Training robot policies from real-world demonstrations is costly, slow, and prone to overfitting, limiting generalization across tasks and environments. A sim-first approach streamlines development, lowers risk and cost, and enables safer, more adaptable deployment.  The latest version of Isaac Lab 2.3, now generally available , improves humanoid robot capabilities with advanced whole-body control, enhanced imitation … Continue reading Streamline Robot Learning with Whole-Body Control and Enhanced Teleoperation in NVIDIA Isaac Lab 2.3