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Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.

LeCAR-Lab/ASAP

[RSS 2025] "ASAP: Aligning Simulation and Real-World Physics for Learning Agile Humanoid Whole-Body Skills"

55MITPython

View on GitHub Website

Stars: 2,077
Forks: 199
Watchers: 28
Open issues: 61
Contributors: 4

Star history, last 90 days+1 over 5 snapshots

2026-07-24 · 2,0762026-08-06 · 2,077

Star history, last 90 days
Date	Stars
2026-07-24	2076
2026-07-25	2077
2026-07-28	2077
2026-07-30	2077
2026-08-06	2077

Today

— stars today

This week

— stars this week

This month

— stars this month

Momentum

0.0

growth rate 0.00%/day

From the README

<h1 align="center"> ASAP: Aligning Simulation and Real-World Physics for 

Learning Agile Humanoid Whole-Body Skills </h1>

<div align="center">

Robotics: Science and Systems (RSS) 2025

[[Website]](https://agile.human2humanoid.com/)
[[Arxiv]](https://arxiv.org/pdf/2502.01143)
[[Video]](https://www.youtube.com/watch?v=tu7LSNYWDTs&ab_channel=LeCARLabatCMU)

<p align="center">
    <img src="imgs/CMU-NV-logo-crop-png.png" height=50"> &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;
</p>




[![IsaacGym](https://img.shields.io/badge/IsaacGym-Preview4-b.svg)](https://developer.nvidia.com/isaac-gym) [![IsaacSim](https://img.shields.io/badge/IsaacSim-4.2.0-b.svg)](https://docs.isaacsim.omniverse.nvidia.com/4.2.0/index.html) [![IsaacSim](https://img.shields.io/badge/Genesis-0.2.1-b.svg)](https://docs.isaacsim.omniverse.nvidia.com/4.2.0/index.html) [![Linux platform](https://img.shields.io/badge/Platform-linux--64-orange.svg)](https://ubuntu.com/blog/tag/22-04-lts) [![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)]()


<img src="https://agile.human2humanoid.com/static/images/asap-preview-gif-480P.gif" width="400px"/>

</div>

<!-- # Table of Contents -->
## 📚 Table of Contents

1. **[Overview](#overview)**  
   - Links: [Website](https://agile.human2humanoid.com/) • [Arxiv](https://arxiv.org/pdf/2502.01143) • [Video](https://www.youtube.com/watch?v=tu7LSNYWDTs&ab_channel=LeCARLabatCMU)  
 

2. **[Installation & Setup](#installation)**  
   2.1 [Base Frameworks](#isaacgym-conda-env)  
   2.2 [IsaacGym Setup](#install-isaacgym)  
   2.3 [HumanoidVerse Setup](#install-humanoidverse)  
   2.4 [IsaacSim + IsaacLab Setup](#isaaclab-environment)  
   2.5 [Genesis Environment Setup](#genesis-environment)  

3. **[Training Pipelines](#motion-tracking-training)**  
   3.1 [Phase-Based Motion Tracking](#motion-tracking-training)  
   3.2 [ASAP Delta Action Model](#asap-delta-action-model-training)  
       - [Train Delta Action Model](#train-delta-action-model)  
       - [Finetune Policy with Delta Action Model](#use-delta-action-model-for-policy-finetuning)  

4. **[Motion Retargeting to Any Humanoid](#motion-retargeting-to-any-humanoid)**  
   4.1 [Step 1: SMPL Shape Preparation](#1-smpl-shape-preparation)  
   4.2 [Step 2: SMPL Motion Preparation (AMASS)](#2-smpl-motion-preparation-amass)  
   4.3 [Step 3: Robot XML & Motion Config](#3-robot-xml-and-motion-config-preparation)  
   4.4 [Step 4: Humanoid-SMPL Shape Fitting](#4-humanoid-smpl-shape-fitting)  
   4.5 [Step 5: Humanoid-SMPL Motion Retargeting](#5-humanoid-smpl-motion-retargeting)  

5. **[Deployment: Sim2Sim & Sim2Real](#sim2simsim2real)**  
   5.1 [Environment Setup](#environment-setup)  
   5.2 [Sim2Sim Deployment](#sim2sim)  
   5.3 [Sim2Real Deployment](#sim2real)  

7. **[Citation](#citation)**  

8. **[License](#license)**


## TODO
- [x] Release code backbone
- [x] Release phase-based motion tracking training pipeline
- [x] Release ASAP motion datasets
- [x] Release motion retargeting pipeline
- [x] Release sim2sim in MuJoCo
- [x] Release sim2real with UnitreeSDK
- [x] Release ASAP delta action model training pipeline


# Installation

ASAP codebase is built on top of [HumanoidVerse](https://github.com/LeCAR-Lab/HumanoidVerse) (a multi-simulator framework for humanoid learning) and [Human2Humanoid](https://github.com/LeCAR-Lab/human2humanoid) (our prior work on humanoid whole-body tracking).

[HumanoidVerse](https://github.com/LeCAR-Lab/HumanoidVerse) allows you to train humanoid skills in multiple simulators, including IsaacGym, IsaacSim, and Genesis. Its key design logic is the separation and modularization of simulators, tasks, and algorithms, which enables smooth transfers between different simulators and the real world with minimum effort (just one line of code change). We leverage this framework to develop [ASAP](https://agile.human2humanoid.com/) and study how to best transfer policies across simulators and the real world.

##

Excerpt of 21,986 characters

Read on GitHub

Top contributors4 shown

Quality score

Would you bet a product on this? Bounded 0–100 and slow moving.

55/10055

Maintenance: 20%; How recently the default branch was pushed to
Releases: 25%; Recency and cadence of tagged releases
Community: 41%; Contributor breadth and bus factor
Issue backlog: 85%; Open issues measured against the size of the audience
Documentation: 100%; README depth, plus a homepage and topics
Licensing: 100%; How freely the code can be adopted

What to know before adopting

No commits in 6+ months
No tagged releases
Usable in commercial products with attribution.

Details

Created: 2 years ago
Last push: 7 months ago
Last release: none
Release tag: —
Releases in the last year: 0
Default branch: main
Size: 59k KB
Owner type: Organization
Owner location: United States of America
Discovered via: topic:robotics
First indexed: 13 days ago
Last synced: 9 days ago

LeCAR-Lab/ASAP

[RSS 2025] "ASAP: Aligning Simulation and Real-World Physics for Learning Agile Humanoid Whole-Body Skills"

55MITPython

View on GitHub Website

Stars: 2,077
Forks: 199
Watchers: 28
Open issues: 61
Contributors: 4

Star history, last 90 days+1 over 5 snapshots

2026-07-24 · 2,0762026-08-06 · 2,077

Star history, last 90 days
Date	Stars
2026-07-24	2076
2026-07-25	2077
2026-07-28	2077
2026-07-30	2077
2026-08-06	2077

Today

— stars today

This week

— stars this week

This month

— stars this month

Momentum

0.0

growth rate 0.00%/day

From the README

<h1 align="center"> ASAP: Aligning Simulation and Real-World Physics for 

Learning Agile Humanoid Whole-Body Skills </h1>

<div align="center">

Robotics: Science and Systems (RSS) 2025

[[Website]](https://agile.human2humanoid.com/)
[[Arxiv]](https://arxiv.org/pdf/2502.01143)
[[Video]](https://www.youtube.com/watch?v=tu7LSNYWDTs&ab_channel=LeCARLabatCMU)

<p align="center">
    <img src="imgs/CMU-NV-logo-crop-png.png" height=50"> &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;
</p>




[![IsaacGym](https://img.shields.io/badge/IsaacGym-Preview4-b.svg)](https://developer.nvidia.com/isaac-gym) [![IsaacSim](https://img.shields.io/badge/IsaacSim-4.2.0-b.svg)](https://docs.isaacsim.omniverse.nvidia.com/4.2.0/index.html) [![IsaacSim](https://img.shields.io/badge/Genesis-0.2.1-b.svg)](https://docs.isaacsim.omniverse.nvidia.com/4.2.0/index.html) [![Linux platform](https://img.shields.io/badge/Platform-linux--64-orange.svg)](https://ubuntu.com/blog/tag/22-04-lts) [![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)]()


<img src="https://agile.human2humanoid.com/static/images/asap-preview-gif-480P.gif" width="400px"/>

</div>

<!-- # Table of Contents -->
## 📚 Table of Contents

1. **[Overview](#overview)**  
   - Links: [Website](https://agile.human2humanoid.com/) • [Arxiv](https://arxiv.org/pdf/2502.01143) • [Video](https://www.youtube.com/watch?v=tu7LSNYWDTs&ab_channel=LeCARLabatCMU)  
 

2. **[Installation & Setup](#installation)**  
   2.1 [Base Frameworks](#isaacgym-conda-env)  
   2.2 [IsaacGym Setup](#install-isaacgym)  
   2.3 [HumanoidVerse Setup](#install-humanoidverse)  
   2.4 [IsaacSim + IsaacLab Setup](#isaaclab-environment)  
   2.5 [Genesis Environment Setup](#genesis-environment)  

3. **[Training Pipelines](#motion-tracking-training)**  
   3.1 [Phase-Based Motion Tracking](#motion-tracking-training)  
   3.2 [ASAP Delta Action Model](#asap-delta-action-model-training)  
       - [Train Delta Action Model](#train-delta-action-model)  
       - [Finetune Policy with Delta Action Model](#use-delta-action-model-for-policy-finetuning)  

4. **[Motion Retargeting to Any Humanoid](#motion-retargeting-to-any-humanoid)**  
   4.1 [Step 1: SMPL Shape Preparation](#1-smpl-shape-preparation)  
   4.2 [Step 2: SMPL Motion Preparation (AMASS)](#2-smpl-motion-preparation-amass)  
   4.3 [Step 3: Robot XML & Motion Config](#3-robot-xml-and-motion-config-preparation)  
   4.4 [Step 4: Humanoid-SMPL Shape Fitting](#4-humanoid-smpl-shape-fitting)  
   4.5 [Step 5: Humanoid-SMPL Motion Retargeting](#5-humanoid-smpl-motion-retargeting)  

5. **[Deployment: Sim2Sim & Sim2Real](#sim2simsim2real)**  
   5.1 [Environment Setup](#environment-setup)  
   5.2 [Sim2Sim Deployment](#sim2sim)  
   5.3 [Sim2Real Deployment](#sim2real)  

7. **[Citation](#citation)**  

8. **[License](#license)**


## TODO
- [x] Release code backbone
- [x] Release phase-based motion tracking training pipeline
- [x] Release ASAP motion datasets
- [x] Release motion retargeting pipeline
- [x] Release sim2sim in MuJoCo
- [x] Release sim2real with UnitreeSDK
- [x] Release ASAP delta action model training pipeline


# Installation

ASAP codebase is built on top of [HumanoidVerse](https://github.com/LeCAR-Lab/HumanoidVerse) (a multi-simulator framework for humanoid learning) and [Human2Humanoid](https://github.com/LeCAR-Lab/human2humanoid) (our prior work on humanoid whole-body tracking).

[HumanoidVerse](https://github.com/LeCAR-Lab/HumanoidVerse) allows you to train humanoid skills in multiple simulators, including IsaacGym, IsaacSim, and Genesis. Its key design logic is the separation and modularization of simulators, tasks, and algorithms, which enables smooth transfers between different simulators and the real world with minimum effort (just one line of code change). We leverage this framework to develop [ASAP](https://agile.human2humanoid.com/) and study how to best transfer policies across simulators and the real world.

##

Excerpt of 21,986 characters

Read on GitHub

Top contributors4 shown

Quality score

Would you bet a product on this? Bounded 0–100 and slow moving.

55/10055

Maintenance: 20%; How recently the default branch was pushed to
Releases: 25%; Recency and cadence of tagged releases
Community: 41%; Contributor breadth and bus factor
Issue backlog: 85%; Open issues measured against the size of the audience
Documentation: 100%; README depth, plus a homepage and topics
Licensing: 100%; How freely the code can be adopted

What to know before adopting

No commits in 6+ months
No tagged releases
Usable in commercial products with attribution.

Details

Created: 2 years ago
Last push: 7 months ago
Last release: none
Release tag: —
Releases in the last year: 0
Default branch: main
Size: 59k KB
Owner type: Organization
Owner location: United States of America
Discovered via: topic:robotics
First indexed: 13 days ago
Last synced: 9 days ago

Top AI Repos — open-source AI, indexed and scored

LeCAR-Lab/ASAP

From the README

Top contributors4 shown

Quality score

What to know before adopting

Categories

Details

LeCAR-Lab/ASAP

From the README

Top contributors4 shown

Quality score

What to know before adopting

Categories

Details

Top AI Repos — open-source AI, indexed and scored

Trend

From the README

Top contributors4 shown

Quality score

What to know before adopting

Categories

Details

Trend

From the README

Top contributors4 shown

Quality score

What to know before adopting

Categories

Details