• Journal of Korean Society for Atmospheric Environment
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• 제18권E4호
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• pp.215-221
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• 2002

The real-time modeling system, named AirWatch System, has been developed to evaluate the environmental impact from a large source. It consists of stack TMS (TeleMetering System) that measures the emission data from the source, AWS (Automatic Weather Station) that monitors the weather data and computer system with the dispersion modeling software. The modeling theories used in the system are Gaussian plume and puff models. The Gaussian plume model is used for the dispersion in the simple terrain with a point meteorological data while the puff model is for the dispersion in complex terrain with three dimensional wind fields. The AirWatch System predicts the impact of the emitted pollutants from the large source on the near-by environment on the real -time base and the alarm is issued to control the emission rate if the calculated concentrations exceed the modeling significance level.

• 제어로봇시스템학회논문지
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• 제18권4호
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• pp.359-364
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• 2012

Real-Time Traversability should be analyzed from the equiped sensors' data in real time for autonomous outdoor navigation. However, it is difficult to find out such traversability that considers the terrain roughness and the vehicle dynamics especially in case of skid type vehicle. The traversability based on real time dynamic analysis was proposed to solve such problem but in navigation with strait driving path. To adapt the method into the navigation with curved driving path, a path following controller should be incorporated into the dynamic model even though it cause the real time problem. In this paper, a dynamic model is proposed to solve the real time problem in the traversability analysis based on real time dynamic simualtion. The dynamic model contains the control dummy which is connected to the vehicle body with a universal joint to follow the curved path without controller. Simulation and experimental results on $6{\times}6$ articulated unmanned ground vehicle demonstrate the method's effectiveness and applicability into the traversability analysis on terrain with bumps.

• 대한기계학회논문집A
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• 제41권5호
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• pp.367-374
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• 2017

본 연구의 목적은 120톤급 전지형 크레인의 조향성능 향상을 위한 제어 알고리즘의 개발이다. 이를 위해 AMESim 소프트웨어를 이용하여 전지형 크레인의 유압조향시스템을 모델링하고, PID 기반의 조향제어용 제어기를 MATLAB/Simulink 환경에서 설계하였다. 설계된 제어기의 성능은 실시간 시뮬레이터를 활용한 유압 및 제어 모델간 연성해석을 통하여 검증하였다.

• 국제학술발표논문집
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• The 3th International Conference on Construction Engineering and Project Management
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• pp.487-492
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• 2009

A large-scaled research project titled "Intelligent Excavating System (IES)" sponsored by Korean government has launched in 2006. An issue of real-time 3D terrain modeling has become a crucial point for successful implementation of IES due to many application limitations of state-of-the-art techniques developed in various high-technology fields. Many feasible technologies such as laser scanning, structured lighting and so on were widely reviewed by professionals and researchers for one year. Various efforts such as literature reviews, interviews, and indoor experiments make us select a structural light technique and stereo vision technique as appropriate techniques for accomplishment of real-time 3D terrain modeling. It, however, revealed that off-the-shelf products of structural light and stereo-vision technique had many technical problems which should be resolved for practical applications in IES. This study introduces diverse methods modifying off-the-shelf package of the structural light method, one of feasible techniques and eventually allowing this technique to be successfully utilized for achieving fundamental research goals. This study also presents many efforts to resolve practical difficulties of this technique considering basic characteristics of excavating operations and particular environment of construction sites. Findings showed in this study would be beneficial for other researchers to conduct new researches for application of vision techniques to construction fields by provision of detail issues about practical application and diverse practical methods as solutions overcoming these issues.

• Wind and Structures
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• 제12권3호
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• pp.219-237
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• 2009

This study examines the accuracy of large-eddy simulation (LES) to simulate the flow around a large irregular sloping complex terrain. Typically, real built up environments are surrounded by complex terrain geometries with many features. The complex terrain surrounding The Hong Kong University of Science and Technology campus was modelled and the flow over an uphill slope was simulated. The simulated results, including mean velocity profiles and turbulence intensities, were compared with the flow characteristics measured in a wind tunnel model test. Given the size of the domain and the corresponding constraints on the resolution of the simulation, the mean velocity components within the boundary layer flow, especially in the stream-wise direction were found to be reasonably well replicated by the LES. The turbulence intensity values were found to differ from the wind tunnel results in the building recirculation zones, mostly due to the constraints placed on spatial and temporal resolutions. Based on the validated mean velocity profile results, the flow-structure interactions around these buildings and the surrounding terrain were examined.

• 제어로봇시스템학회논문지
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• 제13권9호
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• pp.883-895
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• 2007

In this work, we present the development of a patrol robot which is intended to navigate outdoor rough terrain. Proposed mechanism consists of six legs for overcoming an obstacle, and six wheels for traveling. Also, in order to absorb vibration in rough terrain effectively, the slide-spring system and tubed type tire are adopted to each leg and each wheel. The control system of robot consists of several imbedded boards for management of lots of diverse devices such as sensors designed for rough terrain, motor controllers, camera, micro controller and so on. And the base system of the robot is designed to operate in real time and to surveille in the vicinity of the robot, and the robot system is controlled by wireless LAN connected to GUI-based remote control system, while CAN communication connects the control board and the device controllers for sensors and motor controllers. For operating this robot system efficiently, we propose the control algorithms for autonomous navigation using GPS, stabilization maintenance by posture control, obstacle-avoidance by impedance control, and obstacle-overcoming with interference-avoidance between wheels. The performance of the robot and the proposed algorithms are tested and proved by a set of experiments in outdoor rough terrain.

• 한국시뮬레이션학회:학술대회논문집
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• 한국시뮬레이션학회 2002년도 추계학술대회 논문집
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• pp.163-170
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• 2002

Terrain surfaces have to be modeled in very detail and wheel-surface contacting geometry must be well defined in order to obtain proper ground-reaction and friction forces for realistic simulation of off-road vehicles. Delaunay triangulation is one of the most widely used methods in modeling 3-dimensional terrain surfaces, and T-search is a relevant algorithm for searching resulting triangular polygons. The T-search method searches polygons in successive order and may not allow real-time computation of off-road vehicle dynamics if the terrain is modeled with many polygons, depending on the computer performance used in the simulation. In order to accelerate the searching speed of T-search, a terrain database of triangular polygons is modeled in multi-levels by adopting the LOD (Level of Detail) method used in realtime computer graphics. Simulation results show that the new LOD search is effective in shortening the required computing time. The LOD search can be even further accelerated by introducing an NN (Neural Network) algorithm, in the cases where a appropriate range of moving paths can be predicted by cultual information of the simulated terrain, such as lakes, houses, etc.. Numerical tests show that LOD-NN search almost double the speed of the original T-search.

• 설비공학논문집
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• 제17권11호
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• pp.1060-1071
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• 2005

Passive gas dispersions over a 1/1000 scale terrain model at Eiffel type wind tunnel were reproduced by numerical simulation. Large eddy simulation was used to treat the sub-grid scale turbulences. The terrain features were represented by millions of point forces densely distributed over the solid surface using the virtual boundary method. The model simulations agreed very well with the experiments in a consistent fashion for all wind directions. The measured profiles of the wind speeds as well as the tracer gas concentrations were nicely simulated by the CFD model at most locations scattered over the model terrain. With scale factor adjusted and the thermal stratification effects incorporated, the CFD model was expected to provide reliable information on pollutant dispersions over the real complex terrains.

• 로봇학회논문지
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• 제5권4호
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• pp.339-348
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• 2010

One of the requirements for autonomous vehicles on off-road is to move stably in unstructured environments. Such capacity of autonomous vehicles is one of the most important abilities in consideration of mobility. So, many researchers use contact and/or non-contact methods to determine a terrain whether the vehicle can move on or not. In this paper we introduce an algorithm to classify terrains using visual information(one of the non-contacting methods). As a pre-processing, a contrast enhancement technique is introduced to improve classification of terrain. Also, for conducting classification algorithm, training images are grouped according to materials of the surface, and then Bayesian classification are applied to new images to determine membership to each group. In addition to the classification, we can build Traversability map specified by friction coefficients on which autonomous vehicles can decide to go or not. Experiments are made with Load-Cell to determine real friction coefficients of various terrains.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2008년도 하계종합학술대회
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• pp.853-854
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• 2008

The terrain perception technology using passive sensors plays a key role to enhance autonomous mobility for UGV. We present an effective method to classify terrain covers based on the color information. Considering a real-time implementation, neural network is applied for the terrain classifier and wavelet features extracted from the images are used. Test results show that the proposed algorithm has a promising classification performance.