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+.

$ pip install pyelastica

For plotting videos, ffmpeg is typically used.

Documentation of PyElastica is available here.

Related Projects

• C++ elastica for large-simulation: elasticapp
• JAX extension for PyElastica, blocking and GPU computing: PyElastica-Jax
• Cosserat rod with magnetic field: magneto-pyelastica
  • Simulate magnetic Cosserat rods interacting with external magnetic environments.
• gymnasium environment for learning and control: gym-softrobot
• BR2 FREE pneumatic actuator simulation: BR2-simulator
• Octopus muscle actuation model: COOMM
• Blender visualization: Blender-Soft-Rod
• Rhino3D plugin for visualizaion: plugin
• Elastica web-interface: PyElastica-Interactive

Citation

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

@software{PyElastica,
  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},
  year         = 2024,
  publisher    = {Zenodo},
  doi          = {10.5281/zenodo.7658871},
  url          = {https://doi.org/10.5281/zenodo.7658871}
}

References

• Gazzola, Dudte, McCormick, Mahadevan, Forward and inverse problems in the mechanics of soft filaments, Royal Society Open Science, 2018. doi: 10.1098/rsos.171628
• Zhang, Chan, Parthasarathy, Gazzola, Modeling and simulation of complex dynamic musculoskeletal architectures, Nature Communications, 2019. doi: 10.1038/s41467-019-12759-5

List of publications and submissions

• Digital twins for the design, interactive control, and deployment of modular, fiber-reinforced soft continuum arms (2026) (Advanced Intelligent Systems)
• Elastica++: A high-performance, multiphysics framework for large interacting assemblies of Cosserat rods (2026)
• Soft, slender and active structures in fluids: embedding Cosserat rods in vortex methods (2024)
• Neural models and algorithms for sensorimotor control of an octopus arm (2024)
• On the mechanical origins of waving, coiling and skewing in Arabidopsis thaliana roots (2024) (PNAS)
• Pushing with soft robotic arms via deep reinforcement learning (2024) (Advanced Intelligent Systems)
• Topology, dynamics, and control of an octopus-analog muscular hydrostat (2023)
• Hierarchical control and learning of a foraging CyberOctopus (2023) (Advanced Intelligent Systems)
• Energy-shaping control of a muscular octopus arm moving in three dimensions (2023) (Proceedings of the Royal Society A 2023)
• Ablation study of a dynamic model for a 3d-printed pneumatic soft robotic arm (2023) (IEEE Access)
• Learning a controller for soft robotic arms and testing its generalization to new observations, dynamics, and tasks (2023) (IEEE RoboSoft 2023)
• A sensory feedback control law for octopus arm movements (2022) (IEEE CDC 2022)
• Control-oriented modeling of bend propagation in an octopus arm (2021) (IEEE ACC 2022)
• A physics-informed, vision-based method to reconstruct all deformation modes in slender bodies (2021) (IEEE ICRA 2022) code
• Optimal control of a soft CyberOctopus arm (2021) (IEEE ACC 2021)
• Elastica: A compliant mechanics environment for soft robotic control (2021) (IEEE RA-L 2021)
• Controlling a CyberOctopus soft arm with muscle-like actuation (2020) (IEEE CDC 2021)
• Energy shaping control of a CyberOctopus soft arm (2020) (IEEE CDC 2020)

Contribution

If you would like to participate, please read our contribution guideline. Private development branches are moved to elastica-python repository; access is limited to the core developers, collaborators, and maintainers.

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