PyElastica

PyElastica is the python implementation of Elastica: an open-source project for simulating assemblies of slender, one-dimensional structures using Cosserat Rod theory.

Visit www.cosseratrods.org for more information and learn about Elastica and Cosserat rod theory.

How to Start

PyElastica is compatible with Python 3.10 - 3.11.

$ pip install pyelastica

With this you get a minimal version with very little dependencies.

All options:

• examples: installs dependencies to run example cases, found under the folder examples.
• docs: packages to build documentation

Options can be combined e.g.

$ pip install "pyelastica[examples,docs]"

For plotting videos, ffmpeg has to be installed:

$ conda install -c conda-forge ffmpeg

Documentation of PyElastica is available here.

If you want to simulate magnetic Cosserat rods interacting with external magnetic environments you can install the derived package using

$ pip install magneto_pyelastica

Details can be found here.

Citation

We ask that any publications which use Elastica cite as following:

@software{arman_tekinalp_2024_10883271,
  author       = {Arman Tekinalp and
                  Seung Hyun Kim and
                  Yashraj Bhosale and
                  Tejaswin Parthasarathy and
                  Noel Naughton and
                  Ali Albazroun and
                  Rahul Joon and
                  Songyuan Cui and
                  Ilia Nasiriziba and
                  Maximilian Stölzle and
                  Chia-Hsien (Cathy) Shih and
                  Mattia Gazzola},
  title        = {GazzolaLab/PyElastica: v0.3.2},
  month        = mar,
  year         = 2024,
  publisher    = {Zenodo},
  version      = {v0.3.2},
  doi          = {10.5281/zenodo.10883271},
  url          = {https://doi.org/10.5281/zenodo.10883271}
}

List of publications and submissions

• Soft, slender and active structures in fluids: embedding Cosserat rods in vortex methods (UIUC 2024)
• Neural models and algorithms for sensorimotor control of an octopus arm(UIUC 2024)
• On the mechanical origins of waving, coiling and skewing in Arabidopsis thaliana roots (Tel Aviv University, UIUC 2024) (PNAS)
• Topology, dynamics, and control of an octopus-analog muscular hydrostat (UIUC, 2023)
• Hierarchical control and learning of a foraging CyberOctopus (UIUC, 2023) (Advanced Intelligent Systems)
• Energy-shaping control of a muscular octopus arm moving in three dimensions (UIUC, 2023) (Proceedings of the Royal Society A 2023)
• A sensory feedback control law for octopus arm movements (UIUC, 2022) (IEEE CDC 2022)
• Control-oriented modeling of bend propagation in an octopus arm (UIUC, 2021) (IEEE ACC 2022)
• A physics-informed, vision-based method to reconstruct all deformation modes in slender bodies (UIUC, 2021) (IEEE ICRA 2022) code
• Optimal control of a soft CyberOctopus arm (UIUC, 2021) (IEEE ACC 2021)
• Elastica: A compliant mechanics environment for soft robotic control (UIUC, 2021) (IEEE RA-L 2021)
• Controlling a CyberOctopus soft arm with muscle-like actuation (UIUC, 2020) (IEEE CDC 2021)
• Energy shaping control of a CyberOctopus soft arm (UIUC, 2020) (IEEE CDC 2020)

Tutorials

We have created several Jupyter notebooks and Python scripts to help users get started with PyElastica. The Jupyter notebooks are available on Binder, allowing you to try out some of the tutorials without having to install PyElastica.

We have also included an example script for visualizing PyElastica simulations using POVray. This script is located in the examples folder (examples/Visualization).

Contribution

If you would like to participate, please read our contribution guideline

PyElastica is developed by the Gazzola Lab at the University of Illinois Urbana-Champaign.

Senior Developers ✨

Names arranged alphabetically

• Ali Albazroun
• Arman Tekinalp
• Chia-Hsien Shih (Cathy)
• Fan Kiat Chan
• Ilia Nasiriziba
• Noel Naughton
• Seung Hyun Kim
• Songyuan Cui
• Tejaswin Parthasarathy (Teja)
• Xiaotian Zhang
• Yashraj Bhosale