Location via proxy:   [ UP ]  
[Report a bug]   [Manage cookies]                
Next Article in Journal
Self-Reported Data for Sustainable Development from People Living in Rural and Remote Areas
Previous Article in Journal
Optimizing Parkinson’s Disease Prediction: A Comparative Analysis of Data Aggregation Methods Using Multiple Voice Recordings via an Automated Artificial Intelligence Pipeline
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
This is an early access version, the complete PDF, HTML, and XML versions will be available soon.
Data Descriptor

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

Institute of Electronics and Computer Science (EDI), LV-1006 Riga, Latvia
*
Author to whom correspondence should be addressed.
Submission received: 1 November 2024 / Revised: 3 December 2024 / Accepted: 5 January 2025 / Published: 7 January 2025

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.
Keywords: robotics; SLAM; computer vision; LiDAR; dataset; ROS robotics; SLAM; computer vision; LiDAR; dataset; ROS

Share and Cite

MDPI and ACS Style

Racinskis, P.; Krasnikovs, G.; Arents, J.; Greitans, M. The EDI Multi-Modal Simultaneous Localization and Mapping Dataset (EDI-SLAM). Data 2025, 10, 5. https://doi.org/10.3390/data10010005

AMA Style

Racinskis P, Krasnikovs G, Arents J, Greitans M. The EDI Multi-Modal Simultaneous Localization and Mapping Dataset (EDI-SLAM). Data. 2025; 10(1):5. https://doi.org/10.3390/data10010005

Chicago/Turabian Style

Racinskis, Peteris, Gustavs Krasnikovs, Janis Arents, and Modris Greitans. 2025. "The EDI Multi-Modal Simultaneous Localization and Mapping Dataset (EDI-SLAM)" Data 10, no. 1: 5. https://doi.org/10.3390/data10010005

APA Style

Racinskis, P., Krasnikovs, G., Arents, J., & Greitans, M. (2025). The EDI Multi-Modal Simultaneous Localization and Mapping Dataset (EDI-SLAM). Data, 10(1), 5. https://doi.org/10.3390/data10010005

Article Metrics

Back to TopTop