Continuum Robot Control Strategies: From Model-Driven to Embodied Intelligence

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Publication Details

Journal
Bioinspiration & Biomimetics
Published
2026-09-17
DOI
https://doi.org/10.1088/1748-3190/aea951
Primary Topic
Soft Robotics and Applications
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
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article

Continuum Robot Control Strategies: From Model-Driven to Embodied Intelligence

Honghong Wang, Yong Zhu
Bioinspiration & Biomimetics
Soft Robotics and Applications
article

Continuum Robot Control Strategies: From Model-Driven to Embodied Intelligence

Honghong Wang, Yong Zhu
article en

Abstract

Continuum robots leverage intrinsic compliance and a high degree of freedom, making them well-suited for interaction in confined spaces. However, their distributed-parameter nature and pronounced nonlinearities pose major challenges for online closed-loop control. Guided by the origin of structural priors and by how control responsibilities are apportioned across the "brain-body-environment" loop, this survey charts the spectrum from model-driven control to embodied intelligence. Specifically, we organize model-driven control into physics-based, data-driven, and hybrid paradigms; summarize model-free control in terms of task-space feedback control, online mapping estimation, and input-output adaptive methods; and review embodied-intelligence control with an emphasis on morphological computation, distributed embodied sensing, policy learning and digital twins, and morphology-actuation-control co-design. This perspective provides a unified lens for synthesizing and comparing these three classes of control strategies.

Bioinspiration & Biomimetics
Fuyang Normal University (CN)
Fuyang Normal University
Peace, Justice and strong institutions
Openalex Percentile: Top 21%
Soft Robotics and Applications
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Continuum Robot Control Strategies: From Model-Driven to Embodied Intelligence — Honghong Wang, Yong Zhu · Bioinspiration & Biomimetics (2026) | TGRS Research Map | TGRS