RoboStar modelling stack: tackling the reality gap

Ana Cavalcanti
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Abstract

RoboStar technology for model-based Software Engineering for Robotics enables the construction of artefacts that capture and relate assumptions that can play a role in the reality. In this paper, we give a brief overview of the RoboStar approach.
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RoboStar建模堆栈:解决现实差距
RoboStar技术用于基于模型的机器人软件工程,可以构建捕获和关联可以在现实中发挥作用的假设的工件。在本文中,我们简要概述了RoboStar方法。
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RoboStar modelling stack: tackling the reality gap Safe control from signal temporal logic specifications using recurrent neural networks Using control synthesis for falsification and corner case generation Towards verifying neural autonomous systems Verifiable autonomy under perceptual limitations
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