• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2010.05a
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• pp.245-249
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• 2010

In the stereo vision system, information about an object could be gained by searching through images. Edges which are based on the information about an object are used to find the position of the object and send a message of its position coordinate to a unmanned crain. This thesis proposes an algorithm to find the center point of the object's surface which is connected to the unmanned crain's arm, and to recognize the shape of the object by using two CCD cameras. At first, getting information about the edges, and distinguishing each edge's characteristics depend on user's option, and then find the location information by a set of positions that are proposed. This thesis is expected to be devoted to the development of an automation system of unmanned moving equipment.

• Transactions of the Korean Society of Automotive Engineers
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• v.11 no.6
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• pp.213-221
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• 2003

This paper describes a method of lane tracking by means of a vision system which includes vehicle control and modeling. Lane tracking is considered one of the important technologies in an unmanned vehicle and mobile robot system. The current position and condition of the vehicle are calculated from an image processing method by a CCD camera. We deal with lane tracking as follows. First, vehicle control is included in the road model, and lateral and longitudinal controls. Second, the image processing method deals with the lane detection method, image processing algerian, and filtering method. Finally, this paper proposes a correct method for lane detection through a vehicle test by wireless data communication.

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.7
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• pp.617-624
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• 2010

This article describes the system architecture of KUVE (KIST Unmanned Vehicle Electric) and unmanned autonomous navigation of it in KIST. KUVE, which is an electric light-duty vehicle, is equipped with two laser range finders, a vision camera, a differential GPS system, an inertial measurement unit, odometers, and control computers for autonomous navigation. KUVE estimates and tracks the boundary of road such as curb and line using a laser range finder and a vision camera. It follows predetermined trajectory if there is no detectable boundary of road using the DGPS, IMU, and odometers. KUVE has over 80% of success rate of autonomous navigation in KIST.

• Journal of the Korean Society of Industry Convergence
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• v.26 no.6_2
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• pp.1063-1071
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• 2023

Unmanned aerial vehicles (UAVs, drones) are becoming increasingly useful in a variety of fields. Advances in UAV and camera technology have made it possible to equip them with ultra-high resolution sensors and capture images at low altitudes, which has improved the reliability and classification accuracy of object identification on the ground. The distinctive contribution of this study is the derivation of sensor-specific performance metrics (GRD/GSD), which shows that as the GSD increases with altitude, the GRD value also increases. In this study, we identified the characteristics of various onboard sensors and analysed the image quality (discrimination resolution) of aerial photography results using UAVs, and calculated the shooting conditions to obtain the discrimination resolution required for reading ground objects.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.16 no.3
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• pp.15-22
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• 2007

An automatic measurement system which collects experimental data at an unmanned station where the networking to the internet could not be accessed was developed. With a Robo-rail accessing to the unmanned station, wireless local networking between server PC at the Rob-rail and client PC at the unmanned station is possible within 30 m from an access point equipment located at the unmanned station. An algorithm for transferring the data file which is saved in the client PC at the unmanned station to the server PC in the Robo-rail was proposed. IEEE-1394 camera was used to collect the data at the client PC. An extracting program from the IEEE-1394 captured images to character data and number data was developed using image processing technique, which drastically reduces the size of data file comparing to that of the raw image file.

• International Journal of Aeronautical and Space Sciences
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• v.11 no.2
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• pp.69-79
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• 2010

This paper describes the experimental framework for the control system design and validation of a rotorcraft unmanned aerial vehicle (UAV). Our approach follows the general procedure of nonlinear modeling, linear controller design, nonlinear simulation and flight test but uses an indoor-installed multi-camera system, which can provide full 6-degree of freedom (DOF) navigation information with high accuracy, to overcome the limitation of an outdoor flight experiment. In addition, a 3-DOF flying mill is used for the performance validation of the attitude control, which considers the characteristics of the multi-rotor type rotorcraft UAV. Our framework is applied to the design and mathematical modeling of the control system for a quad-rotor UAV, which was selected as the test-bed vehicle, and the controller design using the classical proportional-integral-derivative control method is explained. The experimental results showed that the proposed approach can be viewed as a successful tool in developing the controller of new rotorcraft UAVs with reduced cost and time.

• Journal of The Korean Society of Grassland and Forage Science
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• v.35 no.3
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• pp.225-231
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• 2015

Improving current pasture productivity by precision management requires practical tools to collect site specific pasture biomass data. Recent developments in unmanned aerial vehicle (UAV) technology provide cost effective and real time applications for site specific data collection. For the mapping of herbage biomass (BM) on a hill pasture, we tested a UAV system with digital cameras (visible and near-infrared (NIR) camera). The field measurements were conducted on the grazing hill pasture at Hanwoo Improvement Office, Seosan City, Chungcheongnam-do Province, Korea on May 17 and June 27, 2014. Plant samples were obtained from 28 sites. A UAV system was used to obtain aerial photos from a height of approximately 50 m (approximately 30 cm spatial resolution). Normalized digital number (DN) values of Red and NIR channels were extracted from the aerial photos and a normalized differential vegetation index using DN ($NDVI_{dn}$) was calculated. The results show that the correlation coefficient between BM and $NDVI_{dn}$ was 0.88. For the precision management of hilly grazing pastures, UAV monitoring systems can be a quick and cost effective tool to obtain site-specific herbage BM data.

• Journal of the Korea Institute of Military Science and Technology
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• v.14 no.6
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• pp.993-1001
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• 2011

Unmanned ground vehicle for facility protection mostly uses model of territory for autonomous navigation. However, modeling of territory using several sensors is highly time consuming and sometimes inefficient for road application. Therefore, an estimation of drivable path based on features of road is required for high speed autonomous navigation on road. In this paper, an estimation method of drivable path using camera and 2D laser rangefinder is proposed. First, a vanishing point is estimated based on image data from CCD camera. Second, a road width is estimated based on range data from 2D laser rangefinder. Finally, the drivable path is estimated by fusing the vanishing point and the road width. The proposed method is tested on both well-structured road and unpaved road like cross-country situation.

• Journal of Advanced Navigation Technology
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• v.17 no.3
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• pp.354-360
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• 2013

A stereo vision analysis was performed for motion and depth control of unmanned vehicles. In stereo vision, the depth information in three-dimensional coordinates can be obtained by triangulation after identifying points between the stereo image. However, there are always triangulation errors due to several reasons. Such errors in the vision triangulation can be alleviated by careful arrangement of the camera position and orientation. In this paper, an approach to the determination of the optimal position and orientation of camera is presented for unmanned vehicles.

• Journal of Korea Multimedia Society
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• v.23 no.8
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• pp.1088-1098
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• 2020

This paper proposes an obstacle avoidance method using a depth polar grid. Depth information is a crucial factor for determining the safe path for collision-free navigation of unmanned aerial vehicles (UAVs) as it can perceive the distance to the obstacles effectively. However, the existing depth-camera-based approaches for obstacle avoidance require computational y expensive path planning algorithms. We propose a simple navigation method using the polar-grid of the depth information obtained from the camera with narrow field-of-view(FOV). The effectiveness of the approach was validated by a series of experiments using software-in-the-loop simulation in a realistic outdoor environment. The experimental results show that the proposed approach successfully avoids obstacles using a single depth camera with limited FOV.