UAV Facility Planning Method, Device and UAV Delivery System

Abstract

The present invention discloses a drone facility planning method, device, and drone delivery system, wherein the method includes: obtaining multiple drone order information, determining multiple drone delivery routes based on the multiple drone order information; determining the delivery parameters of the target drone based on the multiple drone order information; determining a deployment strategy for drone transfer facilities based on the multiple drone delivery routes and the delivery parameters; the deployment strategy is used to ensure that the location and number of the drone transfer facilities can meet the transfer requirements of the target drone to complete the multiple drone orders. It can be seen that the present invention can enable drones to use the deployed drone transfer facilities for transfer when completing order tasks, ultimately achieving more efficient drone delivery and providing users with a better delivery service experience.

Description

Technical Field

[0001] The present invention relates to the field of drone technology, and in particular to a drone facility planning method and device, and a drone delivery system. Background Art

[0002] Unmanned aerial vehicles (UAVs), also known as drones, are an emerging technology that has seen rapid growth in recent years. They are widely used in firefighting, inspections, agriculture, logistics, and other fields, and are also gaining widespread acceptance among the general public, with numerous consumer-grade products now available. Consequently, some fast food delivery companies are considering incorporating UAVs into their delivery tools to provide fast food and semi-finished meals for customers.

[0003] However, with the development of drone delivery services, more and more drones are flying at low altitudes, and the density of drones at low altitudes is increasing, which in turn increases the flight burden. Therefore, existing technologies generally use auxiliary facilities such as transfer stations or anti-drop nets to ensure safe and orderly drone flights. However, existing technologies do not provide a reasonable solution for accurately planning the deployment of drone auxiliary facilities. Summary of the Invention

[0004] The technical problem to be solved by the present invention is to provide a drone facility planning method, device and drone delivery system, which can reasonably deploy drone transfer facilities based on the delivery routes and delivery parameters of multiple drones, so that drones can use the deployed drone transfer facilities for transfer when completing order tasks, and ultimately achieve more efficient drone delivery, bringing users a better delivery service experience.

[0005] In order to solve the above technical problems, the first aspect of the present invention discloses a method for planning a drone facility, the method comprising:

[0006] Acquire multiple drone order information, and determine multiple drone delivery routes based on the multiple drone order information; the drone delivery routes are routes that target drones need to travel to complete the drone order information;

[0007] Determining the delivery parameters of the target drone based on the multiple drone order information;

[0008] Based on the multiple drone delivery routes and the delivery parameters, a deployment strategy for the drone transfer facility is determined; the drone transfer facility is used to provide docking services for the drones; the deployment strategy is used to ensure that the location and number of the drone transfer facilities can meet the transfer needs of the target drone to complete the multiple drone orders.

[0009] As an optional embodiment, in the first aspect of the present invention, the target drone includes one or more drones; and / or the delivery parameters include one or more of the delivery speed information, delivery power consumption information, delivery time information and delivery load information of the target drone; and / or the docking service includes one or more of the docking charging service, docking recovery service and docking maintenance service.

[0010] As an optional embodiment, in the first aspect of the present invention, determining multiple drone delivery routes based on the multiple drone order information includes:

[0011] For any of the drone order information, determine the delivery starting point and delivery destination corresponding to the drone order information;

[0012] The drone delivery route between the delivery start point and the delivery end point is determined based on the path planning algorithm and the map of the target delivery area.

[0013] As an optional embodiment, in the first aspect of the present invention, determining the delivery parameters of the target drone based on the plurality of drone order information includes:

[0014] For any of the drone order information, determine the order parameters corresponding to the drone order information;

[0015] determining drone parameters of the target drone;

[0016] The delivery parameters of the target drone are determined according to the order parameters and the drone parameters.

[0017] As an optional embodiment, in the first aspect of the present invention, the order parameters include one or more of order path distance, order delivery route, and order cargo weight information; the drone parameters include one or more of maximum speed parameter, minimum speed parameter, and power consumption per unit distance parameter; and determining the delivery parameters of the target drone based on the order parameters and the drone parameters includes:

[0018] Determine the delivery time information of the target drone based on the order path distance in the order parameters and the average of the maximum speed parameter and the minimum speed parameter in the drone parameters;

[0019] and / or,

[0020] Determine the delivery speed information of the target UAV based on the order delivery route in the order parameters and the congestion obstacle model of the target delivery area;

[0021] and / or,

[0022] The delivery power consumption information of the target drone is determined according to the order path distance in the order parameters and the unit distance power consumption parameter in the drone parameters.

[0023] As an optional embodiment, in the first aspect of the present invention, determining a deployment strategy for a drone transfer facility based on the multiple drone delivery routes and the delivery parameters includes:

[0024] Calculating at least one intersection point of the plurality of drone delivery routes, determining the location of the intersection point as the location of the drone transfer facility, and setting the number of the intersection points to the number of the drone transfer facilities;

[0025] Determining a drone failure rate on each of the drone delivery routes based on the delivery parameters;

[0026] According to the drone failure rate of the drone delivery route, the number and location of the drone transfer facilities on the drone delivery route are corrected.

[0027] As an optional embodiment, in the first aspect of the present invention, the method further comprises:

[0028] Determining an estimated drop point of each drone on the drone delivery route based on the delivery parameters;

[0029] The location of the expected drop point of each drone on the drone delivery route is determined as the setting point of the drone protection facility; the drone protection facility is used to prevent the drone from falling to the ground.

[0030] A second aspect of the present invention discloses a drone facility planning device, comprising:

[0031] A route determination module is used to obtain multiple drone order information and determine multiple drone delivery routes based on the multiple drone order information; the drone delivery route is the route that the target drone needs to take to complete the drone order information;

[0032] A parameter determination module, configured to determine the delivery parameters of the target drone based on the plurality of drone order information;

[0033] A strategy determination module is used to determine the deployment strategy of the drone transfer facilities based on the multiple drone delivery routes and the delivery parameters; the drone transfer facilities are used to provide docking services for the drones; and the deployment strategy is used to ensure that the location and number of the drone transfer facilities can meet the transfer needs of the target drone to complete the multiple drone orders.

[0034] As an optional embodiment, in the second aspect of the present invention, the target drone includes one or more drones; and / or the delivery parameters include one or more of the delivery speed information, delivery power consumption information, delivery time information and delivery load information of the target drone; and / or the docking service includes one or more of the docking charging service, docking recovery service and docking maintenance service.

[0035] As an optional embodiment, in the second aspect of the present invention, the route determination module determines a specific method of multiple drone delivery routes based on the multiple drone order information, including:

[0036] For any of the drone order information, determine the delivery starting point and delivery destination corresponding to the drone order information;

[0037] The drone delivery route between the delivery start point and the delivery end point is determined based on the path planning algorithm and the map of the target delivery area.

[0038] As an optional embodiment, in the second aspect of the present invention, the parameter determination module determines the specific manner of the delivery parameters of the target drone based on the multiple drone order information, including:

[0039] For any of the drone order information, determine the order parameters corresponding to the drone order information;

[0040] determining drone parameters of the target drone;

[0041] The delivery parameters of the target drone are determined according to the order parameters and the drone parameters.

[0042] As an optional embodiment, in the second aspect of the present invention, the order parameters include one or more of order path distance, order delivery route, and order cargo weight information; the drone parameters include one or more of a maximum speed parameter, a minimum speed parameter, and a power consumption per unit distance parameter; and the parameter determination module determines the delivery parameters of the target drone based on the order parameters and the drone parameters in a specific manner, including:

[0043] Determine the delivery time information of the target drone based on the order path distance in the order parameters and the average of the maximum speed parameter and the minimum speed parameter in the drone parameters;

[0044] and / or,

[0045] Determine the delivery speed information of the target UAV based on the order delivery route in the order parameters and the congestion obstacle model of the target delivery area;

[0046] and / or,

[0047] The delivery power consumption information of the target drone is determined according to the order path distance in the order parameters and the unit distance power consumption parameter in the drone parameters.

[0048] As an optional embodiment, in the second aspect of the present invention, the strategy determination module determines a specific manner of deploying a strategy for a drone transfer facility based on the multiple drone delivery routes and the delivery parameters, including:

[0049] Calculating at least one intersection point of the plurality of drone delivery routes, determining the location of the intersection point as the location of the drone transfer facility, and setting the number of the intersection points to the number of the drone transfer facilities;

[0050] Determining a drone failure rate on each of the drone delivery routes based on the delivery parameters;

[0051] According to the drone failure rate of the drone delivery route, the number and location of the drone transfer facilities on the drone delivery route are corrected.

[0052] As an optional embodiment, in the second aspect of the present invention, the device further includes:

[0053] A drop point prediction module, configured to determine an estimated drop point of each drone on the drone delivery route based on the delivery parameters;

[0054] The facility location determination module is used to determine the location of the expected drop point of each drone on the drone delivery route as the setting point of the drone protection facility; the drone protection facility is used to prevent the drone from falling to the ground.

[0055] A third aspect of the present invention discloses another drone facility planning device, comprising:

[0056] a memory storing executable program code;

[0057] a processor coupled to the memory;

[0058] The processor calls the executable program code stored in the memory to execute some or all of the steps in the drone facility planning method disclosed in the first aspect of the embodiment of the present invention.

[0059] The fourth aspect of an embodiment of the present invention discloses a drone delivery system, which includes a planning device, multiple target drones and multiple drone facilities. The planning device is used to execute part or all of the steps in the drone facility planning method disclosed in the first aspect of the embodiment of the present invention to determine the deployment strategy of the drone facilities.

[0060] The fifth aspect of the present invention discloses a computer-readable storage medium having a computer program stored thereon. When the computer program is executed by a processor, it implements part or all of the steps in the drone facility planning method disclosed in the first aspect of an embodiment of the present invention.

[0061] Compared with the prior art, the embodiments of the present invention have the following beneficial effects:

[0062] In an embodiment of the present invention, multiple drone order information is obtained, and multiple drone delivery routes are determined based on the multiple drone order information; the drone delivery route is the route that the target drone needs to pass through to complete the drone order information; the delivery parameters of the target drone are determined based on the multiple drone order information; the deployment strategy of the drone transfer facility is determined based on the multiple drone delivery routes and the delivery parameters; the drone transfer facility is used to provide docking services for the drone; and the deployment strategy is used to ensure that the location and number of the drone transfer facilities can meet the transfer needs of the target drone to complete the multiple drone orders. It can be seen that the present invention can reasonably deploy drone transfer facilities based on the delivery routes and delivery parameters of multiple drones, so that the drones can use the deployed drone transfer facilities for transfer when completing order tasks, ultimately achieving more efficient drone delivery and providing users with a better delivery service experience. BRIEF DESCRIPTION OF THE DRAWINGS

[0063] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0064] Figure 1 This is a flowchart of a method for planning drone facilities disclosed in an embodiment of the present invention;

[0065] Figure 2 This is a schematic structural diagram of a UAV facility planning device disclosed in an embodiment of the present invention;

[0066] Figure 3 It is a structural schematic diagram of another drone facility planning device disclosed in an embodiment of the present invention. DETAILED DESCRIPTION

[0067] In order to enable those skilled in the art to better understand the solutions of the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. All other embodiments obtained by ordinary technicians in this field based on the embodiments of the present invention without making any creative efforts shall fall within the scope of protection of the present invention.

[0068] The terms "first," "second," and so on, in the description and claims of the present invention and the accompanying drawings are used to distinguish between different items, not to describe a specific order. Furthermore, the terms "including," "having," and any variations thereof, are intended to cover non-exclusive inclusions. For example, a process, method, apparatus, product, or end comprising a series of steps or elements is not limited to the listed steps or elements but may optionally include steps or elements not listed therein, or may optionally include other steps or elements inherent to such process, method, product, or end.

[0069] References herein to "embodiments" mean that a particular feature, structure, or characteristic described in connection with the embodiments may be included in at least one embodiment of the present invention. The appearance of this phrase in various places in the specification does not necessarily refer to the same embodiment, nor does it constitute a separate or alternative embodiment that is mutually exclusive of other embodiments. It is understood, both explicitly and implicitly, by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0070] The present invention discloses a drone facility planning method, device, and drone delivery system. These methods can rationally deploy drone transfer facilities based on the delivery routes and delivery parameters of multiple drones, enabling drones to utilize their assigned drone transfer facilities for transfer when completing order tasks. Ultimately, this enables more efficient drone delivery and provides users with a better delivery service experience. These are described in detail below.

[0071] Example 1

[0072] See also Figure 1 , Figure 1 This is a flow chart of a method for planning drone facilities disclosed in an embodiment of the present invention. Figure 1 The described method can be applied to a corresponding planning terminal, planning device or planning server, and the server can be a local server or a cloud server. Figure 1 As shown, the drone facility planning method may include the following operations:

[0073] 101. Obtain multiple drone order information, and determine multiple drone delivery routes based on the multiple drone order information.

[0074] In an embodiment of the present invention, the drone delivery route is the route that the target drone needs to pass through to complete the drone order information. Optionally, the target drone includes one or more drones. Optionally, the drone described in the present invention can be a military drone or a civilian drone. Specifically, it can include but is not limited to ultra-low altitude drones, low altitude drones, medium altitude drones, high altitude drones and ultra-high altitude drones. Optionally, drones can be used to transport prepared food and beverages, or semi-finished products such as ingredient packages. For example, a catering company can use drones to transport semi-finished products such as ingredient packages or raw materials to the catering production area via a transport track, and use automatic food production robots such as automatic fried rice robots set up in the catering production area to process the transported semi-finished products to obtain food and beverages. Furthermore, a catering company can use drones to transport food and beverages to customers via a transport track for them to enjoy. Accordingly, the drone delivery route can also refer to the route of the transport track that the target drone wants to pass through.

[0075] Optionally, drone order information can be generated based on a user's meal ordering needs, or automatically generated based on a timed and quantitative meal ordering needs. Optionally, drone order information can include one or more orders, or a combination of one or more of the following: the order's delivery origin, delivery destination, delivery item volume, and delivery item weight.

[0076] Optionally, a monitoring module may be provided on the transport track for detecting monitoring information of the target drone. Optionally, the drone monitoring information may include one or more of the number information, speed information, power information, and load information of the target drones. Accordingly, the monitoring module may also include one or more of a number monitoring unit, a speed monitoring unit, a power monitoring unit, or a load monitoring unit. Specifically, the power monitoring unit may also establish a connection with a power detector provided on the target drone to obtain the power information of the target drone in real time.

[0077] Furthermore, a transport track can be installed above the city and connected to the customer's residence or a receiving device. For example, a receiving device can be installed at the customer's window to connect to the transport track, so that the customer can receive the items delivered by the target drone. Furthermore, a storage device can be installed on the transport track to store the items delivered by the target drone for the customer to pick up.

[0078] Furthermore, the transport track can also be equipped with a charging module to provide charging services for target drones with insufficient power. This charging service can be an automatically generated task or a task based on the drone's request. Optionally, the charging service can require the entity corresponding to the target drone to pay a certain fee.

[0079] 102. Determine the delivery parameters of the target drone based on multiple drone order information.

[0080] In an embodiment of the present invention, the delivery parameters include one or more of the delivery speed information, delivery power consumption information, delivery time information, and delivery load information of the target UAV.

[0081] 103. Determine the deployment strategy of drone transfer facilities based on multiple drone delivery routes and delivery parameters.

[0082] In an embodiment of the present invention, a drone transfer facility is used to provide docking services for drones. Optionally, the drone transfer facility can be set on a transport track, and its form can be a platform docking device or a storage bin. Optionally, the docking service includes one or more of a docking charging service, a docking recovery service, and a docking maintenance service. For example, a drone can dock at a drone transfer facility for charging when the battery is low, or dock at a drone transfer facility to wait for recovery by a relevant entity when damaged, or dock at a drone transfer facility for repair when a fault occurs. Specifically, the deployment strategy is used to ensure that the location and number of drone transfer facilities can meet the transfer needs of the target drone to complete multiple drone orders.

[0083] It can be seen that the implementation of the method described in the embodiment of the present invention can reasonably deploy drone transfer facilities based on the delivery routes and delivery parameters of multiple drones, so that drones can use the deployed drone transfer facilities for transfer when completing order tasks, and ultimately achieve more efficient drone delivery, bringing users a better delivery service experience.

[0084] In an optional embodiment, the step 101 of determining multiple drone delivery routes based on multiple drone order information includes:

[0085] For any drone order information, determine the delivery starting point and delivery destination corresponding to the drone order information;

[0086] Based on the path planning algorithm and the map of the target delivery area, the drone delivery route between the delivery starting point and the delivery destination is determined.

[0087] In an embodiment of the present invention, the target delivery area is the delivery area corresponding to the drone order information. Specifically, the map of the target delivery area may include specified route information, route congestion information, route speed limit information, etc. The path planning algorithm and the map of the target delivery area can be used to calculate the shortest time-consuming route or the shortest distance route between the delivery starting point and the delivery end point to serve as the drone delivery route.

[0088] It can be seen that the implementation of this optional implementation method can determine the drone delivery route between the delivery starting point and the delivery end point based on the path planning algorithm and the map of the target delivery area, thereby more accurately determining the drone delivery route, which is conducive to improving the accuracy of subsequent calculations of deployment strategies, thereby improving the intelligence and accuracy of drone facility planning.

[0089] In an optional embodiment, determining the delivery parameters of the target drone based on the plurality of drone order information in step 102 includes:

[0090] For any drone order information, determine the order parameters corresponding to the drone order information;

[0091] Determine the drone parameters of the target drone;

[0092] Determine the delivery parameters of the target drone based on the order parameters and drone parameters.

[0093] Optionally, the order parameters include one or more of the order path distance, the order delivery route, and the order cargo weight information. Optionally, the drone parameters include one or more of the maximum speed parameter, the minimum speed parameter, and the power consumption per unit distance parameter.

[0094] It can be seen that the implementation of this optional implementation method can determine the delivery parameters of the target drone based on the order parameters corresponding to the drone order information and the drone parameters of the target drone, thereby more accurately determining the delivery parameters, which is conducive to improving the accuracy of subsequent calculations of deployment strategies, thereby improving the intelligence and accuracy of drone facility planning.

[0095] In an optional embodiment, the above step of determining the delivery parameters of the target drone based on the order parameters and the drone parameters includes:

[0096] The delivery time information of the target drone is determined based on the order path distance in the order parameters and the average of the maximum speed parameter and the minimum speed parameter in the drone parameters.

[0097] Alternatively, the length of the drone delivery path corresponding to the order parameters can be measured using a map of the target delivery area and a path distance calculation algorithm to obtain the order path distance. Alternatively, the ratio of the order path distance to the average of the maximum speed parameter and the minimum speed parameter can be calculated to obtain the target drone delivery time parameter.

[0098] It can be seen that the implementation of this optional implementation method can determine the delivery time information of the target drone based on the order path distance in the order parameters and the average value of the maximum speed parameter and the minimum speed parameter in the drone parameters, thereby more accurately determining the delivery time information of the target drone, which is conducive to improving the accuracy of subsequent calculations of deployment strategies, thereby improving the intelligence and accuracy of drone facility planning.

[0099] In an optional embodiment, the above step of determining the delivery parameters of the target drone based on the order parameters and the drone parameters includes:

[0100] According to the order delivery route in the order parameters and the congestion obstacle model of the target delivery area, the delivery speed information of the target drone is determined.

[0101] Optionally, the drone delivery route corresponding to the order parameters is determined as the order delivery route. Optionally, the congestion obstacle model of the target delivery area is used to indicate the congestion information and obstacle information on any passable path in the target delivery area. Optionally, the congestion information can be the possible congestion situation in any time period. The possible congestion situation can be calculated based on the congestion situation on the passable path in the historical time period corresponding to the time period, which can be used to indicate the average driving speed on the passable path. Optionally, the obstacle information can be used to indicate obstacles or obstacle signs on any passable path in the target delivery area. The obstacles can be aerial obstacles or obstacles on the transportation track, such as a construction site that needs to be bypassed. Optionally, the obstacle sign can be a deceleration sign or a speed limit sign.

[0102] Optionally, the delivery speed information is used to indicate the expected speed of the target drone in different parts of the order delivery route, which can be used to indicate the maximum speed that the target drone can reach in that part.

[0103] It can be seen that the implementation of this optional implementation method can determine the delivery speed information of the target drone based on the order delivery route in the order parameters and the congestion obstacle model of the target delivery area, thereby more accurately determining the delivery speed information of the target drone, which is conducive to improving the accuracy of subsequent calculations of deployment strategies, thereby improving the intelligence and accuracy of drone facility planning.

[0104] In an optional embodiment, the above step of determining the delivery parameters of the target drone based on the order parameters and the drone parameters includes:

[0105] The delivery power consumption information of the target drone is determined based on the order path distance in the order parameters and the unit distance power consumption parameter in the drone parameters.

[0106] Optionally, the ratio between the order path distance and the unit distance power consumption parameter is calculated to determine the delivery power consumption information, and the delivery power consumption information is used to indicate the amount of power required for the target drone to complete the drone order information.

[0107] It can be seen that the implementation of this optional implementation method can determine the delivery power consumption information of the target drone based on the order path distance in the order parameters and the unit distance power consumption parameters in the drone parameters, thereby more accurately determining the delivery power consumption information of the target drone, which is conducive to improving the accuracy of subsequent calculations of deployment strategies, thereby improving the intelligence and accuracy of drone facility planning.

[0108] In an optional embodiment, the above step 103 determines the deployment strategy of the drone transfer facility based on multiple drone delivery routes and delivery parameters, including:

[0109] Calculate at least one intersection point of the plurality of drone delivery routes, determine the location of the intersection point as the location of the drone transfer facility, and set the number of intersection points to the number of drone transfer facilities;

[0110] Determine the drone failure rate on each drone delivery route based on the delivery parameters;

[0111] Based on the drone failure rate of the drone delivery route, the number and location of drone transfer facilities on the drone delivery route are revised.

[0112] It can be seen that the implementation of this optional implementation method can determine the location and number of drone transfer facilities, and according to the drone failure rate of the drone delivery route, correct the number and location of drone transfer facilities on the drone delivery route, so as to finally determine the drone scheduling strategy and reasonably deploy the drone transfer facilities, so that drones can use the deployed drone transfer facilities for transfer when completing order tasks, and ultimately achieve more efficient drone delivery, bringing users a better delivery service experience.

[0113] In an optional embodiment, the above step of determining the drone failure rate on each drone delivery route based on the delivery parameters may include:

[0114] For each drone delivery route, the probability of the target drone on the drone delivery route malfunctioning due to overtime flight is determined based on the delivery time information in the delivery parameters and the maximum flight time of the target drone.

[0115] Optionally, the probability of the target UAV malfunctioning due to overtime flight can be calculated by calculating the difference between the delivery time information and the longest flight time. When the difference is greater than 0, the probability of the target UAV malfunctioning due to overtime flight is proportional to the difference, and the relationship is exponentially proportional.

[0116] It can be seen that the implementation of this optional implementation method can determine the probability of the target drone on the drone delivery route failing due to overtime flight, thereby more accurately determining the drone failure rate of the target drone, which is conducive to improving the accuracy of subsequent calculations of deployment strategies, thereby improving the intelligence and accuracy of drone facility planning.

[0117] In an optional embodiment, the above step of determining the drone failure rate on each drone delivery route based on the delivery parameters may include:

[0118] For each drone delivery route, the probability of a target drone on the drone delivery route malfunctioning due to a flight accident is determined based on the expected speed of the target drone at different parts of the order delivery route indicated in the delivery speed information in the delivery parameters.

[0119] Optionally, the probability of the target UAV malfunctioning due to a flight accident can be calculated using the following steps:

[0120] Calculate the expected speed difference between any two parts of the order delivery route, and determine that the two parts are dangerous connection points when the expected speed difference is greater than a preset threshold;

[0121] The number of all dangerous connection points on the order delivery route is determined, and based on this number, the probability of the target drone malfunctioning due to a flight accident is calculated. Specifically, the probability is proportional to the number and is exponentially proportional.

[0122] It can be seen that the implementation of this optional implementation method can determine the probability of the target drone on the drone delivery route failing due to a flight accident, thereby more accurately determining the drone failure rate of the target drone, which is conducive to improving the accuracy of the subsequent calculation of the deployment strategy, thereby improving the intelligence and accuracy of drone facility planning.

[0123] In an optional embodiment, the above step of determining the drone failure rate on each drone delivery route based on the delivery parameters may include:

[0124] For each drone delivery route, the probability of the target drone on the drone delivery route malfunctioning due to power loss is determined based on the delivery power consumption information in the delivery parameters and the remaining power of the target drone.

[0125] Optionally, the probability of the target UAV malfunctioning due to power loss can be calculated by calculating the difference between the delivery power consumption information and the remaining power. When the difference is greater than 0, the probability of the target UAV malfunctioning due to power loss is proportional to the difference, and the relationship is exponentially proportional.

[0126] It can be seen that the implementation of this optional implementation method can determine the probability of the target drone on the drone delivery route failing due to power failure, thereby more accurately determining the drone failure rate of the target drone, which is conducive to improving the accuracy of the subsequent calculation of the deployment strategy, thereby improving the intelligence and accuracy of drone facility planning.

[0127] In an optional embodiment, the above step of modifying the number and location of drone transfer facilities on the drone delivery route based on the drone failure rate along the drone delivery route may include:

[0128] According to the drone failure rate of all drone delivery routes, all drone delivery routes are sorted from low to high according to the drone failure rate to obtain the route sequence;

[0129] Calculate the sum of the number of drone transfer facilities along all drone delivery routes;

[0130] Allocate the total number of drone transfer facilities to the drone delivery routes from the front to the back of the route sequence in descending order;

[0131] The drone transfer facilities assigned to each drone delivery route will be allocated to the intersection points on the drone delivery route according to the number and the principle of keeping the distance between them as even as possible.

[0132] It can be seen that the implementation of this optional implementation method can correct the number and location of drone transfer facilities on the drone delivery route according to the drone failure rate of the drone delivery route, so as to finally determine the drone scheduling strategy and reasonably deploy the drone transfer facilities, so that drones can use the deployed drone transfer facilities for transfer when completing order tasks, and ultimately achieve more efficient drone delivery, bringing better delivery service experience to users.

[0133] In an optional embodiment, the method further comprises:

[0134] Determine the expected drop point of each drone on its delivery route based on the delivery parameters;

[0135] The location of the drone's expected drop point on each drone delivery route is determined as the setting point for the drone protection facilities.

[0136] In embodiments of the present invention, drone protection facilities are used to prevent drones from falling to the ground. For example, drone protection facilities can be protective nets installed on transportation tracks or high in the air in cities, or they can be made of other load-bearing materials, such as elastic materials, and the present invention is not limited thereto.

[0137] Optionally, determining the expected drop point of the drone on each drone delivery route based on the delivery parameters may include: for each drone delivery route, calculating the ratio of the delivery time information in the delivery parameters to the longest flight time of the target drone, and determining the route length of the drone delivery route at the position point corresponding to the ratio to determine the expected drop point of the drone.

[0138] Optionally, determining the expected drop point of the drone on each drone delivery route based on the delivery parameters may include: for each drone delivery route, calculating the ratio of the remaining power of the target drone and the delivery power consumption information in the delivery parameters, and determining the route length of the drone delivery route at the position point corresponding to the ratio to determine the expected drop point of the drone.

[0139] Optionally, determining the expected drop point of the drone on each drone delivery route based on the delivery parameters may include: for each drone delivery route, determining the intersection of two parts corresponding to all dangerous connection points on the drone delivery route as the expected drop point of the drone.

[0140] It can be seen that the implementation of this optional implementation method can determine the location of the expected drop point of the drone on each drone delivery route as the setting point of the drone protection facility, so as to provide timely protection services for possible drone drops, reduce drone damage, and increase the probability of drone recovery.

[0141] Example 2

[0142] See also Figure 2 , Figure 2 This is a schematic diagram of the structure of a UAV facility planning device disclosed in an embodiment of the present invention. Figure 2 The described apparatus can be applied to corresponding planning terminals, planning devices or planning servers, and the server can be a local server or a cloud server, which is not limited in the embodiment of the present invention. Figure 2 As shown, the device may include:

[0143] The route determination module 201 is used to obtain a plurality of drone order information and determine a plurality of drone delivery routes based on the plurality of drone order information.

[0144] In an embodiment of the present invention, the drone delivery route is the route that the target drone needs to pass through to complete the drone order information. Optionally, the target drone includes one or more drones. Optionally, the drone described in the present invention can be a military drone or a civilian drone. Specifically, it can include but is not limited to ultra-low altitude drones, low altitude drones, medium altitude drones, high altitude drones and ultra-high altitude drones. Optionally, drones can be used to transport prepared food and beverages, or semi-finished products such as ingredient packages. For example, a catering company can use drones to transport semi-finished products such as ingredient packages or raw materials to the catering production area via a transport track, and use automatic food production robots such as automatic fried rice robots set up in the catering production area to process the transported semi-finished products to obtain food and beverages. Furthermore, a catering company can use drones to transport food and beverages to customers via a transport track for them to enjoy. Accordingly, the drone delivery route can also refer to the route of the transport track that the target drone wants to pass through.

[0145] Optionally, drone order information can be generated based on a user's meal ordering needs, or automatically generated based on a timed and quantitative meal ordering needs. Optionally, drone order information can include one or more orders, or a combination of one or more of the following: the order's delivery origin, delivery destination, delivery item volume, and delivery item weight.

[0146] Optionally, a monitoring module may be provided on the transport track for detecting monitoring information of the target drone. Optionally, the drone monitoring information may include one or more of the number information, speed information, power information, and load information of the target drones. Accordingly, the monitoring module may also include one or more of a number monitoring unit, a speed monitoring unit, a power monitoring unit, or a load monitoring unit. Specifically, the power monitoring unit may also establish a connection with a power detector provided on the target drone to obtain the power information of the target drone in real time.

[0147] Furthermore, a transport track can be installed above the city and connected to the customer's residence or a receiving device. For example, a receiving device can be installed at the customer's window to connect to the transport track, so that the customer can receive the items delivered by the target drone. Furthermore, a storage device can be installed on the transport track to store the items delivered by the target drone for the customer to pick up.

[0148] Furthermore, the transport track can also be equipped with a charging module to provide charging services for target drones with insufficient power. This charging service can be an automatically generated task or a task based on the drone's request. Optionally, the charging service can require the entity corresponding to the target drone to pay a certain fee.

[0149] The parameter determination module 202 is used to determine the delivery parameters of the target drone based on the multiple drone order information.

[0150] In an embodiment of the present invention, the delivery parameters include one or more of the delivery speed information, delivery power consumption information, delivery time information, and delivery load information of the target UAV.

[0151] The strategy determination module 203 is used to determine the deployment strategy of the drone transfer facilities based on multiple drone delivery routes and delivery parameters.

[0152] In an embodiment of the present invention, a drone transfer facility is used to provide docking services for drones. Optionally, the drone transfer facility can be set on a transport track, and its form can be a platform docking device or a storage bin. Optionally, the docking service includes one or more of a docking charging service, a docking recovery service, and a docking maintenance service. For example, a drone can dock at a drone transfer facility for charging when the battery is low, or dock at a drone transfer facility to wait for recovery by a relevant entity when damaged, or dock at a drone transfer facility for repair when a fault occurs. Specifically, the deployment strategy is used to ensure that the location and number of drone transfer facilities can meet the transfer needs of the target drone to complete multiple drone orders.

[0153] It can be seen that the device described in the embodiment of the present invention can reasonably deploy drone transfer facilities based on the delivery routes and delivery parameters of multiple drones, so that drones can use the deployed drone transfer facilities for transfer when completing order tasks, and ultimately achieve more efficient drone delivery, bringing users a better delivery service experience.

[0154] As an optional implementation, the route determination module 201 determines a specific method of multiple drone delivery routes based on multiple drone order information, including:

[0155] For any drone order information, determine the delivery starting point and delivery destination corresponding to the drone order information;

[0156] Based on the path planning algorithm and the map of the target delivery area, the drone delivery route between the delivery starting point and the delivery destination is determined.

[0157] In an embodiment of the present invention, the target delivery area is the delivery area corresponding to the drone order information. Specifically, the map of the target delivery area may include specified route information, route congestion information, route speed limit information, etc. The path planning algorithm and the map of the target delivery area can be used to calculate the shortest time-consuming route or the shortest distance route between the delivery starting point and the delivery end point to serve as the drone delivery route.

[0158] It can be seen that the implementation of this optional implementation method can determine the drone delivery route between the delivery starting point and the delivery end point based on the path planning algorithm and the map of the target delivery area, thereby more accurately determining the drone delivery route, which is conducive to improving the accuracy of subsequent calculations of deployment strategies, thereby improving the intelligence and accuracy of drone facility planning.

[0159] As an optional implementation, the parameter determination module 202 determines the specific method of the delivery parameters of the target drone based on the multiple drone order information, including:

[0160] For any drone order information, determine the order parameters corresponding to the drone order information;

[0161] Determine the drone parameters of the target drone;

[0162] Determine the delivery parameters of the target drone based on the order parameters and drone parameters.

[0163] Optionally, the order parameters include one or more of the order path distance, the order delivery route, and the order cargo weight information. Optionally, the drone parameters include one or more of the maximum speed parameter, the minimum speed parameter, and the power consumption per unit distance parameter.

[0164] It can be seen that the implementation of this optional implementation method can determine the delivery parameters of the target drone based on the order parameters corresponding to the drone order information and the drone parameters of the target drone, thereby more accurately determining the delivery parameters, which is conducive to improving the accuracy of subsequent calculations of deployment strategies, thereby improving the intelligence and accuracy of drone facility planning.

[0165] As an optional implementation, the parameter determination module 202 determines the specific method of the delivery parameters of the target drone based on the order parameters and the drone parameters, including:

[0166] Determine the delivery time of the target drone based on the order path distance in the order parameters and the average of the maximum speed parameter and the minimum speed parameter in the drone parameters;

[0167] The delivery time information of the target drone is determined based on the order path distance in the order parameters and the average of the maximum speed parameter and the minimum speed parameter in the drone parameters.

[0168] Alternatively, the length of the drone delivery path corresponding to the order parameters can be measured using a map of the target delivery area and a path distance calculation algorithm to obtain the order path distance. Alternatively, the ratio of the order path distance to the average of the maximum speed parameter and the minimum speed parameter can be calculated to obtain the target drone delivery time parameter.

[0169] It can be seen that the implementation of this optional implementation method can determine the delivery time information of the target drone based on the order path distance in the order parameters and the average value of the maximum speed parameter and the minimum speed parameter in the drone parameters, thereby more accurately determining the delivery time information of the target drone, which is conducive to improving the accuracy of subsequent calculations of deployment strategies, thereby improving the intelligence and accuracy of drone facility planning.

[0170] As an optional implementation, the parameter determination module 202 determines the specific method of the delivery parameters of the target drone based on the order parameters and the drone parameters, including:

[0171] According to the order delivery route in the order parameters and the congestion obstacle model of the target delivery area, the delivery speed information of the target drone is determined.

[0172] Optionally, the drone delivery route corresponding to the order parameters is determined as the order delivery route. Optionally, the congestion obstacle model of the target delivery area is used to indicate the congestion information and obstacle information on any passable path in the target delivery area. Optionally, the congestion information can be the possible congestion situation in any time period. The possible congestion situation can be calculated based on the congestion situation on the passable path in the historical time period corresponding to the time period, which can be used to indicate the average driving speed on the passable path. Optionally, the obstacle information can be used to indicate obstacles or obstacle signs on any passable path in the target delivery area. The obstacles can be aerial obstacles or obstacles on the transportation track, such as a construction site that needs to be bypassed. Optionally, the obstacle sign can be a deceleration sign or a speed limit sign.

[0173] Optionally, the delivery speed information is used to indicate the expected speed of the target drone in different parts of the order delivery route, which can be used to indicate the maximum speed that the target drone can reach in that part.

[0174] It can be seen that the implementation of this optional implementation method can determine the delivery speed information of the target drone based on the order delivery route in the order parameters and the congestion obstacle model of the target delivery area, thereby more accurately determining the delivery speed information of the target drone, which is conducive to improving the accuracy of subsequent calculations of deployment strategies, thereby improving the intelligence and accuracy of drone facility planning.

[0175] As an optional implementation, the parameter determination module 202 determines the specific method of the delivery parameters of the target drone based on the order parameters and the drone parameters, including:

[0176] The delivery power consumption information of the target drone is determined based on the order path distance in the order parameters and the unit distance power consumption parameter in the drone parameters.

[0177] Optionally, the ratio between the order path distance and the unit distance power consumption parameter is calculated to determine the delivery power consumption information, and the delivery power consumption information is used to indicate the amount of power required for the target drone to complete the drone order information.

[0178] It can be seen that the implementation of this optional implementation method can determine the delivery power consumption information of the target drone based on the order path distance in the order parameters and the unit distance power consumption parameters in the drone parameters, thereby more accurately determining the delivery power consumption information of the target drone, which is conducive to improving the accuracy of subsequent calculations of deployment strategies, thereby improving the intelligence and accuracy of drone facility planning.

[0179] As an optional implementation, the strategy determination module 203 determines the specific deployment strategy of the drone transfer facility based on multiple drone delivery routes and delivery parameters, including:

[0180] Calculate at least one intersection point of the plurality of drone delivery routes, determine the location of the intersection point as the location of the drone transfer facility, and set the number of intersection points to the number of drone transfer facilities;

[0181] Determine the drone failure rate on each drone delivery route based on the delivery parameters;

[0182] Based on the drone failure rate of the drone delivery route, the number and location of drone transfer facilities on the drone delivery route are revised.

[0183] It can be seen that the implementation of this optional implementation method can determine the location and number of drone transfer facilities, and according to the drone failure rate of the drone delivery route, correct the number and location of drone transfer facilities on the drone delivery route, so as to finally determine the drone scheduling strategy and reasonably deploy the drone transfer facilities, so that drones can use the deployed drone transfer facilities for transfer when completing order tasks, and ultimately achieve more efficient drone delivery, bringing users a better delivery service experience.

[0184] In an optional embodiment, the strategy determination module 203 determines the specific method of the drone failure rate on each drone delivery route based on the delivery parameters, which may include:

[0185] For each drone delivery route, the probability of the target drone on the drone delivery route malfunctioning due to overtime flight is determined based on the delivery time information in the delivery parameters and the maximum flight time of the target drone.

[0186] Optionally, the probability of the target UAV malfunctioning due to overtime flight can be calculated by calculating the difference between the delivery time information and the longest flight time. When the difference is greater than 0, the probability of the target UAV malfunctioning due to overtime flight is proportional to the difference, and the relationship is exponentially proportional.

[0187] It can be seen that the implementation of this optional implementation method can determine the probability of the target drone on the drone delivery route failing due to overtime flight, thereby more accurately determining the drone failure rate of the target drone, which is conducive to improving the accuracy of subsequent calculations of deployment strategies, thereby improving the intelligence and accuracy of drone facility planning.

[0188] In an optional embodiment, the strategy determination module 203 determines the specific method of the drone failure rate on each drone delivery route based on the delivery parameters, which may include:

[0189] For each drone delivery route, the probability of a target drone on the drone delivery route malfunctioning due to a flight accident is determined based on the expected speed of the target drone at different parts of the order delivery route indicated in the delivery speed information in the delivery parameters.

[0190] Optionally, the probability of the target UAV malfunctioning due to a flight accident can be calculated using the following steps:

[0191] Calculate the expected speed difference between any two parts of the order delivery route, and determine that the two parts are dangerous connection points when the expected speed difference is greater than a preset threshold;

[0192] The number of all dangerous connection points on the order delivery route is determined, and based on this number, the probability of the target drone malfunctioning due to a flight accident is calculated. Specifically, the probability is proportional to the number and is exponentially proportional.

[0193] It can be seen that the implementation of this optional implementation method can determine the probability of the target drone on the drone delivery route failing due to a flight accident, thereby more accurately determining the drone failure rate of the target drone, which is conducive to improving the accuracy of the subsequent calculation of the deployment strategy, thereby improving the intelligence and accuracy of drone facility planning.

[0194] In an optional embodiment, the strategy determination module 203 determines the specific method of the drone failure rate on each drone delivery route based on the delivery parameters, which may include:

[0195] For each drone delivery route, the probability of the target drone on the drone delivery route malfunctioning due to power loss is determined based on the delivery power consumption information in the delivery parameters and the remaining power of the target drone.

[0196] Optionally, the probability of the target UAV malfunctioning due to power loss can be calculated by calculating the difference between the delivery power consumption information and the remaining power. When the difference is greater than 0, the probability of the target UAV malfunctioning due to power loss is proportional to the difference, and the relationship is exponentially proportional.

[0197] It can be seen that the implementation of this optional implementation method can determine the probability of the target drone on the drone delivery route failing due to power failure, thereby more accurately determining the drone failure rate of the target drone, which is conducive to improving the accuracy of the subsequent calculation of the deployment strategy, thereby improving the intelligence and accuracy of drone facility planning.

[0198] In an optional embodiment, the strategy determination module 203 may modify the number and location of drone transfer facilities on the drone delivery route based on the drone failure rate of the drone delivery route, which may include:

[0199] According to the drone failure rate of all drone delivery routes, all drone delivery routes are sorted from low to high according to the drone failure rate to obtain the route sequence;

[0200] Calculate the sum of the number of drone transfer facilities along all drone delivery routes;

[0201] Allocate the total number of drone transfer facilities to the drone delivery routes from the front to the back of the route sequence in descending order;

[0202] The drone transfer facilities assigned to each drone delivery route will be allocated to the intersection points on the drone delivery route according to the number and the principle of keeping the distance between them as even as possible.

[0203] It can be seen that the implementation of this optional implementation method can correct the number and location of drone transfer facilities on the drone delivery route according to the drone failure rate of the drone delivery route, so as to finally determine the drone scheduling strategy and reasonably deploy the drone transfer facilities, so that drones can use the deployed drone transfer facilities for transfer when completing order tasks, and ultimately achieve more efficient drone delivery, bringing better delivery service experience to users.

[0204] As an optional embodiment, the device further includes:

[0205] The drop point prediction module is used to determine the expected drop point of each drone on the delivery route based on the delivery parameters;

[0206] The facility location determination module is used to determine the location of the drone's expected drop point on each drone delivery route as the setting point of the drone protection facility; the drone protection facility is used to prevent the drone from falling to the ground.

[0207] In embodiments of the present invention, drone protection facilities are used to prevent drones from falling to the ground. For example, drone protection facilities can be protective nets installed on transportation tracks or high in the air in cities, or they can be made of other load-bearing materials, such as elastic materials, and the present invention is not limited thereto.

[0208] Optionally, determining the expected drop point of the drone on each drone delivery route based on the delivery parameters may include: for each drone delivery route, calculating the ratio of the delivery time information in the delivery parameters to the longest flight time of the target drone, and determining the route length of the drone delivery route at the position point corresponding to the ratio to determine the expected drop point of the drone.

[0209] Optionally, determining the expected drop point of the drone on each drone delivery route based on the delivery parameters may include: for each drone delivery route, calculating the ratio of the remaining power of the target drone and the delivery power consumption information in the delivery parameters, and determining the route length of the drone delivery route at the position point corresponding to the ratio to determine the expected drop point of the drone.

[0210] Optionally, determining the expected drop point of the drone on each drone delivery route based on the delivery parameters may include: for each drone delivery route, determining the intersection of two parts corresponding to all dangerous connection points on the drone delivery route as the expected drop point of the drone.

[0211] It can be seen that the implementation of this optional implementation method can determine the location of the expected drop point of the drone on each drone delivery route as the setting point of the drone protection facility, so as to provide timely protection services for possible drone drops, reduce drone damage, and increase the probability of drone recovery.

[0212] Example 3

[0213] See also Figure 3 , Figure 3 This is a structural diagram of another drone facility planning device disclosed in an embodiment of the present invention. Figure 3 As shown, the device may include:

[0214] A memory 301 storing executable program code;

[0215] a processor 302 coupled to the memory 301;

[0216] The processor 302 calls the executable program code stored in the memory 301 to execute some or all of the steps in the drone facility planning method disclosed in the first embodiment of the present invention.

[0217] Example 4

[0218] An embodiment of the present invention discloses a computer storage medium, which stores computer instructions. When the computer instructions are called, they are used to execute some or all steps in the drone facility planning method disclosed in Example 1 of the present invention.

[0219] Example 5

[0220] An embodiment of the present invention discloses a drone delivery system, which includes a planning device, multiple target drones and multiple drone facilities. The planning device is used to execute some or all of the steps in the drone facility planning method disclosed in Example 1 of the present invention to determine the deployment strategy of multiple drone facilities.

[0221] Specifically, the drone facilities in the embodiment of the present invention include drone transfer facilities and / or drone protection facilities, wherein the target drone runs on a transport track. The relevant technical details of the drone facilities, transport tracks and target drones can refer to the corresponding descriptions in Example 1, and the embodiment of the present invention will not be repeated here.

[0222] The device embodiments described above are merely illustrative. Modules described as separate components may or may not be physically separate, and components shown as modules may or may not be physical modules, i.e., they may be located in one place or distributed across multiple network modules. Some or all of the modules may be selected based on actual needs to achieve the objectives of the present embodiment. Persons of ordinary skill in the art will be able to understand and implement the present invention without inventive effort.

[0223] Through the detailed description of the above embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus the necessary general hardware platform, or of course, by means of hardware. Based on this understanding, the above technical solution, in essence, or the portion that contributes to the prior art, can be embodied in the form of a software product, which can be stored in a computer-readable storage medium, including a read-only memory (ROM), a random access memory (RAM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), a one-time programmable read-only memory (OTPROM), an electronically erasable programmable read-only memory (EEPROM), a compact disc read-only memory (CD-ROM) or other optical disc storage, magnetic disk storage, magnetic tape storage, or any other computer-readable medium capable of carrying or storing data.

[0224] Finally, it should be noted that the drone facility planning method, device and drone delivery system disclosed in the embodiments of the present invention are only preferred embodiments of the present invention, and are only used to illustrate the technical solutions of the present invention, rather than to limit them. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that the technical solutions described in the aforementioned embodiments can still be modified, or some of the technical features therein can be replaced by equivalents. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the various embodiments of the present invention.

Claims

1. A method for planning drone facilities, characterized in that: The method comprises: Acquire multiple drone order information, and determine multiple drone delivery routes based on the multiple drone order information; the drone delivery routes are routes that target drones need to travel to complete the drone order information, and the target drones include one or more drones; Determining the delivery parameters of the target drone based on the plurality of drone order information, wherein the delivery parameters include delivery speed information, delivery power consumption information, delivery time information, and delivery load information of the target drone; Determining a deployment strategy for drone transfer facilities based on the multiple drone delivery routes and the delivery parameters; the drone transfer facilities are configured to provide docking services for the drones; and the deployment strategy is configured to ensure that the location and number of the drone transfer facilities meet the transfer requirements of the target drones for completing the multiple drone orders. The step of determining the delivery parameters of the target drone based on the plurality of drone order information includes: For any of the drone order information, determine the order parameters corresponding to the drone order information; the order parameters include order path distance, order delivery route and order cargo weight information; Determining the drone parameters of the target drone; the drone parameters include a maximum speed parameter, a minimum speed parameter, and a power consumption per unit distance parameter; Determining the delivery parameters of the target drone based on the order parameters and the drone parameters; And, determining the delivery parameters of the target drone based on the order parameters and the drone parameters includes: Determine the delivery time information of the target drone based on the order path distance in the order parameters and the average of the maximum speed parameter and the minimum speed parameter in the drone parameters; Determine the delivery speed information of the target UAV based on the order delivery route in the order parameters and the congestion obstacle model of the target delivery area; Determining the delivery power consumption information of the target drone based on the order path distance in the order parameters and the unit distance power consumption parameter in the drone parameters; Furthermore, determining a deployment strategy for drone transfer facilities based on the multiple drone delivery routes and the delivery parameters includes: Calculating at least one intersection point of the plurality of drone delivery routes, determining the location of the intersection point as the location of the drone transfer facility, and setting the number of the intersection points to the number of the drone transfer facilities; Determining a drone failure rate on each of the drone delivery routes based on the delivery parameters; According to the drone failure rate of the drone delivery route, the number and location of the drone transfer facilities on the drone delivery route are corrected.

2. The method for planning drone facilities according to claim 1, wherein: The docking service includes one or more of a docking charging service, a docking recycling service, and a docking maintenance service.

3. The method for planning drone facilities according to claim 1, wherein: Determining multiple drone delivery routes based on the multiple drone order information includes: For any of the drone order information, determine the delivery starting point and delivery destination corresponding to the drone order information; The drone delivery route between the delivery start point and the delivery end point is determined based on the path planning algorithm and the map of the target delivery area.

4. The method for planning drone facilities according to claim 1, wherein: The method further comprises: Determining an estimated drop point of each drone on the drone delivery route based on the delivery parameters; The location of the expected drop point of each drone on the drone delivery route is determined as the setting point of the drone protection facility; the drone protection facility is used to prevent the drone from falling to the ground.

5. A drone facility planning device, characterized in that: The device comprises: a route determination module, configured to obtain a plurality of drone order information and determine a plurality of drone delivery routes based on the plurality of drone order information; the drone delivery routes are routes that target drones need to travel through to complete the drone order information, the target drones including one or more drones; a parameter determination module, configured to determine the delivery parameters of the target drone based on the plurality of drone order information, wherein the delivery parameters include delivery speed information, delivery power consumption information, delivery duration information, and delivery load information of the target drone; a strategy determination module, configured to determine a deployment strategy for drone transfer facilities based on the multiple drone delivery routes and the delivery parameters; the drone transfer facilities are configured to provide docking services for the drones; and the deployment strategy is configured to ensure that the location and number of the drone transfer facilities meet the transfer requirements of the target drones for completing the multiple drone orders; The parameter determination module determines the specific manner of the delivery parameters of the target drone based on the plurality of drone order information, including: For any of the drone order information, determine the order parameters corresponding to the drone order information; the order parameters include order path distance, order delivery route and order cargo weight information; Determining the drone parameters of the target drone; the drone parameters include a maximum speed parameter, a minimum speed parameter, and a power consumption per unit distance parameter; Determining the delivery parameters of the target drone based on the order parameters and the drone parameters; Furthermore, the parameter determination module determines the specific manner in which the delivery parameters of the target drone are determined based on the order parameters and the drone parameters, including: Determine the delivery time information of the target drone based on the order path distance in the order parameters and the average of the maximum speed parameter and the minimum speed parameter in the drone parameters; Determine the delivery speed information of the target UAV based on the order delivery route in the order parameters and the congestion obstacle model of the target delivery area; Determining the delivery power consumption information of the target drone based on the order path distance in the order parameters and the unit distance power consumption parameter in the drone parameters; Furthermore, the strategy determination module determines a specific method of deploying a strategy for a drone transfer facility based on the multiple drone delivery routes and the delivery parameters, including: Calculating at least one intersection point of the plurality of drone delivery routes, determining the location of the intersection point as the location of the drone transfer facility, and setting the number of the intersection points to the number of the drone transfer facilities; Determining a drone failure rate on each of the drone delivery routes based on the delivery parameters; According to the drone failure rate of the drone delivery route, the number and location of the drone transfer facilities on the drone delivery route are corrected.

6. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps in the method according to any one of claims 1 to 4 are implemented.

7. A drone delivery system, characterized in that: The system includes a planning device, multiple target drones and multiple drone facilities. The planning device is used to execute the drone facility planning method as described in any one of claims 1 to 4 to determine the deployment strategy of the drone facilities.

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