https://github.com/airo-ugent/airo-planner

Python package for single and dual robot arm motion planning.

https://github.com/airo-ugent/airo-planner

Science Score: 13.0%

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    Low similarity (11.5%) to scientific vocabulary
Last synced: 10 months ago · JSON representation

Repository

Python package for single and dual robot arm motion planning.

Basic Info
  • Host: GitHub
  • Owner: airo-ugent
  • License: mit
  • Language: Jupyter Notebook
  • Default Branch: main
  • Size: 162 KB
Statistics
  • Stars: 11
  • Watchers: 2
  • Forks: 1
  • Open Issues: 5
  • Releases: 1
Created over 2 years ago · Last pushed about 1 year ago
Metadata Files
Readme License

README.md

airo-planner

Python package for single and dual robot arm motion planning.

Key motivation: - 🔗 Bridge the gap between OMPL's powerful (but robot-agnostic) sampling-based planners and Drake's collision checking for robots. - 🦾 Standardize and add other features taylored to robotic arm motion planning such as joint limits and planning to TCP poses.

Overview 🧾

Features: this packages provides two main things: - 🤝 Interfaces: specify interfaces for robot arm motion planning - SingleArmPlanner - DualArmPlanner - 🔌 Implementations: reliable and well-tested implementations of these interfaces. - OMPL for single and dual arm planning to joint configurations or TCP poses

Design goals: - ⚓ Robustness and stability: provide an off-the-shelf motion planner that supports research by reliably covering most (not all) use cases at our labs, prioritizing dependability over niche, cutting-edge features. - 🧩 Modularity and flexibility in the core components: - 🧭 Motion planning algorithms - 💥 Collision checker - 🔙 Inverse kinematics - 🐛 Debuggability and transparency: many things can go wrong in motion planning, so we log generously and store debugging information (IK solutions, alternative paths) to troubleshoot issues.

  • 🧪 Enable experimentation: Facilitate the benchmarking and exploration of experimental planning algorithms.

🗓️ Planned features: - 🎯 Drake optimization-based planning

Getting started 🚀

Complete the Installation 🔧 and then see the getting started notebooks, where we set up: * 🎲 OMPL for sampling-based motion planning * 🐉 Drake for collision checking * 🧮 ur-analytic-ik for inverse kinematics of a UR5e

Installation 🔧

airo-planner is available on PyPI and installable with pip: pip install airo-planner

🚧 Important post-installation step

We depend on ompl with its Python bindings, which are not available on PyPI yet. The easiest way to install this for now is to use a pre-release wheel fom their Github: wget https://github.com/ompl/ompl/releases/download/1.7.0/wheels-ubuntu-latest-x86_64.zip unzip wheels-ubuntu-latest-x86_64.zip && rm wheels-ubuntu-latest-x86_64.zip pip install https://github.com/ompl/ompl/releases/download/prerelease/ompl-1.7.0-cp310-cp310-manylinux_2_28_x86_64.whl

(Replace cp310 with your Python version, e.g. cp311 for Python 3.11)

Developer guide 🛠️

See the airo-mono developer guide. A very similar process and tools are used for this package.

Releasing 🏷️

See airo-models, releasing airo-planner works the same way.

Owner

  • Name: AIRO UGent
  • Login: airo-ugent
  • Kind: organization

GitHub Events

Total
  • Issues event: 1
  • Watch event: 3
  • Issue comment event: 1
  • Push event: 5
  • Pull request event: 2
  • Fork event: 2
  • Create event: 1
Last Year
  • Issues event: 1
  • Watch event: 3
  • Issue comment event: 1
  • Push event: 5
  • Pull request event: 2
  • Fork event: 2
  • Create event: 1

Issues and Pull Requests

Last synced: 10 months ago

All Time
  • Total issues: 0
  • Total pull requests: 1
  • Average time to close issues: N/A
  • Average time to close pull requests: 4 days
  • Total issue authors: 0
  • Total pull request authors: 1
  • Average comments per issue: 0
  • Average comments per pull request: 2.0
  • Merged pull requests: 1
  • Bot issues: 0
  • Bot pull requests: 0
Past Year
  • Issues: 0
  • Pull requests: 1
  • Average time to close issues: N/A
  • Average time to close pull requests: 4 days
  • Issue authors: 0
  • Pull request authors: 1
  • Average comments per issue: 0
  • Average comments per pull request: 2.0
  • Merged pull requests: 1
  • Bot issues: 0
  • Bot pull requests: 0
Top Authors
Issue Authors
  • Victorlouisdg (1)
  • tlpss (1)
  • adverley (1)
Pull Request Authors
  • m-decoster (1)
  • dnatov (1)
Top Labels
Issue Labels
Pull Request Labels

Packages

  • Total packages: 1
  • Total downloads:
    • pypi 217 last-month
  • Total dependent packages: 1
  • Total dependent repositories: 0
  • Total versions: 3
  • Total maintainers: 2
pypi.org: airo-planner

Motion planning for single and dual robot arms.

  • Versions: 3
  • Dependent Packages: 1
  • Dependent Repositories: 0
  • Downloads: 217 Last month
Rankings
Dependent packages count: 9.7%
Average: 36.7%
Dependent repos count: 63.7%
Maintainers (2)
Last synced: 11 months ago

Dependencies

.github/workflows/mypy.yaml actions
  • actions/checkout v4 composite
  • actions/setup-python v2 composite
  • mamba-org/setup-micromamba v1.8.1 composite
.github/workflows/pre-commit.yaml actions
  • actions/checkout v4 composite
  • actions/setup-python v2 composite
  • pre-commit/action v2.0.3 composite
.github/workflows/publish-to-pypi.yaml actions
  • actions/checkout v4 composite
  • actions/download-artifact v3 composite
  • actions/setup-python v4 composite
  • actions/upload-artifact v3 composite
  • pypa/gh-action-pypi-publish release/v1 composite
  • sigstore/gh-action-sigstore-python v1.2.3 composite
.github/workflows/pytest.yaml actions
  • actions/checkout v4 composite
  • mamba-org/setup-micromamba v1.8.1 composite
pyproject.toml pypi
  • airo-drake *
  • loguru *
setup.py pypi
environment.yaml pypi
  • mypy *
  • numpy *
  • pre-commit *
  • pytest *