US 10,219,112 B1Granted

Determining delivery areas for aerial vehicles

AssigneeAmazon Technologies, Inc.

InventorPragyana K. Mishra

Life of this patent

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Abstract

Preferred points or regions in space for performing a task at a location, e.g., the delivery of an item to the location, may be defined based on sensed positions obtained during the prior performance of tasks at the location. The sensed positions may be identified using a GPS sensor or like system. Vectors including coordinates of the sensed position, and uncertainties of such coordinates, may be clustered into groups at the location. Subsequently identified vectors including coordinates and uncertainties may further refine a cluster, or be used to generate a new cluster. A preferred point or region in space may be identified based on such location hypotheses and utilized in the performance of tasks. Some preferred points or regions may be used for routing vehicles to the location, while others may correspond to delivery points for items at the location.

Claims20

Dependent claims

A delivery system comprising:

a plurality of unmanned aerial vehicles, wherein the plurality of unmanned aerial vehicles comprises a first unmanned aerial vehicle and a second unmanned aerial vehicle;
at least one memory component;
and
at least one computer processor,
wherein the at least one computer processor is configured to at least:
receive, from the first unmanned aerial vehicle, a first set of coordinates of the first unmanned aerial vehicle during a first delivery of at least a first item to a location at a first time;
identify a geolocation corresponding to the location;
determine a first level of uncertainty associated with at least one of the first unmanned aerial vehicle at the first time or the first set of coordinates;
determine a first geoscan comprising a first Gaussian distribution having a first mean location at the first set of coordinates and the first level of uncertainty;
define a first region at the location based at least in part on the first geoscan and the geolocation, wherein the first region comprises a second Gaussian distribution having the first mean location at the first set of coordinates and the first level of uncertainty;
store information regarding the first region in at least one data store;
receive a request for a second delivery of at least a second item to the location;
identify at least one attribute of at least one of the second delivery or the second item based at least in part on the request;
determine that the first region is suitable for the second delivery based at least in part on the at least one attribute;
determine a path from an origin to the first region;
and
transmit, to a second unmanned aerial vehicle, an instruction to deliver at least the second item from the origin to the first region along the path.

14 more elements

A method comprising:

after a first delivery of at least a first item to a location,
identifying a first sensed position associated with the first delivery using at least one computer processor;
determining a first level of uncertainty associated with at least the first sensed position using the at least one computer processor;
defining a first vector based at least in part on the first sensed position and the first level of uncertainty using the at least one computer processor;
determining a first geolocation associated with the location;
establishing a first preferred area for landing unmanned aerial vehicles at the location based at least in part on the first vector and the first geolocation using the at least one computer processor;
and
storing information regarding the first preferred area in association with the location in at least one data store,
wherein the information regarding the first preferred area comprises a first probability distribution function for the first preferred area.

6 more elements

A computer-implemented method comprising:

receiving a first geoscan from a first unmanned aerial vehicle over a network, wherein the first geoscan is received from the first unmanned aerial vehicle during a first delivery of at least a first item to a location by the first unmanned aerial vehicle;
defining a location hypothesis by at least one computer processor, wherein the location hypothesis is defined based at least in part on the first geoscan, and wherein the location hypothesis comprises a mean location, a major axis and a minor axis;
receiving a request for a second delivery of at least a second item to the location over the network;
transmitting information regarding the second delivery to a second unmanned aerial vehicle over the network, wherein the information regarding the second delivery comprises at least a first instruction to travel to the location with the second item and a second instruction to deposit the second item on a surface within the location hypothesis;
receiving a second geoscan from the second unmanned aerial vehicle over the network, wherein the second geoscan is received from the second unmanned aerial vehicle during the second delivery;
and
refining the location hypothesis by the at least one computer processor, wherein the location hypothesis is refined based at least in part on the second geoscan,
wherein refining the location hypothesis comprises at least one of:
relocating the mean location;
modifying the major axis;
or
modifying the minor axis.

9 more elements

Dependencies are inferred from the claim text.

Facts

Application: 15/678,972Filed 16 Aug 2017 · continuation
Priority: 30 Sep 2015
Granted: 26 Feb 2019
Term ends: Not estimatedThe source records don’t support an estimate.

Classification6 codes

H04W 4/023
Services making use of location information: using mutual or relative location information between multiple location based services [LBS] targets…
G06Q 10/083
Logistics, e.g. warehousing, loading or distribution; Inventory or stock management: shipping
H04W 4/021
Services making use of location information: services related to particular areas, e.g. point of interest [POI] services, venue services or geofences
G06Q 10/0841
Shipping: compliance with shipping requirements