Recently, robotic applications have been seeing widespread use across industry, often tackling safety-critical scenarios where software reliability is paramount. These scenarios often have unpredictable environments and, therefore, it is crucial to be able to provide assurances about the system at runtime. In this paper, we introduce ROSMonitoring, a framework to support Runtime Verification (RV) of robotic applications developed using the Robot Operating System (ROS). The main advantages of ROSMonitoring compared to the state of the art are its portability across multiple ROS distributions and its agnosticism w.r.t. the specification formalism. We describe the architecture behind ROSMonitoring and show how it can be used in a traditional ROS example. To better evaluate our approach, we apply it to a practical example using a simulation of the Mars curiosity rover. Finally, we report the results of some experiments to check how well our framework scales.

ROSMonitoring: A Runtime Verification Framework for ROS

Ferrando A.;Ancona D.;Franceschini L.;Mascardi V.
2020-01-01

Abstract

Recently, robotic applications have been seeing widespread use across industry, often tackling safety-critical scenarios where software reliability is paramount. These scenarios often have unpredictable environments and, therefore, it is crucial to be able to provide assurances about the system at runtime. In this paper, we introduce ROSMonitoring, a framework to support Runtime Verification (RV) of robotic applications developed using the Robot Operating System (ROS). The main advantages of ROSMonitoring compared to the state of the art are its portability across multiple ROS distributions and its agnosticism w.r.t. the specification formalism. We describe the architecture behind ROSMonitoring and show how it can be used in a traditional ROS example. To better evaluate our approach, we apply it to a practical example using a simulation of the Mars curiosity rover. Finally, we report the results of some experiments to check how well our framework scales.
2020
978-3-030-63485-8
978-3-030-63486-5
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11567/1035245
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