Autonomous machine navigation and training using vision system

A method of navigation training for an autonomous machine comprising:

• directing the autonomous machine during a touring phase of a training mode along at least one of a perimeter or an interior of a work region to record a first set of touring images associated with the perimeter or a second set of touring images associated with the interior;
• generating during an offline mode a three-dimensional point cloud (3DPC) based on at least one of the first set and the second set of touring images;
• and
• directing the autonomous machine during a mapping phase of the training mode along one or more paths to record sensor fusion data to define one or more boundaries for the work region in a navigational map.

An autonomous machine comprising:

• a housing coupled to a maintenance implement;
• a set of wheels supporting the housing over a ground surface;
• a propulsion controller operably coupled to the set of wheels;
• a vision system comprising at least one camera adapted to capture image data;
• and
• a navigation system operably coupled to the vision system and the propulsion controller, the navigation system adapted to:
• determine a current pose of an autonomous machine based on non-vision-based pose data captured by one or more non-vision-based sensors of the autonomous machine, wherein the pose represents one or both of a position and an orientation of the autonomous machine in a work region defined by one or more boundaries;
• determining vision-based pose data based on image data captured by the at least one camera;
• updating the current pose based on the vision-based pose data to correct or localize the current pose and to provide an updated pose of the autonomous machine in the work region for navigating the autonomous machine in the work region;
• and
• direct the autonomous machine within the work region.