Operating environments: Research labs, robot developers, simulation teams and AI training environments.
Target markets: Robotics labs, AI developers and companies training policies before physical deployment.
Deployment model: Open framework and NVIDIA developer ecosystem model.
Whole-body loco-manipulation - Research demonstration - 2026-06-10 - The paper compares unified and dual critic architectures for humanoid loco-manipulation reinforcement learning. - source: arxiv.org
Pick and place - Claimed - 2025-01-06 - The release also adds reference workflows for pick-and-place and object-following plus visual-SLAM and multi-camera 3D reconstruction, giving developers a path from simulation and synthetic data toward physical robot deployment. - source: developer.nvidia.com