SLAM Introduction
SLAM stands for “Simultaneous Localization and Mapping”, and is a general class of problems especially prevalent in robotics. It involves recording measurements from various sensors (Visual Inertial Odometry (VIO), April Tag detection, LIDAR, etc.) to create a map of some space, and your location within it (hence, localization and mapping). This has many applications, especially in autonomous navigation for robots. Invisible Map encounters this problem when a user is creating a new map. The goal of the project is to use the data from the phone's odometry and the April tag detections to generate a map of a space using a SLAM algorithm called G2O.