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CLOUD: Canadian Longterm Outdoor Unmanned Aerial Vehicule Dataset (UAV)

A visual-inertial flight dataset collected by Defence Research and Development Canada in collaboration with the University of Toronto, containing over 30 km of flight data at three locations across Canada.

AccessFree to access
LicenceLicense statement is still being checked
ProducerDefence Research and Development Canada, University of Toronto

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Key facts

InstitutionDefence Research and Development Canada (DRDC), University of Toronto Institute for Aerospace Studies (UTIAS)
CoverageThree locations in Canada: Suffield, Montreal, University of Toronto Institute for Aerospace Studies (UTIAS)
Time spanSee official page
ScaleOver 30 km of visual-inertial flight data

Contents & fields

The dataset contains over 30 km of visual-inertial flight data collected by a DJI M600 UAV with a gimbaled camera. Each location includes Teach and Repeat runs (reverse direction). Data includes Google Earth images, human-readable text files, and a set of Python tools. No field-level description is provided on the source page.

Research uses

Suitable for research in UAV visual localization including robustness to perspective change, lighting change and seasonal changes, as well as satellite image UAV navigation, experience-based localization and simultaneous localization and mapping.

Information comes from the source page. Please check that page for current details and terms.

Keywords

UAVvisual-inertialoutdoorlocalizationCanadaCLOUD

Access and licence

Licence: License statement is still being checked · Source page
Rights details not yet verified
| Free to access

Why this is hard to get on your own

Research on UAV visual localization often requires long-term outdoor data across diverse environments and conditions, but public datasets are often limited in scope or scale.

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