SLAM (Simultaneous Localization and Mapping) is the process of estimating a robot’s position while simultaneously building a map of its environment. It combines motion prediction, odometry, sensor observations, localization, particle filters, scan matching, mapping, and loop closure to maintain a consistent estimate of both the robot and its surroundings.
📚 Primary Resource
Use the SLAM Detailed Study Guide as the primary reference for learning these concepts. It progresses from robot motion and localization fundamentals to particle filters, AMCL, SLAM techniques, loop closure, and navigation, with practical ROS-oriented implementation and debugging.
👁️ Visualization
Use the other provided PDFs, slides, diagrams, and visualization material alongside the book to develop intuition for concepts such as robot motion, LiDAR scans, particle filters, coordinate frames, map building, SLAM, and localization.
Book
SLAM Detailed Study Guide — Book
Visualization PDF
Robotics_Society_SLAM_Session.pdf
Robotics Society SLAM Session — Visualization PDF
Reference