• 제목/요약/키워드: Indoor Map

Search Result 263, Processing Time 0.021 seconds

Construction of Indoor and Outdoor Spatial Information Integration Service System based on Vector Model

  • Kim, Jun Hyun;Kwon, Kee Wook
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
    • /
    • v.36 no.3
    • /
    • pp.185-196
    • /
    • 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.

Integrated Indoor Positioning Systems Reflecting Map Information for Location Based Services (위치기반서비스를 위한 지도정보가 반영된 옥내측위통합 시스템)

  • Yim, Jae-Geol;Joo, Jae-Hun;Jeong, Seung-Hwan
    • The Journal of Information Systems
    • /
    • v.17 no.1
    • /
    • pp.131-153
    • /
    • 2008
  • So many location based service systems, including automobile navigation system logistic management, taxi fleet management, and so on, are being used everywhere. However, these are all outdoors. This paper provides a stepping stone for commercial indoor location based services by developing an integrated system of our indoor positioning and map viewer modules. For the indoor positioning, we propose WLAN (Wireless Local Area Network) based EKF (Extended Kalman Filter) which estimates user's current location and tracts user's trace in the sequence of time. Our map viewer renders a map recorded in an Autocad DXF file and provides functions of map manipulation such as zoom-in, zoom-out, and move. We integrate our indoor positioning and map viewer modules and discuss the experimental results of the integrated system.

Indoor Network Map Matching by Hidden Markov Model (은닉 마르코프 모델을 이용한 실내 네트워크 맵 매칭)

  • Kim, Tae Hoon;Li, Ki-Joune
    • Spatial Information Research
    • /
    • v.23 no.3
    • /
    • pp.1-10
    • /
    • 2015
  • Due to recent improvement of various sensor technologies, indoor positioning becomes available. However, Indoor positioning technologies by Wi-Fi radio map and acceleration sensor and digital campus still have a certain level of errors and a number of researches have been done to increase the positioning accuracy of the indoor positioning. If we could provide a room level accuracy, indoor location based services with current indoor positioning methods such as Wi-Fi radio map and acceleration sensors would be possible. In this paper, we propose an indoor map matching method to provide a room level accuracy based on hidden markov model.

Location Correction Based on Map Information for Indoor Positioning Systems (지도 정보를 반영한 옥내 측위 보정 방안)

  • Yim, Jae-Geol;Shim, Kyu-Bark;Park, Chan-Sik;Jeong, Seung-Hwan
    • Journal of Korea Multimedia Society
    • /
    • v.12 no.2
    • /
    • pp.300-312
    • /
    • 2009
  • An indoor location-based service cannot be realized unless the indoor positioning problem is solved. However, the cost-effective indoor positioning systems are suffering from their inaccurateness. This paper proposes a map information-based correction method for the indoor positioning systems. Using our Kalman filter with map information-based appropriate parameter values, our method estimates the track of the moving object, then it performs the Frechet Distance-based map matching on the obtained track. After that it applies our real time correction method. In order to verify efficiency of our method, we also provide our test results.

  • PDF

3D Map Generation System for Indoor Autonomous Navigation (실내 자율 주행을 위한 3D Map 생성 시스템)

  • Moon, SungTae;Han, Sang-Hyuck;Eom, Wesub;Kim, Youn-Kyu
    • Aerospace Engineering and Technology
    • /
    • v.11 no.2
    • /
    • pp.140-148
    • /
    • 2012
  • For autonomous navigation, map, pose tracking, and finding the shortest path are required. Because there is no GPS signal in indoor environment, the current position should be recognized in the 3D map by using image processing or something. In this paper, we explain 3D map creation technology by using depth camera like Kinect and pose tracking in 3D map by using 2D image taking from camera. In addition, the mechanism of avoiding obstacles is discussed.

3D Multi-floor Precision Mapping and Localization for Indoor Autonomous Robots (실내 자율주행 로봇을 위한 3차원 다층 정밀 지도 구축 및 위치 추정 알고리즘)

  • Kang, Gyuree;Lee, Daegyu;Shim, Hyunchul
    • The Journal of Korea Robotics Society
    • /
    • v.17 no.1
    • /
    • pp.25-31
    • /
    • 2022
  • Moving among multiple floors is one of the most challenging tasks for indoor autonomous robots. Most of the previous researches for indoor mapping and localization have focused on singular floor environment. In this paper, we present an algorithm that creates a multi-floor map using 3D point cloud. We implement localization within the multi-floor map using a LiDAR and an IMU. Our algorithm builds a multi-floor map by constructing a single-floor map using a LOAM-based algorithm, and stacking them through global registration that aligns the common sections in the map of each floor. The localization in the multi-floor map was performed by adding the height information to the NDT (Normal Distribution Transform)-based registration method. The mean error of the multi-floor map showed 0.29 m and 0.43 m errors in the x, and y-axis, respectively. In addition, the mean error of yaw was 1.00°, and the error rate of height was 0.063. The real-world test for localization was performed on the third floor. It showed the mean square error of 0.116 m, and the average differential time of 0.01 sec. This study will be able to help indoor autonomous robots to operate on multiple floors.

A Novel Technique for Human Traffic based Radio Map Updating in Wi-Fi Indoor Positioning Systems

  • Mo, Yun;Zhang, Zhongzhao;Lu, Yang;Agha, Gul
    • KSII Transactions on Internet and Information Systems (TIIS)
    • /
    • v.9 no.5
    • /
    • pp.1881-1903
    • /
    • 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.

Indoor Navigation of a Skid Steering Mobile Robot Via Friction Compensation and Map Matching (마찰 보상과 지도 정합에 의한 미끄럼 조향 이동로봇의 실내 주행)

  • So, Chang Ju;Lyou, Joon
    • Journal of Institute of Control, Robotics and Systems
    • /
    • v.19 no.5
    • /
    • pp.468-472
    • /
    • 2013
  • This paper deals with the indoor localization problem for a SSMR (Skid Steering Mobile Robot) subjected to wheel-ground friction and with one LRF (Laser Range Finder). In order to compensate for some friction effect, a friction related coefficient is estimated by the recursive least square algorithm and appended to the maneuvering command. Also to reduce odometric information based localization errors, the lines are extracted with scan points of LRF and matched with the ones of the corresponding map built in advance. The present friction compensation and scan map matching schemes have been applied to a laboratory SSMR, and experimental results are given to validate the localization performance along an indoor corridor.

A Navigation System for a Patrol Robot in Indoor Environments (실내 환경에서의 경비로봇용 주행시스템)

  • Choi, Byoung-Wook;Lee, Young-Min;Park, Jeong-Ho;Shin, Dong-Kwan
    • The Journal of Korea Robotics Society
    • /
    • v.1 no.2
    • /
    • pp.117-124
    • /
    • 2006
  • In this paper, we develope the navigation system for patrol robots in indoor environment. The proposed system consists of PDA map modelling, a localization algorithm based on a global position sensor and an automatic charging station. For the practical use in security system, the PDA is used to build object map on the given indoor map. And the builded map is downloaded to the mobile robot and used in path planning. The global path planning is performed with a localization sensor and the downloaded map. As a main controller, we use PXA270 based hardware platform in which embedded linux 2.6 is developed. Data handling for various sensors and the localization algorithm are performed in the linux platform. Also, we implemented a local path planning algorithm for object avoidance with ultra sonar sensors. Finally, for the automatic charging, we use an infrared ray system and develop a docking algorithm. The navigation system is experimented with the two-wheeled mobile robot using North-Star localization system.

  • PDF

Three-dimensional Map Construction of Indoor Environment Based on RGB-D SLAM Scheme

  • Huang, He;Weng, FuZhou;Hu, Bo
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
    • /
    • v.37 no.2
    • /
    • pp.45-53
    • /
    • 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.