Project title: MorphoLander: Reinforcement Learning Based Landing of a Group of Drones on the Adaptive Morphogenetic UAV

Description:
This research focuses on a novel robotic system MorphoLander, heterogeneous swarm of drones for exploring rough terrain environments. The morphogenetic leader drone is capable of landing on uneven terrain, traversing it, and maintaining horizontal position to deploy smaller drones for extensive area exploration. After completing their tasks, these drones return and land back on the landing pads of MorphoGear. The Reinforcement Learning algorithm has been developed for a precise landing of drones on the leader robot that either remains static during their mission or relocates to the new position. MorphoLander has the potential to significantly enhance the efficiency of the industrial inspections, seismic surveys, and rescue missions in highly cluttered and unstructured environments. Intern will work on the Reinforcement Learning and conduct flight experiments.

Candidates requirements:
➔ basic programming skills in Python or ROS / Gazebo

Supervisor: Associate Professor Dzmitry Tsetserukou

Internship duration: 1-2 months

The start date of the internship: July 12

End day: August 31

Contact person: Dzmitry Tsetserukou d.tsetserukou@skoltech.ru