| CPC G06N 3/08 (2013.01) [G05B 19/4155 (2013.01); G05B 2219/39271 (2013.01); G05B 2219/40269 (2013.01)] | 24 Claims |
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1. A method performed by at least one computer processor executing computer program instructions stored on at least one non-transitory computer-readable medium, the method comprising:
(A) training a neural network, the training comprising:
(A)(1) receiving, as training data:
a plurality of training images I, each representing a three-dimensional scene at a corresponding time when a robot's end effector is at a corresponding stopping point in the three-dimensional scene; and
a plurality of poses of an end effector of a robot, each representing a corresponding pose of the robot's end effector at a corresponding one of the stopping points; and
(A)(2) training the neural network using the plurality of training images I, and the plurality of poses as the training data, to produce a trained neural network;
(B) applying the trained neural network to predict, for each of a plurality of pixels P in an input image, (1) a depth that the robot's end effector would reach in a three-dimensional environment if the robot's end effector moved into the three-dimensional environment to target a projection of the pixel P onto the three-dimensional environment, and (2) an uncertainty of the depth; and
(C) determining when to slow down the robot's end effector based on the depth and the uncertainty of the depth.
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