A method, system, device and medium for determining a simulated trajectory of an aircraft

Abstract

The present application relates to the field of path planning technology, and discloses a method, system, device and medium for determining a simulated trajectory of an aircraft, including: determining a speed sampling window based on the physical structure of the aircraft and obstacle information; using the speed sampling window to obtain the speed combination of the aircraft within the sampling time; constructing a dynamic window evaluation function including a trajectory point distance evaluation function and a guide point distance evaluation function; wherein the trajectory point distance evaluation function is used to characterize and measure the positional relationship between the simulated trajectory of the aircraft and the simulated trajectory of the obstacle; the guide point distance evaluation function is used to characterize and guide the aircraft to detour in a specified direction to reduce the randomness of the obstacle avoidance movement; using the dynamic window evaluation function to score the simulated trajectory of the aircraft corresponding to the speed combination, and determining the simulated trajectory of the target aircraft based on the scoring result. Its beneficial effect is to enhance the simulated trajectory of the aircraft in a dynamic obstacle environment and achieve accurate obstacle avoidance.

Description

Technical Field

[0001] The present application relates to the field of path planning technology, and in particular to a method, system, device and medium for determining a simulated trajectory of an aircraft. Background Art

[0002] In the field of aircraft obstacle avoidance and path planning, the Dynamic Window Approach (DWA) is a widely used local path planning algorithm, mainly used for real-time obstacle avoidance and navigation. The DWA algorithm dynamically calculates the optimal moving window to generate a safe navigation path by considering the dynamic limitations of the aircraft (such as speed, acceleration, etc.) and the target obstacles in its surrounding environment. The advantage of this method is that it can efficiently handle the problem of avoiding obstacles in the navigation environment and can provide smooth path planning to ensure the safety and flexibility of the aircraft in complex environments.

[0003] Although the DWA algorithm has shown good performance in practical applications, it has an important limitation, that is, it fails to fully consider the dynamic characteristics of potential obstacles, such as the movement speed and steering changes of obstacles. This neglect may cause the vehicle to collide with obstacles with rapidly changing positions during the obstacle avoidance process.

[0004] Therefore, how to improve the relevant evaluation functions to enhance the simulated trajectory of the vehicle in a dynamic obstacle environment and achieve accurate obstacle avoidance is a problem that needs to be solved urgently. Summary of the invention

[0005] The present application provides a method, system, device and medium for determining a simulated trajectory of an aircraft, which solves the technical problem of how to improve relevant evaluation functions to enhance the simulated trajectory of an aircraft in a dynamic obstacle environment, thereby achieving the technical effect of enhancing the simulated trajectory of an aircraft in a dynamic obstacle environment and realizing precise obstacle avoidance.

[0006] In order to achieve the above objectives, the main technical solutions adopted in this application include:

[0007] In a first aspect, an embodiment of the present application provides a method for determining a simulated trajectory of an aircraft, the method comprising:

[0008] Determine the speed sampling window based on the physical structure of the spacecraft and obstacle information;

[0009] Using the speed sampling window to obtain the speed combination of the aircraft within the sampling time;

[0010] Constructing a dynamic window evaluation function including a trajectory point distance evaluation function and a guide point distance evaluation function; wherein the trajectory point distance evaluation function is used to characterize and measure the positional relationship between the simulated trajectory of the aircraft and the simulated trajectory of the obstacle; and the guide point distance evaluation function is used to characterize and guide the aircraft to detour in a specified direction to reduce the randomness of the obstacle avoidance motion;

[0011] The dynamic window evaluation function is used to score the simulated trajectory of the aircraft corresponding to the speed combination, and the simulated trajectory of the target aircraft is determined based on the scoring result.

[0012] This embodiment provides a method for determining a simulated trajectory of an aircraft. By determining a speed sampling window based on the physical structure of the aircraft and obstacle information, it can ensure that the aircraft maintains optimal flexibility and responsiveness in a complex environment. Then, multiple speed combinations are obtained within the sampling time to provide a rich data basis for subsequent decisions and improve the accuracy and efficiency of obstacle avoidance decisions. When constructing a dynamic window evaluation function, the trajectory point and guide point distance evaluation functions are combined so that the simulated path of the aircraft can evaluate the safe distance between the aircraft and obstacles in real time, reduce the risk of collision, and ensure that the aircraft moves along the predetermined path to reduce arbitrariness. Finally, by scoring the simulated trajectory, the optimal motion path can be effectively screened out, thereby improving the success rate of obstacle avoidance and achieving more efficient path planning.

[0013] Optionally, the trajectory point distance evaluation function is constructed in the following manner:

[0014] Determine a first set of potential threat obstacles within a predetermined trajectory point distance evaluation function range;

[0015] Acquire speed information and position information of a first potential threat obstacle in the first potential threat obstacle set, and generate obstacle simulation trajectory point coordinates corresponding to the first potential threat obstacle using a trajectory point simulation model;

[0016] The trajectory point distance evaluation function is constructed based on the coordinates of the obstacle simulation trajectory points, the distance between the aircraft and the first potential threat obstacle, and the aircraft simulation trajectory.

[0017] This embodiment can effectively screen out obstacles that pose a threat to the safety of the aircraft and improve the aircraft's obstacle avoidance capability by determining the first set of potential threat obstacles within the range of action of the pre-set trajectory point distance evaluation function. Next, the speed and position information of these potential threat obstacles are obtained, and the corresponding obstacle simulation trajectory point coordinates are generated using the trajectory point simulation model. It not only provides the dynamic characteristics of potential obstacles, but also lays the foundation for subsequent trajectory analysis, which helps to more accurately predict its future position. Finally, based on the obstacle simulation trajectory point coordinates, the distance between the aircraft and the potential threat obstacle, and the simulated trajectory of the aircraft, a trajectory point distance evaluation function is constructed. This evaluation function can comprehensively consider various factors and evaluate the relative position relationship between the aircraft and the obstacle in real time, thereby providing a scientific basis for subsequent path planning for navigation.

[0018] Optionally, the determining of a first set of potential threat obstacles within a range of action of a preset trajectory point distance evaluation function includes:

[0019] For any obstacle, determining a first angle between a line between the aircraft and the obstacle and a velocity vector in the velocity combination, and a straight-line distance between the aircraft and the obstacle;

[0020] Any obstacles within the aircraft area radius whose first angle is less than or equal to the first angle threshold and whose straight-line distance is less than or equal to the aircraft area radius form the first potential threat obstacle set; wherein the aircraft area radius represents a safe distance range determined by the size of the aircraft itself.

[0021] This embodiment determines the first angle between the line between the aircraft and the obstacle and the velocity vector in the velocity combination, as well as the straight-line distance between the two for any obstacle. This process can evaluate the movement trend and distance of the obstacle relative to the aircraft, helping to identify potential collision risks. By including obstacles whose first angle is less than or equal to the first angle threshold and whose straight-line distance is less than or equal to the aircraft's field radius into the first potential threat obstacle set, this screening mechanism ensures that only those obstacles that are within the aircraft's safety range and may affect the navigation path are identified as potential threats. The setting of the aircraft's field radius is a safe distance range determined based on the size of the aircraft, further increasing the safety of the aircraft. The implementation method of the present application can effectively construct a dynamic potential threat obstacle set by accurately evaluating the obstacle's motion state and relative position to the aircraft, thereby improving the aircraft's safety identification capability and response efficiency in complex environments.

[0022] Optionally, the trajectory point simulation model is:

[0023]

[0024] Among them, (x traj ,y traj ) is the coordinate of the obstacle simulation trajectory point; (x oa ,y oa ) is the position information of the first potential threat obstacle; V p is the speed information of the first potential threat obstacle; θ c V p Angle with the horizontal direction; ΔT 1 The simulation time for simulating trajectories for obstacles.

[0025] Optionally, the trajectory point distance evaluation function is:

[0026]

[0027]

[0028]

[0029] Among them, traj_dist(v,w) is the trajectory point distance evaluation function; R is the radius of the spacecraft; p end is the coordinate of the end point of the simulated trajectory of the aircraft; obi is the coordinate of the simulated trajectory point of the i-th obstacle; τ i is the weight of each first potential threat obstacle; n is the number of first potential threat obstacles; d traj The Euclidean distance between the coordinates of the obstacle simulation trajectory point and the coordinates of the end point of the aircraft simulation trajectory; dist ci is the distance between the aircraft and the first potential threatening obstacle; cj is the distance between the aircraft and the jth first potential threat obstacle.

[0030] Optionally, the guiding point distance evaluation function is constructed in the following manner:

[0031] Determine a second potential threat obstacle set located within a predetermined range of action of the guidance point distance evaluation function;

[0032] Acquire speed information and position information of a second potential threat obstacle in the second potential threat obstacle set, and generate obstacle simulation guide point coordinates corresponding to the second potential threat obstacle by using a guide point simulation model;

[0033] The guidance point distance evaluation function is constructed based on the obstacle simulation guidance point coordinates, the distance between the aircraft and the second potential threat obstacle, and the aircraft simulation trajectory.

[0034] This embodiment determines the set of second potential threat obstacles within the range of the preset guidance point distance evaluation function. It can effectively screen out obstacles related to the aircraft path. By obtaining the speed information and position information of the second potential threat obstacle and using the guidance point simulation model to generate the corresponding obstacle simulation guidance point coordinates, it is possible to dynamically reflect the movement state of the obstacle and provide support for the subsequent guidance of the aircraft to bypass the designated side and rear of the obstacle. The guidance point distance evaluation function is constructed based on the obstacle simulation guidance point coordinates, the distance between the aircraft and the second potential threat obstacle, and the aircraft simulation trajectory, which can achieve a comprehensive analysis of the potential threat of obstacles, enabling it to respond faster and more accurately in complex environments to enhance overall navigation safety.

[0035] Optionally, the determining of a second set of potential threat obstacles within a preset range of action of a guidance point distance evaluation function includes:

[0036] For any obstacle, determining a second angle between a line between the aircraft and the obstacle and a velocity vector in the velocity combination, and a straight-line distance between the aircraft and the obstacle;

[0037] Any obstacles whose second angle is less than or equal to the second angle threshold and whose straight-line distance is less than or equal to the aircraft's field radius form the second potential threat obstacle set; wherein the aircraft's field radius represents a safe distance range determined by the aircraft's own size.

[0038] This embodiment effectively analyzes the relative position relationship between the obstacle's moving direction and the aircraft to provide basic data for subsequent threat assessment. By setting the second angle threshold of the second angle and the straight-line distance, obstacles that meet the conditions are screened out to form a second potential threat obstacle set, thereby improving the aircraft's safety recognition capability and response efficiency in complex environments.

[0039] Optionally, the obstacle simulation guide point coordinates include obstacle simulation left guide point coordinates and obstacle simulation right guide point coordinates; and generating the obstacle simulation guide point coordinates corresponding to the second potential threat obstacle includes:

[0040] Classifying the second potential threat obstacles in the second potential threat obstacle set to obtain left-side potential conflict obstacles and right-side potential conflict obstacles;

[0041] The coordinates of the obstacle-simulated left guide point corresponding to the left potential conflicting obstacle are determined, and the coordinates of the obstacle-simulated right guide point corresponding to the right potential conflicting obstacle are determined.

[0042] This embodiment classifies the second set of potential threat obstacles, thereby identifying the potential conflicting obstacles on the left and right. Subsequently, the coordinates of the left guide point of the obstacle simulation corresponding to the potential conflicting obstacle on the left, and the coordinates of the right guide point of the obstacle simulation corresponding to the potential conflicting obstacle on the right are determined. Through this process, obstacles in different directions can be effectively distinguished, and accurate spatial references can be provided for subsequent path planning, thereby improving the obstacle avoidance capability of the aircraft.

[0043] Optionally, the guide point simulation model used in determining the coordinates of the obstacle simulation left guide point corresponding to the left potential conflict obstacle is:

[0044]

[0045] The guide point simulation model used to determine the right guide point coordinates of the obstacle simulation corresponding to the right potential conflict obstacle is:

[0046]

[0047] Among them, (x lead ,y lead ) is the coordinate of the obstacle simulation guide point; (x ob ,y ob ) is the position information of the second potential threat obstacle; θ c is the angle between the velocity information of the second potential threat obstacle and the horizontal direction; ΔT 2 , ΔT 3 The simulation time for simulating guide points for obstacles.

[0048] Optionally, the guide point distance evaluation function is:

[0049]

[0050]

[0051]

[0052] Among them, lead_dist(v,w) is the evaluation function of the distance between the leading points; R is the radius of the spacecraft; p end is the coordinate of the end point of the simulated trajectory of the aircraft; oba Simulate the coordinates of the guiding point for the ath obstacle; τ a is the weight of each second potential threat obstacle; m is the number of second potential threat obstacles; d lead The Euclidean distance between the coordinates of the obstacle simulation guide point and the coordinates of the end point of the vehicle simulation trajectory; dist ca is the distance between the aircraft and the ath second potential threat obstacle;cb is the distance between the aircraft and the bth second potential threatening obstacle.

[0053] Optionally, the dynamic window evaluation function is:

[0054]

[0055] Among them, heading(v,w) is the azimuth evaluation function; α is the weight of the azimuth evaluation function; velocity(v,w) is the speed evaluation function; β is the weight of the speed evaluation function; dist(v,w) is the distance evaluation function; γ is the weight of the distance evaluation function; traj_dist(v,w) is the trajectory point distance evaluation function; δ is the weight of the trajectory point distance evaluation function; lead_dist(v,w) is the guide point distance evaluation function; ε is the weight of the guide point distance evaluation function; σ is a smoothing function, which normalizes each evaluation function.

[0056] In a second aspect, an embodiment of the present application provides a system for determining a simulated trajectory of an aircraft, the system comprising:

[0057] A window determination unit, used to determine a velocity sampling window based on the physical structure of the aircraft and obstacle information;

[0058] A speed determination unit, configured to use the speed sampling window to obtain a speed combination of the aircraft within a sampling time;

[0059] A function construction unit, used to construct a dynamic window evaluation function including a trajectory point distance evaluation function and a guide point distance evaluation function; wherein the trajectory point distance evaluation function is used to characterize and measure the positional relationship between the simulated trajectory of the aircraft and the simulated trajectory of the obstacle; and the guide point distance evaluation function is used to characterize and guide the aircraft to detour in a specified direction to reduce the randomness of the obstacle avoidance motion;

[0060] The trajectory scoring unit is used to score the simulated trajectory of the aircraft corresponding to the speed combination using the dynamic window evaluation function, and determine the simulated trajectory of the target aircraft based on the scoring result.

[0061] In a third aspect, an embodiment of the present application provides a computer device, including:

[0062] A memory and a processor, wherein the memory and the processor are communicatively connected to each other, the memory stores computer instructions, and the processor executes the above-mentioned method for determining the simulated trajectory of the aircraft by executing the computer instructions.

[0063] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, on which computer instructions are stored, and the computer instructions are used to enable a computer to execute the method for determining the simulated trajectory of an aircraft as described above. BRIEF DESCRIPTION OF THE DRAWINGS

[0064] In order to more clearly illustrate the specific implementation methods of the present application or the technical solutions in the prior art, the drawings required for use in the specific implementation methods or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are some implementation methods of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0065] Figure 1 A flowchart of a method for determining a simulated trajectory of an aircraft provided in an embodiment of the present application;

[0066] Figure 2 A flowchart of a method for obtaining a predicted characteristic state corresponding to an obstacle provided in an embodiment of the present application;

[0067] Figure 3 A flowchart of step S103 provided in an embodiment of the present application;

[0068] Figure 4 A flowchart of a method for constructing a trajectory point distance evaluation function provided in an embodiment of the present application;

[0069] Figure 5 A schematic diagram of the scope of action of the trajectory point distance evaluation function provided in an embodiment of the present application;

[0070] Figure 6 A schematic diagram of a trajectory point distance evaluation function provided in an embodiment of the present application;

[0071] Figure 7 A flowchart of step S511 provided in an embodiment of the present application;

[0072] Figure 8 A flowchart of a method for constructing a guide point distance evaluation function provided in an embodiment of the present application;

[0073] Fig. 9 A schematic diagram of the scope of action of the guidance point distance evaluation function provided in an embodiment of the present application;

[0074] Fig.10 A schematic diagram of a guide point distance evaluation function provided in an embodiment of the present application;

[0075] Fig.11 A flowchart of step S521 provided in an embodiment of the present application;

[0076] Fig.12 A flowchart of step S523 provided in an embodiment of the present application;

[0077] Fig.13 A flowchart of the locust algorithm provided in an embodiment of the present application;

[0078] Fig.14 A block diagram of a system for determining a simulated trajectory of an aircraft provided in an embodiment of the present application;

[0079] Fig.15 A schematic diagram of the structure of a computer device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0080] In order to make the purpose, technical solution and advantages of the embodiments of the present application clearer, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative work are within the scope of protection of the present application.

[0081] In the field of aircraft obstacle avoidance and path planning, the Dynamic Window Approach (DWA) is a widely used local path planning algorithm, mainly used for real-time obstacle avoidance and navigation. The DWA algorithm dynamically calculates the optimal moving window to generate a safe navigation path by considering the dynamic limitations of the aircraft (such as speed, acceleration, etc.) and the target obstacles in its surrounding environment. The advantage of this method is that it can efficiently handle the problem of avoiding obstacles in the navigation environment and can provide smooth path planning to ensure the safety and flexibility of the aircraft in complex environments.

[0082] Although the DWA algorithm has shown good performance in practical applications, it has an important limitation, that is, it fails to fully consider the dynamic characteristics of potential obstacles, such as the movement speed and steering changes of obstacles. This neglect may cause the aircraft to collide with obstacles with rapidly changing positions during the obstacle avoidance process. Therefore, in order to improve the obstacle avoidance capability of the DWA algorithm, this application introduces a new evaluation function in the traditional dynamic window method to incorporate the movement characteristics of obstacles (including speed and trajectory) into the trajectory planning and collision avoidance algorithm.

[0083] With this improvement, the aircraft can adjust its course more flexibly and guide itself to the side and rear of the obstacle. This strategy complies with the International Regulations on Collision at Sea (COLREGS), which clearly states that the side and rear of the aircraft around dynamic obstacles are the best areas to bypass. This method not only improves the collision avoidance capability of the aircraft, but also enhances safety and efficiency in complex navigation environments.

[0084] According to an embodiment of the present application, an embodiment of a method for determining a simulated trajectory of an aircraft is provided. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer executable instructions, and although a logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0085] In this embodiment, a method for determining a simulated trajectory of an aircraft is provided. Figure 1 A flowchart of a method for determining a simulated trajectory of an aircraft provided in an embodiment of the present application, such as Figure 1 As shown, the process includes the following steps:

[0086] Step S1, determining a speed sampling window based on the physical structure of the aircraft and obstacle information.

[0087] The speed sampling window is a set of feasible navigation speed spaces, including the combination of forward speed and steering angle, i.e. angular velocity, which needs to meet the kinematic performance constraints, dynamic performance constraints and safety speed of the aircraft. Therefore, the speed sampling space is determined based on the physical structure of the aircraft and obstacle information.

[0088] Specifically, the minimum linear velocity v that the aircraft can reach can be determined based on the physical structure of the aircraft. min and maximum linear velocity v max , and the minimum angular velocity w that the spacecraft can achieve min and the maximum angular velocity w max . Define the kinematic velocity space V k , kinematic velocity space V k It includes all possible combinations of linear velocity v and angular velocity w that satisfy the kinematic performance constraints of the vehicle.

[0089]

[0090] Due to the limitation of the active force and steering torque of the spacecraft, the speed variation range of the spacecraft within the sampling period is limited, so there is no need to consider speed samples beyond this range, which further narrows the search range of the speed space. According to the physical structure of the spacecraft, the current linear speed v of the spacecraft can be determined c and angular velocity w c ; and the maximum linear acceleration a of the vehicle v and the maximum angular acceleration a w . Determine the sampling period Δt, which is the time interval from the current moment to the next evaluation moment. Define the dynamics velocity space V d , dynamic speed space V dIt includes all possible combinations of linear velocity v and angular velocity w that can be achieved under the constraints of dynamic performance.

[0091]

[0092] In order to ensure that the aircraft can reduce its speed to 0 m / s before colliding with an obstacle, the speed of the aircraft must be limited to a safe range. According to the constraint S of the collision distance between the aircraft and the obstacle information min , S min The minimum safe distance between the simulated trajectory of the aircraft and the surrounding obstacles corresponding to the speed combination (v, w). It is usually determined based on the size of the obstacle area, the size of the aircraft, and the safety buffer. It can also be determined based on historical data. Define the safe speed space V s , safe speed space V s Contains all combinations of linear velocity v and angular velocity w that meet the safety conditions.

[0093]

[0094] Combining the intersection of the above three constraints, that is, , get the speed sampling window.

[0095] Step S3, using the speed sampling window to obtain the speed combination of the vehicle within the sampling time.

[0096] Specifically, the speed sampling window V is discretized according to the sampling time to obtain a series of discrete speed combinations (v, w).

[0097] Step S5, constructing a dynamic window evaluation function including a trajectory point distance evaluation function and a guide point distance evaluation function; wherein the trajectory point distance evaluation function is used to characterize and measure the positional relationship between the simulated trajectory of the aircraft and the simulated trajectory of the obstacle; the guide point distance evaluation function is used to characterize and guide the aircraft to detour in a specified direction to reduce the randomness of the obstacle avoidance motion.

[0098] In the traditional dynamic window method (DWA), the evaluation function is used to evaluate the quality of simulated trajectories under different speed combinations (v, w). This evaluation function G(v, w) is a weighted sum of three parts, each of which reflects different aspects of the trajectory.

[0099] The evaluation function of traditional DWA is defined as:

[0100]

[0101] Among them, heading(v,w) is the azimuth evaluation function, which measures the directional deviation between the direction of the end of the simulated trajectory and the target point at the current set speed; velocity(v,w) is the speed evaluation function, which takes into account the linear speed of the aircraft, encourages the aircraft to move forward at a higher speed, and tends to choose a trajectory that can move forward at a higher speed while satisfying obstacle avoidance; dist(v,w) is the distance evaluation function, which evaluates the minimum distance between the predicted trajectory end point and the surrounding obstacles. A safe trajectory should avoid being too close to obstacles, so the distance evaluation function will give a higher score to those trajectories that keep a long distance from obstacles; α, β, and γ are the weight factors of the three evaluation functions; σ is a smoothing function, which normalizes each evaluation function.

[0102] Specifically, the embodiment of the present application introduces the trajectory point distance evaluation function traj_dist(v,w) and the guide point distance evaluation function lead_dist(v,w) into the original DWA algorithm. The trajectory point distance evaluation function traj_dist(v,w) is used to measure the positional relationship between the simulated trajectory of the aircraft and the simulated trajectory of the obstacle; the guide point distance evaluation function lead_dist(v,w) is used to guide the aircraft to detour in the specified direction to reduce the randomness of the obstacle avoidance movement. According to the International Collision Rules at Sea COLREGS, the side and rear of the dynamic obstacle aircraft is the best area for detour. Therefore, the embodiment of the present application uses the guide point distance evaluation function to guide the aircraft to the side and rear of the obstacle, thereby realizing an effective obstacle avoidance function.

[0103] In some preferred embodiments, the dynamic window evaluation function is:

[0104]

[0105] Among them, heading(v,w) is the azimuth evaluation function; α is the weight of the azimuth evaluation function; velocity(v,w) is the speed evaluation function; β is the weight of the speed evaluation function; dist(v,w) is the distance evaluation function; γ is the weight of the distance evaluation function; traj_dist(v,w) is the trajectory point distance evaluation function; δ is the weight of the trajectory point distance evaluation function; lead_dist(v,w) is the guide point distance evaluation function; ε is the weight of the guide point distance evaluation function; σ is a smoothing function, which normalizes each evaluation function.

[0106] Specifically, the trajectory point distance evaluation function is:

[0107]

[0108]

[0109]

[0110] Among them, traj_dist(v,w) is the trajectory point distance evaluation function; R is the radius of the spacecraft; p end is the coordinate of the end point of the simulated trajectory of the aircraft; obi is the coordinate of the simulated trajectory point of the i-th obstacle; τ i is the weight of each first potential threat obstacle; n is the number of first potential threat obstacles; d traj The Euclidean distance between the coordinates of the obstacle simulation trajectory point and the coordinates of the end point of the aircraft simulation trajectory; dist ci is the distance between the aircraft and the first potential threatening obstacle; cj is the distance between the aircraft and the jth first potential threat obstacle.

[0111] The evaluation function of the guide point distance is:

[0112]

[0113]

[0114]

[0115] Among them, lead_dist(v,w) is the evaluation function of the distance between the leading points; R is the radius of the spacecraft; p end is the coordinate of the end point of the simulated trajectory of the aircraft; oba Simulate the coordinates of the guiding point for the ath obstacle; τ a is the weight of each second potential threat obstacle; m is the number of second potential threat obstacles; d lead The Euclidean distance between the coordinates of the obstacle simulation guide point and the coordinates of the end point of the vehicle simulation trajectory; dist ca is the distance between the aircraft and the ath second potential threat obstacle; cb is the distance between the aircraft and the bth second potential threatening obstacle.

[0116] Step S7, using a dynamic window evaluation function to score the simulated trajectory of the aircraft corresponding to the speed combination, and determining the simulated trajectory of the target aircraft based on the scoring result.

[0117] Specifically, each speed combination can be simulated using the aircraft's motion model to obtain the aircraft's simulated trajectory.

[0118] Assume (X t ,Y t ) represents the position coordinates of the spacecraft in the global coordinate system at time t, θ t represents the heading angle of the vehicle at time t, vt 、w t Respectively represent the linear velocity and angular velocity of the spacecraft at time t, which is equivalent to a discrete velocity combination. Then, in the Δt time period, the global displacement generated by the velocity components of the X-axis and Y-axis of the spacecraft in the spacecraft coordinate system is:

[0119]

[0120]

[0121] Therefore, the position and posture of the aircraft at time t+Δt can be obtained through the aircraft's motion model to obtain the aircraft's simulated trajectory:

[0122]

[0123] That is, the simulated trajectory of the aircraft can be generated by the aircraft's motion model given a discrete velocity combination (v, w).

[0124] The simulation trajectory is scored using an evaluation function. The higher the score, the better. The trajectory with the highest score is selected from all simulation trajectories. The speed combination (v, w) corresponding to this trajectory is considered to be the optimal solution.

[0125] This embodiment provides a method for determining a simulated trajectory of an aircraft. By determining a speed sampling window based on the physical structure of the aircraft and obstacle information, it can ensure that the aircraft maintains optimal flexibility and responsiveness in a complex environment. Then, multiple speed combinations are obtained within the sampling time to provide a rich data basis for subsequent decisions and improve the accuracy and efficiency of obstacle avoidance decisions. When constructing a dynamic window evaluation function, the trajectory point and guide point distance evaluation functions are combined so that the simulated path of the aircraft can evaluate the safe distance between the aircraft and obstacles in real time, reduce the risk of collision, and ensure that the aircraft moves along the predetermined path to reduce arbitrariness. Finally, by scoring the simulated trajectory, the optimal motion path can be effectively screened out, thereby improving the success rate of obstacle avoidance and achieving more efficient path planning.

[0126] In some preferred embodiments, the trajectory point distance evaluation function and the guide point distance evaluation function include characteristic states corresponding to the prediction of obstacles; Figure 2 A flowchart of a method for obtaining a predicted characteristic state corresponding to an obstacle provided in an embodiment of the present application, the process may include the following steps:

[0127] Step S101, obtaining the current characteristic state of the obstacle based on the AIS system.

[0128] Step S103: Based on the current characteristic state, a Kalman wave filter is used to generate a predicted characteristic state corresponding to the obstacle.

[0129] In order to implement an effective collision avoidance strategy, the motion state of obstacles needs to be accurately predicted.

[0130] Specifically, the current characteristic state of the obstacle, including longitude and latitude, speed and heading, is obtained through the AIS system. The Kalman filter is used to predict the future state of the obstacle based on its current state. The Kalman filter is a recursive filter that uses state equations and observation data to estimate the state at the next moment.

[0131] and Figure 1 Compared with the embodiment shown in the figure, this embodiment obtains the current characteristic state of the obstacle in real time based on the AIS system, provides a data basis for subsequent processing, and enhances the perception ability of the aircraft. Subsequently, the Kalman filter is used to process these characteristic states to generate a prediction of the obstacle's motion trajectory. This process improves the obstacle detection accuracy, enables the aircraft to formulate a more reasonable obstacle avoidance strategy, reduces the risk of collision, and thus improves the overall navigation safety.

[0132] Figure 3 The flowchart of step S103 provided in the embodiment of the present application may include the following steps:

[0133] Step S1031, construct the state equation X of the obstacle k , measurement equation Z k And the prediction matrix A k :

[0134]

[0135]

[0136]

[0137]

[0138]

[0139] Among them, x k is the state vector at the kth moment; u k is the input vector at the kth moment; f(x k-1 ,u k-1 ) is the nonlinear state equation; WQ k-1 is the process noise at the k-1th moment; long k is the longitude of the obstacle at the kth moment; vt k is the speed of the obstacle at the kth moment; βt k is the direction of the obstacle at the kth moment; k is the latitude of the obstacle at the kth moment; T is the time interval from the k-1th moment to the kth moment.

[0140] Step S1032, obtain the prediction matrix A at the previous moment k-1 , the state equation at the previous moment X k-1 , the state covariance matrix P at the previous moment k-1 , the process noise covariance matrix Q at the previous moment k-1 , the current measurement noise covariance matrix R k , the measurement equation Z at the current moment k .

[0141] Step S1033: predict the feature state at the current moment ,in, .

[0142] Step S1034: predict the current state covariance matrix ,in, .

[0143] Step S1035, calculate the Kalman gain K at the current moment k ,in, .

[0144] Specifically, the Kalman gain determines the weight of the current measurement when updating the state, ensuring that measurement uncertainty is properly accounted for.

[0145] Step S1036: Update the current state to obtain an updated predicted feature state. ,in, .

[0146] Step S1037, updating the current prediction state covariance matrix to obtain an updated prediction state covariance matrix P k ,in, , I is the identity matrix.

[0147] Specifically, the update combines the predicted state and the measured difference, using the Kalman gain to correct the prediction, achieving real-time estimation of the obstacle's motion state.

[0148] and Figure 2Compared with the embodiment shown in the figure, this embodiment accurately estimates the position, speed and heading of the obstacle by constructing nonlinear state equations and measurement equations and dynamically updating the state vector and input vector. At the same time, the covariance matrix of process noise and measurement noise is used to effectively filter system noise and improve estimation accuracy. The combination of the prediction step and the update mechanism ensures dynamic tracking of the motion state and timely reflection of feature changes. In addition, the calculation of the Kalman gain reasonably distributes the weight of the measurement data in the state update, optimizes the estimation result, and reduces uncertainty. Finally, the updated state covariance matrix reflects the dynamic evaluation of the uncertainty of the obstacle state, ensuring the real-time and reliability of the estimation.

[0149] Figure 4 A flowchart of a method for constructing a trajectory point distance evaluation function provided in an embodiment of the present application, the process may include the following steps:

[0150] Step S511, determining a first set of potential threat obstacles within the range of action of a preset trajectory point distance evaluation function.

[0151] The scope of the trajectory point distance evaluation function refers to determining which obstacles pose a potential threat to the current motion trajectory of the aircraft.

[0152] Specifically, see Figure 5 , it is necessary to obtain the velocity combination obtained by the aircraft in the velocity sampling window. The velocity combination has a corresponding velocity vector, which is defined as the aircraft velocity vector V c ; Define R as the radius of the aircraft area, which represents the safe distance range determined by the size of the aircraft itself. Define θ f It is used to identify obstacles in front of the aircraft. It is the angle between the aircraft's travel direction and the obstacle's travel direction, usually set to 90-135°. is the set of all current obstacles; define θ p For each obstacle DO i The line between them and the vehicle velocity vector V c The angle between the directions; definition d oc DO for the aircraft and each obstacle i Through the constraints of angle and distance, the first potential threat obstacle set O within the range of the trajectory point distance evaluation function is screened out. t :

[0153]

[0154] This means that only those f Only obstacles within a distance of R will be considered.

[0155] Step S513, obtaining speed information and position information of the first potential threat obstacle in the first potential threat obstacle set, and generating obstacle simulation trajectory point coordinates corresponding to the first potential threat obstacle by using the trajectory point simulation model.

[0156] Specifically, see Figure 6 The speed information and position information of the first potential threat obstacle are obtained according to the predicted characteristic state corresponding to the obstacle obtained in step S103, and the speed vector of the obstacle in the predicted characteristic state is defined as V p , that is, V p is the speed information of the first potential threat obstacle; the longitude and latitude of the obstacle in the predicted characteristic state is defined as (x oa ,y oa ), that is, (x oa ,y oa ) is the predicted position information of the first potential threat obstacle; then the trajectory point simulation model is used to generate the obstacle simulation trajectory point coordinates corresponding to the first potential threat obstacle.

[0157] In some preferred embodiments, the trajectory point simulation model is:

[0158]

[0159] Among them, (x traj ,y traj ) is the coordinate of the obstacle simulation trajectory point; (x oa ,y oa ) is the position information of the first potential threat obstacle; V p is the speed information of the first potential threat obstacle; θ c V p Angle with the horizontal direction; ΔT 1 The simulation time for simulating trajectories for obstacles.

[0160] Step S515, constructing a trajectory point distance evaluation function based on the coordinates of the obstacle simulation trajectory points, the distance between the aircraft and the first potential threat obstacle, and the aircraft simulation trajectory.

[0161] Specifically, the purpose of constructing the trajectory point distance evaluation function traj_dist(v,w) is to evaluate the safe distance between the simulated trajectory of the aircraft and the simulated trajectory of the obstacle under a specific speed combination (v,w).

[0162] In some preferred embodiments, the trajectory point distance evaluation function is:

[0163]

[0164]

[0165]

[0166] Among them, traj_dist(v,w) is the trajectory point distance evaluation function; R is the radius of the spacecraft; p end is the coordinate of the end point of the simulated trajectory of the aircraft; obi is the coordinate of the simulated trajectory point of the i-th obstacle; τ i is the weight of each first potential threat obstacle; n is the number of first potential threat obstacles; d traj The Euclidean distance between the coordinates of the obstacle simulation trajectory point and the coordinates of the end point of the aircraft simulation trajectory; dist ci is the distance between the aircraft and the first potential threatening obstacle; cj is the distance between the aircraft and the jth first potential threat obstacle.

[0167] and Figure 1 Compared with the embodiment shown in the figure, this embodiment can effectively screen out obstacles that pose a threat to the safety of the aircraft and improve the obstacle avoidance capability of the aircraft by determining the first set of potential threat obstacles within the range of action of the pre-set trajectory point distance evaluation function. Next, the speed and position information of these potential threat obstacles are obtained, and the corresponding obstacle simulation trajectory point coordinates are generated using the trajectory point simulation model. It not only provides the dynamic characteristics of potential obstacles, but also lays the foundation for subsequent trajectory analysis, which helps to predict its future position more accurately. Finally, based on the coordinates of the obstacle simulation trajectory points, the distance between the aircraft and the potential threat obstacle, and the simulated trajectory of the aircraft, a trajectory point distance evaluation function is constructed. This evaluation function can comprehensively consider various factors and evaluate the relative position relationship between the aircraft and the obstacle in real time, thereby providing a scientific basis for subsequent path planning for navigation.

[0168] Figure 7 The flowchart of step S511 provided in the embodiment of the present application may include the following steps:

[0169] Step S5111, for any obstacle, determine the first angle between the line between the aircraft and any obstacle and the velocity vector in the velocity combination, as well as the straight-line distance between the aircraft and any obstacle.

[0170] Step S5113, any obstacle whose first angle is less than or equal to the first angle threshold and whose straight-line distance is less than or equal to the aircraft's field radius is formed into a first potential threat obstacle set; wherein the aircraft's field radius represents a safe distance range determined by the size of the aircraft itself.

[0171] Specifically, for each obstacle, the line between the aircraft and the obstacle and the aircraft velocity vector V are calculated.c The angle between them is called the first angle. Calculate the straight-line distance between the aircraft and each obstacle. Define the first angle threshold, which is usually an angle value used to determine whether the obstacle is in front of the aircraft or in the threat area. The first angle threshold is preferably 90-135°. Define the aircraft field radius R, which characterizes the safe distance range determined by the aircraft's own size. According to the first angle threshold and the aircraft field radius, screen out those obstacles whose first angle is less than or equal to the first angle threshold and whose straight-line distance is less than or equal to the aircraft field radius. The screened obstacles form the first potential threat obstacle set.

[0172] and Figure 4 Compared with the embodiment shown, this embodiment determines the first angle between the line between the aircraft and the obstacle and the velocity vector in the velocity combination, as well as the straight-line distance between the two for any obstacle. This process can evaluate the movement trend and distance of the obstacle relative to the aircraft, and help identify potential collision risks. By including obstacles whose first angle is less than or equal to the first angle threshold and whose straight-line distance is less than or equal to the aircraft's field radius into the first potential threat obstacle set, this screening mechanism ensures that only those obstacles that are within the aircraft's safety range and may affect the navigation path are identified as potential threats. The setting of the aircraft's field radius is a safe distance range determined based on the size of the aircraft, which further increases the safety of the aircraft. The implementation method of the present application can effectively construct a dynamic potential threat obstacle set by accurately evaluating the movement state of the obstacle and its relative position to the aircraft, thereby improving the aircraft's safety identification capability and response efficiency in complex environments.

[0173] Figure 8 A flowchart of a method for constructing a guide point distance evaluation function provided in an embodiment of the present application, the process may include the following steps:

[0174] Step S521: determine a second set of potential threat obstacles within the range of action of a preset guidance point distance evaluation function.

[0175] The definition of the scope of the guidance point distance evaluation function is to determine which obstacles the current motion trajectory of the guiding vehicle should be circumvented to the side and rear of, thereby reducing the randomness of the obstacle avoidance motion and improving the stability of the algorithm.

[0176] Specifically, see Fig. 9 , it is necessary to obtain the velocity combination obtained by the aircraft in the velocity sampling window. The velocity combination has a corresponding velocity vector, which is defined as the aircraft velocity vector V c ; Define R as the radius of the aircraft area, which represents the safe distance range determined by the size of the aircraft itself. Define θ f’It is used to identify obstacles in front of the aircraft. It is the angle between the aircraft's travel direction and the obstacle's travel direction, usually set to 0-90°; assuming is the set of all current obstacles; define θ p For each obstacle DO i The line between them and the vehicle velocity vector V c The angle between the directions; definition d oc DO for the aircraft and each obstacle i Through the constraints of angle and distance, the second potential threat obstacle set O within the range of the guidance point distance evaluation function is screened out. l :

[0177]

[0178] This means that only those f’ Only obstacles within a distance of R will be considered.

[0179] Step S523, obtaining speed information and position information of the second potential threat obstacle in the second potential threat obstacle set, and generating obstacle simulation guidance point coordinates corresponding to the second potential threat obstacle by using the guidance point simulation model.

[0180] Specifically, see Fig.10 The speed information and position information of the second potential threat obstacle are obtained according to the predicted characteristic state corresponding to the obstacle obtained in step S103, and the speed vector of the obstacle in the predicted characteristic state is defined as V p’ , that is, V p’ is the speed information of the second potential threat obstacle; the longitude and latitude of the obstacle in the predicted characteristic state is defined as (x ob ,y ob ), that is, (x ob ,y ob ) is the predicted position information of the second potential threat obstacle; then the guide point simulation model is used to generate the obstacle simulation guide point coordinates corresponding to the second potential threat obstacle.

[0181] Step S525, constructing a guidance point distance evaluation function based on the obstacle simulation guidance point coordinates, the distance between the aircraft and the second potential threat obstacle, and the aircraft simulation trajectory.

[0182] Specifically, the purpose of constructing the lead point distance evaluation function lead_dist(v,w) is to evaluate the distance between the simulated trajectory of the vehicle under a specific speed combination (v,w) and the obstacle simulation lead point.

[0183] In some preferred embodiments, the guide point distance evaluation function is:

[0184]

[0185]

[0186]

[0187] Among them, lead_dist(v,w) is the evaluation function of the distance between the leading points; R is the radius of the spacecraft; p end is the coordinate of the end point of the simulated trajectory of the aircraft; oba Simulate the coordinates of the guiding point for the ath obstacle; τ a is the weight of each second potential threat obstacle; m is the number of second potential threat obstacles; d lead The Euclidean distance between the coordinates of the obstacle simulation guide point and the coordinates of the end point of the vehicle simulation trajectory; dist ca is the distance between the aircraft and the ath second potential threat obstacle; cb is the distance between the aircraft and the bth second potential threatening obstacle.

[0188] and Figure 1 Compared with the embodiment shown, this embodiment determines the second potential threat obstacle set within the range of action of the preset guidance point distance evaluation function. It can effectively screen out obstacles related to the aircraft path. By obtaining the speed information and position information of the second potential threat obstacle and using the guidance point simulation model to generate the corresponding obstacle simulation guidance point coordinates, it is possible to dynamically reflect the movement state of the obstacle and provide support for the subsequent guidance of the aircraft to bypass the designated side and rear of the obstacle. The guidance point distance evaluation function is constructed based on the obstacle simulation guidance point coordinates, the distance between the aircraft and the second potential threat obstacle, and the aircraft simulation trajectory, which can achieve a comprehensive analysis of the potential threat of obstacles, so that it can respond faster and more accurately in complex environments to enhance overall navigation safety.

[0189] Fig.11 The flowchart of step S521 provided in the embodiment of the present application may include the following steps:

[0190] Step S5211, for any obstacle, determine the second angle between the line between the aircraft and any obstacle and the velocity vector in the velocity combination, as well as the straight-line distance between the aircraft and any obstacle.

[0191] Step S5213, any obstacle whose second angle is less than or equal to the second angle threshold and whose straight-line distance is less than or equal to the aircraft's field radius is formed into a second potential threat obstacle set; wherein the aircraft's field radius represents a safe distance range determined by the aircraft's own size.

[0192] Specifically, for each obstacle, the line between the aircraft and the obstacle and the aircraft velocity vector V are calculated. c The angle between them is called the second angle. Calculate the straight-line distance between the aircraft and each obstacle. Define the second angle threshold, which is usually an angle value used to identify obstacles in front of the aircraft. The second angle threshold is preferably 0-90°. Define the aircraft field radius R, which characterizes the safe distance range determined by the size of the aircraft itself. According to the second angle threshold and the aircraft field radius, screen out those obstacles whose second angle is less than or equal to the second angle threshold and whose straight-line distance is less than or equal to the aircraft field radius. The screened obstacles form the second potential threat obstacle set.

[0193] and Figure 8 Compared with the embodiment shown in the figure, this embodiment effectively analyzes the relative position relationship between the movement direction of the obstacle and the aircraft to provide basic data for subsequent threat assessment. By setting the second angle threshold of the second angle and the straight-line distance, obstacles that meet the conditions are screened out to form a second potential threat obstacle set, thereby improving the safety recognition capability and response efficiency of the aircraft in complex environments.

[0194] Fig.12 The flowchart of step S523 provided in the embodiment of the present application may include the following steps:

[0195] Step S5231: classify the second potential threat obstacles in the second potential threat obstacle set to obtain left potential conflict obstacles and right potential conflict obstacles.

[0196] Specifically, the purpose of classifying the second potential threat obstacles is to more effectively guide the avoidance direction of the aircraft and improve the path planning efficiency of the aircraft. For each second potential threat obstacle, determine the angle θ between its moving direction and the moving direction of the aircraft. v Define the threshold θ k In order to prevent the second potential threat obstacle from shaking in the boundary area and causing the category to change continuously, the classification criteria are obtained through experience or historical data fitting.

[0197] Table 1 Classification criteria

[0198]

[0199] Step S5233, determining the coordinates of the obstacle simulation left guide point corresponding to the left potential conflict obstacle, and determining the coordinates of the obstacle simulation right guide point corresponding to the right potential conflict obstacle.

[0200] Specifically, in the path planning and obstacle avoidance strategy, the simulated guide point coordinates of the left and right potential conflicting obstacles are determined to guide the aircraft to bypass these obstacles. For each obstacle classified as a potential conflict on the left, its left guide point coordinates are calculated. The left guide point coordinates are usually located on the left side of the obstacle and on the obstacle avoidance path of the aircraft. For each obstacle classified as a potential conflict on the right, its right guide point coordinates are calculated. The right guide point coordinates are usually located on the right side of the obstacle and on the obstacle avoidance path of the aircraft.

[0201] In some preferred embodiments, the guide point simulation model used to determine the coordinates of the left guide point of the obstacle simulation corresponding to the left potential conflict obstacle is:

[0202]

[0203] The guidance point simulation model used to determine the right guidance point coordinates of the obstacle simulation corresponding to the potential conflict obstacle on the right is:

[0204]

[0205] Among them, (x lead ,y lead ) is the coordinate of the obstacle simulation guide point; (x ob ,y ob ) is the position information of the second potential threat obstacle; θ c is the angle between the velocity information of the second potential threat obstacle and the horizontal direction; ΔT 2 , ΔT 3 The simulation time for simulating guide points for obstacles.

[0206] and Figure 8 Compared with the embodiment shown in the figure, this embodiment classifies the second potential threat obstacle set, thereby identifying the potential conflicting obstacles on the left and right sides. Subsequently, the coordinates of the left guide point of the obstacle simulation corresponding to the potential conflicting obstacle on the left side and the coordinates of the right guide point of the obstacle simulation corresponding to the potential conflicting obstacle on the right side are determined. Through this process, obstacles in different directions can be effectively distinguished, and accurate spatial references can be provided for subsequent path planning, thereby improving the obstacle avoidance capability of the aircraft.

[0207] In addition, the traditional DWA algorithm scores the aircraft simulation trajectory corresponding to each speed combination through a dynamic window evaluation function, and then selects the speed combination with the highest score to execute the aircraft simulation trajectory. This makes the calculation amount large and time-consuming. Preferably, the embodiment of the present application can also use the locust algorithm for optimization, which can reduce the amount of calculation and quickly find the optimal solution.

[0208] Fig.13The flowchart of the locust algorithm provided in the embodiment of the present application may include the following steps:

[0209] Step S71, obtaining a preset number of current speed combinations, and using the current speed combinations as the current population; wherein any current speed combination in the current population represents a simulated trajectory of an aircraft.

[0210] Specifically, a set of random number n speed combinations is generated as the current population, and each speed combination represents a potential simulated trajectory of the aircraft. The speed combination corresponding to the current population is (v i ,w i ), i=1,2,3,…,n; where v is the linear velocity of the spacecraft and w is the angular velocity of the spacecraft.

[0211] Step S73, based on the dynamic window evaluation function, obtaining the initial evaluation function value of each current speed combination in the current population.

[0212] Specifically, a dynamic window evaluation function is used to score each speed combination to obtain an initial evaluation function value corresponding to each speed combination.

[0213] Step S75, iterative update: keep the position of the current speed combination corresponding to the best evaluation function value in the initial evaluation function value unchanged, use the force function to update the positions of the remaining current speed combinations, and re-obtain the updated evaluation function values ​​of the remaining current speed combinations.

[0214] Specifically, the objective of iterative update is expressed as:

[0215]

[0216] By simulating the group behavior of locusts, the speed combination in the current population is updated according to the evaluation function value to find the optimal solution. First, the current n initial evaluation function values ​​are compared, and the speed combination corresponding to the best evaluation function value among these initial evaluation function values ​​is screened out, and the position of the speed combination is kept unchanged. The position of the remaining n-1 populations is determined by the force function. The force function is:

[0217]

[0218]

[0219]

[0220] Where N is the total number of individuals in the population, d ij is the distance between the ith population and the jth population, s(d ij ) is the attraction intensity between the two populations, f is the attraction coefficient, and l is the attraction range.

[0221] The attraction coefficient f controls the strength of mutual attraction between populations. Larger values ​​of f increase the attraction between populations, causing the algorithm to tend to gather together faster, which helps the algorithm's local search. Conversely, smaller values ​​of f reduce the attraction, giving the algorithm better global search capabilities. In practical applications, the value of f is usually between 0 and 1, and a commonly used starting value is 0.5. The attraction range l defines the effective distance over which the attraction acts. When the distance between populations exceeds this range, the interaction force between them will weaken or disappear. The value of l is usually set to a small positive number, such as 1.5, which allows interactions to be maintained within a certain distance while avoiding invalid interactions between populations that are too far away.

[0222] Step S77, comparing the evaluation function value and the updated evaluation function value, and determining the updated optimal evaluation function value according to the comparison result.

[0223] Step S79, repeat the iterative update until the preset conditions are met, obtain the target speed combination corresponding to the best target evaluation function value, and determine the aircraft simulation trajectory corresponding to the target speed combination as the target aircraft simulation trajectory.

[0224] Specifically, in each iteration, the position of the best speed combination is kept unchanged, while the positions of other speed combinations are updated. For each updated speed combination, its evaluation function value is recalculated to evaluate its performance, and the iteration continues until the preset number of iterations is reached, or the evaluation function value no longer changes, and the aircraft simulation trajectory corresponding to the final target speed combination is obtained and determined as the target aircraft simulation trajectory.

[0225] and Figure 1 Compared with the embodiment shown, this embodiment forms a dynamic speed combination group by obtaining a preset number of current speed combinations, allowing the aircraft to perform diversified trajectory simulations in complex environments. The current speed combination is preliminarily evaluated using a dynamic window evaluation function, providing a quantitative basis for subsequent iterative updates. The best speed combination is kept unchanged, and the positions of the remaining combinations are updated. This strategy combines the advantages of local search and global optimization. It can further explore other possible optimal solutions while maintaining the known best solution, thereby improving the overall optimization efficiency. By comparing the evaluation function value and the update value, the position of the speed combination can be adjusted in real time, and the aircraft trajectory can be continuously optimized. Until the preset conditions are met, it is ensured that the final target speed combination is the optimal solution after multiple rounds of evaluation. This convergence capability enables the aircraft to find the best navigation path in a complex environment, improving safety and obstacle avoidance capabilities.

[0226] Accordingly, please refer to Fig.14 A block diagram of a system for determining a simulated trajectory of an aircraft provided in an embodiment of the present application, the system comprising:

[0227] The window determination unit S001 is used to determine the speed sampling window based on the physical structure of the aircraft and obstacle information;

[0228] The speed determination unit S003 is used to obtain the speed combination of the vehicle within the sampling time using the speed sampling window;

[0229] The function construction unit S005 is used to construct a dynamic window evaluation function including a trajectory point distance evaluation function and a guide point distance evaluation function; wherein the trajectory point distance evaluation function is used to characterize and measure the positional relationship between the simulated trajectory of the aircraft and the simulated trajectory of the obstacle; and the guide point distance evaluation function is used to characterize and guide the aircraft to detour in a specified direction to reduce the randomness of the obstacle avoidance motion;

[0230] The trajectory scoring unit S007 is used to score the simulated trajectory of the aircraft corresponding to the speed combination using the dynamic window evaluation function, and determine the simulated trajectory of the target aircraft based on the scoring result.

[0231] In some preferred embodiments, the trajectory point distance evaluation function is constructed in the following manner:

[0232] Determine a first set of potential threat obstacles within a predetermined trajectory point distance evaluation function range;

[0233] Obtaining speed information and position information of a first potential threat obstacle in the first potential threat obstacle set, and generating obstacle simulation trajectory point coordinates corresponding to the first potential threat obstacle using a trajectory point simulation model;

[0234] Based on the coordinates of the obstacle simulation trajectory points, the distance between the aircraft and the first potential threat obstacle, and the aircraft simulation trajectory, a trajectory point distance evaluation function is constructed.

[0235] In some preferred embodiments, determining a first set of potential threat obstacles within a predetermined range of action of a trajectory point distance evaluation function includes:

[0236] For any obstacle, determine the first angle between the line between the aircraft and any obstacle and the velocity vector in the velocity combination, as well as the straight-line distance between the aircraft and any obstacle;

[0237] Any obstacle whose first angle is less than or equal to the first angle threshold and whose straight-line distance is less than or equal to the aircraft's field radius forms a first potential threat obstacle set; wherein the aircraft's field radius represents a safe distance range determined by the aircraft's own size.

[0238] In some preferred embodiments, the trajectory point simulation model is:

[0239]

[0240] Among them, (x traj ,y traj ) is the coordinate of the obstacle simulation trajectory point; (x oa ,y oa ) is the position information of the first potential threat obstacle; V p is the speed information of the first potential threat obstacle; θ c V p Angle with the horizontal direction; ΔT 1 The simulation time for simulating trajectories for obstacles.

[0241] In some preferred embodiments, the trajectory point distance evaluation function is:

[0242]

[0243]

[0244]

[0245] Among them, traj_dist(v,w) is the trajectory point distance evaluation function; R is the radius of the spacecraft; p end is the coordinate of the end point of the simulated trajectory of the aircraft; obi is the coordinate of the simulated trajectory point of the i-th obstacle; τ i is the weight of each first potential threat obstacle; n is the number of first potential threat obstacles; d traj The Euclidean distance between the coordinates of the obstacle simulation trajectory point and the coordinates of the end point of the aircraft simulation trajectory; dist ci is the distance between the aircraft and the first potential threatening obstacle; cj is the distance between the aircraft and the jth first potential threat obstacle.

[0246] In some preferred embodiments, the guide point distance evaluation function is constructed in the following manner:

[0247] Determine a second potential threat obstacle set located within a predetermined range of action of the guidance point distance evaluation function;

[0248] Acquire speed information and position information of a second potential threat obstacle in the second potential threat obstacle set, and generate obstacle simulation guide point coordinates corresponding to the second potential threat obstacle using a guide point simulation model;

[0249] Based on the coordinates of the obstacle simulation guidance point, the distance between the aircraft and the second potential threat obstacle, and the aircraft simulation trajectory, a guidance point distance evaluation function is constructed.

[0250] In some preferred embodiments, determining a second set of potential threatening obstacles located within a predetermined range of action of the guidance point distance evaluation function includes:

[0251] For any obstacle, determine the second angle between the line between the aircraft and any obstacle and the velocity vector in the velocity combination, as well as the straight-line distance between the aircraft and any obstacle;

[0252] Any obstacle whose second angle is less than or equal to the second angle threshold and whose straight-line distance is less than or equal to the aircraft's field radius forms a second potential threat obstacle set; wherein the aircraft's field radius represents a safe distance range determined by the aircraft's own size.

[0253] In some preferred embodiments, the obstacle simulation guide point coordinates include obstacle simulation left guide point coordinates and obstacle simulation right guide point coordinates; generating the obstacle simulation guide point coordinates corresponding to the second potential threat obstacle includes:

[0254] Classifying the second potential threat obstacles in the second potential threat obstacle set to obtain left potential conflict obstacles and right potential conflict obstacles;

[0255] The coordinates of the left-side guide point of the obstacle simulation corresponding to the potential conflicting obstacle on the left are determined, and the coordinates of the right-side guide point of the obstacle simulation corresponding to the potential conflicting obstacle on the right are determined.

[0256] In some preferred embodiments, the guide point simulation model used to determine the coordinates of the left guide point of the obstacle simulation corresponding to the left potential conflict obstacle is:

[0257]

[0258] The guidance point simulation model used to determine the right guidance point coordinates of the obstacle simulation corresponding to the potential conflict obstacle on the right is:

[0259]

[0260] Among them, (x lead ,y lead ) is the coordinate of the obstacle simulation guide point; (x ob ,y ob ) is the position information of the second potential threat obstacle; θ c is the angle between the velocity information of the second potential threat obstacle and the horizontal direction; ΔT 2 , ΔT 3 The simulation time for simulating guide points for obstacles.

[0261] In some preferred embodiments, the guide point distance evaluation function is:

[0262]

[0263]

[0264]

[0265] Among them, lead_dist(v,w) is the evaluation function of the distance between the leading points; R is the radius of the spacecraft; p end is the coordinate of the end point of the simulated trajectory of the aircraft; oba Simulate the coordinates of the guiding point for the ath obstacle; τ a is the weight of each second potential threat obstacle; m is the number of second potential threat obstacles; d lead The Euclidean distance between the coordinates of the obstacle simulation guide point and the coordinates of the end point of the vehicle simulation trajectory; dist ca is the distance between the aircraft and the ath second potential threat obstacle; cb is the distance between the aircraft and the bth second potential threatening obstacle.

[0266] In some preferred embodiments, the dynamic window evaluation function is:

[0267]

[0268] Among them, heading(v,w) is the azimuth evaluation function; α is the weight of the azimuth evaluation function; velocity(v,w) is the speed evaluation function; β is the weight of the speed evaluation function; dist(v,w) is the distance evaluation function; γ is the weight of the distance evaluation function; traj_dist(v,w) is the trajectory point distance evaluation function; δ is the weight of the trajectory point distance evaluation function; lead_dist(v,w) is the guide point distance evaluation function; ε is the weight of the guide point distance evaluation function; σ is a smoothing function, which normalizes each evaluation function.

[0269] The further functional description of each of the above modules and units is the same as that of the above corresponding embodiments and will not be repeated here.

[0270] In this embodiment, a system for determining a simulated trajectory of an aircraft is presented in the form of a functional unit, where the unit refers to an ASIC (Application Specific Integrated Circuit) circuit, a processor and memory that executes one or more software or fixed programs, and / or other devices that can provide the above-mentioned functions.

[0271] See also Fig.15 , Fig.15A schematic diagram of the structure of a computer device provided in an embodiment of the present application is shown in FIG. Fig.15 As shown, the computer device includes: one or more processors 10, a memory 20, and interfaces for connecting various components, including high-speed interfaces and low-speed interfaces. Various components are connected to each other using different buses for communication, and can be installed on a common mainboard or installed in other ways as needed. The processor can process the instructions executed in the computer device, including instructions stored in or on the memory to display the graphical information of the GUI on an external input / output device (such as, a display device coupled to the interface). In some optional embodiments, if necessary, multiple processors and / or multiple buses can be used together with multiple memories and multiple memories. Similarly, multiple computer devices can be connected, and each device provides some necessary operations (for example, as a server array, a group of blade servers, or a multi-processor system). Fig.15 A processor 10 is taken as an example.

[0272] The processor 10 may be a central processing unit, a network processor or a combination thereof. The processor 10 may further include a hardware chip. The hardware chip may be a dedicated integrated circuit, a programmable logic device or a combination thereof. The programmable logic device may be a complex programmable logic device, a field programmable gate array, a general purpose array logic or any combination thereof.

[0273] The memory 20 stores instructions executable by at least one processor 10, so that the at least one processor 10 executes the method shown in the above embodiment.

[0274] The memory 20 may include a program storage area and a data storage area, wherein the program storage area may store an operating system, an application required for at least one function; the data storage area may store data created according to the use of the computer device, etc. In addition, the memory 20 may include a high-speed random access memory, and may also include a non-transient memory, such as at least one disk storage device, a flash memory device, or other non-transient solid-state storage device. In some optional embodiments, the memory 20 may optionally include a memory remotely arranged relative to the processor 10, and these remote memories may be connected to the computer device via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0275] The memory 20 may include a volatile memory, such as a random access memory; the memory may also include a non-volatile memory, such as a flash memory, a hard disk or a solid state drive; the memory 20 may also include a combination of the above types of memory.

[0276] The computer device further comprises a communication interface 30 for the computer device to communicate with other devices or a communication network.

[0277] The embodiment of the present application also provides a computer-readable storage medium. The above method according to the embodiment of the present application can be implemented in hardware, firmware, or can be implemented as a computer code that can be recorded in a storage medium, or can be implemented as a computer code that is originally stored in a remote storage medium or a non-temporary machine-readable storage medium and will be stored in a local storage medium through a network download, so that the method described herein can be stored in such software processing on a storage medium using a general-purpose computer, a dedicated processor, or programmable or dedicated hardware. Among them, the storage medium can be a magnetic disk, an optical disk, a read-only storage memory, a random access memory, a flash memory, a hard disk or a solid-state hard disk, etc.; further, the storage medium can also include a combination of the above types of memories. It can be understood that a computer, a processor, a microprocessor controller, or programmable hardware includes a storage component that can store or receive software or computer code. When the software or computer code is accessed and executed by a computer, a processor, or hardware, the method shown in the above embodiment is implemented.

[0278] The systems, modules or units described in the above embodiments may be implemented by computer chips or entities, or by products with certain functions. A typical implementation device is a computer. Specifically, the computer may be, for example, a personal computer, a laptop computer, a cellular phone, a camera phone, a smart phone, a personal digital assistant, a media player, a navigation device, an email device, a game console, a tablet computer, a wearable device, or a combination of any of these devices.

[0279] For the convenience of description, the above device is described in various units according to their functions. Of course, when implementing the present application, the functions of each unit can be implemented in the same or multiple software and / or hardware.

[0280] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods and systems. Therefore, the present application may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present application may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program codes.

[0281] The present application is described with reference to the flowcharts and / or block diagrams of the methods and systems according to the embodiments of the present application. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of the processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0282] These computer program instructions may also be stored in a computer readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture including an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0283] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process in the computer or other programmable device. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0284] It should also be noted that the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, commodity or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, commodity or device. In the absence of more restrictions, the elements defined by the sentence "comprises a ..." do not exclude the existence of other identical elements in the process, method, commodity or device including the elements.

[0285] Each embodiment in this specification is described in a progressive manner, and the same or similar parts between the embodiments can be referred to each other, and each embodiment focuses on the differences from other embodiments. In particular, for the system embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiment.

[0286] The above is only the embodiment of the present application and is not intended to limit the present application. For those skilled in the art, the present application may have various changes and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included in the scope of the claims of the present application.

[0287] Although the embodiments of the present application have been described in conjunction with the accompanying drawings, those skilled in the art may make various modifications and variations without departing from the spirit and scope of the present application, and such modifications and variations are all within the scope defined by the appended claims.

Claims

1. A method for determining a simulated trajectory of an aircraft, characterized in that: The method comprises: Determine the speed sampling window based on the physical structure of the spacecraft and obstacle information; Using the speed sampling window to obtain the speed combination of the aircraft within the sampling time; Constructing a dynamic window evaluation function including a trajectory point distance evaluation function and a guide point distance evaluation function; wherein the trajectory point distance evaluation function is used to characterize and measure the positional relationship between the simulated trajectory of the aircraft and the simulated trajectory of the obstacle; and the guide point distance evaluation function is used to characterize and guide the aircraft to detour in a specified direction to reduce the randomness of the obstacle avoidance motion; The construction method of the trajectory point distance evaluation function includes: Determine a first set of potential threat obstacles within a predetermined trajectory point distance evaluation function range; Acquire speed information and position information of a first potential threat obstacle in the first potential threat obstacle set, and generate obstacle simulation trajectory point coordinates corresponding to the first potential threat obstacle using a trajectory point simulation model; Constructing the trajectory point distance evaluation function based on the coordinates of the obstacle simulation trajectory point, the distance between the aircraft and the first potential threat obstacle, and the aircraft simulation trajectory; The trajectory point distance evaluation function is: Among them, traj_dist(v,w) is the trajectory point distance evaluation function; R is the radius of the spacecraft; p end is the coordinate of the end point of the simulated trajectory of the aircraft; obi is the coordinate of the simulated trajectory point of the i-th obstacle; τ i is the weight of each first potential threat obstacle; n is the number of first potential threat obstacles; d traj The Euclidean distance between the coordinates of the obstacle simulation trajectory point and the coordinates of the end point of the aircraft simulation trajectory; dist ci is the distance between the aircraft and the first potential threatening obstacle; cj is the distance between the aircraft and the jth first potential threat obstacle; the aircraft simulation trajectory corresponding to the speed combination is scored using the dynamic window evaluation function, and the target aircraft simulation trajectory is determined based on the scoring result.

2. The method according to claim 1, characterized in that The step of determining a first set of potential threat obstacles within a predetermined range of action of a trajectory point distance evaluation function includes: For any obstacle, determining a first angle between a line between the aircraft and the obstacle and a velocity vector in the velocity combination, and a straight-line distance between the aircraft and the obstacle; Any obstacles within the aircraft area radius whose first angle is less than or equal to the first angle threshold and whose straight-line distance is less than or equal to the aircraft area radius form the first potential threat obstacle set; wherein the aircraft area radius represents a safe distance range determined by the size of the aircraft itself.

3. The method according to claim 1, characterized in that The trajectory point simulation model is: Among them, (x traj ,y traj ) is the coordinate of the obstacle simulation trajectory point; (x oa ,y oa ) is the position information of the first potential threat obstacle; V p is the speed information of the first potential threat obstacle; θ c V p The angle with the horizontal direction; ΔT1 is the simulation time of the obstacle simulation trajectory.

4. The method according to claim 1, characterized in that: The construction method of the guide point distance evaluation function includes: Determine a second potential threat obstacle set located within a predetermined range of action of the guidance point distance evaluation function; Acquire speed information and position information of a second potential threat obstacle in the second potential threat obstacle set, and generate obstacle simulation guide point coordinates corresponding to the second potential threat obstacle by using a guide point simulation model; The guidance point distance evaluation function is constructed based on the obstacle simulation guidance point coordinates, the distance between the aircraft and the second potential threat obstacle, and the aircraft simulation trajectory.

5. The method according to claim 4, characterized in that The step of determining a second set of potential threat obstacles within a preset range of action of a guidance point distance evaluation function includes: For any obstacle, determining a second angle between a line between the aircraft and the obstacle and a velocity vector in the velocity combination, and a straight-line distance between the aircraft and the obstacle; Any obstacles whose second angle is less than or equal to the second angle threshold and whose straight-line distance is less than or equal to the aircraft's field radius form the second potential threat obstacle set; wherein the aircraft's field radius represents a safe distance range determined by the aircraft's own size.

6. The method according to claim 4, characterized in that The obstacle simulation guide point coordinates include obstacle simulation left guide point coordinates and obstacle simulation right guide point coordinates; generating the obstacle simulation guide point coordinates corresponding to the second potential threat obstacle includes: Classifying the second potential threat obstacles in the second potential threat obstacle set to obtain left-side potential conflict obstacles and right-side potential conflict obstacles; The coordinates of the obstacle-simulated left guide point corresponding to the left potential conflicting obstacle are determined, and the coordinates of the obstacle-simulated right guide point corresponding to the right potential conflicting obstacle are determined.

7. The method according to claim 6, characterized in that The guide point simulation model used in determining the obstacle simulation left guide point coordinates corresponding to the left potential conflict obstacle is: The guide point simulation model used to determine the right guide point coordinates of the obstacle simulation corresponding to the right potential conflict obstacle is: Among them, (x lead ,y lead ) is the coordinate of the obstacle simulation guide point; (x ob ,y ob ) is the position information of the second potential threat obstacle; θ c is the angle between the velocity information of the second potential threat obstacle and the horizontal direction; ΔT2 and ΔT3 are the simulation times of the obstacle simulation guidance point.

8. The method according to claim 4, characterized in that The guide point distance evaluation function is: Among them, lead_dist(v,w) is the evaluation function of the distance between the leading points; R is the radius of the spacecraft; p end is the coordinate of the end point of the simulated trajectory of the aircraft; oba Simulate the coordinates of the guiding point for the ath obstacle; τ a is the weight of each second potential threat obstacle; m is the number of second potential threat obstacles; d lead The Euclidean distance between the coordinates of the obstacle simulation guide point and the coordinates of the end point of the vehicle simulation trajectory; dist ca is the distance between the aircraft and the ath second potential threat obstacle; cb is the distance between the aircraft and the bth second potential threat obstacle.

9. The method according to claim 1, characterized in that: The dynamic window evaluation function is: Among them, heading(v,w) is the azimuth evaluation function; α is the weight of the azimuth evaluation function; velocity(v,w) is the speed evaluation function; β is the weight of the speed evaluation function; dist(v,w) is the distance evaluation function; γ is the weight of the distance evaluation function; traj_dist(v,w) is the trajectory point distance evaluation function; δ is the weight of the trajectory point distance evaluation function; lead_dist(v,w) is the guide point distance evaluation function; ε is the weight of the guide point distance evaluation function; σ is a smoothing function, which normalizes each evaluation function.

10. A system for determining a simulated trajectory of an aircraft, characterized in that: The system comprises: A window determination unit, used to determine a speed sampling window based on the physical structure of the aircraft and obstacle information; A speed determination unit, configured to use the speed sampling window to obtain a speed combination of the aircraft within a sampling time; A function construction unit, used to construct a dynamic window evaluation function including a trajectory point distance evaluation function and a guide point distance evaluation function; wherein the trajectory point distance evaluation function is used to characterize and measure the positional relationship between the simulated trajectory of the aircraft and the simulated trajectory of the obstacle; and the guide point distance evaluation function is used to characterize and guide the aircraft to detour in a specified direction to reduce the randomness of the obstacle avoidance motion; The construction method of the trajectory point distance evaluation function includes: Determine a first set of potential threat obstacles within a predetermined trajectory point distance evaluation function range; Acquire speed information and position information of a first potential threat obstacle in the first potential threat obstacle set, and generate obstacle simulation trajectory point coordinates corresponding to the first potential threat obstacle using a trajectory point simulation model; Constructing the trajectory point distance evaluation function based on the coordinates of the obstacle simulation trajectory point, the distance between the aircraft and the first potential threat obstacle, and the aircraft simulation trajectory; The trajectory point distance evaluation function is: Among them, traj_dist(v,w) is the trajectory point distance evaluation function; R is the radius of the spacecraft; p end is the coordinate of the end point of the simulated trajectory of the aircraft; obi is the coordinate of the simulated trajectory point of the i-th obstacle; τ i is the weight of each first potential threat obstacle; n is the number of first potential threat obstacles; d traj The Euclidean distance between the coordinates of the obstacle simulation trajectory point and the coordinates of the end point of the aircraft simulation trajectory; dist ci is the distance between the aircraft and the first potential threatening obstacle; cj is the distance between the aircraft and the jth first potential threat obstacle; The trajectory scoring unit is used to score the simulated trajectory of the aircraft corresponding to the speed combination using the dynamic window evaluation function, and determine the simulated trajectory of the target aircraft based on the scoring result.

11. A computer device, characterized in that: include: A memory and a processor, wherein the memory and the processor are communicatively connected to each other, the memory stores computer instructions, and the processor executes the method for determining the simulated trajectory of an aircraft according to any one of claims 1 to 9 by executing the computer instructions.

12. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a computer to execute the method for determining a simulated trajectory of an aircraft according to any one of claims 1 to 9.

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