• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2007.04a
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• pp.249-252
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• 2007

The objective of this research is to study the method to produce biotope map by using GIS. Surveying and analyzing the situation of biotope map in the country, it was found that biotope map should be produced to be utilized in establishing urban plan and environment preservation plan. Considering the history of materials, preparation method and type of use, the types of original materials can be classified into 3 types, namely, data based on configuration map, the existing thematic map and materials of surveying natural ecology. Biotope map is composed of configuration thematic map that shows the shape and position of surface, urban thematic map that is the standard of unit biotope shape and urban ecology map that shows the urban ecologic situation. Extracted and processed from the original material, each thematic map is produced as biotope map that shows the type of biotope. It is expected that biotope map can be utilized in the area of urban plan including establishment of basic urban plan and urban management plan as well as environment planning area including evaluation of environment influence, establishment of environment preservation plan, consolidated environment management for natural environment and life environment.

• Journal of the Korean housing association
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• v.23 no.5
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• pp.19-29
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• 2012

It is very necessary to know about child recognition of residential environment to plan and design an environment proper for children's growth and development. The research method using Cognitive Map, which may be defined as "an overall mental image of representation of the space and layout of a setting" can be a good tool for studying child recognition of residential environment. This study analyzed the child recognition of the size of home range, the number of residential environment elements, the types of Cognitive Map and the levels of Cognitive Map to understand the contents of child recognition about their residential environment. Subjects were 206 children in age6, 8 and 10 in Gwanju and Jeonnam area. As the result of the study, we found that 70% of child recognized 100~500 M as the size of home range, and that the number of the elements of residential environment was 7, average. And we also found that sequential map was more popular than spatial map in child's Cognitive Map type and that almost 60% of child respondents drew the Cognitive Map of level 1 complexity type. As the result of this study, we could know that the research method using Cognitive Map was very useful for understanding the child recognition of residential environment.

• Journal of Environmental Science International
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• v.24 no.6
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• pp.807-817
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• 2015

In this study the urban atmospheric environment map in Busan was made and it consist of the atmospheric environment element map and the atmospheric environment analysis map. The atmospheric environment element map covered the topography, the urban climate, the air pollutant emission, ozone and PM10 concentrations in Busan and the atmospheric environment analysis map included the thermal environment and the wind flow by using WRF meteorological numerical simulation. The meteorological elements from 2007 to 2011 in Busan were used in this study. As a result, in the center of Busan and Buk-gu along to the Nakdong river was the temperature high. To analyze the air flow of Busan 3 clusters depending on the wind direction were extracted with the cluster analysis. The results of the analysis on the detailed wind field of each cluster showed that the weak ventilation could be happened locally at the specific meteorological condition.

• The Journal of Korea Robotics Society
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• v.2 no.3
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• pp.227-233
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• 2007

Representing an environment as the probabilistic grids is effective to sense outlines of the environment in the mobile robot area. Outlines of an environment can be expressed factually by using the probabilistic grids especially if sonar sensors would be supposed to build an environment map. However, the difficult problem of a sonar such as a specular reflection phenomenon should be overcome to build a grid map through sonar observations. In this paper, the NRF(Neighborhood Recognition Factor) was developed for building a grid map in which the specular reflection effect is minimized. Also the reproduction rate of the gird map built by using NRF was analyzed with respect to a true map. The experiment was conducted in a home environment to verify the proposed technique.

• Journal of Institute of Control, Robotics and Systems
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• v.12 no.7
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• pp.693-699
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• 2006

An accurate and compact map is essential to an autonomous mobile robot system. For navigation, it is efficient to use an occupancy grid map because the environment is represented by probability distribution. But it is difficult to apply it to the large environment since it needs a large amount of memory proportional to the environment size. As an alternative, a topological map can be used to represent it in terms of the discrete nodes with edges connecting them. It is usually constructed by the Voronoi-like graphs, but in this paper the topological map is incrementally built based on the local grid map using the thinning algorithm. This algorithm can extract only meaningful topological information by using the C-obstacle concept in real-time and is robust to the environment change, because its underlying local grid map is constructed based on the Bayesian update formula. In this paper, the position probability is defined to evaluate the quantitative reliability of the end nodes of this thinning-based topological map (TTM). The global TTM can be constructed by merging each local TTM by matching the reliable end nodes determined by the position probability. It is shown that the proposed TTM can represent the environment accurately in real-time and it is readily extended to the global TTM.

• Journal of Korea Multimedia Society
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• v.6 no.7
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• pp.1286-1301
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• 2003

This paper introduces segmentation based environment modeling method and integration method using multiple environment map for constructing the realtime image-based panoramic navigation system. The segmentation-based environment modeling method is easy to implement on the environment map and can be used for environment modeling by extracting the depth value by the segmentation of the environment map. However, an environment model that is constructed using a single environment map has the problem of a blurring effect caused by the fixed resolution, and the stretching effect of the 3D model caused when information that does not exist on the environment map occurs due to the occlusion. In this paper, we suggest environment models integration method using multiple environment map to resolve the above problem. This method can express parallax effect and expand the environment model to express wide range of environment. The segmentation-based environment modeling method using multiple environment map can build a detail model with optimal resolution.

• The Journal of Korea Robotics Society
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• v.7 no.4
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• pp.252-258
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• 2012

This paper describes hierarchical semantic map building using the classified area information in home environments. The hierarchical semantic map consists of a grid, CAIG (Classified Area Information in Grid), and topological map. The grid and CAIG maps are used for navigation and motion selection, respectively. The topological map provides the intuitive information on the environment, which can be used for the communication between robots and users. The proposed semantic map building algorithm can greatly improve the capabilities of a mobile robot in various domains, including localization, path-planning and HRI (Human-Robot Interaction). In the home environment, a door can be used to divide an area into various sections, such as a room, a kitchen, and so on. Therefore, we used not only the grid map of the home environment, but also the door information as a main clue to classify the area and to build the hierarchical semantic map. The proposed method was verified through various experiments and it was found that the algorithm guarantees autonomous map building in the home environment.

• The Journal of Korea Robotics Society
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• v.9 no.2
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• pp.96-103
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• 2014

Global localization is one of the essential issues for mobile robot navigation. In this study, an indoor global localization method is proposed which uses a Kinect sensor and a monocular upward-looking camera. The proposed method generates an environment map which consists of a grid map, a ceiling feature map from the upward-looking camera, and a spatial feature map obtained from the Kinect sensor. The method selects robot pose candidates using the spatial feature map and updates sample poses by particle filter based on the grid map. Localization success is determined by calculating the matching error from the ceiling feature map. In various experiments, the proposed method achieved a position accuracy of 0.12m and a position update speed of 10.4s, which is robust enough for real-world applications.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.9 no.1
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• pp.102-110
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• 2000

This paper presents an algorithm of local map building for autonomous robot navigation using LASER range finder information. We develop a model of sensor output for a LASER range finder, and obtain an output data of the LASER range finder for a given environment. From the output data, a local map is obtained through the following procedures: (1) filtering of output data to remove noisy and unnecessary data, (2) comparison of filtered data with the original data to restore useful data, (3) thickening of the map obtained from the restored data, and (4) skeletonizing of the thickened map to get a final local map. Through some simulation studies, a map is obtained from the LASER range finder information for a given indoor environment, and is compared with the environment.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.71.1-71
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• 2001

In this paper, an improved method of environment map building and a region search algorithm for mobile robot are presented. For the environment map building of mobile robot, measurement data of ultrasonic sensors and certainty grid representation is usually used. In this case, inaccuracies due to the uncertainty of ultrasonic data are included in the map. In order to solve this problem, an environment map building method using a Bayesian model was proposed previously[5]. In this study, we present an improved method of probability map building that uses infrared sensors and shift division Gaussian probability distribution with the existing Bayesian update method using ultrasonic sensors. Also, a region search algorithm for ...