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Shape Control for Modular Continuum Soft Arms: A Distributed Approach to Address Redundancy

Samuele Bordini, Daniele Caradonna, Antonio Bicchi, Egidio Falotico

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Key figure (auto-extracted from paper)
A scalable distributed control framework enables modular soft arms to achieve complex, adaptable shapes and precise tip positioning through local module collaboration without centralized computation.
soft robotics distributed control modular continuum arms shape control tip position regulation decentralized control

Problem

Designing scalable shape controllers for modular continuum soft arms is hindered by modeling complexity, hyper-redundancy, and the computational burden of centralized approaches that do not adapt well to varying module counts.

Approach

Each self-contained module runs a local controller that collaborates with adjacent modules using only minimal relative position data, applying progressively relaxed kinematic strategies alongside a decentralized dynamic controller to regulate shape and tip position.

Key results

  • Scalable distributed kinematic control framework independent of module count
  • Three adapted strategies (Consensus, Bipartite Consensus, Formation Control) enabling progressively complex shapes
  • Decentralized curvature-based dynamic controller ensuring transient stability
  • Validated via numerical analysis and dynamic simulations on 3- and 5-module arms in SoRoSim

Why it matters

Provides a computationally efficient, modular control solution that enables soft robots to adapt to unstructured environments and scale seamlessly with hardware configurations.

Abstract

Modular continuum soft arms represent an emerg- ing class of robotic systems characterized by flexible, highly de- formable structures. Designing shape controllers for these arms poses significant challenges due to their modeling complexity and hyper-redundant nature. Our goal is to develop a scalable control framework for modular arms, where each module is self-contained. Starting from distributed control theory, we assign a collaborative controller to each soft module. Through collaboration among mod- ules,theframeworkenablesthesystemtoachievethedesiredtippo- sition and shape. Each controller relies on the minimal model, such as the Constant Curvature, of its self-contained module and the local transformation shared by adjacent modules. We present three kinematic control strategies - Consensus, Bipartite Consensus, and Formation Control - for a modular continuum soft arm, that pro- gressively relax constraints to achieve more complex, adaptable shapes. In addition, we develop a decentralized curvature-based dynamic controller to manage dynamic coupling among modules. The validation is carried out through numerical analysis and dy- namic simulations of soft arms with varying numbers of modules.

Index terms

Modeling Control and Learning for Soft Robots Distributed Robot Systems

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