Systems and methods for learning and managing robot user interfaces

US12084080B2 · kind B2 · utility

Assignees

• TOYOTA RESEARCH INSTITUTE, INC. · US
• TOYOTA JIDOSHA KABUSHIKI KAISHA · JP

Inventors

• Guy Rosman · Newton, US
• Daniel J. Brooks · Arlington, US
• Simon A. I. Stent · Cambridge, US
• Tiffany L. Chen · San Jose, US
• Emily Sumner · Berkeley, US
• Shabnam Hakimi · San Francisco, US
• Jonathan DeCastro · Arlington, US
• Deepak Edakkattil Gopinath · Chicago, US

Key dates

• Filing date: Aug 26, 2022
• Grant date: Sep 10, 2024
• Expiry date: Mar 16, 2043

Classification

• Technology area (CPC G): Physics
• CPC primary: G06N3/096
• WIPO field: Transport
• WIPO sector: Mechanical engineering

Abstract

Systems and methods for learning and managing robot user interfaces are disclosed herein. One embodiment generates, based on input data including information about past interactions of a particular user with a robot and with existing HMIs of the robot, a latent space using one or more encoder neural networks, wherein the latent space is a reduced-dimensionality representation of learned behavior and characteristics of the particular user, and uses the latent space as input to train a decoder neural network associated with (1) a new HMI distinct from the existing HMIs or (2) a particular HMI among the existing HMIs to alter operation of the particular HMI. The trained first decoder neural network is deployed in the robot to control, at least in part, operation of the new HMI or the particular HMI in accordance with the learned behavior and characteristics of the particular user.