On an Improved State Parametrization for Soft Robots with Piecewise Constant Curvature and Its Use in Model Based Control

Cosimo Della Santina, Antonio Bicchi, Daniela Rus

Research output: Contribution to journalArticlepeer-review

142 Scopus citations

Abstract

Piecewise constant curvature models have proven to be an useful tool for describing kinematics and dynamics of soft robots. However, in their three dimensional formulation they suffer from many issues limiting their range of applicability - as discontinuities and singularities - mainly concerning the straight configuration of the robot. In this work we analyze these flaws, and we show that they are not due to the piecewise constant curvature assumption itself, but that instead they are a byproduct of the commonly employed direction/angle of bending parametrization of the state. We therefore consider an alternative state representation which solves all the discussed issues, and we derive a model based controller based on it. Examples in simulation are provided to support and describe the theoretical results. When using the novel parametrization, the system is able to perform more complex tasks, with a strongly reduced computational burden, and without incurring in spikes and discontinuous behaviors.

Original languageEnglish
Article number8961972
Pages (from-to)1001-1008
Number of pages8
JournalIEEE Robotics and Automation Letters
Volume5
Issue number2
DOIs
StatePublished - Apr 2020
Externally publishedYes

Keywords

  • Modeling
  • and learning for soft robots
  • control
  • motion control
  • natural machine motion

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