• Je něco špatně v tomto záznamu ?

Fast collective evasion in self-localized swarms of unmanned aerial vehicles

F. Novák, V. Walter, P. Petráček, T. Báča, M. Saska

. 2021 ; 16 (6) : . [pub] 20211112

Jazyk angličtina Země Velká Británie

Typ dokumentu časopisecké články, práce podpořená grantem

Perzistentní odkaz   https://www.medvik.cz/link/bmc22003205

A novel approach for achieving fast evasion in self-localized swarms of unmanned aerial vehicles (UAVs) threatened by an intruding moving object is presented in this paper. Motivated by natural self-organizing systems, the presented approach of fast and collective evasion enables the UAV swarm to avoid dynamic objects (interferers) that are actively approaching the group. The main objective of the proposed technique is the fast and safe escape of the swarm from an interferer discovered in proximity. This method is inspired by the collective behavior of groups of certain animals, such as schools of fish or flocks of birds. These animals use the limited information of their sensing organs and decentralized control to achieve reliable and effective group motion. The system presented in this paper is intended to execute the safe coordination of UAV swarms with a large number of agents. Similar to natural swarms, this system propagates a fast shock of information about detected interferers throughout the group to achieve dynamic and collective evasion. The proposed system is fully decentralized using only onboard sensors to mutually localize swarm agents and interferers, similar to how animals accomplish this behavior. As a result, the communication structure between swarm agents is not overwhelmed by information about the state (position and velocity) of each individual and it is reliable to communication dropouts. The proposed system and theory were numerically evaluated and verified in real-world experiments.

Citace poskytuje Crossref.org

000      
00000naa a2200000 a 4500
001      
bmc22003205
003      
CZ-PrNML
005      
20220225105717.0
007      
ta
008      
220113s2021 xxk f 000 0|eng||
009      
AR
024    7_
$a 10.1088/1748-3190/ac3060 $2 doi
035    __
$a (PubMed)34653998
040    __
$a ABA008 $b cze $d ABA008 $e AACR2
041    0_
$a eng
044    __
$a xxk
100    1_
$a Novák, Filip $u Department of Cybernetics, Faculty of Electrical Engineering, Czech Technical University in Prague, 166 36, Prague 6, Czech Republic
245    10
$a Fast collective evasion in self-localized swarms of unmanned aerial vehicles / $c F. Novák, V. Walter, P. Petráček, T. Báča, M. Saska
520    9_
$a A novel approach for achieving fast evasion in self-localized swarms of unmanned aerial vehicles (UAVs) threatened by an intruding moving object is presented in this paper. Motivated by natural self-organizing systems, the presented approach of fast and collective evasion enables the UAV swarm to avoid dynamic objects (interferers) that are actively approaching the group. The main objective of the proposed technique is the fast and safe escape of the swarm from an interferer discovered in proximity. This method is inspired by the collective behavior of groups of certain animals, such as schools of fish or flocks of birds. These animals use the limited information of their sensing organs and decentralized control to achieve reliable and effective group motion. The system presented in this paper is intended to execute the safe coordination of UAV swarms with a large number of agents. Similar to natural swarms, this system propagates a fast shock of information about detected interferers throughout the group to achieve dynamic and collective evasion. The proposed system is fully decentralized using only onboard sensors to mutually localize swarm agents and interferers, similar to how animals accomplish this behavior. As a result, the communication structure between swarm agents is not overwhelmed by information about the state (position and velocity) of each individual and it is reliable to communication dropouts. The proposed system and theory were numerically evaluated and verified in real-world experiments.
650    12
$a algoritmy $7 D000465
650    _2
$a zvířata $7 D000818
650    _7
$a masové shromáždění $7 D000090522 $2 czmesh
650    17
$a bezpilotní létající prostředky $7 D000088722 $2 czmesh
655    _2
$a časopisecké články $7 D016428
655    _2
$a práce podpořená grantem $7 D013485
700    1_
$a Walter, Viktor $u Department of Cybernetics, Faculty of Electrical Engineering, Czech Technical University in Prague, 166 36, Prague 6, Czech Republic
700    1_
$a Petráček, Pavel $u Department of Cybernetics, Faculty of Electrical Engineering, Czech Technical University in Prague, 166 36, Prague 6, Czech Republic
700    1_
$a Báča, Tomáš $u Department of Cybernetics, Faculty of Electrical Engineering, Czech Technical University in Prague, 166 36, Prague 6, Czech Republic
700    1_
$a Saska, Martin $u Department of Cybernetics, Faculty of Electrical Engineering, Czech Technical University in Prague, 166 36, Prague 6, Czech Republic
773    0_
$w MED00200575 $t Bioinspiration & biomimetics $x 1748-3190 $g Roč. 16, č. 6 (2021)
856    41
$u https://pubmed.ncbi.nlm.nih.gov/34653998 $y Pubmed
910    __
$a ABA008 $b sig $c sign $y p $z 0
990    __
$a 20220113 $b ABA008
991    __
$a 20220225105709 $b ABA008
999    __
$a ok $b bmc $g 1750843 $s 1154354
BAS    __
$a 3
BAS    __
$a PreBMC
BMC    __
$a 2021 $b 16 $c 6 $e 20211112 $i 1748-3190 $m Bioinspiration & biomimetics $n Bioinspir Biomim $x MED00200575
LZP    __
$a Pubmed-20220113

Najít záznam

Citační ukazatele

Nahrávání dat ...

Možnosti archivace

Nahrávání dat ...