  In this work we showcase the design and assessment of the performance of a
multi-camera UAV, when coupled with state-of-the-art planning and mapping
algorithms for autonomous navigation. The system leverages state-of-the-art
receding horizon exploration techniques for Next-Best-View (NBV) planning with
3D and semantic information, provided by a reconfigurable multi stereo camera
system. We employ our approaches in an autonomous drone-based inspection task
and evaluate them in an autonomous exploration and mapping scenario. We discuss
the advantages and limitations of using multi stereo camera flying systems, and
the trade-off between number of cameras and mapping performance.
