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A gait pattern generator for closed-loop position control of a soft walking robot
Citation Link: https://doi.org/10.15480/882.2966
Publikationstyp
Journal Article
Publikationsdatum
2020-07-02
Sprache
English
TORE-URI
Enthalten in
Volume
7
Article Number
87
Citation
Frontiers in Robotics and AI (7): 87 (2020-07-02)
Publisher DOI
Scopus ID
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.
Schlagworte
closed-loop position control
gait pattern generator
gecko-inspired soft robot
locomotion controller
mobile robotics
DDC Class
600: Technik
Projekt(e)
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.”
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