• Title/Summary/Keyword: Environment Map

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Environment Map Based Disparity (환경맵 기반 디스페러티)

  • Ryoo Seung-Taek
    • Journal of Korea Multimedia Society
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    • v.9 no.1
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    • pp.109-118
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    • 2006
  • In this paper, we suggest the environment based disparity method that calculate the depth value of the objects from environment maps. This method using the disparity of the environment map can calculate the depth value from two environment map that acquire at different viewpoint. This method can decide the visibility of the object whether it is occluded others or not. Also, we can analogize the depth value of the object that does not relate the reference plane(in case of being in the air) and make three dimensional environment model using the proposed method

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Cloud Based Simultaneous Localization and Mapping with Turtlebot3 (Turtlebot3을 사용한 클라우드 기반 동시 로컬라이제이션 및 매핑)

  • Ahmed, Hamdi A.;Jang, Jong-Wook
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2018.05a
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    • pp.241-243
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    • 2018
  • In this paper, in Simultaneous localization and mapping (SLAM), the robot acquire its map of environment while simultaneously localizing itself relative to the map. Cloud based SLAM, allows us to optimizing resource and data sharing like map of the environment, which allows us, as one of shared available online map. Doing so, unless we add or remove significant change in our environment, the essence of rebuilding new environmental map are omitted to new mobile robot added to the environment. As result, the requirement of additional sensor are curtailed.

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The Development of a Map Building Algorithm using LADAR for Unmanned Ground Vehicle (레이저 레이다를 이용한 무인차량의 지도생성 알고리즘 개발)

  • Lee, Jeong-Yeob;Lee, Sang-Hoon;Kim, Jung-Ha;Han, Chang-Soo
    • Journal of Institute of Control, Robotics and Systems
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    • v.15 no.12
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    • pp.1246-1253
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    • 2009
  • To be high efficient for a navigation of unmanned ground vehicle, it must be able to distinguish between safe and hazardous regions in its immediate environment. We present an advanced method using laser range finder for building global 2D digital maps that include environment information. Laser range finder is used for mapping of obstacles and driving environment in the 2D laser plane. Rotary encoders are used for localization of UGV. The main contributions of this research are the development of an algorithm for global 2D map building and it will turn a UGV navigation based on map matching into a possibility. In this paper, a map building algorithm will be introduced and an assessment of algorithm reliability is judged at an each environment.

Reduction in Sample Size for Efficient Monte Carlo Localization (효율적인 몬테카를로 위치추정을 위한 샘플 수의 감소)

  • Yang Ju-Ho;Song Jae-Bok
    • Journal of Institute of Control, Robotics and Systems
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    • v.12 no.5
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    • pp.450-456
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    • 2006
  • Monte Carlo localization is known to be one of the most reliable methods for pose estimation of a mobile robot. Although MCL is capable of estimating the robot pose even for a completely unknown initial pose in the known environment, it takes considerable time to give an initial pose estimate because the number of random samples is usually very large especially for a large-scale environment. For practical implementation of MCL, therefore, a reduction in sample size is desirable. This paper presents a novel approach to reducing the number of samples used in the particle filter for efficient implementation of MCL. To this end, the topological information generated through the thinning technique, which is commonly used in image processing, is employed. The global topological map is first created from the given grid map for the environment. The robot then scans the local environment using a laser rangefinder and generates a local topological map. The robot then navigates only on this local topological edge, which is likely to be similar to the one obtained off-line from the given grid map. Random samples are drawn near the topological edge instead of being taken with uniform distribution all over the environment, since the robot traverses along the edge. Experimental results using the proposed method show that the number of samples can be reduced considerably, and the time required for robot pose estimation can also be substantially decreased without adverse effects on the performance of MCL.

Quantitative Assessment of Nonpoint Source Load in Nakdong River Basin

  • Kwon, Heon-Gak;Lee, Jae-Woon;Yi, Youn-Jeong;Cheon, Se-Uk
    • Journal of Environmental Science International
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    • v.23 no.1
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    • pp.7-23
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    • 2014
  • This study estimates unit for the nonpoint source(NPS), classified according to the existing Level-1(large scale) land cover map, by monitoring the measurement results from each Level-2(medium scale) land cover map, and verifies the applicability by comparison with previously calculated units using the Level-1 land cover map. The NPS pollutant loading for a basin is evaluated by applying the NPS pollutant unit to Dongcheon basin using the Level-2 land cover map. In addition, the BASINS/HSPF(Better Assessment Science Integrating point & Non-point Sources/Hydrological Simulation Program-Fortran) model is used to evaluate the reliability of the NPS pollutant loading computation by comparing the loading during precipitation in the Dongcheon basin. The NPS pollutant unit for the Level-2 land cover map is computed based on precipitation measured by the Sangju observatory in the Nakdong River basin. Finally, the feasibility of the NPS pollutant loading computation using a BASINS/HSPF model is evaluated by comparing and analyzing the NPS pollutant loading when estimated unit using the Level-2 land cover map and simulated using the BASINS/HSPF models.

Development of a sonar map based position estimation system for an autonomous mobile robot operating in an unknown environment (미지의 영역에서 활동하는 자율이동로봇의 초음파지도에 근거한 위치인식 시스템 개발)

  • 강승균;임종환
    • 제어로봇시스템학회:학술대회논문집
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    • 1997.10a
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    • pp.1589-1592
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    • 1997
  • Among the prerequisite abilities (perception of environment, path planning and position estimation) of an autonomous mobile robot, position estimation has been seldom studied by mobile robot researchers. In most cases, conventional positioin estimation has been performed by placing landmarks or giving the entrire environmental information in advance. Unlikely to the conventional ones, the study addresses a new method that the robot itself can select distinctive features in the environment and save them as landmarks without any a priori knowledge, which can maximize the autonomous behavior of the robot. First, an orjentaion probaility model is applied to construct a lcoal map of robot's surrounding. The feature of the object in the map is then extracted and the map is saved as landmark. Also, presented is the position estimation method that utilizes the correspondence between landmarks and current local map. In dong this, the uncertainty of the robot's current positioin is estimated in order to select the corresponding landmark stored in the previous steps. The usefulness of all these approaches are illustrated with the results porduced by a real robot equipped with ultrasonic sensors.

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CHARACTERISTICS AND PRACTICAL USE OF THE NATIONAL ENVIRONMENTAL ASSESSMENT MAP IN KOREA

  • Jeon, Seong-Woo;Lee, Chong-Soo;Song, Won-Kyong;Lee, Moung-Jin;Lee, Woo-Kyun
    • Proceedings of the KSRS Conference
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    • v.2
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    • pp.876-879
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    • 2006
  • This study was performed for developing the National Environmental Assessment Map (NEAM) in Korea and presenting the application method of NEAM. This NEAM adopted the least indicator method and uses a Geographic Information System (GIS). This map is made through evaluation of 67 items, including greenbelt status and biodiversity. As a result, the construction of NEAM was defined as a process of identifying land use to scientifically assess the physical and environmental value of land and classify conservation value into several grades for the sustainable management of environmental resources. After applying NEAM criteria of five degrees to the whole of Korea, Grade I, showing the highest conservation value, accounted for 45.6% by land area of NEAM. Grades II, III, IV, and Ⅴlikewise accounted for, respectively, 23.6%, 17.9%, 6.3%, and the lowest conservation value of 6.6%. This map can be widely used in, for example, urban and regional planning, development planning, and environment impact assessment.

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A New Mavigation Method in Virtual Environment

  • Koo, Eun-Young;Kon, Tae-Wook;Choy, Yoon-Chul
    • Proceedings of the Korean Information Science Society Conference
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    • 2000.04b
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    • pp.643-645
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    • 2000
  • This paper puts emphasis on navigation in virtual environment, which is one of the major interfaces for the interactivity between human and virtual environment in virtual reality circumstances and worlds. It proposes a new navigation method: 2d Map-Based navigation, which prevents user's spatial lost in 3D Virtual Environment. The 2D Map-Based Navigation is composed of three major processes, Constant Velocity Navigation, Collision Detection and Avoidance, and Path Adjustment. The 2D Map-Based Navigation can reduce user's difficulties and improve user's sense of presence and reality in the virtual environments. The experiment study proved that the 2D Map-Based Navigation is a very natural, straightforward and useful navigation interface in the virtual environment.

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Introduction of the New Evaluation Criteria in the Forest Sector of Environmental Conservation Value Map Using LiDAR (LiDAR를 활용한 국토환경성평가지도 산림부문 신규 평가항목의 도입 가능성 평가)

  • Jeon, Seong-Woo;Hong, Hyun-Jung;Lee, Chong-Soo;Lee, Woo-Kyun;Sung, Hyun-Chan
    • Journal of the Korean Society of Environmental Restoration Technology
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    • v.10 no.5
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    • pp.20-30
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    • 2007
  • Environmental Conservation Value Assessment Map (ECVAM) is the class map to divide the national land into conservation areas and development areas based on legal and ecological assessment criteria. It contributes to enhancements of the efficiency and the scientificity when framing a policy in various fields including the environment. However, it is impossible to understand the multiphase vegetation structure as data on judging the national forest class in ECVAM are restricted to areal information of Ecological Nature Status, Degree of Green Naturality and Forest Map. This point drops the reliability of ECVAM. Therefore we constructed vegetation information using LiDAR (Light Detection And Raging) technology. We generated Biomass Class Maps as final results of this study, to introduce the new forest assessment criterion in ECVAM that alternates or makes up for existing forest assessment criteria. And then, we compared these with Forest Map and Landsat TM NDVI image. As a result, biomass classes are generally higher than stand age classes and DBH classes of Vegetation Map, and lower than NDVI of Landsat TM image because of the difference of time on data construction. However distributions between these classes are mostly similar. Therefore we estimates that it is possible to apply the biomass item to the new forest assessment criterion of ECVAM. The introduction of the biomass in ECVAM makes it useful to detect the vegetation succession, to adjust the class of the changed zone since the production of Vegetation Map and to rectify the class error of Vegetation Map because variations on tree heights, forest area, gaps between trees, vegetation vitality and so on are acquired as interim findings in process of computing biomass.

A Study on the Standardization Model of Noise Map (소음오염도의 지도표현 표준화 모델)

  • 조기호
    • Journal of KSNVE
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    • v.10 no.3
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    • pp.410-422
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    • 2000
  • This paper proposes a model of standardized noise map in korea, The standardization of noise map is accomplished by standardizing the way of map description and by applying international noise mapping criteria to Korean environment. The proposed model can be an useful star or the production of national standardized noise map in Korea.

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