• Title/Summary/Keyword: Indoor map building

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Generation of Indoor Network by Crowdsourcing (크라우드 소싱을 이용한 실내 공간 네트워크 생성)

  • Kim, Bo Geun;Li, Ki-Joune;Kang, Hae-Kyong
    • Spatial Information Research
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    • v.23 no.1
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    • pp.49-57
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    • 2015
  • Due to high density of population and progress of high building construction technologies, the number of high buildings has been increasing. Several information services have been provided to figure out complex indoor structures of building such as indoor navigations and indoor map services. The most fundamental information for these services are indoor network information. Indoor network in building provides topological connectivity between spaces unlike geometric information of buildings. In order to make indoor network information, we have to edit network manually or derive network properties based on the geometric data of buildings. This process is not easy for complex buildings. In this paper, we suggest a method to generate indoor network automatically based on crowdsourcing. From the collected individual trajectories, we derive indoor network information with crowdsourcing. We validate our method with a sample set of trajectory data and the result shows that our method is practical if the indoor positioning technology is reasonably accurate.

Sensor Fusion-Based Semantic Map Building (센서융합을 통한 시맨틱 지도의 작성)

  • Park, Joong-Tae;Song, Jae-Bok
    • Journal of Institute of Control, Robotics and Systems
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    • v.17 no.3
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    • pp.277-282
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    • 2011
  • This paper describes a sensor fusion-based semantic map building which can improve the capabilities of a mobile robot in various domains including localization, path-planning and mapping. To build a semantic map, various environmental information, such as doors and cliff areas, should be extracted autonomously. Therefore, we propose a method to detect doors, cliff areas and robust visual features using a laser scanner and a vision sensor. The GHT (General Hough Transform) based recognition of door handles and the geometrical features of a door are used to detect doors. To detect the cliff area and robust visual features, the tilting laser scanner and SIFT features are used, respectively. The proposed method was verified by various experiments and showed that the robot could build a semantic map autonomously in various indoor environments.

A localization method using sensor fusion system (다중 센서 시스템을 이용한 로봇 위치 인식 제어 방법)

  • Lim, Jea-Gyun;You, Jong-Jin;Hyun, Woong-Keun
    • Proceedings of the KIEE Conference
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    • 2007.07a
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    • pp.1767-1768
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    • 2007
  • This paper represents a map building system of Embedded Linux mobile robot. We propose a localization method which uses multiple sensors such as indoor GPS and encoder sensor for simultaneous map building system. In this paper we proposed a multiple sensor system for SLAM. For this, we developed a sensor based navigation algorithm and grid based map building algorithm under the Embedded Linux O.S. We proved this system's validity through field test

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Vision Based Map-Building Using Singular Value Decomposition Method for a Mobile Robot in Uncertain Environment

  • Park, Kwang-Ho;Kim, Hyung-O;Kee, Chang-Doo;Na, Seung-Yu
    • 제어로봇시스템학회:학술대회논문집
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    • 2001.10a
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    • pp.101.1-101
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    • 2001
  • This paper describes a grid mapping for a vision based mobile robot in uncertain indoor environment. The map building is a prerequisite for navigation of a mobile robot and the problem of feature correspondence across two images is well known to be of crucial Importance for vision-based mapping We use a stereo matching algorithm obtained by singular value decomposition of an appropriate correspondence strength matrix. This new correspondence strength means a correlation weight for some local measurements to quantify similarity between features. The visual range data from the reconstructed disparity image form an occupancy grid representation. The occupancy map is a grid-based map in which each cell has some value indicating the probability at that location ...

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Fast Local Indoor Map Building Using a 2D Laser Range Finder (2차원 레이저 레이진 파이더를 이용한 빠른 로컬 실내 지도 제작)

  • Choi, Ung;Koh, Nak-Yong;Choi, Jeong-Sang
    • Proceedings of the Korean Society of Machine Tool Engineers Conference
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    • 1999.10a
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    • pp.99-104
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    • 1999
  • This paper proposes an efficient method constructing a local map using the data of a scanning laser range finder. A laser range finder yields distance data of polar form, that is, distance data corresponding to every scanning directions. So, the data consists of directional angle and distance. We propose a new method to find a line fitting with a set of such data. The method uses Log-Hough Transformation. Usually, map building from these data requires some transformations between different coordinate systems. The new method alleviates such complication. Also, the method simplifies computation for line recognition and eliminates the slope quantization problems inherent in the classical Cartesian Hough transform method. To show the efficiency of the proposed method, it is applied to find a local map using the data from a laser range finder PLS(Proximity Laser Scanner, made by SICK).

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Optimization-based humanoid robot navigation using monocular camera within indoor environment

  • Han, Young-Joong;Kim, In-Seok;Hong, Young-Dae
    • ETRI Journal
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    • v.40 no.4
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    • pp.446-457
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    • 2018
  • Robot navigation allows robot mobility. Therefore, mobility is an area of robotics that has been actively investigated since robots were first developed. In recent years, interest in personal service robots for homes and public facilities has increased. As a result, robot navigation within the home environment, which is an indoor environment, is being actively investigated. However, the problem with conventional navigation algorithms is that they require a large computation time for their building mapping and path planning processes. This problem makes it difficult to cope with an environment that changes in real-time. Therefore, we propose a humanoid robot navigation algorithm consisting of an image processing and optimization algorithm. This algorithm realizes navigation with less computation time than conventional navigation algorithms using map building and path planning processes, and can cope with an environment that changes in real-time.

Real-time Intelligent Exit Path Indicator Using BLE Beacon Enabled Emergency Exit Sign Controller

  • Jung, Joonseok;Kwon, Jongman;Jung, Soonho;Lee, Minwoo;Mariappan, Vinayagam;Cha, Jaesang
    • International journal of advanced smart convergence
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    • v.6 no.1
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    • pp.82-88
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    • 2017
  • Emergency lights and exit signs are an indispensable part of safety precautions for effective evacuation in case of emergency in public buildings. These emergency sign indicates safe escape routes and emergency doors, using an internationally recognizable sign. However visibility of those signs drops drastically in case of emergency situations like fire smoke, etc. and loss of visibility causes serious problems for safety evacuation. This paper propose a novel emergency light and exit sign built-in with Bluetooth Low Energy (BLE) Beacon to assist the emergency self-guiding evacuation using devices for crisis and emergency management to avoid panic condition inside the buildings. In this approach, the emergency light and exit sign with the BLE beacons deployed in the indoor environments and the smart devices detect their indoor positions, direction to move, and next exit sign position from beacon messages and interact with map server in the Internet / Intranet over the available LTE and/or Wi-Fi network connectivity. The map server generate an optimal emergency exit path according to the nearest emergency exit based on a novel graph generation method for less route computation for each smart device. All emergency exit path data interfaces among three system components, the emergency exit signs, map server, and smart devices, have been defined for modular implementation of our emergency evacuation system. The proposed exit sign experimental system has been deployed and evaluated in real-time building environment thoroughly and gives a good evidence that the modular design of the proposed exit sign system and a novel approach to compute emergency exit path route based on the BLE beacon message, map server, and smart devices is competitive and viable.

Implementation of an Indoor Mobile Robot and Environment Recognition using Line Histogram Method (실내 자율주행 로봇의 구현 및 라인 히스토그램을 이용한 환경인식)

  • Moon, Chan-Woo;Lee, Young-Dae
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.9 no.2
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    • pp.45-50
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    • 2009
  • The environment exploration is an essential process for indoor robots such as clean robot and security robot. Apartment house and office building has common frame structure, but internal arrangement of each room may be slightly different. So, it is more convenient to use a common frame map than to build a new map at every time the arrangement is changed. In this case, it is important to recognize invariant features such as wall, door and window. In this paper, an indoor mobile robot is implemented, and by using the laser scanner data and line segment histogram with respect to segment orientation and distance, an environment exploration method is presented and tested. This robot is fitted with a laser scanner, gyro sensor, ultra sonic sensor and IR sensor, and programed with C language.

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Feature based Map Building by using Orientation Information in a Grid Map (그리드지도의 방향정보를 이용한 형상지도 작성)

  • Kang, Seung-Kyun;Lim, Jong-Hwan
    • Journal of the Korean Society for Precision Engineering
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    • v.22 no.12 s.177
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    • pp.61-69
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    • 2005
  • This paper presents an efficient method of extracting line segments from the occupancy grids in a grid map. The grid map is composed of 2-D grids that have both the occupancy and orientation probabilities using sonar sensors. We evaluate the orientation information of every grid when the occupancy probability of the grid is updated from sonar range data. To find the shape of an object in the map from orientation information, the orientations are clustered into several groups according to their values. The line segments are, then, extracted from the clusters based on Hough transform. Finally, a feature-based map is built with these line segments. The proposed method is illustrated with the results produced by sets of experiments in an indoor environment.

Global Map Building and Navigation of Mobile Robot Based on Ultrasonic Sensor Data Fusion

  • Kang, Shin-Chul;Jin, Tae-Seok
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.7 no.3
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    • pp.198-204
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    • 2007
  • In mobile robotics, ultrasonic sensors became standard devices for collision avoiding. Moreover, their applicability for map building and navigation has exploited in recent years. In this paper, as the preliminary step for developing a multi-purpose autonomous carrier mobile robot to transport trolleys or heavy goods and serve as robotic nursing assistant in hospital wards. The aim of this paper is to present the use of multi-sensor data fusion such as ultrasonic sensor, IR sensor for mobile robot to navigate, and presents an experimental mobile robot designed to operate autonomously within both indoor and outdoor environments. The global map building based on multi-sensor data fusion is applied for recognition an obstacle free path from a starting position to a known goal region, and simultaneously build a map of straight line segment geometric primitives based on the application of the Hough transform from the actual and noisy sonar data. We will give an explanation for the robot system architecture designed and implemented in this study and a short review of existing techniques, Hough transform, since there exist several recent thorough books and review paper on this paper. Experimental results with a real Pioneer DX2 mobile robot will demonstrate the effectiveness of the discussed methods.