Invention Grant
- Patent Title: Systems and method for robotic learning of industrial tasks based on human demonstration
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Application No.: US15860377Application Date: 2018-01-02
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Publication No.: US10913154B2Publication Date: 2021-02-09
- Inventor: Huan Tan , John Robert Hoare , Justin Michael Foehner , Steven Robert Gray , Shiraj Sen , Romano Patrick
- Applicant: General Electric Company
- Applicant Address: US NY Schenectady
- Assignee: General Electric Company
- Current Assignee: General Electric Company
- Current Assignee Address: US NY Schenectady
- Agency: Fletcher Yoder, P.C.
- Main IPC: B25J9/00
- IPC: B25J9/00 ; B25J9/16 ; G05D1/00

Abstract:
A system for performing industrial tasks includes a robot and a computing device. The robot includes one or more sensors that collect data corresponding to the robot and an environment surrounding the robot. The computing device includes a user interface, a processor, and a memory. The memory includes instructions that, when executed by the processor, cause the processor to receive the collected data from the robot, generate a virtual recreation of the robot and the environment surrounding the robot, receive inputs from a human operator controlling the robot to demonstrate an industrial task. The system is configured to learn how to perform the industrial task based on the human operator's demonstration of the task, and perform, via the robot, the industrial task autonomously or semi-autonomously.
Public/Granted literature
- US20190202053A1 SYSTEMS AND METHOD FOR ROBOTIC LEARNING OF INDUSTRIAL TASKS BASED ON HUMAN DEMONSTRATION Public/Granted day:2019-07-04
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