用腕部传感器实时评估人机协作中手臂操作的安全性。
Real-Time Safety Evaluation of Human Arm Operations Using a Wrist-Mounted IMU with PSM System
- 基于弹簧阻尼质量模型，通过惯性数据计算阻抗安全值。
- 三类制造任务中均实现高精度安全评估，计算效率优化。
- 适合需要实时风险预警的工业人机协同场景。
本文提出一种基于腕部惯性测量单元（IMU）与预测安全模型（PSM）融合的新方法，实现人机协作制造环境中的实时安全监控。系统通过针对手腕运动优化的弹簧-阻尼-质量模型，结合阻抗理论进行概率化安全评估，并采用频域分析法建立定量安全阈值。在工具操作、视觉检测和拾取放置三项制造任务中进行了实验验证，结果表明该方法在多种工况下均表现稳健，且通过参数优化保持了良好的计算效率。本研究为人机协作制造环境中的自适应实时风险评估提供了基础框架。
原文摘要 · Abstract (English)
This paper presents a novel approach to real-time safety monitoring in human-robot collaborative manufacturing environments through a wrist-mounted Inertial Measurement Unit (IMU) system integrated with a Predictive Safety Model (PSM). The proposed system extends previous PSM implementations through the adaptation of a spring-damper-mass model specifically optimized for wrist motions, employing probabilistic safety assessment through impedance-based computations. We analyze our proposed impedance-based safety approach with frequency domain methods, establishing quantitative safety thresholds through comprehensive comparative analysis. Experimental validation across three manufacturing tasks - tool manipulation, visual inspection, and pick-and-place operations. Results show robust performance across diverse manufacturing scenarios while maintaining computational efficiency through optimized parameter selection. This work establishes a foundation for future developments in adaptive risk assessment in real-time for human-robot collaborative manufacturing environments.
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