8 papers · 1 filter
Pre-training Visual Dexterity in Simulation
Sarthak Kamat, Adam Rashid, Satvik Sharma +4
Large-scale pre-training has made robot policy fine-tuning increasingly data-efficient, but this progress has largely been driven by datasets and embodiments built around simple pa…
Handroid: Bridging Dexterous Hand and Humanoid
Ruogu Li, Chenyang Ma, Sikai Li +6
Dexterous hands and humanoid robots are typically developed as distinct embodiments: the former enable contact-rich manipulation at the object scale, whereas the latter provide mob…
SceneBot: Contact-Prompted General Humanoid Whole Body Tracking with Scene-Interaction
Sirui Chen, Shibo Zhao, Zhen Wu +3
Current humanoid reinforcement-learning policies excel at free-space motions but struggle with contact-rich tasks, as pure kinematic tracking cannot resolve the physical ambiguitie…
Cloak: Zero-Shot Cross-Embodiment Manipulation by Masking the End-Effector from the VLA
Michael Piseno, Guy Tevet, C. Karen Liu
We present Cloak, a training recipe that endows a Vision-Language-Action (VLA) model with zero-shot cross-embodiment transfer by cloaking the end-effector from its own wrist camera…
Play2Perfect: What Matters in Dexterous Play Pretraining for Precise Assembly?
Tyler Ga Wei Lum, Kushal Kedia, C. Karen Liu +1
Multi-fingered robots promise the speed and dexterity of human hands, yet challenging problems such as precise assembly have remained out of reach. These tasks are contact-rich, ma…
Locomotion Beyond Feet
Tae Hoon Yang, Haochen Shi, Jiacheng Hu +10
Most locomotion methods for humanoid robots focus on leg-based gaits, yet natural bipeds frequently rely on hands, knees, and elbows to establish additional contacts for stability…
Robot Trains Robot: Automatic Real-World Policy Adaptation and Learning for Humanoids
Kaizhe Hu, Haochen Shi, Yao He +3
Simulation-based reinforcement learning (RL) has significantly advanced humanoid locomotion tasks, yet direct real-world RL from scratch or adapting from pretrained policies remain…
ToddlerBot: Open-Source ML-Compatible Humanoid Platform for Loco-Manipulation
Haochen Shi, Weizhuo Wang, Shuran Song +1
Learning-based robotics research driven by data demands a new approach to robot hardware design-one that serves as both a platform for policy execution and a tool for embodied data…