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Neural networks for robotics = an en...
~
Arana-Daniel, Nancy.
Neural networks for robotics = an engineering perspective /
紀錄類型:
書目-語言資料,印刷品 : Monograph/item
正題名/作者:
Neural networks for robotics/ Nancy Arana-Daniel, Alma Y. Alanis, Carlos Lopez-Franco.
其他題名:
an engineering perspective /
作者:
Arana-Daniel, Nancy.
其他作者:
Alanis, Alma Y.
出版者:
Boca Raton, FL :CRC Press, : c2019.,
面頁冊數:
1 online resource (227 p.) :ill., map. :
標題:
Robots - Control systems. -
電子資源:
https://www.taylorfrancis.com/books/9781351231794
ISBN:
9781351231794
Neural networks for robotics = an engineering perspective /
Arana-Daniel, Nancy.
Neural networks for robotics
an engineering perspective /[electronic resource] :Nancy Arana-Daniel, Alma Y. Alanis, Carlos Lopez-Franco. - 1st ed. - Boca Raton, FL :CRC Press,c2019. - 1 online resource (227 p.) :ill., map.
Includes bibliographical references (p. 195-208) and index.
The book offers an insight on artificial neural networks for giving a robot a high level of autonomous tasks, such as navigation, cost mapping, object recognition, intelligent control of ground and aerial robots, and clustering, with real-time implementations. The reader will learn various methodologies that can be used to solve each stage on autonomous navigation for robots, from object recognition, clustering of obstacles, cost mapping of environments, path planning, and vision to low level control. These methodologies include real-life scenarios to implement a wide range of artificial neural network architectures.
ISBN: 9781351231794Subjects--Topical Terms:
557477
Robots
--Control systems.
LC Class. No.: TJ211.35 / .A73 2018
Dewey Class. No.: 629.8/92632
Neural networks for robotics = an engineering perspective /
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The book offers an insight on artificial neural networks for giving a robot a high level of autonomous tasks, such as navigation, cost mapping, object recognition, intelligent control of ground and aerial robots, and clustering, with real-time implementations. The reader will learn various methodologies that can be used to solve each stage on autonomous navigation for robots, from object recognition, clustering of obstacles, cost mapping of environments, path planning, and vision to low level control. These methodologies include real-life scenarios to implement a wide range of artificial neural network architectures.
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https://www.taylorfrancis.com/books/9781351231794
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