• Journal of the Korean Society for Precision Engineering
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• v.26 no.8
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• pp.62-71
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• 2009

In mobile robotics, ultrasonic sensors became one of the most popular devices for collision avoidance and navigation primarily due to data robustness, the easy availability of low-cost systems, their compact size, simple circuits, and their ease in interfacing with computers. However, ultrasonic sonic sensors are subject to noise which results in inaccuracy of mapping and localization of the robot. This paper introduces a new approach to enhance environmental maps based on ultrasonic range data using linear interpolation and Newton interpolation. The simulation and experimental results show that the proposed method improves of the accuracy of the map through better distance estimation between the mobile robot and obstacles.

• The Journal of Korea Robotics Society
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• v.8 no.4
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• pp.256-265
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• 2013

A local map-based exploration algorithm for mobile robots is presented. Segmented frontiers and their relative transformations constitute a tree structure. By the proposed efficient frontier segmentation and a local map management method, a robot can reduce the unknown area and update the local grid map which is assigned to each frontier node. Although this local map-based exploration method uses only local maps and their adjacent node information, mapping completion and efficiency can be greatly improved by merging and updating the frontier nodes. Also, we suggest appropriate graph search exploration methods for corridor and hall environments. The simulation demonstrates that the entire environment can be represented by well-distributed frontier nodes.

• Spatial Information Research
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• v.21 no.1
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• pp.1-13
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• 2013

This paper describes a GIS framework for geo-semantic information retrieval in mobile computing environments. We built geographic ontologies of POI (point of interest) and weather information for use in the combination of semantic, spatial, and temporal functions in a fully integrated database. We also implemented a geo-semantic app for Android-based smartphones that can extract more appropriate POIs in terms of user contexts and geographic ontologies and can visualize the POIs using Google Maps API (application programming interface). The feasibility tests showed our geo-semantic app can provide pertinent POI information according to mobile user contexts such as location, time, schedule, and weather. We can discover a baking CVS (convenience store) in the test of bakery search and can find out a drive-in theater for a not rainy day, which are good examples of the geo-semantic query using semantic, spatial, and temporal functions. As future work, we should need ontology-based inference systems and the LOD (linked open data) of various ontologies for more advanced sharing of geographic knowledge.

• 제어로봇시스템학회:학술대회논문집
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• 1991.10a
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• pp.652-657
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• 1991

Up to date, application areas of mobile robots have been expanded. In addition, Many types of LRF(Laser Range Finder) systems have been developed to acquire three dimensional information about unknown environments. However in real world, because of various noises (sunlight, fluorescent light), it is difficult to separate reflected laser light from these noise. To overcome the previous restriction, we have developed a new type vision system which enables a mobile robot to measure the distance to a object located 1-5 (m) ahead with an error than 2%. The separation and detection algorithm used in this system consists of pulse phase difference method and multi-stripe structured light. The effectiveness and feasibility of the proposed vision system are demonstrated by 3-D maps of detected objects and computation time analysis.

• ETRI Journal
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• v.43 no.4
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• pp.617-629
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• 2021

Although the actual visual simultaneous localization and mapping (SLAM) algorithms provide highly accurate tracking and mapping, most algorithms are too heavy to run live on embedded devices. In addition, the maps they produce are often unsuitable for path planning. To mitigate these issues, we propose a completely closed-loop online dense RGB-D SLAM algorithm targeting autonomous indoor mobile robot navigation tasks. The proposed algorithm runs live on an NVIDIA Jetson board embedded on a two-wheel differential-drive robot. It exhibits lightweight three-dimensional mapping, room-scale consistency, accurate pose tracking, and robustness to moving objects. Further, we introduce a navigation strategy based on the proposed algorithm. Experimental results demonstrate the robustness of the proposed SLAM algorithm, its computational efficiency, and its benefits for on-the-fly navigation while mapping.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.37 no.2
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• pp.45-53
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• 2019

RGB-D SLAM (Simultaneous Localization and Mapping) refers to the technology of using deep camera as a visual sensor for SLAM. In view of the disadvantages of high cost and indefinite scale in the construction of maps for laser sensors and traditional single and binocular cameras, a method for creating three-dimensional map of indoor environment with deep environment data combined with RGB-D SLAM scheme is studied. The method uses a mobile robot system equipped with a consumer-grade RGB-D sensor (Kinect) to acquire depth data, and then creates indoor three-dimensional point cloud maps in real time through key technologies such as positioning point generation, closed-loop detection, and map construction. The actual field experiment results show that the average error of the point cloud map created by the algorithm is 0.0045m, which ensures the stability of the construction using deep data and can accurately create real-time three-dimensional maps of indoor unknown environment.

• Journal of Cadastre & Land InformatiX
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• v.46 no.1
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• pp.59-74
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• 2016

The collapses of retaining walls or embankments, the soil erosion and landslides around urban areas are occurring by heavy rainfalls because of the recent climate change. This study conducts the soil erosion modeling, while applying the spatial information such as soil maps, DEM and landcover maps to the RUSLE model. Especially this study draws up the soil erosion grade map and the unit soil erosion grade map by parcels through coupling the soil erosion with the cadastral map, and by that can calculate the number of parcels by soil erosion grades. Also the sediment disaster information system based on the mobile GIS is developed to identify the soil erosion grades of site in the urban plannings and the construction fields. The sediment disaster information system can identify the present conditions of the registers of lands, buildings and roads, and confirm the RUSLE factors, the soil erosion, the sediment disaster grades by parcels. Also it is anticipated that this system can support the sediment disaster work of site effectively through searching the locations and attributes of the specific parcels by Administrative Dong and the soil erosion grades.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.11B
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• pp.945-952
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• 2006

In hierarchical mobile IPv6 networks, when an inter-domain handover occurs, mobile nodes suffer from excessive signaling traffic and long handover latency, resulting in possible disruption of ongoing connections. Further, the selection of MAP and its load status critically affect the overall system performance. Therefore, we propose a dynamic MAP selection scheme that seeks to distribute load among MAPs as well as reduces inter-domain handovers. Performance is evaluated from not only an analytic model of average signaling cost but also simulation. The analytical and simulation results show that our proposed scheme improves load distributedness and reduces inter-domain handovers and signaling cost compared to another existing IETF based approach.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.65 no.12
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• pp.2138-2144
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• 2016

People with visual disabilities suffer environmentally, socially, and technologically. Navigating through places and recognizing objects are already a big challenge for them who require assistance. This study aimed to develop an android-based assistive application for the visually impaired. Specifically, the study aimed to create a system that could aid visually impaired individuals performs significant tasks through object recognition and identifying locations through GPS and Google Maps. In this study, the researchers used an android phone allowing a visually impaired individual to go from one place to another with the aid of the application. Google Maps is integrated to utilize GPS in identifying locations and giving distance directions and the system has a cloud server used for storing pinned locations. Furthermore, Haar-like features were used in object recognition.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.2
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• pp.1064-1079
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• 2019

Information security has become increasingly important with the rapid development of mobile devices and internet. An efficient encryption system is a key to this end. In this paper, we propose an image encryption method based on the cross diffusion of two chaotic maps. We use two chaotic sequences, namely the Logistic map and the Chebyshev map, for key generation which has larger security key space than single one. Moreover, we use these two sequences for further image encryption diffusion which decreases the correlation of neighboring pixels significantly. We conduct extensive experiments on several well-known images like Lena, Baboon, Koala, etc. Experimental results show that our algorithm has the characteristics of large key space, fast, robust to statistic attack, etc.