Bartels, GeorgBeßler, DanielBeetz, Michael2021-04-232021-04-2320192019http://dx.doi.org/10.1007/s13218-019-00584-3https://dl.gi.de/handle/20.500.12116/36237In the factories and distribution centers of the future, humans and robots shall work together in close proximity and even physically interact. This shift to joint human–robot teams raises the question of how to ensure worker safety. In this manuscript, we present a novel episodic memory system for safety-aware robots. Using this system, the robots can answer questions about their actions at the level of safety concepts. We built this system as an extension of the KnowRob framework and its notion of episodic memories. We evaluated the system in a safe physical human–robot interaction (pHRI) experiment, in which a robot had to sort surgical instruments while also ensuring the safety of its human co-workers. Our experimental results show the efficacy of the system to act as a robot’s belief state for online reasoning, as well as its ability to support offline safety analysis through its fast and flexible query interface. To this end, we demonstrate the system’s ability to reconstruct its geometric environment, course of action, and motion parameters from descriptions of safety-relevant events. We also show-case the system’s capability to conduct statistical analysis.Cognitive human–robot interactionKnowledge representationRobot safetyText/Journal Article10.1007/s13218-019-00584-31610-1987