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

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.

Soft Robots: Implementation, Modeling, and Methods of control

“…When the environment or objective is differing or uncertain, closed-loop control becomes a necessity, just like a freed permit robot over an unknown area or an end-effector that will pick up objects of various volumes and forms. For example, the closed-loop controller is divided into two levels; the first is feedback, which regulates the state of deformation of individual actuators, as shown in Figure 4 (A) [81]. One of the most often used closed-loop control systems is the Finite Element Method (FEM), as demonstrated in Figure (4 B).…”

Underwater Soft Robotics: A Review of Bioinspiration in Design, Actuation, Modeling, and Control

“…A model reference predictive adaptive control (MRPAC) was also implemented on the same model and showed robustness to model uncertainties. Closed-loop control methods have also been demonstrated for the position control of soft robots [122,123].…”

What is an artificial muscle? A comparison of soft actuators to biological muscles

“…Thus, continuum mechanical models are necessary. Although control models for these systems are very challenging to develop and implement, these actuators' advantages and muscle-like behavior are pushing researchers to find innovative bioinspired continuum solutions to model and control these soft-bodied robots [157,198,233,[235][236][237][238][239][240][241].…”