/motion-planning

A pythonic motion planning library

Primary LanguageJupyter NotebookMIT LicenseMIT

Pythonic Motion Planning

PyPI version Open In Colab

Motion planning is a computational problem to find a sequence of valid configurations that moves the object from the source to destination.

This library is designed for robotic applications, especially sampling-based algorithms for high-dimension configuration spaces(e.g., robot arm).

  • pythonic: easy to debug, customize and extend
  • standalone collision checker (hpp-fcl): without relying on any physical simulator (e.g., mujoco, pybullet, sapien) to check collision
  • out-of-box: common motion planning algorithms (e.g., RRT-Connect) are implemented for robotic manipulation

Installation

This library has the following dependencies:

From pip:

pip install motion-planning

From source:

git clone https://github.com/Jiayuan-Gu/motion-planning.git
pip install -e .

From Github directly:

pip install --upgrade git+https://github.com/Jiayuan-Gu/motion-planning.git

Usage

See example.py for basic usage. Note that the SRDF associated with the URDF is needed to remove self-collision.

Logging

The logging level can be specified by the environment variable PYMP_LOG.

# Set the logging level to DEBUG for pymp
export PYMP_LOG=DEBUG

Base pose

We support specifying the pose of the base link during the initialization of the planner. We support many formats of pose (e.g., [x, y, z] for position, [w, i, j, k] for quaternion, [x, y, z, w, i, j, k] for SE(3), or a 4x4 rigid transformation matrix)

from pymp import Planner

planner = Planner(
    ...
    base_pose=[0, 0, 0],
)

Troubleshooting

ImportError: libboost_python38.so or undefined symbol

Try to force reinstall pinocchio: pip install pin --no-cache-dir --force-reinstall --upgrade.