Systems and methods for robotic picking

An apparatus for the picking and perturbation of objects, the apparatus comprising:

• a picking element, wherein the picking element is configured to pick up objects from an area;
• a perturbation element, wherein the perturbation element is configured to reposition the objects within the area;
• one or more cameras, wherein the one or more cameras collect three-dimensional image data to use for operating the picking element and the perturbation element;
• and
• a computing system comprising one or more processors and one or more memories operably coupled to the one or more processors, the one or more memories having stored thereon software instructions that, upon execution by the one or more processors, cause the one or more processors to:
• obtain one or more images from the one or more cameras, wherein the images comprise information related to the objects within the area;
• identify a plurality of distinct objects in the area based on the three-dimensional image data;
• provide at least a portion of the images to one or more machine learning algorithms trained to identify picking strategies, wherein the picking strategies identify an order of the plurality of distinct objects to attempt to pick up and a location on each object of the plurality of distinct objects at which to grasp each object;
• direct the picking element to attempt to pick up an object of the plurality of distinct objects at a first location on the object according to a picking strategy of the picking strategies identified by the one or more machine learning algorithms;
• in response to determining that the object was not successfully picked up, direct the perturbation element to reposition the object such that a position of the object changes;
• after repositioning the object, providing new image data to the one or more machine learning algorithms, wherein the new image data comprises new information related to the objects in the area;
• and
• direct the picking element to pick up the object at a second location on the object according to a different picking strategy identified by the one or more machine learning algorithms.

A robotic system comprising:

• a picking element configured to pick up items in a region;
• one or more cameras configured to collect visual information about the region;
• and
• a computing system comprising one or more processors and one or more memories operably coupled to the one or more processors, the one or more memories having stored thereon software instructions that, upon execution by the one or more processors, cause the one or more processors to:
• identify a plurality of distinct items in the region based on the visual information collected by the one or more cameras;
• provide at least a portion of the visual information to one or more machine learning algorithms trained to identify picking strategies, wherein the picking strategies identify an order of the plurality of distinct items to attempt to pick up and a location on each item of the plurality of distinct items at which to grasp each item;
• attempt to pick up an item of the plurality of distinct items by directing the picking element to pick up the item at a first location on the item using a picking strategy of the picking strategies identified by the one or more machine learning algorithms;
• in response to determining that the item was not successfully picked up, repositioning the item by directing a perturbation element of the robotic system to change a position of the item;
• after repositioning the item, providing new visual information to the one or more machine learning algorithms, wherein the new visual information comprises new information about the region;
• and
• attempt to pick up the item by directing the picking element to pick up the item at a second location on the item using a different picking strategy identified by the one or more machine learning algorithms.