Context
Forge is a great toolkit for converting between robotics dataset formats (RLDS, LeRobot, etc.). As tactile sensing becomes increasingly important in robot learning, there's a growing need for format conversion that includes tactile data.
Proposal
Add TLabel as a supported format for tactile sensor data. TLabel provides:
- Unified schema for tactile data across 10+ sensor types (GelSight, PaXini, Daimon, UniVTAC, VTouch, YCB-Slide, TacQuad, etc.)
- Dataset adapters for loading existing tactile datasets into standardized format
- Real-time sensor adapters for live data capture (PaXini GEN3 SDK, Daimon DM-Tac USB)
- PyPI package:
pip install tlabel (MIT license, 14K+ downloads)
Use case
A researcher has LeRobot dataset with visual + joint data, and wants to augment it with tactile data from GelSight sensors. Forge + TLabel could provide the bridge: convert LeRobot → TLabel (adding tactile channels) → back to LeRobot with enriched modalities.
This would make Forge the go-to tool for multi-modal robotics data format conversion, including the tactile modality.
Refs:
Context
Forge is a great toolkit for converting between robotics dataset formats (RLDS, LeRobot, etc.). As tactile sensing becomes increasingly important in robot learning, there's a growing need for format conversion that includes tactile data.
Proposal
Add TLabel as a supported format for tactile sensor data. TLabel provides:
pip install tlabel(MIT license, 14K+ downloads)Use case
A researcher has LeRobot dataset with visual + joint data, and wants to augment it with tactile data from GelSight sensors. Forge + TLabel could provide the bridge: convert LeRobot → TLabel (adding tactile channels) → back to LeRobot with enriched modalities.
This would make Forge the go-to tool for multi-modal robotics data format conversion, including the tactile modality.
Refs: