A Gait Pattern Generator for Closed-Loop Position Control of a Soft Walking Robot

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This paper presents an approach to control the position of a gecko-inspired soft robot in Cartesian space. By formulating constraints under the assumption of constant curvature, the joint space of the robot is reduced in its dimension from nine to two. The remaining two generalized coordinates describe respectively the walking speed and the rotational speed of the robot and define the so-called velocity space. By means of simulations and experimental validation, the direct kinematics of the entire velocity space (mapping in Cartesian task space) is approximated by a bivariate polynomial. Based on this, an optimization problem is formulated that recursively generates the optimal references to reach a given target position in task space. Finally, we show in simulation and experiment that the robot can master arbitrary obstacle courses by making use of this gait pattern generator.

Original languageEnglish
Article number87
JournalFrontiers in Robotics and AI
Volume7
Number of pages13
DOIs
Publication statusPublished - 02.07.2020
Externally publishedYes

Bibliographical note

Funding Information:
We thank Rohat Yildiz, Duraikannan Maruthavanan, and Jakob Muchynski for the inspiration and preliminary work. Funding. The publication of this work was supported by the German Research Foundation (DFG) and Hamburg University of Technology (TUHH) in the funding programme “Open Access Publishing.”

Publisher Copyright:
© Copyright © 2020 Schiller, Seibel and Schlattmann.

    Research areas

  • closed-loop position control, gait pattern generator, gecko-inspired soft robot, locomotion controller, mobile robotics
  • Engineering

DOI

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