Injecting noise into robot simulation

A method implemented using one or more processors, comprising:

• simulating an environment, wherein the simulated environment includes a simulated robot controlled by an external robot controller;
• intercepting a temporal sequence of robot commands issued by the robot controller to control the simulated robot in the simulated environment;
• generating a temporal sequence of progressing noise values using a time series machine learning model, wherein the generating comprises iteratively applying time series data indicative of wear and tear metrics associated with a real-world robot;
• injecting the temporal sequence of progressing noise values into corresponding robot commands of the temporal sequence of robot commands to generate noisy robot commands, wherein the injecting includes altering, skewing, biasing, or replacing existing robot command values with noisy robot command values;
• and
• operating the simulated robot in the simulated environment based on the noisy robot commands.

A method implemented using one or more processors, comprising:

• simulating an environment, wherein the simulated environment includes a simulated robot controlled by an external robot controller;
• intercepting a temporal sequence of robot commands issued by the robot controller to control the simulated robot in the simulated environment;
• injecting a temporal sequence of progressing noise values into corresponding robot commands of the temporal sequence of robot commands to generate noisy robot commands, wherein the injecting includes altering, skewing, biasing, or replacing existing robot command values with noisy robot command values, and wherein the temporal sequence of progressing noise values simulate a bias of gravity over time on oscillations of one or more joints of the simulated robot;
• and
• operating the simulated robot in the simulated environment based on the noisy robot commands.

A system comprising one or more processors and memory storing instructions that, in response to execution by the one or more processors, cause the one or more processors to:

• simulate an environment, wherein the simulated environment includes a simulated robot controlled by an external robot controller;
• intercept a temporal sequence of robot commands issued by the robot controller to control the simulated robot in the simulated environment;
• generate a temporal sequence of progressing noise values using a time series machine learning model, wherein the time series machine learning model is trained based on empirical data about effects of environmental conditions on robot joint operation;
• inject the temporal sequence of progressing noise values into corresponding robot commands of the temporal sequence of robot commands to generate noisy robot commands, wherein the injecting includes altering, skewing, biasing, or replacing existing robot command values with noisy robot command values;
• and
• operate the simulated robot in the simulated environment based on the noisy robot commands.

A system comprising one or more processors and memory storing instructions that, in response to execution by the one or more processors, cause the one or more processors to:

• simulate an environment, wherein the simulated environment includes a simulated robot controlled by an external robot controller;
• intercept a temporal sequence of robot commands issued by the robot controller to control the simulated robot in the simulated environment;
• generate a temporal sequence of progressing noise values using a time series machine learning model, wherein the instructions to generate include instructions to iteratively apply time series data indicative of wear and tear metrics associated with a real-world robot;
• inject the temporal sequence of progressing noise values into corresponding robot commands of the temporal sequence of robot commands to generate noisy robot commands, wherein the injecting includes altering, skewing, biasing, or replacing existing robot command values with noisy robot command values;
• and
• operate the simulated robot in the simulated environment based on the noisy robot commands.

A system comprising one or more processors and memory storing instructions that, in response to execution by the one or more processors, cause the one or more processors to:

• simulate an environment, wherein the simulated environment includes a simulated robot controlled by an external robot controller;
• intercept a temporal sequence of robot commands issued by the robot controller to control the simulated robot in the simulated environment;
• inject a temporal sequence of progressing noise values into corresponding robot commands of the temporal sequence of robot commands to generate noisy robot commands, wherein the injecting includes altering, skewing, biasing, or replacing existing robot command values with noisy robot command values, and wherein the temporal sequence of progressing noise values simulate a bias of gravity over time on oscillations of one or more joints of the simulated robot;
• and
• operate the simulated robot in the simulated environment based on the noisy robot commands.