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Open Source Science

https://github.com/ami-iit/paper_romualdi_viceconte_2024_humanoids_dnn-mpc-walking

Code associated to Humanoids 2024 paper submission

https://github.com/ami-iit/paper_romualdi_viceconte_2024_humanoids_dnn-mpc-walking

Science Score: 23.0%

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    CITATION.cff file
  • ✓
    codemeta.json file
    Found codemeta.json file
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    .zenodo.json file
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    DOI references
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    Academic publication links
    Links to: arxiv.org, ieee.org
  • ○
    Committers with academic emails
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    Scientific vocabulary similarity
    Low similarity (9.2%) to scientific vocabulary

Keywords

deep-learning humanoid humanoids2024 optimization robots

Keywords from Contributors

lie-group urdf-models
Last synced: 5 months ago · JSON representation

Repository

Code associated to Humanoids 2024 paper submission

Basic Info
Statistics
  • Stars: 17
  • Watchers: 6
  • Forks: 2
  • Open Issues: 0
  • Releases: 1
Topics
deep-learning humanoid humanoids2024 optimization robots
Created over 1 year ago · Last pushed about 1 year ago
Metadata Files
Readme License

README.md

Online DNN-Driven Nonlinear MPC for Stylistic Humanoid Robot Walking with Step Adjustment

Giulio Romualdi, Paolo Maria Viceconte, Lorenzo Moretti, Ines Sorrentino, Stefano Dafarra, Silvio Traversaro, and Daniele Pucci
Co-first authors: Paolo Maria Viceconte and Giulio Romualdi


📅 Accepted for publication at the 2024 IEEE-RAS International Conference on Humanoid Robots (Humanoids), Nancy, France 🤖


📜 Paper     📚 arXiv     🎥 Video     🖼️ Poster     🔧 Experiments     🌐 Website     📂 Dataset


Reproducing the Experiments

You can reproduce the experiments using Docker, Conda, or Pixi.

Docker

Run the experiments via Docker for an isolated and reproducible environment.

  1. Pull the Docker image: bash docker pull ghcr.io/ami-iit/dnn-mpc-walking-docker:latest

  2. Launch the container: bash xhost + docker run -it --rm \ --device=/dev/dri:/dev/dri \ --env="DISPLAY=$DISPLAY" \ --net=host \ ghcr.io/ami-iit/dnn-mpc-walking-docker:latest

  3. Wait for Gazebo to start and launch the experiment.

⚠️ Known Issue: The Gazebo real-time factor is scaled by a factor of 10 due to the MUMPS linear solver in the IPOPT Docker image. Alternative solvers (e.g., MA97) are available but cannot be redistributed.

Conda

Follow these steps to set up the experiments using Conda:

  1. Install the environment: bash conda env create -f environment.yml

  2. Activate the environment: bash conda activate dnn-mpc-env

  3. Compile the code: bash cd paper_romualdi_viceconte_2024_humanoids_dnn-mpc-walking mkdir build && cd build cmake .. make -j make install

  4. Run the simulation: bash ./run_simulation.sh

⚠️ The Gazebo real-time factor is scaled by a factor of 10 due to the MUMPS linear solver.

Pixi

To run the experiments with Pixi:

  1. Clone the repository: bash git clone https://github.com/ami-iit/paper_romualdi_viceconte_2024_humanoids_dnn-mpc-walking cd paper_romualdi_viceconte_2024_humanoids_dnn-mpc-walking

  2. Run the simulation: bash pixi run -e default run_simulation

Using MA97 Solver (Optional): If you have access to the Coin-HSL license, you can use the MA97 solver to improve performance: 1. Obtain the Coin-HSL archive (coinhsl-2023.11.17.zip) and place it in the ./coinhsl_src folder. 2. Run: bash pixi run -e coinhsl run_simulation

Maintainers

Paolo Maria Viceconte
👨‍💻 Paolo Maria Viceconte 		Giulio Romualdi
👨‍💻 Giulio Romualdi

Owner

  • Name: Artificial and Mechanical Intelligence
  • Login: ami-iit
  • Kind: organization
  • Location: Italy

GitHub Events

Total
  • Release event: 1
  • Watch event: 13
  • Delete event: 1
  • Issue comment event: 2
  • Push event: 17
  • Pull request review event: 1
  • Pull request event: 3
  • Fork event: 2
  • Create event: 2
Last Year
  • Release event: 1
  • Watch event: 13
  • Delete event: 1
  • Issue comment event: 2
  • Push event: 17
  • Pull request review event: 1
  • Pull request event: 3
  • Fork event: 2
  • Create event: 2

Committers

Last synced: 8 months ago

All Time
  • Total Commits: 34
  • Total Committers: 2
  • Avg Commits per committer: 17.0
  • Development Distribution Score (DDS): 0.029
Past Year
  • Commits: 34
  • Committers: 2
  • Avg Commits per committer: 17.0
  • Development Distribution Score (DDS): 0.029
Top Committers
Name Email Commits
Giulio Romualdi g****i@g****m 33
Silvio Traversaro s****o@t****t 1
Committer Domains (Top 20 + Academic)
traversaro.it: 1

Issues and Pull Requests

Last synced: 8 months ago

All Time
  • Total issues: 0
  • Total pull requests: 2
  • Average time to close issues: N/A
  • Average time to close pull requests: 4 days
  • Total issue authors: 0
  • Total pull request authors: 2
  • Average comments per issue: 0
  • Average comments per pull request: 1.5
  • Merged pull requests: 2
  • Bot issues: 0
  • Bot pull requests: 0
Past Year
  • Issues: 0
  • Pull requests: 2
  • Average time to close issues: N/A
  • Average time to close pull requests: 4 days
  • Issue authors: 0
  • Pull request authors: 2
  • Average comments per issue: 0
  • Average comments per pull request: 1.5
  • Merged pull requests: 2
  • Bot issues: 0
  • Bot pull requests: 0
View more stats
Top Authors
Issue Authors
Pull Request Authors
  • GiulioRomualdi (2)
  • traversaro (1)
Top Labels
Issue Labels
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Dependencies

scripts/generate_animation_meshcat/environment.yml pypi
scripts/plotting/environment.yml pypi