A Gait Pattern Generator for Closed-Loop Position Control of a Soft Walking Robot
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In: Frontiers in Robotics and AI, Vol. 7, 87, 02.07.2020.
Research output: Journal contributions › Journal articles › Research › peer-review
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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 -