dc.contributor.author | Polycarpou, Marios M. | en |
dc.contributor.author | Yang, Yanli | en |
dc.contributor.author | Liu, Yang | en |
dc.contributor.author | Passino, Kevin | en |
dc.contributor.editor | Butenko, Sergiy | en |
dc.contributor.editor | Murphey, Robert | en |
dc.contributor.editor | Pardalos, Panos M. | en |
dc.coverage.spatial | Boston, MA | en |
dc.creator | Polycarpou, Marios M. | en |
dc.creator | Yang, Yanli | en |
dc.creator | Liu, Yang | en |
dc.creator | Passino, Kevin | en |
dc.date.accessioned | 2019-04-08T07:47:59Z | |
dc.date.available | 2019-04-08T07:47:59Z | |
dc.date.issued | 2003 | |
dc.identifier.isbn | 978-1-4757-3758-5 | |
dc.identifier.uri | http://gnosis.library.ucy.ac.cy/handle/7/44691 | |
dc.description.abstract | The main objective of this research is to develop and evaluate the performance of strategies for cooperative control of autonomous air vehicles that seek to gather information about a dynamic target environment, evade threats, and coordinate strikes against targets. The chapter presents an approach for cooperative search by a team of uninhabited autonomous air vehicles, which are equipped with sensors to view a limited region of the environment, and are able to communicate with one another to enable cooperation. The developed cooperative search framework is based on two inter-dependent tasks: (i) on-line learning of the environment and storing of the information in the form of a “search map†; and (ii) utilization of the search map and other information to compute on-line a guidance trajectory for the vehicle to follow. We develop a real-time approach for on-line cooperation between air vehicles, which is based on treating the paths of other vehicles as “soft obstacles†to be avoided. Based on artificial potential field methods, we develop the concept of “rivaling force†between vehicles as a way of enhancing cooperation. We study the stability of vehicular swarms in a multidimensional framework to try to understand what types of communications are needed to achieve cooperative search and engagement, and characteristics that affect swarm aggregation and disintegration. Simulation results are presented to illustrated the concepts developed in the chapter. | en |
dc.publisher | Springer US | en |
dc.source | Cooperative Control: Models, Applications and Algorithms | en |
dc.source.uri | https://doi.org/10.1007/978-1-4757-3758-5_13 | |
dc.title | Cooperative Control Design for Uninhabited Air Vehicles | en |
dc.type | info:eu-repo/semantics/bookChapter | |
dc.description.startingpage | 283 | |
dc.description.endingpage | 321 | |
dc.author.faculty | Πολυτεχνική Σχολή / Faculty of Engineering | |
dc.author.department | Τμήμα Ηλεκτρολόγων Μηχανικών και Μηχανικών Υπολογιστών / Department of Electrical and Computer Engineering | |
dc.type.uhtype | Book Chapter | en |
dc.contributor.orcid | Polycarpou, Marios M. [0000-0001-6495-9171] | |
dc.gnosis.orcid | 0000-0001-6495-9171 | |