Procedural memory learning and robot control

An apparatus for procedural memory learning to control a robot to perform a task, the robot having a robot controller which includes an artificial neural network (ANN), the apparatus comprising:

• a signal interface for receiving a plurality of signals from the robot controller;
• a correlator for generating a correlation of at least two of the signals and producing a correlation output;
• a matrix unit for generating a similarity matrix having an element containing the correlation and sending the matrix to the ANN via the robot controller;
• a low-level control interface for sending direct control commands to the robot controller;
• and
• an aggregator for aggregating control signals from the ANN according to a kinematics model of the robot.

A computer-readable non-transitory storage medium including computer-executable instructions for procedural memory learning to control a robot to perform a task, which instructions, when executed by a computer, cause the computer to:

• compute a similarity matrix whose elements comprise values according to at least one function of similarity of a plurality of signals from the robot, the signals related to an action of the task performed by the robot with direct control command via a low-level interface;
• input into an artificial neural network (ANN) controller of the robot:
• the direct control command;
• and
• the similarity matrix;
• receive control signals from the ANN controller to control the robot;
• aggregate the control signals from the ANN controller by an aggregator according to a kinematics model of the robot;
• and
• send-aggregated control signals from the aggregator to the robot, to perform the task.