AWS ML BlogWednesday · June 10, 2026FREEScale Robot Reinforcement Learning with NVIDIA Isaac Lab on Amazon SageMaker AI
This post details how to train robot policies for the Unitree H1 humanoid using NVIDIA Isaac Lab on Amazon SageMaker AI. Two compute options are available: Amazon SageMaker HyperPod, designed for large-scale distributed training, and Amazon SageMaker Training Jobs, which offers a managed environment for iterative experimentation. The integration allows developers to leverage SageMaker's infrastructure for reinforcement learning tasks, including simulation and policy optimization. By using Isaac Lab, a GPU-accelerated framework for robot learning, users can train complex locomotion and manipulation policies. The post provides a step-by-step guide, covering environment setup, training configuration, and deployment. This approach aims to simplify scaling robot learning from research to production by combining NVIDIA's simulation tools with AWS's managed ML services.
Enables scalable robot policy training using managed AWS infrastructure and NVIDIA simulation.