  A novel relative localization approach for cooperative guidance of a
micro-scale Unmanned Aerial Vehicle (UAV) fusing Visual-Inertial Odometry (VIO)
with Light Detection and Ranging (LiDAR) is proposed in this paper. LiDAR-based
localization is accurate and robust to challenging environmental conditions,
but 3D LiDARs are relatively heavy and require large UAV platforms. Visual
cameras are cheap and lightweight. However, visual-based self-localization
methods exhibit lower accuracy and can suffer from significant drift with
respect to the global reference frame. We focus on cooperative navigation in a
heterogeneous team of a primary LiDAR-equipped UAV and secondary
camera-equipped UAV. We propose a novel cooperative approach combining LiDAR
relative localization data with VIO output on board the primary UAV to obtain
an accurate pose of the secondary UAV. The pose estimate is used to guide the
secondary UAV along trajectories defined in the primary UAV reference frame.
The experimental evaluation has shown the superior accuracy of our method to
the raw VIO output and demonstrated its capability to guide the secondary UAV
along desired trajectories while mitigating VIO drift.
