Digital twins offer a unique opportunity to design, test, deploy, monitor, and control real-world robotic processes. In this paper we present a novel, modular digital twinning framework developed for the investigation of safety within collaborative robotic manufacturing processes. The modular architecture supports scalable representations of user-defined cyber-physical environments, and tools for safety analysis and control. This versatile research tool facilitates the creation of mixed environments of Digital Models, Digital Shadows, and Digital Twins, whilst standardising communication and physical system representation across different hardware platforms. The framework is demonstrated as applied to an industrial case-study focused on the safety assurance of a collaborative robotic manufacturing process. We describe the creation of a digital twin scenario, consisting of individual digital twins of entities in the manufacturing case study, and the application of a synthesised safety controller from our wider work. We show how the framework is able to provide adequate evidence to virtually assess safety claims made against the safety controller using a supporting validation module and testing strategy. The implementation, evidence and safety investigation is presented and discussed, raising exciting possibilities for the use of digital twins in robotic safety assurance.
Abstract-This paper introduces an effective Static Probabilistic Timing Analysis (SPTA) for multi-path programs. The analysis estimates the temporal contribution of an evict-on-miss, random replacement cache to the probabilistic Worst-Case Execution Time (pWCET) distribution of multi-path programs. The analysis uses a conservative join function that provides a proper overapproximation of the possible cache contents and the pWCET distribution on path convergence, irrespective of the actual path followed during execution. Simple program transformations are introduced that reduce the impact of path indeterminism while ensuring sound pWCET estimates. Evaluation shows that the proposed method is efficient at capturing locality in the cache, and substantially outperforms the only prior approach to SPTA for multi-path programs based on path merging. The evaluation results show incomparability with analysis for an equivalent deterministic system using an LRU cache.
A key issue with Worst-Case Execution Time (WCET) analyses is the evaluation of the tightness and soundness of the results produced. In the absence of a ground truth, i.e. the Actual WCET (AWCET), such evaluations rely on comparison between di↵erent estimates or observed values.In this paper, we introduce a framework for the evaluation of measurement-based timing analyses. This framework uses abstract models of synthetic tasks to provide realistic execution time data as input to the analyses, while ensuring that a corresponding AWCET can be computed. The effectiveness of the framework is demonstrated by evaluating the impact of imperfect structural coverage on an existing measurement-based probabilistic timing analysis.
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