Wenli Xiao
@_wenlixiao • 2,675 subscribers
@physical_int | PhD Student at @CMU_Robotics | Ex GEAR Lab @NvidiaAI | Physical AI & Robotics
Videos
What if robots could improve themselves by learning from their own failures in the real-world? Introducing 𝗣𝗟𝗗 (𝗣𝗿𝗼𝗯𝗲, 𝗟𝗲𝗮𝗿𝗻, 𝗗𝗶𝘀𝘁𝗶𝗹𝗹) — a recipe that enables Vision-Language-Action (VLA) models to self-improve for high-precision manipulation tasks. PLD couples real-world residual reinforcement learning with standard supervised fine-tuning — letting robots discover, recover, and distill their own data flywheel. Quick 🧵
Wenli Xiao184,912 просмотров • 8 месяцев назад
🚨 Without Any Motion Priors, how to make humanoids do versatile parkour jumping🦘, clapping dance🤸, cliff traversal🧗, and box pick-and-move📦 with a unified RL framework? Introduce WoCoCo: 🧗 Whole-body humanoid Control with sequential Contacts 🎯Unified designs for minimal tuning across tasks 🤖Generalize to various high-DoF robots Website:
Wenli Xiao70,332 просмотров • 2 лет назад
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