A gait pattern generator for closed-loop position control of a soft walking robot

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.

Subjects

closed-loop position control

gait pattern generator

gecko-inspired soft robot

locomotion controller

mobile robotics

DDC Class

600: Technik

Funding(s)

Publikationsfonds 2020

More Funding Information

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.”

Publication version

publishedVersion

Lizenz

https://creativecommons.org/licenses/by/4.0/

Name

frobt-07-00087.pdf

Size

1.46 MB

Format

Adobe PDF

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A gait pattern generator for closed-loop position control of a soft walking robot