EXOKERN — The Data Engine for Physical AI

Contact-rich. Sensor-annotated. Industrially validated. EU AI Act ready.

We produce high-fidelity force/torque manipulation datasets for enterprise robotics, humanoid robot manufacturers, and research institutions — with full data provenance and compliance documentation.

🎯 The Problem

Over 95% of existing robotics datasets lack force/torque sensor data. Vision-only approaches fail at contact-rich tasks like insertion, assembly, and manipulation — where precise haptic feedback is critical.

Starting August 2026, the EU AI Act requires documented data provenance for AI training data. Most existing datasets cannot meet this standard.

💡 Our Solution

EXOKERN provides industrially calibrated 6-axis force/torque (wrench) data alongside standard observations, enabling robots to learn manipulation skills that require physical contact understanding.

Capture → Anchor → Ship

Phase	What We Do	Output
01 Capture	Operators generate specific contact forces incl. systematic failures in calibrated environments	Raw data + Failure Taxonomy + QC Report
02 Anchor	Real friction logs calibrate simulation. Physics parameters validated against F/T measurements	Calibrated Sim Assets (MJCF/USD/JSON)
03 Ship	ML-ready exports in all major formats — clean, tagged, quality-certified	RLDS, HDF5, Zarr, MCAP, LeRobot v3.0

📦 Datasets

Dataset	Task	F/T Data	Status
contactbench-forge-peginsert-v0	Peg-in-Hole Insertion	✅ 6-axis Wrench	Available

🗺️ More contact-rich datasets in development — including assembly, grasping, and deformable object manipulation. Commercial Contact Skill Packs available for enterprise customers.

🔧 What Makes Our Data Different

Force/Torque annotations on every frame (Fx, Fy, Fz, Mx, My, Mz)
LeRobot v3.0 compatible — plug directly into policy training pipelines
Industrially relevant tasks — insertion, assembly, contact-rich manipulation
Calibrated sensors — not estimated, not vision-derived, directly measured
Full data provenance — capture methodology, operator ID, QC reports, EU AI Act compliant
Sim-anchoring — calibrated simulation assets bridge the Sim2Real gap

🏗️ Built With

NVIDIA Isaac Lab for high-fidelity physics simulation
LeRobot v3.0 format for interoperability
Franka FR3 (7-DOF) robot platform
Bota Systems SensONE 6-axis F/T sensor

📬 Contact

🌐 Website: exokern.com
🤗 HuggingFace: huggingface.co/EXOKERN
📧 Enterprise inquiries: info@exokern.com

EXOKERN — Bridging the Haptic Data Gap in Physical AI