Trajectory Optimization for Cable-Driven Soft Robot Locomotion

James M. Bern, P. Banzet, Roi Poranne, Stelian Coros

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review


Compliance is a defining characteristic of biological systems. Understanding how to exploit soft materials as effectively as living creatures do is consequently a fundamental challenge that is key to recreating the complex array of motor skills displayed in nature. As an important step towards this grand challenge, we propose a model-based trajectory optimization method for dynamic, cable-driven soft robot locomotion. To derive this trajectory optimization formulation, we begin by modeling soft robots using the Finite Element Method. Through a numerically robust implicit time integration scheme, forward dynamics simulations are used to predict the motion of the robot over arbitrarily long time horizons. Leveraging sensitivity analysis, we show how to efficiently compute analytic derivatives that encode the way in which entire motion trajectories change with respect to parameters that control cable contractions. This information is then used in a forward shooting method to automatically generate optimal locomotion trajectories starting from high-level goals such as the target walking speed or direction. We demonstrate the efficacy of our method by generating and analyzing locomotion gaits for multiple soft robots. Our results include both simulation and fabricated prototypes.

Original languageEnglish
Title of host publicationRobotics
Subtitle of host publicationScience and Systems 2019
EditorsAntonio Bicchi, Hadas Kress-Gazit, Seth Hutchinson
PublisherMIT Press Journals
ISBN (Print)9780992374754
StatePublished - 2019
Event15th Robotics: Science and Systems, RSS 2019 - Freiburg im Breisgau, Germany
Duration: 22 Jun 201926 Jun 2019

Publication series

NameRobotics: Science and Systems


Conference15th Robotics: Science and Systems, RSS 2019
CityFreiburg im Breisgau

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Control and Systems Engineering
  • Electrical and Electronic Engineering


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