Overview

SLAM for Beginners is the perfect starting point for anyone curious about how robots understand and navigate the world. Written in clear, accessible language, this book demystifies Simultaneous Localization and Mapping - the core technology behind drones, autonomous vehicles, AR/VR devices, warehouse robots, and modern AI systems. You'll explore how robots build maps, track their position, fuse sensor data, detect loop closures, handle uncertainty, and operate in dynamic environments. Each chapter breaks down complex ideas into intuitive explanations, real-world examples, and practical insights. No advanced math or prior robotics experience required. Whether you're a student, hobbyist, engineer transitioning into robotics, or simply fascinated by how intelligent machines perceive space, this book gives you the foundation you need to understand and work with SLAM systems. Inside you'll learn: How cameras, lidars, IMUs, and depth sensors work together The difference between visual SLAM, lidar SLAM, and multi-modal SLAM Mapping representations: point clouds, occupancy grids, meshes, TSDFs, and semantic maps Loop closure, drift correction, and global optimization Robustness, failure modes, and how real robots recover The future of SLAM: neural SLAM, semantic mapping, world models, and spatial AI If you've ever wondered how robots ""see"" the world - this is your guide.

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