Stabilizing Low-Stiffness Soft Robots at Unstable Equilibria: A Model-Based Optimal Control Approach

Engineering notes

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Chinese explanation / 中文解读

中文解读待补充：本站会优先为 VLA、具身智能、人形机器人控制、机器人操作等高价值论文补充中文说明。

Original abstract

Continuum soft robots are highly nonlinear and underactuated systems, which makes stabilizing them around unstable equilibrium points difficult. This challenge becomes even greater in low stiffness regimes, where gravitational forces dominate elastic forces. In this letter, we explore whether optimal control can address these challenges using a computa- tionally efficient method suitable for real time use. We propose a nonlinear model predictive control (NMPC) approach based on Differential Dynamic Programming (DDP), combined with an accurate reduced order Variable Strain model with analytical derivatives. This results in an efficient control framework for addressing the stabilization problem. Tested on a soft inverted pendulum and other hybrid soft rigid systems, the method outperforms traditional controllers, stabilizes more challenging configurations, and operates reliably at real time speeds (50 150 Hz), demonstrating both effectiveness and practical feasibility in experimental settings.

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• Official / arXiv page
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