用动态参数实时评估人机协作风险，提升安全防护精度。
Dynamic Risk Assessment for Human-Robot Collaboration Using a Heuristics-based Approach
- 通过距离、速度和头部朝向等参数构建风险指标
- 非线性启发函数将参数转为可量化危害值
- 适合工业场景下人机协作的安全监控应用
人机协作（HRC）带来显著安全挑战，尤其在保护与协作机器人（cobots）共处的人类操作员方面。现有ISO标准虽强调风险评估与危险识别，但在涉及多种设计因素和动态交互的复杂环境中仍显不足。本文提出一种基于启发式方法的客观危险分析技术，支持动态风险评估，减少对专家经验的依赖。该方法监测人体部位与cobot间的距离、cobot的笛卡尔速度，以及人类头部在协作工作区内的朝向等场景参数，并通过非线性启发函数将其转换为危险指标。这些指标被聚合以估算特定场景的总体危险水平。所提方法在包含多种人-机器人交互的工业数据集上进行了验证。
原文摘要 · Abstract (English)
Human-robot collaboration (HRC) introduces significant safety challenges, particularly in protecting human operators working alongside collaborative robots (cobots). While current ISO standards emphasize risk assessment and hazard identification, these procedures are often insufficient for addressing the complexity of HRC environments, which involve numerous design factors and dynamic interactions. This publication presents a method for objective hazard analysis to support Dynamic Risk Assessment, extending beyond reliance on expert knowledge. The approach monitors scene parameters, such as the distance between human body parts and the cobot, as well as the cobot`s Cartesian velocity. Additionally, an anthropocentric parameter focusing on the orientation of the human head within the collaborative workspace is introduced. These parameters are transformed into hazard indicators using non-linear heuristic functions. The hazard indicators are then aggregated to estimate the total hazard level of a given scenario. The proposed method is evaluated using an industrial dataset that depicts various interactions between a human operator and a cobot.
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