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How Autonomous Vehicles and Robots Navigate in the Real World: with MATLAB examples
Louise Reader
Read on Louise Reader App.
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:
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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