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Patent drawing for Machine learning based target localization for autonomous unmanned vehicles
US 11,537,906 B2
Machine learning US 11,537,906 B2 Not in force

Machine learning based target localization for autonomous unmanned vehicles

This invention helps an autonomous vehicle, like a drone, find a specific object. It starts by taking a wide-view picture and uses a first computer model to check if the object is visible. If not, a second computer model identifies a smaller, more probable area where the object might be, and the vehicle then moves to this new area, specifically adjusting its distance for better visibility, with the second model also helping select the best camera settings for the conditions.

Why it matters: Since 2019, advancements in machine learning, particularly for computer vision and autonomous navigation, have made training and deploying such models significantly more efficient and robust. This reduces the development burden for the core ML components described.

Status
Not in forceListed as no longer active. The specific reason is not in the record we hold.
How hard to build
SpecializedMachine learning, autonomous navigation, sensor integration

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