  In this paper, we propose a factor-graph-based cooperative positioning
algorithm that uses RSS radio measurements and accounts for the directivity of
the antennas. This is achieved by modeling the directivity with a parametric
antenna pattern and jointly estimating position and orientation of the agents.
We propose two different approaches whereas the first one uses a continuous
representation of the orientation state and the second one a discrete
representation. We validate our proposed methods with simulations and
measurements in a static sensor network with more than 900 agents in an indoor
environment and show that the positioning accuracy can be improved
significantly by considering the influence of orientations.
