• Journal of the Korean Wood Science and Technology
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• v.24 no.2
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• pp.71-80
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• 1996

Handling the manufacured goods is the most cost-consuming task in material handling system in wooden furniture industries. Fully automated warehouse for cartoned goods of a furniture manufacturing company was analized to provide plant engineers and managers with some important informations on the utility and profitability of the automated storage and retrieval system(AS/RS). Process-oriented simulation modeling tech-niques were used to describe the system and to propose some alternatives to promote the efficiency of AS/RS. Simulation report could be inter-preted as follows: 1. Warehouse for the furniture goods must be designed in accordance with reliable material handling program and constructed with suitable equipments depending on the specification of packed products. 2. An excess of palletized products induced the indigestion and the inefficiency of AS/RS of the furniture industry and put this high-costly system into the shade. 3. Overcrowded AS/RS of the furniture factories could regain its material handling function by cutting down the deposit of products into the automated warehouse. For this purpose, reducing the regular output and direct delivering the outside products to the destination should be considered as the definite counterplan. And additional operation of conventional handy warehouse was also expected to improve the efficiency of main AS/RS.

• The Journal of Korea Robotics Society
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• v.16 no.2
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• pp.103-111
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• 2021

This study addresses a low-cost lidar sensor-based glass feature extraction method for an accurate map representation using statistical moments, i.e. the mean and variance. Since the low-cost lidar sensor produces range-only data without intensity and multi-echo data, there are some difficulties in detecting glass-like objects. In this study, a principle that an incidence angle of a ray emitted from the lidar with respect to a glass surface is close to zero degrees is concerned for glass detection. Besides, all sensor data are preprocessed and clustered, which is represented using statistical moments as glass feature candidates. Glass features are selected among the candidates according to several conditions based on the principle and geometric relation in the global coordinate system. The accumulated glass features are classified according to the distance, which is lastly represented on the map. Several experiments were conducted in glass environments. The results showed that the proposed method accurately extracted and represented glass windows using proper parameters. The parameters were empirically designed and carefully analyzed. In future work, we will implement and perform the conventional SLAM algorithms combined with our glass feature extraction method in glass environments.

• IEMEK Journal of Embedded Systems and Applications
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• v.3 no.2
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• pp.102-108
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• 2008

This paper describes a mapping and localization based on wave algorithm[11] and Kalman filter for effective SLAM. Each robot in a multi robot system has its own task such as building a map for its local position. By combining their data into a shared map, the robot scans actively seek to verify their relative locations. For simultaneous localization the algorithm which is well known as Kalman Filter (KF) is used. For modelling the robot position we wish to know three parameters (x, y coordinates and its orientation) which can be combined into a vector called a state variable vector. The Kalman Filter is a smart way to integrate measurement data into an estimate by recognizing that measurements are noisy and that sometimes they should ignored or have only a small effect on the state estimate. In addition to an estimate of the state variable vector, the algorithm provides an estimate of the state variable vector uncertainty i.e. how confident the estimate is, given the value for the amount of error in it.

• Journal of Drive and Control
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• v.19 no.4
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• pp.97-103
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• 2022

Low fertility rates and increased life expectancy further exacerbate the process of an aging society. This is also reflected in the gradual increase in the proportion of vulnerable groups in the social population. The demand for improved mobility among vulnerable groups such as the elderly or the disabled has greatly driven the growth of the electric-assisted mobility device market. However, such mobile devices generally require a certain operating capability, which limits the range of vulnerable groups who can use the device and increases the cost of learning. Therefore, autonomous driving technology needs to be introduced to make mobility easier for a wider range of vulnerable groups to meet their needs of work and leisure in different environments. This study uses mini PC Odyssey, Velodyne Lidar VLP-16, electronic device and Linux-based ROS program to realize the functions of working environment recognition, simultaneous localization, map generation and navigation of electric powered mobile devices for vulnerable groups. This autonomous driving mobility device is expected to be of great help to the vulnerable who lack the immediate response in dangerous situations.

• Journal of Sensor Science and Technology
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• v.32 no.2
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• pp.118-123
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• 2023

This study presents sensor system for autonomous mobile robot capable of floor-to-floor self-navigation. The robot was modified using the Turtlebot3 hardware platform and ROS2 (robot operating system 2). The robot utilized the Navigation2 package to estimate and calibrate the moving path acquiring a map with SLAM (simultaneous localization and mapping). For elevator boarding, ultrasonic sensor data and threshold distance are compared to determine whether the elevator door is open. The current floor information of the elevator is determined using image processing results of the ceiling-fixed camera capturing the elevator LCD (liquid crystal display)/LED (light emitting diode). To realize seamless communication at any spot in the building, the LoRa (long-range) communication module was installed on the self-navigating autonomous mobile robot to support the robot in deciding if the elevator door is open, when to get off the elevator, and how to reach at the destination.

• Structural Monitoring and Maintenance
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• v.2 no.3
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• pp.283-300
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• 2015

Visual condition inspections remain paramount to assessing the current deterioration status of a bridge and assigning remediation or maintenance tasks so as to ensure the ongoing serviceability of the structure. However, in recent years, there has been an increasing backlog of maintenance activities. Existing research reveals that this is attributable to the labour-intensive, subjective and disruptive nature of the current bridge inspection method. Current processes ultimately require lane closures, traffic guidance schemes and inspection equipment. This not only increases the whole-of-life costs of the bridge, but also increases the risk to the travelling public as issues affecting the structural integrity may go unaddressed. As a tool for bridge condition inspections, Unmanned Aerial Vehicles (UAVs) or, drones, offer considerable potential, allowing a bridge to be visually assessed without the need for inspectors to walk across the deck or utilise under-bridge inspection units. With current inspection processes placing additional strain on the existing bridge maintenance resources, the technology has the potential to significantly reduce the overall inspection costs and disruption caused to the travelling public. In addition to this, the use of automated aerial image capture enables engineers to better understand a situation through the 3D spatial context offered by UAV systems. However, the use of UAV for bridge inspection involves a number of critical issues to be resolved, including stability and accuracy of control, and safety to people. SLAM (Simultaneous Localisation and Mapping) is a technique that could be used by a UAV to build a map of the bridge underneath, while simultaneously determining its location on the constructed map. While there are considerable economic and risk-related benefits created through introducing entirely new ways of inspecting bridges and visualising information, there also remain hindrances to the wider deployment of UAVs. This study is to provide a context for use of UAVs for conducting visual bridge inspections, in addition to addressing the obstacles that are required to be overcome in order for the technology to be integrated into current practice.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.20 no.2
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• pp.96-104
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• 1984

This paper is on the prediction and response of the ship hull girder due to slamming of foreward flat bottom plate. The response with respect to foreward flat bottom is divided two kinds by estimating method. One is the estimation of impact forces by slamming, Another is the response of hull girder due to impact forces, that is, displacement, velocity, acceleration, etc. must calculate the values for considered ship hull girder. In this paper, therefore, was estimated only impact forces along ship ordinate of foreward. The analysis of data for estimation followed mainly papers of Ochi. These estimated data shall contribute for ship gull construction for basic optimum design. In particular, the estimated impact forces shall be given for the response of ship gull girder on the foreward flat bottom plate with characteristics of external forces.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.10
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• pp.1545-1550
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• 2022

In this research, a method for minimizing the replacement time of AMR (Autonomous Mobile Robot), which is used in various industrial groups such as logistics and manufacturing, was studied in the event of a LiDAR failure. In this regard, a general LiDAR exchange process was defined and a new exchange process based on the newly designed jig, which is mounted on the AMR, for the quick change of LiDAR was proposed. The experiment is conducted using commercialized AMR which was developed for application in the factory of an automobile manufacturing company. It was confirmed that LiDAR can be replaced and aligned within 24 minutes when the new exchange process is employed, which is about 76% or more shorter than the general LiDAR exchange process. As a result, we can minimize AMR downtime and overall process delays by applying the proposed process.

• Journal of Navigation and Port Research
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• v.31 no.3 s.119
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• pp.205-212
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• 2007

Due to the construction of Incheon Grand Bridge, there is driven a necessity for rearranging the function of Inner Port with the development of Outer South Port. In this paper, I'd like to simulate the port operation levels of Lock Gate in Inner Port with estimating the traffic volumes of 2011 and 2015, which will reveal the Demurrage Cost and the Accumulation Cost of Freight in Inner Port. Finally I will evaluate the economic movement effects of the container ship's calling from Inner port to South Port/Outer South Port from 2011 to 2015. The results are as followings ; (1) The average utilization of Lock Gates are reduced by $7\sim8$ percentage point. (2) The mean queueing value are saved by 25 percentage point. (3) The Demurrage Cost and the Accumulation Cost of Freight except Lock Gate charges and the Benefit of Routeing Reduction are saved about 800 million Won annually.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2005.06a
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• pp.1034-1039
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• 2005

SALM(Simultaneous localization and mapping) and AI(Artificial intelligence) have been active research areas in robotics for two decades. In particular, localization is one of the most important tasks in mobile robot research. Until now expensive sensors such as a laser sensor have been used for mobile robot localization. Currently, the proliferation of RFID technology is advancing rapidly, while RFID reader devices, antennas and tags are becoming increasingly smaller and cheaper. So, in this paper, the smart floor using passive RFID tags is proposed and, passive RFID tags are mainly used for identifying location of the mobile robot in the smart floor. We discuss a number of challenges related to this approach, such as tag distribution (density and structure), typing and clustering. In the smart floor using RFID tags, the localization error results from the sensing area of the RFID reader, because the reader just knows whether the tag is in the sensing range of the sensor and, until now, there is no study to estimate the heading of mobile robot using RFID tags. So, in this paper, two algorithms are suggested to. The Markov localization method is used to reduce the location(X,Y) error and the Kalman Filter method is used to estimate the heading($\theta$) of mobile robot. The algorithms which are based on Markov localization require high computing power, so we suggest fast Markov localization algorithm. Finally we applied these algorithms our personal robot CMR-P3. And we show the possibility of our probability approach using the cheap sensors such as odometers and RFID tags for mobile robot localization in the smart floor