  In this paper we consider the localization problem for a visual sensor
network. Inspired by the alternate attitude and position distributed
optimization framework discussed in [1], we propose an estimation scheme that
exploits the unit dual quaternion algebra to describe the sensors pose. This
representation is beneficial in the formulation of the optimization scheme
allowing to solve the localization problem without designing two interlaced
position and orientation estimators, thus improving the estimation error
distribution over the two pose components and the overall localization
performance. Furthermore, the numerical experimentation asserts the robustness
of the proposed algorithm w.r.t. the initial conditions.
