NVIDIA AI Introduces ASPIRE: A Self-Improving Robotics Framework Reaching 31% Zero-Shot on LIBERO-Pro Long Tasks
Traditional robot programming is hard to scale. It requires orchestrating multimodal perception, physical contact dynamics, diverse configurations, and execution failures by hand. Code-as-policy systems let language models compose these into executable robot programs. That makes robot behavior inspectable, editable, and debuggable. But existing robotic coding agents run in naive execution environments. They receive only coarse,…
