  This paper discusses developments for a multi-limb morphogenetic UAV,
MorphoGear, that is capable of both aerial flight and ground locomotion. A
hybrid path planning algorithm based on A* strategy has been developed enabling
seamless transition between air-to-ground navigation modes, thereby enhancing
robot's mobility in complex environments. Moreover, precise path following is
achieved during ground locomotion with a Model Predictive Control (MPC)
architecture for its novel walking behaviour. Experimental validation was
conducted in the Unity simulation environment utilizing Python scripts to
compute control values. The algorithms' performance is validated by the Root
Mean Squared Error (RMSE) of 0.91 cm and a maximum error of 1.85 cm, as
demonstrated by the results. These developments highlight the adaptability of
MorphoGear in navigation through cluttered environments, establishing it as a
usable tool in autonomous exploration, both aerial and ground-based.
