Toward generic control for soft robotic systems

TL;DR

This paper proposes a universal control framework for soft robots that leverages control compliance inspired by human motor control, enabling robustness, adaptability, and cross-platform transferability.

Contribution

It introduces a novel control paradigm that shifts from rigid-body logic to exploiting control compliance, unifying control methods across diverse soft robotic systems.

Findings

Demonstrates stable control across various soft robot morphologies

Achieves safe and reliable behavior in different actuation mechanisms

Validates the framework's transferability and robustness

Abstract

Soft robotics has advanced rapidly, yet its control methods remain fragmented: different morphologies and actuation schemes still require task-specific controllers, hindering theoretical integration and large-scale deployment. A generic control framework is therefore essential, and a key obstacle lies in the persistent use of rigid-body control logic, which relies on precise models and strict low-level execution. Such a paradigm is effective for rigid robots but fails for soft robots, where the ability to tolerate and exploit approximate action representations, i.e., control compliance, is the basis of robustness and adaptability rather than a disturbance to be eliminated. Control should thus shift from suppressing compliance to explicitly exploiting it. Human motor control exemplifies this principle: instead of computing exact dynamics or issuing detailed muscle-level commands, it expresses intention through high-level movement tendencies, while reflexes and biomechanical mechanisms autonomously resolve local details. This architecture enables robustness, flexibility, and cross-task generalization. Motivated by this insight, we propose a generic soft-robot control framework grounded in control compliance and validate it across robots with diverse morphologies and actuation mechanisms. The results demonstrate stable, safe, and cross-platform transferable behavior, indicating that embracing control compliance, rather than resisting it, may provide a widely applicable foundation for unified soft-robot control.