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Episodic Memories for Safety-Aware Robots: Knowledge Representation and Reasoning for Robots that Safely Interact with Human Co-Workers

机译:安全意识机器人的情节记忆:安全地与人类同事互动的机器人的知识表示和推理

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In 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.
机译:在未来的工厂和分销中心,人类和机器人应在近距离且甚至身体互动中共同努力。这转向联合人体机器人团队提出了如何确保工人安全的问题。在这份手稿中,我们为安全意识机器人提供了一种新型的情节内存系统。使用此系统,机器人可以在安全概念水平上回答有关其行为的问题。我们建立了该系统作为知识框架的扩展及其概念的影片内记忆。我们在安全的物理人员机器人相互作用(PHRI)实验中评估了该系统,其中机器人必须对手术器械进行分类,同时也确保其人类同事的安全性。我们的实验结果表明,系统作为机器人的信仰状态进行在线推理的效果,以及通过快速和灵活的查询界面支持离线安全性分析的能力。为此,我们展示了系统重建其几何环境,行动方向和运动参数的能力,从对安全相关事件的描述中。我们还展示了系统进行统计分析的能力。

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