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.

翻译：在人类身边工作的机器人，特别是在辅助老年人日常任务或与制造业工人协作等敏感场景中，必须保证安全并培养用户信任。连续体软体机械臂通过材料顺应性承诺安全性，但随着设计向更高精度、更大负载能力和更快速度演进，并越来越多地融入刚性元件，其伤害风险再次显现。本文提出一个综合的高阶控制屏障函数（HOCBF）+ 高阶控制李雅普诺夫函数（HOCLF）框架，该框架在环境交互过程中对整个软体机器人身体实施严格的接触力限制。我们的方法将可微分分段Cosserat杆段动力学模型与基于软体机器人几何形状的凸多边形距离近似度量——称为可微分保守分离轴定理（DCSAT）——相结合，以实现实时的全身碰撞检测、解决及安全约束的强制执行。通过将HOCBF嵌入我们的优化例程，我们保证了安全性，例如允许在HOCLF驱动的运动目标下实现操作空间内的安全导航。大量的平面仿真表明，我们的方法在实现精确的形状和任务空间调节的同时，保持了安全有界的接触。因此，这项工作为软体机器人在以人为中心的环境中的部署奠定了可证明安全性和性能的基础。