实时生成动态安全区，让机器人在复杂环境中避障并准时完成任务
Real-Time Spatiotemporal Tubes for Dynamic Unsafe Sets
- 用实时感知数据动态构建时变状态空间安全域
- 无需近似计算，直接推导出保证安全的控制指令
- 适用于移动机器人和飞行器在复杂动态环境中的高可靠性导航
本文提出一种针对具有未知动态特性的非线性纯反馈系统，在动态环境中满足预设时间内到达-避开-停留任务的实时控制框架。为此，引入实时时空管（STT）机制：STT 是状态空间中随时间变化的球体，其中心与半径仅依赖实时感知输入在线自适应调整。基于此，推导出闭式、无需近似计算的控制律，确保系统输出始终被约束在 STT 内，从而保障安全性和任务达成。本文提供了障碍物规避与按时完成任务的形式化保证。通过在移动机器人和空中飞行器上的仿真与硬件实验，验证了该框架在复杂动态环境下的有效性与可扩展性。
原文摘要 · Abstract (English)
This paper presents a real-time control framework for nonlinear pure-feedback systems with unknown dynamics to satisfy reach-avoid-stay tasks within a prescribed time in dynamic environments. To achieve this, we introduce a real-time spatiotemporal tube (STT) framework. An STT is defined as a time-varying ball in the state space whose center and radius adapt online using only real-time sensory input. A closed-form, approximation-free control law is then derived to constrain the system output within the STT, ensuring safety and task satisfaction. We provide formal guarantees for obstacle avoidance and on-time task completion. The effectiveness and scalability of the framework are demonstrated through simulations and hardware experiments on a mobile robot and an aerial vehicle, navigating in cluttered dynamic environments.
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