• Spatial Information Research
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• v.23 no.3
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• pp.91-100
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• 2015

We developed a micro UAV based rapid mapping system that provides geospatial information of target areas in a rapid and automatic way. Users can operate the system easily although they are inexperienced in UAV operation and photogrammetric processes. For the aerial data acquisition, we constructed a micro UAV system mounted with a digital camera, a GPS/IMU, and a control board for the sensor integration and synchronization. We also developed a flight planning software and data processing software for the generation of geo-spatial information. The processing software operates automatically with a high speed to perform data quality control, image matching, georeferencing, and orthoimage generation. With the system, we have generated individual ortho-images within 30 minutes from 57 images of 3cm resolution acquired from a target area of $400m{\times}300m$.

• Spatial Information Research
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• v.16 no.3
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• pp.317-330
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• 2008

In this paper, the acquisition of digital imagery and the orthoimage generation were performed to set up working process. And another purpose of this thesis is to evaluate the accuracy of orthoimage by overlapping digital topographic map and digital cadastral map on it. The digital topographic map and digital cadastral map were superimposed on the orthoimage to check the accuracy as another approach of evaluation. The RMSE is ${\pm}0.364m$ in X direction and ${\pm}0.413m$ in Y direction with digital topographical maps(1/5,000). And the RMSE is ${\pm}1.283m$ in X direction and ${\pm}1.085m$ in Y direction with digital cadastral map. It is necessary for the application of a newly developed digital aerial camera to make an exact synchronization between GPS/IMU data and image data, use a technology for setting a standard image resolution and the number of ground control points.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.26 no.3
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• pp.311-320
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• 2008

A LIDAR can rapidly generate 3D points by densely sampling the surfaces of targets using laser pulses, which has been efficiently utilized to reconstruct 3D models of the targets automatically. Due to this advantage, LIDARs are increasingly applied to the fields of Defense and Security, for examples, being employed to intelligently guided missiles and manned/unmanned reconnaissance planes. For the prior verification of the LIDAR applicability, this study aims at generating simulated LIDAR data. Here, we derived the sensor equation by modelling the geometric relationships between the LIDAR sub-modules, such as GPS, IMU, LS and the systematic errors associated with them. Based on this equation, we developed a program to generate simulated data with the system parameters, the systematic errors, the flight trajectories and attitudes, and the reference terrain model given. This program had been applied to generating simulated LIDAR data for urban areas. By analyzing these simulated data, we verified the accuracy and usefulness of the simulation. The simulator developed in this study will provide economically various test data required for the development of application algorithms and contribute to the optimal establishment of the flight and system parameters.

• Journal of Korean Society for Geospatial Information Science
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• v.19 no.3
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• pp.91-98
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• 2011

Road signs are part of the traffic facilities intended to guide drivers to their destinations in a safe and comfortable manner. Due to the creation of new routes, changes to the old routes, and the deterioration of road signs, road signs do require efforts to do ongoing field investigations and put the results in a database. The purpose of this study was to propose methodologies to do field investigations and build a database for road signs efficiently. For that purpose, a mobile mapping system was designed for field investigations. The designed mobile mapping system was comprised of three cameras to produce image information about road signs, GPS/IMU/DMI to obtain information about the position and attitude of a vehicle, and a laser scanner to generate information about the locations of road signs and routes. Also proposed in the study was a procedure to automatically detect the areas of road signs in the road signs images and recognize their characters.

• Journal of Korean Society for Geospatial Information Science
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• v.16 no.2
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• pp.67-76
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• 2008

Recently, one of the most outstanding technological characteristics of aerial survey is an application of Direct Georeferencing, which is based on the integration of main sensing sensors such as aerial camera or Lidar with positioning sensors GPS and IMU. In addition, a variety of digital aerial mapping cameras is developed and supplied with the verification of their technical superiority and applicability. In accordance with this requirement, the development of a multi-looking aerial photographing system is just making 3-D information acquisition and texture mapping possible for the dead areas arising from building side and high terrain variation where the use of traditional phptogrammetry is not valid. However, the development of a multi-looking camera integrating different sensors and multi-camera array causes some problems to conduct time synchronization among sensors and their geometric and radiometric calibration. The establishment of a test field for aerial sensor calibration is absolutely necessary to solve this problem. Therefore, this paper describes investigations for photogrammetric Test Field of foreign countries and suggest an establishment scheme for domestic test field.

• Korean Journal of Remote Sensing
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• v.37 no.5_1
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• pp.1095-1109
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• 2021

The technology used to recognize the location and surroundings of autonomous vehicles is called SLAM. SLAM standsfor Simultaneously Localization and Mapping and hasrecently been actively utilized in research on autonomous vehicles,starting with robotic research. Expensive GPS, INS, LiDAR, RADAR, and Wheel Odometry allow precise magnetic positioning and mapping in centimeters. However, if it can secure similar accuracy as using cheaper Cameras and GPS data, it will contribute to advancing the era of autonomous driving. In this paper, we present a method for converging monocular camera with RTK-enabled GPS data to perform RMSE 33.7 cm localization and mapping on the urban road.

• ETRI Journal
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• v.30 no.1
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• pp.59-67
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• 2008

The necessity for the precise time synchronization of measurement data from multiple sensors is widely recognized in the field of global positioning system/inertial navigation system (GPS/INS) integration. Having precise time synchronization is critical for achieving high data fusion performance. The limitations and advantages of various time synchronization scenarios and existing solutions are investigated in this paper. A criterion for evaluating synchronization accuracy requirements is derived on the basis of a comparison of the Kalman filter innovation series and the platform dynamics. An innovative time synchronization solution using a counter and two latching registers is proposed. The proposed solution has been implemented with off-the-shelf components and tested. The resolution and accuracy analysis shows that the proposed solution can achieve a time synchronization accuracy of 0.1 ms if INS can provide a hard-wired timing signal. A synchronization accuracy of 2 ms was achieved when the test system was used to synchronize a low-grade micro-electromechanical inertial measurement unit (IMU), which has only an RS-232 data output interface.

• The Journal of Korea Robotics Society
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• v.9 no.3
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• pp.154-159
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• 2014

The Global Positioning System (GPS) is widely used to aid the navigation of aerial vehicles. However, the GPS cannot be used indoors, so alternative navigation methods are needed to be developed for micro aerial vehicles (MAVs) flying in GPS-denied environments. In this paper, a real-time three-dimensional (3-D) indoor navigation system and closed-loop control of a quad-rotor aerial vehicle equipped with an inertial measurement unit (IMU) and a low-cost light detection and ranging (LIDAR) is presented. In order to estimate the pose of the vehicle equipped with the two-dimensional LIDAR, an octree-based grid map and Monte-Carlo Localization (MCL) are adopted. The navigation results using the MCL are then evaluated by making a comparison with a motion capture system. Finally, the results are used for closed-loop control in order to validate its positioning accuracy during procedures for stable hovering and waypoint-following.

• International Journal of Highway Engineering
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• v.15 no.1
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• pp.155-161
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• 2013

PURPOSES: This study is to develop a road traffic sign recognition and automatic positioning for road facility management. METHODS: In this study, we installed the GPS, IMU, DMI, camera, laser sensor on the van and surveyed the car position, fore-sight image, point cloud of traffic signs. To insert automatic position of traffic sign, the automatic traffic sign recognition S/W developed and it can log the traffic sign type and approximate position, this study suggests a methodology to transform the laser point-cloud to the map coordinate system with the 3D axis rotation algorithm. RESULTS: Result show that on a clear day, traffic sign recognition ratio is 92.98%, and on cloudy day recognition ratio is 80.58%. To insert exact traffic sign position. This study examined the point difference with the road surveying results. The result RMSE is 0.227m and average is 1.51m which is the GPS positioning error. Including these error we can insert the traffic sign position within 1.51m CONCLUSIONS: As a result of this study, we can automatically survey the traffic sign type, position data of the traffic sign position error and analysis the road safety, speed limit consistency, which can be used in traffic sign DB.

• International Journal of Automotive Technology
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• v.8 no.6
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• pp.753-760
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• 2007

In this paper, a roll and pitch estimation algorithm using a set of accelerometers and wireless sensor networks(S/N) is presented for use in a passenger vehicle. While an inertial measurement unit(IMU) is generally used for roll/pitch estimation, performance may be degraded in the presence of longitudinal acceleration and yaw motion. To compensate for this performance degradation, a new roll and pitch estimation algorithm is proposed that uses an accelerometer array, global positioning system(GPS) and in-vehicle networks to get information from yaw rate and roll rate sensors. Angular acceleration and roll and pitch approximation are first calculated based on vehicle kinematics. A discrete Kalman filter is then applied to estimate both roll and pitch more precisely by reducing noise from the running engine and from road disturbance. Finally, the feasibility of the proposed algorithm is shown by comparing its performance experimentally with that of an IMU in the framework of an indoor test platform as well as a test vehicle.