A Hybrid Control Approach for a Pneumatic-Actuated Soft Robot

Conference paper (2024)

Authors

C. Della Santina Deutsches Zentrum für Luft- und Raumfahrt (DLR), Learning & Autonomous Control - Mechanical, Maritime and Materials Engineering
Pablo Borja Plymouth University
Research Group
Learning & Autonomous Control (Mechanical, Maritime and Materials Engineering) (TU Delft)
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Published Date

2024

Language

English

Reuse Rights

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Faculty

Mechanical, Maritime and Materials Engineering

Department

Cognitive Robotics

Research Group

Learning & Autonomous Control

Abstract

The compliant nature of soft robots is appealing to a wide range of applications. However, this compliant property also poses several control challenges, e.g., how to deal with infinite degrees of freedom and highly nonlinear behaviors. This paper proposes a hybrid controller for a pneumatic-actuated soft robot. To this end, a model-based feedforward controller is designed and combined with a correction torque calculated via Gaussian process regression. Then, the proposed model-based and hybrid controllers are experimentally validated, and a detailed comparison between controllers is presented. Notably, the experimental results highlight the potential benefits of adding a learning approach to a model-based controller to enhance the closed-loop performance while reducing the computational load exhibited by purely learning strategies.

Files

978-3-031-55000-3_2.pdf
(pdf | 2.26 Mb)
- Embargo expired in 10-09-2024