The o1 Moment in Robotics Arrives: Harvard, Berkeley, NVIDIA Introduce RAX, Enabling Cross-Embodiment Online Exploration and Skill Accumulation

A research team from Harvard University, NVIDIA, University of California, Berkeley, Massachusetts Institute of Technology, and Stanford University has introduced RAX (Robot Agent eXploration), a framework that enables robots to learn through online exploration, achieving significant performance improvements across multiple benchmarks without requiring human demonstrations. RAX achieves an average lead of 37.4 percentage points across five simulation benchmarks and can perform tasks such as precise hole insertion and manipulation of flexible objects on real robots without human demonstration. This study marks the first systematic investigation into cross-simulation, cross-robot, and cross-embodiment online exploration scaling, providing an extensible platform for the continued development of embodied intelligence.