Operational Pipeline

Multimodal Labeling for Robotic Foundation Models

From raw sensor capture to a reconciled, training-ready dataset — six modality-specialist teams work in parallel, then a cross-modal pass enforces consistency.

1Multi-Stream Capture
2Modality-Specific Labeling
3Cross-Modal Reconciliation
1Multi-Stream Capture
Sensor Streams 6 modalities
Camera 30 Hz
Joint angles 200 Hz
Motor commands 100 Hz
Brain state 10 Hz
Fingertip pressure 500 Hz
Wrench (force/torque) 1 kHz
2Modality-Specific Labeling
V
Vision-Language Label → QA
●Trained: vision + NL
P
Proprioception Label → QA
●Trained: kinematics
A
Action Label → QA
●Trained: control
M
Memory Label → QA
●Trained: episodic state
T
Tactile Label → QA
●Trained: contact dynamics
W
Torque Label → QA
●Trained: force/torque
3Cross-Modal Reconciliation
Reconciliation consistency
Timestamp alignment
Phase-boundary verify
Ontology compliance
Output Dataset
Data flow
Reconciled output
Hover any lane for the labeler skill profile