AC-ROS: Assurance Case Driven Adaptation for the Robot Operating System
Cyber-physical systems that implement self-adaptive behavior, such as autonomous robots, need to ensure that requirements remain satisfied across run-time adaptations. The Robot Operating System (ROS), a middleware infrastructure for robotic systems, is widely used in both research and industrial applications. However, ROS itself does not provide functionality to assure self-adaptive behavior. This paper introduces AC-ROS, which fills this gap by using assurance case models at run time to manage the self-adaptive operation of ROS-based software. Assurance cases provide structured arguments that a system satisfies requirements and can be specified graphically with Goal Structuring Notation (GSN) models. AC-ROS uses GSN models to instantiate and populate a ROS-based MAPE-K framework, which in turn uses these models at run time to assure system behavior adheres to requirements across adaptations. For this study, AC-ROS is implemented and tested on EvoRally, a 1:5-scale autonomous vehicle controlled by software based on ROS.
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Sophie Wood, Nicholas MatragkasUniversity of York, Dimitris KolovosUniversity of York, Richard PaigeMcMaster University, Simos GerasimouUniversity of York, UKLink to publication Pre-print
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