wheel of the mobile robot. The moving direction of the mobile robot is measured by a gyro sensor on the robot. When the person in danger pushes a button of the mobile robot, the mobile robot transmits the trajectory data to a designated server.

• Proceedings of the KIEE Conference
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• 2001.11c
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• pp.107-110
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• 2001

Recently, there are lots of concerning on robot agent system working for itself with the trends of the research of bio-mimetic system and intelligent robot. In this paper, a virtual 3D interface system is proposed based on Internet for remote controlling and monitoring of mobile robot. The proposed system is constructed as manager-agent model. A worker can order the robot agent move to a new position by clicking the destination on virtual space of 3D graphic interface in manager. Then the robot agent move to the position automatically with avoiding collision by using range finding and autonomous control algorithm. The proposed robot agent system lets us control the mobile robot remotely located more conveniently.