• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.603-605
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• 2003

Constructing a geo-spatial database of Graphic Information Systems(GIS) in various applications is suffering from the difficulty of data acquisition, which is labor-intensive and time consuming. In order to provide the spatial data rapidly and accurately, 4S-Van, a prototype mobile mapping system, has been developed. This paper presents a novel approach for an analysis for Mobile Mapping Systems. Furthermore, we discuss the accuracy of measurements using images acquired from the 4S-Van. The first part of this paper introduces accuracies of other mobile mapping systems. Then, we describe main features of the 4S-Van and our proposed method for an analysis accuracies, which can be applicable to other mobile mapping systems. The last part of paper concludes with a summary and our suggestions for implementation of mobile mapping system.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2010.04a
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• pp.311-313
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• 2010

This study is on the adapting vehicle-based mobile mapping system to the frequent unscheduled revision of 1:5000 scale national base map. We analyzed map layers which could be built by vehicle-based mobile mapping systems and studied surveying methods for each layers. Also, the methods of maintain surveying accuracy to satisfy accuracy standards of national base map were suggested. The maps of Yeouido, Hyangnam, and Suwon area were revised by vehicle-based mobile mapping system on a trial bases and possibility of utilizing vehicle-based mobile mapping system for map revision was analyzed. As a results it was revealed that vehicle-based mobile mapping systems were adequate for a irregular revision of national base map.

• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.705-708
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• 2005

Mobile Mapping Systems using the vehicle equipped the GPS, IMU, CCD Cameras is the effective system for the management of the road facilities, update of the digital map, and etc. They must provide users with the sensor data which is acquired by Mobile Mapping Systems in real-time so that users can process what they want by using the latest data. But it' s not an easy process because the amount of sensor data is very large, particularly image data to be transmitted. So it is necessary to reduce the amount of image data so that it is transmitted effectively. In this study, the effective method was suggested for the compression/decompression image data using the Wavelet Transformation and Huffman Coding. This technique will be possible to transmit of the geographic information effectively such as position data, attitude data, and image data acquired by Mobile Mapping Systems in the wireless internet environment when data is transmitted in real-time.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2010.04a
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• pp.281-284
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• 2010

Recently the development of digital based measurement sensor with which a variety of surveying equipment and methods are being developed. In the field of aerial mapping using GPS, INS and Digital Camera instead of Film based Camera. In case of aerial photogrammetry for mapping, it is effective on wide area. But it is ineffective on narrow area. Therefore, the research experimented that used LiDAR sensor based mobile mapping systems for modify and update about region of Suwon and Yeouido. From these results a possibility and an effectiveness analyzed and evaluated LiDAR sensor based mobile mapping systems.

• Spatial Information Research
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• v.17 no.1
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• pp.67-77
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• 2009

Mobile mapping systems with CCD cameras, GPS and IMU etc. can acquire massive photos and geographic informations along by roads. But it is easy to involve many errors or omissions of images and informations about roads and facilities with various files. And there were contained any conflicts or non-consistencies in massive mobile mapping data which were acquired by multiple survey teams in various survey regions. As an image tag standard, Exif helps us to encapsulate the precise GPS times and essential informations in the header of JPEG files and uses with the identification code for consistent managements of massive mobile mapping data in this paper. And Systematic management systems with data synchronization technology manage more consistently massive photos and their information.

• Journal of the Korean Institute of Intelligent Systems
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• v.17 no.4
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• pp.506-510
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• 2007

Digital Magnetic Compass(DMC) has a robust feature against interference in the indoor environment better than compass which is easily disturbed by electromagnetic sources or large ferromagnetic structures. Ultrasonic Sensors are cheap and can give relatively accurate range readings. So they ate used in Simultaneous Localization and Mapping(SLAM). In this paper, we study the Simultaneous Localization and Mapping(SLAM) of mobile robot in the indoor environment with Digital Magnetic Compass and Ultrasonic Sensors. Autonomous mobile robot is aware of robot's moving direction and position by the restricted data. Also robot must localize as quickly as possible. And in the moving of the mobile robot, the mobile robot must acquire a map of its environment. As application for the Simultaneous Localization and Mapping(SLAM) on the autonomous mobile robot system, robot can find the localization and the mapping and can solve the Kid Napping situation for itself. Especially, in the Kid Napping situation, autonomous mobile robot use Ultrasonic sensors and Digital Magnetic Compass(DMC)'s data for moving. The robot is aware of accurate location By using Digital Magnetic Compass(DMC).

• Journal of the Korean Institute of Intelligent Systems
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• v.20 no.1
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• pp.60-65
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• 2010

This paper describes the results of 2D mapping, feature detection and matching to create the surrounding environment in the mounted stereo camera on Mobile robot. Extract method of image's feature in real-time processing for quick operation uses the edge detection and Sum of Absolute Difference(SAD), stereo matching technique can be obtained through the correlation coefficient. To estimate the location of a mobile robot using ZigBee beacon and encoders mounted on the robot is estimated by Kalman filter. In addition, the merged gyro scope to measure compass is possible to generate map during mobile robot is moving. The Simultaneous Localization and Mapping (SLAM) of mobile robot technology with an intelligent robot can be applied efficiently in human life would be based.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.10
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• pp.36-41
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• 2017

The mobile mapping system first introduced at Ohio State University in 1991 is being developed in various forms as sensor technology develops. The mobile mapping system can acquire geospatial information around amoving object quickly using the information gathered using the position and attitude information of the moving object and the data from various sensors. The mobile mapping system can rapidly acquire large amounts of Geospatial information and MMS provides maximum productivity in the same measurement methods as existing GNSS and total stations. Currently, a variety of systems are being launched, mainly by foreign companies, and they are applied to the construction of geospatial information. On the other hand, the application of domestic technology development or production is insufficient. This paper provides basic data for the introduction of a mobile mapping system to geospatial information related business by conducting the status survey and feature analysis of a commercialized system focusing on the ground-based mobile mapping system. The research identified the current status and characteristics of high-priced, low-priced, indoor, and handheld mobile mapping systems based on vehicles and suggest that the recent system development trends are moving toward lowering the unit prices. The mobile mapping system is currently being developed as a platform for the application of geospatial information construction and the launch of low-cost models. The development of data processing technologies, such as automatic matching and the launch of low-cost models, are forming a basis for the application of mobile mapping systems in the field of geospatial information construction.

• International Journal of Control, Automation, and Systems
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• v.6 no.2
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• pp.282-287
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• 2008

In distributed mobile robot systems, autonomous robots accomplish complicated tasks through intelligent cooperation with each other. This paper presents behavior learning and online distributed evolution for cooperative behavior of a group of autonomous robots. Learning and evolution capabilities are essential for a group of autonomous robots to adapt to unstructured environments. Behavior learning finds an optimal state-action mapping of a robot for a given operating condition. In behavior learning, a Q-learning algorithm is modified to handle delayed rewards in the distributed robot systems. A group of robots implements cooperative behaviors through communication with other robots. Individual robots improve the state-action mapping through online evolution with the crossover operator based on the Q-values and their update frequencies. A cooperative material search problem demonstrated the effectiveness of the proposed behavior learning and online distributed evolution method for implementing cooperative behavior of a group of autonomous mobile robots.

• International Journal of Control, Automation, and Systems
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• v.5 no.3
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• pp.251-268
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• 2007

A Gaussian sum filter (GSF) is proposed in this paper on simultaneous localization and mapping (SLAM) for mobile robot navigation. In particular, the SLAM problem is tackled here for cases when only bearing measurements are available. Within the stochastic mapping framework using an extended Kalman filter (EKF), a Gaussian probability density function (pdf) is assumed to describe the range-and-bearing sensor noise. In the case of a bearing-only sensor, a sum of weighted Gaussians is used to represent the non-Gaussian robot-landmark range uncertainty, resulting in a bank of EKFs for estimation of the robot and landmark locations. In our approach, the Gaussian parameters are designed on the basis of minimizing the representation error. The computational complexity of the GSF is reduced by applying the sequential probability ratio test (SPRT) to remove under-performing EKFs. Extensive experimental results are included to demonstrate the effectiveness and efficiency of the proposed techniques.