CLARU
phicoltan2024CC0 1.0 Universal

BorealTC

Contains IMU and wheel timeseries data recorded with a Husky A200 UGV on five terrain types: snow, ice, silty loam, asphalt, and flooring. Recorded in boreal forest environments in Quebec, Canada.

Downloads137
Hours1.93

Why This Matters for Physical AI

This dataset enables terrain classification for wheeled robots operating in challenging boreal forest environments, essential for autonomous navigation and locomotion adaptation on variable natural surfaces.

Technical Profile

Modalities
imuproprioception
Robot Embodiments
Husky A200
Environment
outdoorforest
Task Types
terrain_classification
Total Hours
1.93
Data Format
CSV
Annotation Types
terrain_labels
License
CC0 1.0 Universal
Part of the BorealTC family

Access

View on HuggingFaceRead Paper

Need custom imu data?

Claru builds purpose-built datasets for outdoor applications with dense human annotations and quality assurance.

Request a Sample Pack

Related Datasets

Xperience-10M

A large-scale egocentric multimodal dataset of human experience containing 10 million interactions and 10,000 hours of synchronized first-person recordings with six video streams, audio, stereo depth, camera pose, hand mocap, full-body mocap, IMU, and hierarchical language annotations for embodied AI, robotics, and world modeling research.

rgbaudiodepthproprioception+3
2.3M downloadsother

Open-H-Embodiment

A multi-embodiment community-driven dataset of paired kinematics and video for training AI autonomy models in surgical robotics and ultrasound applications. The dataset includes tabletop exercises, clinical procedures, and simulations of healthcare robotics tasks.

rgbproprioception
118K downloads2026cc-by-4.0

Open-H-Embodiment

A community-driven, multi-embodiment dataset of paired kinematics and video for training and evaluating AI autonomy models in surgical robotics and ultrasound applications, including tabletop exercises, clinical procedures, and healthcare robotics simulations.

rgbproprioception
76K downloads2026cc-by-4.0

PhysicalAI-Robotics-Manipulation-Kitchen-Demos

A large-scale dataset of 600 hours of human-teleoperated demonstrations across 316 different kitchen manipulation tasks, totalling 55k trajectories collected using a Franka Panda robot with an Omron mobile base.

rgbproprioception
57K downloads2025cc-by-4.0

TartanGround

A large-scale, multi-modal dataset designed to advance perception and autonomy of ground robots operating in diverse environments, collected across 63 photorealistic simulation environments with over 1.44 million samples from 878 trajectories.

rgbdepthsemantic_segmentationoptical_flow+5
42K downloads2025cc-by-4.0

RealSource World

A large-scale real-world robotics manipulation dataset collected using the RS-02 dual-arm humanoid robot, containing 14+ million frames across 11,428+ episodes of diverse long-horizon manipulation tasks with fine-grained annotations.

rgbproprioceptionforce_torque
31K downloads2025cc-by-nc-sa-4.0