Cooperative localization in agent networks based on interagent time-of-flightmeasurements is closely related to synchronization. To leverage this relation,we propose a Bayesian factor graph framework for cooperative simultaneouslocalization and synchronization (CoSLAS). This framework is suited to mobileagents and time-varying local clock parameters. Building on the CoSLAS factorgraph, we develop a distributed (decentralized) belief propagation algorithmfor CoSLAS in the practically important case of an affine clock model andasymmetric time stamping. Our algorithm allows for real-time operation and issuitable for a time-varying network connectivity. To achieve high accuracy atreduced complexity and communication cost, the algorithm combines particleimplementations with parametric message representations and takes advantage ofa conditional independence property. Simulation results demonstrate the goodperformance of the proposed algorithm in a challenging scenario withtime-varying network connectivity.
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