Scaling Robot Policy Evaluations to Thousands of Parallel Simulations

Evaluating a robot foundation model is one of the most demanding closed-loop problems in robotics. Before you can trust a policy to move a real robot, you have to test it thousands of times across thousands of starting conditions each, pairing GPU-heavy inference with GPU-heavy physics simulation step by step, at a scale that quickly becomes a complex infrastructure problem.

In this session, Ian Jordan, PhD - Robotics / AV Technical Specialist at Anyscale, will walk through this by covering:

• Benefits and trends in policy evaluation via simulations

• Challenges in scaling / distributing two GPU-based workloads

• How Ray Serve and Isaac Lab separate the policy service from the simulators

• Live walkthrough deploying NVIDIA's GR00T-N1.7-3B VLA to drive a Unitree G1 humanoid, fanned out across hundreds of parallel rollouts.

If you're a robotics engineer, ML engineer, or simulation infrastructure engineer working on robot foundation models, humanoids, manipulation, or any physical AI system, this session is for you.