TY - JOUR

T1 - A Gait Pattern Generator for Closed-Loop Position Control of a Soft Walking Robot

AU - Schiller, Lars

AU - Seibel, Arthur

AU - Schlattmann, Josef

N1 - 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.

PY - 2020/7/2

Y1 - 2020/7/2

N2 - 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.

AB - 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.

KW - closed-loop position control

KW - gait pattern generator

KW - gecko-inspired soft robot

KW - locomotion controller

KW - mobile robotics

KW - Engineering

UR - http://www.scopus.com/inward/record.url?scp=85088468772&partnerID=8YFLogxK

U2 - 10.3389/frobt.2020.00087

DO - 10.3389/frobt.2020.00087

M3 - Journal articles

C2 - 33501254

AN - SCOPUS:85088468772

VL - 7

JO - Frontiers in Robotics and AI

JF - Frontiers in Robotics and AI

SN - 2296-9144

M1 - 87

ER -