Optimizing workspace division for multi-UAV systems

(English) With the advance of UAV-related technology using several drones in the context of a single mission becomes more and more common. New problems and challenges appear as a result. When analyzing research works on using systems of multiple UAVs we could notice that the majority of the authors...

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Bibliographic Details
Author: Skorobogatov, Georgy|||0000-0003-2536-1470
Format: doctoral thesis
Publication Date:2023
Country:España
Institution:Universitat Politècnica de Catalunya (UPC)
Repository:UPCommons. Portal del coneixement obert de la UPC
Language:English
OAI Identifier:oai:upcommons.upc.edu:2117/404667
Online Access:https://hdl.handle.net/2117/404667
https://dx.doi.org/10.5821/dissertation-2117-404667
Access Level:Open access
Keyword:Àrees temàtiques de la UPC::Aeronàutica i espai
Description
Summary:(English) With the advance of UAV-related technology using several drones in the context of a single mission becomes more and more common. New problems and challenges appear as a result. When analyzing research works on using systems of multiple UAVs we could notice that the majority of the authors provided few details on how the path planning or workspace division was done. Out of those researchers who mentioned it, some pointed out that the planning or area partitioning was performed by hand. Other researchers presented brief ideas of algorithms with too little information to implement it. In other research works very brief lists of algorithms were given that could solve the problem. And even in those cases when the information on the algorithms was provided, the algorithms themselves did not have any freely available implementations. The purpose of this thesis is to fill the gap in the area of workspace division in order to facilitate the usage of systems consisting of multiple UAVs. In order to accomplish the aforementioned goal, in this thesis, we performed analysis of the literature on the subject of workspace decomposition between multiple robots and UAVs in particular. As it will be shown later, there are almost no research works published in this area. We implemented two state of the art algorithms and shared information on how we achieved that and what were the aspects that needed clarification or could be improved. We analyzed thoroughly the produced results, and propose improvements to the algorithm that yielded better results. And finally, we proposed, implemented, and analyzed two alternative algorithms based on the obtained experience. These algorithms outperformed the algorithm from the literature in terms of quality of the resulting partition. One algorithm solves the partition problem for convex polygons and the other one solves the partition problem for non-convex polygons. Finally, we have summarized a set of open problems that could be solved in future.