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Other titles in the Applied Computing series:
Mobile Robotics: A Practical Introduction: History, Design, Analysis and Examples (Applied Computing)by Ulrich Nehmzow
Synopses & Reviews
Mobile Robotics: A Practical Introduction is an excellent introduction to the foundations and methods used for designing completely autonomous mobile robots. In this book you are introduced to the fundamental concepts of this complex field via twelve detailed case studies which show how to build and program real working robots. This book provides a very practical introduction to mobile robotics for a general scientific audience, and is essential reading for final year undergraduate students and postgraduate students studying Robotics, Artificial Intelligence, Cognitive Science and Robot Engineering. Its update and overview of core concepts in mobile robotics will assist and encourage practitioners of the field, and set challenges to explore new avenues of research in this exciting field.
Table of Contents
Introduction.- Foundations.- Definitions.- Applications of Mobile Robots.- History of Mobile Robotics: Early Implementations.- History of Mobile Robotics: Control Paradigms.- Robot Hardware.- Robot Sensors.- Robot Actuators.- Example: The Mobile Robot Forty Two.- The Need for Sensor Signal Interpretation.- Further Reading.- Robot Learning: Making Sense of Raw Sensor Data.- Introduction.- Learning Methods in Detail.- Further Reading on Learning Methods.- Case Studies of Learning Robots.- Exercise 2: A Target-Following, Obstacle-Avoiding Robot Navigation.- Principles of Navigation.- Fundamental Navigation Strategies in Animals and Humans Robot Navigation.- Case Studies of Navigating Robots.- Simulation: Modelling Robot-Environment Interaction.- Motivation.- Fundamentals of Computer Simulation.- Alternatives to Numerical Models.- Case Study on Simulation of Robot-Environment Interaction.- Analysis of Robot Behaviour.- Motivation.- Statistical Analysis of Robot Behaviour.- Case Studies of Performance Evaluation and Analysis.- Summary.- Outlook.- Achievements.- Reasons for Success.- Challenges.- The Beginning.- Further Reading.- Answers to Exercises.- Sonar Sensors.- Robot Learning.- Error Calculations and Contingency Table Analysis.- Analysis of Categorical Data.- List of Exercises and Case Studies.- References.- Index.
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