• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1996.10a
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• pp.219-222
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• 1996

During the navigation of mobile robot, one of the essential task is to determination the absolute location of mobile robot. In this paper, we proposed a method to determine the position of the camera from a landmark through the visual image of a quadrangle typed landmark using neural network. In determining the position of the camera on the world coordinate, there is difference between real value and calculated value because of uncertainty in pixels, incorrect camera calibration and lens distortion etc. This paper describes the solution of the above problem using BPN(Back Propagation Network). The experimental results show the superiority of the proposed method in comparison to conventional method in the performance of determining camera position.

• Korean Journal of Computational Design and Engineering
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• v.7 no.1
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• pp.18-26
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• 2002

The suggested modular projection system can have flexible arrangements of screens. Modular and continuous arrangements of the display system enable us to modify the screen configuration easily, so that the system can be used in various applications. The image of each screen is calculated automatically by using window projection and the tracked position of the viewer. This system also uses the off-axis stereoscopic projection for the seamless stereoscopic edge blending of multiple connections of screens. The system has been successfully tested for the general navigation model and the CAU driving simulator with motion platform.

• Journal of Korean Port Research
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• v.13 no.2
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• pp.381-388
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• 1999

To improve the productivity in the harbor, successful development of an UCT(Unmanned Container Transporter) is needed. Well-designed steering and velocity control systems are the key factor for the development of the UCT. In this paper, a research concerning the achievement of the steering control is introduced. To get an information on the guide line that the UCT should track, the vision system is applied. By using neural network, proper steering angle is gotten fast with less influence of the image disturbance. A simulation based on the UCT kinematics is performed with the measured steering angle, and it shows satisfactory results.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.24 no.9B
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• pp.1704-1712
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• 1999

This research features efficient detection of obstacles, especially vehicles, in the forward direction of navigation for the development of unmanned automous vehicle. We separate image regions into ground and non-ground planes using the Helmholtz shearing technique in order to reliably exclude regions that do not contain obstacles. We propose a computationally simple and efficient method for the detection of vehicles in the forward direction by analysis of horizontally and vertically projected histograms of residual disparity map obtained from Helmholtz shearing. We have experimented the proposed method on real outdoor stereo data. Experimental results show that our method gives accurate detection of forward vehicles and is computationally very efficient.

• Proceedings of the KIEE Conference
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• 1993.07a
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• pp.387-390
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• 1993

The most important technique for an indoor robot navigation is to find out the direction and the distance from the current location to the destination through the information achieved from the sensor. For this purpose, we suggest sensor-based local homing method which compares the destination sensory data with the current location. As for the sensors, we use the CCD camera and the ultrasonic sensor, and recorded entire 360 degree panoramic data. We match the features of the image data, and the distance and the direction of the matched point will be considered as fuzzy numbers. Through a simple fuzzy arithmetic, we infer the geometric relations between the current location and the destination location.

• Journal of Korean Port Research
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• v.12 no.2
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• pp.225-232
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• 1998

Todays, the efficient management of container has not been realized in container terminal, because of the excessive quantity of container transported and manual system. For the efficient and automated management of container in terminal, the automated container identifier recognition system in terminal is a significant problem. However, the identifier recognition rate is decreased owing to the difficulty of image preprocessing caused the refraction of container surface, the change of weather and the damaged identifier characters. Therefore, this paper proposes more accurate system for container identifier recognition as suggestion of LSPRD(Line-Scan Proper Region Detection) for stronger preprocessing against external noisy element and MBP(Momentum Back-Propagation) neural network to recognize the identifier.

• 한국방재학회:학술대회논문집
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• 2008.02a
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• pp.661-664
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• 2008

U-Eco City is promoted nation-wide by development of recent IT technology, method of effective countermeasure disasters, which real-time wire/wireless communication network, and 3D-Web GIS shall be connected that massive database, intelligent service be perceived. U&V-City is the four-dimensional future city that actualizes an intelligent daily ubiquitous computing service by embodying 3D-Virtual City, the reproduction of real world U-City while using Digital map, satellite image, VRML(Virtual Reality Modeling Language), which are presentation tool to describe city components and by efficiently catch and cope about nature and human disasters while employing EAI(External Authoring Interface) that provides HTML&JAVA, and interface for efficient removal/process of massive information/service and also by employing GPS/LBS/Navigation in support of the world-wide orientation concept, and RTLS(Real Time Location System).

• Journal of Drive and Control
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• v.17 no.4
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• pp.8-14
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• 2020

Intelligent devices using ICT technology have been introduced in the field of construction machinery to improve productivity and stability. Among the intelligent devices, Machine Guidance is a device that provides real-time posture, location, and work range to drivers by installing various sensors, controllers, and satellite navigation systems on construction machines. Conversely, the efficiency of equipment that requires location information, such as machine guidance, will be greatly reduced in buildings, and tunnels in the GPS blind spots. Thus, the other high-precision positioning technologies are required in the GPS blind spot zone. In this study, we will develop a relative position measurement system that provides precise location information such as construction machinery and robots in a local area where the GPS reception is difficult. A relative position measurement system tracks a marker in the form of a sphere installed on a vehicle by using the image base tracking technology, and measures the distance and direction information to the marker to calculate a position.

• Journal of information and communication convergence engineering
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• v.20 no.3
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• pp.226-233
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• 2022

Video surveillance is widely used in security surveillance, military navigation, intelligent transportation, etc. Its main research fields are pattern recognition, computer vision and artificial intelligence. This article uses OpenCV to detect and track vehicles, and monitors by establishing an adaptive model on a stationary background. Compared with traditional vehicle detection, it not only has the advantages of low price, convenient installation and maintenance, and wide monitoring range, but also can be used on the road. The intelligent analysis and processing of the scene image using CAMSHIFT tracking algorithm can collect all kinds of traffic flow parameters (including the number of vehicles in a period of time) and the specific position of vehicles at the same time, so as to solve the vehicle offset. It is reliable in operation and has high practical value.

• The Journal of Korea Robotics Society
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• v.18 no.3
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• pp.271-280
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• 2023

FMCW (Frequency Modulated Continuous Wave) radar system is widely used in autonomous driving and navigation applications due to its high detection capabilities independent of weather conditions and environments. However, radar signals can be easily contaminated by various noises such as speckle noise, receiver saturation, and multipath reflection, which can worsen sensing performance. To handle this problem, we propose a learning-free noise removal technique for radar to enhance detection performance. The proposed method leverages adaptive thresholding to remove speckle noise and receiver saturation, and wavelet transform to detect multipath reflection. After noise removal, the radar image is reconstructed with the geometric structure of the surrounding environments. We verify that our method effectively eliminated noise and can be applied to autonomous driving by improving the accuracy of odometry and place recognition.