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Tracking and mapping of spatiotempor...

Oyekan, John Oluwagbemiga.

Tracking and mapping of spatiotemporal quantities using unicellular swarm intelligencevisualisation of invisible hazardous substances using unicellular swarm intelligence /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Tracking and mapping of spatiotemporal quantities using unicellular swarm intelligenceby John Oluwagbemiga Oyekan.
Reminder of title:	visualisation of invisible hazardous substances using unicellular swarm intelligence /
Author:	Oyekan, John Oluwagbemiga.
Published:	Cham :Springer International Publishing :2016.
Description:	x, 194 p. :ill. (some col.), digital ;24 cm.
Contained By:	Springer eBooks
Subject:	Swarm intelligence.
Online resource:	http://dx.doi.org/10.1007/978-3-319-27425-6
ISBN:	9783319274256$q(electronic bk.)

Tracking and mapping of spatiotemporal quantities using unicellular swarm intelligencevisualisation of invisible hazardous substances using unicellular swarm intelligence /
Oyekan, John Oluwagbemiga.

Tracking and mapping of spatiotemporal quantities using unicellular swarm intelligencevisualisation of invisible hazardous substances using unicellular swarm intelligence /[electronic resource] :by John Oluwagbemiga Oyekan. - Cham :Springer International Publishing :2016. - x, 194 p. :ill. (some col.), digital ;24 cm. - Biosystems & biorobotics,v.142195-3562 ;. - Biosystems & biorobotics ;v.4..

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.

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.

ISBN: 9783319274256$q(electronic bk.)

Standard No.: 10.1007/978-3-319-27425-6doiSubjects--Topical Terms:

237730
Swarm intelligence.

LC Class. No.: Q337.3

Dewey Class. No.: 006.3824

Tracking and mapping of spatiotemporal quantities using unicellular swarm intelligencevisualisation of invisible hazardous substances using unicellular swarm intelligence /
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505 0 $a 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.
520 $a 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.
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