Amazon Technologies, Inc.

Jon T Hanlon

Neil Whitney Woodward, Iii

Mark Daniel Sibon

Asaf Gilboa-Amir

James Christopher Curlander

Scott Raymond Harris

Jason Leonard Peacock

Samuel Theodore Sandler

Tally Etel Portnoi

Daniel Tarekegn

Monica T McCann

An automated system is provided that receives and utilizes travel related data from unmanned aerial vehicles ('UAVs') for optimizing the scheduling and routing of deliveries by UAVs. Travel routes through delivery areas are planned and when it is determined that a first UAV has deviated from a planned travel route to avoid a location in an area, a second UAV (e.g., which may have additional sensors and/or recording capabilities) may be sent to collect updated travel related data regarding the location. The updated travel related data (e.g., which may indicate that there is a new obstacle, a source of magnetic interference, a wind, etc. at the location) may be utilized for planning future travel routes for deliveries.

Unmanned aerial vehicles utilized to collect updated travel related data for deliveries

A maintenance notification for a UAV may be sent to a service provider. The service provider may identify the UAV, such as to access a profile associated with the UAV that includes at least hardware and software configurations for the UAV. The service provider may generate a customized maintenance decision tree to organize tasks to be performed for the specific UAV to determine a maintenance action to remedy a fault or problem associated with the maintenance notification. The decision tree may be formed using history of the UAV and information about other UAVs to construct the decision tree tailored to the specific UAV under analysis. At least some operations included in the decision tree may be automated. Traversal of the decision tree may lead to updates of the UAV of hardware, software, or both.

Unmanned aerial vehicle maintenance troubleshooting decision tree

Approaches presented herein enable credentials to be revoked or otherwise modified while limiting the impact of inadvertent or unintended changes in access. In some embodiments, the revocation of a credential can occur over a period of time with the level of access being diminished over that period, in order to prevent an inadvertent denial of access while indicating to the requestor that there is an issue with the credential. When a new policy is created for a new credential, a prior policy can be retained for at least a period of time such that users with inadvertently revoked access can obtain a level of access per the previous policy. Various embodiments trace the calls for a credential throughout the system in order to determine which services, processes, or components might be affected by the revocation, such that an appropriate remedial action can be taken.

Ownership maintenance in a multi-tenant environment

A delivery robot may provide an approach notification to enable people to understand and interpret actions by an unmanned aerial vehicle (UAV), such as an intention to land or deposit a package at a particular location. The delivery robot may include a display, lights, a speaker, and one or more sensors to enable the robot to provide information, barcodes, and text to the UAV and/or bystanders. The robot can provide final landing authority, and can 'wave-off' the UAV, if an obstacle or person exists in the landing zone. The delivery robot can receive packages and (1) store them for retrieval (2) deliver them to the delivery location and/or (3) deliver them to an automated locker system. The delivery robot can temporarily close lanes or streets to enable a package to be delivered by UAV. The system may include a shelter to secure, maintain, and charge the delivery robot.

Landing and delivery robot

A weight distribution associated with an unmanned aerial vehicle (UAV) may be determined prior to dispatch of the UAV and/or after the UAV returns from operation (e.g., a flight). In some embodiments, one or more UAVs may be placed on or proximate to a physical metrics acquisition (PMA) device. The PMA device may include a configurable scale and may be used to determine a distribution of weight of the UAV at three or more points associated with the UAV. The distribution of weight may be used generate analytics, which may include a total weight of a vehicle, a center of mass of the vehicle (in two or more dimensions), power requirements of the UAV for a given flight task (e.g., how much battery power the UAV requires, etc.), and/or other analytics. In various embodiments, the PMA device may perform moment of inertia tests for the UAV.

Unmanned aerial vehicle scale alignment

An automated system is provided that receives and utilizes travel related data from unmanned aerial vehicles ('UAVs') and other sources (e.g., data aggregators, weather services, obstacle databases, etc.) for optimizing the scheduling and routing of deliveries by UAVs. The travel related data that is received from the sensors of UAVs and other sources may indicate the locations and characteristics of obstacles, weather, crowds of people, magnetic interference, etc., which may be evaluated and utilized for determining and updating flight plans for UAVs. In various implementations, the travel related data received from the sensors of a UAV may be combined with other travel related data and stored (e.g., at a central management system, in UAVs, etc.) for further analysis and use in determining UAV delivery schedules and related operations of materials handling facilities.

Unmanned aerial vehicle data collection for routing

Ownership maintenance of multi-tenant environment

A UAV tethering system provides an environment in which to fly an unmanned aerial vehicle (UAV) where the tether is selected to prevent the UAV from unintentional contact with the ground or other objects within the flight area. A tether may connect the UAV to a shuttle that slides along a track. The tether may be used to provide efficient, robust and accurate positioning information. The system can be configured to detect the angle at which the tethering line extends from the shuttle, the length of the extended tethering line, and then compute the position of the UAV relative to the shuttle. Furthermore, by knowing the position of the shuttle, the absolute position of the UAV can be determined.

Track and tether vehicle position estimation

Systems and methods for delivering packages via aerial vehicles are disclosed. The system can comprise a label that includes a parachute to enable the packages to be dropped from the aerial vehicle, yet land at the package's destination without damage. The system can include a self-adhesive backing, a plurality of parachute cords, a parachute, and a breakaway cover. The parachute cords can include a shock absorber to reduce the shock on the package of the parachute opening. The parachute and/or the breakaway cover can include graphics to provide address, velocity, or spin information for the package. The parachute cords can include a harness to separate the cords and reduce tangling of the cords and spinning of the parachute canopy with respect to the package.

Aerial package delivery system

An application program interface may be used to collect and disseminate physical metrics of an unmanned aerial vehicle (UAV). A weight distribution associated with a UAV may be determined prior to dispatch of the UAV and/or after the UAV returns from operation (e.g., a flight). In some embodiments, one or more UAVs may be placed on or proximate to a physical metrics acquisition (PMA) device to determine a distribution of weight of the UAV at three or more points associated with the UAV. The distribution of weight may be used generate analytics, which may include a total weight of a vehicle, a center of mass of the vehicle (in two or more dimensions), power requirements of the UAV for a given flight task (e.g., how much battery power the UAV requires, etc.), and/or other analytics. In various embodiments, the PMA device may perform moment of inertia tests for the UAV.

Application program interface for weight and balance metrics

A weight distribution associated with an unmanned aerial vehicle (UAV) may be determined prior to dispatch of the UAV and/or after the UAV returns from operation (e.g., a flight). In some embodiments, one or more UAVs may be placed on or proximate to a physical metrics acquisition (PMA) device. The PMA device may include a grid or array of load cells may be used to determine a distribution of weight of the UAV at three or more points associated with the UAV. The distribution of weight may be used generate analytics, which may include a total weight of a vehicle, a center of mass of the vehicle (in two or more dimensions), power requirements of the UAV for a given flight task (e.g., how much battery power the UAV requires, etc.), and/or other analytics. In various embodiments, the PMA device may perform moment of inertia tests for the UAV.

Unmanned aerial vehicle physical metrics acquisition

Disclosed herein is a platform for automating the discovery of product bundles that are promising for sale to customers (i.e., they are relevant, valuable and/or timely). Techniques are disclosed for generating a set of potential product bundles according to criteria, thresholds and/or scores which indicate a propensity for items to be purchased together by customers. The generated set of potential product bundles may be ranked according to opportunity metrics and/or scores which indicate value to a merchant and/or customers. A subset of product bundles is selected from the set of potential product bundles based at least in part on the ranking, and each product bundle in the selected subset is matched to one or more entities, such as merchants. These product bundles may then be presented to the associated (i.e., matched) entity based on some criteria, such as offerings of the merchants.

Growing community of inventors

Mercer Island, WA, United States of America

Jon T Hanlon