Domain adaptation using simulation to simulation transfer

A robotic agent configured to:

• receive an input image of a real-word environment captured while the robotic agent is interacting with the real-world environment;
• process the input image of the real-world environment using a trained generator neural network to generate an adapted image from the input image, the trained generator neural network having been trained to adapt images of a randomized simulation of the real-world environment into images of a canonical simulation of the real-world environment;
• provide the adapted image as input to a control policy for the robotic agent to select a subsequent action to be performed by the robotic agent;
• and
• control the robotic agent to perform the selected subsequent action in the real-world environment.

One or more non-transitory computer-readable storage media storing instructions that when executed by one or more computers cause the one or more computers to perform operations comprising:

• receiving an input image of a real-word environment captured while a robotic agent is interacting with the real-world environment;
• processing the input image of the real-world environment using a trained generator neural network to generate an adapted image from the input image, the trained generator neural network having been trained to adapt images of a randomized simulation of the real-world environment into images of a canonical simulation of the real-world environment;
• providing the adapted image as input to a control policy for the robotic agent to select a subsequent action to be performed by the robotic agent;
• and
• controlling the robotic agent to perform the selected subsequent action in the real-world environment.