• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.36 no.3
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• pp.185-196
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• 2018

In order to overcome the problem that outdoor and indoor spatial information service are separately utilized, an integration service system of spatial information that is linked from outdoor to indoor has been implemented. As a result of the study, "0001.xml" corresponding to the file index key value, which is the service connection information in the building information of the destination, was extracted from the prototype verification of the system, the search word of 'Kim AB' was transmitted to the indoor map server and converted from the outdoor map service to the indoor map service through confirmation of the navigation service connected information, using service linkage information and search words of the indoor map service was confirmed that the route was displayed from the entrance of the building to the destination in the building through the linkage search DB (Database) table and the search query. Therefore, through this study was examined the possibility of linking indoor and outdoor DB through vector spatial information integration service system. The indoor map and the map engine were implemented based on the same vector map format as the outdoor map engine, it was confirmed that the connectivity of the map engine can be applied.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.5
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• pp.1881-1903
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• 2015

With the fast-developing of mobile terminals, positioning techniques based on fingerprinting method draws attention from many researchers even world famous companies. To conquer some shortcomings of the existing fingerprinting systems and further improve its performance, we propose a radio map building and updating technique, which is able to customize the spatial and temporal dependency of radio maps. The method includes indoor propagation and penetration modeling and the analysis of human traffic. Based on the combination of Ray-Tracing Algorithm, Finite-Different Time-Domain and Rough Set Theory, the approach of indoor propagation modeling accurately represents the spatial dependency of the radio map. In terms of temporal dependency, we specifically study the factor of moving people in the interest area. With measurement and statistics, the factor of human traffic is introduced as the temporal updating component. We improve our existing indoor positioning system with the proposed building and updating method, and compare the localization accuracy. The results show that the enhanced system can conquer the influence caused by moving people, and maintain the confidence probability stable during week, which enhance the actual availability and robustness of fingerprinting-based indoor positioning system.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.20 no.2
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• pp.133-138
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• 2011

RFID system can be used to improve object recognition, map building and localization for robot area. A novel method of indoor navigation system for a mobile robot is proposed using RFID technology. The mobile robot With a RFID reader and antenna is able to find what obstacles are located where in circumstance and can build the map similar to indoor circumstance by combining RFID information and distance data obtained from sensors. Using the map obtained, the mobile robot can avoid obstacles and finally reach the desired goal by $A^*$ algorithm. 3D map which has the advantage of robot navigation and manipulation is able to be built using z dimension of products. The proposed robot navigation system is proved to apply for SLAM and path planning in unknown circumstance through numerous experiments.

• Journal of Institute of Control, Robotics and Systems
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• v.22 no.9
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• pp.745-752
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• 2016

We suggest an efficient Simultaneous Localization and 3D Polygon Map Building (SLAM) method with Kinect depth sensor for mobile robots in indoor environments. In this method, Kinect depth data is separated into row planes so that scan line segments are on each row plane. After grouping all scan line segments from all row planes into line groups, a set of 3D Scan polygons are fitted from each line group. A map matching algorithm then figures out pairs of scan polygons and existing map polygons in 3D, and localization is performed to record correct pose of the mobile robot. For 3D map-building, each 3D map polygon is created or updated by merging each matched 3D scan polygon, which considers scan and map edges efficiently. The validity of the proposed 3D SLAM algorithm is revealed via experiments.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.724-728
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• 2005

This paper represents a development of a range finder sensor module for indoor 2-D mapping and modified Hough transformation for map building. A range finder sensor module has been developed by using optic PSD (Position Sensitive Detector) sensor array at a low price. While PSD sensor is cost effective and light weighting, it has switching noise and white noise. To remove these noises, we propose a heuristic filter. For line-based map building, also we proposed advanced Hough transformation and navigation algorithm. Some experiments were illustrated for the validity of the developed system.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.41 no.8
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• pp.986-994
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• 2016

In this paper, we proposed ultrasonic radar module and fixed module for the 2D indoor map building and from each of the modules, we can see the possibilities, limitations and considerations. And finally show the result of building actual 2D indoor map from the modules. Recently there are lots of works for the building indoor map by spotlight on the simultaneous localization and mapping (SLAM). And the LiDAR, ultrasonic, camera sensors are usually used for this work. Especially the LiDAR sensor have a higher resolution and wider detection range more than the ultrasonic sensor, but also there are limitation in the size of module, higher cost, much more throughput of processing data, and weaker to use in various indoor environment noises. So from these reasons, in this paper we could verify that proposed modules and schemes have a enough performance to build the 2D indoor map instead of using LiDAR and camera sensor with minimum number of ultrasonic sensors and less throughput of processing data.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2022.11a
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• pp.47-48
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• 2022

The positioning technology that measures the position of a person or object is a key technology to deal with the location of the real coordinate system or converge the real and virtual worlds, such as digital twins, augmented reality, virtual reality, and autonomous driving. In estimating the location of a person or object at an indoor construction site, there are restrictions that it is impossible to receive location information from the outside, the communication infrastructure is insufficient, and it is difficult to install additional devices. Therefore, this study tested the direct sparse odometry algorithm, one of the visual Simultaneous Localization and Mapping (vSLAM) that estimate the current location and surrounding map using only image information, at an indoor construction site and analyzed its applicability as an indoor positioning technology. As a result, it was found that it is possible to properly estimate the surrounding map and the current location even in the indoor construction site, which has relatively few feature points. The results of this study can be used as reference data for researchers related to indoor positioning technology for construction sites in the future.

• Journal of information and communication convergence engineering
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• v.8 no.6
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• pp.709-715
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• 2010

This paper represents a map building and localization system for mobile robot. Map building and navigation is a complex problem because map integrity cannot be sustained by odometry alone due to errors introduced by wheel slippage, distortion and simple linealized odometry equation. For accurate localization, we propose sensor fusion system using encoder sensor and indoor GPS module as relative sensor and absolute sensor, respectively. To build a map, we developed a sensor based navigation algorithm and grid based map building algorithm based on Embedded Linux O.S. A wall following decision engine like an expert system was proposed for map building navigation. We proved this system's validity through field test.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2010.05a
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• pp.79-80
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• 2010

• Journal of Korea Society of Digital Industry and Information Management
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• v.5 no.3
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• pp.39-45
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• 2009

In this paper we present a cleaning robot system for an autonomous mobile robot. Our robot performs goal reaching tasks into unknown indoor environments by using sensor fusion. The robot's operation objective is to clean floor or any other applicable surface and to build a map of the surrounding environment for some further purpose such as finding the shortest path available. Using its cleaning robot system for an autonomous mobile robot can move in various modes and perform dexterous tasks. Performance of the cleaning robot system is better than a fixed base redundant robot in avoiding singularity and obstacle. Sensor fusion using the clean robot improves the performance of the robot with redundant freedom in workspace and Map-Building. In this paper, Map-building of the cleaning robot has been studied using sensor fusion. A sequence of this alternating task execution scheme enables the clean robot to execute various tasks efficiently. The proposed algorithm is experimentally verified and discussed with a cleaning robot, KCCR.