用虚拟围栏实时预测人体动作，保障人机协作安全高效
A Virtual Fencing Framework for Safe and Efficient Collaborative Robotics
- 通过检测与预测人体运动构建虚拟围栏
- 在保证安全前提下减少机器人停顿时间
- 模块化设计适合各类人机协作场景
协作机器人（cobots）越来越多地与人类共同工作，亟需可靠的实时安全保障。现有安全标准（如ISO 10218、ANSI/RIA 15.06、ISO/TS 15066）要求进行风险评估，但对实时响应指导有限。本文提出一种虚拟围栏方法，通过检测与预测人体运动，确保协作机器人的安全运行。安全与性能的权衡被建模为优化问题，并通过序列二次规划求解。实验验证表明，该方法在保持安全性的前提下最小化了操作停顿，提供了一种模块化的人机协作解决方案。
原文摘要 · Abstract (English)
Collaborative robots (cobots) increasingly operate alongside humans, demanding robust real-time safeguarding. Current safety standards (e.g., ISO 10218, ANSI/RIA 15.06, ISO/TS 15066) require risk assessments but offer limited guidance for real-time responses. We propose a virtual fencing approach that detects and predicts human motion, ensuring safe cobot operation. Safety and performance tradeoffs are modeled as an optimization problem and solved via sequential quadratic programming. Experimental validation shows that our method minimizes operational pauses while maintaining safety, providing a modular solution for human-robot collaboration.
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