US 2026/0295847 A1Published application

Station for moving objects using machine learning models

AssigneeAmazon Technologies, Inc.

InventorsTimothy Stallman, Jeremy Kenneth Skorinko, Spencer Pallas

Life of this patent

Estimating the term…

Loading patent…

Abstract

Systems and methods are disclosed for a station used to move and capture objects from one area to another. The systems may obtain a first set of images that includes an object located within a region positioned corresponding to the first area, wherein the region is to be determined based, at least in part, on a field of view of a first sensor that generated the first set of images. The systems may identify, using a first machine learning model, an identifier associated with the object based, at least in part, on the first set of images. The systems may generate using a second machine learning model, an indication of whether the object is placed inside the first container based, at least in part, on the second set of images.

Claims20

Dependent claims

A station comprising:

a first rectangular area, a second rectangular area, and a third rectangular area, wherein the second rectangular area is adjacent to the first rectangular area along a first edge, the third rectangular area is adjacent to the first rectangular area along a second edge, the second edge being perpendicular to the first edge, forming an L-shaped arrangement with the first rectangular area;
one or more processors;
and
one or more non-transitory computer-readable media storing thereon executable instructions that, as a result of being executed by one or more processors of a computer system, cause the station to at least:
use a first camera to generate one or more first images that include an object that enters an area of interest positioned above the first rectangular area from a first container located within the second rectangular area, wherein the area of interest is determined based, at least in part, on a placement of the first camera and dimensions of the first rectangular area;
detect, using a first machine learning model, an identifier corresponding to the object based, at least in part, on the one or more first images;
use a second camera positioned above the third rectangular area to generate one or more second images comprising the object that is outside the area of interest;
generate, using a second machine learning model, an indication of whether the object is stored within a second container based, at least in part, on the one or more second images;
and
cause the second container to move to a destination outside of the station based, at least in part, on the indication of whether the object is stored within the second container and information of the object obtained from the identifier.

7 more elements

A system comprising:

a first area, a second area, and a third area, wherein the second area is adjacent to the first area along a first edge, the third area is adjacent to the first area along a second edge, and the second edge being perpendicular to the first edge;
one or more processors;
and
memory that stores computer-executable instructions that, if executed by the one or more processors, cause the system to:
obtain a first set of images that includes an object located within a region positioned corresponding to the first area, wherein the region is to be determined based, at least in part, on a field of view of a first sensor that generated the first set of images;
identify, using a first machine learning model, an identifier associated with the object based, at least in part, on the first set of images;
obtain a second set of images that includes the object to be placed in a first container located in the third area;
and
generate, using a second machine learning model, an indication of whether the object is placed inside the first container based, at least in part, on the second set of images.

6 more elements

A computer-implemented method, comprising:

causing a first sensor within a space corresponding to a first area of a station to generate one or more first images including an object that is to be moved from a first container located within a second area of the station, wherein the second area borders the first area along a first edge, a third area borders the first area along a second edge, and the second edge being positioned perpendicularly to the first edge.
using a first set of machine learning models to identify an identifier of the object based, at least in part, on the one or more first images;
causing a second sensor within another space corresponding to the third area to generate one or more second images including an object that is to be placed within a second container located within the third area;
using a second set of machine learning models to determine whether the object is placed within the second container based, at least in part, on the one or more second images;
and
causing the second container to be moved to a destination outside of the station as a result of the determination on whether the object is placed within the second container.

3 more elements

Dependencies are inferred from the claim text.