Samsung Electronics Co., Ltd.

Ben Eisner

Daniel Dongyuel Lee

Eric Anthony Mitchell

Sebastian Seung

Daewon Lee

Bhoram Lee

Jinwook Huh

Volkan Isler

Riley Simmons-Edler

Tarik Tosun

An apparatus for performing continuous actions includes a memory storing instructions, and a processor configured to execute the instructions to obtain a first action of an agent, based on a current state of the agent, using a cross-entropy guided policy (CGP) neural network, and control to perform the obtained first action. The CGP neural network is trained using a cross-entropy method (CEM) policy neural network for obtaining a second action of the agent based on an input state of the agent, and the CEM policy neural network is trained using a CEM and trained separately from the training of the CGP neural network.

Apparatus for Q-learning for continuous actions with cross-entropy guided policies and method thereof

An apparatus for estimating a trajectory of a tool may include: a memory storing instructions; and a processor configured to execute the instructions to: receive a task to be performed by the tool on a target object; receive a grayscale image and a depth image of the target object; and estimate a tool trajectory for performing the task, from the grayscale image and the depth image, via a pixels-to-plans neural network that is trained based on a labeled tool trajectory that is generated from a point cloud model of the target object.

Method and apparatus for estimating tool trajectories

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Ben Eisner