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

Lars Schiller; Arthur Seibel; Josef Schlattmann

doi:10.3389/frobt.2020.00087

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

Front Robot AI. 2020 Jul 2:7:87. doi: 10.3389/frobt.2020.00087. eCollection 2020.

Authors

Lars Schiller¹, Arthur Seibel², Josef Schlattmann¹

Affiliations

¹ Workgroup on System Technologies and Engineering Design Methodology, Hamburg University of Technology, Hamburg, Germany.
² Fraunhofer Research Institution for Additive Manufacturing Technologies IAPT, Hamburg, Germany.

Abstract

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.

Keywords: closed-loop position control; gait pattern generator; gecko-inspired soft robot; locomotion controller; mobile robotics.