Reduced order modeling and model order reduction for continuum manipulators: an overview

Hadi Sadati, S. Elnaz Naghibi, Lyndon da Cruz, Christos Bergeles

Research output: Contribution to journalReview articlepeer-review

Abstract

Soft robot’s natural dynamics calls for the development of tailored modeling techniques for control. However, the high-dimensional configuration space of the geometrically exact modeling approaches for soft robots, i.e., Cosserat rod and Finite Element Methods (FEM), has been identified as a key obstacle in controller design. To address this challenge, Reduced Order Modeling (ROM), i.e., the approximation of the full-order models, and Model Order Reduction (MOR), i.e., reducing the state space dimension of a high fidelity FEM-based model, are enjoying extensive research. Although both techniques serve a similar purpose and their terms have been used interchangeably in the literature, they are different in their assumptions and implementation. This review paper provides the first in-depth survey of ROM and MOR techniques in the continuum and soft robotics landscape to aid Soft Robotics researchers in selecting computationally efficient models for their specific tasks.

Original languageEnglish
Article number1094114
JournalFront. Robot. AI
Volume10
DOIs
Publication statusPublished - 2023

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