Patents by Inventor Vivian Yaw-Wen Chu

Vivian Yaw-Wen Chu has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).

  • Patent number: 11904470
    Abstract: Systems, apparatus, and methods are described for robotic learning and execution of skills. A robotic apparatus can include a memory, a processor, sensors, and one or more movable components (e.g., a manipulating element and/or a transport element). The processor can be operatively coupled to the memory, the movable elements, and the sensors, and configured to obtain information of an environment, including one or more objects located within the environment. In some embodiments, the processor can be configured to learn skills through demonstration, exploration, user inputs, etc. In some embodiments, the processor can be configured to execute skills and/or arbitrate between different behaviors and/or actions. In some embodiments, the processor can be configured to execute skills and/or behaviors using cached trajectories or plans. In some embodiments, the processor can be configured to execute skills requiring navigation and manipulation behaviors.
    Type: Grant
    Filed: August 8, 2023
    Date of Patent: February 20, 2024
    Assignee: Diligent Robotics, Inc.
    Inventors: Andrea Lockerd Thomaz, Vivian Yaw-Wen Chu, Peter Worsnop, Reymundo Gutierrez, Lauren Hutson, Shuai Li, Anjana Nellithimaru, Frank Mathis
  • Patent number: 11833684
    Abstract: Systems, apparatus, and methods are described for robotic learning and execution of skills. A robotic apparatus can include a memory, a processor, sensors, and one or more movable components (e.g., a manipulating element and/or a transport element). The processor is operatively coupled to the memory, the movable elements, and the sensors, and configured to obtain information of an environment, including one or more objects located within the environment. In some embodiments, the processor is configured to learn skills through demonstration, exploration, user inputs, etc. In some embodiments, the processor is configured to execute skills and/or arbitrate between different behaviors and/or actions. In some embodiments, the processor is configured to learn an environmental constraint. In some embodiments, the processor is configured to learn using a general model of a skill.
    Type: Grant
    Filed: March 1, 2021
    Date of Patent: December 5, 2023
    Assignee: Diligent Robotics, Inc.
    Inventors: Vivian Yaw-Wen Chu, Shuai Li, Forrest Green, Peter Worsnop, Andrea Lockerd Thomaz
  • Publication number: 20230381959
    Abstract: Systems, apparatus, and methods are described for robotic learning and execution of skills. A robotic apparatus can include a memory, a processor, sensors, and one or more movable components (e.g., a manipulating element and/or a transport element). The processor can be operatively coupled to the memory, the movable elements, and the sensors, and configured to obtain information of an environment, including one or more objects located within the environment. In some embodiments, the processor can be configured to learn skills through demonstration, exploration, user inputs, etc. In some embodiments, the processor can be configured to execute skills and/or arbitrate between different behaviors and/or actions. In some embodiments, the processor can be configured to execute skills and/or behaviors using cached trajectories or plans. In some embodiments, the processor can be configured to execute skills requiring navigation and manipulation behaviors.
    Type: Application
    Filed: August 8, 2023
    Publication date: November 30, 2023
    Applicant: Diligent Robotics, Inc.
    Inventors: Andrea Lockerd THOMAZ, Vivian Yaw-Wen CHU, Peter WORSNOP, Reymundo GUTIERREZ, Lauren HUTSON, Shuai LI, Anjana NELLITHIMARU, Frank MATHIS
  • Publication number: 20220371193
    Abstract: Systems, apparatus, and methods are described for robotic learning and execution of skills. A robotic apparatus can include a memory, a processor, sensors, and one or more movable components (e.g., a manipulating element and/or a transport element). The processor can be operatively coupled to the memory, the movable elements, and the sensors, and configured to obtain information of an environment, including one or more objects located within the environment. In some embodiments, the processor can be configured to learn skills through demonstration, exploration, user inputs, etc. In some embodiments, the processor can be configured to execute skills and/or arbitrate between different behaviors and/or actions. In some embodiments, the processor can be configured to learn an environmental constraint. In some embodiments, the processor can be configured to learn using a general model of a skill.
    Type: Application
    Filed: March 9, 2022
    Publication date: November 24, 2022
    Inventors: Vivian Yaw-Wen CHU, Shuai LI, Forrest GREEN, Peter WORSNOP, Andrea Lockerd THOMAZ
  • Patent number: 11298825
    Abstract: Systems, apparatus, and methods are described for robotic learning and execution of skills. A robotic apparatus can include a memory, a processor, sensors, and one or more movable components (e.g., a manipulating element and/or a transport element). The processor can be operatively coupled to the memory, the movable elements, and the sensors, and configured to obtain information of an environment, including one or more objects located within the environment. In some embodiments, the processor can be configured to learn skills through demonstration, exploration, user inputs, etc. In some embodiments, the processor can be configured to execute skills and/or arbitrate between different behaviors and/or actions. In some embodiments, the processor can be configured to learn an environmental constraint. In some embodiments, the processor can be configured to learn using a general model of a skill.
    Type: Grant
    Filed: October 18, 2021
    Date of Patent: April 12, 2022
    Assignee: Diligent Robotics, Inc.
    Inventors: Vivian Yaw-Wen Chu, Shuai Li, Forrest Green, Peter Worsnop, Andrea Lockerd Thomaz
  • Publication number: 20220032458
    Abstract: Systems, apparatus, and methods are described for robotic learning and execution of skills. A robotic apparatus can include a memory, a processor, sensors, and one or more movable components (e.g., a manipulating element and/or a transport element). The processor can be operatively coupled to the memory, the movable elements, and the sensors, and configured to obtain information of an environment, including one or more objects located within the environment. In some embodiments, the processor can be configured to learn skills through demonstration, exploration, user inputs, etc. In some embodiments, the processor can be configured to execute skills and/or arbitrate between different behaviors and/or actions. In some embodiments, the processor can be configured to learn an environmental constraint. In some embodiments, the processor can be configured to learn using a general model of a skill.
    Type: Application
    Filed: October 18, 2021
    Publication date: February 3, 2022
    Applicant: Diligent Robotics, Inc.
    Inventors: Vivian Yaw-Wen CHU, Shuai LI, Forrest GREEN, Peter WORSNOP, Andrea Lockerd THOMAZ
  • Publication number: 20210379758
    Abstract: Systems, apparatus, and methods are described for robotic learning and execution of skills. A robotic apparatus can include a memory, a processor, sensors, and one or more movable components (e.g., a manipulating element and/or a transport element). The processor can be operatively coupled to the memory, the movable elements, and the sensors, and configured to obtain information of an environment, including one or more objects located within the environment. In some embodiments, the processor can be configured to learn skills through demonstration, exploration, user inputs, etc. In some embodiments, the processor can be configured to execute skills and/or arbitrate between different behaviors and/or actions. In some embodiments, the processor can be configured to learn an environmental constraint. In some embodiments, the processor can be configured to learn using a general model of a skill.
    Type: Application
    Filed: March 1, 2021
    Publication date: December 9, 2021
    Inventors: Vivian Yaw-Wen CHU, Shuai LI, Forrest GREEN, Peter WORSNOP, Andrea Lockerd THOMAZ
  • Patent number: 11148288
    Abstract: Systems, apparatus, and methods are described for robotic learning and execution of skills. A robotic apparatus can include a memory, a processor, sensors, and one or more movable components (e.g., a manipulating element and/or a transport element). The processor can be operatively coupled to the memory, the movable elements, and the sensors, and configured to obtain information of an environment, including one or more objects located within the environment. In some embodiments, the processor can be configured to learn skills through demonstration, exploration, user inputs, etc. In some embodiments, the processor can be configured to execute skills and/or arbitrate between different behaviors and/or actions. In some embodiments, the processor can be configured to learn an environmental constraint. In some embodiments, the processor can be configured to learn using a general model of a skill.
    Type: Grant
    Filed: June 28, 2019
    Date of Patent: October 19, 2021
    Assignee: Diligent Robotics, Inc.
    Inventors: Vivian Yaw-Wen Chu, Shuai Li, Forrest Green, Peter Worsnop, Andrea Lockerd Thomaz
  • Publication number: 20200070343
    Abstract: Systems, apparatus, and methods are described for robotic learning and execution of skills. A robotic apparatus can include a memory, a processor, sensors, and one or more movable components (e.g., a manipulating element and/or a transport element). The processor can be operatively coupled to the memory, the movable elements, and the sensors, and configured to obtain information of an environment, including one or more objects located within the environment. In some embodiments, the processor can be configured to learn skills through demonstration, exploration, user inputs, etc. In some embodiments, the processor can be configured to execute skills and/or arbitrate between different behaviors and/or actions. In some embodiments, the processor can be configured to learn an environmental constraint. In some embodiments, the processor can be configured to learn using a general model of a skill.
    Type: Application
    Filed: June 28, 2019
    Publication date: March 5, 2020
    Inventors: Andrea Lockerd THOMAZ, Vivian Yaw-Wen Chu
  • Patent number: 8630989
    Abstract: Described herein are methods, systems, apparatuses and products for automatically discovering patterns in a text corpus. An aspect provides extracting at least one context string related to at least one annotator from the at least one text corpus; analyzing the at least one context string for at least one sequence, the at least one sequence comprised of at least one subsequence; determining at least one sequence signature for each at least one sequence by applying applicable rules to the at least one sequence; and grouping the at least one sequence signature into at least one group.
    Type: Grant
    Filed: May 27, 2011
    Date of Patent: January 14, 2014
    Assignee: International Business Machines Corporation
    Inventors: Sebastian Johannes Blohm, Vivian Yaw-Wen Chu, Ching-Tien Ho, Yunyao Li, Huaiyu Zhu
  • Publication number: 20120303661
    Abstract: Described herein are methods, systems, apparatuses and products for automatically discovering patterns in a text corpus. An aspect provides extracting at least one context string related to at least one annotator from the at least one text corpus; analyzing the at least one context string for at least one sequence, the at least one sequence comprised of at least one subsequence; determining at least one sequence signature for each at least one sequence by applying applicable rules to the at least one sequence; and grouping the at least one sequence signature into at least one group.
    Type: Application
    Filed: May 27, 2011
    Publication date: November 29, 2012
    Applicant: INTERNATIONAL BUSINESS MACHINES CORPORATION
    Inventors: Sebastian Johannes Blohm, Vivian Yaw-Wen Chu, Ching-Tien Ho, Yunyao Li, Huaiyu Zhu