• Journal of Institute of Control, Robotics and Systems
• /
• v.20 no.5
• /
• pp.557-562
• /
• 2014

It is well known that solar tracking systems can increase the efficiency of exiting solar panels significantly. In this paper, a hybrid solar tracking system has been developed by using both astronomical estimates from a GPS and the image processing results of a camera vision system. A decision making process is also proposed to distinguish current weather conditions using camera images. Based on the decision making results, the proposed hybrid tracking system switches two tracking control methods. The one control method is based on astronomical estimates of the current solar position. And the other control method is based on the solar image processing result. The developed hybrid solar tracking system is implemented on an experimental platform and the performance of the developed control methods are verified.

• 제어로봇시스템학회:학술대회논문집
• /
• 2003.10a
• /
• pp.1694-1699
• /
• 2003

A windshield wiper system plays a key part in assuring the driver's safety during the rainfall. However, because the quantity of rain and snow vary irregularly according to time and the velocity of the automobile, a driver changes wiper speed and interval from time to time to secure enough visual field in the traditional windshield wiper system. Because a manual operation of windshield wiper distracts driver's sensitivity and causes inadvertent driving, this is becoming a direct cause of traffic accidents. Therefore, this paper presents the basic architecture of a vision-based smart windshield wiper system and a rain sensing algorithm that regulates speed and interval of the windshield wiper automatically according to the quantity of rain or snow. This paper also introduces a fuzzy wiper control algorithm based on human's expertise, and evaluates the performance of the suggested algorithm in an experimental simulator.

• IEMEK Journal of Embedded Systems and Applications
• /
• v.3 no.2
• /
• pp.57-65
• /
• 2008

Recently many researches on intelligent robots have been studied. An intelligent robot is capable of recognizing environments or objects to autonomously perform specific tasks using sensor readings. One of fundamental problems in vision-based robot applications is to recognize where it is and to decide safe path to perform autonomous navigation. However, previous approaches only consider well-organized environments that there is no moving object and environment changes. In this paper, we introduce a novel navigation strategy to handle occlusions caused by moving objects using various computer vision techniques. Experimental results demonstrate the capability to overcome such difficulties for autonomous navigation.

• Journal of Sensor Science and Technology
• /
• v.9 no.3
• /
• pp.208-212
• /
• 2000

A protein based vision biomembrane was fabricated by adsorbing bacteriorhodopsin into electrochemically polymerized polypyrrole film substrate mainly through strong electrostatic interaction. The immobilized bacteriorhodopsin on the polypyrrole film was demonstrated by SEM and SRET. The light signal transducing function from the bacteriorhodopsin which was adsorbed into Polypyrrole film was evaluated by electroretinogram(ERG). A wave form analysis of the electroretinogram indicated that the adsorbed bacteriorhodopsin retained its activity and light signal was obtained from the protein for at least one month.

• Journal of Sensor Science and Technology
• /
• v.27 no.2
• /
• pp.137-141
• /
• 2018

Detecting the ego-lane of a vehicle (the lane on which the vehicle is currently running) is one of the basic techniques for a smart car. Vision sensing is a widely-used method for the ego-lane detection. Existing studies usually find road lane lines by detecting edge pixels in the image from a vehicle camera, and then connecting the edge pixels using Hough Transform. However, this approach takes rather long processing time, and too many straight lines are often detected resulting in false detections in various road conditions. In this paper, we find the lane lines by scanning only a limited number of horizontal lines within a small image region of interest. The horizontal image line scan replaces the edge detection process of existing methods. Automatic thresholding and spatiotemporal filtering procedures are also proposed in order to make our method reliable. In the experiments using real road images of different conditions, the proposed method resulted in high success rate.

• Transactions of the Korean Society of Mechanical Engineers A
• /
• v.26 no.8
• /
• pp.1666-1671
• /
• 2002

A lane sensing algorithm using vision sensors is developed based on lane geometry models. The parameters of the lane geometry models are estimated by a Kalman filter and utilized to reconstruct the lane geometry in the global coordinate. The inverse perspective mapping from image plane to global coordinate assumes earth to be flat, but roll and pitch motions of a vehicle are considered from the perspective of the lane sensing. The proposed algorithm shows robust lane sensing performance compared to the conventional algorithms.

• Journal of Welding and Joining
• /
• v.16 no.6
• /
• pp.68-76
• /
• 1998

A CCD camera with a laser stripe was applied to realized the automatic weld seam tracking. The 3-dimensional information obtained from the vision system made it possible to generate the weld torch path. The adaptive Hough transformation was used to extract laser stripes an to obtain specific weld points. It takes relatively long time to process image on-line control using the basic control using the basic Hough transformation, but it has a tendency of robustness over the noises such as spatter. For this reason, it was complemented with adaptive Hough transformation to have an on-line processing ability for scanning specific weld points. The dead zone, where the sensing of weld line is impossible, was eliminated by rotating the camera with its rotating axis centered at the weld torch. When weld lines were detected, the camera angle was controlled in order to get the minimum image data for sensing of weld lines. Consequently, the image processing time was reduced.

• Transactions of the Korean Society of Machine Tool Engineers
• /
• v.16 no.2
• /
• pp.92-99
• /
• 2007

Welding fabrication invariantly involves three district sequential steps: preparation, actual process execution and post-weld inspection. One of the major problems in automating these steps and developing autonomous welding systems, is the lack of proper sensing strategies. Conventionally, machine vision is used in robotic arc welding only for the correction of pre-taught welding paths in single pass. In this paper, novel presented, developed vision processing techniques are detailed, and their application in welding fabrication is covered. The software for joint tracking system is finally proposed.

• Proceedings of the Korean Society of Precision Engineering Conference
• /
• 2004.10a
• /
• pp.600-603
• /
• 2004

UAV (Unmanned Aerial Vehicle) is an aerial vehicle that can accomplish the mission without pilot. UAV was developed for a military purpose such as a reconnaissance in an early stage. Nowadays usage of UAV expands into a various field of civil industry such as a drawing a map, broadcasting, observation of environment. These UAV, need vision system to offer accurate information to person who manages on ground and to control the UAV itself. Especially LOS(Line-of-Sight) system wants to precisely control direction of system which wants to tracking object using vision sensor like an CCD camera, so it is very important in vision system. In this paper, we propose a method to recognize object from image which is acquired from camera mounted on gimbals and offer information of displacement between center of monitor and center of object.

• 제어로봇시스템학회:학술대회논문집
• /
• 2002.10a
• /
• pp.41.1-41
• /
• 2002

This paper describes a robust landmark matching method to reduce ambiguity of candidate of landmark. General robot system acquires the candidate of landmark through vision sensor in outdoor environment. Our robot uses the omnidirectional vision system to get all around the view. Thus, the robot obtains more candidates of landmark than the conventional vision system. To obtain the candidates of landmark, robot uses the two types of feature. They are vertical edge and merged region of vertical edges. The former is to extract the vertical line of building, street lamp, etc. The latter is to reduce ambiguity of vertical edge in similar region. It is difficult to match the candidates of landmark...