US 12,296,484 B2
Skill template distribution for robotic demonstration learning
Bala Venkata Sai Ravi Krishna Kolluri, Fremont, CA (US); Stefan Schaal, Mountain View, CA (US); Benjamin M. Davis, Oakland, CA (US); Ralf Oliver Michael Schönherr, San Francisco, CA (US); and Ning Ye, Palo Alto, CA (US)
Assigned to Intrinsic Innovation LLC, Mountain View, CA (US)
Filed by Intrinsic Innovation LLC, Mountain View, CA (US)
Filed on Jun. 26, 2023, as Appl. No. 18/340,968.
Application 18/340,968 is a continuation of application No. 16/880,860, filed on May 21, 2020, granted, now 11,685,047.
Prior Publication US 2023/0356393 A1, Nov. 9, 2023
Int. Cl. B25J 9/16 (2006.01); B25J 9/00 (2006.01); G06N 20/00 (2019.01)
CPC B25J 9/163 (2013.01) [B25J 9/0081 (2013.01); B25J 9/1661 (2013.01); B25J 9/1697 (2013.01); G06N 20/00 (2019.01)] 20 Claims
OG exemplary drawing
 
1. A method performed by one or more computers, the method comprising:
receiving, from a user device by a skill template distribution system, characteristics of a robot and a selection of a skills template from a list of available skill templates compatible with the characteristics of the robot;
providing, by the skill template distribution system, to the user device, the selected skill template, wherein the skill template comprises information representing a state machine of one or more tasks, and wherein the skill template specifies which of the one or more tasks require adaptation using training data;
receiving, by the skill template distribution system, training data for a subtask of the skill template;
training a machine learning model for the subtask using the training data to generate learned parameter values; and
providing, to the user device, the learned parameter values for the machine learning model that causes the robot to implement a control policy that executes the subtask adapted using the training data.