WO2021194852A1

WO2021194852A1 - Uav delivery network

Info

Publication number: WO2021194852A1
Application number: PCT/US2021/023010
Authority: WO
Inventors: Matthew Sweeny; Allison MALLOY
Original assignee: Flirtey Holdings, Inc.
Priority date: 2020-03-24
Filing date: 2021-03-18
Publication date: 2021-09-30

Abstract

The present disclosure provides am Unmanned Aerial Vehicle (UAV) delivery network comprising a plurality of UAVs, a plurality of UAV facilities and one or more fulfillment centers located at each of the UAV facilities. The UAV delivery network may be reconfigured by reassigning UAVs from a first UAV facility to a second UAV facility and/or by relocating a UAV facility within the network. Deliveries may be made to customers based on the time required to fulfill and deliver the customer order. The order fulfillment and delivery time may be displayed to the user before an order is placed. The UAV delivery network may further comprise one or more emergency UAVs, which may be assigned to UAV facilities such that part or all of the UAV delivery network can be reached by an emergency UAV.

Description

UAV DELIVERY NETWORK

BACKGROUND OF THE INVENTION

Field of the Invention

[0001] The present invention relates to Unmanned Aerial Vehicle (UAV) delivery networks and in particular to methods of operating and configuring UAV delivery networks.

Description of the Related Technology

[0002] Figure 1 shows a graphical representation of a UAV facility 110 (sometimes referred to as a UAV portal) and a plurality of UAVs 10, or drones, which can be operated from a UAV facility 110. A number of UAV facilities can be operated together to form a UAV delivery network. Each UAV facility operates with one or more fulfillment centers to deliver packages from the fulfillment centers to customers. One or more fulfillment centers may be co-located with a UAV facility. A fulfillment center may be a restaurant, a shop, a pharmacy, a vending machine or other commercial or business enterprise. The UAV delivery network may be used as the last leg of a parcel delivery network or courier network or for delivering orders made via online shopping platforms. Further details as to the operation and function of a UAV facility can be found in the Applicant’s co-pending application 62/731,562, the contents of which are incorporated herein by reference.

SUMMARY

[0003] According to a first aspect of the present disclosure there is provided a delivery network for delivering a payload to a customer using an Unmanned Aerial Vehicle, UAV, said delivery network comprising a plurality of UAV facilities and a plurality of UAVs, each of said plurality of UAVs being assigned to one of the plurality of UAV facilities, wherein the delivery network is reconfigured in response to the utilization of the delivery network.

[0004] The delivery network may be reconfigured in response to the utilization of one or more UAV facilities falling below a first predetermined value. Alternatively, the delivery network may be reconfigured in response to the utilization of one or more UAV facilities exceeding a second predetermined value. The delivery network may be reconfigured by moving one of said UAV facilities from a first location to a second location. Furthermore, the delivery network may be reconfigured by moving a first UAV facility from a first location to a second location, wherein a second UAV facility is also located at the second location. The delivery network may be reconfigured by activating a further UAV facility. The further UAV facility may be activated at a location where a UAV facility is operating. The delivery network may be reconfigured by deactivating one of the plurality of UAV facilities.

[0005] Alternatively, or in addition, the delivery network may be reconfigured in response to the utilization of one or more UAVs falling below a third predetermined value. Furthermore, the delivery network may be is reconfigured in response to the utilization of one or more UAVs exceeding a fourth predetermined value. The delivery network may be reconfigured by re-assigning one or more UAVs from a first UAV facility to a second UAV facility. Furthermore, the delivery network may comprise a plurality of a first type of UAVs and a plurality of a second type of UAVs and the delivery network may be reconfigured by re assigning one or more UAVs of said first type from a first UAV facility to a second UAV facility.

[0006] The utilization of the delivery network may be determined in part in accordance with customer demand: The utilization of the delivery network may be determined in part in accordance with the number of customer requests received from a geographical area; the rate of customer requests received or in response to the number of pending orders. Alternatively, the utilization of the delivery network may be determined in part in accordance with predicted customer demand.

[0007] By reconfiguring the delivery network in this manner, it is possible to utilize the UAVs in the network in an efficient manner. The number of UAVs active in the network can be controlled in response to customer demand and the UAVs can be deployed to those UAV facilities which are experiencing the greatest customer demand. This flexible allocation of resources enables customer demand to be met whilst minimizing wasted expenditure on unused UAVs and UAV facilities.

According to a second aspect of the present disclosure there is provided a method of delivering an order to a customer using an Unmanned Aerial Vehicle, UAV, delivery network, the UAV delivery network comprising a plurality of UAV facilities, one or more fulfillment centers and a plurality of UAVs, the method comprising the steps of: i) receiving an order from a customer; ii) identifying a plurality of fulfillment centers which can fulfill the order; iii) for each of the fulfillment centers identified in step ii), determining an associated UAV facility; iv) for each of the fulfillment centers identified in step ii), determining the time required to deliver the fulfilled order to the customer from the associated UAV facility identified in step iii); v)assigning the customer order to the fulfillment center having the shortest time to deliver the fulfilled order as determined in step iv); and vi) delivering the order to the customer using a UAV.

[0008] In step iv) the time required to deliver the fulfilled order may be determined in accordance with the time required to fulfill the order and the time required for a UAV to fly from the UAV facility to the customer location.

[0009] Alternatively, in step iv) the time required to deliver the fulfilled order is determined in accordance with the time required to load the fulfilled order onto an available UAV and the time required for a UAV to fly from the UAV facility to the customer location. The time required to deliver the fulfilled order may be determined in accordance with one or more UAV characteristics. The time required to deliver the fulfilled order may be determined in accordance with the distance of the customer location from each of the fulfillment centers. Furthermore, the time required to deliver the fulfilled order may be determined in accordance with meteorological data received from one or more meteorological data sources. The time required to load the fulfilled order onto an available UAV may comprise the time required to relocate a UAV to the UAV facility associated with the fulfillment center. Additionally, or in the alternative, the time required to load the fulfilled order onto an available UAV may comprise the time required to replace a UAV battery or the time required to perform some other maintenance procedure for a UAV, a UAV facility and/or a fulfillment center.

[0010] Orders can be delivered to a customer from the fulfillment center which is able to provide the fastest delivery. The customer does not need to know where the fulfillment centers are located or which of the fulfillment centers is closest to the customer. The order is allocated to the fulfillment center which is able to fulfill and deliver the order the soonest, based on the activity level of the fulfilment center, the associated UAV facility and other external factors (such as the weather) which may affect the delivery time.

[0011] According to a third aspect of the present disclosure there is provided a non- transitory computer-readable medium having computer-executable instructions stored thereon, wherein the instructions, when executed, cause a computer system having at least one computer processor to perform a method comprising the steps of: i) receiving an order from a customer; ii) identifying a plurality of fulfillment centers which can fulfill the order; iii) for each of the fulfillment centers identified in step ii), determining the time required to deliver the fulfilled order to the customer from an Unmanned Aerial Vehicle, UAV, facility associated with said fulfillment center; iv) assigning the customer order to the fulfillment center having the shortest time to deliver the fulfilled order as determined in step iii); and v) causing the order to be delivered to the customer using a UAV. [0012] According to a fourth aspect of the present disclosure there is provided a computing system, comprising: one or more processors; and a memory coupled to the processor and storing program instructions that when executed by the processor causes the processor to at least: i) receive an order from a customer; ii) identify a plurality of fulfillment centers which can fulfill the order; iii) for each of the fulfillment centers identified in step ii), determine the time required to deliver the fulfilled order to the customer from an Unmanned Aerial Vehicle, UAV, facility associated with said fulfillment center; iv) assign the customer order to the fulfillment center having the shortest time to deliver the fulfilled order as determined in step iii); and v) cause the order to be delivered to the customer using a UAV.

[0013] According to a fifth aspect of the present disclosure there is provided a system for use with an Unmanned Aerial Vehicle, UAV, delivery network, the system comprising a customer facing server and a plurality of fulfillment center servers, the customer facing server being configured in use to receive data from a UAV flight management system and the plurality of fulfillment center servers such that, in use, the customer facing server: a) receives an order from a customer; b) identifies a plurality of fulfillment centers which can fulfill the customer order; c) determines the time required to deliver the fulfilled order to the customer from the associated UAV facility for each of the fulfillment centers identified in step b); and d) assigns the customer order to the fulfillment center having the shortest time to deliver the fulfilled order as determined in step c).

[0014] In step c) the customer facing server may determine the time required to deliver the fulfilled order in accordance with the time required to fulfill the order and the time required for a UAV to fly from the UAV facility to the customer location. Alternatively, in step c) the customer facing server may determine the time required to deliver the fulfilled order in accordance with the time required to load the fulfilled order onto an available UAV and the time required for a UAV to fly from the UAV facility to the customer location. The customer facing server may determine the time required to deliver the fulfilled order in accordance with one or more UAV characteristics. The time required to deliver the fulfilled order may be determined in accordance with the distance of the customer location from each of the fulfillment centers. The time required to deliver the fulfilled order may be determined in accordance with meteorological data received from one or more meteorological data sources.

[0015] According to a sixth aspect of the present disclosure there is provided a method of processing an online order for delivery using an Unmanned Aerial Vehicle, UAV, delivery network, the UAV delivery network comprising a plurality of UAV facilities, one or more fulfillment centers associated with each of the plurality of UAV facilities and a plurality of UAVs, the method comprising the steps of: a) receiving a request from a customer, the customer request comprising one or more items for delivery; b) receiving data from a UAV flight management system; c) receiving data from a plurality of fulfillment centers; d) for each of the fulfillment centers which can supply the one or more items specified in the customer request, determining the time required to deliver the one or more items to the customer; e) selecting the fulfillment center having the smallest delivery time; and f) displaying to the customer the delivery time for the fulfillment center selected in step e) before the customer places an order.

[0016] The time required to deliver the one or more items to the customer may be determined in accordance with the time required to fulfill the customer order and the time required for a UAV to fly from the UAV facility to the customer location. Alternatively, the time required to deliver the one or more items to the customer is determined in accordance with the time required to load the customer order onto an available UAV and the time required for a UAV to fly from the UAV facility to the customer location. The time required to deliver the one or more items to the customer may be determined in accordance with one or more UAV characteristics. In an alternative, the time required to deliver the one or more items to the customer may be determined in accordance with the distance of the customer location from each of the fulfillment centers. The time required to deliver the one or more items to the customer is determined in accordance with meteorological data received from one or more meteorological data sources.

[0017] The method enables the customer to be informed of the delivery time before the order is placed, with the delivery time being calculated in accordance with the activity level of the fulfillment center and the associated UAV facility. If the delivery time is relatively low then this may make a customer more inclined to place an order. Conversely, the method enables a customer to know when delivery times are long and provides a superior customer experience as the customer will not place an order only to subsequently discover that they will gave to endure a long wait for their order to be delivered.

[0018] According to a seventh aspect of the present disclosure there is provided an Unmanned Aerial Vehicle, UAV, network for delivering a payload to a customer using a UAV, said delivery network comprising a plurality of UAV facilities, a first plurality of delivery UAVs, and a second plurality of emergency UAVs wherein each of said plurality of emergency UAVs is assigned to one of the UAV facilities such that emergency UAV cover is provided to the UAV network in accordance with one or more pre-determined metrics. The UAV delivery network may be re-configured to maintain the emergency UAV cover provided to the UAV network in accordance with said one or more pre-determined metrics. The UAV delivery network may be re-configured by re-assigning an emergency UAV from a first UAV facility to a second UAV facility. Alternatively, or in addition, the UAV delivery network may be re configured by re-classifying a delivery UAV as an emergency UAV. A delivery UAV may be re-classified as an emergency UAV by loading a delivery UAV with an emergency payload. The emergency UAV may comprise a UAV which has an extended range compared to a conventional UAV. The one or more pre-determined metrics may comprise a proportion of the UAV network which can be reached by an emergency UAV within a pre-determined period of time and/or a proportion of the UAV network which is provided with emergency UAV cover.

[0019] This aspect of the disclosure enables a number of emergency UAVs to be located across the UAV delivery network. The type of emergency UAVs deployed and the location of the emergency UAVs deployed in the UAV delivery network can be varied in order to provide the necessary level of emergency UAV cover. Additional emergency UAVs can be deployed as and when necessary. Such an arrangement enables a network operator to provide sufficient emergency UAV coverage whilst avoiding the need to deploy an excessive number of emergency UAVs.

BRIEF DESCRIPTION OF THE DRAWINGS

[0020] Figure 1 shows a graphical representation of a UAV facility and a plurality of UAVs;

[0021] Figure 2 shows a schematic depiction of a UAV delivery network according to an embodiment of the present disclosure;

[0022] Figure 3 shows a schematic depiction of the delivery network of Figure 2 after the network has been re-configured into a second configuration;

[0023] Figure 4 shows a schematic depiction of the delivery network of Figure 2 after the network has been re-configured into a third configuration;

[0024] Figure 5 shows a schematic depiction of a further UAV delivery network;

[0025] Figure 6 shows a schematic depiction of a communications network which can be used to enable the allocation of an order;

[0026] Figure 7 shows a graphical depiction of a flowchart describing an order allocation process according to an aspect of the present disclosure;

[0027] Figure 8 shows a graphical depiction of a flowchart describing a method according to a further aspect of the present disclosure; and [0028] Figure 9 shows a schematic depiction of a UAV delivery network according to a further aspect of the present disclosure.

DETAILED DESCRIPTION OF CERTAIN INVENTIVE EMBODIMENTS

[0029] Figure 2 shows a schematic depiction of a UAV delivery network 100 according to an embodiment of the present disclosure. The UAV delivery network 100 comprises a plurality of UAV facilities 110, each of which has a respective delivery area 120. Figure 2 shows an exemplary delivery network which comprises a first UAV facility 110A, a second UAV facility 110B and a third UAV facility llOC with respective first, second and third delivery areas 120A, 120B, 120C. It can be seen that as the respective delivery areas overlap with each other then there will be a number of areas 125a, 125b, 125c which can be served from two different UAV facilities. There is also one area 125d which can be served from all three of the UAV facilities. The delivery area of each UAV facility is defined by the maximum distance that a UAV can fly from the UAV facility to a customer location with a payload and then return to the UAV facility after having delivered the payload to the customer. Preferably the UAV will return with a minimum battery charge level so that there is a safety margin in the event that the weather conditions change, or the UAV is caused to take an indirect route between the UAV facility and the customer location, for example to avoid the path of another UAV on another flight. The UAV delivery network 100 will further comprise a plurality of fulfillment centers. For the sake of clarity, the fulfillment centers are not shown in Figure 2. A fulfillment center will be associated with one or more UAV facilities, such that orders from the fulfillment center are delivered from an associated UAV facility. A fulfillment center which is co-located with a UAV facility will be associated with that UAV facility such that the co-located UAV facility is typically used for deliveries. A fulfillment center which is not co located with a UAV facility may be associated with a single remote UAV facility, such that the single remote UAV facility is used for deliveries. In some cases, a fulfillment center may be associated with more than one remote UAV facilities. When the fulfillment center receives an order then one of the associated remote UAV facilities will be selected to deliver the order.

[0030] In use, the delivery network will operate with a number of UAVs, which will operate from the various UAV facilities. For example, the delivery network shown in Figure 2 may be operated with 12 UAVs, with 4 UAVs being assigned to each of the UAV facilities. A UAV is assigned to a UAV facility in order to meet demand for deliveries in the delivery area associated with the UAV facility. The utilization of each of the UAV facilities can be determined, as well as the utilization of each of the UAVs which have been assigned to each of the UAV facilities. If the utilization of a UAV facility falls below a first predetermined value then the UAV facility may be classified as being under-utilized. In such a case, action may be taken, such as, for example, re-locating one or more UAVs assigned to that UAV facility to a further UAV facility, deactivating the UAV facility or re-locating the UAV facility to a different location. Similarly, if the utilization of a UAV facility exceeds a second predetermined value then the UAV facility may be classified as being over-utilized. In such a case, action may be taken, such as, for example, allocating one or more further UAVs to the over-utilized UAV facility or activating a further UAV facility. If the utilization of a UAV falls below a third predetermined value then the UAV may be classified as being under-utilized. In such a case, action may be taken, such as, for example, deactivating the UAV or re-locating the UAV to a different UAV facility. Similarly, if the utilization of a UAV exceeds a fourth predetermined value then the UAV facility may be classified as being over-utilized. In such a case, action may be taken, such as, for example, allocating one or more further UAVs to the UAV facility to which the over-utilized UAV is assigned. The utilization of a UAV facility may be determined directly on the basis of operational data associated with the UAV facility, for example the number of UAV movements in a time period. Similarly, the utilization of a UAV may be determined directly on the basis of operational data associated with the UAV, for example the number of number of flights made in a time period. In addition to this, the utilization of a UAV facility or a UAV may be determined in part with data relating to customer demand, for example the number of customer requests received in a period of time, the number of customer requests received from a geographical area, the rate of received customer requests, the number of pending customer orders, etc. As will be seem from the following discussion, the assignment of a UAV to a UAV facility is dynamic and may change in response to the utilization of the UAV facilities and/or the UAVs. If the utilization of each of the first, second and third UAV facilities is roughly equal then the assignment of 4 UAVs to each UAV facility will be maintained.

[0031] In the event that the utilization of the second UAV facility 110B exceeds the second predetermined value, then it may be possible for one or more UAVs to be re-assigned. For example, one UAV may be reassigned from first UAV facility 110A to second UAV facility 110B. This re-assignment may be performed by flying the re-assigned UAV from the first UAV facility 110A to the second UAV facility 110B. However, this is an inefficient use of UAV resource as a flight is being made without any delivery being made. It is preferred that if there is a payload for delivery to a customer location in the intersection area 125 a then the delivery can be made by a UAV assigned to the first UAV facility 110A. Instead of retuming to the first UAV facility 110A after making the delivery, the UAV will proceed to the second UAV facility 110B and the UAV will then be reassigned to the second UAV facility. Subsequently, that UAV will operate from the second UAV facility, making deliveries to customer locations in the second delivery area. In a similar manner, a UAV may be re-assigned from the third UAV facility llOC to the second UAV facility 110B, with the re-assignment of the UAV involving a flight from the third UAV facility 1 IOC to a customer location in the intersection area 125b and thence to the second UAV facility 110B. In this example, a UAV facility may only be capable of supporting six UAVs and this will limit the number of UAVs which can be assigned to a UAV facility from other UAV facilities. The utilization of the first UAV facility 110A and the third UAV facility HOC may be used to determine which UAV facility will have one of its UAVs re-assigned to the second UAV facility 110B.

[0032] In addition to the re-assignment of UAVs, it should be understood that it is possible to make deliveries into the delivery area 120B associated with the second UAV facility 110B from either the first UAV facility 110A or the third UAV facility 1 IOC. In the event that customer orders are received from within the overlap delivery areas 125a, 125b or 125d then it will be understood that these orders can be fulfilled using a UAV which is assigned to the first UAV facility 110A or the second UAV facility HOC, as appropriate. Furthermore, a UAV from, for example, the first UAV facility 110A may make a delivery to a customer location in the overlap region 125a between delivery areas 120 A & 120B and then proceed to the second UAV facility HOB. Once the UAV has received a new payload, and received a new battery (if required), then the UAV may make a further delivery in the overlap region 125a before returning to the first UAV facility 110A to continue operating as a UVA assigned to the first UAV facility, delivering payloads to customers in the first delivery area 120A.

[0033] It should be understood that overall demand and the pattern of demand for the delivery network will change during the day and that the utilization of the UAV facilities and UAVs will vary accordingly. For example, if the second delivery area 120B covers a commercial or business area and the first delivery area 120A covers a residential area then it will be understood that it is likely that demand will change as people move from the residential area into the commercial or business area at the start of the working day. This will lead to an increase in demand for deliveries in the second delivery area, which may lead to one or more UAVs being reassigned to the second UAV facility as described above.

[0034] It is also likely that this process will be reversed at the end of the working day as people return home from work. The process which is described above with respect to meeting increased demand for the delivery network in delivery area 120B during working hours is likely to be reversed, such that each of the UAVs that were re-assigned to the second UAV facility will be re-assigned back to the first or third UAV facilities as the utilization of the second UAV facility decreases , such that each of the UAV facilities 110A, 110B & HOC are operating with 4 UAVs assigned to them. If a further decrease in the utilization of the second UAV facility were to be followed by a further increase in the utilization of the first UAV facility then more UAVs could be assigned to the first UAV facility, from either the second UAV facility and/or the third UAV facility. As discussed above, each of the UAV facilities will have a maximum number of UAVs which can be operated from the facility. This will impose a limit on the number of orders that can be delivered to a particular delivery area within a given period of time from a single UAV facility.

[0035] Figure 3 shows a schematic depiction of the delivery network 100 described above with reference to Figure 2 after the network has been re-configured into a second configuration. In this example, due to low utilization of the third UAV facility HOC, the third UAV facility has been temporarily deactivated and is then moved to a new location. This new location may be next to a fulfillment center which was not previously co-located with a UAV facility. This may be due to the fulfillment center not being operational or not operating at a level of demand that would justify the co-location of a UAV facility. The third UAV facility is then reactivated such that the delivery network now comprises first UAV facility 110A, second UAV facility HOB and third UAV facility HOC’. Again, each of the UAV facilities is associated with a respective delivery area 120A, 120B, 120C’. Due to the new location of the third UAV facility 1 IOC’ , there is no longer an overlap between the second delivery area 120B and the third delivery area 120C’. Also, the new location of the third UAV facility HOC’ is such that there is a relatively large overlap 125c between the first delivery area and the third delivery area (that is the overlap 125c between the first delivery area and the third delivery area is significantly greater than the overlap 125a between the first delivery area and the second delivery area). Such a reconfiguration of the delivery network increases the proportion of the first delivery area which can be served from UAVs which are assigned to the third UAV facility, thereby increasing the number of deliveries that can be made in a given period of time to the first delivery area 120A. The relocation of the third UAV facility 1 IOC’ may cause one or more fulfillment centers to associate with the third UAV facility HOC’, for example if third UAV facility HOC’ is now located closer to a particular fulfillment center. Similarly, if the third UAV facility 1 IOC’ is moved away from a fulfillment center then the fulfillment center may terminate its association with the third UAV facility 1 IOC’ and form an association with a further remote UAV facility. [0036] When the delivery network is re-configured as described above with reference to Figures 2 & 3, the fulfillment centers will re-assess the UAV facilities with which they are associated. For example, if the re-configuration of the delivery network causes a UAV facility to be moved away from an associated fulfillment center then that association may be discarded, for example if the distance between the UAV facility and the fulfillment center exceeds a pre determined value. Alternatively, if the re-configuration of the delivery network causes a UAV facility to move such that it is within a pre-determined distance of a fulfillment center then the UAV facility may be associated with that fulfillment center. It should be understood that the number of associated UAV facilities may vary as the network is reconfigured. If a fulfillment center is associated with a further UAV facility due to the re-location of that facility then the fulfillment center may terminate the association with one of the UAV facilities with which it was previously associated. This decision may be made in accordance with one or more parameter, for example the distance between the UAV facility and the fulfillment center, or the location of the UAV facility relative to the fulfillment center.

[0037] Figure 4 shows a schematic depiction of the delivery network 100 described above with reference to Figure 2 after the network has been re-configured into a third configuration. In this example, due to low utilization of the third UAV facility HOC, the third UAV facility has been temporarily deactivated and is then moved to the fulfillment center which is co-located with the first UAV facility. The third UAV facility is then reactivated such that the delivery network now comprises first UAV facility 110A, second UAV facility 110B and third UAV facility llOC”. Again, each of the UAV facilities is associated with a respective delivery area 120A, 120B, 120C”. Due to the new location of the third UAV facility HOC”, there is no longer an overlap between the second delivery area 120B and the third delivery area 120C’ and the first delivery area 120A and the third delivery area 120C” are effectively coterminous. The combined first and third delivery areas are now having orders delivered from the first and third UAV facilities and this provides a further increase in the delivery capacity that is made available. Furthermore, it will be possible to make deliveries in respect of orders from the overlap area 125e between the first/third delivery area and the second delivery area using UAVs which are assigned to the second UAV facility. For the sake of clarity, Figure 4 shows the first and third UAV facilities being located next to each other. In operation, the first and third delivery areas will be essentially identical.

[0038] It will be understood that in the examples described above with respect to Figures 3 & 4 only the third UAV facility was moved in response to customer demand in order to provide greater delivery capacity in high demand areas. It should be understood that it would be also be possible to move the second UAV facility to a different location if that would provide increased delivery capacity in response to customer demand. It will be understood that a real life delivery network is likely to comprise a large number of UAV facilities and the above methods may be applied as needed. Furthermore, it may be possible to increase delivery capacity in particular areas of the network by having UAV facilities which are deactivated during periods of low utilization but are then activated in response to demand rising above a predetermined threshold value. For example, some UAV facilities may be located in areas which will experience significant demand only at certain times and the UAV facilities will be active for those times. At other times, that is when demand is low and the utilization of those UAV facilities falls below the first predetermined value, those UAV facilities will be inactive. A delivery network such as that described above can be re-configured through a combination of UAV facility activation, deactivation or re-location and/or through the re-assignment of UAVs between different UAV facilities.

[0039] The delivery network may also be reconfigured in response to other triggers. For example, a UAV may develop a fault and need to be taken out of service. If a fault is detected whilst in flight then the UAV may re-route to the nearest UAV facility such that it can land safely. A message may be sent to the nearest UAV facility, for example via a flight management system (see below), which prompts the UAV facility to prepare for the arrival of the UAV such that the UAV can land safely and then be stored such that maintenance or repair processes can be scheduled. A technician may be able to repair the UAV at the UAV facility or it may need to be retrieved and taken to a repair facility. If one or more UAVs are inoperable due to fault conditions then it may be necessary to re-assign one or more UAVs to different UAV facilities in order to meet demand at those UAV facilities. As UAVs are repaired and returned to the delivery network, or as further UAVs are activated to replace inoperable UAVs then these UAVs are assigned to UAV facilities in accordance with customer demand and UAV facility capacity.

[0040] It will be understood that a UAV facility may develop a fault such that it is no longer operable to receive and/or launch UAVs, for example due to a power outage or the failure of a component or system. In such a case, the UAV facility can be removed from the network until the fault is remedied. If a UAV facility becomes inoperable due to a fault then the fulfillment centers which had an association with that UAV facility will terminate the association. Those fulfillment centers may then attempt to make associations with other remote UAV facilities. UAVs which had been routed to fly to the inoperable UAV facility can be re routed to a further UAV facility. These re-routed UAVs can then be re-assigned to UAV facilities in accordance with customer demand. Any UAVs which are located at the inoperable UAV facility will be deactivated such that deliveries are not assigned to them. Once the UAV facility is restored to operational capability then these UAVs may be reactivated such that they can be used to make deliveries. When a UAV facility is restored to operational capability then one or more fulfillment centers may associate with the UAV facility.

[0041] The preceding discussion assumed that each UAV facility had the capacity to operate with 6 UAVs and that normally 4 UAVs would be assigned to each of the UAV facilities. It will be understood that UAV facilities may be provided that have the capacity to operate with a greater (or a lesser) number of UAVs. For example, a larger UAV facility, that is one which is able to operate with a greater number of UAVs, may be associated with a fulfillment center which frequently experiences greater demand than other fulfillment centers in the delivery network. Alternatively, a high demand fulfillment center may be associated with multiple UAV facilities which can then be operated as a single, high capacity UAV facility. As described above with reference to Figures 3 and 4, UAV facilities may be deactivated and moved to different locations if the re-location of the UAV facility would lead to more efficient operation of the network.

[0042] Similarly, the number of UAVs assigned to each facility may be varied. UAV facilities which frequently experience greater demand than other UAV facilities may have a greater number of UAVs assigned to them. This may be achieved by adding further UAVs to the delivery network or by re-assigning UAVs which were previously assigned to UAV facilities which frequently experience lower demand levels. It is unlikely to be effective to provide each of the UAV facilities with the maximum number of UAVs that they can operate with, unless all of the UAV facilities are always operating under high demand conditions. In normal situations it is likely that there will be periods of low and high demand and these variations in demand can be managed in an efficient manner by re-assigning UAVs from UAV facilities with low demand to UAV facilities with high demand and then making further re assignments of UAVs as demand patterns change. If a UAV facility is frequently operating at the maximum UAV capacity then this may be used as an indicator that the UAV facility capacity should be expanded, for example by providing an additional UAV facility at that location or by upgrading the UAV facility to one with a greater capacity. In a similar manner, if a UAV facility is frequently operating with a low number of UAVs then this may indicate that the UAV facility is not being operated in an efficient manner. In such a case, historic demand data can be analyzed to determine a location which would enable the UAV facility to be operated more efficiently. [0043] It should be understood that different types of UA V s may be used in the delivery network. For example, one type of UAV may be provided which has a longer range compared to other UAVs, may be able to deliver a heavier or larger payload than other UAVs or may have a greater maximum flying speed than other UAVs. Such UAV characteristics may limit the type of orders which can be delivered by one type of UAV or make one type of UAV a preferred candidate for delivering certain types of order. If, for example, there is a high demand for orders at one UAV facility which require a UAV which is capable of delivering a heavy payload then UAVs of that type may be re-assigned to that particular UAV facility. If the increased demand is only in respect of heavy payload orders then the UAVs which were previously assigned to that UAV facility which were not suited to heavy payload delivery may be re-assigned to other UAV facilities such that those UAVs can be used to make general deliveries from their re-assigned UAV facility.

[0044] Referring to the delivery network shown in Figure 2, consider that the first UAV facility is located such that it serves both a takeaway food store and a pharmacy. Assume that each of the UAV facilities 110A, 110B, HOC can operate with a maximum of six UAVs and that in normal operations each of the UAV facilities is assigned two regular UAVs and two high capacity UAVs, which can deliver a payload which is larger and heavier than that which can be carried by a regular UAV. Assume that the pharmacy is operating from 8.00 am to 8.00 pm and that the takeaway food store operates from 11.00 to midnight. It will be understood that the typical delivery payload from the pharmacy, for example a prescription for a box of tablets, is likely to be smaller and lighter than the typical delivery payload from the takeaway food store, for example, a burger, a pizza and a bottle of drink. In the morning, if there is demand for deliveries from the third UAV facility that require a high capacity UAV then a high capacity UAV may be re-assigned from the first UAV facility to the third UAV facility. In return, a regular UAV can be re-assigned from the third UAV facility to the first UAV facility such that deliveries can be made from the pharmacy located with the first UAV facility. When the takeaway food store opens it may be possible for the first UAV facility to operate efficiently with only one high capacity UAV and three normal UAVs. In the event that efficient operation is not possible with this configuration then a second high capacity UAV may be assigned to the first UAV facility. This may be the high capacity UAV which was previously re-assigned from the first UAV facility to the third UAV facility. Alternatively, a high capacity UAV may be assigned to the first UAV facility from the second UAV facility (or a further UAV facility which is not shown in Figure 2). Again, one of the regular UAVs assigned to the first UAV facility may be re-assigned if it is needed to meet order demand at a further UAV facility. [0045] As the demand for deliveries from the takeaway food store increases relative to the demand for deliveries from the pharmacy, and in particular past 8.00 pm when the pharmacy closes, then further high capacity UAVs may be assigned to the first UAV facility in order to be able to fulfil delivery demands. Again, one or more regular UAVs may be re assigned to further UAV facilities in order to meet demands for orders from those UAV facilities. Furthermore, as the first UAV facility is only able to operate with a maximum of six UAVs, then if there is a high demand for orders which require a high capacity UAV then it would be efficient for the first UAV facility to operate with as many high capacity UAVs as are available for re-assignment. It should be realized that the re-assignment of UAVs to a UAV facility may be made on the basis of the number of UAVs required at a particular UAV facility, the type of UAVs required at a particular UAV facility or a combination of the two factors. It should be understood that more than two types of UAV may be operated in a particular delivery network and that the different types may be differentiated by one or more different characteristics, for example, payload size, payload weight, UAV speed, UAV range, etc.

[0046] Customer demand may be determined from the number of orders which are received within a given delivery area, or the number of orders which are received within a predetermined period of time. Demand may alternatively be determined on the basis of how many orders are waiting to be fulfilled and sent out for delivery. If the number of pending orders is increasing then that is an indication that demand is increasing and that some action should be taken to address the situation. Similarly, the time taken to deliver an order may indicate that demand is increasing and that it may be appropriate to allocate further delivery resources, such as reassigning UAVs and/or UAV facilities to increase delivery capacity in delivery areas of high demand.

[0047] In an alternative, rather than operating in a reactive manner and allocating delivery resource based on demand, it may be possible to predict customer demand and allocate delivery resources accordingly. By examining historical customer demand data, it is possible to identify trends in customer demand such that times and locations of high customer demand can be detected. Such analysis may be undertaken by human analysts or the customer demand data may be analyzed using machine learning techniques to determine periods of high and low demand. In particular, the present demand figure may be used to predict the likely demand in the near future, for example 5-15 minutes in the future, and the predicted future demand used when determining how much delivery capacity should be provided in each of the delivery areas.

[0048] Figure 5 shows a schematic depiction of a UAV delivery network 100’ which comprises first UAV facility 110A, a second UAV facility 110B and a third UAV facility 1 IOC with respective first, second and third delivery areas 120 A, 120B, 120C. It can be seen that as the respective delivery areas overlap with each other then there will be a number of areas 125 a, 125b, 125c which can be served from two different UAV facilities. There is also one area 125d which can be served from all three of the UAV facilities. Co-located with each of the UAV facilities 110A, 110B, 1 IOC are a respective fulfillment center 115A, 115B, 115C. Each of the UAV facilities 110A, 110B, HOC are in communication with a flight management system (FMS) 200 which collects data from each of the UAV facilities and also transmits data to each of the UAV facilities regarding UAV flight activity and other data which is relevant to the operation of the delivery network and the respective UAV facility. Also shown in Figure 5 are first customer location 300A and second customer location 300B. The first customer location 300 A is in the overlap area 125 a between the first delivery area 120 A and the second delivery area 120B. The second customer location is in the overlap area 125d between the first, second and third delivery areas 120A, 120B, 120C. Figure 5 is a schematic depiction of the delivery network 100’ and is not to scale but the nearest UAV facility to the first customer location is the second UAV facility 110B and the nearest UAV facility to the second customer location is the third UAV facility HOC.

[0049] The delivery network described above with reference to Figures 2 to 4 shows each of the delivery areas as being circular. This means that the UAVs are substantially unaffected by the weather conditions whilst making delivery flights. It should be understood that this is an unrealistic assumption as weather conditions, and particularly wind conditions, will have an effect on the UAVs when they are in flight. This is shown schematically in Figure 5, which shows each of the delivery areas as having an elliptical shape. Each of the UAV facilities has a weather station which measures, amongst other parameters, the windspeed at the UAV facility. The windspeed reported to the FMS from each UAV facility can be used to generate an estimate of the windspeed across the delivery network. The data reported by the UAV facilities can be augmented with meteorological data supplied by a third-party in order to generate a more accurate determination of windspeed and weather conditions across the whole of the UAV delivery network. This data can then be used to estimate the delivery area associated with each of the UAV facilities. It will be understood that for a small delivery network, such as that shown in Figure 5, then there is a reasonable prospect that each of the delivery areas will have substantially the same shape and/or size. However, for larger delivery networks, which comprise a larger number of UAV facilities, it is less likely that the weather conditions will be similar for all of the delivery areas and thus it is more likely that the delivery areas will have different shapes and/or sizes. It will be understood that the topology and geography of the delivery areas is likely to have an effect on the shape and/or size of the delivery areas. The delivery network may be reconfigured in response to measured or predicted weather conditions, for example by activating further UAV facilities in order to provide sufficient delivery capacity in particular areas or by re-locating one or more active UAV facilities in order to provide sufficient delivery capacity.

[0050] Figure 5 also shows a further fulfillment center 115D. Fulfillment center 115D is located within the delivery area 120C but it is not co-located with the third UAV facility llOC. However, fulfillment center 115D is associated with the third UAV facility HOC such that in normal operation of the UAV delivery network 100’ orders which are placed with fulfillment center 115D will be delivered using the third UAV facility HOC. If the third UAV facility HOC were to become inoperable then fulfillment center 115D would need to form an association with one or more further UAV facilities. For example, fulfillment center 115D may form an association with the second UAV facility HOB as this is the UAV facility which is closest to fulfillment center 115D. However, if the time required to transfer an order from fulfillment center 115D to the first UAV facility 110A is less than the time required to transfer an order from fulfillment center 115D to the second UAV facility HOB then the fulfillment center 115D may be associated with the first UAV facility 110A.

[0051] In a further alternative, it is possible for a fulfillment center to be associated with more than one UAV facility. Thus, in the event that the third UAV facility HOC were to become inoperable then the fulfillment center 115D could be associated with both the first UAV facility 110A and the second UAV facility HOB. When an order is received at the fulfillment center 115D then one of the associated UAV facilities will be selected such that it is used in the delivery of the order. For example, if the order is received from a customer location in the first delivery area 120 A then the first UAV facility 110A will be selected (and similarly, if the order is received from a customer location in the second delivery area 120B then the second UAV facility HOB will be selected). If the customer location is in the overlap area 125a then either of the associated UAV facilities may be selected. The fulfillment center 115D may select one of the associated UAV facilities on the basis of the predicted time to deliver the order to the customer (see below), how busy each of the associated UAV facilities are, or on the basis of one or more other factors.

[0052] Consider for the sake of the following discussion that each of the fulfillment centers are restaurants operated by the same organization, which use the UAV facilities to deliver food and beverages to customers. Figure 6 shows a schematic depiction of a communications network 400 which can be used to enable the placing, fulfillment and delivery of an order. A customer terminal 310 can be used to access a customer-facing server 410 operated by, or on behalf of, the restaurant operator. The customer- facing server 410 is in communication with the FMS 200 operated by the operator of the UAV delivery network and with a plurality of fulfillment center servers 430A, 430B, 430C, 430D which are located at respective fulfillment centers 115A, 115B, 115C, 115D. In operation, the customer-facing server is able to receive data from the FMS regarding the number and type of UAVs which are assigned to each of the UAV facilities in the delivery network. The customer-facing server also receives data regarding how many UAVs are currently available to receive a payload for delivery, the time at which UAVs which are currently undertaking a delivery will return to a UAV facility, the time at which those UAVs which are currently undertaking a delivery will next be available for a further delivery, and other data parameters regarding the UAV fleet and its operational performance. All of the data may be supplied directly to the customer-facing server by the FMS or the FMS may provide a subset of the data and the customer- facing server will then generate the rest of the data on the basis of the information provided by the FMS. The customer-facing server further receives data from each of the fulfillment center servers: this data will comprise data regarding stock levels at each of the fulfillment centers, staffing levels and number of orders received and being processed by each of the fulfillment centers.

[0053] The customer-facing server 410 may comprise one or more central processing units (CPUs) 412, random access memory (RAM) 414, read only memory (ROM) 416 and non-volatile data storage 418, which may comprise hard disk drives, solid state drives, a mixture of disk drives and solid state drives or other conventional data storage technology. The non-volatile data storage will store operating system computer code 420 and one or more computer programs 422 which are used to control the operation of the customer-facing server and its interactions with the FMS, the fulfillment center servers and any other network entities. The operation of the customer- facing server may be modified or augmented by the modification of the one or more computer programs 422 held within the non-volatile data storage. The non volatile data storage will also store operational data 424 which is generated by the customer facing server or which is received from the FMS, the fulfillment center servers or other entities connected to the network. The one or more CPUs, ROM, RAM and the non-volatile data storage are in communication with each other such that data may be exchanged between the different components such that the one or more computer programs can process the operational data in the manner set out in the present disclosure. Each of the plurality of fulfillment center servers 430A, 430B, 430C shown in Figure 6 may comprise the same components as those described above with reference to the customer-facing server 410 but for the sake of clarity those components are not shown in Figure 6.

[0054] It will be understood that in an alternative to implementing the customer- facing server and the plurality of fulfillment center servers using conventional computer server hardware, as described above, some or all of the server-based functionality may be implemented using network-based computing resources, often referred to as cloud-based computing. In such a case, network-based CPU, memory and data storage resources are activated and used as necessary to implement the customer-facing server and/or the fulfillment center servers. Cloud-based computing resources may be used as a back-up resource in the event of hardware failure for one or more servers or may be used to augment the customer facing server and/or the fulfillment center servers in the event that the demand for the customer facing server and/or the fulfillment center servers exceeds the capacity of the installed servers. It will be understood that the exact nature of the underlying server technology is not relevant to the present disclosure.

[0055] In use, the customer terminal will initiate a communications session with the customer-facing server 410. The customer will examine the menu, select the required food and beverage items and then pay for the order. The customer-facing server will then use the data received from the FMS and the plurality of fulfillment center servers to determine which of the fulfillment centers will be used to fulfill and deliver the order to the customer. Referring to Figure 5, if the customer order was made from the first customer location 300A then it can be seen that the customer location is in the first and second delivery areas and thus the delivery may be made from either the first or second UAV facility. As the first customer location is closer to the second UAV facility than the first UAV facility then it might be assumed that the delivery is made from the second UAV facility. However, using the second fulfillment center and the second UAV facility to fulfill and deliver the order may not be the fastest way to deliver the order to the customer.

[0056] When the customer order is received at the customer-facing server, the customer-facing server can determine the most appropriate fulfillment centers to which the order can be allocated for fulfillment. This process will now be explained with reference to Figure 7, which shows a graphical depiction of a flowchart describing the order allocation process. At step S700, the customer-facing server will determine which of the fulfillment centers can be used to fulfill the customer order. The customer location may be determined by the customer terminal, which may be a smartphone or similar device, for example, reporting its location to the customer-facing server. Alternatively, the customer may have successfully logged into an account maintained by the customer-facing server such that an address for the customer is provided as a part of setting up the account.

[0057] If an order is received from a customer location that is outside of the area covered by the UAV delivery network then the customer facing server will terminate the process described above with reference to Figure 7 at step S700 as there are no valid fulfillment centers for that customer location. An alternative process may be initiated, which allows the customer to place their order such that the customer collects the order from the fulfillment center which is nearest to the customer or that the order is delivered using an alternative delivery mechanism.

[0058] If the customer location is outside of the one of the overlap areas 125 shown in Figure 5 then the customer can only be supplied by a single fulfillment center. In such a case, the process will be terminated with the order being allocated to the only fulfillment center which is identified in step S700.

[0059] If, for example, the order came from the first customer location then the order can be fulfilled by either the first fulfillment center 115 A or the second fulfillment center 115B : in this case both of the two valid fulfillment centers are passed on to step S710. At step S710, the customer-facing server will determine which of the valid fulfillment centers are able to fulfill the order. For example, if the customer order requires an ingredient which is temporarily unavailable at one of the fulfillment centers then that fulfillment center will not be able to fulfill the customer order. The customer-facing server will select each of the fulfillment centers which are able to fulfill the customer order and the selected fulfillment centers will be passed on to step S720. If there is only one fulfillment center which is capable of fulfilling the customer order then the process will be terminated and the order will be allocated to the only valid fulfillment center which is capable of fulfilling the customer order.

[0060] At step S720 the UAV facility to be used is determined for each of the fulfillment centers selected in step 710. A fulfillment center which is co-located with a UAV facility will use the co-located UAV facility. A fulfillment center which is associated with a single remote UAV facility will use that remote UAV facility. If a fulfillment center is associated with more than one remote UAV facilities then one of these remote UAV facilities will be selected. The fulfillment center may select the associated remote UAV facility which is nearest to the fulfillment center, either by distance or by time taken to travel from the fulfillment center to the remote UAV facility. The remote UAV facility may be selected in accordance with other criteria, for example the remote UAV facility which is closest to the customer location. [0061] At step S730 the order process time will be determined for each of the fulfillment centers which were selected in S710. The order process time comprises three different factors: the order fulfillment time (determined at S732), the order loading time (determined at S734) and the order delivery time (determined at S736). The order fulfillment time is the time taken by a fulfillment center to prepare and cook the order such that the food and beverage which comprise the order are received in a package which can be carried by a UAV. The order loading time is the time taken for the package to be inserted into an insertion port received within the UAV facility associated with the fulfillment center and for the package to be attached to a UAV. The order delivery time is the time taken for the UAV to take off from the UAV facility, fly to the customer location and deliver the customer order to the customer.

[0062] Referring once again to Figure 5, under normal conditions it is to be expected that the order fulfillment time for each of the restaurants would be similar as each kitchen will be similarly equipped and will be operated by a similar number of staff who have been trained in the same way. However, it should be appreciated that one restaurant may be experiencing greater demand for orders than other restaurants, for example due to orders for table service, and thus will have a higher order fulfillment time than the restaurants which are experiencing lower levels of demand. The order fulfillment time for each of the selected fulfillment center can be determined based on the expected time taken to prepare the order and the current demand at that fulfillment center. If a fulfillment center is co-located with a UAV facility then the time required to move the packaged order from the fulfillment center to the UAV facility will be minimal and may be disregarded when determining the order fulfillment time. However, for a fulfillment center which is associated with a remote UAV facility the time required to transport the packaged order from the fulfillment center to the remote UAV facility will need to be determined and then included within the order fulfillment time.

[0063] When a customer order is received at the customer-facing server the customer facing server can search data received from the FMS to determine the UAVs which are located at the UAV facilities which are associated with the two or more selected fulfillment centers. The FMS data will also indicate the type of UAV which are present at those UAV facilities. If the size and/or the weight of the customer order means that a UAV having particular characteristics are required to deliver the customer order to the customer location then that requirement can be used when searching for available UAVs.

[0064] If a suitable UAV is available at one or more of the UAV facilities associated with the selected fulfillment centers and it is ready to have a payload comprising the customer order attached then the UAV can be reserved for potential use and the loading time can be determined, based on the typical time required to attach the payload to the UAV. If a suitable UAV is present at one or more of the UAV facilities associated with the selected fulfillment centers but the UAV is not currently ready for use, for example, it is undergoing a battery change, then the order loading time can be determined, for example based on acquired knowledge regarding the typical time required to perform a battery change and then the time that would be required to attach the payload to the UAV. The UAV can be reserved for potential use. If there is no suitable UAV at a UAV facility associated with a selected fulfillment center then the customer-facing server can determine from the data received from the FMS the location of other suitable UAVs within the delivery network. The customer-facing server can then determine the time that it would take for those UAVs to undertake a repositioning flight (or flights) to reach the UAV facility and then be ready for a delivery flight. The UAV which can be re-positioned to the UAV facility in question in the least amount of time will be reserved for potential use. The order loading time can then be determined based on the time required to re-position a suitable UAV, to prepare the UAV for a further flight and to attach the payload to the UAV.

[0065] The order delivery time can be determined by calculating the typical flight time for each of the reserved UAVs from the respective UAV facility from where the delivery flight will begin to the customer location. Referring to Figure 5, it can be seen that the first customer location 300A is to the east of the first UAV facility and to the west of the second UAV facility. If there is a strong wind blowing from west to east then even though the second UAV facility is nearest to the first customer location it may be quicker to fly a UAV from the first UAV facility to the first customer location as it will have a tailwind whereas a UAV flying from the second UAV facility to the first customer location will have to fly into a headwind.

[0066] The order process time can be determined for each of the selected fulfillment centers on the basis of the respective order fulfillment time, order loading time and the order delivery time. The customer order will be allocated at step S730 to the fulfillment center which has the shortest order process time. Once the order has been allocated to the fulfillment center having the shortest order process time then the order will be produced, packaged, loaded onto a UAV and then delivered to the customer. It will be understood that the UAVs which were reserved for potential use but which were not needed will be released such that they can be used for other operations.

[0067] Referring to Figure 5, it can be seen that the first customer location 300A can be served from either the first fulfillment center 115A or the second fulfillment center 115B. Although the first customer location is closer to the second fulfillment center 115B than the first fulfillment center 115 A it will be understood that the order will be fulfilled by the fulfillment center which will be able to deliver the order to the first customer location the soonest, considering each of the activity level of each fulfillment center, the related UAV facility and the weather conditions. Similarly, the second customer location 300B is in overlap region 125d such that it can be served by the first fulfillment center 115A, the second fulfillment center 115B or the third fulfillment center 115C. Again, the delivery will be made from the fulfillment center which make the quickest delivery to the second customer location.

[0068] It should be understood that the order process time is not necessarily determined simply by adding together the order fulfillment time, the order loading time and the order delivery time. It will be understood that the order fulfillment operation and the order delivery operation must be performed in series and thus the order process time can never be less than the sum of the order fulfillment time and the order delivery time. If the order loading time is greater than the order fulfillment time then the order process time will be the sum of the order loading time and the order delivery time. If the order loading time is greater than the order fulfillment time then the order fulfillment operations may be delayed such that the order is fulfilled at substantially the same time as the UAV is ready for loading. Such a delay means that a food order, for example, can be delivered to the customer without any delays caused by waiting for an available UAV. It should be understood that the time required to fulfil and deliver each order will be determined in accordance with a number of different factors, such as the nature of the order, the demand for the fulfillment centers to which the order could be assigned, the demand for the UAV facilities associated with those fulfillment centers, the status of the UAVs assigned to the respective UAV facilities, etc.

[0069] Consider an exemplary order for which the order fulfillment time is 20 minutes, the order loading time is 15 minutes and the order delivery time is 10 minutes. In such a case, the order fulfillment time is the time taken to prepare and cook the requested items. The order loading time may be the time required to fly a suitable UAV from a further UAV facility to the UAV facility located with the fulfillment center to which the order is allocated, the time to swap a fully charged battery into the UAV and then the time for the UAV to be moved into a position such that it can receive the order as a payload. In this case, because the order loading time is less than the order fulfillment time it is possible that the reserved UAV is in position to receive the order as soon as the order is prepared because the order fulfillment operation and the order loading operation can be executed simultaneously. Thus, the order process time is only 30 minutes, that is the sum of order fulfillment time and the order delivery time. However, for a further exemplary order, if the order fulfillment time is 10 minutes, the order loading time is 15 minutes and the order delivery time is 10 minutes then it can be seen that the order process time will be 25 minutes, that is the 15 minutes required to have the UAV located at the respective UAV facility in a condition ready to deliver the order and 10 minutes to deliver the order. In this case, as the order fulfillment time is less than the order loading time then the actual value of the order fulfillment time does not affect the order process time.

[0070] If the customer order is for food items then it will be understood that it is important that the order is delivered as soon as possible. Thus, for a UAV facility which is co located with a restaurant and a pharmacy, for example, then food orders from the restaurant may be prioritized over pharmacy orders such that the food orders are delivered sooner. For example, if a UAV has been reserved for use for delivering a pharmacy order then that reservation may be overridden if there is an order for a food delivery that requires the use of a UAV. Similarly, if the UAV facility is used for the scheduled delivery of parcels, for example for the delivery of online shopping orders, then the customer facing server can make food orders a higher priority than scheduled deliveries, subject to the constraint that the packages must be delivered within a pre-determined time period.

[0071] If one of the fulfillment centers is experiencing significant demands for orders, for example for table service orders at a restaurant, then the customer facing server may temporarily place a block on that fulfillment center for the placing of orders for UAV delivery as the time to deliver a fulfilled order will be too great. In such a case, one or more of the UAVs assigned to the associated UAV facility may be re-assigned to further UAV facilities such that they can be utilized by other fulfillment centers. Once the temporary block for that fulfillment center is removed or expired then those UAVs can be re-assigned back to the UAV facility associated with the fulfillment center in accordance with the demand for UAV deliveries.

[0072] Similarly, if a UAV facility becomes too busy and it is not possible to increase capacity by assigning further UAVs to that facility then the customer facing server may temporarily place a block on that UAV facility such that no further orders are allocated to the fulfillment centers associated with the UAV facility. Once the activity of the UAV facility has decreased below a threshold value then the block may be removed such that further orders can be delivered via that UAV facility. If customer demand means that the time taken to fulfil and deliver an order exceeds a pre-determined threshold value, for example an hour, then the customer order may be refused. It should be understood that the pre-determined threshold value may be varied in accordance with customer expectation or the nature of the goods being ordered.

[0073] It will be understood that other the method described above with reference to Figure 7 can be used with fulfillment centers other than restaurants. For example, if the fulfillment center is a pharmacy then the order fulfillment time will be the time taken for the prescription to be prepared and checked. A pharmacy will be selected in step S710 as a valid fulfillment center if the requested items are held in stock by the pharmacy. If the fulfillment center is a vending machine then the order fulfillment time can be assumed to be zero as order fulfillment will involve the dispensing of the requested item(s). A vending machine will be selected in step S710 as a valid fulfillment center if the requested items are stocked in the vending machine.

[0074] It can be seen that the customer can have their order delivered as soon as is possible without needing to know which of the fulfillment centers is nearest to their home or most likely to produce their order quickly. The present method allows demand to be spread around multiple fulfillment centers, mitigating the risk that one fulfillment center is overloaded with orders whilst other fulfillment centers are operating significantly below capacity. The method also allocates orders to fulfillment centers in accordance with the ability of co-located UAV facilities to deliver the fulfilled orders. It will be understood that the UAV delivery network can be reconfigured as discussed above in order to provide additional delivery capacity in those areas of the UAV delivery network which are experiencing the greatest demand. It should be understood that this may include the re-assignment of UAVs and/or the relocation of UAV facilities.

[0075] A customer may also place an order which is scheduled to be delivered at a particular time and/or date in the future. If the order is valid, for example the order is not scheduled for a time when the required fulfillment center is closed, then the order will be accepted. If there is only one fulfillment center which is capable of fulfilling the order then it is still necessary to determine the order process time as this will be needed such that the delivery can be made at the scheduled time. For example, if the customer order is scheduled for delivery at 7.30 and the order process time is 20 minutes then the fulfillment center will need to start preparing the order at 7.10. When determining the order process time it will be necessary to estimate the order fulfillment time, loading time and delivery time. These estimations may be based on typical activity levels for the respective fulfillment centers for the time and/or day for which the delivery is scheduled. If there are multiple valid fulfillment centers which are capable of fulfilling the order then the order can be allocated to the fulfillment center which has the shortest order process time. The order will be scheduled such that the order is delivered at the requested time, with a UAV being reserved such that it is ready to deliver to the customer at the appropriate time. The order may be re-evaluated periodically and re-scheduled if this will be necessary to enable the delivery to be made on time. For example, if an increase in activity at the fulfillment center means that the order fulfillment time is likely to be greater than was predicted then the order may be re-scheduled such that the fulfillment center starts preparing the order at an earlier time. Similarly, if the associated UAV facility is less busy than normal such that the order loading time is likely to be less than predicted then the order may be re-scheduled such that the fulfillment center starts preparing the order at a later time.

[0076] Figure 8 shows a graphical depiction of a method according to a further aspect of the present disclosure. When a customer is placing an order via the customer facing server, this will conventionally be performed by adding one or more items sequentially to a shopping basket or cart. Referring to Figure 8, an item which will comprise a customer order is placed in the shopping basket at step S800. Once the item has been received in the basket, a part of the process described above with reference to Figure 7 will be performed by the customer facing server. The customer facing server will access data held by the FMS and the plurality of fulfillment center servers to determine the order process time for each of the valid fulfillment servers which can fulfill the order. The lowest order process time can then be shown to the customer via the screen of the customer terminal as the customer builds the order via an update to the order basket screen (S810). This allows the customer to see the predicted delivery time for the requested items before they place the order.

[0077] The customer may then add a further item to the order basket, returning to S800 from S810, which will cause the customer facing server to determine the new lowest order process time for the items held in the order basket. It should be noted that depending upon the ordered item and the state of the fulfillment centers and UAV facilities which comprise the UAV delivery network, the selection of a new item may cause a different fulfillment center to have the lowest order process time. The customer will continue to build their order by adding further items at S800 and each time an item is added to (or deleted from) the order basket then the lowest order process time will be re-evaluated and displayed to the customer at S 810. When the customer has finished building their order then at S820 they can place their order knowing the predicted delivery time for the order. After the order has been placed, some form of countdown or timer can be displayed to the customer. The countdown may be updated if there is a significant deviation between the predicted time for fulfilling, loading or delivering an order and the actual time required for fulfilling, loading or delivering an order. Once the order has been loaded onto a UAV the progress of the UAV between the UAV facility and the customer premises may be displayed and periodically updated to the customer using a graphical display, for example the route taken by the UAV and the planned route of the UAV, overlaid on a map. The customer may also be provided with notifications of the progress of the order, for example the start of the order preparation, order completion, order loaded on a UAV, etc., such that the customer is informed of the progress of the order.

[0078] In a variant of the present disclosure, if a customer orders, for example, a pizza which can be delivered from a number of different restaurants then the customer may be presented with a graphical display of the different restaurants which are capable of order fulfillment and delivery, along with the predicted delivery time for each of the different restaurants. The customer may then select the restaurant which will fulfill the order. After the order has been placed, some form of countdown or timer can be displayed to the customer, which may be updated if there is a significant deviation between the predicted time and the actual time required for fulfilling, loading or delivering an order. Again, the customer may be provided with notifications regarding the progress of the order and a graphical depiction of the route and progress of the UAV may be provided.

[0079] Referring again to Figure 2, it will be understood that the UAV facilities of the UAV delivery network may comprise different types of UAVs. In particular, the UAV facilities may comprise one or more emergency UAVs. An emergency UAV is a UAV which has a payload which comprises medical supplies and equipment such that the emergency UAV can be deployed to the site of an accident or medical emergency. Such an emergency UAV is described in the Applicant’s co-pending application 62/731,567, the contents of which are herein incorporated by reference.

[0080] If an emergency UAV is located at a UAV facility then this will reduce the capacity of that UAV facility to operate delivery UAVs. It should be understood that emergency UAVs should not be re-assigned away from a busy UAV facility in order for the capacity of delivery UAVs to be increased. If there is a need for each UAV to have an emergency UAV on standby then if an emergency UAV is activated in response to an emergency then one of the delivery UAVs present at that facility may be converted to an emergency UAV role, for example by loading a payload of medical supplies and then being classified as an emergency UAV. Once the emergency UAV which has been activated in response to an emergency has responded to the emergency situation then it may return to the UAV facility to which it has been assigned and continue as an emergency UAV. Alternatively, the unused medical supplies may be offloaded and the UAV may be classified as a delivery UAV and it may be assigned to a delivery function as described above. In a further alternative, the emergency UAV may be reassigned to a further UAV facility and continue to function as an emergency UAV.

[0081] Figure 9 shows a schematic depiction of a UAV delivery network 900 according to a further aspect of the present disclosure. The UAV delivery network 900 comprises five UAV facilities 110A, ... , 110E, each of which has an associated delivery area 120A, ... , 120E. The UAV delivery network 900 further comprises one or more fulfillment centers, which are not shown in Figure 9 for the sake of clarity. Each of the one or more fulfillment centers will be associated with one or more of the UAV facilities. Each of the UAV facilities 110A, ..., 110E will have one or more delivery UAVs assigned to them. Furthermore, an emergency UAV has been assigned to UAV facility 110E. The emergency UAV is an enhanced UAV which is capable of greater flying speed and greater range than a conventional UAV which is used for deliveries. The emergency UAV range obtained using an enhanced UAV is shown by the dotted circle 120E’. It can be seen from Figure 9 that the range of the emergency UAV is significantly greater than that of the conventional UAVs. In such a situation, it is possible to position emergency UAVs across the network such that any location can be reached by an emergency UAV, regardless of the type of UAV (that is, a conventional UAV or an enhanced UAV) which has been assigned to the role of emergency UAV. It will be understood that deployed UAV delivery networks will be significantly larger and more complex than the exemplary network described above and shown in Figure 9. It will be understood that it is possible for the entire network to be covered using a plurality of emergency UAVs, which may comprise a mix of enhanced UAVs and conventional UAVs. The FMS can be used to determine the combination of enhanced UAVs and conventional UAVs which comprise the fleet of emergency UAVs. Given the increased range possible with the enhanced UAV it is possible to provide emergency UAV cover for the entire delivery network area without needing to assign an emergency UAV to each of the UAV facilities. A delivery UAV may be converted into an emergency UAV by loading emergency medical supplies to a delivery UAV and then placing the emergency UAV on standby at an appropriate UAV facility. An emergency UAV can be converted into a delivery UAV by unloading the emergency medical supplies carried by an emergency UAV at a UAV facility.

[0082] Emergency cover for the UAV network may be defined by one or more pre determined metrics, for example: coverage of the entire UAV delivery network; coverage of a proportion of the geographical area covered by the delivery network; maximum flight time to any location within the delivery network; maximum flight time to a subset of locations within the delivery network etc. It should be understood that it is be possible to re-position emergency UAVs within the delivery network to allow UAVs to perform delivery flights from busy UAV facilities such that the efficiency of the delivery network can be increased without losing the required emergency UAV coverage for the entire delivery network.

[0083] The maximum flight time for an emergency UAV will be determined on the basis of the maximum speed of the emergency UAV, whether a conventional or an enhanced UAV, the location of the UAV facilities and the weather conditions, principally windspeed. Thus, an emergency UAV may be re-assigned from a first UAV facility to a second UAV facility as the weather conditions change to ensure that a particular location may be reached within the specified maximum flight time. Furthermore, weather conditions may reduce the flight range of a UAV. In such a situation, an emergency UAV may be re-assigned from a first UAV facility to a second UAV facility as the weather conditions change to ensure that a particular area of the delivery network can be reached by an emergency UAV.

[0084] When an emergency UAV is deployed to an emergency it is given priority over the delivery UAVs which are active. This may mean that delivery UAVs may need to be re routed to allow an emergency UAV to fly the most direct route to the location of an emergency or that an emergency UAV makes use of a UAV facility in preference to a delivery UAV. When an emergency UAV is required the FMS can determine the UAV facility from which the emergency UAV (or UAVs) can be deployed and the route to be flown to the location of the emergency. The FMS can then notify the UAV facilities and fulfillment centers which may be affected by the deployment of the emergency UAV. If the deployment of the emergency UAV will cause a delivery to a customer to be delayed, for example because a delivery UAV needs to be re-routed or because access to a UAV facility is delayed, then the customer can be notified of the delay and provided with an updated estimated delivery time. In the event that the deployment of an emergency UAV prevents a delivery from being made, for example if a delivery UAV needs to be classified as an emergency UAV and there is no delivery UAV available to make a delivery, then the customer will be notified of the situation and arrangements can be made such that the customer order can be delivered to the customer using an alternative delivery method. If the customer order is not time critical and the customer agrees then the order may be rescheduled such the order is delivered by a UAV at a later time and/or date.

[0085] Although at least some aspects of the embodiments described herein with reference to the drawings comprise computer processes performed in processing systems or processors, the disclosure also extends to computer programs, particularly computer programs on or in a carrier, adapted for putting the invention into practice. The program may be in the form of non-transitory source code, object code, a code intermediate source and object code such as in partially compiled form, or in any other non-transitory form suitable for use in the implementation of processes according to the disclosure. The carrier may be any entity or device capable of carrying the program. For example, the carrier may comprise a storage medium, such as a solid-state drive (SSD) or other semiconductor-based RAM; a ROM, for example a CD ROM or a semiconductor ROM; a magnetic recording medium, for example a floppy disk or hard disk; optical memory devices in general; etc.

[0086] It will be understood that the processor or processing system or circuitry referred to herein may in practice be provided by a single chip or integrated circuit or plural chips or integrated circuits, optionally provided as a chipset, an application-specific integrated circuit (ASIC), field-programmable gate array (FPGA), digital signal processor (DSP), etc. The chip or chips may comprise circuitry (as well as possibly firmware) for embodying at least one or more of a data processor or processors, a digital signal processor or processors, baseband circuitry and radio frequency circuitry, which are configurable so as to operate in accordance with the exemplary embodiments. In this regard, the exemplary embodiments may be implemented at least in part by computer software stored in (non-transitory) memory and executable by the processor, or by hardware, or by a combination of tangibly stored software and hardware (and tangibly stored firmware).

Claims

WHAT IS CLAIMED IS:

1. A delivery network for delivering a payload to a customer using an Unmanned Aerial Vehicle, UAV, said delivery network comprising a plurality of UAV facilities and a plurality of UAVs, each of said plurality of UAVs being assigned to one of the plurality of UAV facilities, wherein the delivery network is reconfigured in response to the utilization of the delivery network.

2. A delivery network according to Claim 1, wherein the delivery network is reconfigured in response to the utilization of one or more UAV facilities falling below a first predetermined value.

3. A delivery network according to Claim 1, wherein the delivery network is reconfigured in response to the utilization of one or more UAV facilities exceeding a second predetermined value.

4. The delivery network of Claim 1, wherein the delivery network is reconfigured by moving one of said UAV facilities from a first location to a second location.

5. The delivery network of Claim 4, wherein the delivery network is reconfigured by moving a first UAV facility from a first location to a second location, wherein a second UAV facility is also located at the second location.

6. The delivery network of Claim 1, wherein the delivery network is reconfigured by activating a further UAV facility.

7. The delivery network of Claim 6, wherein the delivery network is reconfigured by activating a further UAV facility at a location where a UAV facility is operating.

8. The delivery network of Claim 1, wherein the delivery network is reconfigured by deactivating one of the plurality of UAV facilities.

9. A delivery network according to Claim 1, wherein the delivery network is reconfigured in response to the utilization of one or more UAVs falling below a third predetermined value.

10. A delivery network according to Claim 1, wherein the delivery network is reconfigured in response to the utilization of one or more UAVs exceeding a fourth predetermined value.

11. The delivery network of Claim 1, wherein the delivery network is reconfigured by re-assigning one or more UAVs from a first UAV facility to a second UAV facility.

12. The delivery network of Claim 1, wherein the delivery network comprises a plurality of a first type of UAVs and a plurality of a second type of UAVs and the delivery network is reconfigured by re-assigning one or more UAVs of said first type from a first UAV facility to a second UAV facility.

13. The delivery network of Claim 11, wherein, in use, a UAV is re-assigned from said first UAV facility to said second UAV facility by making a delivery with the UAV from said first facility to a customer location, then re-locating said UAV to said second UAV facility.

14. The delivery network of Claim 1 , wherein the utilization of the delivery network is determined in part in accordance with the number of customer requests received from a geographical area.

15. The delivery network of Claim 1 , wherein the utilization of the delivery network is determined in part in accordance with the rate of customer requests received.

16. The delivery network of Claim 1, wherein the utilization of the delivery network is determined in part in accordance with the number of pending orders.

17. The delivery network of Claim 1, wherein the utilization of the delivery network is determined in part in accordance with predicted customer demand.

18. A method of delivering an order to a customer using an Unmanned Aerial Vehicle, UAV, delivery network, the UAV delivery network comprising a plurality of UAV facilities, one or more fulfillment centers and a plurality of UAVs, the method comprising the steps of: i) receiving an order from a customer; ii) identifying a plurality of fulfillment centers which can fulfill the order; iii) for each of the fulfillment centers identified in step ii), determining an associated UAV facility; iv) for each of the fulfillment centers identified in step ii), determining the time required to deliver the fulfilled order to the customer from the associated UAV facility identified in step iii); v) assigning the customer order to the fulfillment center having the shortest time to deliver the fulfilled order as determined in step iv); and vi) delivering the order to the customer using a UAV.

19. The method of Claim 18, wherein in step iv) the time required to deliver the fulfilled order is determined in accordance with the time required to fulfill the order and the time required for a UAV to fly from the UAV facility to the customer location.

20. The method of Claim 18, wherein in step iv) the time required to deliver the fulfilled order is determined in accordance with the time required to load the fulfilled order onto an available UAV and the time required for a UAV to fly from the UAV facility to the customer location.

21. The method of Claim 18, wherein in step iv) the time required to deliver the fulfilled order is determined in accordance with one or more UAV characteristics.

22. The method of Claim 18, wherein in step iv) the time required to deliver the fulfilled order is determined in accordance with the distance of the customer location from each of the fulfillment centers.

23. The method of Claim 18, wherein in step iv) the time required to deliver the fulfilled order is determined in accordance with meteorological data received from one or more meteorological data sources.

24. The method of Claim 20, wherein the time required to load the fulfilled order onto an available UAV comprises the time required to relocate a UAV to the UAV facility associated with the fulfillment center.

25. The method of Claim 20, wherein the time required to load the fulfilled order onto an available UAV comprises the time required to replace a UAV battery.

26. A non-transitory computer-readable medium having computer-executable instructions stored thereon, wherein the instructions, when executed, cause a computer system having at least one computer processor to perform a method comprising the steps of: i) receiving an order from a customer; ii) identifying a plurality of fulfillment centers which can fulfill the order; iii) for each of the fulfillment centers identified in step ii), determining the time required to deliver the fulfilled order to the customer from an Unmanned Aerial Vehicle, UAV, facility associated with said fulfillment center; iv) assigning the customer order to the fulfillment center having the shortest time to deliver the fulfilled order as determined in step iii); and v) causing the order to be delivered to the customer using a UAV.

27. A computing system, comprising: one or more processors; and a memory coupled to the processor and storing program instructions that when executed by the processor causes the processor to at least: i) receive an order from a customer; ii) identify a plurality of fulfillment centers which can fulfill the order; iii) for each of the fulfillment centers identified in step ii), determine the time required to deliver the fulfilled order to the customer from a UAV facility associated with said fulfillment center; iv) assign the customer order to the fulfillment center having the shortest time to deliver the fulfilled order as determined in step iii); and v) cause the order to be delivered to the customer using a UAV.

28. A system for use with an Unmanned Aerial Vehicle, UAV, delivery network, the system comprising a customer facing server and a plurality of fulfillment center servers, the customer facing server being configured in use to receive data from a UAV flight management system and the plurality of fulfillment center servers such that, in use, the customer facing server a) receives an order from a customer; b) identifies a plurality of fulfillment centers which can fulfill the customer order; c) determines the time required to deliver the fulfilled order to the customer from the associated UAV facility for each of the fulfillment centers identified in step b); and d) assigns the customer order to the fulfillment center having the shortest time to deliver the fulfilled order as determined in step c).

29. The system of Claim 28 wherein in step c) the customer facing server determines the time required to deliver the fulfilled order in accordance with the time required to fulfill the order and the time required for a UAV to fly from the UAV facility to the customer location.

30. The system of Claim 28 wherein in step c) the customer facing server determines the time required to deliver the fulfilled order in accordance with the time required to load the fulfilled order onto an available UAV and the time required for a UAV to fly from the UAV facility to the customer location.

31. The system of Claim 28 wherein in step c) the customer facing server determines the time required to deliver the fulfilled order in accordance with one or more UAV characteristics.

32. The system of Claim 28 wherein in step c) the customer facing server determines the time required to deliver the fulfilled order in accordance with the distance of the customer location from each of the fulfillment centers.

33. The system of Claim 28 wherein in step c) the customer facing server determines the time required to deliver the fulfilled order in accordance with meteorological data received from one or more meteorological data sources.

34. A method of processing an online order for delivery using an Unmanned Aerial Vehicle, UAV, delivery network, the UAV delivery network comprising a plurality of UAV facilities, one or more fulfillment centers associated with each of the plurality of UAV facilities and a plurality of UAVs, the method comprising the steps of: a) receiving an online order request from a customer terminal, the online order request comprising one or more items for delivery; b) receiving data from a UAV flight management system; c) receiving data from a plurality of fulfillment centers; d) for each of the fulfillment centers which can supply the one or more items specified in the online order request, determining the time required to deliver the one or more items to the customer; e) selecting the fulfillment center having the smallest delivery time; and f) displaying to the customer the delivery time for the fulfillment center selected in step e) before the customer places an order.

35. The method of Claim 34 wherein in step d) the time required to deliver the one or more items to the customer is determined in accordance with the time required to fulfill the online order request and the time required for a UAV to fly from the UAV facility to the customer location.

36. The method of Claim 34 wherein in step d) the time required to deliver the one or more items to the customer is determined in accordance with the time required to load the one or more items onto an available UAV and the time required for a UAV to fly from the UAV facility to the customer location.

37. The method of Claim 34 wherein in step d) the time required to deliver the one or more items to the customer is determined in accordance with one or more UAV characteristics.

38. The method of Claim 34 wherein in step d) the time required to deliver the one or more items to the customer is determined in accordance with the distance of the customer location from each of the fulfillment centers.

39. The method of Claim 34 wherein in step d) the time required to deliver the one or more items to the customer is determined in accordance with meteorological data received from one or more meteorological data sources.

40. An Unmanned Aerial Vehicle, UAV, delivery network for delivering a payload to a customer using a UAV, said delivery network comprising a plurality of UAV facilities, a first plurality of delivery UAVs, and a second plurality of emergency UAVs wherein each of said plurality of emergency UAVs is assigned to one of the UAV facilities such that emergency UAV cover is provided to the UAV network in accordance with one or more pre-determined metrics.

41. The UAV network of Claim 40, the UAV delivery network is re-configured to maintain the emergency UAV cover provided to the UAV network in accordance with said one or more pre-determined metrics.

42. The UAV network of Claim 40, wherein the UAV delivery network is re configured by re-assigning an emergency UAV from a first UAV facility to a second UAV facility.

43. The UAV network of Claim 40, wherein the UAV delivery network is re configured by re-classifying a delivery UAV as an emergency UAV.

44. The UAV network of Claim 43, wherein the delivery UAV is re-classified as an emergency UAV by loading a delivery UAV with an emergency payload.

45. The UAV network of Claim 40, wherein the emergency UAV comprises a UAV which has an extended range compared to a conventional UAV.

46. The UAV network of Claim 40, wherein the one or more pre-determined metrics comprise a proportion of the UAV network which is provided with emergency UAV cover.

47. The UAV network of Claim 40, wherein the one or more pre-determined metrics comprise a proportion of the UAV network which can be reached by an emergency UAV within a pre-determined period of time.