Mobile Robots: The Evolutionary Approach (Studies in Computational Intelligence, 50),Used

Mobile Robots: The Evolutionary Approach (Studies in Computational Intelligence, 50),Used

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Brand: Springer
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This product may contain chemicals known to the State of California to cause cancer, birth defects, or other reproductive harm.

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  • Q: What topics are covered in 'Mobile Robots: The Evolutionary Approach'? A: The book covers the evolution of mobile robotics, including kinematics, locomotion mechanisms, sensor data, localization, planning, and navigation, as well as the application of bio-inspired techniques.
  • Q: Who are the authors of this book? A: The authors are Nadia Nedjah, Leandro dos Santos Coelho, and Luiza de Macedo Mourelle.
  • Q: What is the condition of this book? A: The book is listed as 'New', ensuring it is in excellent condition for readers.
  • Q: How many pages does this book have? A: The book contains 223 pages.
  • Q: What is the publication date of this book? A: The book was published on January 1, 2007.
  • Q: What is the binding type of 'Mobile Robots: The Evolutionary Approach'? A: The book is available in hardcover binding.
  • Q: Is this book suitable for beginners in mobile robotics? A: Yes, the book provides foundational concepts and advancements in mobile robotics, making it suitable for both beginners and experienced readers.
  • Q: Does this book include practical examples or case studies? A: Yes, the book discusses real-world implementations and simulations of mobile robots, highlighting their adaptability in dynamic environments.
  • Q: Can this book be useful for engineering students? A: Absolutely, it integrates concepts from various engineering disciplines, making it a valuable resource for engineering students interested in robotics.
  • Q: What is the significance of bio-inspired techniques in mobile robotics as discussed in this book? A: Bio-inspired techniques, such as reinforcement learning and swarm intelligence, are vital for enhancing robot design and functionality, allowing robots to adapt to their environments effectively.

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