Aircraft air-dropped material recovery method and device and computer equipment

Abstract

The invention relates to an aircraft air-dropped material recycling method and device and computer equipment. The method comprises the following steps: constructing a design variable of an optimal release point of the materials released by the aircraft; the design variables comprise release point coordinates and course angles; according to a motion equation of a material landing process and the design variable, establishing a relationship between the design variable and a landing point position vector; determining a drop point evaluation function according to a pre-acquired launching mode, simulating and calculating a drop point position vector corresponding to each course angle by adopting a course angle traversing mode, and selecting a corresponding course angle and a corresponding drop point position vector according to a drop point evaluation function optimization principle; and solving a traveling salesman problem by adopting a greedy algorithm, and traversing landing points of all the landing point position vectors to obtain an optimal path plan of material recovery. By adopting the method, the course angle can be dynamically adjusted according to the real-time environment data, and the material delivery requirement is met.

Description

Technical Field

[0001] The present application relates to the technical field of flight dynamic planning, and in particular to a method, device and computer equipment for recovering airdropped materials from an aircraft. Background Art

[0002] After a natural disaster (such as an earthquake, flood, or hurricane) occurs, timely delivery of supplies (e.g., food, medicine, tents, and other necessities) to the affected areas is crucial to saving lives and alleviating the disaster. Aircraft have been increasingly used in the field of disaster relief supplies delivery due to their high maneuverability, lack of influence from ground traffic conditions, and ability to quickly reach remote disaster-stricken areas.

[0003] Among the existing aircraft disaster relief material delivery technologies, path planning based on the traveling salesman problem (TSP) is a common method. TSP aims to find the shortest path for a traveling salesman to return to the starting city after visiting multiple cities. In the disaster relief scenario, each material delivery point is regarded as a "city". The aircraft starts from the material supply base and needs to visit these delivery points in turn and return to the base. However, after a natural disaster occurs, the environment in the disaster area is often highly uncertain, including meteorological conditions (such as strong winds, heavy rains, unstable airflow, etc.) and terrain changes (such as road damage, landslides causing terrain changes, etc.). The TSP problem is usually based on static geographic data and relatively stable environmental assumptions when planning the path. When faced with these uncertain factors, the actual flight path of the aircraft may deviate greatly from the planned path, affecting the accuracy and timeliness of material delivery. Summary of the invention

[0004] Based on this, it is necessary to provide a method, device and computer equipment for recovering airdropped materials from an aircraft to address the above technical problems.

[0005] A method for recovering airdropped materials from an aircraft, the method comprising:

[0006] Constructing design variables for the optimal release point of the aircraft for dropping materials; the design variables include the release point coordinates and the heading angle;

[0007] According to the motion equation of the material landing process and the design variables, the relationship between the design variables and the landing point position vector is established;

[0008] According to the pre-acquired delivery mode, the landing point evaluation function is determined, and the landing point position vector corresponding to each heading angle is simulated and calculated by traversing the heading angle, and the corresponding heading angle and the corresponding landing point position vector are selected according to the optimal principle of the landing point evaluation function;

[0009] The greedy algorithm is used to solve the traveling salesman problem to traverse the landing points of all landing position vectors to obtain the optimal path planning for material recovery.

[0010] In one embodiment, the design variables for constructing the best release point for the aircraft to release supplies include:

[0011] u=[x c ,y c ,ψ]

[0012] Among them, u represents the design variable, x c ,y c represents the coordinates of the release point, and ψ represents the heading angle.

[0013] In one embodiment, the motion equation of the material falling to the ground is:

[0014]

[0015] Among them, vv represents the mass center velocity vector of the material, represents the rate of change of the velocity vector of the center of mass, D is the air resistance, g is the acceleration of gravity, m is the mass of the material, ρ is the air density, R is the instantaneous projection radius of the parachute deployment, is the rate of change of the projection radius.

[0016] In one embodiment, the method further includes: determining a drop point evaluation function according to a pre-acquired delivery mode, including:

[0017] f(x I p1,x I p2, ..., x I p n ,u)

[0018] Among them, x I p i Represents the location vector of the i-th material on the ground;

[0019] Alternatively, according to the pre-acquired delivery mode, the drop point evaluation function is determined, including:

[0020]

[0021] Among them, n is the total number of airdropped supplies, x T is the target landing point coordinate vector.

[0022] In one embodiment, the method further includes: using a greedy algorithm to solve the traveling salesman problem to traverse the landing points of all landing point position vectors, and obtaining the optimal path planning for material recovery as follows:

[0023]

[0024] x ij ∈{0,1},i,j∈V

[0025] Among them, d ij represents the distance between the i-th and j-th drop points, x ij represents a decision variable, taking the value of 1 or 0, V represents a node set, and S is a subset of the node set V.

[0026] In one embodiment, the method further includes: using a greedy algorithm to solve the traveling salesman problem to traverse the landing points of all landing point position vectors, and obtaining the optimal path planning for material recovery as follows:

[0027]

[0028] ∑k j =n

[0029] in, They are the objective function of the path distance and the objective function of time during the jth departure of the vehicle, and x is the path and time Weighted sum, k j is the number of drop points traversed during the jth departure, d[i][j] is the distance between the i-th drop point and the j-th drop point, t[i][j] is the time interval between the i-th drop point and the j-th drop point, x[i] is the i-th material recovered, and x[i]-x[j] represents a path, where And when j≠i, x[i]≠x[j], v[x[j]] is the volume function of the jth material to be recycled in the path sequence, and the maximum volume that the vehicle can carry is V max , d[x[i]]][x[j]] represents the distance function between the i-th landing point and the j-th landing point, and t[x[i]][x[j]] is the time function between the i-th landing point and the j-th landing point.

[0030] An aircraft airdrop material recovery device, the device comprising:

[0031] A design variable construction module, used to construct design variables for the optimal release point of the aircraft to drop materials; the design variables include the release point coordinates and heading angle;

[0032] A relationship building module, used to establish a relationship between the design variables and the landing point position vector according to the motion equation of the material landing process and the design variables;

[0033] The landing evaluation module is used to determine the landing point evaluation function according to the pre-acquired delivery mode, simulate and calculate the landing point position vector corresponding to each heading angle by traversing the heading angle, and select the corresponding heading angle and the corresponding landing point position vector according to the optimal principle of the landing point evaluation function;

[0034] The planning module is used to solve the traveling salesman problem by using a greedy algorithm to traverse the landing points of all landing position vectors and obtain the optimal path planning for material recovery.

[0035] In one embodiment, the design variable construction module is also used to construct the design variables of the optimal release point of the aircraft dropping materials, including:

[0036] u=[x c ,y c ,ψ]

[0037] Among them, u represents the design variable, x c ,y c represents the coordinates of the release point, and ψ represents the heading angle.

[0038] A computer device comprises a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, the following steps are implemented:

[0039] Constructing design variables for the optimal release point of the aircraft for dropping materials; the design variables include the release point coordinates and the heading angle;

[0040] According to the motion equation of the material landing process and the design variables, the relationship between the design variables and the landing point position vector is established;

[0041] According to the pre-acquired delivery mode, the landing point evaluation function is determined, and the landing point position vector corresponding to each heading angle is simulated and calculated by traversing the heading angle, and the corresponding heading angle and the corresponding landing point position vector are selected according to the optimal principle of the landing point evaluation function;

[0042] The greedy algorithm is used to solve the traveling salesman problem to traverse the landing points of all landing position vectors to obtain the optimal path planning for material recovery.

[0043] A computer-readable storage medium stores a computer program, which, when executed by a processor, implements the following steps:

[0044] Constructing design variables for the optimal release point of the aircraft for dropping materials; the design variables include the release point coordinates and the heading angle;

[0045] According to the motion equation of the material landing process and the design variables, the relationship between the design variables and the landing point position vector is established;

[0046] According to the pre-acquired delivery mode, the landing point evaluation function is determined, and the landing point position vector corresponding to each heading angle is simulated and calculated by traversing the heading angle, and the corresponding heading angle and the corresponding landing point position vector are selected according to the optimal principle of the landing point evaluation function;

[0047] The greedy algorithm is used to solve the traveling salesman problem to traverse the landing points of all landing position vectors to obtain the optimal path planning for material recovery.

[0048] The above-mentioned aircraft airdrop material recovery method, device, computer equipment and storage medium, by taking the heading angle into consideration, can optimize the accuracy of material delivery based on the motion equation of the material landing process, so that the materials can land more accurately in the predetermined disaster area and avoid terrain obstacles. At the same time, this variable helps to optimize the distribution of material landing points, thereby shortening the ground recovery path and improving rescue efficiency. In terms of dealing with environmental uncertainties, the heading angle can be dynamically adjusted according to real-time environmental data to ensure the smooth progress of the material delivery mission. In addition, combined with the material needs of different disaster-stricken areas, flexible adjustment of the heading angle can meet diverse needs, and in terms of resource utilization, it can optimize the energy consumption and equipment utilization of the aircraft, so that the aircraft can play a greater role in disaster relief. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] Figure 1 A schematic diagram of a flow chart of a method for recovering aerial dropped materials from an aircraft in one embodiment;

[0050] Figure 2 A schematic diagram of a coordinate system definition for an airdrop release process in one embodiment;

[0051] Figure 3 It is a structural block diagram of an aircraft airdrop material recovery device in one embodiment;

[0052] Figure 4 FIG. 4 is a diagram showing the internal structure of a computer device in one embodiment. DETAILED DESCRIPTION

[0053] In order to make the purpose, technical solution and advantages of the present application more clearly understood, the present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0054] In one embodiment, Figure 1 As shown, a method for recovering airdropped materials from an aircraft is provided, comprising the following steps:

[0055] Step 102, constructing design variables for the optimal release point for dropping supplies from an aircraft.

[0056] The design variables include the release point coordinates and the heading angle.

[0057] In this step, different heading angles result in different distribution of material landing points. Therefore, the design of the heading angle can significantly improve the distribution results, which is more conducive to material recovery. On the other hand, for the uncertain factors of the delivery scene, real-time planning of the heading angle can also ensure the accuracy of the landing point distribution.

[0058] Step 104, based on the motion equation of the material landing process and the design variables, establish the relationship between the design variables and the landing point position vector.

[0059] In this step, since the landing point of material delivery is affected by various factors, the motion equation of the material landing process is considered. The mapping relationship between the release point coordinates and the ground is calculated through the motion equation of the material landing process. Therefore, when the heading angle is changed, the landing point information can be accurately predicted, which is convenient for the subsequent ground recovery efficiency.

[0060] Step 106, determine the landing point evaluation function according to the pre-acquired delivery mode, simulate and calculate the landing point position vector corresponding to each heading angle by traversing the heading angle, and select the corresponding heading angle and the corresponding landing point position vector according to the optimal principle of the landing point evaluation function.

[0061] In this step, different landing point evaluation functions can be designed for different delivery modes. The landing point evaluation function is an evaluation index for evaluating the proximity between the landing point and the expected landing point. Since the relationship between the design variables and the landing point position vector is established in advance, a simulation calculation method can be used to traverse each heading angle within the heading angle constraint to obtain the predicted landing point position vector, and then the landing point can be evaluated according to the landing point evaluation function, so as to optimize the optimal heading angle.

[0062] Step 108, using a greedy algorithm to solve the traveling salesman problem to traverse the landing points of all landing position vectors to obtain the optimal path planning for material recovery.

[0063] After the materials land, since all landing points are optimized through heading angle optimization, the greedy algorithm is used to solve the traveling salesman problem to traverse the landing points of all landing position vectors, which can realize the optimal path planning for material recovery.

[0064] In the above-mentioned method of recovering materials dropped by aircraft, by taking the heading angle into consideration, the accuracy of material delivery can be optimized based on the motion equation of the material landing process, so that the materials can land more accurately in the predetermined disaster-stricken area and avoid terrain obstacles. At the same time, this variable helps to optimize the distribution of material landing points, thereby shortening the ground recovery path and improving rescue efficiency. In terms of dealing with environmental uncertainties, the heading angle can be dynamically adjusted according to real-time environmental data to ensure the smooth progress of the material delivery mission. In addition, combined with the material needs of different disaster-stricken areas, flexible adjustment of the heading angle can meet diverse needs, and in terms of resource utilization, it can optimize the energy consumption and equipment utilization of drones, so that drones can play a greater role in disaster relief.

[0065] In one of the embodiments, the flight altitude of a general aircraft is fixed, and the flight altitude of the aircraft is not considered as an optimization design variable. In the process of using an uncontrolled parachute to airdrop supplies, the parachute system does not have autonomous maneuverability, so the only design variables that can be selected are the airdrop position and the flight direction of the aircraft. The design variables for the uncertainty optimization of the optimal release point are written as:

[0066] u=[x c ,y c ,ψ]

[0067] Among them, u represents the design variable, x c ,y c represents the release point coordinates, ψ represents the heading angle, as shown in the following example: Figure 2 shown.

[0068] The objective function and constraints of the uncertainty optimization of the airdrop release point need to be determined according to the specific application scenario, and its calculation needs to be combined with the dynamic model of the material airdrop process. In one embodiment, the motion equation of the material landing process is:

[0069]

[0070] Among them, vv represents the mass center velocity vector of the material, represents the rate of change of the velocity vector of the center of mass, D is the air resistance, g is the acceleration of gravity, m is the mass of the material, ρ is the air density, R is the instantaneous projection radius of the parachute deployment, is the rate of change of the projection radius.

[0071] Specifically, the air resistance D can be further expressed as

[0072] In the formula, C d is the air resistance coefficient, S is the resistance reference area, and the wind speed vector is w, then v ∞ It can be expressed as v ∞ =wv. The additional mass is generated by the forced motion of the air in the canopy, which can usually be calculated by multiplying the mass of the air contained in a sphere with the same radius as the parachute projection by a constant coefficient k. a To express

[0073] When there is wind field interference, the main parachute opening dynamics has a significant impact on the landing time and airdrop landing point. By summarizing a large amount of experimental data, an empirical formula for the change of drag area with opening time during the parachute opening process is proposed:

[0074]

[0075] Among them, Cd S0 is the steady-state drag area after inflation is completed, t0 is the parachute opening time, η is the ratio of the projected area when straightened to the fully expanded projected area, and t is the time from the start of inflation to the current moment.

[0076] Assuming that the canopy projection shape during the inflation process is approximately circular, we can further obtain that the rate of change of the canopy projection radius over time is

[0077] Among them, R0 is the projected radius of the canopy after it is fully inflated.

[0078] Based on the above results, projecting the vector form of the motion equations to the earth system can obtain the set of ordinary differential equations for the center of mass motion dynamics of the object-umbrella system.

[0079] In another embodiment, the purpose of the airdrop mission is to make the distance between the cargo and the ground recovery personnel as short as possible after landing, so as to facilitate the collection by the ground personnel. I p i is the location vector of the i-th cargo on the ground, then the landing point evaluation function can be expressed as

[0080] f(x I p1,x I p2, ..., x I p n ,u)

[0081] In a specific embodiment, n is the total number of airdropped goods. Taking fixed-point airdrop as an example, the drop point evaluation function can be calculated as follows:

[0082] where x T is the target point coordinate vector. Under uncertain conditions, x I p i are all random variables.

[0083] In summary, after establishing the motion equation of the material landing process and the landing point evaluation function, in the continuous cargo airdrop process, after the previous cargo leaves the cabin, the tow parachute of the next cargo is released and opened immediately. Therefore, the time when the previous cargo leaves the cabin determines the initial airdrop position of the next cargo. Due to the errors in the actual flight process, the actual initial airdrop release point may also be different from the calculated airdrop release point. The error of the airdrop release point is related to the current flight direction of the transport aircraft. In order to explore the influence of the heading angle of the transport aircraft on the recovery problem of multi-point cargo delivery, considering the influence of wind speed and uncertainty factors, we can take 1° as a step size, traverse all navigation directions, and obtain the range of airdrop release points according to the airdrop planning method under certain conditions.

[0084] In one embodiment, the problem of recycling landed materials can be regarded as a typical traveling salesman problem, which is a classic combinatorial optimization problem in graph theory. It can be transformed into the problem of finding a Hamiltonian circuit with the minimum weight in a weighted completely undirected graph and making the total weight of the circuit the minimum. Find the shortest traversal order to minimize the following objective function:

[0085]

[0086] where t i is the landing point of the airdrop cargo, and the subscripts 1 to n represent the number of landing points of the airdrop cargo. i , t i+1 ) represents the distance between point i and point i+1. d(t0, t i ) and d(t n , t0) represent the distance from the base to the first cargo drop point and the distance back to the destination after recovering the last cargo.

[0087] The shortest traversal sequence of a vehicle that recovers materials starts from the base, traverses all target locations once and only once, and finally returns to the starting point is expressed as F = (X[1], X[2], X[3]..., X[n]).

[0088]

[0089] ∑k j =n

[0090] They are the objective function of the path distance and the objective function of time during the vehicle's first departure, and x is the path and time The weighted sum is the objective function to be optimized. j is the number of drop points traversed during the jth departure, d[i][j] is the distance between the i-th drop point and the j-th drop point, t[i][j] is the time interval between the i-th drop point and the j-th drop point, x[i] is the i-th item recovered, and x[i]-x[j] represents a path, where And when j≠i, x[i]≠x[j], v[x[j]] is the volume function of the i-th cargo to be recovered in the path sequence, and the maximum volume that the delivery vehicle can carry is V max . d[x[i]][x[j]] represents the distance function between the ith landing point and the th landing point, and t[x[i]][x[j]] represents the time function between the ith landing point and the th landing point. t[x[i]][x[j]] is based on d[x[i]][x[j]]. The driving speed takes into account the terrain and road conditions of the mountainous area, and the driving speeds on different sections of the road are different.

[0091] The TSP problem of parachute airdrop cargo recovery of the present invention can be described as an airplane dropping cargo by parachute at high altitude at regular intervals, and the logistics personnel on the ground will set out from the base to collect all the cargo by vehicle and return to the base. The vehicle has a certain volume, and the cargo to be recovered has a certain volume. Only a fixed volume of cargo can be recovered at a time. After the recovered materials fill the vehicle, it must return to the base to unload the cargo before setting off again. The way to traverse the cargo landing points is not a simple straight line connection, but to travel along feasible roads in the actual terrain, and is affected by road conditions, terrain, etc. The condition for the shortest path for recovering cargo is described in the language of graph theory: in a weighted complete graph, find a Hamilton circuit with the minimum weight. Let G(V, E) be a weighted complete graph, V = (1, 2, ..., n) be a vertex set, E be an edge set, and the distance between each vertex is known: (d ij >0,d ii =0,i,j∈V).

[0092] The mathematical model of the TSP problem of collecting landed goods can be written in the form of a linear programming:

[0093]

[0094] x ij ∈∈{0,1},i,j∈V

[0095] Among them, j represents the distance between the i-th and j-th landing points, xi j represents a decision variable, taking the value of 1 or 0, V represents a node set, and S is a subset of the node set V.

[0096] It should be understood that although Figure 1 The steps in the flowchart are shown in sequence as indicated by the arrows, but these steps are not necessarily executed in the order indicated by the arrows. Unless otherwise specified in this document, there is no strict order restriction for the execution of these steps, and these steps can be executed in other orders. Moreover, Figure 1 At least part of the steps may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily executed at the same time, but can be executed at different times. The execution order of these sub-steps or stages is not necessarily sequential, but can be executed in turn or alternately with other steps or at least part of the sub-steps or stages of other steps.

[0097] In one embodiment, Figure 3 As shown, an aircraft airdrop material recovery device is provided, including: a design variable construction module 302, a relationship construction module 304, a landing evaluation module 306 and a planning module 308, wherein:

[0098] A design variable construction module 302 is used to construct design variables for the optimal release point of the aircraft for dropping materials; the design variables include the release point coordinates and the heading angle;

[0099] A relationship building module 304 is used to establish a relationship between the design variables and the landing point position vector according to the motion equation of the material landing process and the design variables;

[0100] The landing evaluation module 306 is used to determine the landing point evaluation function according to the pre-acquired delivery mode, simulate and calculate the landing point position vector corresponding to each heading angle by traversing the heading angle, and select the corresponding heading angle and the corresponding landing point position vector according to the optimal principle of the landing point evaluation function;

[0101] The planning module 308 is used to solve the traveling salesman problem by using a greedy algorithm to traverse the landing points of all landing position vectors to obtain the optimal path planning for material recovery.

[0102] In one embodiment, the design variable construction module 302 is also used to construct the design variables of the optimal release point of the aircraft dropping materials, including:

[0103] u=[x c ,y c ,ψ]

[0104] Among them, u represents the design variable, x c ,y c represents the coordinates of the release point, and ψ represents the heading angle.

[0105] In one embodiment, the motion equation of the material falling to the ground is:

[0106]

[0107] Among them, vv represents the mass center velocity vector of the material, represents the rate of change of the velocity vector of the center of mass, D is the air resistance, g is the acceleration of gravity, m is the mass of the material, ρ is the air density, R is the instantaneous projection radius of the parachute deployment, is the rate of change of the projection radius.

[0108] In one embodiment, the landing evaluation module 306 is further used to determine a landing point evaluation function according to a pre-acquired delivery mode, including:

[0109] f(x I p1,x I p2, ..., x I p n ,u)

[0110] Among them, xI p i Represents the location vector of the i-th material on the ground;

[0111] Alternatively, according to the pre-acquired delivery mode, the drop point evaluation function is determined, including:

[0112]

[0113] Among them, n is the total number of airdropped supplies, x T is the target landing point coordinate vector.

[0114] In one embodiment, the planning module 308 is further used to solve the traveling salesman problem by using a greedy algorithm to traverse the landing points of all landing point position vectors, and obtain the optimal path planning for material recovery as follows:

[0115]

[0116] x ij ∈{0,1},i,j∈V

[0117] Among them, d ij represents the distance between the i-th and j-th drop points, x ij represents a decision variable, taking the value of 1 or 0, V represents a node set, and S is a subset of the node set V.

[0118] In one embodiment, the planning module 308 is further used to solve the traveling salesman problem by using a greedy algorithm to traverse the landing points of all landing point position vectors, and obtain the optimal path planning for material recovery as follows:

[0119]

[0120] ∑k j =n

[0121] in, They are the objective function of the path distance and the objective function of time during the vehicle's first departure, and x is the path and time Weighted sum, k j is the number of drop points traversed during the jth departure, d[i][j] is the distance between the i-th drop point and the j-th drop point, t[i][j] is the time interval between the i-th drop point and the j-th drop point, x[i] is the i-th material recovered, and x[i]-x[j] represents a path, where And when j≠i, x[i]≠x[j], v[x[j]] is the volume function of the jth material to be recycled in the path sequence, and the maximum volume that the vehicle can carry is V max, d[x[i]][x[j]] represents the distance function between the i-th landing point and the j-th landing point, and t[x[i]][x[j]] is the time function between the i-th landing point and the j-th landing point.

[0122] For the specific definition of the aircraft airdrop material recovery device, please refer to the definition of the aircraft airdrop material recovery method above, which will not be repeated here. Each module in the above-mentioned aircraft airdrop material recovery device can be implemented in whole or in part by software, hardware and a combination thereof. The above-mentioned modules can be embedded in or independent of the processor in the computer device in the form of hardware, or can be stored in the memory of the computer device in the form of software, so that the processor can call and execute the operations corresponding to the above modules.

[0123] In one embodiment, a computer device is provided. The computer device may be a terminal, and its internal structure diagram may be as follows: Figure 4 As shown. The computer device includes a processor, a memory, a network interface, a display screen and an input device connected through a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The network interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, a method for recovering airdropped materials from an aircraft is implemented. The display screen of the computer device can be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer device can be a touch layer covering the display screen, or a key, trackball or touchpad set on the computer device housing, or an external keyboard, touchpad or mouse, etc.

[0124] Those skilled in the art will understand that Figure 4 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0125] In one embodiment, a computer device is provided, including a memory and a processor, wherein the memory stores a computer program, and the processor implements the steps of the method in the above embodiment when executing the computer program.

[0126] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the steps of the method in the above embodiment are implemented.

[0127] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. As an illustration and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).

[0128] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0129] The above-mentioned embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the invention patent. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the patent of the present application shall be subject to the attached claims.

Claims

1. A method for recovering materials dropped from aircraft, characterized in that: The method comprises: Constructing design variables for the optimal release point of the aircraft for dropping materials; the design variables include the release point coordinates and the heading angle; According to the motion equation of the material landing process and the design variables, the relationship between the design variables and the landing point position vector is established; According to the pre-acquired delivery mode, the landing point evaluation function is determined, and the landing point position vector corresponding to each heading angle is simulated and calculated by traversing the heading angle, and the corresponding heading angle and the corresponding landing point position vector are selected according to the optimal principle of the landing point evaluation function; The greedy algorithm is used to solve the traveling salesman problem to traverse the landing points of all landing position vectors to obtain the optimal path planning for material recovery.

2. The method according to claim 1, characterized in that The design variables for constructing the optimal release point for aircraft to drop supplies include: u=[x c ,y c ,ψ] Where u represents the design variable, x c ,y c represents the coordinates of the release point, and ψ represents the heading angle.

3. The method according to claim 1, characterized in that The motion equation of the material landing process is: Among them, v represents the mass center velocity vector of the material, represents the rate of change of the velocity vector of the center of mass, D is the air resistance, g is the acceleration of gravity, m is the mass of the material, ρ is the air density, R is the instantaneous projection radius of the parachute deployment, is the rate of change of the projection radius.

4. The method according to claim 2, characterized in that: According to the pre-acquired delivery mode, the drop point evaluation function is determined, including: f(x I p1,x I p2,...,x I p n ,u) Among them, x I p i Represents the location vector of the i-th material on the ground; Alternatively, according to the pre-acquired delivery mode, the drop point evaluation function is determined, including: Among them, n is the total number of airdropped supplies, x T is the target landing point coordinate vector.

5. The method according to claim 1, characterized in that The greedy algorithm is used to solve the traveling salesman problem to traverse the landing points of all landing position vectors to obtain the optimal path planning for material recovery, including: The greedy algorithm is used to solve the traveling salesman problem and traverse the landing points of all landing point position vectors to obtain the optimal path planning for material recovery: xij∈{0,1},i,j∈V Among them, d ij represents the distance between the i-th and j-th drop points, x ij represents a decision variable, taking the value of 1 or 0, V represents a node set, and S is a subset of the node set V.

6. The method according to claim 5, characterized in that The greedy algorithm is used to solve the traveling salesman problem and traverse the landing points of all landing point position vectors to obtain the optimal path planning for material recovery, which also includes: The greedy algorithm is used to solve the traveling salesman problem and traverse the landing points of all landing point position vectors to obtain the optimal path planning for material recovery: ∑k j =n in, They are the objective function of the path distance and the objective function of time during the jth departure of the vehicle, and x is the path and time Weighted sum, k j is the number of drop points traversed during the jth departure, d[i][j] is the distance between the i-th drop point and the j-th drop point, t[i][j] is the time interval between the i-th drop point and the j-th drop point, x[i] is the i-th material recovered, and x[i]-x[j] represents a path, where And when j = i, x[i] ≠ x[j], v[x[j]] is the volume function of the jth material to be recycled in the path sequence, and the maximum volume that the vehicle can carry is V max , d[x[i]][x[j]] represents the distance function between the i-th landing point and the j-th landing point, and t[x[i]][x[j]] is the time function between the i-th landing point and the j-th landing point.

7. An aircraft airdrop material recovery device, characterized in that: The device comprises: A design variable construction module, used to construct design variables for the optimal release point of the aircraft to drop materials; the design variables include the release point coordinates and heading angle; A relationship building module, used to establish a relationship between the design variables and the landing point position vector according to the motion equation of the material landing process and the design variables; The landing evaluation module is used to determine the landing point evaluation function according to the pre-acquired delivery mode, simulate and calculate the landing point position vector corresponding to each heading angle by traversing the heading angle, and select the corresponding heading angle and the corresponding landing point position vector according to the optimal principle of the landing point evaluation function; The planning module is used to solve the traveling salesman problem by using a greedy algorithm to traverse the landing points of all landing position vectors and obtain the optimal path planning for material recovery.

8. The device according to claim 7, characterized in that The design variable construction module is also used to construct the design variables for the optimal release point of the aircraft to release materials, including: u=[x c ,y c ,ψ] Where u represents the design variable, x c ,y c represents the coordinates of the release point, and ψ represents the heading angle.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 6 are implemented.

10. 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 of the method according to any one of claims 1 to 6 are implemented.

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