SLAM Handbook: From Localization and Mapping to Spatial Intelligence($165.00Value)

Description

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. Comprehensive coverage by leading experts on foundations, current practice, and emerging Spatial AI trends, unifying theory and systems. Luca Carlone is an Associate Professor in the Department of Aeronautics and Astronautics and the Director of the SPARK Lab at the Massachusetts Institute of Technology. His lab works at the cutting edge of robotics and autonomous systems research, combining rigorous theory and practical implementations. His goal is to enable human-level perception and world understanding on mobile robotics platforms operating in the real world. He is an IEEE senior member, an AIAA associate fellow, a Sloan fellow, and a Kavli fellow. Ayoung Kim is Professor in the Department of Mechanical Engineering at Seoul National University. Before joining SNU, she was at the Korea Advanced Institute of Science and Technology (KAIST) from 2014 to 2021. She received an M.S. degree in electrical engineering and a Ph.D. in mechanical engineering from the University of Michigan (UM), Ann Arbor, in 2011 and 2012. Timothy D. Barfoot is Professor at the University of Toronto Institute for Aerospace Studies where he leads the Autonomous Space Robotics Lab focused on navigation for mobile robotics. He is interested in using rich onboard sensing and compute to enable autonomous operations for a variety of applications including space, mining, and transportation. He is an IEEE Fellow, serves as EiC of the IEEE Transactions on Field Robotics, and is author of the book State Estimation for Robotics (Cambridge 2017, 2024). Daniel Cremers is Professor at TU Munich and Director of the Munich Center for Machine Learning. He works on the interface of computer vision, machine learning and robotics. A recipient of multiple ERC grants and major awards such as the ECCV 2024 Koenderink Test of Time Award, he leads one of the most influential computer vision labs worldwide, serves as President of the European Computer Vision Association, and engages in multiple startups, most recently the spatial intelligence startup SE3 Labs. Frank Dellaert is Professor in the School of Interactive Computing at the Georgia Institute of Technology. In addition, he has led research at Skydio, Facebook Reality Labs, Google AI, and Verdant Robotics. His research is in the overlap between robotics and computer vision, with a focus on graphical model techniques to solve large-scale problems in mapping, 3D reconstruction, and model-predictive control.