Awesome SLAM datasets
A curated collection of datasets for Simultaneous Localization and Mapping (SLAM) research, categorized by topic, platform, and environment.
What is Awesome SLAM datasets?
Awesome SLAM Datasets is a curated, open-source list of datasets for Simultaneous Localization and Mapping (SLAM) research. It solves the problem of fragmented and hard-to-find data by providing a centralized, categorized repository of datasets that include crucial ground truth information like pose and maps. This enables researchers and engineers to efficiently find appropriate data for developing, testing, and benchmarking SLAM algorithms.
Robotics researchers, computer vision engineers, and graduate students working on SLAM, visual odometry, 3D mapping, and related perception tasks for autonomous systems.
Developers choose this project because it offers a uniquely comprehensive and meticulously organized collection, saving significant time in dataset discovery. Its structured categorization by topic, sensor, and platform, along with active updates from the research community, makes it the most reliable starting point for SLAM data.
Overview
A curated list of awesome datasets for SLAM
Use Cases
Best For
- Finding benchmark datasets for visual-inertial odometry algorithms
Related Projects
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