We introduce a novel simulation-based approach to identify hazards that result from unexpected worker behavior in human-robot collaboration. Simulation-based safety testing must take into account the fact that human behavior is variable and that human error can occur. When only the expected worker behavior is simulated, critical hazards can remain undiscovered. On the other hand, simulating all possible worker behaviors is computationally infeasible. This raises the problem of how to find interesting (i.e., potentially hazardous) worker behaviors given a limited number of simulation runs. We frame this as a search problem in the space of possible worker behaviors. Because this search space can get quite complex, we introduce the following measures: (1) Search space restriction based on workflow-constraints, (2) prioritization of behaviors based on how far they deviate from the nominal behavior, and (3) the use of a risk metric to guide the search towards high-risk behaviors which are more likely to expose hazards. We demonstrate the approach in a collaborative workflow scenario that involves a human worker, a robot arm, and a mobile robot.
翻译:我们引入了一种新的基于模拟的方法来识别人类-机器人合作中工人意外行为造成的危害。 模拟基于安全测试必须考虑到人类行为变幻莫测的事实, 人类错误可能发生。 当只模拟了预期的工人行为时, 关键危险仍然无法被发现。 另一方面, 模拟所有可能的工人行为是计算不可行的。 这就提出了如何找到有趣的( 即潜在危险) 工人行为的问题, 在模拟运行次数有限的情况下。 我们将此设置为在可能的工人行为空间中的搜索问题。 由于这一搜索空间可能变得相当复杂, 我们引入了以下措施:(1) 搜索基于工作流程限制的空间,(2) 根据它们与名义行为不同的程度确定行为的优先顺序,(3) 使用风险指标来指导对更可能暴露危害的高风险行为的搜索。 我们展示了在涉及人类工人、 机器人臂 和移动机器人的协作工作流程情景中的方法 。