Industrial human-robot collaborative systems must be validated thoroughly with regard to safety. The sooner potential hazards for workers can be exposed, the less costly is the implementation of necessary changes. Due to the complexity of robot systems, safety flaws often stay hidden, especially at early design stages, when a physical implementation is not yet available for testing. Simulation-based testing is a possible way to identify hazards in an early stage. However, creating simulation conditions in which hazards become observable can be difficult. Brute-force or Monte-Carlo-approaches are often not viable for hazard identification, due to large search spaces. This work addresses this problem by using a human model and an optimization algorithm to generate high-risk human behavior in simulation, thereby exposing potential hazards. A proof of concept is shown in an application example where the method is used to find hazards in an industrial robot cell.

中文翻译：

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基于仿真的机器人系统早期安全验证测试

工业人机协作系统必须在安全性方面进行全面验证。暴露给工人的潜在危害越早，实施必要变更的成本越低。由于机器人系统的复杂性，安全漏洞经常被隐藏起来，尤其是在早期设计阶段，当物理实现尚不可用于测试时。基于仿真的测试是在早期识别危害的一种可能方法。但是，很难创建可观察到危害的模拟条件。由于搜索空间大，暴力破解或蒙特卡洛方法通常无法进行危险识别。这项工作通过使用人体模型和优化算法在仿真中生成高风险的人类行为来解决此问题，从而暴露出潜在的危害。