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AI-Based Learning Approach with Consideration of Safety Criteria on Example of a Depalletization Robot

Mark Jocas, Philip Kurrek, Firas Zoghlami, Mario Gianni, Vahid Salehi

发表年份
2019
引用次数
8
访问权限
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摘要

Abstract Robotic systems need to achieve a certain level of process safety during the performance of the task and at the same time ensure compliance with safety criteria for the expected behaviour. To achieve this, the system must be aware of the risks related to the performance of the task in order to be able to take these into account accordingly. Once the safety aspects have been learned from the system, the task performance must no longer influence them. To achieve this, we present a concept for the design of a neural network that combines these characteristics. This enables the learning of safe behaviour and the fixation of it. The subsequent training of the task execution no longer influences safety and achieves targeted results in comparison to a conventional neural network.

关键词

Task (project management)Computer scienceArtificial neural networkProcess (computing)Risk analysis (engineering)RobotArtificial intelligenceHuman–computer interactionMachine learningEngineering

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