Journal of the Japan society of photogrammetry and remote sensing
Online ISSN : 1883-9061
Print ISSN : 0285-5844
ISSN-L : 0285-5844
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Volume 62, Issue 5
Displaying 1-6 of 6 articles from this issue
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Preface
  • [title in Japanese]
    [in Japanese]
    2023 Volume 62 Issue 5 Pages 224-226
    Published: 2023
    Released on J-STAGE: November 01, 2024
    DOIhttps://doi.org/10.4287/jsprs.62.224
    JOURNAL FREE ACCESS
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  • Spread of SLAM in surveying work
    Seishi TAJIMA
    2023 Volume 62 Issue 5 Pages 227-230
    Published: 2023
    Released on J-STAGE: November 01, 2024
    DOIhttps://doi.org/10.4287/jsprs.62.227
    JOURNAL FREE ACCESS
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    The handheld Hovermap ST is effective for surveying small-scale disaster sites. GCP is automatically detected and matched to the site coordinate. Although it is less accurate than TLS, it has sufficient performance to understand the situation on-site. In addition, SLAM is installed in MMS as a position information correction device and is used for surveying work.

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  • －SLAM Surveying example－
    Noriyoshi KIMURA
    2023 Volume 62 Issue 5 Pages 231-234
    Published: 2023
    Released on J-STAGE: November 01, 2024
    DOIhttps://doi.org/10.4287/jsprs.62.231
    JOURNAL FREE ACCESS
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    In June 2022, a manual for public surveying using SLAM (Simultaneous Localization and Mapping) technology was published, and its use has been promoted. There is a wide variety of SLAMs, and even with the same sensor, the accuracy and apparent results can vary greatly depending on the method of measurement and processing. In this article, we will take one of these products, NavVis VLX2, as an example and introduce its measurement points, cautions, and features.

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  • Utilization of SLAM for Autonomous Driving in Urban Areas
    Takeshi ISHITA, Yuki KITSUKAWA
    2023 Volume 62 Issue 5 Pages 235-238
    Published: 2023
    Released on J-STAGE: November 01, 2024
    DOIhttps://doi.org/10.4287/jsprs.62.235
    JOURNAL FREE ACCESS
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    Simultaneous Localization and Mapping (SLAM) is a critical technology used in robotics that involves the real-time construction or updating of an environment map while simultaneously determining the precise position and orientation of the robot within that map using Lidar, cameras. Autonomous Driving systems require accurate ego-vehicle localization capabilities to navigate complex scenarios safely. For that reason, autonomous driving systems often utilize technologies based on SLAM. This article introduces a SLAM solution implemented in the well-known open-source software “Autoware” and an advanced camera-based localization approach, as well as the current challenges and possible solutions when processing in outdoor environments.

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