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Statements

Subject Item
n2:RIV%2F68407700%3A21230%2F13%3A00206002%21RIV14-MSM-21230___
rdf:type
skos:Concept n21:Vysledek
rdfs:seeAlso
https://controls.papercept.net/conferences/scripts/abstract.pl?ConfID=53&Number=70
dcterms:description
A leader-follower formation driving algorithm developed for control of heterogeneous groups of unmanned micro aerial and ground vehicles stabilized under a top-view relative localization is presented in this paper. The core of the proposed method lies in a novel avoidance function, in which the entire 3D formation is represented by a convex hull projected along a desired path to be followed by the group. Such a representation of the formation provides non-collision trajectories of the robots and respects requirements of the direct visibility between the team members in environment with static as well as dynamic obstacles, which is crucial for the top-view localization. The algorithm is suited for utilization of a simple yet stable visual based navigation of the group (referred to as GeNav), which together with the on-board relative localization enables deployment of large teams of micro-scale robots in environments without any available global localization system. We formulate a novel Model Predictive Control (MPC) based concept that enables to respond to the changing environment and that provides a robust solution with team members' failure tolerance included. The performance of the proposed method is verified by numerical and hardware experiments inspired by reconnaissance and surveillance missions. A leader-follower formation driving algorithm developed for control of heterogeneous groups of unmanned micro aerial and ground vehicles stabilized under a top-view relative localization is presented in this paper. The core of the proposed method lies in a novel avoidance function, in which the entire 3D formation is represented by a convex hull projected along a desired path to be followed by the group. Such a representation of the formation provides non-collision trajectories of the robots and respects requirements of the direct visibility between the team members in environment with static as well as dynamic obstacles, which is crucial for the top-view localization. The algorithm is suited for utilization of a simple yet stable visual based navigation of the group (referred to as GeNav), which together with the on-board relative localization enables deployment of large teams of micro-scale robots in environments without any available global localization system. We formulate a novel Model Predictive Control (MPC) based concept that enables to respond to the changing environment and that provides a robust solution with team members' failure tolerance included. The performance of the proposed method is verified by numerical and hardware experiments inspired by reconnaissance and surveillance missions.
dcterms:title
Navigation, Localization and Stabilization of Formations of Unmanned Aerial and Ground Vehicles Navigation, Localization and Stabilization of Formations of Unmanned Aerial and Ground Vehicles
skos:prefLabel
Navigation, Localization and Stabilization of Formations of Unmanned Aerial and Ground Vehicles Navigation, Localization and Stabilization of Formations of Unmanned Aerial and Ground Vehicles
skos:notation
RIV/68407700:21230/13:00206002!RIV14-MSM-21230___
n21:predkladatel
n22:orjk%3A21230
n3:aktivita
n20:S n20:P
n3:aktivity
P(7E08006), P(7E11017), P(GPP103/12/P756), P(LH11053), S
n3:dodaniDat
n8:2014
n3:domaciTvurceVysledku
n5:1695541 n5:3933334 n5:4334175 n5:4187288 n5:3276155
n3:druhVysledku
n17:D
n3:duvernostUdaju
n24:S
n3:entitaPredkladatele
n19:predkladatel
n3:idSjednocenehoVysledku
90873
n3:idVysledku
RIV/68407700:21230/13:00206002
n3:jazykVysledku
n12:eng
n3:klicovaSlova
Model Predictive Control; Autonomous Mobile Robots; Compact Formations; Trajectory Planning; Aerial Vehicles
n3:klicoveSlovo
n18:Aerial%20Vehicles n18:Compact%20Formations n18:Model%20Predictive%20Control n18:Trajectory%20Planning n18:Autonomous%20Mobile%20Robots
n3:kontrolniKodProRIV
[37436D33F71A]
n3:mistoKonaniAkce
Atlanta
n3:mistoVydani
New York
n3:nazevZdroje
Proceedings of 2013 International Conference on Unmanned Aircraft Systems
n3:obor
n7:JC
n3:pocetDomacichTvurcuVysledku
5
n3:pocetTvurcuVysledku
5
n3:projekt
n15:7E11017 n15:LH11053 n15:7E08006 n15:GPP103%2F12%2FP756
n3:rokUplatneniVysledku
n8:2013
n3:tvurceVysledku
Vaněk, Petr Přeučil, Libor Vonásek, Vojtěch Saska, Martin Krajník, Tomáš
n3:typAkce
n16:WRD
n3:wos
000326842400100
n3:zahajeniAkce
2013-05-28+02:00
s:numberOfPages
10
n6:doi
10.1109/ICUAS.2013.6564767
n4:hasPublisher
Springer-Verlag
n23:isbn
978-1-4799-0817-2
n10:organizacniJednotka
21230