An online conflict resolution method and device for close-range flight of multiple unmanned aerial vehicles

Abstract

The application discloses a kind of online conflict resolution method and device of multi-architecture unmanned aerial vehicle close flight, belong to unmanned aerial vehicle cooperative control technical field.Method includes: obtaining the first state information of itself and the second state information of surrounding other unmanned aerial vehicles, and obtaining the task information of itself;According to the first state information and the second state information, it is judged whether conflict occurs, and after detecting that conflict occurs, pairwise conflict type analysis is carried out, and the corresponding coordination method is obtained according to the analysis result to carry out conflict coordination, and obtain feasible region;If multiple pairwise conflicts occur simultaneously, obtain the common feasible region as the final feasible region;According to the first state information and task information, task analysis is carried out to obtain optimal heading;Feasible region and optimal heading are optimized on line to obtain optimal heading change angle.The online conflict resolution coordination method based on classification model provided by the application can ensure the safety and orderly flight of a large number of unmanned aerial vehicles when flying in close range.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of unmanned aerial vehicle cooperative control, and in particular to an online conflict resolution method and device for close-range flight of multiple unmanned aerial vehicles. BACKGROUND

[0002] The use scenarios of current unmanned aerial vehicles are becoming more and more extensive, including logistics transportation, remote sensing, traffic monitoring, etc. In the future, unmanned aerial vehicles will also be used in smart cities and metaverse. With the wide application of unmanned aerial vehicles, there will be a large number of unmanned aerial vehicles flying in local airspace in the future. If the unmanned aerial vehicles fly too close to each other, there may be mutual interference leading to collision or crash. In order to ensure that the unmanned aerial vehicles fly in an orderly manner while maintaining a safe distance from other unmanned aerial vehicles, the problem of conflict resolution needs to be solved when multiple unmanned aerial vehicles fly close to each other.

[0003] When unmanned aerial vehicles are widely used in local airspace, centralized conflict resolution methods have the problems of poor system robustness and low computational efficiency. Therefore, decentralized conflict resolution methods can be used as an effective supplement to coordinate the flight safety of unmanned aerial vehicles. Existing decentralized conflict resolution methods include artificial potential field method, flight rule-based method and geometric navigation method. The artificial potential field method can ensure the safe separation between unmanned aerial vehicles in a good initial state, but it is easy to cause the unmanned aerial vehicles to deviate from the flight path, greatly reducing the flight efficiency. The flight rule-based method proposes that all possible mutually affected unmanned aerial vehicles adopt right-side maneuvering, and further distributed planning is carried out. This method has low computational efficiency. The geometric navigation-based method includes the speed obstacle-based method and the collision cone-based method. These two methods can make the unmanned aerial vehicles deviate from the intended flight path less, but the problem is that existing methods proposed are easy to make the unmanned aerial vehicles fly chaotically in local airspace, and it is difficult to quickly return to the intended flight path. Therefore, this kind of method also has problems in coordinating the flight of unmanned aerial vehicles.

[0004] The solution to the conflict resolution problem of a large number of unmanned aerial vehicles is based on the analysis of the conflict between two unmanned aerial vehicles. Some decentralized conflict resolution methods propose to determine the conflict resolution strategy of two unmanned aerial vehicles according to the airspace conflict category involved by the two unmanned aerial vehicles. This method can establish consensus between unmanned aerial vehicles without a coordination center. However, the existing classification method directly considers the speed direction and position of two unmanned aerial vehicles, without revealing the true characteristics of the multiple types of conflicts faced by the two unmanned aerial vehicles. SUMMARY

[0005] To at least partially solve one of the technical problems existing in the prior art, the purpose of the present application is to provide an online conflict resolution method and device for close-range flight of multiple unmanned aerial vehicles.

[0006] The technical solution adopted by the present application is:

[0007] An online conflict resolution method for close-range flight of multiple unmanned aerial vehicles, independently executed by each unmanned aerial vehicle, comprising the following steps:

[0008] Obtaining state information of itself and surrounding unmanned aerial vehicles, and obtaining task information of itself; wherein the state information comprises position, speed and movement direction of the unmanned aerial vehicle, etc.

[0009] Judging whether a conflict occurs according to the state information of itself and surrounding unmanned aerial vehicles, and after detecting that a conflict occurs, analyzing two-by-two conflict types, determining corresponding coordination methods for conflict coordination according to the analysis results to obtain a feasible region; if a certain unmanned aerial vehicle is involved in multiple two-by-two conflicts, a common region of the feasible regions corresponding to the multiple two-by-two conflicts is taken as a final feasible direction region.

[0010] Performing task analysis according to the state information and the task information of itself to obtain an optimal heading;

[0011] Performing online optimization on the feasible direction region and the optimal heading to obtain an optimal heading change angle.

[0012] Further, the online conflict resolution method for multiple unmanned aerial vehicles comprises the following steps of discussing conflict resolution problems through a Cartesian coordinate system:

[0013] According to a right turn strategy, obtaining a constraint condition for conflict-free of two unmanned aerial vehicles:

[0014]

[0015]

[0016] In the formula, v i and v j are speeds of unmanned aerial vehicle A i and unmanned aerial vehicle A j , φ i and φ j are movement directions of unmanned aerial vehicle A i and unmanned aerial vehicle A j , is a maneuvering angle of unmanned aerial vehicle A i and unmanned aerial vehicle A j , is a critical slope of a right side feasible region;

[0017] The functions f and f are respectively taken as independent variables φ and φ

[0018] In the Cartesian coordinate system, the X axis represents the value of φ , and the Y axis represents The value; and The value is in the range [-1, 1]; conflict-free regions and conflict regions are separated by straight lines. Division;

[0019] According to drone A i and drone A j The initial state is obtained A conflict-free region is defined as: In actual conflicts, The minimum distance between the non-conflict regions is represented by a vector. To describe.

[0020] Furthermore, pairwise conflicts include actual conflicts and potential conflicts; the actual conflicts include normal actual conflicts and singular actual conflicts; the potential conflicts include normal potential conflicts and singular potential conflicts.

[0021] The definition of actual conflict is: if two drones maintain their current motion state and the distance between them will be less than the preset safe distance in the future, then it is determined that an actual conflict has occurred between the two drones.

[0022] The definition of potential conflict is: if there is no actual conflict between two drones, but according to the drones' maneuverability range, inappropriate heading maneuvers by the drones would lead to an actual conflict, then a potential conflict is determined to exist between the two drones.

[0023] The definition of a normal actual conflict is: if there is an actual conflict between two drones, and the angle value is calculated based on the states of the two drones and the safe distance between them. and Within semicircles with different sine values, such actual conflicts are judged as normal actual conflicts;

[0024] The singular actual collision is defined as: if there is an actual collision between two drones, and the angle value is calculated based on the states of the two drones and the safe distance between them. and Within the same sine value semicircle, such a real conflict is determined to be a singular real conflict;

[0025] The definition of a normal potential conflict is: if there is a potential conflict between two drones, and the angle value is calculated based on the states of the two drones and the safe distance between them. and Within semicircles with different sine values, such potential conflicts are judged as normal potential conflicts;

[0026] The definition of the singular potential conflict is: if there is a potential conflict between two UAVs, and the angle value calculated according to the state of the two UAVs and the safety distance is and in the same sine value semicircle, then such a potential conflict is determined as a singular potential conflict.

[0027] Further, when the pairwise conflict type is a normal actual conflict, the coordination method comprises:

[0028] According to and determine the feasible region of the heading angle and , wherein the angle value greater than 0 is defined as left turn, and the angle value less than 0 is defined as right turn.

[0029] Further, when the pairwise conflict type is a singular actual conflict, the coordination method comprises:

[0030] Both UAVs should turn right at the same time to avoid the danger of losing the safety distance, and the heading angle and should be and the UAV involved in the singular conflict should search for a conflict resolution strategy, so that the UAV generates a feasible region.

[0031] Further, in order to avoid too large heading maneuver, an iterative method is used to generate the feasible region, that is, the conflict between the UAVs is realized by a series of small avoidance maneuvers to achieve the safe separation between the UAVs:

[0032] Define the constraint condition

[0033] The two UAVs will update the heading angle to predict the minimum distance d min and the remaining time t lose before losing the safety distance, and the expressions are as follows:

[0034]

[0035] Define the conflict avoidance evaluation parameter as:

[0036]

[0037] Where t c is a constant; is the latest time when the singular actual conflict needs to be completely solved;

[0038] In the kth improved planning process, the heading angle should be rate greater than 1, and the definition and then the feasible region of UAV A i is denoted as

[0039] Further, when the pairwise conflict type is normal potential conflict, the coordination method comprises:

[0040] Based on the decoupling method, the UAVs involved in the potential conflict can independently determine their directional adjustment constraint conditions, boundary values are defined as the boundary maneuver angle is determined by trigonometric calculation, and is defined as and the feasible region of UAV A i is denoted as wherein is the maximum angle of left turning of UAV A i .

[0041] Further, when the pairwise conflict type is singular potential conflict, the coordination method comprises:

[0042] When one UAV is restricted to perform a large right turning maneuver, the other UAV which can freely right turn will change its movement direction according to to expand the maneuver range of the other party, wherein μ is a predefined coefficient.

[0043] Further, the feasible region and the optimal heading are optimized online to obtain an optimal heading change angle, comprising:

[0044] After the feasible direction region and the optimal heading are determined, the optimal heading maneuver angle in the feasible direction region which can minimize the objective function is searched as the optimal heading change angle;

[0045] wherein the expression of the objective function is:

[0046]

[0047]

[0048]

[0049] In the formula, is the maneuver angle of UAV A i , is the angle difference between the current flight direction and the optimal flight direction of UAV A i ; is the maximum angle that UAV A i can turn within a time period τ, is the safety separation constraint boundary value of UAV A i in the lth pairwise conflict, For unmanned aerial vehicle A i The number of pairwise conflicts involved.

[0050] Another technical solution adopted by the present application is:

[0051] An online conflict resolution device for close-range flight of multiple unmanned aerial vehicles, comprising:

[0052] At least one processor;

[0053] At least one memory for storing at least one program;

[0054] When the at least one program is executed by the at least one processor, the at least one processor implements the method as described above.

[0055] The present application has the beneficial effects that: the present application proposes to define angles and based on the relative distance, motion state and safety radius of two mutually conflicting unmanned aerial vehicles according to the geometric navigation method, and classifies the conflicts involved by the two unmanned aerial vehicles into normal conflicts and singular conflicts based on the positions of the two angles in the sine value circle. This classification method reveals the differences between the conflicts involved by the two unmanned aerial vehicles from a deeper level. The present application further proposes to explicitly resolve the conflicts of the unmanned aerial vehicles according to this classification method. Such a decentralized coordination strategy can ensure the safe and orderly flight of a large number of unmanned aerial vehicles in close-range flight. BRIEF DESCRIPTION OF DRAWINGS

[0056] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the following introduces the drawings of the related technical solutions in the embodiments of the present application or the prior art. It should be understood that the drawings in the following introduction are only for the convenience of clearly describing part of the embodiments in the technical solutions of the present application, and for those skilled in the art, other drawings can also be obtained from these drawings without creative labor.

[0057] Figure 1 is a schematic diagram of pairwise conflicts between two unmanned aerial vehicles based on a collision cone in the embodiments of the present application;

[0058] Figure 2 is a schematic diagram of a conflict avoidance strategy in the embodiments of the present application;

[0059] Figure 3 is a schematic diagram of a feasible region of relative velocity and heading in the embodiments of the present application;

[0060] Figure 4 is a schematic diagram of safety separation constraints of actual pairwise conflicts and potential pairwise conflicts in the new Cartesian coordinate system in the embodiments of the present application;

[0061] Figure 5 is a schematic diagram of the relationship analysis of the value and the angle

[0062] Figure 6 is a schematic diagram of the iterative conflict improvement process in the embodiment of the present application;

[0063] Figure 7 is a schematic diagram of the related variables in the iterative improvement method in the embodiment of the present application;

[0064] Figure 8 is a schematic diagram of the cooperative adjustment coordination of the potential conflict unmanned aerial vehicle in the embodiment of the present application;

[0065] Figure 9 is a schematic diagram of the decentered conflict resolution flowchart in the embodiment of the present application. DETAILED DESCRIPTION

[0066] The embodiments of the present application are described in detail below, examples of which are shown in the accompanying drawings, wherein the same or similar notations represent the same or similar elements or elements having the same or similar functions throughout. The embodiments described below by referring to the accompanying drawings are exemplary and are only used to explain the present application, and cannot be understood as a limitation of the present application. For the step numbers in the following embodiments, they are only set for the convenience of description and explanation, and the order between the steps is not limited in any way, and the execution order of each step in the embodiments can be adaptively adjusted according to the understanding of those skilled in the art.

[0067] In the description of the present application, it should be understood that the orientation description, such as the orientation or position relationship indicated by up, down, front, back, left, right, etc. is based on the orientation or position relationship shown in the drawings, and is only for the convenience of describing the present application and simplifying the description, and therefore cannot be understood as a limitation of the present application. The device or element indicated is not required to have a particular orientation, to be constructed and operated in a particular orientation, and therefore cannot be understood as a limitation of the present application.

[0068] In the description of the present application, the meaning of several is one or more, and the meaning of multiple is two or more. Greater than, less than, more than, etc. are understood as not including the number, and above, below, etc. are understood as including the number. If the first and the second are described, they are only used for the purpose of distinguishing technical features, and cannot be understood as indicating or implying relative importance or implicitly indicating the number of indicated technical features or the order of indicated technical features.

[0069] ​Further, in the description of the present application, "a plurality of" means two or more, unless otherwise specified. The association relationship of "and / or" describes the association relationship of the associated objects, which means that there can be three relationships, for example, A and / or B can represent the following three cases: A exists alone, A and B exist together, and B exists alone. The character " / " generally represents an "or" relationship between the associated objects before and after it.

[0070] In the description of the present application, unless otherwise explicitly limited, the words such as setting, installing, connecting and the like should be understood in a broad sense, and the person skilled in the art can reasonably determine the specific meaning of the above words in the present application in combination with the specific content of the technical solution.

[0071] In view of the existing technical problems, the present application proposes to define angles based on the relative distance, motion state and safety radius of two mutually conflicting unmanned aerial vehicles according to the geometric navigation method and and classifies the conflict involving the two unmanned aerial vehicles into normal conflict and singular conflict based on the positions of the two angles in the sine value circle. This classification method reveals the difference between the conflicts involving the two unmanned aerial vehicles from a deeper level. The present application further proposes a decentralized coordination strategy for conflict resolution of unmanned aerial vehicles according to this classification method. Such a decentralized coordination strategy can ensure the safe and orderly flight of a large number of unmanned aerial vehicles in close proximity.

[0072] As shown in Figure 9 , the embodiment provides an online conflict resolution coordination method, comprising the following steps:

[0073] Obtain the first state information of itself and the second state information of other unmanned aerial vehicles around, and obtain the task information of itself;

[0074] Determine whether a conflict occurs according to the first state information and the second state information, and after detecting that a conflict occurs, analyze the type of two-by-two conflict, obtain the corresponding coordination method according to the analysis result to coordinate the conflict, and obtain a feasible region; if multiple two-by-two conflicts occur simultaneously, the common region of the feasible regions corresponding to the multiple two-by-two conflicts is taken as the final feasible region;

[0075] Perform task analysis according to the first state information and the task information to obtain an optimal heading;

[0076] Online optimization is performed on the feasible region and the optimal heading to obtain an optimal heading change angle.

[0077] In the embodiment, the above method is named as online conflict resolution coordination method based on classification model (C3R). The process of the decentralized conflict resolution method is as shown in Figure 9As shown, when a drone detects a danger of losing safe distance, it will begin independently resolving the conflict resolution problem: On one hand, the drone analyzes each pair of conflicts it is involved in based on the status of its neighboring drones. Based on the starting angle, pair of conflicts are categorized into normal and singular conflicts. Appropriate coordination methods are used to determine feasible areas based on the type of each pair of conflicts. If multiple pair of conflicts are involved, there will be multiple constraints defined by different pair of conflicts. On the other hand, the drone will determine the optimal heading. It first analyzes the mission requirements. Based on the mission requirements and flight status, temporary objectives can be determined. Then, it generates the optimal heading based on its own status and the temporary objectives. After the drone involved in the conflict determines the feasible area and optimal heading, it will search for the optimal heading maneuver angle that minimizes the objective function. Because all constraints are linear and the objective function is a simple absolute value function, the optimal heading change angle can be effectively determined.

[0078] The above method will be explained in detail below with reference to the accompanying drawings and specific embodiments.

[0079] (1) Kinematics of Unmanned Aerial Vehicles

[0080] Assume there are N drones in a local airspace. For drone A... i (hereinafter referred to as A) i ), i∈N, and its dynamic characteristics can be described using the Cartesian coordinate system. This embodiment mainly studies the conflict resolution of UAVs in two-dimensional space. Equation (1) defines A i State in two-dimensional space:

[0081]

[0082] Where P i (t) represents A i Position; x i (t),y i (t) represents P i (t) Components of φ on the x and y axes; i (t) represents A i The direction of motion in the horizontal plane; v i and w i (t) represent the velocity and rotation rate at time t, respectively. In this embodiment, the vectors are represented in bold. Assuming UAV A... i Its speed is constant when adjusting direction to resolve conflicts, A i The state characteristics are A i Will be controlled by w i (t) is used to resolve airspace conflicts and is subject to condition (2).

[0083]

[0084] where is A i 's minimum turning radius. It is related to the dynamics of v i and A i .

[0085] According to the method of the present embodiment, each UAV needs to achieve the operation of adjusting the direction angle within the time [0, τ]. When is determined, A i will track the adjustment strategy. According to and the amount of look-ahead time [0, τ], the maximum reachable turning angle can be obtained. The maneuvering angle of the UAV within the time period [0, τ] is subject to basic constraints such as formula (3):

[0086]

[0087] (2) Geometric analysis of conflict resolution

[0088] To ensure the safety of the UAVs, a safety region of an exclusive circle with a radius of is defined for each UAV is determined by the platform specifications of A i , such as size, maneuverability, and power.

[0089] The relationship between the UAVs is analyzed using a local coordinate system. As shown in Figure 1 , the current position of A j (hereinafter referred to as A j ) is set as the origin of the local coordinate system. The initial coordinates of A i become (4):

[0090] P i (0) = (x i (0) - x j (0), y i (0) - y j (0)) (4)

[0091] The composite safety region is denoted as where The velocity of A j relative to A i is v ji , and the slope of v ji is k ji :

[0092]

[0093] wherein and is A i and drone A j heading maneuver angle.

[0094] In Figure 1 the scenario shown in (a), v ji is located in the gray triangular region. This means that A j is about to enter the compound safety region of A i , which is defined as an actual conflict. The two drones involved in the actual conflict will lose the safety separation in the future.

[0095] When two drones fly in close proximity in a local airspace, there is another danger. As shown in (b), according to the states of the two drones, their inappropriate heading maneuvers can lead to an actual conflict. This situation is defined as a potential conflict. Figure 1

[0096] To maintain the safety separation from each other, the heading maneuver of a drone should ensure that it not only resolves the existing actual conflict but also does not cause a potential conflict. This means that for the actual / potential pairwise conflicts of drones, the inequalities (6) should be satisfied:

[0097]

[0098] where P ix and P iy are the components of P i (0).

[0099] According to equations (5) and (6), it can be seen that and are coupled in the safety separation constraints. In the decentralized conflict resolution problem, a suitable coordination method is needed to decouple the feasible regions of drones, so that each drone can determine the feasible region in each pair of conflicts independently. i The safety separation constraint in the lth pairwise conflict involving A i can be defined as (7):

[0100]

[0101] where N is the number of pairwise conflicts involving A i .

[0102] The maneuver angle that resolves the conflict should satisfy the safety separation constraints of all N pairwise conflicts. The decentralized coordination method should ensure that each drone has a common feasible region considering all relevant pairwise conflicts.

[0103] (3) Objective function

[0104] Conflict resolution considers finding the least costly avoidance strategy. A drone's directional maneuvers will cause it to deviate from its intended flight path. After the conflict is resolved, the drone will return to its intended flight path. This results in an additional flight distance. The cost of the drone is described in terms of this additional flight distance.

[0105] In multi-drone online conflict resolution scenarios, replanning the entire flight path for each drone is inefficient. Instead, drones will determine suitable temporary targets based on a predetermined flight path and the conflict situation. The optimal heading of a drone towards its temporary target is defined as follows: Figure 2 As shown, there is a positive correlation between the additional flight distance of each drone and the deviation from the optimal heading. A difference is expected between the preferred heading and the current heading for each drone, expressed as follows:

[0106] In order to utilize this bias to evaluate A i The objective function is defined as (8) to determine the additional flight distance:

[0107]

[0108] This objective function is nonlinear. The solution to equation (8) should satisfy the constraints defined in (3) and (7). Each UAV aims to minimize its own objective function, so the priority of other UAVs is not considered.

[0109] (4) Decentralized conflict resolution methods

[0110] This section explores a decentralized conflict resolution approach to generate effective conflict avoidance solutions for each drone.

[0111] As mentioned above, in each pairwise conflict involving each drone individually, a decentralized coordination method is needed to generate its feasible region. Furthermore, this coordination method should ensure that all pairwise conflicts involving a single drone share a common feasible region. Therefore, a carefully designed decentralized coordination method is required.

[0112] 4.1) Linearization Methods

[0113] The safety separation constraint defined in inequality (6) is further discussed. Equation (9) is defined based on the boundary conditions:

[0114]

[0115] When A i With A j The distance between them is greater than When the time comes, the root of equation (9) is:

[0116]

[0117] where

[0118] Since the conflict resolution problem does not change with the rotation of the coordinate system, the safety separation constraint in the local coordinate system is discussed, as shown in Figure 3

[0119] The feasible solution region of inequality (6) is determined by and

[0120]

[0121] As shown in Figure 3 , in the pairwise conflict scenario, the unsafe region is the acute angle region formed by two rays with slopes and . The two UAVs can avoid the danger of excessive proximity by taking a coordinated heading maneuver, making A j pass D ij from the left or right side.

[0122] When a UAV encounters multiple pairwise conflicts, the conflict avoidance strategies for different pairwise conflicts should not contradict each other. Therefore, one of the primary requirements of the coordination method is to ensure that each UAV has its feasible heading maneuver region on the same side (left or right) of its flight direction under all pairwise conflicts it is involved in.

[0123] Since each UAV can only determine its own maneuver strategy, in order to make the conflict avoidance maneuver effective, there needs to be a consistent agreement on the safety separation constraint for each pair of conflicts. Therefore, the UAVs involved in the conflict can take a coordinated heading maneuver. From a broader perspective, the UAVs in the local airspace can generate consistent maneuver strategies.

[0124] In many fields, all agents choose to turn right to avoid neighbors, which is a general rule. The right-turn strategy is useful in decentralized conflict resolution problems. If all UAVs search for conflict avoidance solutions based on the right-side condition, they will fly in order.

[0125] According to the right-turn strategy, the constraint conditions of and are further discussed. As shown in Figure 3 , if two UAVs generate conflict avoidance strategies according to the constraint conditions generated based on , they will pass each other from the right side of D ij . According to equation (6) and constraint condition (11), inequality (12) can be obtained when : ​​

[0126]

[0127] in

[0128] Since the constraint contains a sine function, the feasible region is non-convex. To simplify the analysis, the function... and Treat them as independent variables and Define the starting angle To describe A i and A j In the pairwise conflicts between A i The initial state. By A i The correlation between initial course and conflict avoidance Composition. The value of this angle is crucial for subsequent research.

[0129] Discussing conflict resolution within a new Cartesian coordinate system, such as Figure 4 As shown. The X-axis represents... The value, represented by the Y-axis The value of . and The value is in the range [-1, 1]. In the new Cartesian coordinate system, each pair of conflicting safety separation constraints is linear. Therefore, it is convenient to discuss coordination methods to avoid conflicts.

[0130] 4.2) Relevant Coordination Methods for Actual Conflicts

[0131] like Figure 4 As shown, in the new Cartesian coordinate system, conflict-free regions and conflict regions are represented by straight lines. Division. yes The angle between the x-axis and the x-axis. According to A i and A j The initial state is obtained A conflict-free region is defined as: In actual conflicts, The minimum distance between a region and a conflict-free region can be represented by a vector. This vector can be used to decouple the responsibility for conflict resolution from UAVs. Figure 4 Taking the case in (a) as an example, the decoupling rule is defined as: A i A heading maneuver should be adopted. make The value must increase at least A j A heading maneuver should be adopted. make The value must increase at least

[0132] According to the defined safety separation constraint condition, A i and A j should pass by each other's right side and move away from each other. It is expected that all the UAVs involved in the conflict can generate right turn maneuvering range according to the right side condition. However, due to the UAVs in various situations, the right side condition does not always generate the right turn strategy of the UAVs.

[0133] The characteristics of different types of pairwise conflicts in the unit circle are analyzed, such as Figure 5 as shown. This circle is named as the sine value circle. and The angle value of and is the angle between the unit vector and the positive direction of the horizontal axis. and The sine value of and is the projection of the unit vector on the vertical axis. The circle is divided into two semicircles by the vertical axis. In the right semicircle, the sine value increases with the increase of the angle. It is named as the positive direction semicircle. In the left semicircle, the sine value decreases with the increase of the angle. It is named as the negative direction semicircle.

[0134] As shown in Figure 4 , in order to avoid the conflict, one of and needs to increase and the other needs to decrease. For the pairwise conflict involving UAVs, there are two different cases:

[0135] a) and are in different semicircles

[0136] When and are in different semicircles, the two UAVs need to turn to the same side along their flight direction.

[0137] According to the selected right turn avoidance requirement, the possibility that the two UAVs involved in the conflict need to turn left to solve the conflict can be excluded. That is, both UAVs need to pass through the right turn to eliminate the conflict, and such a conflict is defined as a normal actual conflict. The definition is reorganized as follows:

[0138] If there is an actual conflict between two UAVs, and the angle values and calculated by the two UAVs after calculation are in different sine value semicircles, then such an actual conflict is a normal actual conflict.

[0139] Under this condition, and the feasible region can be directly determined according to and Determination. As Figure 4 (a) shows, the no-conflict region is defined as the boundary value of the heading maneuver angle and can be determined by trigonometric calculation. Thus, the feasible region of A j when A i is considered in any lth pairwise conflict can be determined, denoted as

[0140] b) and are in the same semicircle

[0141] When and are in the same semicircle, the coordination problem becomes more complex. As Figure 4 (a) shows, and one needs to increase, and the other needs to decrease. According to the same correlation between the angle and the sine value of the angle, one UAV needs to turn left, and the other UAV needs to turn right. This is contradictory to the simultaneous right-turn strategy. Such a pairwise conflict is defined as a singular actual conflict.

[0142] If there is an actual conflict between two UAVs, and the calculated angle values and of the two UAVs are in the same semicircle of the sine value, then such an actual conflict is a singular actual conflict.

[0143] When two UAVs encounter a singular actual conflict, the linearization method cannot be used to generate the feasible region of the UAVs. An appropriate coordination method is needed to ensure that the UAVs generate a right-turn strategy.

[0144] Suppose that two UAVs turn right to avoid the danger of losing the safety distance. The heading maneuver angles and should satisfy the inequality (13):

[0145]

[0146] Define and let the UAVs involved in the singular conflict search for conflict resolution strategies according to constraint (13), then these UAVs can consistently generate the feasible region. However, the corresponding heading maneuvers of the two UAVs may be too large. Therefore, in most cases, it is inefficient and impractical to let the UAVs resolve the conflict through one maneuver.

[0147] Because the forward-looking time window is [0, τ], the two drones have sufficient time to change course before losing safe distance. Therefore, this embodiment proposes an iterative improvement method, whereby a collision between drones can be safely separated through a series of small evasive maneuvers, such as... Figure 6 As shown.

[0148] During the conflict mitigation process, the two drones will continuously mitigate the threat of conflict until the actual conflict is completely resolved. Define constraints. like Figure 7 As shown. The two drones will update their maneuver angles. To predict the minimum distance between them and the remaining time before losing the safe distance, they are denoted as d. min and t lose . t lose Defined as:

[0149]

[0150] The conflict avoidance evaluation parameter is defined as:

[0151]

[0152] Where t c It is a constant. This is the latest time when the singular actual conflict needs to be completely resolved. This value is set to ensure the flight safety of both drones.

[0153] The iterative conflict improvement method is as follows: during the k-th improvement planning process, the heading maneuver... c rate Guaranteed to be greater than 1. Definition and A i The feasible region is denoted as

[0154] Iterative improvement methods have two advantages. First, and The value will vary with the flight direction φ i and φ j And change. During the iteration process... and It is possible that it will transform into different semicircles, thus converting a singular conflict into a normal conflict. Secondly, by adjusting φ... i and φ j With iterative corrections, drones do not need to perform drastic directional maneuvers. Therefore, they have a relatively small impact on local air traffic.

[0155] 4.3) Coordination methods related to potential conflicts

[0156] In multi-drone conflict scenarios, a drone should consider potential conflicts when planning conflict avoidance maneuvers.

[0157] There are two possibilities for potential conflicts between drones. One is the relative velocity v. ij Is it on the left or right side of the collision cone? Figure 3 As shown. To ensure air traffic order and flight safety, A... i With A j relative velocity v ij The situation to the left of the collision cone is considered an actual collision. Because when v ij When on the left side of the collision cone, if A i With A j If the conflict between the two drones is considered a potential conflict, then due to safety separation constraints, the two drones will be restricted from making large right turns. This will limit the drones from generating feasible right-turn maneuvers in response to other existing conflicts they are involved in; therefore, the potential conflict of the relative velocities of the two drones to the left of the collision cone is considered an existing conflict.

[0158] Therefore, we only consider the case where two drones engage in potential pairwise collisions, and v ij The situation is on the right side of the collision cone. In potential pairwise collision scenarios, the maneuver range of the two drones can be determined by the values ​​obtained through a linear decoupling method, such as... Figure 4 As shown in (b). In the coordinate system middle, and The feasible region can be determined by and To determine. Contrary to actual conflict scenarios, and Decision made and The maximum adjustable value.

[0159] Since drones search for right-turn maneuvers to resolve actual conflicts based on a right-turn strategy, there should not be too many restrictions on the feasible right-turn range for drones involved in actual conflicts when they encounter potential conflicts. Therefore, it should be clearly stated... and Coordination methods under different circumstances.

[0160] a) and In different semicircles

[0161] Based on the above discussion, when and Within different semicircles, there is only one possibility: an inappropriate left turn by the drone could lead to a dangerous actual conflict. Therefore, this type of potential conflict does not affect the drone's right turn and is defined as a normal potential conflict.

[0162] If there is a potential conflict between two UAVs, while the angle values of the two UAVs determined by calculation and are in different sinusoidal value semicircles, then such a potential conflict is a normal potential conflict.

[0163] Based on the decoupling method, the UAV involved in the potential conflict can independently determine its directional adjustment constraint condition. It is similar to the actual conflict, the boundary value is defined as the angle boundary value that can maneuver to the left side can be determined by trigonometric calculation. Define and the feasible region of A i is recorded as

[0164] b) and are in the same semicircle

[0165] According to the above discussion, when and are in the same semicircle, the two UAVs will be restricted from making a large right turn maneuver. This type of potential conflict is defined as a singular potential conflict.

[0166] If there is a potential conflict between two UAVs, while the angle values of the two UAVs determined by calculation and are in the same sinusoidal value semicircle, then such a potential conflict is a singular potential conflict.

[0167] A method of coordinated adjustment is designed for this case. Because the two UAVs can detect singular potential conflicts according to their respective states. The proposed coordination method is as follows:

[0168] When one UAV is restricted to make a large right turn maneuver, the other UAV that can freely right turn will change its movement direction according to to expand the other's maneuvering range, where μ is a predefined coefficient. μ is less than 1.

[0169] As Figure 8 shown, assuming A j can freely right turn in a singular potential conflict, and represent the restrictions on and respectively. According to the decoupling rule, the limited value of A i indicates that A j cannot make a large right turn. If A j right turns with angle , then there is Therefore, the new location It will be A i exist The feasible region will be expanded to:

[0170]

[0171] Although drone A i The maneuverable right turn range is expanded to (16), but from A i From this perspective, it cannot fully understand A. j The surrounding environment. Therefore, A. i Unable to know The exact value cannot be determined. The value of A. i The only certainty is that when they encounter a single potential conflict, A j It will not turn left. Therefore, A i Can occupy by A defined range. i The maximum adjustable unit becomes:

[0172]

[0173] Drone A i Based on Generate boundary maneuver angle definition And A i The feasible region is denoted as At the same time, A j The feasible area is

[0174] According to the coordination method, if A i If a serious actual conflict occurs, it can continue to turn right because A j It will continue to make room for it. This coordination method ensures a high level of coordination between drones.

[0175] (5) Online conflict resolution coordination method based on classification model

[0176] The method proposed in this embodiment has been described in detail above. In this embodiment, the method is named the online conflict resolution coordination method based on a classification model (C3R).

[0177] The decentralized conflict resolution method process is as follows: Figure 9 As shown. When a drone detects a danger of losing safe distance, it will begin to independently resolve the conflict:

[0178] On one hand, it analyzes each pairwise conflict involved based on the state of its neighboring machines. According to the starting angle defined earlier, pairwise conflicts are categorized into normal conflicts and singular conflicts. Based on the type of each pairwise conflict, an appropriate coordination method is used to determine the feasible region. If it involves multiple pairwise conflicts, there will be multiple constraints defined by different pairwise conflicts.

[0179] On the other hand, the drone will determine the optimal course. It will first analyze the mission requirements. Based on the mission requirements and flight status, a temporary target can be identified. Then, it will generate the optimal course based on its own status and the temporary target.

[0180] After determining the feasible area and optimal heading for the UAV involved in the conflict, it will search for the optimal heading maneuver angle that minimizes the objective function. Because all constraints are linear and the objective function is a simple absolute value function, the optimal heading change angle can be effectively determined.

[0181] This application also discloses a computer program product or computer program, which includes computer instructions stored in a computer-readable storage medium. A processor of a computer device can read the computer instructions from the computer-readable storage medium and execute the computer instructions, causing the computer device to perform... Figure 9 The method shown.

[0182] This embodiment also provides a drone, which is equipped with such... Figure 9 The program illustrates an online conflict resolution method for multiple drones flying close together. When surrounding drones are detected, the drones resolve conflicts using this method.

[0183] This embodiment also provides an online conflict resolution device for multiple drones, including:

[0184] At least one processor;

[0185] At least one memory for storing at least one program;

[0186] When the at least one program is executed by the at least one processor, the at least one processor performs the following: Figure 9 The method shown.

[0187] This embodiment of the multi-drone online conflict resolution device can execute the online conflict resolution method for close-range flight of multiple drones provided in the method embodiment of the present invention. It can execute any combination of the implementation steps of the method embodiment and has the corresponding functions and beneficial effects of the method.

[0188] The embodiment also provides a storage medium storing instructions or programs for executing the online conflict resolution method for close-range flight of multiple unmanned aerial vehicles provided by the method embodiment of the application, when the instructions or programs are executed, any combination of the method embodiments can execute the steps, and has the corresponding functions and advantages of the method.

[0189] In some alternative embodiments, the functions / operations mentioned in the block diagram can not occur in the order mentioned in the operation diagram. For example, depending on the functions / operations involved, two blocks shown in succession can actually be executed substantially simultaneously with each other or the blocks can sometimes be executed in reverse order. In addition, the embodiments presented and described in the flowcharts of the present application are provided by way of example, with the purpose of providing a more comprehensive understanding of the technology. The disclosed method is not limited to the operations and logical flows presented herein. Alternative embodiments are contemplated in which the order of various operations is changed and in which sub-operations described as part of a larger operation are independently executed.

[0190] In addition, although the present application is described in the context of functional modules, it should be understood that, unless otherwise stated to the contrary, one or more of the described functions and / or features can be integrated in a single physical device and / or software module, or one or more functions and / or features can be implemented in separate physical devices or software modules. It can also be understood that a detailed discussion of the actual implementation of each module is unnecessary for an understanding of the present application. Rather, given the properties, functions and internal relationships of the various functional modules in the devices disclosed herein, the actual implementation of the module will be within the routine skill of the engineer, given the benefit of this disclosure. Thus, the present application, as set forth in the claims, is capable of being practiced without resort to undue experimentation in light of the disclosure presented herein. It can also be understood that the disclosed specific concepts are merely illustrative and are not intended to limit the scope of the present application, which is defined by the full scope of the appended claims and their equivalents.

[0191] If the functions are implemented in the form of software function units and sold or used as independent products, they can be stored in a computer readable storage medium. Based on this understanding, the technical solutions of the present application or the parts of the technical solutions that essentially contribute to the prior art or the parts of the technical solutions can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes a plurality of instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present application. The aforementioned storage medium includes: a U disk, a mobile hard disk, a read-only memory (ROM, Read-Only Memory), a random access memory (RAM, Random Access Memory), a magnetic disk or an optical disk, and various media that can store program codes.

[0192] The logic and / or steps represented in the flowcharts or otherwise described herein, for example, can be considered as a list of executable instructions for implementing logic functions, which can be embodied in any computer-readable medium for use by or in connection with an instruction execution system, apparatus or device, such as a computer-based system, a system including a processor or other system that can fetch the instructions from the instruction execution system, apparatus or device and execute the instructions, or in conjunction with these instructions execution systems, apparatus or devices. For the purpose of this specification, the "computer-readable medium" can be any device that can contain, store, communicate, propagate or transport programs for use by or in connection with an instruction execution system, apparatus or device, or in conjunction with these instruction execution systems, apparatus or devices.

[0193] More specific examples (a non-exhaustive list) of the computer-readable medium include the following: an electrical connection having one or more wires (electrical devices), a portable computer diskette (magnetic devices), a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disc read-only memory (CDROM). In addition, the computer-readable medium can even be paper or other suitable medium on which the program can be printed, because the program can be electronically obtained, for example, by optical scanning of the paper or other medium, followed by editing, interpreting or otherwise processing, if necessary, in other suitable ways, to be electronically obtained and then stored in the computer memory.

[0194] It should be understood that various parts of the present application can be implemented in hardware, software, firmware or a combination thereof. In the above embodiments, various steps or methods can be implemented in software or firmware that is stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, any of the following technologies, known in the art, or their equivalents, can be employed for implementation: discrete logic circuitry having logic gates for implementing logic functions upon data signals, application specific integrated circuits having appropriate combinational logic gates, programmable gate arrays (PGA), field programmable gate arrays (FPGA), and the like.

[0195] In the above description of the present specification, the description of the terms "one embodiment / one example", "another embodiment / another example", or "certain embodiments / certain examples" and the like means that the specific features, structures, materials or characteristics described in connection with the embodiments or examples are included in at least one embodiment or example of the present application. In the present specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Also, the specific features, structures, materials or characteristics described can be combined in any one or more embodiments or examples in a suitable manner.

[0196] Although the embodiments of the present application have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and variations can be made thereto without departing from the principles and spirit of the present application, the scope of which is defined by the claims and their equivalents.

[0197] The above is a specific description of the preferred embodiments of the present application, but the present application is not limited to the above-described embodiments, and those skilled in the art can make various equivalent modifications or substitutions without departing from the spirit of the present application, and these equivalent modifications or substitutions are included in the scope defined by the claims of the present application.

Claims

1. An online conflict resolution method for close-range flight of multiple unmanned aerial vehicles, characterized in that, The method is independently executed by each unmanned aerial vehicle and comprises the following steps: acquiring state information of the unmanned aerial vehicle and surrounding unmanned aerial vehicles and task information of the unmanned aerial vehicle; judging whether a conflict occurs according to the state information of the unmanned aerial vehicle and surrounding unmanned aerial vehicles, performing two-by-two conflict type analysis after detecting that a conflict occurs, determining a corresponding coordination method for conflict coordination according to an analysis result, and obtaining a feasible region; if a certain unmanned aerial vehicle is involved in multiple two-by-two conflicts, a common region of feasible regions corresponding to the multiple two-by-two conflicts is taken as a final feasible direction region; performing task analysis according to the state information and task information of the unmanned aerial vehicle to obtain an optimal heading direction; performing online optimization on the feasible direction region and the optimal heading direction to obtain an optimal heading change angle; the online conflict resolution method of the multiple unmanned aerial vehicles comprises the following steps of discussing conflict resolution through a Cartesian coordinate system: acquiring a no-conflict constraint condition of the two unmanned aerial vehicles according to a right-turn strategy: wherein, , is the speed of the UAV A i and the UAV A j , , is the direction of motion of the UAV A i and the UAV A j , , is the angle of maneuver of the UAV A i and the UAV A j , is the critical slope of the right feasible region; Consider the functions and as arguments and respectively. In the Cartesian coordinate system, the X axis represents the value of and the Y axis represents the value of ; and the values of the values in the range [-1, 1]; the non-conflict area and the conflict area are divided by the straight line ; According to drone A i and drone A j The initial state is obtained A conflict-free region is defined as: In actual conflicts, The minimum distance between the region and the conflict-free region is represented by a vector. To describe; the two-by-two conflict comprises an actual conflict and a potential conflict; the actual conflict comprises a normal actual conflict and a singular actual conflict; the potential conflict comprises a normal potential conflict and a singular potential conflict; the actual conflict is defined as: if two unmanned aerial vehicles maintain a current motion state and a distance between the two unmanned aerial vehicles is less than a preset safe distance in the future, it is determined that an actual conflict occurs between the two unmanned aerial vehicles; the potential conflict is defined as: if an actual conflict does not exist between two unmanned aerial vehicles, but when the two unmanned aerial vehicles appear an inappropriate heading maneuver, the actual conflict will be caused according to a maneuverable range of the unmanned aerial vehicles, it is determined that a potential conflict occurs between the two unmanned aerial vehicles; The definition of the normal actual conflict is: if there is an actual conflict between two unmanned aerial vehicles, and the angle value calculated according to the state and safety distance of the two unmanned aerial vehicles is and In different sine value semicircles, such an actual conflict is determined as a normal actual conflict; The definition of the singular actual conflict is: if there is an actual conflict between two UAVs, and the angle value calculated according to the state of the two UAVs and the safety distance is and In the same sine value semicircle, such an actual conflict is determined as a singular actual conflict; The definition of the normal potential conflict is: if there is a potential conflict between two unmanned aerial vehicles, and the angle value calculated according to the state and safety distance of the two unmanned aerial vehicles is and In different sine value semicircles, such a potential conflict is determined as a normal potential conflict; The definition of the singular potential conflict is: if there is a potential conflict between two UAVs, and the angle value calculated according to the state of the two UAVs and the safety distance is and In the same sine value semicircle, such a potential conflict is determined as a singular potential conflict.

2. The online conflict resolution method for close-range flight of multiple UAVs according to claim 1, wherein, when the two-by-two conflict type is a normal actual conflict, the coordination method comprises: According to and determining the feasible region of the two drones' angular velocities, where an angular value greater than 0 is defined as a left turn and an angular value less than 0 is defined as a right turn. and determining the feasible region of the two drones' angular velocities, where an angular value greater than 0 is defined as a left turn and an angular value less than 0 is defined as a right turn.

3. The online conflict resolution method for close proximity flight of multiple UAVs according to claim 1, wherein, when the two-by-two conflict type is a singular actual conflict, the coordination method comprises: Both drones should turn right at the same time to avoid the danger of losing the safe distance and define the feasible region for each drone to search.

4. The online conflict resolution method for close-range flight of multiple UAVs according to claim 3, wherein, in order to avoid a large change in the heading maneuver, an iterative improvement method is used to generate a feasible region, that is, a safe separation between the unmanned aerial vehicles is achieved through a series of small avoidance maneuvers: Define constraints ; The two drones will predict their minimum distance and the time remaining before losing safe separation by updating their maneuver angles expressed as follows: a conflict avoidance evaluation parameter is defined as: wherein is a constant; is the latest time at which the actual conflict needs to be completely resolved; In the first k improvement planning process, the heading maneuver should be ensured to be greater than 1, defining and the feasible region of UAV A i as .

5. The online conflict resolution method for close proximity flight of multiple UAVs according to claim 1, wherein, when the two-by-two conflict type is a normal potential conflict, the coordination method comprises: Based on the decoupling approach, the UAVs involved in potential conflicts can independently determine their directional adjustment constraints, boundary values defined as ; boundary maneuver angle determined by trigonometric calculations, defined as and the feasible region of UAV A i is denoted as where is the maximum angle that UAV A i can turn left.

6. The online conflict resolution method for close proximity flight of multiple UAVs according to claim 1, wherein, when the two-by-two conflict type is a singular potential conflict, the coordination method comprises: When one drone is restricted from making large right turns, another drone that can turn right freely will... Change its direction of movement to expand the opponent's range of maneuver, among which It is a predefined coefficient.

7. The online conflict resolution method for close proximity flight of multiple UAVs according to claim 1, wherein, the online optimization of the feasible direction region and the optimal heading direction to obtain the optimal heading change angle comprises: after the feasible direction region and the optimal heading direction are determined, a best heading maneuver angle that can minimize a target function is searched in the feasible direction region as the optimal heading change angle; an expression of the target function is: In the formula, is the maneuvering angle of the UAV A i , is the angle difference between the current flight direction and the optimal flight direction of the UAV A i , is the maximum angle that the UAV A i can turn within the time period , , is the safe separation constraint boundary value of the UAV A i in the first l pairwise conflict, is the number of pairwise conflicts involved in the UAV A i .

8. An online conflict resolution apparatus for close proximity flight of multiple unmanned aerial vehicles, characterized in that, comprise: at least one processor; at least one memory for storing at least one program; when the at least one program is executed by the at least one processor, the at least one processor implements the method in any one of claims 1-7.

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