Autonomous Navigation, Part 3: Understanding SLAM Using Pose Graph Optimization

Watch the other videos in this series: What Is Autonomous Navigation?: Understanding the Particle Filter: This video provides some intuition around Pose Graph Optimization—a popular framework for solving the simultaneous localization and mapping (SLAM) problem in autonomous navigation. We’ll cover why uncertainty in a vehicle’s sensors and state estimation makes building a map of the environment difficult and how pose graph optimization can deal with it. We’ll also briefly cover occupancy grid maps as one way to represent the environment model. Additional Resources: - Implement Simultaneous Localization and Mapping (SLAM) with MATLAB: - Download ebook: Sensor Fusion and Tracking for Autonomous Systems: An Overview: - Download white paper: Sensor Fusion and Tracking for Autonomous Systems - - SLAM Course - 15 - Least Squares SLAM - Cyri