Simultaneous Localization and Mapping (SLAM) is a foundational technology that enables robots and autonomous systems to map and navigate complex environments. This handbook provides a comprehensive overview of the field, bringing together more than 60 leading researchers from around the world. The book is organized into three parts. Part I introduces the mathematical and algorithmic foundations of SLAM, including estimation, optimization, and modern map representations. Part II focuses on the state of practice, covering sensor modalities and real-world systems, from inertial and visual odometry to LiDAR, radar, and multimodal SLAM. Part III explores emerging directions, highlighting the field's transition toward Spatial AI, where machines build richer spatial and semantic understanding of their environments. Designed as a unified reference for advanced students, researchers, and engineers, this handbook presents both the principles and the future of robotic spatial perception.