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The EDI Multi-Modal Simultaneous Localization and Mapping Dataset (EDI-SLAM)

Author

Listed:
  • Peteris Racinskis

    (Institute of Electronics and Computer Science (EDI), LV-1006 Riga, Latvia)

  • Gustavs Krasnikovs

    (Institute of Electronics and Computer Science (EDI), LV-1006 Riga, Latvia)

  • Janis Arents

    (Institute of Electronics and Computer Science (EDI), LV-1006 Riga, Latvia)

  • Modris Greitans

    (Institute of Electronics and Computer Science (EDI), LV-1006 Riga, Latvia)

Abstract

This paper accompanies the initial public release of the EDI multi-modal SLAM dataset, a collection of long tracks recorded with a portable sensor package. These include two global shutter RGB camera feeds, LiDAR scans, as well as inertial and GNSS data from an RTK-enabled IMU-GNSS positioning module—both as satellite fixes and internally fused interpolated pose estimates. The tracks are formatted as ROS1 and ROS2 bags, with separately available calibration and ground truth data. In addition to the filtered positioning module outputs, a second form of sparse ground truth pose annotation is provided using independently surveyed visual fiducial markers as a reference. This enables the meaningful evaluation of systems that directly utilize data from the positioning module into their localization estimates, and serves as an alternative when the GNSS reference is disrupted by intermittent signals or multipath scattering. In this paper, we describe the methods used to collect the dataset, its contents, and its intended use.

Suggested Citation

  • Peteris Racinskis & Gustavs Krasnikovs & Janis Arents & Modris Greitans, 2025. "The EDI Multi-Modal Simultaneous Localization and Mapping Dataset (EDI-SLAM)," Data, MDPI, vol. 10(1), pages 1-14, January.
    • Handle: RePEc:gam:jdataj:v:10:y:2025:i:1:p:5-:d:1562055
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