Abstract: Object picking optimization is disclosed, including: receiving an image of a target object; inputting the image in a machine learning model that is configured to output a pick probability heat map corresponding to the target object; selecting a pick location on the target object based at least in part on the pick probability heat map corresponding to the target object; and causing a diverting mechanism to perform a pick operation on the target object based at least in part on the pick location.

Abstract: Pick quality determination is disclosed, including: using a pressure meter to sense a pressure associated with an airflow through a gripper mechanism of a diverting mechanism over time during a pick operation on a target object; storing the sensed pressure associated with the airflow through the gripper mechanism over time as a pressure sequence associated with the pick operation on the target object; and correlating the pressure sequence with representative pressure sequences associated with corresponding pick quality types to determine whether the pick operation on the target object was successful or not.