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Patent drawing for Controlling a robot during interaction with a human
US 20,240,157,557 A1
Robotics US 20,240,157,557 A1 Not in force

Controlling a robot during interaction with a human

This system teaches a robot to perform tasks by controlling its movements around objects held in place by stationary fixtures. It uses a computer brain, called a neural network, which learns how to move and grasp objects safely. The learning process specifically involves planning out collision-free movements and pre-defined ways to grab things, ensuring the robot avoids hitting the stationary holders.

Why it matters: The efficiency and accessibility of training complex neural networks for robot control and collision avoidance have significantly improved since 2023, making development more practical.

Status
Not in forceListed as no longer active. The specific reason is not in the record we hold.
How hard to build
SpecializedHeavy software system, neural network training

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