Cooperative Simultaneous Localization and Synchronization in Mobile Agent Networks

TL;DR

This paper introduces a Bayesian factor graph framework and a distributed belief propagation algorithm for cooperative localization and synchronization in mobile agent networks, effectively handling time-varying connectivity and clock parameters.

Contribution

It presents a novel CoSLAS framework and a decentralized algorithm that combines particle and parametric methods for real-time, accurate localization and synchronization.

Findings

Algorithm achieves high accuracy in simulations

Handles time-varying network connectivity effectively

Reduces complexity and communication costs

Abstract

Cooperative localization in agent networks based on interagent time-of-flight measurements is closely related to synchronization. To leverage this relation, we propose a Bayesian factor graph framework for cooperative simultaneous localization and synchronization (CoSLAS). This framework is suited to mobile agents and time-varying local clock parameters. Building on the CoSLAS factor graph, we develop a distributed (decentralized) belief propagation algorithm for CoSLAS in the practically important case of an affine clock model and asymmetric time stamping. Our algorithm allows for real-time operation and is suitable for a time-varying network connectivity. To achieve high accuracy at reduced complexity and communication cost, the algorithm combines particle implementations with parametric message representations and takes advantage of a conditional independence property. Simulation results demonstrate the good performance of the proposed algorithm in a challenging scenario with time-varying network connectivity.