Logistics unmanned aerial vehicle distribution path dynamic planning method and device and storage medium

Abstract

The invention discloses a dynamic planning method for a distribution path of a logistics unmanned aerial vehicle, and the method comprises the following steps: obtaining distribution information inputted by a user, positioning a take-off and landing field and a distribution cabinet according to the distribution information, and generating a distribution route at the same time; generating a same-point transport increasing coverage area and a same-field transport increasing coverage area according to the distribution information; and when the matched transportation increasing distribution information is obtained, transportation increasing task data are called and deployed according to the distribution information and the transportation increasing distribution information, and the transportation increasing task data are distributed to the logistics unmanned aerial vehicle, so that the carrying capacity of the logistics unmanned aerial vehicle can be utilized to the maximum extent, the data volume of the unmanned aerial vehicle in the air is reduced, and redundant and repeated route conflicts are avoided.

Description

Technical Field

[0002] The present invention relates to a method, device and storage medium for dynamically planning the delivery path of a logistics drone. Background Art

[0003] In recent years, the logistics delivery by drones has developed rapidly. Currently, the basic elements of urban logistics delivery by drones are logistics drones + drone takeoff and landing sites + drone logistics delivery cabinets. The performance parameters of conventional logistics drones are: cruising speed of about 15 m / s, maximum load of about 10 KG, flight duration of about 30 minutes under full load, maximum safe flight distance of 20 km, and conventional cruising altitude of 120 meters; the drone takeoff and landing sites are fixed points scattered within the urban area, where the batteries of the drones are replaced and maintenance is carried out. According to the endurance of conventional drones, a drone takeoff and landing site can serve a radius of 10 KM; the drone logistics delivery cabinet is the starting point or the end point of the goods delivery. Drones can take off and land on the top of the delivery cabinet. The drones can automatically put the goods into the delivery cabinet, and users can pick up the goods from the delivery cabinet or put the goods to be delivered into the delivery cabinet.

[0004] The existing conventional process is as follows: The user puts the goods into the delivery cabinet and enters the delivery destination. After the delivery cabinet receives the goods, it sends the weight of the goods and the delivery destination to the back-end system server to generate a corresponding pick-up code; after receiving the delivery request, the system operation staff allocates the corresponding drone and plans the flight route for goods delivery; after receiving the instruction, the drone takes off from the drone takeoff and landing site, flies to the pick-up point according to the planned flight route to pick up the goods, then flies to the delivery destination to put the goods, and returns to the nearest takeoff and landing site after putting the goods; the receiving user can normally pick up the goods after entering the pick-up code in the delivery cabinet.

[0005] Currently, in the urban scenario of drone logistics delivery under high density and high frequency, it is necessary to maximize the cargo capacity of the drones. The existing drone delivery scheduling is all for single drone and single cargo delivery. Under the trend of high-density and high-frequency delivery orders, the delivery capacity of the drones cannot be maximally utilized. In the case of single drone and single delivery route, the air routes will be congested, affecting the delivery efficiency. Summary of the Invention

[0006] The main purpose of the present invention is to provide a method, device and storage medium for dynamically planning the delivery path of a logistics drone, aiming to solve the above technical problems.

[0007] To achieve the above purpose, the present invention provides a method for dynamically planning the delivery path of a logistics drone.

[0008] The method for dynamically planning the delivery path of the logistics drone includes the following steps: Obtain the delivery information input by the user, locate the takeoff and landing site and the delivery cabinet according to the delivery information, and generate a delivery route at the same time; Generate a same-point additional transportation coverage area and a same-site additional transportation coverage area according to the delivery information; When obtaining matching additional transportation delivery information, retrieve and deploy additional transportation task data according to the delivery information and the additional transportation delivery information, and dispatch the additional transportation task data to the logistics drone.

[0009] In one embodiment, the step of generating a same-point additional transportation coverage area and a same-site additional transportation coverage area according to the delivery information includes: Obtain the remaining carrying capacity of the logistics drone according to the delivery information; Generate a same-point additional transportation coverage area and a same-site additional transportation coverage area based on the remaining carrying capacity of the logistics drone; Encode the same-point additional transportation coverage area and the same-site additional transportation coverage area.

[0010] In one embodiment, both the same-point additional transportation coverage area and the same-site additional transportation coverage area are circular coverage areas with the center located on the delivery route.

[0011] In one embodiment, the step of retrieving and deploying additional transportation task data according to the delivery information and the additional transportation delivery information includes: Match the additional transportation delivery information with the encoding of the same-point additional transportation coverage area, and after successful matching, judge whether the destination of the additional transportation delivery information is the same delivery cabinet as the destination of the delivery information; If so, judge whether the departure location of the additional transportation delivery information is within the same-point additional transportation coverage area; If so, add the current additional transportation delivery information to the corresponding delivery route.

[0012] In one embodiment, the step of retrieving and deploying additional transportation task data according to the delivery information and the additional transportation delivery information includes: If the destination of the additional transportation delivery information is not the same delivery cabinet as the destination of the delivery information, match the additional transportation delivery information with the encoding of the same-site additional transportation coverage area; Judge whether the departure location of the additional transportation delivery information is covered by the same-site additional transportation coverage area; If so, add the current additional transportation delivery information to the corresponding delivery route.

[0013] In one embodiment, after the step of, when obtaining matching additional transportation delivery information, retrieving and deploying additional transportation task data according to the delivery information and the additional transportation delivery information, and dispatching the additional transportation task data to the logistics drone, the method further includes: Recalculate the remaining carrying capacity and update and re-encode the same-point additional transportation coverage area and the same-site additional transportation coverage area.

[0014] In addition, to achieve the above object, the present invention also provides a device for dynamically planning the delivery path of a logistics UAV. The device for dynamically planning the delivery path of a logistics UAV includes: a memory, a processor, and a program for dynamically planning the delivery path of a logistics UAV stored on the memory and executable on the processor. When the program for dynamically planning the delivery path of a logistics UAV is executed by the processor, the steps of the method for dynamically planning the delivery path of a logistics UAV as described above are implemented.

[0015] In addition, to achieve the above object, the present invention also provides a computer-readable storage medium. A program for dynamically planning the delivery path of a logistics UAV is stored on the computer-readable storage medium. When the program for dynamically planning the delivery path of a logistics UAV is executed by a processor, the steps of the method for dynamically planning the delivery path of a logistics UAV as described above are implemented.

[0016] The beneficial effects that the present invention can achieve: A method for dynamically planning the delivery path of a logistics UAV proposed in an embodiment of the present invention obtains the delivery information input by a user, locates the takeoff and landing site and the delivery cabinet according to the delivery information, and simultaneously generates a delivery route; generates a same-point additional transportation coverage area and a same-site additional transportation coverage area according to the delivery information; when obtaining matching additional transportation delivery information, retrieves and deploys additional transportation task data according to the delivery information and the additional transportation delivery information, and distributes the additional transportation task data to the logistics UAV, which can maximize the utilization of the carrying capacity of the logistics UAV, reduce the amount of data of the UAV in the air, and avoid redundant and repeated route conflicts. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 is a schematic structural diagram of a device in the hardware operating environment related to the solution of the embodiment of the present invention; Figure 2 is a schematic flowchart of an embodiment of the method for dynamically planning the delivery path of a logistics UAV of the present invention; Figure 3 is a schematic diagram of the delivery information and the delivery route of the present invention; Figure 4 is a schematic diagram of the same-point additional transportation coverage area of the present invention; Figure 5 is a schematic diagram of the same-site additional transportation coverage area of the present invention; Figure 6 is a schematic diagram of the path points after additional transportation of the present invention.

[0018] The realization, functional features, and advantages of the object of the present invention will be further described in conjunction with the embodiments with reference to the accompanying drawings. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0019] It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0020] As shown Figure 1 in Figure 1 Figure 1, it is a schematic diagram of the terminal structure of the hardware operating environment involved in the embodiment of the present invention.

[0021] The terminal in the embodiment of the present invention can be a PC, or a smart phone, a tablet computer, an e-book reader, an MP3 (Moving Picture Experts Group Audio Layer III) player, an MP4 (Moving Picture Experts Group Audio Layer IV) player, a portable computer and other movable terminal devices with a display function. And the terminal device in the embodiment of the present invention can be installed on a logistics UAV to realize the automated distribution and scheduling of the logistics UAV.

[0022] As shown Figure 1 in

[0023] Optionally, the terminal may further include a camera, an RF (Radio Frequency) circuit, sensors, an audio circuit, a WiFi module, etc. Among them, the sensors include, for example, a light sensor, a motion sensor, and other sensors. Specifically, the light sensor may include an ambient light sensor and a proximity sensor. Among them, the ambient light sensor can adjust the brightness of the display screen according to the brightness of the ambient light, and the proximity sensor can turn off the display screen and / or the backlight when the mobile terminal is moved to the ear. As a kind of motion sensor, the gravity acceleration sensor can detect the magnitude of the acceleration in each direction (generally three axes). When stationary, it can detect the magnitude and direction of gravity and can be used for applications that identify the posture of the mobile terminal (such as horizontal and vertical screen switching, related games, magnetometer posture calibration), vibration recognition related functions (such as pedometer, tapping), etc. Of course, the mobile terminal can also be configured with other sensors such as a gyroscope, a barometer, a hygrometer, a thermometer, an infrared sensor, etc., which will not be elaborated here.

[0024] Those skilled in the art can understand that Figure 1 the terminal structure shown in

[0025] does not limit the terminal and may include more or fewer components than shown in the figure, or combine some components, or have different component arrangements. Figure 1 As shown in

[0026] In the terminal shown in Figure 1 , the network interface 1004 is mainly used to connect to the background server and communicate with the background server for data; the user interface 1003 is mainly used to connect to the client (user side) and communicate with the client for data; and the processor 1001 can be used to call the logistics UAV delivery path dynamic planning program stored in the memory 1005 and perform the following operations: Obtain the delivery information input by the user, locate the takeoff and landing site and the delivery cabinet according to the delivery information, and generate a delivery route at the same time; Generate a same-point additional transportation coverage area and a same-site additional transportation coverage area according to the delivery information; When obtaining the matching additional transportation delivery information, retrieve the deployed additional transportation task data according to the delivery information and the additional transportation delivery information, and dispatch the additional transportation task data to the logistics UAV.

[0027] Furthermore, the processor 1001 can call the logistics UAV delivery path dynamic planning program stored in the memory 1005 and also perform the following operations: Obtain the remaining transport capacity of the logistics UAV according to the delivery information; Generate the same - point additional - transport coverage area and the same - field additional - transport coverage area based on the remaining capacity of the logistics UAV; Encode the same - point additional - transport coverage area and the same - field additional - transport coverage area.

[0028] Furthermore, the processor 1001 can call the logistics UAV delivery path dynamic programming program stored in the memory 1005 and also perform the following operations: Match the additional - transport delivery information with the encoding of the same - point additional - transport coverage area. After successful matching, determine whether the destination of the additional - transport delivery information is the same delivery cabinet as the destination of the delivery information; If so, determine whether the departure location of the additional - transport delivery information is within the same - point additional - transport coverage area; If so, add the current additional - transport delivery information to the corresponding delivery route.

[0029] Furthermore, the processor 1001 can call the logistics UAV delivery path dynamic programming program stored in the memory 1005 and also perform the following operations: If the destination of the additional - transport delivery information is not the same delivery cabinet as the destination of the delivery information, then match the additional - transport delivery information with the encoding of the same - field additional - transport coverage area; Determine whether the departure location of the additional - transport delivery information is covered by the same - field additional - transport coverage area; If so, add the current additional - transport delivery information to the corresponding delivery route.

[0030] Furthermore, the processor 1001 can call the logistics UAV delivery path dynamic programming program stored in the memory 1005 and also perform the following operations: Recalculate the remaining capacity and update and re - encode the same - point additional - transport coverage area and the same - field additional - transport coverage area.

[0031] The specific embodiments of the present invention applying the data storage device are basically the same as those of the following embodiments of the logistics UAV delivery path dynamic programming method, and will not be elaborated here.

[0032] Refer to Figure 2-3 , the first embodiment of the present invention provides a logistics UAV delivery path dynamic programming method, and the logistics UAV delivery path dynamic programming method includes: Obtain the delivery information input by the user, locate the take - off and landing site and the delivery cabinet according to the delivery information, and generate a delivery route at the same time; Generate the same - point additional - transport coverage area and the same - field additional - transport coverage area according to the delivery information; When obtaining the matching additional - transport delivery information, retrieve the deployed additional - transport task data according to the delivery information and the additional - transport delivery information, and dispatch the additional - transport task data to the logistics UAV.

[0033] In this embodiment, the deployment points of the takeoff and landing site and the logistics distribution cabinet are as follows Figure 3 The blue dots starting with H shown represent the location of a distribution cabinet. The distribution cabinet will dynamically adjust its location and the number of cabinets according to demand; the area covered by the blue circle represents a takeoff and landing site, and a takeoff and landing site will cover the distribution cabinets within a certain radius range. In this embodiment, the radius range is set to 1 KM. When setting up the distribution cabinet, the system will synchronously configure the distance between the distribution cabinet and the corresponding takeoff and landing site. For example, for H1001, the system will store its distance from the corresponding takeoff and landing site 1 as 600 meters (including climb and descent distances).

[0034] In one embodiment, the step of generating the same-point additional transportation coverage area and the same-site additional transportation coverage area according to the distribution information includes: Obtaining the remaining carrying capacity of the logistics UAV according to the distribution information; Generating the same-point additional transportation coverage area and the same-site additional transportation coverage area based on the remaining carrying capacity of the logistics UAV; Encoding the same-point additional transportation coverage area and the same-site additional transportation coverage area.

[0035] Obtain the distribution information entered by the user in the distribution cabinet: cargo weight 2KG; distribution distance 12446m; the corresponding coordinates of the pick-up distribution cabinet H1001 are (120.08262634, 30.31487631), the target end distribution cabinet is H12001 with corresponding coordinates (120.195923, 30.260897), the distance between H1001 and the corresponding takeoff and landing site is 600 meters, and the distance between H12001 and the corresponding UAV takeoff and landing site is 900 meters.

[0036] According to the above information (initial distribution task), dispatch a UAV from takeoff and landing site 1 to execute the distribution task, and calculate the current remaining carrying capacity of the UAV: maximum 10000g - 2000g = 8000g, remaining transportation distance: 20000m (longest transportation distance) - 600m (from takeoff and landing site to pick-up point) - 12446m (flight path distance) = 6954m, generate distribution task data, and assume the corresponding flight path task number is F12112121.

[0037] Please refer to Figure 4-5 According to the distribution information, the same-point additional transportation coverage area and the same-site additional transportation coverage area can be generated.

[0038] If the distribution destination is the same distribution cabinet, and the target distribution cabinet is the same H12001, with a distance of 900m from the takeoff and landing site, then the remaining distance is 6054m.

[0039] Round-trip distance (6054m - descent 120m - climb 120m) = 5814m, then the radius of the additional transportation coverage circle is 2907m. Then, a same-point additional transportation coverage area is generated with a center point every 2907m within the flight path distance.

[0040] Three same - point increased - transport coverage areas can be obtained through calculation and marked with the same - point increased - transport distribution code. The rule of the same - point increased - transport distribution code is: take - off and landing field number - distribution cabinet number - remaining load - route number, that is, 12 - H12001 - 8000 - F12112121. The corresponding data sets of the center points of the three increased - transport coverage areas (longitude, latitude, radius) are: (120.109577, 30.302095, 2907), (120.136528, 30.289307, 2907), (120.164294, 30.276046, 2907).

[0041] Generate the data of the maximum same - field increased - transport coverage area for the take - off and landing field 12 where the delivery destination belongs to the same take - off and landing field.

[0042] The target distribution cabinets are all within the coverage range of the take - off and landing field 12. For the path of distribution cabinets A -> distribution cabinet B -> landing at the take - off and landing field point within the same take - off and landing field, the longest path is 3 radii, that is, 3000m, and the remaining available transport distance is 3954m; 3954m - 120m - 120m = 3714m. Then the radius of the increased - transport coverage area circle is 1857m. A center point is generated every 1857m within the route distance to form the same - field increased - transport coverage area, with a total of 5.

[0043] Five same - field increased - transport coverage areas (circles) are obtained through calculation and marked with the same - field increased - transport distribution code. The rule is: take - off and landing field number - remaining load - route number: 12 - 8000 - F31211212. The corresponding data sets of the center points of the increased - transport coverage areas are: (120.099750, 30.306859, 1857), (120.117087, 30.298555, 1857), (120.134329, 30.290315, 1857), (120.151548, 30.282091, 1857), (120.168886, 30.273771, 1857).

[0044] Based on the above - mentioned embodiments, the steps of retrieving and deploying the increased - transport task data according to the delivery information and the increased - transport delivery information are specifically as follows: Match the increased - transport delivery information with the code of the same - point increased - transport coverage area. After successful matching, judge whether the destination of the increased - transport delivery information is the same distribution cabinet as the destination of the delivery information; If so, judge whether the departure location of the increased - transport delivery information is within the same - point increased - transport coverage area; If so, add the current increased - transport delivery information to the corresponding delivery route.

[0045] If the destination of the additional transportation and delivery information is not the same delivery cabinet as the destination of the delivery information, then match according to the additional transportation and delivery information and the code of the on-site additional transportation coverage area; Determine whether the departure location of the additional transportation and delivery information is covered by the on-site additional transportation coverage area; If so, add the current additional transportation and delivery information to the corresponding delivery route.

[0046] Specifically, after the delivery plan is generated, the drone takes off normally and starts to execute the delivery task. When a new delivery request appears, check whether it can be added to the existing delivery route task according to the following rules: The target delivery cabinet of the new delivery order is H12001, and the weight of the order goods is 3000g; Search for a load capacity greater than 3000g from the codes of the same-point additional transportation and delivery areas of 12-H12001; If there is an available code for the same-point additional transportation and delivery area, then determine whether the departure delivery cabinet location of the new delivery order is within the coverage range, and traverse the coverage in order from the set; If it is within the range, add the current additional transportation task to the corresponding route task. The route change method is to add a round trip between the corresponding additional transportation coverage area dot coordinates and the delivery pick-up point, as Figure 6 shown. The original route is AD, and the changed route is AB-BC-CB-BD.

[0047] If it is not within the coverage range or no available corresponding code can be found in the same-point additional transportation and delivery area, then search from the set of on-site additional transportation and delivery area codes; If an available on-site additional transportation and delivery area code is found and the departure delivery cabinet of the new delivery order is within the coverage range, then add the current additional transportation task to the corresponding route task. After the addition is successful, recalculate the remaining additional transportation capacity, update the data of the corresponding same-point additional transportation area of the current route according to the above steps, the delivery cabinet number is the target delivery cabinet number of the new delivery order, and at the same time update the data of the corresponding on-site additional transportation area of the current route.

[0048] In addition, if no corresponding additional allocation code is found, arrange a new drone for delivery from the corresponding take-off and landing site, and generate the same-point additional transportation and delivery code and on-site additional transportation and delivery code, as well as the corresponding additional transportation coverage range data according to the above steps.

[0049] During the flight of the drone, the system determines whether it has reached the center point of the additional transportation coverage area according to the received real-time longitude and latitude data of the drone. If it has passed, the corresponding data needs to be removed.

[0050] In addition, an embodiment of the present invention also proposes a computer-readable storage medium, on which a logistics drone delivery path dynamic planning program is stored. When the logistics drone delivery path dynamic planning program is executed by a processor, the following operations are implemented: Obtain the delivery information input by the user, locate the takeoff and landing site and the delivery cabinet according to the delivery information, and generate a delivery route at the same time; Generate a same-point additional transportation coverage area and a same-site additional transportation coverage area according to the delivery information; When obtaining the matching additional transportation delivery information, retrieve the deployed additional transportation task data according to the delivery information and the additional transportation delivery information, and dispatch the additional transportation task data to the logistics drone.

[0051] Furthermore, when the logistics drone delivery path dynamic programming program is executed by the processor, the following operations are also implemented: Obtain the remaining carrying capacity of the logistics drone according to the delivery information; Generate a same-point additional transportation coverage area and a same-site additional transportation coverage area based on the remaining carrying capacity of the logistics drone; Encode the same-point additional transportation coverage area and the same-site additional transportation coverage area.

[0052] Furthermore, when the logistics drone delivery path dynamic programming program is executed by the processor, the following operations are also implemented: Match the additional transportation delivery information with the encoding of the same-point additional transportation coverage area, and after successful matching, determine whether the destination of the additional transportation delivery information is the same delivery cabinet as the destination of the delivery information; If so, determine whether the departure location of the additional transportation delivery information is within the same-point additional transportation coverage area; If so, add the current additional transportation delivery information to the corresponding delivery route.

[0053] Furthermore, when the logistics drone delivery path dynamic programming program is executed by the processor, the following operations are also implemented: If the destination of the additional transportation delivery information is not the same delivery cabinet as the destination of the delivery information, then match the additional transportation delivery information with the encoding of the same-site additional transportation coverage area; Determine whether the departure location of the additional transportation delivery information is covered by the same-site additional transportation coverage area; If so, add the current additional transportation delivery information to the corresponding delivery route.

[0054] Furthermore, when the logistics drone delivery path dynamic programming program is executed by the processor, the following operations are also implemented: Recalculate the remaining carrying capacity and update and re-encode the same-point additional transportation coverage area and the same-site additional transportation coverage area.

[0055] The specific embodiments of the computer-readable storage medium of the present invention are basically the same as those of the above-mentioned embodiments of the logistics drone delivery path dynamic programming method, and will not be elaborated here.

[0056] It should be noted that in this article, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, such that a process, method, article or system comprising a series of elements not only includes those elements but also other elements not explicitly listed, or further includes elements inherent to such process, method, article or system. Without further limitation, an element defined by the phrase "comprising one..." does not exclude the existence of additional identical elements in the process, method, article or system comprising such element.

[0057] The serial numbers of the above embodiments of the present invention are only for description and do not represent the superiority or inferiority of the embodiments.

[0058] Through the description of the above embodiments, those skilled in the art can clearly understand that the above-described embodiment methods can be implemented by means of software plus a necessary general hardware platform. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation. Based on such an understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium as described above (such as ROM / RAM, magnetic disk, optical disc) and includes several instructions to enable a terminal device (which can be a mobile phone, computer, server, air conditioner, or network device, etc.) to execute the methods described in various embodiments of the present invention.

[0059] The above are only the preferred embodiments of the present invention and do not limit the patent scope of the present invention accordingly. Any equivalent structural or equivalent process transformation made by using the specification and drawings of the present invention, or directly or indirectly applied in other related technical fields, shall equally be included in the patent protection scope of the present invention.

Claims

1. A method for dynamic planning of logistics drone delivery paths, characterized in that: The method for dynamically planning the logistics drone delivery path includes the following steps: Obtain the delivery information entered by the user, locate the take-off and landing field and delivery cabinet based on the delivery information, and generate the delivery route; Generate same-point additional transportation coverage area and same-field additional transportation coverage area based on delivery information; When the matching additional transportation and delivery information is obtained, the additional transportation task data is retrieved and deployed according to the delivery information and the additional transportation and delivery information, and the additional transportation task data is dispatched to the logistics drone.

2. The method for dynamic planning of logistics drone delivery paths according to claim 1, characterized in that: The step of generating the same-point additional transportation coverage area and the same-field additional transportation coverage area according to the delivery information comprises: Determine the remaining transport capacity of the logistics drone based on the delivery information; Generate same-point additional transportation coverage area and same-field additional transportation coverage area based on the remaining transportation capacity of logistics drones; The increased transportation coverage areas at the same point and the increased transportation coverage areas at the same field are coded.

3. The method for dynamic planning of logistics drone delivery paths according to claim 2 is characterized in that: The same-point additional transportation coverage area and the same-field additional transportation coverage area are both circular coverage areas with their centers located on the distribution route.

4. The method for dynamic planning of logistics drone delivery paths as claimed in claim 2, characterized in that: The step of retrieving and deploying the increased transportation task data according to the delivery information and the increased transportation delivery information comprises: Match the additional transport information with the code of the additional transport coverage area at the same point, and after the match is successful, determine whether the destination of the additional transport information is the same delivery cabinet as the destination of the delivery information; If so, determine whether the departure location of the additional transportation delivery information is within the same-point additional transportation coverage area; If yes, the current additional delivery information will be added to the corresponding delivery route.

5. The method for dynamic planning of logistics drone delivery paths according to claim 4 is characterized in that: The step of retrieving and deploying the increased transportation task data according to the delivery information and the increased transportation delivery information comprises: If the destination of the additional delivery information is not the same delivery cabinet as the destination of the delivery information, the additional delivery information is matched with the code of the additional delivery coverage area in the same field; Determine whether the departure location of the additional transportation information is covered by the additional transportation coverage area of ​​the same venue; If yes, the current additional delivery information will be added to the corresponding delivery route.

6. The method for dynamic planning of logistics drone delivery paths according to claim 4 is characterized in that: After the step of acquiring the matching increased transportation delivery information, retrieving and deploying increased transportation task data according to the delivery information and the increased transportation delivery information, and dispatching the increased transportation task data to the logistics drone, the method further includes: Recalculate the remaining capacity and update and recode the increased transportation coverage areas at the same point and the increased transportation coverage areas at the same field.

7. A logistics drone delivery path dynamic planning device, characterized in that: The logistics drone delivery path dynamic planning device includes: a memory, a processor, and a logistics drone delivery path dynamic planning program stored in the memory and executable on the processor. When the logistics drone delivery path dynamic planning program is executed by the processor, the steps of the logistics drone delivery path dynamic planning method as described in any one of claims 1 to 6 are implemented.

8. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a logistics drone delivery path dynamic planning program, and when the logistics drone delivery path dynamic planning program is executed by the processor, the steps of the logistics drone delivery path dynamic planning method as described in any one of claims 1 to 6 are implemented.

Images