Invention Grant
- Patent Title: Neural networks to generate robotic task demonstrations
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Application No.: US17695756Application Date: 2022-03-15
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Publication No.: US12202147B2Publication Date: 2025-01-21
- Inventor: Ankur Handa , Iretiayo Akinola , Dieter Fox , Yashraj Shyam Narang
- Applicant: NVIDIA CORPORATION
- Applicant Address: US CA Santa Clara
- Assignee: NVIDIA CORPORATION
- Current Assignee: NVIDIA CORPORATION
- Current Assignee Address: US CA Santa Clara
- Agency: Artegis Law Group, LLP
- Main IPC: B25J9/16
- IPC: B25J9/16

Abstract:
A technique for training a neural network, including generating a plurality of input vectors based on a first plurality of task demonstrations associated with a first robot performing a first task in a simulated environment, wherein each input vector included in the plurality of input vectors specifies a sequence of poses of an end-effector of the first robot, and training the neural network to generate a plurality of output vectors based on the plurality of input vectors. Another technique for generating a task demonstration, including generating a simulated environment that includes a robot and at least one object, causing the robot to at least partially perform a task associated with the at least one object within the simulated environment based on a first output vector generated by a trained neural network, and recording demonstration data of the robot at least partially performing the task within the simulated environment.
Public/Granted literature
- US20230191605A1 NEURAL NETWORKS TO GENERATE ROBOTIC TASK DEMONSTRATIONS Public/Granted day:2023-06-22
Information query
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