robomanipbaselines

A software framework integrating various imitation learning methods and benchmark environments for robotic manipulation

https://github.com/isri-aist/robomanipbaselines

Science Score: 26.0%

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Scientific vocabulary similarity
Low similarity (13.1%) to scientific vocabulary

Keywords

imitation-learning robot-learning robot-manipulation

Last synced: 6 months ago · JSON representation

Repository

A software framework integrating various imitation learning methods and benchmark environments for robotic manipulation

Basic Info

Host: GitHub
Owner: isri-aist
License: bsd-2-clause
Language: Python
Default Branch: master
Homepage: https://isri-aist.github.io/RoboManipBaselines-ProjectPage/
Size: 88.5 MB

Statistics

Stars: 232
Watchers: 11
Forks: 31
Open Issues: 2
Releases: 0

Topics

imitation-learning robot-learning robot-manipulation

Created almost 2 years ago · Last pushed 6 months ago

Metadata Files

Readme Contributing License Citation

RoboManipBaselines

A software framework integrating various imitation learning methods and benchmark environments for robotic manipulation.
Provides easy-to-use baselines for policy training, evaluation, and deployment.

https://github.com/user-attachments/assets/c37c9956-2d50-488d-83ae-9c11c3900992

https://github.com/user-attachments/assets/ba4a772f-0de5-47da-a4ec-bdcbf13d7d58

Quick Start

Start collecting data in the MuJoCo simulation, train your model, and rollout the ACT policy in just a few steps!
See the Quick Start Guide.

Installation

Follow our step-by-step Installation Guide to get set up smoothly.

Policies

We provide several powerful policy architectures for manipulation tasks:

MLP: Simple feedforward policy
SARNN: Sequence-aware RNN-based policy
ACT: Transformer-based imitation policy
MT-ACT: Multi-task Transformer-based imitation policy
Diffusion Policy: Diffusion-based behavior cloning policy
3D DiffusionPolicy: Diffusion-based policy using 3D point cloud observations

Data

Dataset List: Pre-collected expert demonstration datasets
Learned Parameters: Trained model checkpoints and configs
Data Format: Description of the custom RMB data format used in RoboManipBaselines

Teleoperation

Use your own teleop interface to collect expert data.
See Teleop Tools for more info.

Multiple SpaceMouse: Setup multiple SpaceMouse for high-degree-of-freedom robots

Environments

Explore diverse manipulation environments:

Environment Catalog: Overview of all task environments
Env Setup: Installation guides per environment
How to Add a New Environment: Guide for adding a custom environment
MuJoCo Tactile Sensor: Guide for using tactile sensors in MuJoCo environments

Miscellaneous

Check out Misc Scripts for standalone tools and utilities.

Evaluation Results

See Benchmarked Performance across environments and policies.

Contributing

We welcome contributions!
Check out the Contribution Guide to get started.

License

This repository is licensed under the BSD 2-Clause License, unless otherwise stated.
Please check individual files or directories (especially third_party and assets) for specific license terms.

Citation

If you use RoboManipBaselines in your work, please cite us:

bibtex @software{RoboManipBaselines_GitHub2024, author = {Murooka, Masaki and Motoda, Tomohiro and Nakajo, Ryoichi}, title = {{RoboManipBaselines}}, url = {https://github.com/isri-aist/RoboManipBaselines}, version = {1.0.0}, year = {2024}, month = dec, }

Owner

Name: Intelligent Systems Research Institute, AIST
Login: isri-aist
Kind: organization

Repositories: 17
Profile: https://github.com/isri-aist

GitHub Events

Total

Create event: 14
Issues event: 11
Watch event: 210
Delete event: 12
Issue comment event: 17
Public event: 1
Push event: 363
Pull request review comment event: 2
Pull request review event: 3
Pull request event: 12
Fork event: 32

Last Year

Create event: 14
Issues event: 11
Watch event: 210
Delete event: 12
Issue comment event: 17
Public event: 1
Push event: 363
Pull request review comment event: 2
Pull request review event: 3
Pull request event: 12
Fork event: 32

Issues and Pull Requests

Last synced: 6 months ago

All Time

Total issues: 7
Total pull requests: 6
Average time to close issues: 12 days
Average time to close pull requests: about 13 hours
Total issue authors: 6
Total pull request authors: 5
Average comments per issue: 1.29
Average comments per pull request: 0.67
Merged pull requests: 4
Bot issues: 0
Bot pull requests: 0

Past Year

Issues: 7
Pull requests: 6
Average time to close issues: 12 days
Average time to close pull requests: about 13 hours
Issue authors: 6
Pull request authors: 5
Average comments per issue: 1.29
Average comments per pull request: 0.67
Merged pull requests: 4
Bot issues: 0
Bot pull requests: 0

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Top Authors

Issue Authors

yoann-fleytoux (2)
AndyCao1125 (1)
kylehuo8 (1)
lllzheng (1)
Ryuya-Sato-Pay (1)
saitenntaisei (1)

Pull Request Authors

mmurooka (3)
Naoki-Shibayama (1)
sjtuyinjie (1)
saitenntaisei (1)

Top Labels

Issue Labels

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Dependencies

.github/workflows/install.yml actions

actions/checkout v4 composite
actions/setup-python v5 composite

.github/workflows/pre-commit.yml actions

actions/checkout v4 composite
actions/setup-python v5 composite
pre-commit/action v3.0.1 composite

pyproject.toml pypi

gymnasium ==1.0.0
imageio >=2.14.1
ipdb *
ipython *
matplotlib >=3.3.4
mujoco ==3.1.6
numba *
numpy *
opencv-python *
pin *
pyspacemouse *
scipy *
tqdm *

setup.py pypi