SLAM stands for Simultaneous Localization and Mapping, which is crucial for robots to navigate effectively.
Graph SLAM is a method used to solve the SLAM problem by creating a puzzle of constraints that helps the robot determine its position relative to its surroundings.
In Graph SLAM, the robot utilizes movement and sensor data to build a matrix (Ω and ξ) that represents the relationships and clues collected during its exploration.
By solving the equation Ω⋅μ = ξ, the robot can estimate its trajectory and the map of its environment by incorporating motion constraints and sensor observations.