Neural Networks for Robotics
About this book
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.
Reader Profile
3.8/5 · 1 readers · 228 pages · ≈ 4 h 13 m · Moderate
How long does it take to read Neural Networks for Robotics?
About ≈ 4 h 13 m — 228 pages, assuming roughly 250 words per page at 225 words per minute.
How many pages is Neural Networks for Robotics?
228 pages in its most-read edition.
Is Neural Networks for Robotics in the public domain?
No — it is still under copyright.
Who wrote Neural Networks for Robotics?
Nancy Arana-Daniel.