  Reliable deployment of Unmanned Aerial Vehicles (UAVs) in cluttered unknown
environments requires accurate sensors for Global Navigation Satellite System
(GNSS)-denied localization and obstacle avoidance. Such a requirement limits
the usage of cheap and micro-scale vehicles with constrained payload capacity
if industrial-grade reliability and precision are required. This paper
investigates the possibility of offloading the necessity to carry heavy sensors
to another member of the UAV team while preserving the desired capability of
the smaller robot intended for exploring narrow passages. A novel cooperative
guidance framework offloading the sensing requirements from a minimalistic
secondary UAV to a superior primary UAV is proposed. The primary UAV constructs
a dense occupancy map of the environment and plans collision-free paths for
both UAVs to ensure reaching the desired secondary UAV's goals even in areas
not accessible by the bigger robot. The primary UAV guides the secondary UAV to
follow the planned path while tracking the UAV using Light Detection and
Ranging (LiDAR)-based relative localization. The proposed approach was verified
in real-world experiments with a heterogeneous team of a 3D LiDAR-equipped
primary UAV and a micro-scale camera-equipped secondary UAV moving autonomously
through unknown cluttered GNSS-denied environments with the proposed framework
running fully on board the UAVs.
