This paper addresses the problem of decentralized, collaborative state
estimation in robotic teams. In particular, this paper considers problems where
individual robots estimate similar physical quantities, such as each other's
position relative to themselves. The use of \emph{pseudomeasurements} is
introduced as a means of modelling such relationships between robots' state
estimates, and is shown to be a tractable way to approach the decentralized
state estimation problem. Moreover, this formulation easily leads to a
general-purpose observability test that simultaneously accounts for
measurements that robots collect from their own sensors, as well as the
communication structure within the team. Finally, input preintegration is
proposed as a communication-efficient way of sharing odometry information
between robots, and the entire theory is appropriate for both vector-space and
Lie-group state definitions. The proposed framework is evaluated on three
different simulated problems, and one experiment involving three quadcopters.Comment: 15 pages, 13 figures, submitted to IEE