• The Journal of Korea Robotics Society
• /
• v.5 no.4
• /
• pp.367-376
• /
• 2010

This Paper Proposes A Robust Image Stabilization System For A Mobile Robot Using An Extended Kalman Filter (Ekf). Though Image Information Is One Of The Most Efficient Data Used For Robot Navigation, It Is Subjected To Noise Which Is The Result Of Internal Vibration As Well As External Factors Such As Uneven Terrain, Stairs, Or Marshy Surfaces. The Camera Vibration Deteriorates The Image Resolution By Destroying The Image Sharpness, Which Seriously Prevents Mobile Robots From Recognizing Their Environment For Navigation. In This Paper, An Inclinometer Was Used To Measure The Vibration Angle Of The Camera System Mounted On The Robot To Obtain A Reliable Image By Compensating For The Angle Of The Camera Vibration. In Addition The Angle Prediction Obtained By Using The Ekf Enhances The Image Response Analysis For Real Time Performance. The Experimental Results Show The Effectiveness Of The Proposed System Used To Compensate For The Blurring Of The Images.

• Journal of Korean Society for Atmospheric Environment
• /
• v.10 no.3
• /
• pp.197-202
• /
• 1994

The research described in this paper is conducted to estimate the short-term concentrations of nonreactive pollutants such as CO and TSP from vehicle emissions near Kyungbu Highway. An emphasis is placed on the development of a model for a hourly traffic volume for each vehicle type, which is based on real traffic data. By using the model and the calculated emission factor due to vehicle speed for each vehicle type, the emission rate of CO and TSP for each traffic line is computed. The hourly emission rate and meteorological data are used to simulate by HIWAY-2 for the distance of 5m and 10m from the downwind edge of Kyungbu Highway located in relatively uncomplicated terrain.

• Proceedings of the IEEK Conference
• /
• 2003.11a
• /
• pp.393-396
• /
• 2003

This paper proposes a method to speed up the document image binarization using a water flow model. The proposed method extracts the region of interest (ROI) around characters from a document image and restricts pouring water onto a 3-dimensional terrain surface of an image only within the ROI. The amount of water to be filled into a local valley is determined automatically depending on its depth and slope. Then, the proposed method accumulates weighted water not only on the locally lowest position but also on its neighbors. Finally, the depth of each pond is adaptively thresholded for robust character segmentation. Experimental results on real document images shows that the proposed method has attained good binarization performance as well as remarkably reduced processing time compared with that of the existing method based on a water flow model.

• Journal of Institute of Control, Robotics and Systems
• /
• v.14 no.5
• /
• pp.489-495
• /
• 2008

This paper offers a practical control scheme for driving mode transformation of a rescue robot already developed. The rescue robot, VSTR(Variable Single-Tracked Robot), has two driving modes, so can traverse untidy terrain and overcome obstacles such as stairs easily by use of timely driving mode transformation. Classical PI control scheme was used firstly for driving mode transformation, but stationary phenomenon, which might have a bad effect on the performance in real situation, came into existence. Therefore, we suggest a new controller, PI-based feedforward controller, which should be a good alternative for the problem, and compare it with other nonlinear control scheme.

• Proceedings of the KSRS Conference
• /
• 2007.10a
• /
• pp.573-575
• /
• 2007

Current accuracy of GPS is within the meter level, which is sufficient for route guidance of car navigation system(CNS). But receiving condition of GPS signal varies time to time according to surrounding objects such as building, trees, and terrain. For this reason, the performance of the route guidance is degraded in urban region. In this paper, to improve the performance of the route guidance of CNS, we propose a method for determining location of vehicle using a location of the traffic signal and its pixel size extracted from real-time Image.

• Journal of the military operations research society of Korea
• /
• v.26 no.2
• /
• pp.75-89
• /
• 2000

This paper deals with complex system theory to describe guerrilla warfare situation using EINSTein (Enhanced ISAAC Neural Simulation Tool) simulation model. EINSTein model is an agent-based artificial "laboratory" for exploring self-organized emergent behavior in land combat. Many studies have shown that existing Lanchester equations used in most guerrilla warfare models do not describe changes of combat units, real guerrilla warfare situation and qualitative factors in combat. Future warfare will be information warfare with various weapon system and complex combat units. We have compared and tested results with Lanchester models and EINSTein model. And the EINSTein model has been applied and analyzed to guerrilla warfare model (C4I facilities, coastal, urbanized terrain critical facilities defense). The results show that the EINSTein model has a possibility to apply and analyze guerrilla warfare more properly than Lanchester models.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
• /
• v.22 no.11
• /
• pp.773-780
• /
• 2010

The dispersion of plume which is emitted from a chimney is governed by a lot of factors： wind, local terrain, turbulence intensity of atmosphere, and temperature, etc. In this study, we numerically investigate the plume dispersions for various altitudinal temperature gradients and wind speeds. The normal atmosphere has the temperature decrease of $0.6^{\circ}C/100m$, however, actually the real atmosphere has the various altitudinal temperature profiles according to the meteorological factors. A previous study focused on this atmospheric temperature gradient which induces a large scale vertical flow motion in the atmosphere thus makes a peculiar plume dispersion characteristics. In this paper, the effects of the atmospheric temperature gradient as well as the wind speed are investigated concurrently. The results for the developing processes in the atmosphere and the affluent's concentrations at the ambient and ground level are compared under the various altitudinal temperature gradients and wind speeds.

• Journal of Institute of Control, Robotics and Systems
• /
• v.21 no.8
• /
• pp.773-780
• /
• 2015

Navigation in outdoor environments is a fundamental and challenging problem for unmanned ground vehicles. Detecting lane markings or boundaries on the road may be one of the solutions to make navigation easy. However, because of various environments and road conditions, a robust lane detection is difficult. In this paper, we propose a new approach for estimating virtual lanes on a traversable region. Estimating the virtual lanes consist of two steps: (i) we detect virtual road region through road model selection based on traversability at current frame and similarity between the interframe and (ii) we estimate virtual lane using the number of lane on the road and results of previous frame. To improve the detection performance and reduce the searching region of interests, we use a probability map representing the traversability of the outdoor terrain. In addition, by considering both current and previous frame simultaneously, the proposed method estimate more stable virtual lanes. We evaluate the performance of the proposed approach using real data in outdoor environments.

• Journal of Environmental Science International
• /
• v.6 no.3
• /
• pp.205-211
• /
• 1997

For the prediction of multi-site rainfall with radar data and ground meteorological data, a rainfall prediction model was proposed, which uses the neural network theory, a kind of artifical Intelligence technique. The Input layer of the prediction model was constructed with current ground meteorological data, their variation, moving vectors of rain- fall field and digital terrain of the measuring site, and the output layer was constructed with the predicted rainfall up to 3 hours. In the application of the prediction model to the Pyungchang river basin, the learning results of neural network prediction model showed more Improved results than the parameter estimation results of an existing physically based model. And the proposed model comparisonally well predicted the time distribution of ralnfall.

• Journal of Navigation and Port Research
• /
• v.30 no.7
• /
• pp.611-615
• /
• 2006

This paper proposes a method for generating radar images used in a ship handling simulator, which includes mathematical logics based on radar equations and information from Openflight format files. In order to make radar image much similar to that of real radar in PPI type, the proposed mathematical logic derives radar video signals under the consideration of not only the data form flight format file of simulation scenes, but also geographical radar's position. The proposed method is considered useful to make radar images in ship handling simulator with accuracy and reality.