| dc.description.abstract | Unmanned aerial vehicles and autonomous robots have gained popularity in recent
years, finding use in military applications, surveillance of urban areas, and hobbies.
Autonomous drones require programming to follow distinct paths for their motion, and ultimately decide the shortest and most effective path in a vast network of nodes.
This can range from maneuvering around in a city for surveillance and monitoring, to reach a certain destination during natural disasters as quickly as possible to gather
life-saving environmental data.
This research is concerned with the matters of creating graph networks and ultimately calculate the shortest path from a given position to a given destination. Further motion planning for UAVs and their maneuverability based on the planned paths are also of great concern, whether it is based on following the path itself or maintaining stability of the system. Algorithms for determining the shortest path are investigated, regardless of the complexity of the graph network. Simulations are carried out and discussed, in order to illustrate and reflect various problem settings. | en_US |
