An Unmanned Aerial Vehicle Multi-Floor Game Delivery Method and Delivery System under a Shadow-Part Occlusion Scenario

Abstract

The present invention discloses a method and a delivery system for multi-floor game delivery of an unmanned aerial vehicle in a scenario where a shaded part is blocked, including the following steps: Step 1, collect environmental parameters; Step 2, calculate the user parameters #imgabs1# of #imgabs0# floors, and re-sort the users on #imgabs3# floors in ascending order of the parameter #imgabs2# to form a new user set #imgabs4#; Step 3, according to the different sizes of the load value #imgabs5# of the unmanned aerial vehicle, give a closed solution of the optimal load quota resources obtained by the followers. The present invention can give a closed solution of the optimal load quota resources obtained by the users on each floor according to the different sizes of the load value of the unmanned aerial vehicle.

Description

Technical Field

[0001] The present invention relates to the technical field of unmanned aerial vehicle (UAV) flight logistics, and particularly to a method and system for UAV multi-floor game delivery in a scenario where a shaded area is blocked. Background Art

[0002] With the rapid development of UAV technology, UAV delivery service for different floors is a major innovation in the logistics industry, which relies on the rapid development of UAV technology and the intelligent upgrade of the logistics system. This service utilizes advanced UAV autonomous flight control technology, combined with high-precision navigation and positioning systems, enabling UAVs to fly stably in complex urban environments and accurately reach the designated floors. At the same time, UAVs are also equipped with lifting and loading systems, which can safely transport goods from the ground to the receiving points of high-rise buildings. In addition, the UAV 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 the delivery efficiency, reduces the labor cost, but also solves the problems in traditional logistics for high-rise building delivery. With the continuous progress of technology and the expansion of applications, UAV delivery service for different floors will bring more convenience and innovation to the logistics industry. When multiple users on different floors compete for the limited load capacity of UAV-delivered goods within the same delivery cycle, how to reasonably allocate the cargo load quota for these users on different floors is a key problem that urgently needs to be solved. Summary of the Invention

[0003] Object of the Invention: The present invention provides a method and system for UAV multi-floor game delivery in a scenario where a shaded area is blocked, which can give a closed solution of the optimal load quota resources obtained by users on each floor according to the different sizes of the UAV load value.

[0004] Technical Solution: A method for UAV multi-floor game delivery in a scenario where a shaded area is blocked according to the present invention includes the following steps:

[0005] Step 1: Collect environmental parameters;

[0006] Step 2: Calculate the user parameters of floors, and re-sort the users on floors in ascending order according to the parameter to form a new user set ; ;

[0007] Step 3: According to the different sizes of the UAV load value , give a closed solution of the optimal load quota resources obtained by the followers.

[0008] Further, in Step 1, when collecting environmental parameters, initialize the height of each floor , local acceleration of gravity , air density , the area and number of rotors of the UAV and , the flight speed of the UAV , the photoelectric conversion efficiency of the solar panel , the area of the solar panel carried by the UAV , sunlight irradiation intensity , the shadow height suffered by the target delivery building and the load capacity limit of the UAV .

[0009] Further, in step 2, calculate user parameters of floors , forming a new user set , that is .

[0010] Further, in step 3, if the load capacity limit of the UAV , the optimal load quota resource obtained by the follower is

[0011]

[0012] Further, in step 3, if the load capacity limit of the UAV , the optimal load quota resource obtained by the follower is

[0013]

[0014] and

[0015]

[0016] Further, if the load capacity limit of the UAV , then there is

[0017]

[0018] indicating that the UAV has no cargo load quota for sale, and thus users on each floor do not participate in the game.

[0019] Correspondingly, a UAV multi-floor game delivery system in a shaded area occlusion scenario 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 of floors , and re-sorts the users on floors in ascending order of the parameter , the resource allocation module gives the closed - form solution of the optimal load quota resources obtained by the followers according to the load value of the UAV. Based on the different sizes, it gives the closed - form solution of the optimal load quota resources obtained by the followers.

[0020] Beneficial effects: Compared with the prior art, the present invention has the following remarkable advantages: According to the load of the UAV value, it gives the closed - form solution of the optimal load quota resources obtained by users on each floor, with relatively low computational complexity. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] Figure 1 It is a schematic flowchart of the method of the present invention. DETAILED DESCRIPTION OF THE INVENTION

[0022] As Figure 1 shown, the UAV provides delivery services for users on different floors. Due to the obstruction of buildings, there is a shadow with a height of covering the target delivery building. In the present invention, it is assumed that the set of users for whom the UAV provides delivery services on different floors is , and the height of each user's floor is . Since traditional UAVs usually rely on battery power and have limited endurance, installing solar panels on the UAV can enable the UAV to absorb solar energy and convert it into electrical energy during flight to charge the UAV's battery. Therefore, if the height where the user is located is in the shadow, the UAV cannot receive sunlight radiation when delivering goods to this user.

[0023] In the present invention, due to the limited load of the UAV, when users on multiple different floors all need their goods to be delivered within the same delivery cycle, how the UAV reasonably allocates the load quota of goods for users on these floors is a key problem that urgently needs to be solved. At the same time, considering that users on each floor hope to purchase the load quota of the UAV's goods, so that the UAV can provide flight energy consumption for these users who obtain the quota to transport goods. Therefore, in the present invention, there is a competitive relationship among users on different floors in the issue of purchasing the limited load resources of the UAV's goods.

[0024] The Stackelberg game model is an asymmetric competition model in economics, proposed by the German economist Heinrich von Stackelberg in 1934. This model describes the dynamic game relationship between leaders and followers in the market. The leader takes the lead in acting, formulating output or price strategies, and the followers then adjust their behaviors according to the leader's decisions. This model is often used to analyze the strategic interactions among enterprises, especially in the case where one party holds a dominant position. The Stackelberg model emphasizes the order of decision-making. The leader's first-mover advantage enables it to maximize its own profit, while the followers respond passively. The core of the model lies in backward solving: the leader first predicts the reaction function of the followers and then optimizes its own decision based on this. After observing the leader's actions, the followers choose the optimal strategy to maximize their own profit. In the present invention, the UAV serves as the leader of the game model, and the users on each floor who only have partial information act as the followers.

[0025] The flight energy consumption for the UAV to transport goods to the th user in the set

[0026]

[0027] where is the load quota for the UAV to transport goods to the th user, is the local acceleration of gravity; and are the rotor area and the number of rotors respectively, and is the flight speed of the UAV.

[0028] Since the solar panels carried by the UAV itself can charge it, the output power of the solar panels is expressed as

[0029]

[0030] where is the photoelectric conversion efficiency of the solar panels; is the area of the solar panels carried by the UAV; is the sunlight intensity.

[0031] Therefore, the energy received from the sun by the UAV during the process of transporting goods to the th user in the set

[0032]

[0033] Among them, if , then represents the distance that the UAV flies in the sunlight. At this time, ; if , then represents that the UAV does not fly in the sunlight. At this time, .

[0034] When the quota for the UAV to transport goods for the th user in the set is , this user can not only obtain the flight energy benefit of the UAV, but may also receive the energy benefit from the sun. Model the game benefit of the th user in the set when purchasing the limited cargo load resource of the UAV as

[0035]

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

[0037]

[0038] Among them, represents the price per unit of cargo load sold by the leader to the th user in the set. It can be seen that as the follower purchases a larger quota of cargo load for delivery, the flight energy benefit it obtains also increases; at the same time, the higher the user is, the more likely the energy benefit from the sun it obtains will increase. However, the cost function it pays will also increase. For each follower in the game model, its goal is to obtain a higher game benefit at a lower cost in the game behavior.

[0039] And the leader in the game relationship sells the limited cargo load resource of the UAV to multiple competing users on different floors for the transportation of their goods. Therefore, the objective function in its game relationship is defined as the total cost paid by all competing users on different floors for purchasing the cargo load quotas they obtain, which is

[0040]

[0041] Also, due to the limited load of the UAV, there is a constraint at the leader in the game relationship as

[0042]

[0043] Among them, is the maximum payload of the UAV.

[0044] In the game, the UAV, as the leader, aims to obtain benefits by selling limited payload resources. Therefore, for the leader, there is

[0045]

[0046] s.t.

[0047] The profit optimization problems of the leader and multiple followers together constitute the game model. By the game actions of both sides of the game according to certain rules, the final equilibrium can be obtained, that is, the optimal unit resource price is obtained by maximizing the utility function of the leader selling limited payload resources using the traditional convex optimization method , and at the same time, the optimal payload quota resources are obtained by maximizing the profit obtained by the followers purchasing payload quotas , as follows:

[0048] Calculate the user parameters of floors , , and re - sort the users of floors in ascending order of the parameter to form a new user set , that is . In the present invention, the subscripts of the following users are all the subscripts of the users in the set

[0049] 1) If , then there is

[0050]

[0051] Thus, there is

[0052]

[0053] 2) If , then there is

[0054]

[0055] Thus, there is

[0056]

[0057] and

[0058]

[0059] Among them, represents the user set in the th user has no load quota.

[0060] 3) If , then there is

[0061]

[0062] It indicates that the drone sells without cargo load quota, and thus users on each floor do not participate in the game.

[0063] Correspondingly, a multi - floor game delivery system for drones in a shaded - part occlusion scenario includes: a parameter acquisition module, a floor sorting module, and a resource allocation module; the parameter acquisition module acquires environmental parameters, the floor sorting module calculates user parameters of floors and re - sorts the users of floors in ascending order of the parameter to form a new user set ; the resource allocation module gives the closed - form solution of the optimal load quota resources obtained by the followers according to the different magnitudes of the drone load value

Claims

1. A method for the multi-floor game delivery of drones in a scenario where the shaded part is blocked, characterized in that, It includes the following steps: Step 1: Collect environmental parameters; initialize the height of each floor , local gravitational acceleration , air density , the area and number of rotors of the drone and , the flight speed of the drone , the photoelectric conversion efficiency of the solar panel , the area of the solar panel carried by the UAV , sunlight irradiation intensity , the shadow height suffered by the target delivery building and the payload limit of the drone ; Step 2: Calculate the user parameters of floors, and re-sort the users of floors in ascending order of the parameters to form a new user set ; Calculate the user parameters of floors to form a new user set , that is ; Step 3: Based on the drone load value Depending on the size, give the closed solution of the optimal load quota resources obtained by the follower.

2. The method for the multi-floor game delivery of drones in the shaded area occlusion scenario according to claim 1, wherein In step 3, if the payload limit of the drone , the optimal payload quota resource obtained by the follower is 3. The method for the multi-floor game delivery of drones in the shaded area occlusion scenario according to claim 1, characterized in that, In step 3, if the payload limit of the drone , the optimal payload quota resource obtained by the follower is and 4. The method for multi-floor game delivery of drones in the scenario of shaded area occlusion as claimed in claim 1, wherein If the payload limit of the drone , then there is It shows that the drone sells without a cargo load quota, and thus users on each floor do not participate in the game.

5. A system for implementing the method for the multi - floor game delivery of drones in the shaded - part occlusion scenario as described in claim 1, characterized in that, It includes: a parameter acquisition module, a floor sorting module, and a resource configuration module; The parameter acquisition module acquires environmental parameters, and the floor sorting module calculates the user parameters of each floor and sorts the users on each floor again in ascending order of the parameters to form a new user set . The resource allocation module gives the closed solution of the optimal load quota resources obtained by the followers according to the different values of the drone load sizes.

Images