055-amp-adversarial-motion-priors-for-stylized-physics-based-character-control
Science Score: 18.0%
This score indicates how likely this project is to be science-related based on various indicators:
-
✓CITATION.cff file
Found CITATION.cff file -
○codemeta.json file
-
○.zenodo.json file
-
○DOI references
-
○Academic publication links
-
○Academic email domains
-
○Institutional organization owner
-
○JOSS paper metadata
-
○Scientific vocabulary similarity
Low similarity (3.3%) to scientific vocabulary
Last synced: 10 months ago
·
JSON representation
·
Repository
Basic Info
- Host: GitHub
- Owner: SZU-AdvTech-2023
- Default Branch: main
- Size: 0 Bytes
Statistics
- Stars: 0
- Watchers: 0
- Forks: 0
- Open Issues: 0
- Releases: 0
Created over 2 years ago
· Last pushed over 2 years ago
Metadata Files
Citation
https://github.com/SZU-AdvTech-2023/055-AMP-Adversarial-Motion-Priors-for-Stylized-Physics-Based-Character-Control/blob/main/
## AMP: Adversarial Motion Priors for Stylized Physics-Based Character Control ### Linux Python 3.8 3D Isaac Gym Preview 4 [](https://developer.nvidia.com/isaac-gym)`python/examples` `joint_monkey.py` ``` "gym==0.23.1", "torch", "omegaconf", "termcolor", "jinja2", "hydra-core>=1.2", "rl-games>=1.6.0", "pyvirtualdisplay", "urdfpy==0.0.22", "pysdf==0.1.9", "warp-lang==0.10.1", "trimesh==3.23.5", ``` ### HumanoidAMPPO.yaml `reward_combine: 'add' ` ```bash python launch.py task=HumanoidAMP headless=True ``` ```bash python launch.py task=HumanoidAMP headless=False test=True num_envs=64 checkpoint=/path/to/saved/model/in/runs/nn ``` HumanoidAMPPO.yaml `reward_combine: 'mul' ` ```bash python launch.py task=HumanoidAMP headless=True ``` ```bash python launch.py task=HumanoidAMP headless=False test=True num_envs=64 checkpoint=/path/to/saved/model/in/runs/nn ``` ### ```bash python launch.py task=HumanoidAMP headless=False test=True num_envs=64 checkpoint=/path/to/saved/model/in/runs/nn capture_video=True ``` ### `fmbvh` `./isaacgymenvs/tasks/amp/utils_amp/motion_lib.export_bvh` `./runs/`
Owner
- Name: SZU-AdvTech-2023
- Login: SZU-AdvTech-2023
- Kind: organization
- Repositories: 1
- Profile: https://github.com/SZU-AdvTech-2023
Citation (citation.txt)
@article{REPO055,
author = "Peng, Xue Bin and Ma, Ze and Abbeel, Pieter and Levine, Sergey and Kanazawa, Angjoo",
journal = "ACM Transactions on Graphics (ToG)",
number = "4",
pages = "1--20",
title = "{AMP: Adversarial Motion Priors for Stylized Physics-Based Character Control}",
volume = "40",
year = "2021"
}
GitHub Events
Total
- Watch event: 40
- Fork event: 4
Last Year
- Watch event: 40
- Fork event: 4