Unmanned aerial vehicle multi-floor game delivery method and delivery system in shadow part shielding scene

Abstract

The invention discloses an unmanned aerial vehicle multi-floor game delivery method and delivery system in a shadow part shielding scene. The method comprises the following steps: step 1, acquiring environmental parameters; step 2, calculating a user parameter # imgabs1 # of the # imgabs0 # floor, and sorting the users of the # imgabs3 # floor again according to an ascending sequence of the parameter # imgabs2 # to form a new user set # imgabs4 #; and step 3, giving a closed solution of the optimal load quota resource obtained by the follower according to the difference of the load value # imgabs5 # of the unmanned aerial vehicle. According to the method, the closed solution of the optimal load quota resource obtained by each floor user can be given according to different load values of the unmanned aerial vehicle.

Description

Technical Field

[0001] The present invention relates to the technical field of drone flight logistics, and in particular to a drone multi-floor game delivery method and a delivery system in a scene where a shadow partially blocks the scene. Background Art

[0002] With the rapid development of drone technology, drone delivery service on different floors is a major innovation in the logistics industry. It relies on the rapid development of drone technology and the intelligent upgrade of logistics systems. This service uses advanced drone autonomous flight control technology, combined with high-precision navigation and positioning systems, to enable drones to fly stably in complex urban environments and accurately reach designated floors. At the same time, drones are also equipped with lifting and loading systems to safely transport goods from the ground to the receiving point of high-rise buildings. In addition, the drone delivery system also has real-time monitoring and cargo tracking functions to ensure the safety and timely delivery of goods. The application of this technology not only improves delivery efficiency and reduces labor costs, but also solves the difficulties of traditional logistics in high-rise building delivery. With the continuous advancement of technology and the expansion of applications, drone delivery service on different floors will bring more convenience and innovation to the logistics industry. When users on multiple floors compete for the limited drone delivery cargo load in the same delivery cycle, how drones can reasonably allocate cargo load quotas to users on these floors is a key issue that needs to be solved urgently. Summary of the invention

[0003] Purpose of the invention: The present invention provides a drone multi-floor game delivery method and delivery system in a shadow-partially obscured scene, which can provide a closed solution for the optimal load quota resources obtained by users on each floor according to the different load values ​​of the drone.

[0004] Technical solution: The method for delivering goods by drone on multiple floors in a scene with partial shadow occlusion described in the present invention comprises the following steps:

[0005] Step 1: Collect environmental parameters;

[0006] Step 2: Calculation User parameters for each floor , and follow the parameters Ascending order of The users on each floor are sorted again to form a new user set ;

[0007] Step 3: According to the drone load value The closed solution of the optimal load quota resources obtained by followers is given for different sizes.

[0008] Furthermore, in step 1, environmental parameters are collected to initialize the height of each floor , local gravity acceleration , air density , UAV rotor area and number of rotors and , the flight speed of the drone , Photovoltaic conversion efficiency of solar panels 、The area of ​​solar panels carried by the UAV , Sunlight intensity , the shadow height of the target delivery building And the upper limit of the drone's cargo capacity .

[0009] Furthermore, in step 2, calculate User parameters for each floor , , forming a new user set ,Right now .

[0010] Furthermore, in step 3, if the drone's cargo capacity is , the optimal load quota resource obtained by the follower is

[0011]

[0012] Furthermore, in step 3, if the drone's cargo capacity is , the optimal load quota resource obtained by the follower is

[0013]

[0014] and

[0015]

[0016] Furthermore, if the drone's cargo capacity is , then

[0017]

[0018] This indicates that there are no cargo load quotas for sale for drones, and thus users on all floors do not participate in the game.

[0019] Accordingly, a drone multi-floor game delivery system in a shadow-partially blocked scene includes: a parameter acquisition module, a floor sorting module and a resource allocation module; the parameter acquisition module acquires environmental parameters, and the floor sorting module calculates User parameters for each floor , and follow the parameters Ascending order of The users on each floor are sorted again to form a new user set , the resource allocation module is based on the drone load value The closed solution of the optimal load quota resources obtained by followers is given for different sizes.

[0020] Beneficial effects: Compared with the prior art, the present invention has the following significant advantages: The difference in value size gives a closed-form solution for the optimal load quota resources obtained by users on each floor, which has a lower computational complexity. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] Figure 1 It is a schematic diagram of the method flow of the present invention. DETAILED DESCRIPTION

[0022] like Figure 1 As shown in the figure, the drone provides delivery services to users on different floors. Due to the obstruction of buildings, there is a height of In the present invention, it is assumed that the user set for which the drone provides delivery services on different floors is , the floor height of each user is Since traditional drones are usually powered by batteries and have limited flight time, installing solar panels on drones allows the UAV to absorb solar energy and convert it into electricity during flight to charge the drone's battery. Therefore, if the user is in the shadow at a certain height, the drone will not receive sunlight when delivering goods to the user.

[0023] In the present invention, due to the limited load capacity of the UAV, when users on multiple floors all need to have their goods delivered in the same delivery cycle, how the UAV can reasonably allocate cargo load quotas to the users on these floors is a key issue that needs to be solved urgently. At the same time, considering that users on each floor want to purchase the cargo load quota of the UAV, the UAV can provide flight energy consumption for these users who have obtained the quota in order to deliver the goods. Therefore, in the present invention, users on different floors are in a competitive relationship with each other in terms of purchasing the limited cargo load resources of the UAV.

[0024] The Stackelberg game model is an asymmetric competition model in economics, proposed by German economist Heinrich von Stackelberg in 1934. The model describes the dynamic game relationship between leaders and followers in the market. The leader takes the lead and formulates a production or price strategy, and the followers then adjust their behavior according to the leader's decision. This model is often used to analyze strategic interactions between companies, especially when one party is dominant. The Stackelberg model emphasizes the order of decision-making. The leader's first-mover advantage enables it to maximize its own profits, while the followers respond passively. The core of the model lies in the reverse solution: the leader first predicts the follower's reaction function, and then optimizes its own decision based on this. After observing the leader's actions, the follower chooses the optimal strategy to maximize its own profits. In the present invention, the UAV is used as the leader of the game model, and the users on each floor who only have partial information act as followers.

[0025] UAV for collection Middle The flight energy consumption of a user transporting goods is

[0026]

[0027] in, For drones The load quota for each user to transport goods, is the local gravitational acceleration; is the air density; and are the rotor area and the number of rotors and is the flight speed of the drone.

[0028] Since the UAV itself can be charged by the solar panels it carries, the output power of the solar panels is expressed as

[0029]

[0030] in, is the photoelectric conversion efficiency of the solar panel; The area of ​​solar panels carried by the UAV; The intensity of sunlight.

[0031] Therefore, UAV is a collection Middle The energy received from the sun by a user during the delivery of goods can be expressed as

[0032]

[0033] Among them, if ,but It is the distance the drone flies in the sunlight. ;like ,but Indicates that the drone is not flying in the sun. .

[0034] When UAV is a collection Middle The quota for shipping goods per user is When the user can not only obtain the flight energy of the UAV, but also receive energy from the sun, Middle The game profit model of a user in purchasing limited cargo load resources of UAV is:

[0035]

[0036] In the present invention, users on each floor hope to increase the cargo load resources allocated by the drone to them, so as to obtain higher game benefits. Therefore, the optimization problem of the follower in each game relationship is modeled as

[0037]

[0038] in, Indicates that the leader sells to the collection Middle The price per unit of cargo delivery load for each user. It can be seen that as the follower purchases more cargo delivery load quotas, the flight energy benefits they obtain also increase; at the same time, the higher the user's altitude, the greater the solar energy benefits they obtain. However, the cost function For each follower in the game model, the goal is to obtain higher game benefits at a lower cost in the game behavior.

[0039] The leader in the game relationship sells limited drone cargo load resources to multiple competing users on different floors for the transportation of their cargo. Therefore, the objective function in the game relationship is defined as the total price paid by all competing users on different floors to purchase their respective cargo load quotas, which is

[0040]

[0041] Since the UAV’s load capacity is limited, the leader in the game relationship has the constraint

[0042]

[0043] in, is the maximum payload of the UAV.

[0044] In the game, UAV, as the leader, aims to gain profits by selling limited load resources. Therefore, for the leader,

[0045]

[0046] st

[0047] The revenue optimization problem of the leader and multiple followers together constitutes a game model. The final equilibrium can be obtained by the two parties playing the game according to certain rules. That is, the optimal unit resource pricing is obtained by maximizing the utility function of the leader selling limited load resources using the traditional convex optimization method. , while maximizing the benefits of followers purchasing load quotas to obtain the optimal load quota resources , as detailed below:

[0048] calculate User parameters for each floor , , and follow the parameters Ascending order of The users on each floor are sorted again to form a new user set ,Right now In this invention, the following user subscripts are all sets User subscript in .

[0049] 1) If , then

[0050]

[0051] Thus, there is

[0052]

[0053] 2) If , then

[0054]

[0055] Thus, there is

[0056]

[0057] and

[0058]

[0059] in, Represents a user collection The No load quota for each user.

[0060] 3) If , then

[0061]

[0062] This indicates that there are no cargo load quotas for sale for drones, and thus users on all floors do not participate in the game.

[0063] Accordingly, a drone multi-floor game delivery system in a shadow-partially blocked scene includes: a parameter acquisition module, a floor sorting module and a resource allocation module; the parameter acquisition module acquires environmental parameters, and the floor sorting module calculates User parameters for each floor , and follow the parameters Ascending order of The users on each floor are sorted again to form a new user set , the resource allocation module is based on the drone load value The closed solution of the optimal load quota resources obtained by followers is given for different sizes.

Claims

1. A drone multi-floor game delivery method in a shadow-partially obscured scene, characterized in that: The steps include: Step 1: Collect environmental parameters; Step 2: Calculation User parameters for each floor , and follow the parameters Ascending order of The users on each floor are sorted again to form a new user set ; Step 3: According to the drone load value The closed solution of the optimal load quota resources obtained by followers is given for different sizes.

2. The drone multi-floor game delivery method in the shadow partial occlusion scene as claimed in claim 1 is characterized in that: In step 1, collect environmental parameters and initialize the height of each floor , local gravity acceleration , air density , UAV rotor area and number of rotors and , the flight speed of the drone , Photovoltaic conversion efficiency of solar panels 、The area of ​​solar panels carried by the UAV , Sunlight intensity , the shadow height of the target delivery building And the upper limit of the drone's cargo capacity .

3. The drone multi-floor game delivery method in the shadow partial occlusion scene as claimed in claim 1 is characterized in that: In step 2, calculate User parameters for each floor , , forming a new user set ,Right now .

4. The drone multi-floor game delivery method in a shadow-partially blocked scene as claimed in claim 1, characterized in that: In step 3, if the drone's cargo capacity is , the optimal load quota resource obtained by the follower is 5. The drone multi-floor game delivery method in a shadow-partially blocked scene as claimed in claim 1, characterized in that: In step 3, if the drone's cargo capacity is , the optimal load quota resource obtained by the follower is and 6. The drone multi-floor game delivery method in a shadow-partially blocked scene as claimed in claim 1, characterized in that: If the drone's cargo capacity is limited , then This indicates that there are no cargo load quotas for sale for drones, and thus users on all floors do not participate in the game.

7. A system for implementing the drone multi-floor game delivery method in a shadow-partially blocked scene as claimed in claim 1, characterized in that: include: Parameter collection module, floor sorting module and resource configuration module; The parameter collection module collects environmental parameters, and the floor sorting module calculates User parameters for each floor , and follow the parameters Ascending order of The users on each floor are sorted again to form a new user set , the resource allocation module is based on the drone load value The closed solution of the optimal load quota resources obtained by followers is given for different sizes.

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