Neural Processing Unit (NPU)

The Neural Processing Unit (NPU) is a ROS2-based system that leverages Large Language Models (LLMs) to dynamically generate and execute behavior trees (BTs) based on natural language commands. Designed for general-purpose robotic systems, NPU introduces an adaptable, modular framework that allows robots to interpret instructions and act autonomously within any compatible ROS2 infrastructure.

Key Features:
- Utilizes LLMs to parse and understand natural language commands, converting them into structured robotic actions.
- Generates real-time behavior trees tailored to the robot's capabilities and the given task.
- Offers universal compatibility through a YAML-based configuration file that describes the robot’s available functions.
- Seamlessly integrates with ROS2 (Humble), enabling dynamic task execution on physical or simulated robots.
- Lightweight and infrastructure-agnostic, built for maximum portability and customization.

Technical Overview:
- LLM Integration: Natural language is parsed and transformed into semantic task graphs, enabling real-time planning and execution.
- Behavior Tree Generation: The system dynamically composes and modifies BTs based on user commands and context.
- YAML Configuration: Each robot defines its capabilities in a YAML file, allowing the LLM to reason within a constrained, robot-specific action space.

Project Status:
- OpenVLA dropped around June 2024 as one of the first generalist Vision–Language–Action models in robotics.
- In August 2024, papers like DISCO showed real-time embodied agents with visual navigation and manipulation.
- By October 31, 2024, π₀ (Pi‑Zero) from Physical Intelligence busted onto the scene—a real generalist robot policy that learns from multi-robot data and a vision-language backbone.

Basically, my NPU was born cool... but aged like milk. Within the same month, these powerful embodied AI models surfaced, making NPU feel instantly obsolete. Consider it my summer fling with embodied AI!