Method of synthesising training datasets for autonomous robotic control

Abstract

The present disclosure relates to a computer-implemented method of synthesising a training dataset for training a comparison function of a machine learning service in the detection of a multi-pick event in which a robotic manipulator erroneously picks two or more items concurrently, the method comprising: selecting first image data representative of an image of a plurality of items to be picked by the robotic manipulator; selecting intermediate image data representative of an image of the plurality of items following the removal, by the robotic manipulator, of an item from the plurality of items; selecting final image data representative of an image of the plurality of items following the removal, by the robotic manipulator, of another item from the plurality of items; and, generating the training dataset representative of a notional multi-pick event based on a sequence of unlabelled image data consisting of the first and final image data.