Autonomous machine navigation and training using vision system

Autonomous machine navigation techniques may generate a three-dimensional point cloud that represents at least a work region based on feature data and matching data. Pose data associated with points of the three-dimensional point cloud may be generated that represents poses of an autonomous machine....

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Main Authors Beyer, Brian Daniel, LaRose, David Arthur, Frick, Alexander Steven, Kraft, Jason Thomas, Parker, Zachary Irvin, Landers, Stephen Paul Elizondo, Ingvalson, Ryan Douglas, Ramsay, Michael Jason, Osterwood, Christopher Charles, Williams, Adam Richard
Format Patent
LanguageEnglish
Published 17.05.2022
Subjects
AGRICULTURE
ANIMAL HUSBANDRY
CONTROLLING
FISHING
FORESTRY
GYROSCOPIC INSTRUMENTS
HARVESTING
HUMAN NECESSITIES
HUNTING
MEASURING
MEASURING DISTANCES, LEVELS OR BEARINGS
MOWING
NAVIGATION
PHOTOGRAMMETRY OR VIDEOGRAMMETRY
PHYSICS
REGULATING
SURVEYING
SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
TESTING
TRAPPING
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Summary:Autonomous machine navigation techniques may generate a three-dimensional point cloud that represents at least a work region based on feature data and matching data. Pose data associated with points of the three-dimensional point cloud may be generated that represents poses of an autonomous machine. A boundary may be determined using the pose data for subsequent navigation of the autonomous machine in the work region. Non-vision-based sensor data may be used to determine a pose. The pose may be updated based on the vision-based pose data. The autonomous machine may be navigated within the boundary of the work region based on the updated pose. The three-dimensional point cloud may be generated based on data captured during a touring phase. Boundaries may be generated based on data captured during a mapping phase.
Bibliography:Application Number: US201916534515