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Tracking and mapping of spatiotemporal quantities using unicellular swarm intelligence[electronic resource] :visualisation of invisible hazardous substances using unicellular swarm intelligence /

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
杜威分類號:	006.3824
書名/作者:	Tracking and mapping of spatiotemporal quantities using unicellular swarm intelligence : visualisation of invisible hazardous substances using unicellular swarm intelligence // by John Oluwagbemiga Oyekan.
作者:	Oyekan, John Oluwagbemiga.
出版者:	Cham : : Springer International Publishing :, 2016.
面頁冊數:	x, 194 p. : : ill. (some col.), digital ;; 24 cm.
Contained By:	Springer eBooks
標題:	Swarm intelligence.
標題:	Multiagent systems.
標題:	Engineering.
標題:	Robotics and Automation.
標題:	Complexity.
標題:	Environmental Engineering/Biotechnology.
標題:	Microbiology.
標題:	Statistical Physics, Dynamical Systems and Complexity.
ISBN:	9783319274256
ISBN:	9783319274232
內容註:	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.
摘要、提要註:	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.
電子資源:	http://dx.doi.org/10.1007/978-3-319-27425-6

Tracking and mapping of spatiotemporal quantities using unicellular swarm intelligence[electronic resource] :visualisation 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.7..

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

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

470574
Swarm intelligence.

LC Class. No.: Q337.3

Dewey Class. No.: 006.3824

Tracking and mapping of spatiotemporal quantities using unicellular swarm intelligence[electronic resource] :visualisation 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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