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Neural networks for robotics : an engineering perspective an engineering perspective / Nancy Arana-Daniel, Carlos Lopez-Franco, Alma Y. Alanis.

By: Contributor(s): Material type: TextTextPublisher: Boca Raton, FL : CRC Press/Taylor & Francis Group, 2019Description: xvii;209 pContent type:
  • text
Media type:
  • unmediated
Carrier type:
  • volume
ISBN:
  • 9780815378686 (hardback : acid-free paper)
Subject(s): DDC classification:
  • 629.892632 ARA 23
LOC classification:
  • TJ211.35 .A73 2018
Summary: The book offers the reader the insight on artificial neural networks for giving a robot a high level of autonomy tasks such as navigation, object recognition, and clustering, with real-time implementations. These methodologies include real-life scenarios to implement a wide range of artificial neural network architectures to solve different kinds of problems encountered in autonomous navigation and object recognition problems. 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-- Provided by publisher.
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Holdings
Item type Current library Collection Call number Status Barcode
Book Book Air University Central Library Islamabad Biomedical Engineering Location Ground Floor Biomedical Engineering: Shelve No 31-35 629.892632 ARA (Browse shelf(Opens below)) Available P5815

"A CRC title, part of the Taylor & Francis imprint, a member of the Taylor & Francis Group, the academic division of T&F Informa plc."

Includes bibliographical references and index.

The book offers the reader the insight on artificial neural networks for giving a robot a high level of autonomy tasks such as navigation, object recognition, and clustering, with real-time implementations. These methodologies include real-life scenarios to implement a wide range of artificial neural network architectures to solve different kinds of problems encountered in autonomous navigation and object recognition problems. 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-- Provided by publisher.

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