CANOE: Autonomous Marine Navigation Sensor Data from Ontario Lakes
Available on 1 platform
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Description
A dataset from the Autonomous Space Robotics Laboratory (ASRL) for developing aquatic autonomous navigation algorithms. It includes synchronized data from a 360-degree radar, a 128-beam lidar, a stereo camera, imaging sonar, motor inputs, and GNSS, collected on lakes and reservoirs in Ontario, Canada. The data is hosted on AWS Open Data and released under a CC-BY-4.0 license.
Use Cases
Benchmarking sensor fusion algorithms based on the synchronized 360-degree radar, lidar, camera, and sonar data
Developing obstacle detection and avoidance models based on the lidar point clouds and sonar imagery
Training visual odometry or SLAM systems based on the stereo camera and integrated IMU data
Testing autonomous navigation control policies based on the motor inputs and GNSS trajectory data
Strengths
Includes data from a 128-beam Ouster OS1 lidar, providing high-resolution 3D point clouds
Features synchronized multi-sensor data from radar, lidar, stereo camera, sonar, IMU, and GNSS
Released under a permissive CC-BY-4.0 license for broad reuse
Limitations
Column-level documentation is absent; field semantics must be inferred after download
Row count and dataset size are unknown, which may limit suitability assessment
Data may reflect geographic bias inherent to collection in Ontario lake environments
Provenance
Source
Autonomous Space Robotics Laboratory (ASRL)
Collection Method
Collected autonomously on a marine vehicle using a suite of sensors.
Time Range
null
Freshness
Last update date is unknown; freshness unverified.
Geography
Lakes and reservoirs in Ontario, Canada
Data is hosted in S3 format on AWS Open Data; specific access tools may be required.