Project GR00T: Generalist Humanoid Robot 00 Technology from NVIDIA

NVIDIA's Project GR00T is inspired by the success of ChatGPT in NLP. Just like ChatGPT is a generalist model that solves most of the NLP tasks, NVIDIA wants to build a generalist Robot that can be used to perform a diverse set of tasks alongside humans— in a factory, in a restaurant, at home, in a hospital. The GR00T project aims to develop general purpose foundational models, tools and technologies that can accelerate the development of humanoid robots.

A humanoid robot is an embodied AI. It is a general-purpose, bipedal robot that looks like a human being and is designed to work alongside humans for a variety of tasks like grasping, moving, loading, unloading objects etc. These robots learn and adapt to changes in environment and are equipped with actuators, sensors, computers and code to mimic human intelligence and dexterity.

Training Humanoid Robots

Training these robots is a complex process. It uses adaptive algorithms, AI Foundational models, simulation environments, synthetic data, reinforcement learning, imitation learning (robots capture the human movements/actions using sensors or cameras, then these movements are translated into robotic commands which let the robot mimic the observed behaviors), optimized software stack, training frameworks, and containerized microservices.

3 Computers of NVIDIA’s Robotics Stack

NVIDIA uses its three-computer robotics stack for this project — NVIDIA AI and DGX for model training, NVIDIA ISAAC Lab and ISAAC Sim for robot learning in simulation environment, and the NVIDIA Jetson Thor HPC platform with ISAAC ROS for robot runtime. Tools like NVIDIA’s Isaac Lab and Omniverse accelerate training by enabling faster-than-real-time simulations, including complex scenarios. Models like GPT-4 can be leverage to automate reward function design, domain randomization, and other robotic training tasks.

Humanoid robots can be used in various sectors — manufacturing, warehouse and logistics, healthcare, home assistants, customer service.

The challenges to building these robots include: Limited training data of precise human movements, unpredictability of natural world, need for a lightweight, versatile and powerful design, energy efficiency of onboard batteries, need for better coordination across complex mechanical and control systems to give the robot more degrees of freedom.

3 Principles of Humanoid Robots

1. Data Pyramid Principle : The data pyramid principle says that the training of humanoid robots requires the data at three levels — internet scale data in Eeta Bytes per day to train large foundational models, data generated by simulations to train robots in Tera Bytes per GPU-day, real data generated by interaction of robots with environment in a 24 hour robot day.
2. The Matrix Principle: Simulations allow for scalable, efficient training as they allow to bypass real-world constraints like time and resources. RoboCasa and MimicGen are NVIDIA’s solutions for generating simulations to train the robots. MimicGen and RoboCasa generate and augment training data efficiently, multiplying limited real-world demonstrations. Sim2Real Transfer is a technique for transfering knowledge from simulated to real-world robotics by domain randomization.
3. Foundational Agent Principle : Building generalist foundational models that can control various robot embodiments, master diverse skills and operate across simulations and real-world scenarios. Models like GPT-4 can be leverage to automate reward function design, domain randomization, and other robotic training tasks.

Conclusion:

Humanoid robots could revolutionize labor markets, making AI-driven automation a trillion-dollar industry soon. However, it is important to align embodied AI with human values and optimize it for usability, affordability and ease of operation. Making human-agent interaction easy will improve the acceptability of the embodied AI.

References:

https://developer.nvidia.com/project-gr00t

https://www.softimpact.net/articles/blogs/518/elon-musk-launches-optimus-robot-as-greatest-produ/en

https://www.fortunebusinessinsights.com/humanoid-robots-market-110188