Swarm Robotics
Collectively working robot teams can solve a problem more efficiently than a single robot, while also providing robustness and flexibility to the group. Swarm robotics model is a key component of a cooperative algorithm that controls the behaviors and interactions of all individuals. The robots in t...
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| Κύριος συγγραφέας: | |
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| Μορφή: | Online |
| Γλώσσα: | Αγγλικά |
| Έκδοση: |
MDPI - Multidisciplinary Digital Publishing Institute
2021
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| Θέματα: | |
| Διαθέσιμο Online: | 33641 |
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| _version_ | 1869530634296229888 |
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| author | Spezzano, Giandomenico |
| author_browse | Spezzano, Giandomenico |
| author_facet | Spezzano, Giandomenico |
| author_sort | Spezzano, Giandomenico |
| collection | Directory of Open Access Books |
| description | Collectively working robot teams can solve a problem more efficiently than a single robot, while also providing robustness and flexibility to the group. Swarm robotics model is a key component of a cooperative algorithm that controls the behaviors and interactions of all individuals. The robots in the swarm should have some basic functions, such as sensing, communicating, and monitoring, and satisfy the following properties: |
| format | Online |
| id | doab-20.500.12854ir-60367 |
| institution | Directory of Open Access Books |
| language | eng |
| publishDate | 2021 |
| publishDateRange | 2021 |
| publishDateSort | 2021 |
| publisher | MDPI - Multidisciplinary Digital Publishing Institute |
| publisherStr | MDPI - Multidisciplinary Digital Publishing Institute |
| record_format | ojs |
| spelling | doab-20.500.12854ir-603672024-04-14T10:28:06Z Swarm Robotics Spezzano, Giandomenico QA75.5-76.95 T58.5-58.64 n/a self-organization signal source localization multi-robot system sensor deployment parallel technique shape normalization genetic algorithm multiple robots optimization improved potential field optimal configuration autonomous docking asymmetrical interaction comparison behaviors patterns self-assembly robots congestion control surface-water environment target recognition coordinate motion UAV swarms formation reconfiguration swarm robotics swarm intelligence artificial bee colony algorithm obstacle avoidance fish swarm optimization search algorithm robotics time-difference-of-arrival (TDOA) formation mobile robots formation control meta-heuristic event-triggered communication search virtual structure 3D model identification surveillance event-driven coverage scale-invariant feature transform system stability Swarm intelligence algorithm bionic intelligent algorithm unmanned aerial vehicle underwater environment artificial flora (AF) algorithm swarm behavior weighted implicit shape representation Cramer–Rao low bound (CRLB) environmental perception particle swarm optimization modular robots cooperative target hunting virtual linkage multi-AUV consensus control panoramic view nonlinear disturbance observer sliding mode controller path optimization Swarm Chemistry multi-agents thema EDItEUR::U Computing and Information Technology::UY Computer science Collectively working robot teams can solve a problem more efficiently than a single robot, while also providing robustness and flexibility to the group. Swarm robotics model is a key component of a cooperative algorithm that controls the behaviors and interactions of all individuals. The robots in the swarm should have some basic functions, such as sensing, communicating, and monitoring, and satisfy the following properties: 2021-02-12T05:03:31Z 2021-02-12T05:03:31Z 2019-06-26 08:44:06 2019 book 33641 9783038979234 9783038979227 https://directory.doabooks.org/handle/20.500.12854/60367 eng image/jpeg Attribution-NonCommercial-NoDerivatives 4.0 International https://mdpi.com/books/pdfview/book/1294 MDPI - Multidisciplinary Digital Publishing Institute 10.3390/books978-3-03897-923-4 10.3390/books978-3-03897-923-4 46cabcaa-dd94-4bfe-87b4-55023c1b36d0 9783038979234 9783038979227 310 open access |
| spellingShingle | QA75.5-76.95 T58.5-58.64 n/a self-organization signal source localization multi-robot system sensor deployment parallel technique shape normalization genetic algorithm multiple robots optimization improved potential field optimal configuration autonomous docking asymmetrical interaction comparison behaviors patterns self-assembly robots congestion control surface-water environment target recognition coordinate motion UAV swarms formation reconfiguration swarm robotics swarm intelligence artificial bee colony algorithm obstacle avoidance fish swarm optimization search algorithm robotics time-difference-of-arrival (TDOA) formation mobile robots formation control meta-heuristic event-triggered communication search virtual structure 3D model identification surveillance event-driven coverage scale-invariant feature transform system stability Swarm intelligence algorithm bionic intelligent algorithm unmanned aerial vehicle underwater environment artificial flora (AF) algorithm swarm behavior weighted implicit shape representation Cramer–Rao low bound (CRLB) environmental perception particle swarm optimization modular robots cooperative target hunting virtual linkage multi-AUV consensus control panoramic view nonlinear disturbance observer sliding mode controller path optimization Swarm Chemistry multi-agents thema EDItEUR::U Computing and Information Technology::UY Computer science Spezzano, Giandomenico Swarm Robotics |
| title | Swarm Robotics |
| title_full | Swarm Robotics |
| title_fullStr | Swarm Robotics |
| title_full_unstemmed | Swarm Robotics |
| title_short | Swarm Robotics |
| title_sort | swarm robotics |
| topic | QA75.5-76.95 T58.5-58.64 n/a self-organization signal source localization multi-robot system sensor deployment parallel technique shape normalization genetic algorithm multiple robots optimization improved potential field optimal configuration autonomous docking asymmetrical interaction comparison behaviors patterns self-assembly robots congestion control surface-water environment target recognition coordinate motion UAV swarms formation reconfiguration swarm robotics swarm intelligence artificial bee colony algorithm obstacle avoidance fish swarm optimization search algorithm robotics time-difference-of-arrival (TDOA) formation mobile robots formation control meta-heuristic event-triggered communication search virtual structure 3D model identification surveillance event-driven coverage scale-invariant feature transform system stability Swarm intelligence algorithm bionic intelligent algorithm unmanned aerial vehicle underwater environment artificial flora (AF) algorithm swarm behavior weighted implicit shape representation Cramer–Rao low bound (CRLB) environmental perception particle swarm optimization modular robots cooperative target hunting virtual linkage multi-AUV consensus control panoramic view nonlinear disturbance observer sliding mode controller path optimization Swarm Chemistry multi-agents thema EDItEUR::U Computing and Information Technology::UY Computer science |
| topic_facet | QA75.5-76.95 T58.5-58.64 n/a self-organization signal source localization multi-robot system sensor deployment parallel technique shape normalization genetic algorithm multiple robots optimization improved potential field optimal configuration autonomous docking asymmetrical interaction comparison behaviors patterns self-assembly robots congestion control surface-water environment target recognition coordinate motion UAV swarms formation reconfiguration swarm robotics swarm intelligence artificial bee colony algorithm obstacle avoidance fish swarm optimization search algorithm robotics time-difference-of-arrival (TDOA) formation mobile robots formation control meta-heuristic event-triggered communication search virtual structure 3D model identification surveillance event-driven coverage scale-invariant feature transform system stability Swarm intelligence algorithm bionic intelligent algorithm unmanned aerial vehicle underwater environment artificial flora (AF) algorithm swarm behavior weighted implicit shape representation Cramer–Rao low bound (CRLB) environmental perception particle swarm optimization modular robots cooperative target hunting virtual linkage multi-AUV consensus control panoramic view nonlinear disturbance observer sliding mode controller path optimization Swarm Chemistry multi-agents thema EDItEUR::U Computing and Information Technology::UY Computer science |
| url | 33641 |
| work_keys_str_mv | AT spezzanogiandomenico swarmrobotics |