Real-Time VLAs via Future-state-aware Asynchronous Inference.
Project description
LUNA: Real-Time VLAs via Future-state-aware Asynchronous Inference
LUNA is an efficient and easy-to-use framework for VLAs inference.
Features
LUNA is efficient through:
- Asynchronous Inference: Overlaps action prediction with execution to achieve real-time performance
- Future-state Awareness: Uses predicted future states for more accurate action planning
LUNA is easy to use with:
- Simple CLI: Clean command-line interface for inference and serving
- Flexible Configuration: YAML-based configuration for easy customization
Installation
# Create conda environment
conda create -n "luna" python=3.10
conda activate luna
# Install dependencies
pip install -e .
Usage
# Run inference with a trained policy
luna run examples/inference/async.yaml
# Start model server for remote inference
luna server examples/inference/async.yaml
# Run inference with custom parameters
luna run examples/inference/async.yaml --action_quant_ratio=2
LUNA is designed to be flexible and extensible, allowing users to easily integrate new policies and customize existing ones.
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