Skip to main content

Large Behavioral Model from Toyota Research

Project description

Screenshot 2025-07-10 at 5 12 49 PM

LBM - TRI (wip)

Implementation of the Large Behavioral Model architecture for dexterous manipulation from Toyota Research Institute.

Project Page

Data Normalization Takeaway

Install

$ pip install TRI-LBM

Usage

import torch
from TRI_LBM.lbm import LBM

lbm = LBM(
    action_dim = 20,
    dim_pose = 10
)

commands = ['pick up the apple and place in the blue tray']
images = torch.randn(1, 3, 3, 224, 224)
actions = torch.randn(1, 16, 20)
pose = torch.randn(1, 10)

loss = lbm(
    text = commands,
    images = images,
    pose = pose,
    actions = actions,
)

loss.backward()

# after much training

sampled_actions = lbm.sample(
    text = commands,
    images = images,
    pose = pose,
) # (1, 16, 20)

Citations

@misc{trilbmteam2025carefulexaminationlargebehavior,
    title  = {A Careful Examination of Large Behavior Models for Multitask Dexterous Manipulation}, 
    author = {TRI LBM Team and Jose Barreiros and Andrew Beaulieu and Aditya Bhat and Rick Cory and Eric Cousineau and Hongkai Dai and Ching-Hsin Fang and Kunimatsu Hashimoto and Muhammad Zubair Irshad and Masha Itkina and Naveen Kuppuswamy and Kuan-Hui Lee and Katherine Liu and Dale McConachie and Ian McMahon and Haruki Nishimura and Calder Phillips-Grafflin and Charles Richter and Paarth Shah and Krishnan Srinivasan and Blake Wulfe and Chen Xu and Mengchao Zhang and Alex Alspach and Maya Angeles and Kushal Arora and Vitor Campagnolo Guizilini and Alejandro Castro and Dian Chen and Ting-Sheng Chu and Sam Creasey and Sean Curtis and Richard Denitto and Emma Dixon and Eric Dusel and Matthew Ferreira and Aimee Goncalves and Grant Gould and Damrong Guoy and Swati Gupta and Xuchen Han and Kyle Hatch and Brendan Hathaway and Allison Henry and Hillel Hochsztein and Phoebe Horgan and Shun Iwase and Donovon Jackson and Siddharth Karamcheti and Sedrick Keh and Joseph Masterjohn and Jean Mercat and Patrick Miller and Paul Mitiguy and Tony Nguyen and Jeremy Nimmer and Yuki Noguchi and Reko Ong and Aykut Onol and Owen Pfannenstiehl and Richard Poyner and Leticia Priebe Mendes Rocha and Gordon Richardson and Christopher Rodriguez and Derick Seale and Michael Sherman and Mariah Smith-Jones and David Tago and Pavel Tokmakov and Matthew Tran and Basile Van Hoorick and Igor Vasiljevic and Sergey Zakharov and Mark Zolotas and Rares Ambrus and Kerri Fetzer-Borelli and Benjamin Burchfiel and Hadas Kress-Gazit and Siyuan Feng and Stacie Ford and Russ Tedrake},
    year   = {2025},
    eprint = {2507.05331},
    archivePrefix = {arXiv},
    primaryClass = {cs.RO},
    url = {https://arxiv.org/abs/2507.05331}, 
}
@inproceedings{Wagenmaker2025SteeringYD,
    title   = {Steering Your Diffusion Policy with Latent Space Reinforcement Learning},
    author  = {Andrew Wagenmaker and Mitsuhiko Nakamoto and Yunchu Zhang and Seohong Park and Waleed Yagoub and Anusha Nagabandi and Abhishek Gupta and Sergey Levine},
    year    = {2025},
    url     = {https://api.semanticscholar.org/CorpusID:279464702}
}
@misc{heng2025vitacformerlearningcrossmodalrepresentation,
    title   = {ViTacFormer: Learning Cross-Modal Representation for Visuo-Tactile Dexterous Manipulation}, 
    author  = {Liang Heng and Haoran Geng and Kaifeng Zhang and Pieter Abbeel and Jitendra Malik},
    year    = {2025},
    eprint  = {2506.15953},
    archivePrefix = {arXiv},
    primaryClass = {cs.RO},
    url     = {https://arxiv.org/abs/2506.15953}, 
}
@misc{cheang2025gr3technicalreport,
    title   = {GR-3 Technical Report}, 
    author  = {Chilam Cheang and Sijin Chen and Zhongren Cui and Yingdong Hu and Liqun Huang and Tao Kong and Hang Li and Yifeng Li and Yuxiao Liu and Xiao Ma and Hao Niu and Wenxuan Ou and Wanli Peng and Zeyu Ren and Haixin Shi and Jiawen Tian and Hongtao Wu and Xin Xiao and Yuyang Xiao and Jiafeng Xu and Yichu Yang},
    year    = {2025},
    eprint  = {2507.15493},
    archivePrefix = {arXiv},
    primaryClass = {cs.RO},
    url     = {https://arxiv.org/abs/2507.15493}, 
}
@misc{PI2025,
    title = {VLAs that Train Fast, Run Fast, and Generalize Better},
    author = {Danny Driess, Jost Tobias Springenberg, Brian Ichter, Lili Yu, Adrian Li-Bell, Karl Pertsch, Allen Z. Ren, Homer Walke, Quan Vuong, Lucy Xiaoyang Shi, Sergey Levine},
    year   = {2025},
    url    = {https://www.physicalintelligence.company/research/knowledge_insulation}
}

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

tri_lbm-0.0.22.tar.gz (10.2 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

tri_lbm-0.0.22-py3-none-any.whl (9.2 kB view details)

Uploaded Python 3

File details

Details for the file tri_lbm-0.0.22.tar.gz.

File metadata

  • Download URL: tri_lbm-0.0.22.tar.gz
  • Upload date:
  • Size: 10.2 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.9.23

File hashes

Hashes for tri_lbm-0.0.22.tar.gz
Algorithm Hash digest
SHA256 39781d1480a0ec669ff0e0dc7956daa4d8b98391ddb797ab0111250cd03f2057
MD5 8b469b425ab14cc2c63a4c07cecfe710
BLAKE2b-256 5d7e10ad99c5f3f0f83a1ac018476c3c55cacb0b4f46c2e14e281cfd08a5c9ad

See more details on using hashes here.

File details

Details for the file tri_lbm-0.0.22-py3-none-any.whl.

File metadata

  • Download URL: tri_lbm-0.0.22-py3-none-any.whl
  • Upload date:
  • Size: 9.2 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.9.23

File hashes

Hashes for tri_lbm-0.0.22-py3-none-any.whl
Algorithm Hash digest
SHA256 fa00421c6a5be06cb5999f051fce891bda9d2b2a740be7a4f0f3d6117ce9efcf
MD5 5e5fa6b2607c3c3d9abb4c297536ea87
BLAKE2b-256 bb92858cbaf045eadfaf8e24cf35d5e7dbfced680f9e1d214289834c28502152

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page