用高阶控制屏障函数确保软体机器人接触安全,适合人机协作场景。
Contact-Aware Safety in Soft Robots Using High-Order Control Barrier and Lyapunov Functions
- 结合高阶屏障与李雅普诺夫函数,实现全身体接触力约束。
- 仿真验证在保持安全接触的同时精准控制形状和任务空间轨迹。
- 适合需高安全性的老人协助或工厂人机协同场景。
在协助老年人日常活动或工厂人机协作等敏感场景中,机器人必须保障安全并建立用户信任。虽然连续体软机械臂因材料柔顺性具有天然安全性,但随着设计向更高精度、载荷和速度演进,并引入更多刚性部件,其伤害风险重新浮现。本文提出一种综合的高阶控制屏障函数(HOCBF)与高阶控制李雅普诺夫函数(HOCLF)框架,可在软体机器人与环境交互过程中对全身体接触力实施严格限制。方法结合可微分的分段柯瑟拉-段(PCS)动力学模型与基于几何的可微保守分离轴定理(DCSAT)距离近似度量,实现实时全身体碰撞检测、化解与安全约束执行。通过将HOCBF嵌入优化流程,确保安全,支持在HOCLF驱动的运动目标下安全操作空间导航。大量平面仿真表明,该方法能在保持接触力安全边界的同时实现精确的形状与任务空间调节。本工作为软体机器人在以人为本环境中部署提供了可证明的安全与性能基础。
原文摘要 · Abstract (English)
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.
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