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Autonomous Navigation datasets

archive 2025-07-28

6 datasets carry the task tag "Autonomous Navigation" (the task itself: Autonomous Navigation), ordered by the archive's paper count. Page 1 of 1: 6 shown of 6. Facet routes are this site's own (the archive records the tag string, not a page).

The archive holds 12,214 dataset rows; 12,172 are listed. 6 are withheld from every listing and count here as vandalised before snapshot (6 with contact-centre spam in the title, 0 with a spam description on a row that has no homepage, no paper and no papers counted; none with more than 1 paper, 0 with a benchmark), listed in withheld.json; 1 listed row carries a vandalised description, withheld on its page. This gate never withholds a row with a homepage or a paper that resolves, and a clean description; the content rules below withhold a row whose name is spam whatever else it carries. The gate is a phrase list: these are the rows it caught, not a claim that the rest is clean. Before that gate, the site's content rules withhold 36 more rows (invite-code, gambling, travel-booking, contact-centre and similar spam in the name or on a row with nothing real behind it); they have no page and are listed in withheld.json.

Filter 51 task tags shown of 3,717, by dataset count; the full filter by modality, task and language is on /datasets

Autonomous Navigation datasets 1–6 of 6

RELLIS-3D is a multi-modal dataset for off-road robotics.
57 papers · 3 benchmarks
JRDB (JackRabbot Dataset and Benchmark)
A novel egocentric dataset collected from social mobile manipulator JackRabbot.
33 papers · 1 benchmark
MIDGARD is an open-source simulator for autonomous robot navigation in outdoor unstructured environments.
2 papers · 0 benchmarks
IN2LAAMA is a set of lidar-inertial datasets collected with a Velodyne VLP-16 lidar and a Xsens MTi-3 IMU.
1 paper · 0 benchmarks
LDDRS (LWIR DoFP Dataset of Road Scene)
The LWIR DoFP Dataset of Road Scene (LDDRS) is a road detection dataset with 2,113 annotated images.
1 paper · 0 benchmarks
Hyper Drive (Hyperspectral Driving Dataset)
Towards automated analysis of large environments, hyperspectral sensors must be adapted into a format where they can be operated from mobile robots.
0 papers · 0 benchmarks

Paper counts and descriptions are the archive's, frozen 2025-07-28; no citation counts, no stars, no trending. Sorting by "most cited" or "newest" was a live-site feature the archive does not carry.