  When a vehicle observes another one, the two vehicles' poses are correlated
by this spatial relative observation, which can be used in cooperative
localization for further increasing localization accuracy and precision. To use
spatial relative observations, we propose to add them into a pose graph for
optimal pose estimation. Before adding them, we need to know the identities of
the observed vehicles. The vehicle identification is formulated as a linear
assignment problem, which can be solved efficiently. By using pose graph
techniques and the start-of-the-art factor composition/decomposition method,
our cooperative localization algorithm is robust against communication delay,
packet loss, and out-of-sequence packet reception. We demonstrate the usability
of our framework and effectiveness of our algorithm through both simulations
and real-world experiments using three vehicles on the road.
