Robotic demonstration retrieval systems and methods

A method for operating a robot system, the method comprising:

• selecting a stored demonstration for a robot from a database of stored demonstrations for different tasks of the robot;
• determining, using an attention model, a similarity value reflecting a similarity between:
• a user input demonstration for the robot;
• and
• one or more of the stored demonstrations for the robot;
• wherein the determining the similarity value includes determining the similarity value based on masking one or more scaled outputs and generating a concatenation based on the user input demonstration and the selected one of the stored demonstrations;
• producing an output indicating whether the one or more stored demonstrations correspond to as the user input demonstration and belong to the same task based on the similarity value;
• and
• actuating actuators of the robot based on a policy trained using the selected one of the stored demonstrations output for augmenting training of the policy,
• wherein the attention model is trained using a training dataset of training demonstrations and a listwise loss over concatenated pairs of training demonstrations, wherein each of the concatenated pairs of training demonstrations are based on a task identifier associated with each training demonstration,
• the training demonstrations each including a temporal sequence of observation-action tuples of successive behaviors for tasks.

A method for operating a robot system comprising:

• obtaining a trained policy stored in a memory;
• and
• actuating actuators of a robot using the trained policy thereby performing a task defined by one or more user input demonstrations;
• and
• wherein the trained policy includes a trained attention model that is trained using a training dataset of training demonstrations and a listwise loss over concatenated pairs of the training demonstrations, wherein each of the concatenated pairs of training demonstrations are based on a task identifier associated with each training demonstration,
• the training demonstrations each including a temporal sequence of observation-action tuples of successive behaviors for tasks, and
• wherein the training dataset of demonstrations, which includes the one or more user input demonstrations for the robot, and which is used to train the trained policy for actuating the actuators of the robot, is augmented with one or more stored demonstrations for the robot when the stored demonstrations are determined to correspond to the one or more user input demonstration and belong to the same task when their similarity values are greater than a predetermined value,
• the augmenting including masking one or more scaled outputs and generating a concatenation based on the one or more user input demonstrations and the one or more stored demonstrations.

A robot system comprising:

• a first circuit configured to select a stored demonstration for a robot from a database of stored demonstrations for different tasks of the robot;
• a second circuit configured to determine, using an attention model, a similarity value reflecting a similarity between:
• a user input demonstration for the robot;
• and
• the selected one of the stored demonstrations for the robot;
• wherein the determining the similarity value includes determining the similarity value based on masking one or more scaled outputs and generating a concatenation based on the user input demonstration and the selected one of the stored demonstrations;
• a third circuit configured to indicate whether the selected one of the stored demonstrations corresponds to the user input demonstration and belongs to the same task based on the similarity value;
• and
• a fourth circuit configured to actuate actuators of the robot based on a policy trained using the selected one of the stored demonstrations output for augmenting training of the policy,
• wherein the attention model is trained using a training dataset of training demonstrations and a listwise loss over concatenated pairs of training demonstrations, wherein each of the concatenated pairs of training demonstrations are based on a task identifier associated with each training demonstration,
• the training demonstrations each including a temporal sequence of observation-action tuples of successive behaviors for tasks.