Lidar scan matching with rtk-gnss positioning and geometric constraints

Masafumi Nakagawa, Shinjiro Abe, Sho Sanuka, Kazuo Saito, Masahiro Miyo

研究成果: Conference contribution

抄録

Scan matching in simultaneous localization and mapping (SLAM) has several technical issues, such as error accumulation, high processing cost in point cloud matching and optimization, and position loss problems after scan matching failures. Error adjustment processing can improve the performance of SLAM with loop closure and global optimization approach. However, measurement path plans and higher processing cost are required for the error adjustment and global optimization. In contrast, global navigation satellite system (GNSS) positioning can simplify the scan matching. Thus, we propose scan matching for multilayer LiDAR data registration with RTK-GNSS positioning and geometric constraints. Through experiments on point cloud acquisition with multilayer LiDAR and a single-frequency RTK-GNSS positioning device, we verify that our methodology can integrate point clouds acquired in mobile mapping without an inertial measurement unit. We also confirm that our methodology can avoid error accumulation problems in conventional SLAM processing.

本文言語English
ホスト出版物のタイトルACRS 2020 - 41st Asian Conference on Remote Sensing
出版社Asian Association on Remote Sensing
ISBN(電子版)9781713829089
出版ステータスPublished - 2020
イベント41st Asian Conference on Remote Sensing, ACRS 2020 - Deqing City, Virtual, China
継続期間: 2020 11 92020 11 11

出版物シリーズ

名前ACRS 2020 - 41st Asian Conference on Remote Sensing

Conference

Conference41st Asian Conference on Remote Sensing, ACRS 2020
国/地域China
CityDeqing City, Virtual
Period20/11/920/11/11

ASJC Scopus subject areas

  • コンピュータ ネットワークおよび通信

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