TWIST2: Scalable, Portable, and Holistic Humanoid Data Collection System
Authors: name: Yanjie Ze, name: Siheng Zhao, name: Weizhuo Wang, name: Angjoo Kanazawa, name: Rocky Duan, name: Pieter Abbeel, name: Guanya Shi, name: Jiajun Wu, name: C. Karen Liu

Large-scale data has driven breakthroughs in robotics, from language models
to vision-language-action models in bimanual manipulation. However, humanoid
robotics lacks equally effective data collection frameworks. Existing humanoid
teleoperation systems either use decoupled control or depend on expensive
motion capture setups. We introduce TWIST2, a portable, mocap-free humanoid
teleoperation and data collection system that preserves full whole-body control
while advancing scalability. Our system leverages PICO4U VR for obtaining
real-time whole-body human motions, with a custom 2-DoF robot neck (cost around
$250) for egocentric vision, enabling holistic human-to-humanoid control. We
demonstrate long-horizon dexterous and mobile humanoid skills and we can
collect 100 demonstrations in 15 minutes with an almost 100% success rate.
Building on this pipeline, we propose a hierarchical visuomotor policy
framework that autonomously controls the full humanoid body based on egocentric
vision. Our visuomotor policy successfully demonstrates whole-body dexterous
manipulation and dynamic kicking tasks. The entire system is fully reproducible
and open-sourced at https://yanjieze.com/TWIST2 . Our collected dataset is also
open-sourced at https://twist-data.github.io .