Neural Networks for Robotics

Neural Networks for Robotics
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An Engineering Perspective
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Artikel-Nr:
9781351231770
Veröffentl:
2018
Einband:
EPUB
Seiten:
246
Autor:
Alma Y. (University of Guadalajara Alanis
eBook Typ:
EPUB
eBook Format:
EPUB
Kopierschutz:
Adobe DRM [Hard-DRM]
Sprache:
Deutsch
Beschreibung:

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.

 

  • Includes real-time examples for various robotic platforms.
  • Discusses real-time implementation for land and aerial robots.
  • Presents solutions for problems encountered in autonomous navigation.
  • Explores the mathematical preliminaries needed to understand the proposed methodologies.
  • Integrates computing, communications, control, sensing, planning, and other techniques by means of artificial neural networks for robotics.

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.

 

  • Includes real-time examples for various robotic platforms.
  • Discusses real-time implementation for land and aerial robots.
  • Presents solutions for problems encountered in autonomous navigation.
  • Explores the mathematical preliminaries needed to understand the proposed methodologies.
  • Integrates computing, communications, control, sensing, planning, and other techniques by means of artificial neural networks for robotics.

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