• Title/Summary/Keyword: 루프 클로징

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A loop closing scheme using UWB based indoor positioning technique (UWB 기반 실내 측위 기술을 활용한 루프 클로징 기법)

  • Hyunwoo You;Jungkyun Lee;Somi Nam;Juyeon Lee;Yoonseo Lee;Minsung Kim;Hong Min
    • Smart Media Journal
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    • v.12 no.4
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    • pp.41-46
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    • 2023
  • UWB is a type of technology used for indoor positioning and is characterized by higher accuracy than RSSI-based schemes. Mobile equipment operating based on ROS can monitor the environment around the equipment using lidar and cameras. When applying the loop closing technique to determine the starting position in this monitoring process, the existing method has a problem of low accuracy because the closing operation occurs only when there are feature points on the image. In this paper, to solve this problem, we designed a system that increases the accuracy of loop closing work by providing location information by mounting a UWB tag on a mobile device. In addition, the accuracy of the UWB-based indoor positioning system was evaluated through experiments, and it was verified that it could be used for loop closing techniques.

2D Pose Nodes Sampling Heuristic for Fast Loop Closing (빠른 루프 클로징을 위한 2D 포즈 노드 샘플링 휴리스틱)

  • Lee, Jae-Jun;Ryu, Jee-Hwan
    • Journal of Institute of Control, Robotics and Systems
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    • v.22 no.12
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    • pp.1021-1026
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    • 2016
  • The graph-based SLAM (Simultaneous Localization and Mapping) approach has been gaining much attention in SLAM research recently thanks to its ability to provide better maps and full trajectory estimations when compared to the filtering-based SLAM approach. Even though graph-based SLAM requires batch processing causing it to be computationally heavy, recent advancements in optimization and computing power enable it to run fast enough to be used in real-time. However, data association problems still require large amount of computation when building a pose graph. For example, to find loop closures it is necessary to consider the whole history of the robot trajectory and sensor data within the confident range. As a pose graph grows, the number of candidates to be searched also grows. It makes searching the loop closures a bottleneck when solving the SLAM problem. Our approach to alleviate this bottleneck is to sample a limited number of pose nodes in which loop closures are searched. We propose a heuristic for sampling pose nodes that are most advantageous to closing loops by providing a way of ranking pose nodes in order of usefulness for closing loops.