• 한국통신학회논문지
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• 제16권5호
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• pp.451-457
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• 1991

이원 트래픽의 호손률 계산을 위한 네가지의 알고리즘이 착시되고 승제 계산의 복잡도, 소요 메모리, 계산가능한 채널수등이 서로 비교된다. 처음 세가지의 알고리즘은 오버플로우나 언더플로우 문제때문에 계산 채널수의 상한선이 제한되는 반면에 새로 착시한 알고리즘은 이러한 문제점을 해결할 수 있어 1,0000 채널 이상의 대용량 시스템의 호손율계산도 가능하다. 이러한 알고리즘을 이용하여 1 스롯호와 6스롯호인 경우에 대하여 각 호손율을 계산하여 검토해 보며, 또한 SLAM II의 시뮬레이션을 통하여 계산된 결과와 비교하여 본다.

• 한국생산제조학회지
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• 제20권2호
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• pp.133-138
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• 2011

RFID system can be used to improve object recognition, map building and localization for robot area. A novel method of indoor navigation system for a mobile robot is proposed using RFID technology. The mobile robot With a RFID reader and antenna is able to find what obstacles are located where in circumstance and can build the map similar to indoor circumstance by combining RFID information and distance data obtained from sensors. Using the map obtained, the mobile robot can avoid obstacles and finally reach the desired goal by $A^*$ algorithm. 3D map which has the advantage of robot navigation and manipulation is able to be built using z dimension of products. The proposed robot navigation system is proved to apply for SLAM and path planning in unknown circumstance through numerous experiments.

• 산업경영시스템학회지
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• 제20권43호
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• pp.287-297
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• 1997

This research is concerned with operation control problem for an automated manufacturing system which consists of two machine centers and a single automatic guided vehicle. The objective is to develop and evaluate heuristic scheduling procedures that minimize maximum completion time to be included travel time of AGV. A new heuristic algorithm is proposed and a numerical example illustrates the proposed algorithm. The heuristic algorithm is implemented for various cases by SLAM II. The results show that the proposed algorithm provides better solutions than the previous algorithms.

• 산업공학
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• 제14권2호
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• pp.148-157
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• 2001

This paper considers a network restoration algorithm for all-optical WDM networks. As the increasing traffic and transmission speed, any failure on the networks will lead to loss of huge data and disruption of the services. Therefore, a network restoration algorithm is necessary for the high-speed all-optical networks. This paper suggests a distributed restoration algorithm for line or channel level failures under the dynamic rerouting. For the algorithm, some measures for performance evaluation are explicitly derived and simulation studies are exploited to evaluate its usability by SLAM(Simulation Language for Alternative Modeling) II.

• 대한임베디드공학회논문지
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• 제16권3호
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• pp.107-111
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• 2021

A 3D point cloud map is an essential elements in various fields, including precise autonomous navigation system. However, generating a 3D point cloud map using a single sensor has limitations due to the price of expensive sensor. In order to solve this problem, we propose a precise 3D mapping system using low-cost sensor fusion. Generating a point cloud map requires the process of estimating the current position and attitude, and describing the surrounding environment. In this paper, we utilized a commercial visual-inertial odometry sensor to estimate the current position and attitude states. Based on the state value, the 2D LiDAR measurement values describe the surrounding environment to create a point cloud map. To analyze the performance of the proposed algorithm, we compared the performance of the proposed algorithm and the 3D LiDAR-based SLAM (simultaneous localization and mapping) algorithm. As a result, it was confirmed that a precise 3D point cloud map can be generated with the low-cost sensor fusion system proposed in this paper.

• 한국경영과학회지
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• 제19권2호
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• pp.107-118
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• 1994

This research is concerned with production scheduling for a flexible manufacturing cell which consists of two machine centers with unlimited buffer space and a single automatic guided vehicle. The objective is to develop and evaluate heuristic scheduling procedures that minimize maximum completion time. A numerical example illustrates the proposed algorithm. The heuristic algorithm is implemented for various cases by SLAM II. The results show that the proposed algorithm provides better solutions than Johnson's. It also gets good solutions to minimize mean flowtime.

• 한국정밀공학회지
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• 제33권2호
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• pp.129-138
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• 2016

This paper presents a natural corners-based SLAM (Simultaneous Localization and Mapping) with a robust data association algorithm in a real unknown environment. Corners are extracted from raw laser sensor data, which are chosen as landmarks for correcting the pose of mobile robot and building the map. In the proposed data association method, the extracted corners in every step are separated into several groups with small numbers of corners. In each group, local best matching vector between new corners and stored ones is found by joint compatibility, while nearest feature for every new corner is checked by individual compatibility. All these groups with local best matching vector and nearest feature candidate of each new corner are combined by partial compatibility with linear matching time. Finally, SLAM experiment results in an indoor environment based on the extracted corners show good robustness and low computation complexity of the proposed algorithms in comparison with existing methods.

• 한국통신학회논문지
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• 제22권4호
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• pp.842-854
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• 1997

본 연구에서는 멀티미디어 데이터의 동기 셀 손실율을 줄이기 위해 개선된 Dual Leaky-Bucket 알고리즘을 제안하였다. 기존의 DLB 알고리즘은 동기셀에 대하여 어떠한 지원도 하지 않았으나 제안 알고리즘은 동기셀에 높은 우선순위를 부여한다. 본 연구에서는 동기셀의 손실율을 줄이기 위해 동기셀 검출기를 사용하였다. 동기셀 검출기는 수신셀을 검사하여 동기셀이며 1단계 Leaky-Bucket을 거치지 않고 바로 2단게 Leaky-Bucket으로 전달하게 된다. 이것은 동기셀에 우선순위를 주는 것과 유사한 효과를 보인다. On/Off와 Two-state MMPP로 모델링한 Audio와 Video 트래픽을 SLAM II 시뮬레이션 팩키지를 통해 시뮬레이션 한 결과 제안 알고리즘이 기존 알고리즘에 비하여 낮은 동기셀 손실율을 얻을 수 있음을 보였다. 멀티미디어 동기화를 위하여 개선된 DLB 알고리즘은 높은 우선순위를 요구하는 다른 임의의 셀에 대해서도 확장되어 적용할 수 있다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제17권5호
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• pp.1339-1355
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• 2023

Localization is a hot research spot for many areas, especially in the mobile robot field. Due to the weak signal of the global positioning system (GPS), the alternative schemes in an indoor environment include wireless signal transmitting and receiving solutions, laser rangefinder to build a map followed by a re-localization stage and visual positioning methods, etc. Among all wireless signal positioning techniques, Wi-Fi is the most common one. Wi-Fi access points are installed in most indoor areas of human activities, and smart devices equipped with Wi-Fi modules can be seen everywhere. However, the localization of a mobile robot using a Wi-Fi scheme usually lacks orientation information. Besides, the distance error is large because of indoor signal interference. Another research direction that mainly refers to laser sensors is to actively detect the environment and achieve positioning. An occupancy grid map is built by using the simultaneous localization and mapping (SLAM) method when the mobile robot enters the indoor environment for the first time. When the robot enters the environment again, it can localize itself according to the known map. Nevertheless, this scheme only works effectively based on the prerequisite that those areas have salient geometrical features. If the areas have similar scanning structures, such as a long corridor or similar rooms, the traditional methods always fail. To address the weakness of the above two methods, this work proposes a coarse-to-fine paradigm and an improved localization algorithm that utilizes Wi-Fi to assist the robot localization in a geometrically similar environment. Firstly, a grid map is built by using laser SLAM. Secondly, a fingerprint database is built in the offline phase. Then, the RSSI values are achieved in the localization stage to get a coarse localization. Finally, an improved particle filter method based on the Wi-Fi signal values is proposed to realize a fine localization. Experimental results show that our approach is effective and robust for both global localization and the kidnapped robot problem. The localization success rate reaches 97.33%, while the traditional method always fails.

• 한국멀티미디어학회논문지
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• 제20권12호
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• pp.1865-1873
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• 2017

The feature-based visual SLAM requires 3D positions for the extracted feature points to perform 3D-2D motion estimation. LiDAR can provide reliable and accurate 3D position information with low computational burden, while stereo camera has the problem of the impossibility of stereo matching in simple texture image region, the inaccuracy in depth value due to error contained in intrinsic and extrinsic camera parameter, and the limited number of depth value restricted by permissible stereo disparity. However, the sparsity of LiDAR data may increase the inaccuracy of motion estimation and can even lead to the result of motion estimation failure. Therefore, in this paper, we propose three interpolation methods which can be applied to interpolate sparse LiDAR data. Simulation results obtained by applying these three methods to a visual odometry algorithm demonstrates that the selective bilinear interpolation shows better performance in the view point of computation speed and accuracy.