Built for the world. Built by the world.
Light-O1: Scaling Whole-Body Intelligence with Human Action Pretraining
Light-O1 learns a transferable human action prior from human videos, connecting language, vision, and whole-body action. Scaling human action pretraining yields power-law reductions in action prediction loss and whole-body pose error after adaptation across embodiments. We demonstrate long-horizon loco-manipulation in real environments and whole-body motion generation from open-ended instructions.
Light REACT: Building Resilient Whole-Body Intelligence for Scalable Deployment
Light REACT is our first step toward scalable deployment at the control level. Transformer-based Whole-Body In-Context Learning uses recent physical interactions to infer the effects of external forces, hardware impairments, and environmental constraints, then respond with adaptive whole-body skills. Specialist training, multi-teacher distillation, and preference alignment encourage upright recovery and locomotion whenever feasible while retaining crawling as a fallback, reducing human intervention and task interruptions.
LightNav-0: Scaling Real2Sim2Real for Zero-Shot Generalist Navigation
LightNav-0, our first general-purpose navigation brain, demonstrates zero-shot generalization across diverse robot embodiments, tasks, and scenes. Behind this capability is scalable alignment, enabled by a Real2Sim2Real data engine that turns 2,000+ real-world scenes into 4,000+ hours of simulation-based navigation experience.
LightParkour: Growing Humanoid Parkour Skills through Real2Sim2Real
Parkour as a testbed for contact-rich skill learning: ground a short human-motion seed in physics, grow it across terrain variation, and distill locomotion and whole-body skills into one deployable depth policy — running onboard Lightbot 0 with no runtime reference or skill label.
