- Patent Title: System and methods for training robot policies in the real world
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Application No.: US17094521Application Date: 2020-11-10
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Publication No.: US11992945B2Publication Date: 2024-05-28
- Inventor: Jie Tan , Sehoon Ha , Peng Xu , Sergey Levine , Zhenyu Tan
- Applicant: Google LLC
- Applicant Address: US CA Mountain View
- Assignee: GOOGLE LLC
- Current Assignee: GOOGLE LLC
- Current Assignee Address: US CA Mountain View
- Agency: Gray Ice Higdon
- Main IPC: B25J9/16
- IPC: B25J9/16 ; B25J13/08 ; G05D1/00 ; G06N3/08

Abstract:
Techniques are disclosed that enable training a plurality of policy networks, each policy network corresponding to a disparate robotic training task, using a mobile robot in a real world workspace. Various implementations include selecting a training task based on comparing a pose of the mobile robot to at least one parameter of a real world training workspace. For example, the training task can be selected based on the position of a landmark, within the workspace, relative to the pose. For instance, the training task can be selected such that the selected training task moves the mobile robot towards the landmark.
Public/Granted literature
- US20220143819A1 SYSTEM AND METHODS FOR TRAINING ROBOT POLICIES IN THE REAL WORLD Public/Granted day:2022-05-12
Information query
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