CANOE: Autonomous Marine Navigation Sensor Data from Ontario Lakes

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