GitHub

VMRobotControl.jl

VMRobotControl allows you to build dynamic controllers for your robot as intuitive virtual mechanisms. You design your controller by building a virtual mechanism. You connect the virtual mechanism to the robot through compliant elements (like springs and dampers). The control action is automatically translated to the robot actuators (desired joint forces/torques).

This package is designed for building, simulating and controlling robots using passivity-based controllers represented by virtual mechanisms. This is in the tradition of virtual model control and energy shaping/damping injection. For a defined robot geometry, you can select specific coordinates and connect components to shape the robot dynamic properties. properties. This provides a simple way to program complex robot behaviour incrementally, from mechanical primitives.

Design features

  • Easy creation of rigid body mechanisms with dynamic components
  • Library of components like springs and dampers, both linear and nonlinear
  • Library of geometry 'coordinates' with Jacobians to help build components
  • VirtualMechanismSystem type for building virtual-mechanism controllers
  • Allocation free computation methods for fast simulation/control
  • Loading URDFs
  • Plotting and simulation with Makie.jl and DifferentialEquations.jl

Installation

Install julia.

The current recommended method to install this package is to clone the github repository and mark it as a package under development. In your terminal:

git clone git@github.com:Cambridge-Control-Lab/VMRobotControl.jl.git
julia

Then in julia, hit ] to enter Pkg mode, and run the commands

registry update
dev ./VMRobotControl.jl

Citing this library

Please cite this library as

@misc{VMRobotControl,
    author = {Daniel Larby},
    title = {VMRobotControl.jl},
    howpublished = {\url{https://github.com/Cambridge-Control-Lab/VMRobotControl}},
    year = {2024}
}

and also consider citing the authors works on optimal virtual model control and robot control for robotic surgery.

@misc{larby2024optimalvirtualmodelcontrol,
      title={Optimal Virtual Model Control for Robotics: Design and Tuning of Passivity-Based Controllers}, 
      author={Daniel Larby and Fulvio Forni},
      year={2024},
      eprint={2411.06627},
      archivePrefix={arXiv},
      primaryClass={cs.RO},
      doi = {https://doi.org/10.48550/arXiv.2411.06627},
      url={https://arxiv.org/abs/2411.06627}, 
}
@article{LARBY20238548,
    title = {A Generalized Approach to Impedance Control Design for Robotic Minimally Invasive Surgery},
    journal = {IFAC-PapersOnLine},
    year = {2023},
    note = {22nd IFAC World Congress},
    doi = {https://doi.org/10.1016/j.ifacol.2023.10.015},
    author = {Daniel Larby and Fulvio Forni},
}

Authors and Acknowledgements

I'm Daniel Larby. This package was initially developed during my PhD (here is my website!) at the Control Lab, in the Department of Engineering, University of Cambridge, CB2 1PZ, UK.

I was supported by my supervisor, Fulvio Forni, and the other students in the group.

My PhD was graciously supported by the Engineering and Physical Sciences Research Council; and by CMR Surgical.