Probabilistic Resilience of Dynamic Multi-Robot Systems

In this letter, we aim to calculate the probability that a dynamic multi-robot system (MRS) satisfies the conditions of <inline-formula><tex-math notation="LaTeX">(r,s)</tex-math></inline-formula>-robustness, given that robot communication is subject to random failu...

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Bibliographic Details
Published inIEEE robotics and automation letters Vol. 6; no. 2; pp. 1777 - 1784
Main Authors Wehbe, Remy, Williams, Ryan K.
Format Journal Article
LanguageEnglish
Published Piscataway IEEE 01.04.2021
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
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Summary:In this letter, we aim to calculate the probability that a dynamic multi-robot system (MRS) satisfies the conditions of <inline-formula><tex-math notation="LaTeX">(r,s)</tex-math></inline-formula>-robustness, given that robot communication is subject to random failures that can be modeled using a probability distribution. The property of <inline-formula><tex-math notation="LaTeX">(r,s)</tex-math></inline-formula>-robustness is a topological property used to quantify the resilience of a multi-robot system against misbehaving robots. In the presence of random communication failures, which are typical of real-world deployments, we argue it is important to calculate the probability that an MRS will be resilient at a given time instance. To this end, we begin by enumerating edge sets that represent the conditions of <inline-formula><tex-math notation="LaTeX">(r,s)</tex-math></inline-formula>-robustness. Then, we use a tree structure known as a binary decision diagram (BDD) to efficiently encode the <inline-formula><tex-math notation="LaTeX">(r,s)</tex-math></inline-formula>-robustness conditions into a graphical form. This approach allows us to calculate the exact probability of resilience, as well as to derive bounds which are less computationally expensive to compute. To demonstrate the validity of our results, we track the probability of resilience of an MRS performing a collaborative task.
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ISSN:2377-3766
2377-3766
DOI:10.1109/LRA.2021.3060378