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Excited to introduce TWIST2, our next-generation humanoid data collection system. TWIST2 is portable (use anywhere, no MoCap), scalable (100+ demos in 15 mins), and holistic (unlock major whole-body human skills). Fully open-sourced:

101,418 views • 1 year ago •via X (Twitter)

33 Comments

Yanjie Ze's profile picture
Yanjie Ze1 year ago

2/n Why to build TWIST2? I still remember 1 year ago, painfully teleoperating a full-size humanoid for simple pick & place to collect a few demonstrations. Even getting 10 episodes was tough, and we had to lock the lower body to keep the robot stable. That is a well-known bottleneck of teleop: "Not scalable". This problem gets much harder in humanoids: the state and action space are much larger than tabletop arms, and dynamics are more complex. video from iDP3 (

Yanjie Ze's profile picture
Yanjie Ze1 year ago

3/n TWIST2 system overview We finally have such a teleop system that has all the features we need for general-purpose robot data collection: - Scalable - Portable - Holistic

Yanjie Ze's profile picture
Yanjie Ze1 year ago

4/n Portable You can just put on a VR headset (and 2 motion trackers) and start teleoperating anywhere. Rapid setup, no motion capture required. From walk in with the VR device to finish setup, it takes only 1 min.

Yanjie Ze's profile picture
Yanjie Ze1 year ago

5/n Holistic We find that egocentric active vision is essential to achieve long-horizon complex tasks. Therefore, we build a 2-DoF low-cost neck, which can be easily attached/detached to Unitree G1 without need to remove its original head.

Yanjie Ze's profile picture
Yanjie Ze1 year ago

6/n Holistic This is what it looks like in VR when doing teleoperation. The robot view is floating in the center of the VR view.

Yanjie Ze's profile picture
Yanjie Ze1 year ago

7/n Teleop skills Our system achieves human-like whole-body skills in a unified manner. Case 1: folding 3 towels consecutively, a very long-horizon and dexterous whole-body manipulation task.

Yanjie Ze's profile picture
Yanjie Ze1 year ago

8/n Teleop skills Case 2: walk around like humans

Yanjie Ze's profile picture
Yanjie Ze1 year ago

9/n Teleop skills Case 3: Pick an object from the ground

Yanjie Ze's profile picture
Yanjie Ze1 year ago

10/n Scalable data collection TWIST2 enables data collection at an unprecedented scale: ~50 mobile manipulation demos in 15 minutes

Yanjie Ze's profile picture
Yanjie Ze1 year ago

11/n Scalable data collection TWIST2 enables data collection at an unprecedented scale: ~100 manipulation demos in 15 minutes

Yanjie Ze's profile picture
Yanjie Ze1 year ago

12/n Visuomotor policy learning With TWIST2 data, we further build a hierarchical visuomotor policy learning framework, that controls the full body of a humanoid with imitation learning.

Yanjie Ze's profile picture
Yanjie Ze1 year ago

13/n Visuomotor policy learning That means, our visuomotor policy can not only pick & place objects,

Yanjie Ze's profile picture
Yanjie Ze1 year ago

14/n Visuomotor policy learning ...but can also use feet to kick a T-shaped box to the target region, i.e., Humanoid Kick-T.

Yanjie Ze's profile picture
Yanjie Ze1 year ago

15/n Visuomotor policy learning Our visuomotor policy predicts future whole-body joint positions. Across *Space & Time*.

Yanjie Ze's profile picture
Yanjie Ze1 year ago

16/n Humanoid data We also believe humanoid datasets should be universally shareable. So we built a platform to host and visualize humanoid data, and welcome contributions from the community:

Yanjie Ze's profile picture
Yanjie Ze1 year ago

n/n That's all. Hope you enjoy our work. This work was done while interning at Amazon FAR, with incredible collaborators @sihengzhao @KenWangWeizhuo, and guidance from amazing advisors @akanazawa @rocky_duan @pabbeel @GuanyaShi @jiajunwu_cs Karen. Website: arXiv: YouTube:

Cheng Chi's profile picture
Cheng Chi1 year ago

Glad to see humanoid teleop getting to useable state for manipulation! Congrats Yanjie

William Mason (feat Bear)'s profile picture
William Mason (feat Bear)1 year ago

@Scobleizer @zeyanjie, would love to chat about collaborating (@Contact_CI)

James's profile picture
James1 year ago

Wow this is nice! I didn't know Pico had motion trackers like that, those look very interesting! How is the tracking and SLAM compared to Quest 3?

RYC's profile picture
RYC1 year ago

I am curious why you choose ZED2 rather than RealSense D435i as the head camera?

Emerson Segura's profile picture
Emerson Segura1 year ago

@chichengcc Nice work!

Neil Nie's profile picture
Neil Nie1 year ago

This is so cool!! Congrats @ZeYanjie!

Durable's profile picture
Durable1 year ago

super cool!! can it do my laundry for me?? (^_~)

Rxct Ftvy's profile picture
Rxct Ftvy11 months ago

So futuristic, good way to train, good work.

Tian Fang's profile picture
Tian Fang1 year ago

@ZeYanjie I remember that you mentioned the human motions in videos can also be retarget to robots instantly in the RoboPaper talk, please remind me which papers are you referring to? Thank you,

Wang Fu's profile picture
Wang Fu1 year ago

牛逼!

Miguel's profile picture
Miguel10 months ago

The paper mentions a Discord server, is it still active? The link on the paper website is no longer working

luiz's profile picture
luiz10 months ago

Hello! I don’t have a Pico 4, so I tried deploying TWIST2 with the provided motion lib. Something still feels quite weird, the walking isn’t fluid (the video below is from the 001 example, which walks forward, turns, and walks back). Any hint about a misconfig I might have made?

MAX ONBOARDER ⭕'s profile picture
MAX ONBOARDER ⭕1 year ago

@Scobleizer This is soo good

JJ Walker's profile picture
JJ Walker1 year ago

TWIST2 is like the Swiss Army knife for robotics-portable, scalable, and open-source. Seriously game-changing stuff! Which whole-body skill do you want to see demoed next?

Lorenzo Pieri's profile picture
Lorenzo Pieri1 year ago

The neck looks great, thanks for sharing with the community!

Jakie PLA's profile picture
Jakie PLA1 year ago

TWIST2's open-source approach is brilliant! Portable, scalable AND holistic? This will supercharge humanoid tech development. Can't wait to try the 2-DoF neck for active perception!

Tobe Duru's profile picture
Tobe Duru1 year ago

game changer for data collection

Related Videos

In just one week, Binh and I trained a full-body Unitree G1. Here's a recap: 1. Secured a Unitree G1 humanoid through a LinkedIn post 2. Deployed TWIST2 full-body teleoperation pipelines 3. Adapted TWIST2 for Zed stereo camera & collected full-body teleoperation samples (carried by Binh ) 4. Adapted & fine-tuned NVIDIA Gr00T N1.5 VLA on the TWIST2 public datasets, which I fine-tuned on an 8xNVIDIA H100 Cluster. We picked Gr00T N1.5 as it was trained with Unitree G1 embodiment data. 5. Adapted the TWIST2 codebase to stream in the actions from Gr00T via ZMQ using a co-located NVIDIA H100 for ~200ms inference latency 6. Tested the model in sim, then deployed to the real-world Unitree G1. We streamed a training sample observation to the VLA (as we didn't want to break robot in case real observations were OOD) We were the first team in the world to deploy the full TWIST2 data collection pipeline to the unitree g1 :) Much more work ahead though, which I'll work on as a side-project over the next months: 1. Exploring the various types of 'world models': video backbones, dynamics models, v-jepa-2 models. I believe these will generalize better & train much more data-efficiently than VLM backbones 2. Speeding up inference - I believe low-latency robotics inference will be a big challenge. There are many works in video diffusion which I'd like to test (e.g. SageAttention, SparseAttention, Drifting Models). Perhaps also writing custom CUDA kernels. 3. Economics of inference scaling :) What will be the compute demands as we scale inference up to millions of humanoids? Will it run on edge or on distributed 'co-located' inference clusters? These are questions I'd like to answer. Adapted TWIST2 codebase: Adapted Gr00T-N1.5 codebase: The ETH Robotics Club are doing a cool GTC Golden ticket competition with NVIDIA , so this is my submission :) The DGX Spark compute will get me a long way with initial prototyping & especially working on inference optimization for next-gen Blackwell GPUs #NVIDIAGTC #GOLDENTICKET #ETHRC

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24,672 views • 9 months ago