US 12,280,499 B2
Domain adaptation for simulated motor backlash
Sergey Bashkirov, Salida, CA (US); and Michael Taylor, San Mateo, CA (US)
Assigned to Sony Interactive Entertainment Inc., Tokyo (JP)
Filed by Sony Interactive Entertainment Inc., Tokyo (JP)
Filed on Nov. 11, 2020, as Appl. No. 17/095,586.
Prior Publication US 2022/0143820 A1, May 12, 2022
This patent is subject to a terminal disclaimer.
Int. Cl. B25J 9/16 (2006.01); B25J 9/12 (2006.01); G06F 30/27 (2020.01); G06N 3/048 (2023.01); G06N 3/084 (2023.01); G06V 10/75 (2022.01)
CPC B25J 9/163 (2013.01) [B25J 9/12 (2013.01); G06F 30/27 (2020.01); G06N 3/084 (2013.01); G06V 10/751 (2022.01); G06N 3/048 (2023.01)] 20 Claims
OG exemplary drawing
 
1. A method for training a control input system, comprising:
a) taking an integral of an output value from a Motion Decision Neural Network for one or more movable joints to generate an integrated output value;
b) comparing the integrated output value to a backlash threshold;
c) generating a subsequent output value using a machine learning algorithm that includes as inputs a sensor value and a previous joint position when the integrated output value does not at least meet the threshold;
d) simulating a position of the one or more movable joints based on an integral of the subsequent output value; and
e) training the Motion Decision Neural Network with the machine learning algorithm based upon at least a result of the simulation of the position of the one or more movable joints;
repeating a) through e), wherein c) includes generating the subsequent output value using a machine learning algorithm that includes a sensor value and the integrated output value when the integrated output value meets or exceeds the threshold; and
controlling a robot by passing the integrated output value to a movable joint when the integrated output value meets or exceeds the threshold.