Abstract
This article presents an approach for assessing contingency resolution strategies using temporal logic. We present a framework for nominal mission modeling, then specifying contingency resolution strategies and evaluating their effectiveness for the mission. Our approach focuses on leveraging the use of model checkers to the domain of multi-robot missions to assess the adequacy of contingency resolution strategies that minimize the adverse effects of contingencies on the mission execution. We consider missions with deterministic as well as probabilistic transitions. We demonstrate our approach using two case studies. We consider the escorting of a ship in a port where multiple contingencies may occur concurrently and assess the adequacy of the proposed contingency resolution strategies. We also consider a manufacturing scenario where multiple assembly stations collaborate to create a product. In this case, assembly operations may fail, and human intervention is needed to complete the assembly process. We investigate several different strategies and assess their effectiveness based on mission characteristics.
Highlights
Multi-robot systems are increasingly being used to automate complex missions.1–7 Many such missions are collections of spatially separated tasks that are executed by multi-robot teams in parallel
We demonstrate the modeling of contingency resolution strategies with specific examples of contingencies for two case studies
In the first case study, we verify the correctness of contingency resolution strategies and use NuSMV to generate mission execution plans for different scenarios
Summary
Multi-robot systems are increasingly being used to automate complex missions. Many such missions are collections of spatially separated tasks that are executed by multi-robot teams in parallel. This article focuses on leveraging the use of model checkers to the domain of multi-robot missions to assess the adequacy of contingency resolution strategies to minimize the adverse effects of contingencies on the mission execution. The use of formal methods has become popular (refer to the second section) to analyze mission execution protocols and contingency resolution strategies. Formal methods provide a complete framework for handling dynamic and uncertain systems in a mathematically rigorous and logically consistent manner These methods can be exploited to quickly evaluate contingency resolution strategies and screen them for their performance. Our main focus in this article is to present an approach for evaluating contingency resolution strategies that may occur during multi-robot missions and demonstrate our approach using two examples; the first one using NuSMV model checker described, and the second one using PRISM model checker described in the fifth section Our main focus in this article is to present an approach for evaluating contingency resolution strategies that may occur during multi-robot missions and demonstrate our approach using two examples; the first one using NuSMV model checker described in the fourth section, and the second one using PRISM model checker described in the fifth section
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