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

CLOUD: Canadian Longterm Outdoor Unmanned Aerial Vehicule Dataset (UAV) Study done by Defence Research and Development Canada in collaboration with the University of Toronto. This Canadian Long term Outdoor UAV Long term Dataset (CLOUD) contains over 30 km of visual-inertial flight data collected at 3 different locations across Canada. Specifically, these locations include paths in Suffield, Montreal and the University of Toronto Institute for Aerospace Studies (UTIAS) in Toronto. In these experiments, a DJI M600 UAV with gimbaled camera is flown to create a Teach run which is immediately followed by a Repeat run traversed in the reverse direction. The data for each location is included in the dataset as well the links to download the zip files with data for each the trials. A more detailed description of the data can be found on the UTIAS homepage link included in the metadata of this dataset. It includes Google Earth images, data in human-readable text files and a set of Python tools provided to work with the data. Teach and Repeat runs can be download individually as needed as well. The data is well-suited for research in UAV visual localization including robustness to perspective change, lighting change and seasonal changes. Other potential use cases include satellite image UAV navigation, experience-based localization and simultaneous localization and mapping. The data is provided solely in English. 2022-12-29 National Defence open-ouvert@tbs-sct.gc.ca Science and TechnologyUnmanned Aerial Vehicle (UAV)visual-inertialmultiple outdoor environments and conditions CLOUD: Canadian Longterm Outdoor Unmanned Aerial Vehicule DataCSV https://open.canada.ca/data/dataset/45104589-ec39-4240-898f-2c11f28bd513/resource/4e37cea2-4c58-4c4a-ad96-a7ec3a97d7ce/download/admst-cloud-uav-dataset.csv

Study done by Defence Research and Development Canada in collaboration with the University of Toronto. This Canadian Long term Outdoor UAV Long term Dataset (CLOUD) contains over 30 km of visual-inertial flight data collected at 3 different locations across Canada. Specifically, these locations include paths in Suffield, Montreal and the University of Toronto Institute for Aerospace Studies (UTIAS) in Toronto. In these experiments, a DJI M600 UAV with gimbaled camera is flown to create a Teach run which is immediately followed by a Repeat run traversed in the reverse direction.

The data for each location is included in the dataset as well the links to download the zip files with data for each the trials. A more detailed description of the data can be found on the UTIAS homepage link included in the metadata of this dataset. It includes Google Earth images, data in human-readable text files and a set of Python tools provided to work with the data. Teach and Repeat runs can be download individually as needed as well. The data is well-suited for research in UAV visual localization including robustness to perspective change, lighting change and seasonal changes. Other potential use cases include satellite image UAV navigation, experience-based localization and simultaneous localization and mapping. The data is provided solely in English.

  • Publisher - Current Organization Name: National Defence
  • Publisher - Organization Name at Publication: Defence Research and Development Canada (DRDC), University of Toronto Institute for Aerospace Studies (UTIAS)
  • Licence: Open Government Licence - Canada

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