Tracking and Mapping of Spatiotemporal Quantities Using Unicellular Swarm Intelligence

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Details

The book discusses new algorithms capable of searching for, tracking, mapping and providing a visualization of invisible substances. It reports on the realization of a bacterium-inspired robotic controller that can be used by an agent to search for any environmental spatial function such as temperature or pollution. Using the parameters of a mathematical model, the book shows that it is possible to control the exploration, exploitation and sensitivity of the agent. This feature sets the work apart from the usual method of applying the bacterium behavior to robotic agents. The book also discusses how a computationally tractable multi-agent robotic controller was developed and used to track as well as provide a visual map of a spatio-temporal distribution of a substance. On the one hand, this book provides biologists and ecologists with a basis to perform simulations related to how individual organisms respond to spatio-temporal factors in their environment as well as predict and analyze the behavior of organisms at a population level. On the other hand, it offers robotic engineers practical and fresh insights into the development of computationally tractable algorithms for spatial exploratory and mapping robots. It also allows a more general audience to gain an understanding of the design of computational intelligence algorithms for autonomous physical systems.


Describes novel biological inspired algorithms as well as their validation and analysis using simulation and physical Provides readers with an insight on how to cast an engineering problem into a nature that can be solved using biological inspired solutions Presents a good balance between theory and practice: from the analysis of biological systems to the implementation of bioinspired algorithms for engineering control purposes Includes supplementary material: sn.pub/extras

Inhalt
Introduction.- Literature Review.- Investigative Process.- Developing and Implementing a Source Finding Controller.- Relationship between the Berg-Brown Model and the Keller-Segel Model.- Behaviour Based Coverage Controller.- Improvements and towards RealWorld Applications.- Conclusion.

Weitere Informationen

  • Allgemeine Informationen
    • GTIN 09783319274232
    • Lesemotiv Verstehen
    • Genre Mechanical Engineering
    • Auflage 1st edition 2016
    • Sprache Englisch
    • Anzahl Seiten 204
    • Herausgeber Springer International Publishing
    • Größe H241mm x B160mm x T17mm
    • Jahr 2015
    • EAN 9783319274232
    • Format Fester Einband
    • ISBN 3319274236
    • Veröffentlichung 29.12.2015
    • Titel Tracking and Mapping of Spatiotemporal Quantities Using Unicellular Swarm Intelligence
    • Autor John Oyekan
    • Untertitel Visualisation of Invisible Hazardous Substances Using Unicellular Swarm Intelligence
    • Gewicht 477g

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