Contact-Aware Safety in Soft Robots Using High-Order Control Barrier and Lyapunov Functions

TL;DR

This paper presents a novel control framework combining high-order control barrier and Lyapunov functions to ensure safety in soft robots during environmental interactions, enabling real-time collision avoidance and force regulation.

Contribution

It introduces a comprehensive HOCBF + HOCLF framework with a differentiable PCS model and DCSAT for real-time safety enforcement in soft robots, addressing safety concerns with provable guarantees.

Findings

Maintains safety-bounded contacts during simulations

Enables precise shape and task-space regulation

Guarantees safety during environmental interactions

Abstract

Robots operating alongside people, particularly in sensitive scenarios such as aiding the elderly with daily tasks or collaborating with workers in manufacturing, must guarantee safety and cultivate user trust. Continuum soft manipulators promise safety through material compliance, but as designs evolve for greater precision, payload capacity, and speed, and increasingly incorporate rigid elements, their injury risk resurfaces. In this letter, we introduce a comprehensive High-Order Control Barrier Function (HOCBF) + High-Order Control Lyapunov Function (HOCLF) framework that enforces strict contact force limits across the entire soft-robot body during environmental interactions. Our approach combines a differentiable Piecewise Cosserat-Segment (PCS) dynamics model with a convex-polygon distance approximation metric, named Differentiable Conservative Separating Axis Theorem (DCSAT), based on the soft robot geometry to enable real-time, whole-body collision detection, resolution, and enforcement of the safety constraints. By embedding HOCBFs into our optimization routine, we guarantee safety, allowing, for instance, safe navigation in operational space under HOCLF-driven motion objectives. Extensive planar simulations demonstrate that our method maintains safety-bounded contacts while achieving precise shape and task-space regulation. This work thus lays a foundation for the deployment of soft robots in human-centric environments with provable safety and performance.