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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:

pip install https://github.com/ompl/ompl/releases/download/prerelease/ompl-1.6.0-cp310-cp310-manylinux_2_28_x86_64.whl

For Python 3.11:

pip install https://github.com/ompl/ompl/releases/download/prerelease/ompl-1.6.0-cp311-cp311-manylinux_2_28_x86_64.whl

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.