Description
Localization and Mapping of Autonomous Mobile Robots
Navigate the complex frontiers of autonomous navigation and spatial intelligence. Localization and Mapping of Autonomous Mobile Robots provides a rigorous, technical deep dive into the algorithms that allow machines to perceive and understand their physical environment. This essential volume bridges the gap between raw sensor data and the high-precision SLAM (Simultaneous Localization and Mapping) frameworks that drive the next generation of industrial and consumer robotics.
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What You Will Learn:
Foundational SLAM Principles: Master the mathematical frameworks of Simultaneous Localization and Mapping, including Filter-based and Optimization-based methodologies.
Multi-Sensor Fusion: Learn how to integrate data from LiDAR, cameras, IMUs, and ultrasonic sensors to create robust, redundant navigation systems.
Environment Modeling: Discover advanced techniques for 2D and 3D map reconstruction in dynamic, unpredictable, and GPS-denied environments.
Real-World Deployment: Review practical strategies for implementing localization algorithms in autonomous mobile robots (AMRs) for logistics, search and rescue, and smart manufacturing.
Who This Book is For: This advanced technical resource is essential for robotics engineers, AI researchers, computer vision specialists, and graduate students. It is an invaluable reference for professional teams building autonomous systems that require centimeter-level precision and high operational reliability.
Product Details:
Format: Digital PDF Download
Authors: Junzhi Yu; Zhiqiang Cao; Peiyu Guan; Chengpeng Wang
Publisher: CRC Press LLC
Edition: 1st Edition
Publication Date: August 20, 2025
ISBN-13: 9781032917047
ISBN-10: 1032917040
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