Autonomous navigation represents a cornerstone capability across a broad spectrum of robotic applications, such as self-driving vehicles and ground-based mobile robots. The precise estimation of the system’s motion over time is a process commonly known as odometry and it is central to achieving such autonomy. Over the years, numerous techniques have been developed to address this task, each offering distinct advantages and limitations depending on the sensors exploited and methodologies employed. Visual Odometry (VO) estimates the pose of a robot using images acquired from single or multiple cameras attached to the robot and has become one of the most robust techniques for vehicle localization.