Training robot policies from real-world demonstrations is costly, slow, and prone to overfitting, limiting generalization across tasks and environments. A…
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, in early developer preview, improves humanoid robot capabilities with advanced whole-body…
