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210512 ||| eng |
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|a 9783038979227
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|a 9783038979234
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|a books978-3-03897-923-4
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| 100 |
1 |
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|a Spezzano, Giandomenico
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| 245 |
0 |
0 |
|a Swarm Robotics
|h Elektronische Ressource
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| 260 |
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|b MDPI - Multidisciplinary Digital Publishing Institute
|c 2019
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| 300 |
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|a 1 electronic resource (310 p.)
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| 653 |
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|a particle swarm optimization
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| 653 |
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|a artificial flora (AF) algorithm
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| 653 |
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|a weighted implicit shape representation
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| 653 |
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|a target recognition
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| 653 |
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|a formation reconfiguration
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| 653 |
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|a event-driven coverage
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| 653 |
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|a genetic algorithm
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| 653 |
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|a unmanned aerial vehicle
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| 653 |
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|a n/a
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| 653 |
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|a coordinate motion
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| 653 |
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|a optimal configuration
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| 653 |
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|a mobile robots
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| 653 |
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|a Swarm Chemistry
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| 653 |
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|a event-triggered communication
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| 653 |
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|a formation
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| 653 |
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|a search
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| 653 |
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|a surface-water environment
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| 653 |
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|a obstacle avoidance
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| 653 |
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|a congestion control
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| 653 |
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|a environmental perception
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| 653 |
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|a meta-heuristic
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| 653 |
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|a surveillance
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| 653 |
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|a swarm intelligence
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| 653 |
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|a sliding mode controller
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| 653 |
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|a shape normalization
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| 653 |
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|a UAV swarms
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| 653 |
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|a multiple robots
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| 653 |
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|a panoramic view
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| 653 |
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|a swarm behavior
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| 653 |
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|a asymmetrical interaction
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| 653 |
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|a time-difference-of-arrival (TDOA)
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| 653 |
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|a fish swarm optimization
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| 653 |
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|a self-assembly robots
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| 653 |
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|a swarm robotics
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| 653 |
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|a system stability
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| 653 |
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|a autonomous docking
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| 653 |
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|a search algorithm
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| 653 |
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|a nonlinear disturbance observer
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| 653 |
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|a comparison
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| 653 |
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|a Computer science / bicssc
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| 653 |
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|a bionic intelligent algorithm
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| 653 |
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|a path optimization
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| 653 |
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|a Cramer-Rao low bound (CRLB)
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| 653 |
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|a improved potential field
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| 653 |
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|a virtual structure
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| 653 |
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|a patterns
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| 653 |
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|a consensus control
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| 653 |
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|a signal source localization
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| 653 |
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|a artificial bee colony algorithm
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| 653 |
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|a sensor deployment
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| 653 |
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|a multi-robot system
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| 653 |
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|a 3D model identification
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| 653 |
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|a behaviors
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| 653 |
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|a scale-invariant feature transform
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| 653 |
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|a self-organization
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| 653 |
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|a virtual linkage
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| 653 |
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|a parallel technique
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| 653 |
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|a underwater environment
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| 653 |
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|a robotics
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| 653 |
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|a modular robots
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| 653 |
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|a cooperative target hunting
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| 653 |
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|a formation control
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| 653 |
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|a optimization
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| 653 |
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|a multi-agents
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| 653 |
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|a multi-AUV
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| 653 |
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|a Swarm intelligence algorithm
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| 041 |
0 |
7 |
|a eng
|2 ISO 639-2
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| 989 |
|
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|b DOAB
|a Directory of Open Access Books
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| 500 |
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|a Creative Commons (cc), https://creativecommons.org/licenses/by-nc-nd/4.0/
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| 024 |
8 |
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|a 10.3390/books978-3-03897-923-4
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| 856 |
4 |
0 |
|u https://www.mdpi.com/books/pdfview/book/1294
|7 0
|x Verlag
|3 Volltext
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| 856 |
4 |
2 |
|u https://directory.doabooks.org/handle/20.500.12854/60367
|z DOAB: description of the publication
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|a 363
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|a 000
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|a 540
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|a 380
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|a 700
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|a 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:
|