The book "Vision and Navigation: The Carnegie Mellon Navlab" is a compilation of papers from the Navlab Project, edited by Charles E. Thorpe. The project, initiated in 1984, focuses on developing technologies for mobile robots to navigate autonomously in natural outdoor environments. The book covers a wide range of topics, including color vision for road following, explicit models for robot road following, knowledge-based interpretation of outdoor natural color road scenes, neural network-based autonomous navigation, car recognition, building and navigating maps of road scenes using active range and reflectance data, 3D vision techniques for autonomous vehicles, and various navigation systems and control schemes. Key contributions include the development of algorithms for sensors such as sonars, color cameras, 3D range finders, and inertial navigation systems. The project has also explored nonconventional computing engines like systolic computers and neural net computing. The book highlights the progress made in planning and integration architecture, as well as the demonstration of integrated working systems for tasks like road following, open terrain navigation, and fast navigation by position control. The foreword emphasizes the importance of vision and navigation in mobile robotics, noting that these technologies are crucial for enabling robots to see, plan, and execute tasks in their environment. The Navlab Project has played a catalytic role in advancing and integrating many facets of intelligent robotics, making this book a significant milestone in the field of autonomous mobile robot research.The book "Vision and Navigation: The Carnegie Mellon Navlab" is a compilation of papers from the Navlab Project, edited by Charles E. Thorpe. The project, initiated in 1984, focuses on developing technologies for mobile robots to navigate autonomously in natural outdoor environments. The book covers a wide range of topics, including color vision for road following, explicit models for robot road following, knowledge-based interpretation of outdoor natural color road scenes, neural network-based autonomous navigation, car recognition, building and navigating maps of road scenes using active range and reflectance data, 3D vision techniques for autonomous vehicles, and various navigation systems and control schemes. Key contributions include the development of algorithms for sensors such as sonars, color cameras, 3D range finders, and inertial navigation systems. The project has also explored nonconventional computing engines like systolic computers and neural net computing. The book highlights the progress made in planning and integration architecture, as well as the demonstration of integrated working systems for tasks like road following, open terrain navigation, and fast navigation by position control. The foreword emphasizes the importance of vision and navigation in mobile robotics, noting that these technologies are crucial for enabling robots to see, plan, and execute tasks in their environment. The Navlab Project has played a catalytic role in advancing and integrating many facets of intelligent robotics, making this book a significant milestone in the field of autonomous mobile robot research.