A method, device, equipment and storage medium for determining a flight attitude sequence

Abstract

The present invention discloses a method, device, equipment and storage medium for determining a flight attitude sequence. The method includes: obtaining a set of flight attitudes, where the set of flight attitudes includes at least two flight attitudes; obtaining pheromone values and switching factors corresponding to any two flight attitudes in the set of flight attitudes; and determining a target flight attitude sequence according to the pheromone values and the switching factors. Through data modeling, the embodiments of the present invention complete the optimal power experiment under different flight attitude combination states of the aircraft with the support of big data for multiple times, and verify the algorithm under virtual environment conditions, avoiding the high-cost hardware equipment required for experiments in the physical state and reducing the experimental cost; at the same time, the technical solution of the embodiments of the present invention provides a solution idea for seeking the optimal solution, solving the problems of how to achieve the optimal power usage efficiency when the aircraft passes through obstacles and the optimal resource allocation for obstacle avoidance.

Description

Technical Field

[0001] The present invention relates to the technical field of resource calculation optimization of aircraft, and particularly to a method, device, equipment and storage medium for determining a flight attitude sequence. Background Art

[0002] At present, commercial aircraft (such as drones, etc.) are increasingly widely used in different business fields. Due to their small and light design, it is impossible to configure a battery for the aircraft to fly for a long time in terms of business. Under the current battery technology conditions, how to improve the use efficiency of the aircraft battery is an algorithmic issue. The current difficulties are mainly reflected in the following two aspects: the limited battery capacity installed on the aircraft and the need for high-cost hardware equipment during the verification process of the algorithm. Summary of the Invention

[0003] The present invention provides a method, device, equipment and storage medium for determining a flight attitude sequence to solve the problem of how to seek the optimal use efficiency of electric energy on the basis of limited aircraft battery capacity.

[0004] According to one aspect of the present invention, a method for determining a flight attitude sequence is provided. The method includes:

[0005] Obtaining a flight attitude set, where the flight attitude set includes at least two flight attitudes;

[0006] Obtaining a pheromone value and a switching factor corresponding to any two flight attitudes in the flight attitude set;

[0007] Determining a target flight attitude sequence according to the pheromone value and the switching factor.

[0008] According to another aspect of the present invention, a device for determining a flight attitude sequence is provided. The device includes:

[0009] A first obtaining module for obtaining a flight attitude set, where the flight attitude set includes at least two flight attitudes;

[0010] A second obtaining module for obtaining a pheromone value and a switching factor corresponding to any two flight attitudes in the flight attitude set;

[0011] A first determining module for determining a target flight attitude sequence according to the pheromone value and the switching factor.

[0012] According to another aspect of the present invention, an electronic device is provided. The electronic device includes:

[0013] At least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores a computer program executable by the at least one processor, and when the computer program is executed by the at least one processor, the at least one processor is enabled to execute the flight attitude sequence determination method according to any embodiment of the present invention.

[0014] According to another aspect of the present invention, there is provided a computer-readable storage medium storing computer instructions for causing a processor to implement the flight attitude sequence determination method according to any embodiment of the present invention when executed.

[0015] The technical solution of the embodiment of the present invention obtains a set of flight attitudes, obtains pheromone values and switching factors corresponding to any two flight attitudes in the set of flight attitudes, and determines a target flight attitude sequence according to the pheromone values and the switching factors. The technical solution of the embodiment of the present invention provides a solution idea for seeking an optimal solution. By using the ant colony algorithm to determine the target flight attitude sequence, it solves the problems of how to achieve the optimal power usage efficiency when the aircraft passes through obstacles and the optimal resource allocation for obstacle avoidance.

[0016] It should be understood that the content described in this part is not intended to identify the key or important features of the embodiments of the present invention, nor is it used to limit the scope of the present invention. Other features of the present invention will become easily understood through the following description. Description of the Drawings

[0017] To more clearly illustrate the technical solutions in the embodiments of the present invention, the following will briefly introduce the drawings required for the description of the embodiments. Obviously, the following drawings are only some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0018] Figure 1 is a flowchart of a flight attitude sequence determination method provided according to Embodiment 1 of the present invention;

[0019] Figure 2 is a schematic structural diagram of a flight attitude sequence determination device provided according to Embodiment 2 of the present invention;

[0020] Figure 3 is a schematic structural diagram of an electronic device for implementing the flight attitude sequence determination method of the embodiment of the present invention. Detailed Embodiments

[0021] To enable those skilled in the art to better understand the solution of the present invention, the following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the scope of protection of the present invention.

[0022] It should be noted that the terms "first", "target", etc. in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects, and do not necessarily need to describe a specific order or sequence. It should be understood that such data can be interchanged under appropriate circumstances, so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusion. For example, a process, method, system, product or device including a series of steps or units does not necessarily have to be limited to those steps or units clearly listed, but may include other steps or units not clearly listed or inherent to these processes, methods, products or devices.

[0023] Embodiment 1

[0024] Figure 1 is a flowchart of a method for determining a flight attitude sequence according to Embodiment 1 of the present invention. This embodiment is applicable to the situation of determining a flight attitude sequence. This method can be executed by a flight attitude sequence determining device, which can be implemented in the form of hardware and / or software, and the flight attitude sequence determining device can be integrated in any electronic device providing the function of determining a flight attitude sequence. As Figure 1 shown, the method includes:

[0025] S101. Obtain a set of flight attitudes.

[0026] It can be known that the flight attitude refers to the state of the three axes of the aircraft in the air relative to a certain reference line, a certain reference plane or a certain fixed coordinate system.

[0027] It should be noted that the set of flight attitudes can be a set composed of multiple flight attitudes. Among them, the set of flight attitudes includes at least two flight attitudes. In this embodiment, the flight attitudes in the set of flight attitudes can be multiple different flight attitudes preset by the user according to the actual situation. For example, the set of flight attitudes can include flight attitude A, flight attitude B, flight attitude C, flight attitude D, and flight attitude E.

[0028] Specifically, obtain a flight attitude set composed of multiple different flight attitudes preset by the user according to the actual situation. The flight attitude set includes at least two flight attitudes.

[0029] S102. Obtain the pheromone value and the switching factors corresponding to any two flight attitudes in the flight attitude set.

[0030] It should be explained that the pheromone value refers to the pheromone of the parameter in the ant colony algorithm. In this embodiment, the algorithm for seeking the theoretical optimal value of the power consumption efficiency of the aircraft is the ant colony algorithm. The ant colony algorithm is an intelligent optimization algorithm. Through ant colony optimization, complex problems can be solved. The ant colony algorithm has good superiority in discrete optimization problems.

[0031] In this embodiment, the switching factor refers to the factor value when switching from one flight attitude to another. Among them, the switching factor can be preset by the user according to the actual situation, and this embodiment does not limit it. Preferably, the switching factor between two identical flight attitudes can be 0, and the switching factors from flight attitude A to flight attitude B and from flight attitude B to flight attitude A may not be the same.

[0032] Specifically, obtain the pheromone value, where the pheromone can include the initial pheromone, and the initial pheromone can be a value preset by the user according to the actual situation; obtain the switching factors corresponding to any two flight attitudes in the flight attitude set, where the switching factor can be preset by the user according to the actual situation.

[0033] S103. Determine the target flight attitude sequence according to the pheromone value and the switching factor.

[0034] It should be noted that the target flight attitude sequence can be the flight attitude sequence obtained by sorting all the flight attitudes included in the flight attitude set, that is, the flight attitude sequence that can achieve the optimal power consumption efficiency of the aircraft when passing through obstacles and the optimal resource allocation for obstacle avoidance.

[0035] Specifically, continuously perform iterative calculations according to the pheromone value and the switching factor, and continuously sort all the flight attitudes included in the flight attitude set until the target flight attitude sequence is iterated, that is, obtain the flight attitude sequence that can achieve the optimal power consumption efficiency of the aircraft when passing through obstacles and the optimal resource allocation for obstacle avoidance.

[0036] The technical solution of the embodiment of the present invention obtains a set of flight postures, obtains pheromone values and switching factors corresponding to any two flight postures in the set of flight postures, and determines a target flight posture sequence according to the pheromone values and the switching factors. The technical solution of the embodiment of the present invention provides a solution idea for seeking an optimal solution. By using the ant colony algorithm to determine the target flight posture sequence, it solves the problems of how to achieve the optimal power usage efficiency when the aircraft passes through obstacles and the optimal resource allocation for obstacle avoidance.

[0037] Optionally, determining the target flight posture sequence according to the pheromone value and the switching factor includes:

[0038] Determining a set of target probability values according to the pheromone value and the switching factor information.

[0039] It should be noted that the set of target probability values can be a set composed of switching probabilities corresponding to any two flight postures in the set of flight postures calculated according to the pheromone value and the switching factor information.

[0040] Among them, the set of target probability values includes: switching probabilities corresponding to any two flight postures in the set of flight postures.

[0041] It should be explained that the switching probability can be the probability of switching from any one flight posture in the set of flight postures to another flight posture in the set of flight postures.

[0042] Specifically, determining the switching probabilities corresponding to any two flight postures in the set of flight postures according to the pheromone value and the switching factor information, and forming a set of target probability values from the switching probabilities corresponding to any two flight postures in the set of flight postures.

[0043] Determining the target flight posture sequence according to the set of target probability values.

[0044] Specifically, determining the target flight posture sequence according to the switching probabilities corresponding to any two flight postures in the set of flight postures in the set of target probability values.

[0045] Optionally, determining the target flight posture sequence according to the set of target probability values includes:

[0046] Determining the maximum switching probability corresponding to the current flight posture according to the switching probabilities corresponding to any two flight postures in the set of flight postures.

[0047] Among them, the current flight posture can be the flight posture that the aircraft is currently in, for example, it can be flight posture A.

[0048] It should be noted that the maximum switching probability can be the maximum value among all the switching probabilities for the aircraft to switch from the current flight posture to other flight postures.

[0049] Specifically, the switching probability corresponding to any two flight postures in the flight posture set is determined according to the pheromone value and the switching factor information, and the maximum value among the switching probabilities corresponding to any two flight postures in the flight posture set is determined as the maximum switching probability corresponding to the current flight posture. For example, the flight posture set includes flight posture A, flight posture B, flight posture C, flight posture D, and flight posture E, and the current flight posture of the aircraft is flight posture A. According to the pheromone value and the switching factor information, the switching probability from flight posture A to flight posture B is 0.278, the switching probability from flight posture A to flight posture C is 0.139, the switching probability from flight posture A to flight posture D is 0.417, and the switching probability from flight posture A to flight posture E is 0.167. Then, the maximum value 0.417 among the above 4 switching probabilities is determined as the maximum switching probability corresponding to the current flight posture A.

[0050] The next flight posture is determined according to the maximum switching probability corresponding to the current flight posture until the target flight posture sequence is obtained.

[0051] Among them, the next flight posture can be the flight posture that the aircraft is about to switch to from the current flight posture.

[0052] Specifically, the flight posture corresponding to the maximum switching probability corresponding to the current flight posture is determined as the next flight posture until the target flight posture sequence is obtained. Exemplarily, the switching probability from flight posture A to flight posture B is 0.278, the switching probability from flight posture A to flight posture C is 0.139, the switching probability from flight posture A to flight posture D is 0.417, and the switching probability from flight posture A to flight posture E is 0.167. Then, the switching probability 0.417 is determined as the maximum switching probability corresponding to the current flight posture A, and the flight posture D corresponding to the switching probability 0.417 is determined as the next flight posture; similarly, the flight posture corresponding to the maximum switching probability among the switching probabilities from flight posture D to flight posture B, from flight posture D to flight posture C, and from flight posture D to flight posture E is determined as the next flight posture; and so on until the target flight posture sequence is obtained.

[0053] Optionally, the method further includes:

[0054] If the current flight posture is the first flight posture, any flight posture in the flight posture set is determined as the current flight posture.

[0055] It should be noted that the first flight posture can be the first flight posture adopted by the aircraft during flight, that is, before the aircraft adopts this flight posture for flight, it has not adopted any flight posture in the flight posture set.

[0056] Specifically, if the current flight attitude is the first flight attitude, any flight attitude in the flight attitude set is determined as the current flight attitude, that is, the first flight attitude of the aircraft can be any flight attitude in the flight attitude set, and the first flight attitude is randomly determined.

[0057] If the current flight attitude is not the first flight attitude, the current flight attitude is determined according to the maximum switching probability corresponding to the previous flight attitude of the current flight attitude.

[0058] Among them, the non-first flight attitude can be switched from any flight attitude in other flight attitude sets adopted by the aircraft during flight, that is, before the aircraft adopts this flight attitude, it has adopted other flight attitudes in the flight attitude set.

[0059] Specifically, if the current flight attitude is not the first flight attitude, the flight attitude corresponding to the maximum switching probability of the previous flight attitude of the current flight attitude is determined as the current flight attitude. Exemplarily, the previous flight attitude is flight attitude A, the switching probability from flight attitude A to flight attitude B is 0.278, the switching probability from flight attitude A to flight attitude C is 0.139, the switching probability from flight attitude A to flight attitude D is 0.417, and the switching probability from flight attitude A to flight attitude E is 0.167. Then, the flight attitude D corresponding to the maximum switching probability 0.417 of the previous flight attitude A is determined as the current flight attitude.

[0060] Optionally, determining the target probability value set according to the pheromone value and the switching factor information includes:

[0061] Obtain the initial pheromone value, the weight of the initial pheromone value, the switching factors corresponding to any two flight attitudes in the flight attitude set, and the weight of the switching factors.

[0062] Among them, the initial pheromone value can be preset by the user according to the actual situation, and this embodiment does not limit this. Preferably, the initial pheromone value can be 3.

[0063] It should be noted that the weight of the initial pheromone value can be the weight degree of the initial pheromone. The weight of the switching factor can be the weight degree of the switching factor, and the greater the weight of the switching factor, the faster the calculation of the switching probability value converges.

[0064] Specifically, obtain the initial pheromone value, the weight of the initial pheromone value, the switching factors corresponding to any two flight attitudes in the flight attitude set, and the weight of the switching factors, where the initial pheromone value and the switching factors can be preset by the user according to the actual situation, and this embodiment does not limit this.

[0065] Determine the switching probability corresponding to any two flight postures according to the initial pheromone value, the weight of the initial pheromone value, the switching factor corresponding to any two flight postures in the set of flight postures, and the weight of the switching factor.

[0066] Specifically, the switching probability corresponding to any two flight postures can be calculated by the following formula:

[0067]

[0068] Among them, a represents the current flight posture, b represents the next flight posture, and p ab represents the switching probability corresponding to switching from the current flight posture a to the next flight posture b, ph ab represents the initial pheromone value, q represents the weight of the initial pheromone value, and u ab represents the switching factor corresponding to switching from the current flight posture a to the next flight posture b, β represents the weight of the switching factor, M represents the set of next flight postures composed of other flight postures in the set of flight postures except the current flight posture a, v represents any flight posture in the set of next flight postures, and ph av represents the initial pheromone value, and u av represents the switching factor corresponding to switching from the current flight posture a to any flight posture in the set of next flight postures.

[0069] Determine the set of target probability values according to the switching probability corresponding to any two flight postures.

[0070] Specifically, determine the switching probability corresponding to any two flight postures according to the initial pheromone value, the weight of the initial pheromone value, the switching factor corresponding to any two flight postures in the set of flight postures, and the weight of the switching factor, and determine the set of target probability values according to the switching probability corresponding to any two flight postures.

[0071] Optionally, determine the target flight posture sequence according to the pheromone value and the switching factor, including:

[0072] Perform iterative calculations according to the pheromone value and the switching factor until the flight posture sequences corresponding to two adjacent iterations are the same, then determine any one of the flight posture sequences corresponding to two adjacent iterations as the target flight posture sequence.

[0073] In this embodiment, the process of sorting all the flight postures in the set of flight postures to obtain a flight posture sequence is a process of one iterative calculation.

[0074] Specifically, iterative calculations are performed based on the pheromone value and the switching factor to obtain a flight attitude sequence corresponding to each iterative calculation process until the flight attitude sequences corresponding to two adjacent iterations are the same, at which point the iterative calculation process ends, and any one of the flight attitude sequences corresponding to two adjacent iterations is determined as the target flight attitude sequence.

[0075] Optionally, the iterative calculation based on the pheromone value and the switching factor includes:

[0076] If the current iteration is the first iteration, the initial pheromone value is determined as the pheromone value corresponding to the current iteration.

[0077] It should be noted that the first iteration can be the process of sorting all the flight attitudes in the flight attitude set for the first time to obtain a flight attitude sequence.

[0078] Specifically, if the current iteration is the first iteration, the initial pheromone value set by the user according to the actual situation is determined as the pheromone value corresponding to the current iteration.

[0079] Based on the initial pheromone value and the switching factors corresponding to any two flight attitudes in the flight attitude set, the target probability value set corresponding to the current iteration is determined.

[0080] Specifically, according to the initial pheromone value and the switching factor information corresponding to any two flight attitudes in the flight attitude set, the switching probability corresponding to any two flight attitudes in the flight attitude set corresponding to the current iteration is determined, and the target probability value set corresponding to the current iteration is determined from the switching probabilities corresponding to any two flight attitudes in the flight attitude set corresponding to the current iteration.

[0081] Based on the target probability value set corresponding to the current iteration, the flight attitude sequence corresponding to the current iteration is determined.

[0082] Specifically, according to the switching probabilities corresponding to any two flight attitudes in the flight attitude set corresponding to the current iteration, the maximum switching probability corresponding to the current flight attitude in the current iteration is determined, and based on the maximum switching probability corresponding to the current flight attitude in the current iteration, the next flight attitude in the current iteration is determined until the flight attitude sequence corresponding to the current iteration is obtained.

[0083] If the current iteration is not the first iteration, the pheromone value corresponding to the current iteration is determined according to the target probability value set corresponding to the previous iteration.

[0084] It should be noted that the non - first iteration can be the process of sorting all the flight attitudes in the flight attitude set for the Nth (N is a positive integer and N > 1) time to obtain a flight attitude sequence.

[0085] Specifically, if the current iteration is not the first iteration, the pheromone value corresponding to the switch between any two postures in the current iteration process is the sum of the pheromone values corresponding to the switch between these two postures in the target probability value set corresponding to the previous iteration. For example, during the second iteration calculation, the pheromone value corresponding to the switch from flight posture A to flight posture B is the sum of all the pheromone values corresponding to the switch from flight posture A to flight posture B in the target probability value set corresponding to the first iteration.

[0086] Determine the target probability value set corresponding to the current iteration according to the pheromone value corresponding to the current iteration and the switching factor corresponding to any two flight postures in the flight posture set.

[0087] Specifically, determine the switching probability corresponding to any two flight postures in the flight posture set corresponding to the current iteration according to the pheromone value corresponding to the current iteration and the switching factor information corresponding to any two flight postures in the flight posture set, and determine the target probability value set corresponding to the current iteration from the switching probability corresponding to any two flight postures in the flight posture set corresponding to the current iteration.

[0088] Determine the flight posture sequence corresponding to the current iteration according to the target probability value set corresponding to the current iteration.

[0089] Specifically, determine the maximum switching probability corresponding to the current flight posture corresponding to the current iteration according to the switching probability corresponding to any two flight postures in the flight posture set corresponding to the current iteration, and determine the next flight posture corresponding to the current iteration according to the maximum switching probability corresponding to the current flight posture corresponding to the current iteration until the flight posture sequence corresponding to the current iteration is obtained.

[0090] Optionally, the method further includes:

[0091] Obtain the switching power corresponding to any two flight postures in the flight posture set.

[0092] It should be noted that during the process of switching from any one flight posture in the flight posture set to another flight posture in the flight posture set, the aircraft needs to use a certain amount of power. The switching power can be the power used by the aircraft during the process of switching from any one flight posture in the flight posture set to another flight posture in the flight posture set. It should be noted that the power used by the aircraft to switch from flight posture A to flight posture B and from flight posture B to flight posture A can be different, and the power used between two identical flight postures can be 0.

[0093] Specifically, the switching power corresponding to any two flight postures in the flight posture set can be set by the user according to the actual situation. Exemplarily, the switching power corresponding to any two flight postures in the flight posture set can be as shown in Table 1:

[0094] Table 1

[0095] A B C D E A 0 3 6 2 5 B 4 0 5 8 3 C 7 4 0 5 9 D 3 7 4 0 2 E 4 2 4 3 0

[0096] As shown in Table 1, the first column is the current flight attitude of the aircraft, and the first row is the next flight attitude of the aircraft. For example, the power consumption for switching from flight attitude A to flight attitude B is 3 (unit: joule), and the power consumption for switching from flight attitude B to flight attitude A is 4 (unit: joule).

[0097] Determine the power consumption corresponding to the target flight attitude sequence according to the switching power consumption and the target flight attitude sequence.

[0098] It should be noted that the power consumption corresponding to the target flight attitude sequence can be the total power consumption when the aircraft flies according to the target flight attitude sequence.

[0099] Specifically, obtain the switching power consumption corresponding to any two flight attitudes in the flight attitude set, and determine the power consumption corresponding to the target flight attitude sequence according to the switching power consumption and the target flight attitude sequence. Exemplarily, the target flight attitude sequence is flight attitude A → flight attitude D → flight attitude E → flight attitude B → flight attitude C → flight attitude A (it should be noted that after sorting all the flight attitudes in the flight attitude set, the first flight attitude needs to be returned again to finally form the target flight attitude sequence), then the power consumption corresponding to the target flight attitude sequence is 2 + 2 + 2 + 5 + 7 = 18 (unit: joule).

[0100] As an exemplary description of this embodiment, there are currently 5 aircraft, and the flight attitude set {A, B, C, D, E} is composed of five flight attitudes: flight attitude A, flight attitude B, flight attitude C, flight attitude D, and flight attitude E. Let the initial pheromone value be 3, the weight q of the initial pheromone value be 1, the weight β of the switching factor be 1, and the switching factors corresponding to any two flight attitudes in the flight attitude set are shown in Table 2:

[0101] Table 2

[0102] A B C D E A 0 1 / 3 1 / 6 1 / 2 1 / 5 B 1 / 4 0 1 / 5 1 / 8 1 / 3 C 1 / 7 1 / 4 0 1 / 5 1 / 9 D 1 / 3 1 / 7 1 / 4 0 1 / 2 E 1 / 4 1 / 2 1 / 4 1 / 3 0

[0103] As shown in Table 2, the first column is the current flight attitude of the aircraft, and the first row is the next flight attitude of the aircraft. For example, the switching factor corresponding to switching from flight attitude A to flight attitude B is 1 / 3, and the switching factor corresponding to switching from flight attitude B to flight attitude A is 1 / 4.

[0104] Now assume that 5 aircraft respectively select 5 different flight attitudes in the flight attitude set as the first flight attitude for the first iteration. The first iteration process of the first aircraft is shown in Table 3:

[0105] Table 3

[0106]

[0107] As can be seen from Table 3, the first flight attitude of the first aircraft is flight attitude A. When switching from flight attitude A to the next flight attitude, the switching probability corresponding to flight attitude D is 0.417, which is the maximum switching probability corresponding to flight attitude A. Therefore, flight attitude D is determined as the next flight attitude. And so on. Finally, the flight attitude sequence corresponding to the first iteration is flight attitude A → flight attitude D → flight attitude E → flight attitude B → flight attitude C → flight attitude A.

[0108] The first iteration process of the second aircraft is shown in Table 4:

[0109] Table 4

[0110]

[0111] As can be seen from Table 4, the first flight attitude of the second aircraft is flight attitude B. When switching from flight attitude B to the next flight attitude, the switching probability corresponding to flight attitude A is 0.323, which is the maximum switching probability corresponding to flight attitude B. Therefore, flight attitude A is determined as the next flight attitude. And so on. Finally, the flight attitude sequence corresponding to the first iteration is flight attitude B → flight attitude A → flight attitude D → flight attitude E → flight attitude C → flight attitude B.

[0112] The first iteration process of the third aircraft is shown in Table 5.

[0113] As can be seen from Table 5, the first flight attitude of the third aircraft is flight attitude C. When switching from flight attitude C to the next flight attitude, the switching probability corresponding to flight attitude A is 0.323, which is the maximum switching probability corresponding to flight attitude C. Therefore, flight attitude A is determined as the next flight attitude. And so on. Finally, the flight attitude sequence corresponding to the first iteration is flight attitude C → flight attitude A → flight attitude D → flight attitude E → flight attitude B → flight attitude C.

[0114] Table 5

[0115]

[0116] The first iteration process of the fourth aircraft is shown in Table 6:

[0117] Table 6

[0118]

[0119] As can be seen from Table 6, the first flight attitude of the fourth aircraft is flight attitude D. When switching from flight attitude D to the next flight attitude, the switching probability of 0.408 corresponding to flight attitude E is the maximum switching probability corresponding to flight attitude D. Therefore, flight attitude E is determined as the next flight attitude. And so on. Finally, the flight attitude sequence corresponding to the first iteration is flight attitude D → flight attitude E → flight attitude B → flight attitude A → flight attitude C → flight attitude D.

[0120] The first iteration process of the fifth aircraft is shown in Table 7:

[0121] Table 7

[0122]

[0123] As can be seen from Table 7, the first flight attitude of the fifth aircraft is flight attitude E. When switching from flight attitude E to the next flight attitude, the switching probability of 0.373 corresponding to flight attitude B is the maximum switching probability corresponding to flight attitude E. Therefore, flight attitude B is determined as the next flight attitude. And so on. Finally, the flight attitude sequence corresponding to the first iteration is flight attitude E → flight attitude B → flight attitude A → flight attitude D → flight attitude C → flight attitude E.

[0124] So far, the first iteration process is completed. According to the above target probability value set, the pheromone value is updated. During the second iteration process, the pheromone value corresponding to the switching between any two attitudes is the sum of the pheromone values corresponding to the switching between these two attitudes in the target probability value set corresponding to the first iteration. For example, during the second iteration calculation, the pheromone value corresponding to the switching from flight attitude A to flight attitude B is the sum of all pheromone values corresponding to the switching from flight attitude A to flight attitude B in the target probability value set corresponding to the first iteration. The updated pheromone values after the first iteration process are shown in Table 8:

[0125] Table 8

[0126] A B C D E A 0 0.278 3.632 1.581 0.592 B 1.314 0 2.05 0.378 0.258 C 0.323 0.258 0 0.161 0.258 D 0.271 0.497 1.816 0 2.411 E 0.438 2.54 1.771 0.25 0

[0127] The 5 aircraft respectively select 5 different flight attitudes in the flight attitude set as the first flight attitude for the second iteration. According to the pheromone values in Table 8 and the switching factors in Table 2, the flight attitude sequence corresponding to the second iteration is determined. And so on. The iterative calculation is continuously carried out until the flight attitude sequences corresponding to two adjacent iterations are the same. Then, any one of the flight attitude sequences corresponding to the two adjacent iterations is determined as the target flight attitude sequence. After determining the target flight attitude sequence, the power consumption corresponding to the target flight attitude sequence is determined according to the switching power in Table 1 and the target flight attitude sequence.

[0128] The technical solution of the embodiment of the present invention provides a solution idea for seeking the optimal solution, which solves the problems of how to adopt a flight strategy to achieve the optimal power usage efficiency when the aircraft passes through obstacles and the optimal resource allocation for obstacle avoidance. At the same time, it can complete the verification of the optimal power experiment algorithm in different flight attitude combination states of the aircraft under virtual environment conditions, avoiding the high-cost hardware equipment required for experiments in the physical state, and achieving the beneficial effect of reducing the experimental cost.

[0129] Embodiment 2

[0130] Figure 2 It is a schematic structural diagram of a flight attitude sequence determination device provided according to Embodiment 2 of the present invention. As Figure 2 shown, the device includes: a first acquisition module 201, a second acquisition module 202, and a first determination module 203.

[0131] Among them, the first acquisition module 201 is used to acquire a flight attitude set, where the flight attitude set includes: at least two flight attitudes;

[0132] The second acquisition module 202 is used to acquire pheromone values and switching factors corresponding to any two flight attitudes in the flight attitude set;

[0133] The first determination module 203 is used to determine a target flight attitude sequence according to the pheromone value and the switching factor.

[0134] Optionally, the first determination module 203 includes:

[0135] A first determination unit is used to determine a target probability value set according to the pheromone value and the switching factor information, where the target probability value set includes: switching probabilities corresponding to any two flight attitudes in the flight attitude set;

[0136] A second determination unit is used to determine a target flight attitude sequence according to the target probability value set.

[0137] Optionally, the second determination unit includes:

[0138] A first determination subunit is used to determine the maximum switching probability corresponding to the current flight attitude according to the switching probabilities corresponding to any two flight attitudes in the flight attitude set;

[0139] A second determination subunit is used to determine the next flight attitude according to the maximum switching probability corresponding to the current flight attitude until a target flight attitude sequence is obtained.

[0140] Optionally, the device further includes:

[0141] A second determination module, configured to determine any flight attitude in the flight attitude set as the current flight attitude if the current flight attitude is the first flight attitude;

[0142] A third determination module, configured to determine the current flight attitude according to the maximum switching probability corresponding to the previous flight attitude of the current flight attitude if the current flight attitude is not the first flight attitude.

[0143] Optionally, the first determination unit includes:

[0144] An acquisition subunit, configured to acquire an initial pheromone value, a weight of the initial pheromone value, a switching factor corresponding to any two flight attitudes in the flight attitude set, and a weight of the switching factor;

[0145] A third determination subunit, configured to determine a switching probability corresponding to any two flight attitudes according to the initial pheromone value, the weight of the initial pheromone value, the switching factor corresponding to any two flight attitudes in the flight attitude set, and the weight of the switching factor;

[0146] A fourth determination subunit, configured to determine a set of target probability values according to the switching probability corresponding to any two flight attitudes.

[0147] Optionally, the first determination module 203 includes:

[0148] An iterative calculation unit, configured to perform iterative calculation according to the pheromone value and the switching factor until the flight attitude sequences corresponding to two adjacent iterations are the same, and then determine any one of the flight attitude sequences corresponding to two adjacent iterations as the target flight attitude sequence.

[0149] Optionally, the iterative calculation unit includes:

[0150] A fifth determination subunit, configured to determine the initial pheromone value as the pheromone value corresponding to the current iteration if the current iteration is the first iteration;

[0151] A sixth determination subunit, configured to determine a set of target probability values corresponding to the current iteration according to the initial pheromone value and the switching factor corresponding to any two flight attitudes in the flight attitude set;

[0152] A seventh determination subunit, configured to determine a flight attitude sequence corresponding to the current iteration according to the set of target probability values corresponding to the current iteration;

[0153] An eighth determination subunit, configured to determine the pheromone value corresponding to the current iteration according to the set of target probability values corresponding to the previous iteration if the current iteration is not the first iteration;

[0154] A ninth determination subunit, configured to determine a target probability value set corresponding to the current iteration according to the pheromone value corresponding to the current iteration and the switching factors corresponding to any two flight postures in the set of flight postures;

[0155] A tenth determination subunit, configured to determine a flight posture sequence corresponding to the current iteration according to the target probability value set corresponding to the current iteration.

[0156] Optionally, the device further includes:

[0157] A third acquisition module, configured to acquire the switching power corresponding to any two flight postures in the set of flight postures;

[0158] A fourth determination module, configured to determine the power consumption corresponding to the target flight posture sequence according to the switching power and the target flight posture sequence.

[0159] The flight posture sequence determination device provided by the embodiments of the present invention can execute the flight posture sequence determination method provided by any embodiment of the present invention, and has corresponding functional modules and beneficial effects for executing the method.

[0160] Embodiment 3

[0161] Figure 3 FIG. shows a schematic structural diagram of an electronic device 30 that can be used to implement the embodiments of the present invention. The electronic device is intended to represent various forms of digital computers, such as, for example, a laptop computer, a desktop computer, a workbench, a personal digital assistant, a server, a blade server, a mainframe computer, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as, for example, a personal digital processor, a cellular phone, a smart phone, a wearable device (such as a helmet, glasses, a watch, etc.) and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the present invention described and / or claimed herein.

[0162] As Figure 3 shown, the electronic device 30 includes at least one processor 31, and a memory communicatively connected to at least one processor 31, such as a read-only memory (ROM) 32, a random access memory (RAM) 33, etc. The memory stores a computer program executable by at least one processor. The processor 31 can perform various appropriate actions and processes according to the computer program stored in the read-only memory (ROM) 32 or the computer program loaded from the storage unit 38 into the random access memory (RAM) 33. In the RAM 33, various programs and data required for the operation of the electronic device 30 can also be stored. The processor 31, the ROM 32, and the RAM 33 are connected to each other through a bus 34. The input / output (I / O) interface 35 is also connected to the bus 34.

[0163] Multiple components in the electronic device 30 are connected to the I / O interface 35, including: an input unit 36, such as a keyboard, a mouse, etc.; an output unit 37, such as various types of displays, speakers, etc.; a storage unit 38, such as a disk, an optical disc, etc.; and a communication unit 39, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 39 allows the electronic device 30 to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunication networks.

[0164] The processor 31 can be various general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of the processor 31 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various dedicated artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. The processor 31 executes the various methods and processes described above, such as the flight attitude sequence determination method:

[0165] Obtain a set of flight attitudes, where the set of flight attitudes includes: at least two flight attitudes;

[0166] Obtain the pheromone value and the switching factors corresponding to any two flight attitudes in the set of flight attitudes;

[0167] Determine a target flight attitude sequence according to the pheromone value and the switching factors.

[0168] In some embodiments, the flight attitude sequence determination method can be implemented as a computer program, which is tangibly contained in a computer-readable storage medium, such as the storage unit 38. In some embodiments, part or all of the computer program can be loaded and / or installed onto the electronic device 30 via the ROM 32 and / or the communication unit 39. When the computer program is loaded into the RAM 33 and executed by the processor 31, one or more steps of the flight attitude sequence determination method described above can be executed. Alternatively, in other embodiments, the processor 31 can be configured to execute the flight attitude sequence determination method in any other suitable manner (e.g., by means of firmware).

[0169] The various embodiments of the systems and techniques described above in this specification can be implemented in digital electronic circuitry, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on a chip (SOCs), complex programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments can include: being implemented in one or more computer programs that are executable and / or interpretable on a programmable system including at least one programmable processor, which can be a special-purpose or general-purpose programmable processor that receives data and instructions from, and transmits data and instructions to, a storage system, at least one input device, and at least one output device.

[0170] The computer programs for implementing the methods of the present invention can be written in any combination of one or more programming languages. These computer programs can be provided to a processor of a general purpose computer, special purpose computer, or other programmable data processing apparatus, such that the computer programs, when executed by the processor, cause the functions / operations specified in the flowchart and / or block diagram to be implemented. The computer programs can be executed entirely on the machine, partly on the machine, as a stand-alone software package partly on the machine and partly on a remote machine or entirely on the remote machine or server.

[0171] In the context of the present invention, a computer-readable storage medium can be a tangible medium that can contain or store a computer program for use by or in connection with an instruction execution system, apparatus, or device. The computer-readable storage medium can include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination of the foregoing. Alternatively, the computer-readable storage medium can be a machine-readable signal medium. More specific examples of the machine-readable storage medium would include an electrical connection based on one or more wires, a portable computer diskette, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or Flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0172] To provide interaction with a user, the systems and techniques described herein can be implemented on an electronic device having: a display device for displaying information to the user (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor); and a keyboard and a pointing device (e.g., a mouse or a trackball) through which the user can provide input to the electronic device. Other kinds of devices can also be used to provide interaction with the user; for example, the feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including acoustic input, voice input, or tactile input).

[0173] The systems and techniques described herein can be implemented in a computing system including backend components (e.g., as a data server), or a computing system including middleware components (e.g., an application server), or a computing system including frontend components (e.g., a user computer having a graphical user interface or a web browser through which the user can interact with an implementation of the systems and techniques described herein), or a computing system including any combination of such backend components, middleware components, or frontend components. The components of the system can be interconnected by digital data communication in any form or medium (e.g., a communication network). Examples of communication networks include: local area network (LAN), wide area network (WAN), blockchain network, and the Internet.

[0174] A computing system can include a client and a server. The client and the server are generally far from each other and usually interact through a communication network. The client-server relationship is created by computer programs running on the respective computers and having a client-server relationship with each other. The server can be a cloud server, also known as a cloud computing server or a cloud host, which is a host product in the cloud computing service system and solves the defects of difficult management and weak business scalability existing in traditional physical hosts and VPS services.

[0175] It should be understood that various forms of the processes shown above can be used, with steps reordered, added, or deleted. For example, the steps recited in the present invention can be executed in parallel, sequentially, or in a different order, as long as the desired results of the technical solution of the present invention can be achieved, and this is not limited herein.

[0176] The above specific embodiments do not constitute a limitation on the protection scope of the present invention. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention shall be included within the protection scope of the present invention.

Claims

1. A method for determining a flight attitude sequence, characterized in that, it includes: Obtain a set of flight attitudes, where the set of flight attitudes includes: at least two flight attitudes; Obtain the pheromone value and the switching factor corresponding to any two flight attitudes in the set of flight attitudes; where the pheromone value is the parameter pheromone corresponding to the switching between two flight attitudes, and the switching factor is the factor value when switching between two flight attitudes; Determine the target flight attitude sequence according to the pheromone value and the switching factor; Among them, determining the target flight attitude sequence according to the pheromone value and the switching factor includes: Determine a set of target probability values according to the pheromone value and the switching factor information, where the set of target probability values includes: the switching probability corresponding to any two flight attitudes in the set of flight attitudes; Determine the target flight attitude sequence according to the set of target probability values; Among them, determining the target flight attitude sequence according to the set of target probability values includes: Determine the maximum switching probability corresponding to the current flight attitude according to the switching probability corresponding to any two flight attitudes in the set of flight attitudes; Determine the next flight attitude according to the maximum switching probability corresponding to the current flight attitude until the target flight attitude sequence is obtained.

2. The method according to claim 1, characterized in that, it further includes: If the current flight attitude is the first flight attitude, determine any flight attitude in the set of flight attitudes as the current flight attitude; If the current flight attitude is not the first flight attitude, determine the current flight attitude according to the maximum switching probability corresponding to the previous flight attitude of the current flight attitude.

3. The method according to claim 1, characterized in that, Determining the set of target probability values according to the pheromone value and the switching factor information includes: Obtain the initial pheromone value, the weight of the initial pheromone value, the switching factor corresponding to any two flight attitudes in the set of flight attitudes, and the weight of the switching factor; Determine the switching probability corresponding to any two flight attitudes according to the initial pheromone value, the weight of the initial pheromone value, the switching factor corresponding to any two flight attitudes in the set of flight attitudes, and the weight of the switching factor; Determine the set of target probability values according to the switching probability corresponding to any two flight attitudes.

4. The method according to claim 1, characterized in that, Determining the target flight attitude sequence according to the pheromone value and the switching factor includes: Perform iterative calculation according to the pheromone value and the switching factor until the flight attitude sequences corresponding to two adjacent iterations are the same, then determine any one of the flight attitude sequences corresponding to two adjacent iterations as the target flight attitude sequence.

5. The method according to claim 4, characterized in that, Performing iterative calculation according to the pheromone value and the switching factor includes: If the current iteration is the first iteration, determine the initial pheromone value as the pheromone value corresponding to the current iteration; Determine the set of target probability values corresponding to the current iteration according to the initial pheromone value and the switching factor corresponding to any two flight attitudes in the set of flight attitudes; Determine the flight attitude sequence corresponding to the current iteration according to the set of target probability values corresponding to the current iteration; If the current iteration is not the first iteration, determine the pheromone value corresponding to the current iteration according to the set of target probability values corresponding to the previous iteration; Determine the set of target probability values corresponding to the current iteration according to the pheromone value corresponding to the current iteration and the switching factor corresponding to any two flight attitudes in the set of flight attitudes; Determine the flight attitude sequence corresponding to the current iteration according to the set of target probability values corresponding to the current iteration.

6. The method according to claim 1, wherein, further comprising: Obtain the switching power consumption corresponding to any two flight attitudes in the set of flight attitudes; Determine the power consumption corresponding to the target flight attitude sequence according to the switching power consumption and the target flight attitude sequence.

7. A device for determining a flight attitude sequence, wherein, comprising: A first acquisition module, configured to acquire a set of flight attitudes, where the set of flight attitudes includes: at least two flight attitudes; A second acquisition module, configured to acquire pheromone values and switching factors corresponding to any two flight attitudes in the set of flight attitudes; wherein, the pheromone value is the parameter pheromone corresponding to the switching between two flight attitudes, and the switching factor is the factor value corresponding to the switching between two flight attitudes; A first determination module, configured to determine a target flight attitude sequence according to the pheromone value and the switching factor; wherein, the first determination module includes: A first determination unit, configured to determine a set of target probability values according to the pheromone value and the switching factor information, where the set of target probability values includes: switching probabilities corresponding to any two flight attitudes in the set of flight attitudes; A second determination unit, configured to determine a target flight attitude sequence according to the set of target probability values; wherein, the second determination unit includes: A first determination subunit, configured to determine the maximum switching probability corresponding to the current flight attitude according to the switching probabilities corresponding to any two flight attitudes in the set of flight attitudes; A second determination subunit, configured to determine the next flight attitude according to the maximum switching probability corresponding to the current flight attitude until a target flight attitude sequence is obtained.

8. An electronic device, wherein, the electronic device includes: At least one processor; and A memory communicatively connected to the at least one processor; wherein, The memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the flight attitude sequence determination method according to any one of claims 1-6.

9. A computer-readable storage medium, wherein, The computer-readable storage medium stores computer instructions, and the computer instructions are used to cause a processor to execute the flight attitude sequence determination method according to any one of claims 1-6 when executed.

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