Machine learning systems and techniques to optimize teleoperation and/or …

This patent describes an autonomous vehicle equipped with standard components like processors, sensors, and communication systems. While the abstract discusses using machine learning to predict optimal actions for the vehicle or a remote operator based on performance issues or new sensor data, the actual claims only cover the vehicle's basic hardware and its communication links, not the specific machine learning application itself.

Why it matters: In 2016, advanced machine learning for real-time autonomous vehicle decision-making and teleoperation was still largely theoretical. By 2026, significant advancements in deep learning, reinforcement learning, and real-time sensor fusion have made the sophisticated predictive and optimization capabilities described in the abstract far more feasible and robust.

Status: Not in forceListed as no longer active. The specific reason is not in the record we hold.
How hard to build: SpecializedAutonomous vehicle hardware, complex software system

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