  We present a new approach to the cooperative localisation problem by applying
the theory of minimum energy filtering. We consider the problem of estimating
the pose of a group of mobile robots in an environment where robots can
perceive fixed landmarks and neighbouring robots as well as share information
with others over a communication channel. Whereas the vast majority of the
existing literature applies some variant of a Kalman Filter, we derive a set of
filter equations for the global state estimate based on the principle of
minimum energy filtering. We show how the filter equations can be decoupled and
the calculations distributed among the robots in the network without requiring
a central processing node. Finally, we provide a demonstration of the filter's
performance in simulation.
