• Journal of Institute of Control, Robotics and Systems
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• v.7 no.4
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• pp.326-333
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• 2001

This paper focuses on a method to connect mobile devices such as mobile robot. Automated Guided Vehicle (AGV) and Unmanned Container Transporter(UCT) to a fieldbus. In this paper, the IEEE 802.11 wireless LAN is used to extend a Profibus network for the mobile devices. In order to integrate these two networks, a gateway is developed using two threads and an internal buffer. Furthermore, a polling algorithm is applied at the gateway in order to satisfy real-time requirements on data communication, Finally, the performance measures such as data latency and throughput are experimentally evaluated on a wirelessly-extended Profibus network. The results shows the feasibility of the wireless extension of Profilbus for various mobile device.

• International conference on construction engineering and project management
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• 2024.07a
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• pp.731-737
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• 2024

The accident rate in the South Korean construction industry has increased by 50% over the past ten years, reaching seven times the average growth rate of the entire industry. However, the number of management personnel at construction sites is decreasing, making it increasingly difficult to establish a safety monitoring system through professional personnel. This study aims to develop an intelligent control system to address the problem of insufficient management personnel and support the establishment of a continuous safety monitoring system. This system consists of a mobile information collection robot (S-BOT) and an intelligent algorithm. The visual information collected by S-BOT can be analyzed in real-time using computer vision-based intelligent algorithms to detect unsafe situations. The results of this study will contribute to preventing unnecessary social and economic losses by maximizing safety management efficiency and supporting timely decision-making through the sharing of information provided by the intelligent control system.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.2568-2574
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• 2005

Control architecture of the action based robot engineering can be divided into two types of deliberate type - and reactive type- controller. Typical deliberate type, slow in reaction speed, is well suited for the realization of the higher intelligence with its capability to forecast on the basis of environmental model according to time flow, while reactive type is suitable for the lower intelligence as it fits to the realization of speedy reactive action by inputting the sensor without a complete environmental model. Looking at the environments in the application areas in which robots are actually used, we can see that they have been mostly covered by the uncertain and unknown dynamic changes depending on time and place, the previously known knowledge being existed though. It may cause, therefore, any deterioration of the robot performance as well as further happen such cases as the robots can not carry out their desired performances, when any one of these two types is solely engaged. Accordingly this paper aims at suggesting Goal-oriented Geometric Model(GGM) Based Intelligent System Architecture which leads the actions of the robots to perform their jobs under variously changing environment and applying the suggested system structure to the navigation issues of the robots. When the robots do perform navigation in human life changing in a various manner with time, they can appropriately respond to the changing environment by doing the action with the recognition of the state. Extending this concept to cover the highest hierarchy without sticking only to the actions of the robots can lead us to apply to the algorithm to perform various small jobs required for the carrying-out of a large main job.

• Journal of the Korean Institute of Intelligent Systems
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• v.16 no.5
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• pp.587-593
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• 2006

This paper is to present gesture analysis for human-robot interaction. Understanding human emotions through gesture is one of the necessary skills for the computers to interact intelligently with their human counterparts. Gesture analysis is consisted of several processes such as detecting of hand, extracting feature, and recognizing emotions. For efficient operation we used recognizing a gesture with HMM(Hidden Markov Model). We constructed a large gesture database, with which we verified our method. As a result, our method is successfully included and operated in a mobile system.

• Journal of the Korean Institute of Intelligent Systems
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• v.17 no.2
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• pp.208-213
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• 2007

As recent research on home service robot has been performed actively in these days. It becomes very important for the robot to react upon voice and sound source, and then tracks an object position in dynamic environment like a home. When people choose a path for finding a destination of objects, in case of sound, they track a direction of the sound source. Or in case as a position of the object be girded with a point on map, people track the position according to absolute orientation of the present position and the sound source position. In this paper, In this manner we had views on what people decide own direction when they react one's voice or go some directions. We suggest a algorithm that intelligent mobile robots on which we installed a sound source tracking board and a digital magnetic compass board go some object's positions by the direction of sound source and absolute orientation.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.8 no.5
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• pp.73-80
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• 2008

The recent trend in home network system includes intelligent home environments that remote monitoring and control service is achieved without restrictions by device types, time, and place. Also the use of a vacuum robot in homes is gradually generalized on account of the convenience of the use. In this paper, we proposed and realized new home-monitoring system with the employment of an self-movement robot as one trial for realizing an intelligent home under home network environment. The proposed system can freely monitor every where in home, because the system effectively overcame the surveillance limitations of the existing monitoring system by attaching a Wireless Router and WebCam to a commercial vacuum robot. The outdoor users of this system can readily monitor any place which they want to supervise by controlling a vacuum robot with mobile telecommunication devices such as PDA. The wireless router installed with Linux operation system "OpenWrt" made it possible for the system users to transmit images and to control a vacuum robot with RS-232 communication.

• Journal of the Korean Institute of Intelligent Systems
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• v.17 no.5
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• pp.591-597
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• 2007

In swarm robot systems, each robot must behaves by itself according to the its states and environments, and if necessary, must cooperates with other robots in order to carry out a given task. Therefore it is essential that each robot has both learning and evolution ability to adapt the dynamic environments. In this paper, the new polygon based Q-learning algorithm and distributed genetic algorithms are proposed for behavior learning and evolution of collective autonomous mobile robots. And by distributed genetic algorithm exchanging the chromosome acquired under different environments by communication each robot can improve its behavior ability Specially, in order to improve the performance of evolution, selective crossover using the characteristic of reinforcement learning is adopted in this paper. we verify the effectiveness of the proposed method by applying it to cooperative search problem.

• Journal of the Korean Institute of Intelligent Systems
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• v.12 no.1
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• pp.19-26
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• 2002

There are some difficulties to construct a sensory-motor controller for an autonomous mobile robot such as coordinating the mechanics and control system parts of the robot, and managing interaction with external environments. In previous research, we evolve the CAM-Brain, neural networks based on cellular automata, to control an autonomous mobile robot. In this paper, we propose the method of combining multi-modules evolved to do simple behavior in order to making more sophisticated behaviors because the controller composed of one neural network module is difficult to make complex behaviors. In experimental results, we can get the controller adapting to more complex environments by combining CAM-Brain modules evolved to do simple behavior by rule-based approach.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.1190-1195
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• 2003

In this paper, it is shown how a robot with n passive trailers can be controlled in backward direction. When driving backward direction, a kinematic model of the system is represented highly nonlinear equations. The problem is formulated as a trajectory following problem, rather than control of independent generalized coordinates. Also, the state and input saturation problems are formulated as a trajectory generation problem. The trajectory is traced by a rear hinge point of the last trailer, and reference trajectories include line segments, circular shapes and rectangular turns. Experimental verifications were carried out with the PSR-2(public service robot $2^{nd}$ version) with three passive trailers. Experimental result showed that the backward motion control can be successfully carried out using the proposed control scheme.

• Journal of Institute of Control, Robotics and Systems
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• v.17 no.2
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• pp.116-124
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• 2011

A service robot can identify its own position relative to landmarks, the locations of which are known in advance. The main contribution of this research is that it gives various ways of making the self-localizing error smaller by referring to special landmarks which are developed as high gain reflection material and coded array associations. In this paper, the authors propose a set of indices to evaluate the accuracy of self-localizing methods using the selective reflection landmark and infrared projector, and the indices are derived from the sensitivity enhancement using 3D distortion calibration of camera. And then, the accurarcy of self-localizing a mobile robot with landmarks based on the indices is evaluated, and a rational way to minimize to reduce the computational cost of selecting the best self-localizing method. The simulation results show a high accuracy and a good performance.