Swarm control with collision avoidance for multiple underactuated surface vehicles

In this paper, a novel swarm control strategy based path following guidance is addressed for multiple underactuated surface vehicles (USVs) with complex unknowns including uncertain dynamics and time-varying disturbances. By employing swarm center position (SCP) guidance together with neural network...
Ausführliche Beschreibung

Gespeichert in:

Autor*in:	Liang, Xiao [verfasserIn] Qu, Xingru [verfasserIn] Wang, Ning [verfasserIn] Li, Ye [verfasserIn] Zhang, Rubo [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2019

Schlagwörter:	Underactuated surface vehicle Swarm control Collision avoidance Swarm center position guidance Artificial potential field

Übergeordnetes Werk:	Enthalten in: Ocean engineering - Amsterdam [u.a.] : Elsevier Science, 1970, 191
Übergeordnetes Werk:	volume:191

DOI / URN:	10.1016/j.oceaneng.2019.106516

Katalog-ID:	ELV003215024

Internformat


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245	1	0	\|a Swarm control with collision avoidance for multiple underactuated surface vehicles
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520			\|a In this paper, a novel swarm control strategy based path following guidance is addressed for multiple underactuated surface vehicles (USVs) with complex unknowns including uncertain dynamics and time-varying disturbances. By employing swarm center position (SCP) guidance together with neural network approximators, the distributed robust controller is developed for each vehicle to follow the desired path, and guarantees that path following errors converge to a small neighborhood of origin. An improved artificial potential field (APF) is further responsible for collision avoidance, which makes vehicles bypass obstacles smoothly. The superiority of the proposed swarm control strategy is that the distributed controller and flexible formation enable USVs to follow the target and avoid collisions autonomously. Simulation results are proposed to illustrate the universal applicability and effectiveness of the proposed strategy.
650		4	\|a Underactuated surface vehicle
650		4	\|a Swarm control
650		4	\|a Collision avoidance
650		4	\|a Swarm center position guidance
650		4	\|a Artificial potential field
700	1		\|a Qu, Xingru \|e verfasserin \|4 aut
700	1		\|a Wang, Ning \|e verfasserin \|4 aut
700	1		\|a Li, Ye \|e verfasserin \|4 aut
700	1		\|a Zhang, Rubo \|e verfasserin \|4 aut
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author_variant	x l xl x q xq n w nw y l yl r z rz
matchkey_str	article:00298018:2019----::wrcnrliholsoaodneomliludrcu
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allfields	10.1016/j.oceaneng.2019.106516 doi (DE-627)ELV003215024 (ELSEVIER)S0029-8018(19)30655-9 DE-627 ger DE-627 rda eng 690 DE-600 50.92 bkl Liang, Xiao verfasserin aut Swarm control with collision avoidance for multiple underactuated surface vehicles 2019 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier In this paper, a novel swarm control strategy based path following guidance is addressed for multiple underactuated surface vehicles (USVs) with complex unknowns including uncertain dynamics and time-varying disturbances. By employing swarm center position (SCP) guidance together with neural network approximators, the distributed robust controller is developed for each vehicle to follow the desired path, and guarantees that path following errors converge to a small neighborhood of origin. An improved artificial potential field (APF) is further responsible for collision avoidance, which makes vehicles bypass obstacles smoothly. The superiority of the proposed swarm control strategy is that the distributed controller and flexible formation enable USVs to follow the target and avoid collisions autonomously. Simulation results are proposed to illustrate the universal applicability and effectiveness of the proposed strategy. Underactuated surface vehicle Swarm control Collision avoidance Swarm center position guidance Artificial potential field Qu, Xingru verfasserin aut Wang, Ning verfasserin aut Li, Ye verfasserin aut Zhang, Rubo verfasserin aut Enthalten in Ocean engineering Amsterdam [u.a.] : Elsevier Science, 1970 191 Online-Ressource (DE-627)30658977X (DE-600)1498543-3 (DE-576)259484164 0029-8018 nnns volume:191 GBV_USEFLAG_U SYSFLAG_U GBV_ELV GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_150 GBV_ILN_151 GBV_ILN_224 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2008 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4393 50.92 Meerestechnik AR 191
spelling	10.1016/j.oceaneng.2019.106516 doi (DE-627)ELV003215024 (ELSEVIER)S0029-8018(19)30655-9 DE-627 ger DE-627 rda eng 690 DE-600 50.92 bkl Liang, Xiao verfasserin aut Swarm control with collision avoidance for multiple underactuated surface vehicles 2019 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier In this paper, a novel swarm control strategy based path following guidance is addressed for multiple underactuated surface vehicles (USVs) with complex unknowns including uncertain dynamics and time-varying disturbances. By employing swarm center position (SCP) guidance together with neural network approximators, the distributed robust controller is developed for each vehicle to follow the desired path, and guarantees that path following errors converge to a small neighborhood of origin. An improved artificial potential field (APF) is further responsible for collision avoidance, which makes vehicles bypass obstacles smoothly. The superiority of the proposed swarm control strategy is that the distributed controller and flexible formation enable USVs to follow the target and avoid collisions autonomously. Simulation results are proposed to illustrate the universal applicability and effectiveness of the proposed strategy. Underactuated surface vehicle Swarm control Collision avoidance Swarm center position guidance Artificial potential field Qu, Xingru verfasserin aut Wang, Ning verfasserin aut Li, Ye verfasserin aut Zhang, Rubo verfasserin aut Enthalten in Ocean engineering Amsterdam [u.a.] : Elsevier Science, 1970 191 Online-Ressource (DE-627)30658977X (DE-600)1498543-3 (DE-576)259484164 0029-8018 nnns volume:191 GBV_USEFLAG_U SYSFLAG_U GBV_ELV GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_150 GBV_ILN_151 GBV_ILN_224 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2008 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4393 50.92 Meerestechnik AR 191
allfields_unstemmed	10.1016/j.oceaneng.2019.106516 doi (DE-627)ELV003215024 (ELSEVIER)S0029-8018(19)30655-9 DE-627 ger DE-627 rda eng 690 DE-600 50.92 bkl Liang, Xiao verfasserin aut Swarm control with collision avoidance for multiple underactuated surface vehicles 2019 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier In this paper, a novel swarm control strategy based path following guidance is addressed for multiple underactuated surface vehicles (USVs) with complex unknowns including uncertain dynamics and time-varying disturbances. By employing swarm center position (SCP) guidance together with neural network approximators, the distributed robust controller is developed for each vehicle to follow the desired path, and guarantees that path following errors converge to a small neighborhood of origin. An improved artificial potential field (APF) is further responsible for collision avoidance, which makes vehicles bypass obstacles smoothly. The superiority of the proposed swarm control strategy is that the distributed controller and flexible formation enable USVs to follow the target and avoid collisions autonomously. Simulation results are proposed to illustrate the universal applicability and effectiveness of the proposed strategy. Underactuated surface vehicle Swarm control Collision avoidance Swarm center position guidance Artificial potential field Qu, Xingru verfasserin aut Wang, Ning verfasserin aut Li, Ye verfasserin aut Zhang, Rubo verfasserin aut Enthalten in Ocean engineering Amsterdam [u.a.] : Elsevier Science, 1970 191 Online-Ressource (DE-627)30658977X (DE-600)1498543-3 (DE-576)259484164 0029-8018 nnns volume:191 GBV_USEFLAG_U SYSFLAG_U GBV_ELV GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_150 GBV_ILN_151 GBV_ILN_224 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2008 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4393 50.92 Meerestechnik AR 191
allfieldsGer	10.1016/j.oceaneng.2019.106516 doi (DE-627)ELV003215024 (ELSEVIER)S0029-8018(19)30655-9 DE-627 ger DE-627 rda eng 690 DE-600 50.92 bkl Liang, Xiao verfasserin aut Swarm control with collision avoidance for multiple underactuated surface vehicles 2019 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier In this paper, a novel swarm control strategy based path following guidance is addressed for multiple underactuated surface vehicles (USVs) with complex unknowns including uncertain dynamics and time-varying disturbances. By employing swarm center position (SCP) guidance together with neural network approximators, the distributed robust controller is developed for each vehicle to follow the desired path, and guarantees that path following errors converge to a small neighborhood of origin. An improved artificial potential field (APF) is further responsible for collision avoidance, which makes vehicles bypass obstacles smoothly. The superiority of the proposed swarm control strategy is that the distributed controller and flexible formation enable USVs to follow the target and avoid collisions autonomously. Simulation results are proposed to illustrate the universal applicability and effectiveness of the proposed strategy. Underactuated surface vehicle Swarm control Collision avoidance Swarm center position guidance Artificial potential field Qu, Xingru verfasserin aut Wang, Ning verfasserin aut Li, Ye verfasserin aut Zhang, Rubo verfasserin aut Enthalten in Ocean engineering Amsterdam [u.a.] : Elsevier Science, 1970 191 Online-Ressource (DE-627)30658977X (DE-600)1498543-3 (DE-576)259484164 0029-8018 nnns volume:191 GBV_USEFLAG_U SYSFLAG_U GBV_ELV GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_150 GBV_ILN_151 GBV_ILN_224 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2008 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4393 50.92 Meerestechnik AR 191
allfieldsSound	10.1016/j.oceaneng.2019.106516 doi (DE-627)ELV003215024 (ELSEVIER)S0029-8018(19)30655-9 DE-627 ger DE-627 rda eng 690 DE-600 50.92 bkl Liang, Xiao verfasserin aut Swarm control with collision avoidance for multiple underactuated surface vehicles 2019 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier In this paper, a novel swarm control strategy based path following guidance is addressed for multiple underactuated surface vehicles (USVs) with complex unknowns including uncertain dynamics and time-varying disturbances. By employing swarm center position (SCP) guidance together with neural network approximators, the distributed robust controller is developed for each vehicle to follow the desired path, and guarantees that path following errors converge to a small neighborhood of origin. An improved artificial potential field (APF) is further responsible for collision avoidance, which makes vehicles bypass obstacles smoothly. The superiority of the proposed swarm control strategy is that the distributed controller and flexible formation enable USVs to follow the target and avoid collisions autonomously. Simulation results are proposed to illustrate the universal applicability and effectiveness of the proposed strategy. Underactuated surface vehicle Swarm control Collision avoidance Swarm center position guidance Artificial potential field Qu, Xingru verfasserin aut Wang, Ning verfasserin aut Li, Ye verfasserin aut Zhang, Rubo verfasserin aut Enthalten in Ocean engineering Amsterdam [u.a.] : Elsevier Science, 1970 191 Online-Ressource (DE-627)30658977X (DE-600)1498543-3 (DE-576)259484164 0029-8018 nnns volume:191 GBV_USEFLAG_U SYSFLAG_U GBV_ELV GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_150 GBV_ILN_151 GBV_ILN_224 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2008 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4393 50.92 Meerestechnik AR 191
language	English
source	Enthalten in Ocean engineering 191 volume:191
sourceStr	Enthalten in Ocean engineering 191 volume:191
format_phy_str_mv	Article
bklname	Meerestechnik
institution	findex.gbv.de
topic_facet	Underactuated surface vehicle Swarm control Collision avoidance Swarm center position guidance Artificial potential field
dewey-raw	690
isfreeaccess_bool	false
container_title	Ocean engineering
authorswithroles_txt_mv	Liang, Xiao @@aut@@ Qu, Xingru @@aut@@ Wang, Ning @@aut@@ Li, Ye @@aut@@ Zhang, Rubo @@aut@@
publishDateDaySort_date	2019-01-01T00:00:00Z
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author	Liang, Xiao
spellingShingle	Liang, Xiao ddc 690 bkl 50.92 misc Underactuated surface vehicle misc Swarm control misc Collision avoidance misc Swarm center position guidance misc Artificial potential field Swarm control with collision avoidance for multiple underactuated surface vehicles
authorStr	Liang, Xiao
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topic_title	690 DE-600 50.92 bkl Swarm control with collision avoidance for multiple underactuated surface vehicles Underactuated surface vehicle Swarm control Collision avoidance Swarm center position guidance Artificial potential field
topic	ddc 690 bkl 50.92 misc Underactuated surface vehicle misc Swarm control misc Collision avoidance misc Swarm center position guidance misc Artificial potential field
topic_unstemmed	ddc 690 bkl 50.92 misc Underactuated surface vehicle misc Swarm control misc Collision avoidance misc Swarm center position guidance misc Artificial potential field
topic_browse	ddc 690 bkl 50.92 misc Underactuated surface vehicle misc Swarm control misc Collision avoidance misc Swarm center position guidance misc Artificial potential field
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title	Swarm control with collision avoidance for multiple underactuated surface vehicles
ctrlnum	(DE-627)ELV003215024 (ELSEVIER)S0029-8018(19)30655-9
title_full	Swarm control with collision avoidance for multiple underactuated surface vehicles
author_sort	Liang, Xiao
journal	Ocean engineering
journalStr	Ocean engineering
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author_browse	Liang, Xiao Qu, Xingru Wang, Ning Li, Ye Zhang, Rubo
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title_sort	swarm control with collision avoidance for multiple underactuated surface vehicles
title_auth	Swarm control with collision avoidance for multiple underactuated surface vehicles
abstract	In this paper, a novel swarm control strategy based path following guidance is addressed for multiple underactuated surface vehicles (USVs) with complex unknowns including uncertain dynamics and time-varying disturbances. By employing swarm center position (SCP) guidance together with neural network approximators, the distributed robust controller is developed for each vehicle to follow the desired path, and guarantees that path following errors converge to a small neighborhood of origin. An improved artificial potential field (APF) is further responsible for collision avoidance, which makes vehicles bypass obstacles smoothly. The superiority of the proposed swarm control strategy is that the distributed controller and flexible formation enable USVs to follow the target and avoid collisions autonomously. Simulation results are proposed to illustrate the universal applicability and effectiveness of the proposed strategy.
abstractGer	In this paper, a novel swarm control strategy based path following guidance is addressed for multiple underactuated surface vehicles (USVs) with complex unknowns including uncertain dynamics and time-varying disturbances. By employing swarm center position (SCP) guidance together with neural network approximators, the distributed robust controller is developed for each vehicle to follow the desired path, and guarantees that path following errors converge to a small neighborhood of origin. An improved artificial potential field (APF) is further responsible for collision avoidance, which makes vehicles bypass obstacles smoothly. The superiority of the proposed swarm control strategy is that the distributed controller and flexible formation enable USVs to follow the target and avoid collisions autonomously. Simulation results are proposed to illustrate the universal applicability and effectiveness of the proposed strategy.
abstract_unstemmed	In this paper, a novel swarm control strategy based path following guidance is addressed for multiple underactuated surface vehicles (USVs) with complex unknowns including uncertain dynamics and time-varying disturbances. By employing swarm center position (SCP) guidance together with neural network approximators, the distributed robust controller is developed for each vehicle to follow the desired path, and guarantees that path following errors converge to a small neighborhood of origin. An improved artificial potential field (APF) is further responsible for collision avoidance, which makes vehicles bypass obstacles smoothly. The superiority of the proposed swarm control strategy is that the distributed controller and flexible formation enable USVs to follow the target and avoid collisions autonomously. Simulation results are proposed to illustrate the universal applicability and effectiveness of the proposed strategy.
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title_short	Swarm control with collision avoidance for multiple underactuated surface vehicles
remote_bool	true
author2	Qu, Xingru Wang, Ning Li, Ye Zhang, Rubo
author2Str	Qu, Xingru Wang, Ning Li, Ye Zhang, Rubo
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doi_str	10.1016/j.oceaneng.2019.106516
up_date	2024-07-06T18:52:45.853Z
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fullrecord_marcxml	<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000caa a22002652 4500</leader><controlfield tag="001">ELV003215024</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20230524125339.0</controlfield><controlfield tag="007">cr uuu---uuuuu</controlfield><controlfield tag="008">230430s2019 xx \|\|\|\|\|o 00\| \|\|eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1016/j.oceaneng.2019.106516</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)ELV003215024</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(ELSEVIER)S0029-8018(19)30655-9</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rda</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="082" ind1="0" ind2="4"><subfield code="a">690</subfield><subfield code="q">DE-600</subfield></datafield><datafield tag="084" ind1=" " ind2=" "><subfield code="a">50.92</subfield><subfield code="2">bkl</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Liang, Xiao</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Swarm control with collision avoidance for multiple underactuated surface vehicles</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2019</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">nicht spezifiziert</subfield><subfield code="b">zzz</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">Computermedien</subfield><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Online-Ressource</subfield><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">In this paper, a novel swarm control strategy based path following guidance is addressed for multiple underactuated surface vehicles (USVs) with complex unknowns including uncertain dynamics and time-varying disturbances. By employing swarm center position (SCP) guidance together with neural network approximators, the distributed robust controller is developed for each vehicle to follow the desired path, and guarantees that path following errors converge to a small neighborhood of origin. An improved artificial potential field (APF) is further responsible for collision avoidance, which makes vehicles bypass obstacles smoothly. The superiority of the proposed swarm control strategy is that the distributed controller and flexible formation enable USVs to follow the target and avoid collisions autonomously. 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