![trip_logo](docs/source/trip_logo.svg) [![Code Grade](https://api.codiga.io/project/29339/score/svg)](https://frontend.code-inspector.com/project/29339/dashboard) [![codecov](https://codecov.io/gh/TriPed-Robot/TriP/branch/main/graph/badge.svg?token=T6TMY8CD8M)](https://codecov.io/gh/TriPed-Robot/TriP) [![Documentation Status](https://readthedocs.org/projects/trip-kinematics/badge/?version=main)](https://trip-kinematics.readthedocs.io/en/main/?badge=main) ![example workflow](https://github.com/TriPed-Robot/TriP/actions/workflows/python-package.yml//badge.svg) [![DOI](https://joss.theoj.org/papers/10.21105/joss.03967/status.svg)](https://doi.org/10.21105/joss.03967) # TriP TriP is a python library designed to calculate the forward- and inverse-kinematics of rigid mechanisms. This includes open chains, closed chains, and even combinations of both. ## Features - Model any robot (including closed and hybrid chains) - Generate symbolic representations of forward kinematics - Compute Jacobian matrices for differential kinematics - Compute the inverse kinematics of arbitrary rigid mechanisms - Compute the Inverse Kinematics in position and/or orientation - Support arbitrary joint types and quaternions - Includes several ready to use examples (TriPed robot, Excavator Arm) - TriPs validates the inverse kinematics algorithms with extensive testing using analytic solutions. ## Installation Installing the latest release (recommended): ``` pip install trip-kinematics ``` Installing the newest version from source: ``` git clone https://github.com/TriPed-Robot/trip_kinematics cd trip_kinematics pip install src/ ``` ## Documentation The documentation can be found [here](https://trip-kinematics.readthedocs.io/en/main/) ## How to cite this library If you find this work useful please give credits to the authors by citing: * Baumgärtner et al., (2022). TriP: A Python package for the kinematic modeling of serial-parallel hybrid robots. Journal of Open Source Software, 7(71), 3967, https://doi.org/10.21105/joss.03967 ``` @article{Baumgärtner2022, doi = {10.21105/joss.03967}, url = {https://doi.org/10.21105/joss.03967}, year = {2022}, publisher = {The Open Journal}, volume = {7}, number = {71}, pages = {3967}, author = {Jan Baumgärtner and Torben Miller}, title = {TriP: A Python package for the kinematic modeling of serial-parallel hybrid robots}, journal = {Journal of Open Source Software} } ```