• 한국정보기술응용학회:학술대회논문집
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• 한국정보기술응용학회 2005년도 6th 2005 International Conference on Computers, Communications and System
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• pp.113-117
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• 2005

This paper describes a visual control scheme, fuzzy logic system for visual servoing of an autonomous mobile robot. An existing communication autonomous mobile robot always needs to keep the object in image to detect the moving object. This is a problem in an autonomous mobile robot for spontaneous activity. To solve it, some features for an object are taken from an image and then use in the design of fuzzy logic system for decision of moving location and direction of visual servoing contrivance(apparatus). So continuous tracking is possible by moving the visual servoing contrivance. We present some simulation results and further studies in the Section of Simulation and Concluding Remarks.

• 자동차안전학회지
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• 제11권2호
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• pp.17-22
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• 2019

This paper describes the tracking algorithm performance evaluation for autonomous vehicle using a safety envelope based path. As the level of autonomous vehicle technologies evolves along with the development of relevant supporting modules including sensors, more advanced methodologies for path generation and tracking are needed. A safety envelope zone, designated as the obstacle free regions between the roadway edges, would be introduced and refined for further application with more detailed specifications. In this paper, the performance of the path tracking algorithm based on the generated path would be evaluated under safety envelop environment. In this process, static obstacle map for safety envelope was created using Lidar based vehicle information such as current vehicle location, speed and yaw rate that were collected under various driving setups at Seoul National University roadways. A level of safety was evaluated through CarSim simulation based on paths generated with two different references: a safety envelope based path and a GPS data based one. A better performance was observed for tracking with the safety envelop based path than that with the GPS based one.

• 전자공학회논문지CI
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• 제47권2호
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• pp.54-64
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• 2010

위치측정은 사용자나 사물에게 주변 환경에 대한 인식을 가능케 하는 기본적인 요소이기 때문에 센서네트워크 환경에서는 가장 핵심적인 요소이다. 기존 위치측정 기법은 크게 Range-based방식과 Range-free방식으로 나눌 수 있다. Range-based방식은 전파의 불규칙하고 추가 장비가 필요한 반면에 Range-free방식은 능동적인 통신을 수단으로 위치를 측정하므로 자원제약적인 센서네트워크에서는 적합한 것으로 알려져 있다. 그러나 위치측정의 정확성이 주변노드의 수에 따라 크게 좌우된다. 특히 밀집도가 낮은 센서네트워크 환경에서는 위치측정의 정확성이 매우 낮다. 본 논문에서 제안된 DRTS(Distributed Range-hybrid Tracking Scheme)는 Range-based와 Range-free방식을 혼합하고 주변노드의 위치와 통신범위 및 세기정보를 최대한 활용하여 이동물체를 추적할 수 있는 기법을 제시한다. 특히 주변노드를 최대한 활용한 효율적인 위치측정기법과 제안된 EGP(Estimative Gird Points)의 예측기법을 활용하여 위치추적의 정확성을 획기적으로 개선할 수 있는 방안을 제시한다. 그리고 시뮬레이션 결과를 통해 기존 위치추적 알고리즘 보다 추적의 정확도 관점에서 제안된 기법의 성능이 우수함을 증명하였다.

• 한국군사과학기술학회지
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• 제17권1호
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• pp.96-107
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• 2014

Tracking the tactical object is a fundamental affair in network-equipped modern warfare. Geodetic coordinate system based on longitude, latitude, and height is suitable to represent the location of tactical objects considering multi platform data fusion. The motion of tactical object described as a dynamic model requires an appropriate filtering to overcome the system and measurement noise in acquiring information from multiple sensors. This paper introduces the filter suitable for multi-sensor data fusion and tactical object tracking, particularly the unscented transform(UT) and its detail. The UT in Unscented Kalman Filter(UKF) uses a few samples to estimate nonlinear-propagated statistic parameters, and UT has better performance and complexity than the conventional linearization method. We show the effects of UT-based filtering via simulation considering practical tactical object tracking scenario.

• 국제학술발표논문집
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• The 8th International Conference on Construction Engineering and Project Management
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• pp.510-519
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• 2020

Within an intelligent automated cyber-physical system, the realization of the autonomous mechanism for data collection, data integration, and data analysis plays a critical role in the design, development, operation, and maintenance of such a system. This construct is particularly vital for fault-tolerant route-finding systems that rely on the imprecise GPS location of the vehicles to properly operate, timely plan, and continuously produce informative feedback to the user. More essentially, the integration of digital twins with cyber-physical route-finding systems has been overlooked in intelligent transportation services with the capacity to construct the network routes solely from the locations of the operating vehicles. To address this limitation, the present study proposes a conceptual architecture that employs digital twin to autonomously maintain, update, and manage intelligent transportation systems. This virtual management simulation can improve the accuracy of time-of-arrival prediction based on auto-generated routes on which the vehicle's real-time location is mapped. To that end, first, an intelligent transportation system was developed based on two primary mechanisms: 1) an automated route finding process in which predictive data-driven models (i.e., regularized least-squares regression) can elicit the geometry and direction of the routes of the transportation network from the cloud of geotagged data points of the operating vehicles and 2) an intelligent mapping process capable of accurately locating the vehicles on the map whereby their arrival times to any point on the route can be estimated. Afterward, the digital representations of the physical entities (i.e., vehicles and routes) were simulated based on the auto-generated routes and the vehicles' locations in near-real-time. Finally, the feasibility and usability of the presented conceptual framework were evaluated through the comparison between the primary characteristics of the physical entities with their digital representations. The proposed architecture can be used by the vehicle-tracking applications dependent on geotagged data for digital mapping and location tracking of vehicles under a systematic comparison and simulation cyber-physical system.

• 한국통신학회논문지
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• 제25권5A호
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• pp.763-771
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• 2000

적외선 탐색기에 널리 사용되는 레티클 시스템은 시계(field of view ; FOV) 상에 존재하는 표적의 위치를 구하는 대표적인 방법이다. 본 논문에서는 동심원(concentric annular ring) 레티클 탐색기의 표적 추적 성능을 시뮬레이션할 수 있는 효과적인 툴이 제안된다. 동적인 시뮬레이션을 위해 대상 탐색기는 Matlab-Simulink 상에서 구성되었으며, 이는 탐색기 및 무기의 개발 등이 필수적이다. 시계상에 섬광탄 등의 대응능력이 존재하는 경우, 표적에 대한 정확한 추적은 매우 어렵게 된다. 본 연구에서는 이러한 대응능력의 영향을 줄이기 위해 입력 신호와 기준 신호와의 상관 관계를 이용하는 반대응 기법이 제안된다. 구성된 툴 상에서 제안된 방법이 기존 방법에 비해 보다 효과적인 표적 추적 결과를 보임을 확인하였다.

• Journal of Electrical Engineering and Technology
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• 제6권6호
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• pp.806-816
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• 2011

Interest about social security has recently increased in favor of safety for infrastructure. In addition, advances in computer vision and pattern recognition research are leading to video-based surveillance systems with improved scene analysis capabilities. However, such video surveillance systems, which are controlled by human operators, cannot actively cope with dynamic and anomalous events, such as having an invader in the corporate, commercial, or public sectors. For this reason, intelligent surveillance systems are increasingly needed to provide active social security services. In this study, we propose a core technique for intelligent surveillance system that is based on swarm robot technology. We present techniques for invader enclosing using swarm robots based on multiple distributed object environment. The proposed methods are composed of three main stages: location estimation of the object, specified object tracking, and decision of the cooperative behavior of the swarm robots. By using particle filter, object tracking and location estimation procedures are performed and a specified enclosing point for the swarm robots is located on the interactive positions in their coordinate system. Furthermore, the cooperative behaviors of the swarm robots are determined via the result of path navigation based on the combination of potential field and wall-following methods. The results of each stage are combined into the swarm robot-based invader-enclosing technique on multiple distributed object environments. Finally, several simulation results are provided to further discuss and verify the accuracy and effectiveness of the proposed techniques.

• 전자공학회논문지CI
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• 제48권2호
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• pp.106-116
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• 2011

USN(Ubiquitous Sensor Network) 환경은 언제, 어디서나 정보를 이용할 수 있게 한다. 이러한 환경의 기반이 되는 기술은 타겟의 정확한 위치설정을 전제로 한다. 특히 ITS(Intelligent Transportation Systems)는 USN 기술을 적용함으로써 쉽게 구축 될 수 있다. 위치측정은 Range-based 방식과 Range-free 방식으로 나눌 수 있다. Range-based 방식은 전파의 불규칙하고 추가 장비가 필요로 센서네트워크기반 위치측정에 적합하지 않은 것으로 알려져 있다. 반면에 Range-free 방식은 능동적인 통신을 수단으로 위치를 측정하므로 자원제약적인 센서네트워크에서는 적합한 것으로 알려져 있다. 그러나 Range-free 방식은 일반적으로 정확성이 부족하며, 특히 밀집도가 낮은 환경에서는 정확성이 매우 낮다. 따라서 이 두 기법은 장단점을 가지고 있다. 그러므로 두 기법을 혼합하여 위치추적의 정확성을 개선할 수 있는 새로운 기법이 요구된다. 본 논문은 Range-free 방식을 개선할 수 있도록 추가 장비가 요구되지 않은 RSSI(Received Signal Strength Indication) 신호 값을 분류하고 주변노드의 위치와 통신범위 및 세기정보를 최대한 활용하여 이동차량을 보다 정확하게 추적할 수 있는 Range-hybrid 기반의 위치추적기법을 제시한다. 추가적으로 예측기법을 활용하여 위치추적의 정확성을 획기적으로 개선할 수 있는 방안을 제시한다. 그리고 시뮬레이션 결과, 제안된 기법이 기존 위치추적 알고리즘 보다 교통 환경에서 위치추적의 정확도가 우수함을 증명하였다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제9권2호
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• pp.600-619
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• 2015

We propose a cost-efficient hybrid algorithm for online location updates that efficiently combines feature point detection with the online trajectory-based sampling algorithm. Our algorithm is designed to minimize the average trajectory error with the minimal number of sample points. The algorithm is composed of 3 steps. First, we choose corner points from the map as sample points because they will most likely cause fewer trajectory errors. By employing the online trajectory sampling algorithm as the second step, our algorithm detects several missing and important sample points to prevent unwanted trajectory errors. The final step improves cost efficiency by eliminating redundant sample points on straight paths. We evaluate the proposed algorithm with real GPS trajectory data for various bus routes and compare our algorithm with the existing one. Simulation results show that our algorithm decreases the average trajectory error 28% compared to the existing one. In terms of cost efficiency, simulation results show that our algorithm is 29% more cost efficient than the existing one with real GPS trajectory data.

• Nuclear Engineering and Technology
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• 제53권7호
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• pp.2334-2340
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• 2021

Radioactive particle tracking (RPT) is a minimally invasive nuclear technique that tracks a radioactive particle inside a volume of interest by means of a mathematical location algorithm. During the past decades, many algorithms have been developed including ones based on artificial intelligence techniques. In this study, RPT technique is applied in a simulated test section that employs a simplified mixer filled with concrete, six scintillator detectors and a¹³⁷Cs radioactive particle emitting gamma rays of 662 keV. The test section was developed using MCNPX code, which is a mathematical code based on Monte Carlo simulation, and 3516 different radioactive particle positions (x,y,z) were simulated. Novelty of this paper is the use of a location algorithm based on a deep learning model, more specifically a 6-layers deep rectifier neural network (DRNN), in which hyperparameters were defined using a Bayesian optimization method. DRNN is a type of deep feedforward neural network that substitutes the usual sigmoid based activation functions, traditionally used in vanilla Multilayer Perceptron Networks, for rectified activation functions. Results show the great accuracy of the DRNN in a RPT tracking system. Root mean squared error for x, y and coordinates of the radioactive particle is, respectively, 0.03064, 0.02523 and 0.07653.