Model-Based Control of Planar Piezoelectric Inchworm Soft Robot for Crawling in Constrained Environments

TL;DR

This paper presents a model-based control approach for a planar piezoelectric inchworm soft robot, enabling precise shape control and movement in constrained environments, validated through experiments and simulations.

Contribution

It introduces a full-shape control method using a soft-body model for a piezoelectric soft robot, including calibration techniques for improved accuracy in real-world conditions.

Findings

Achieved shape control with mean-squared error reduced from 0.05 cm² to 0.01 cm² with calibration.

Demonstrated optimal movement under overhead constraints, maximizing speed.

Validated control approach through experiments and simulations in various roof shapes.

Abstract

Soft robots have drawn significant attention recently for their ability to achieve rich shapes when interacting with complex environments. However, their elasticity and flexibility compared to rigid robots also pose significant challenges for precise and robust shape control in real-time. Motivated by their potential to operate in highly-constrained environments, as in search-and-rescue operations, this work addresses these challenges of soft robots by developing a model-based full-shape controller, validated and demonstrated by experiments. A five-actuator planar soft robot was constructed with planar piezoelectric layers bonded to a steel foil substrate, enabling inchworm-like motion. The controller uses a soft-body continuous model for shape planning and control, given target shapes and/or environmental constraints, such as crawling under overhead barriers or "roof" safety lines. An approach to background model calibrations is developed to address deviations of actual robot shape due to material parameter variations and drift. Full experimental shape control and optimal movement under a roof safety line are demonstrated, where the robot maximizes its speed within the overhead constraint. The mean-squared error between the measured and target shapes improves from ~0.05 cm$^{2}$ without calibration to ~0.01 cm$^{2}$ with calibration. Simulation-based validation is also performed with various different roof shapes.