  During the planning phase of industrial robot workplaces, hazard analyses are
required so that potential hazards for human workers can be identified and
appropriate safety measures can be implemented. Existing hazard analysis
methods use human reasoning, checklists and/or abstract system models, which
limit the level of detail. We propose a new approach that frames hazard
analysis as a search problem in a dynamic simulation environment. Our goal is
to identify workplace hazards by searching for simulation sequences that result
in hazardous situations. We solve this search problem by placing virtual humans
into workplace simulation models. These virtual humans act in an adversarial
manner: They learn to provoke unsafe situations, and thereby uncover workplace
hazards. Although this approach cannot replace a thorough hazard analysis, it
can help uncover hazards that otherwise may have been overlooked, especially in
early development stages. Thus, it helps to prevent costly re-designs at later
development stages. For validation, we performed hazard analyses in six
different example scenarios that reflect typical industrial robot workplaces.
