Sensor Fusion Approaches for Positioning, Navigation, and Mapping
eBook - PDF

Sensor Fusion Approaches for Positioning, Navigation, and Mapping

How Autonomous Vehicles and Robots Navigate in the Real World: With MATLAB Examples

  1. 540 pages
  2. English
  3. PDF
  4. Available on iOS & Android
eBook - PDF

Sensor Fusion Approaches for Positioning, Navigation, and Mapping

How Autonomous Vehicles and Robots Navigate in the Real World: With MATLAB Examples

About this book

Unique exploration of the integration of multi-sensor approaches in navigation and positioning technologies.

Sensor Fusion Approaches for Positioning, Navigation, and Mapping discusses the fundamental concepts and practical implementation of sensor fusion in positioning and mapping technology, explaining the integration of inertial sensors, radio positioning systems, visual sensors, depth sensors, radar measurements, and LiDAR measurements. The book includes case studies on ground wheeled vehicles, drones, and wearable devices to demonstrate the presented concepts.

To aid in reader comprehension and provide readers with hands-on training in sensor fusion, pedagogical features are included throughout the text: block diagrams, photographs, plot graphs, examples, solved problems, case studies, sample codes with instruction manuals, and guided tutorials.

Rather than simply addressing a specific sensor or problem domain without much focus on the big picture of sensor fusion and integration, the book utilizes a holistic and comprehensive approach to enable readers to fully grasp interrelated concepts.

Written by a highly qualified author, Sensor Fusion Approaches for Positioning, Navigation, and Mapping discusses sample topics such as:

  • Mathematical background, covering linear algebra, Euclidean space, coordinate frames, rotation and transformation, quaternion, and lie groups algebra.
  • Kinematics of rigid platforms in 3D space, covering motion modeling in rotating and non-rotating frames and under gravity field, and different representations of position, velocity, and orientation.
  • Signals and systems, covering measurements, and noise, probability concepts, random processes, signal processing, linear dynamic systems, and stochastic systems.
  • Theory, measurements, and signal processing of state-of-the-art positioning and mapping sensors/systems covering inertial sensors, radio positioning systems, ranging and detection sensors, and imaging sensors.
  • State Estimation and Sensor Fusion methods covering filtering-based methods and learning-based approaches.

A comprehensive introductory text on the subject, Sensor Fusion Approaches for Positioning, Navigation, and Mapping enables students to grasp the fundamentals of the subject and support their learning via ample pedagogical features. Practicing robotics and navigation systems engineers can implement included sensor fusion algorithms on practical platforms.

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Yes, you can access Sensor Fusion Approaches for Positioning, Navigation, and Mapping by Mohamed M. Atia in PDF and/or ePUB format, as well as other popular books in Technology & Engineering & Automation in Engineering. We have over one million books available in our catalogue for you to explore.

Table of contents

  1. Cover
  2. Series Page
  3. Title Page
  4. Copyright Page
  5. Dedication Page
  6. Contents
  7. About the Author
  8. Preface
  9. Acknowledgment
  10. Chapter 1 Coordinate Systems and Motion Modeling
  11. Chapter 2 Signals and Systems
  12. Chapter 3 Sensor Fusion Methods and Algorithms
  13. Chapter 4 Inertial Sensors and Inertial Navigation Systems
  14. Chapter 5 Radio Positioning Systems
  15. Chapter 6 Active Ranging Sensors
  16. Chapter 7 Imaging Sensors
  17. Chapter 8 Mapping Algorithms
  18. Chapter 9 Case Study #1: Wheeled Platforms
  19. Chapter 10 Case Study #2: Aerial Vehicles
  20. Chapter 11 Case Study #3: AHRS and PDR
  21. Chapter 12 Learning-Based Fusion Methods
  22. Index
  23. EULA