High-speed moving body dynamic obstacle avoidance control method based on line-of-sight rotation coordinate system

Abstract

The application relates to the technical field of intelligent traffic and logistics transportation, in particular to a high-speed moving body dynamic obstacle avoidance control method based on a line-of-sight rotation coordinate system. The method comprises the following steps: in an incomplete perception information scene, a nonlinear relative motion model is established, and an optimal maneuvering direction is determined; based on the optimal control principle, the obstacle avoidance problem of the high-speed moving body is constructed into an optimal control problem with terminal constraints and energy constraints, and optimal obstacle avoidance control instructions are generated by solving the problem; when a preset condition is met, the high-speed moving body is controlled so that the driving force is preferentially used to adjust the maneuvering acceleration direction of the high-speed moving body to coincide with the optimal maneuvering direction. The method can solve the technical problem of how the moving body selects and tracks the optimal maneuvering direction in a three-dimensional space to realize stable and energy-efficient dynamic obstacle avoidance without relying on prior knowledge of the obstacle motion model in the incomplete perception information scene.

Description

Technical Field

[0001] The embodiments of this application relate to the field of intelligent transportation and logistics technology, and in particular to a dynamic obstacle avoidance control method for high-speed moving bodies based on a line-of-sight rotating coordinate system. Background Technology

[0002] In modern transportation scenarios such as autonomous driving and intelligent logistics delivery, the dynamic obstacle avoidance capability of high-speed moving bodies (e.g., high-speed aircraft, autonomous vehicles, logistics drones, etc.) is crucial for ensuring traffic safety and improving transportation efficiency. However, in actual road or low-altitude flight environments, the vehicle is often in a complex and ever-changing perception environment (i.e., a scenario with incomplete perception information), meaning it cannot obtain all the state information of surrounding vehicles or dynamic obstacles in real time and accurately, but can only rely on localized and noisy observation information. Existing technical solutions for dynamic obstacle avoidance mainly suffer from the following shortcomings: Some studies assume that the motion control strategies of surrounding obstacles (such as uniform motion, predetermined trajectories, etc.) are known and design obstacle avoidance strategies based on this assumption. However, in complex real-world traffic scenarios, the driving behavior of other road users is often unpredictable, rendering this assumption invalid and limiting the practicality of the designed control strategies. Furthermore, other studies employ intelligent algorithms based on deep learning and reinforcement learning to generate obstacle avoidance strategies. These methods typically require simplifying complex traffic dynamics models to a low-dimensional state space, involve complex reward function design, suffer from training convergence difficulties, and offer limited applicability to high-speed, highly dynamic traffic obstacle avoidance scenarios.

[0003] Furthermore, most studies are based on two-dimensional planar collision avoidance models, whose "standard collision avoidance geometry" may fail for obstacles with strong maneuverability (e.g., vehicles suddenly changing lanes). When an obstacle approaches at high speed from the side, the vehicle's ability to provide effective maneuvering acceleration perpendicular to the line of sight in a two-dimensional plane may be insufficient, but this does not mean that the vehicle's maneuverability perpendicular to the line of sight in three-dimensional space (e.g., three-dimensional traffic or UAV airspace containing vertical directions) is insufficient. Therefore, it is necessary to extend the research to three-dimensional nonlinear motion models. However, in three-dimensional space, there are countless directions perpendicular to the line of sight, such as on a plane with the line of sight as the normal vector. Choosing the optimal maneuvering direction for the moving vehicle that maximizes obstacle avoidance effectiveness is a problem that has not yet been systematically solved by existing technologies. Summary of the Invention

[0004] In view of this, embodiments of this application propose a dynamic obstacle avoidance control method for high-speed moving bodies based on a line-of-sight rotating coordinate system. This method aims to solve the technical problem of how a moving body can select and track the optimal maneuvering direction in three-dimensional space without relying on prior knowledge of the obstacle motion model in scenarios with incomplete perception information, so as to achieve stable and energy-efficient dynamic obstacle avoidance.

[0005] To achieve the above objectives, embodiments of this application propose a dynamic obstacle avoidance control method for high-speed moving bodies based on a line-of-sight rotating coordinate system, the method comprising the following steps: In scenarios with incomplete perception information, a nonlinear relative motion model between a high-speed moving body and surrounding dynamic obstacles is established. Under the line-of-sight rotation coordinate system, the optimal maneuvering direction for the high-speed moving body to avoid dynamic obstacles is analyzed and determined. Based on the principle of optimal control, under the premise of assuming that the dynamic obstacle adopts a known control strategy, the obstacle avoidance problem of high-speed moving body is constructed as an optimal control problem with terminal constraints and energy constraints. By solving this optimal control problem, the optimal obstacle avoidance control command of high-speed moving body is generated. Based on the optimal maneuvering direction and the optimal obstacle avoidance control command, when the preset conditions are met, the high-speed moving body is controlled so that it prioritizes using the driving force to adjust its maneuvering acceleration direction to coincide with the optimal maneuvering direction.

[0006] To achieve the above objectives, embodiments of this application also propose a dynamic obstacle avoidance control system for high-speed moving bodies based on a line-of-sight rotating coordinate system, the system comprising: The model building and analysis module is used to build a nonlinear relative motion model between a high-speed moving body and surrounding dynamic obstacles in scenarios with incomplete perception information, and to analyze and determine the optimal maneuvering direction of the high-speed moving body to avoid dynamic obstacles in the line-of-sight rotation coordinate system. The problem construction and solution module is used to construct the obstacle avoidance problem of high-speed moving bodies into an optimal control problem with terminal constraints and energy constraints based on the optimal control principle and assuming that the dynamic obstacles adopt a known control strategy. By solving this optimal control problem, the optimal obstacle avoidance control command of the high-speed moving body is generated. The control module is used to control the high-speed moving body based on the optimal maneuvering direction and the optimal obstacle avoidance control command, when the preset conditions are met, so that it prioritizes the use of driving force to adjust its maneuvering acceleration direction to coincide with the optimal maneuvering direction.

[0007] To achieve the above objectives, embodiments of this application also propose an electronic device, including: a processor and a memory, wherein the memory stores instructions executable by the processor, and the processor is configured to execute the instructions such that the electronic device can implement a dynamic obstacle avoidance control method for high-speed moving bodies based on a line-of-sight rotation coordinate system as described above.

[0008] To achieve the above objectives, embodiments of this application also propose a computer-readable storage medium storing a computer program that, when executed by a processor, enables a dynamic obstacle avoidance control method for high-speed moving bodies based on a line-of-sight rotation coordinate system as described above.

[0009] This application proposes a dynamic obstacle avoidance control method for high-speed moving bodies based on a line-of-sight rotating coordinate system. In scenarios with incomplete perception information, a nonlinear relative motion model between the high-speed moving body and surrounding dynamic obstacles is established. Under the line-of-sight rotating coordinate system, the optimal maneuvering direction for the high-speed moving body to avoid dynamic obstacles is analyzed and determined. Based on the optimal control principle, assuming the dynamic obstacles employ a known control strategy, the obstacle avoidance problem of the high-speed moving body is constructed as an optimal control problem with terminal constraints and energy constraints. By solving this optimal control problem, the optimal obstacle avoidance control command for the high-speed moving body is generated. Based on the optimal maneuvering direction and the optimal obstacle avoidance control command, when preset conditions are met, the high-speed moving body is controlled so that it prioritizes using its driving force to adjust its maneuvering acceleration direction to coincide with the optimal maneuvering direction. This scheme can solve the technical problem of how a moving body can select and track the optimal maneuvering direction in three-dimensional space without relying on prior knowledge of the obstacle motion model in scenarios with incomplete perception information, thereby achieving stable and energy-efficient dynamic obstacle avoidance.

[0010] Optionally, in the line-of-sight rotation coordinate system, the optimal maneuvering direction for the high-speed moving body to avoid dynamic obstacles is analyzed and determined, including: establishing a line-of-sight rotation coordinate system with the line-of-sight direction as the x-axis, the line-of-sight angular momentum direction as the z-axis, and the y-axis as the cross product of the z-axis and x-axis; deriving expressions for the approach acceleration and the rate of change of line-of-sight angular momentum between the high-speed moving body and the dynamic obstacle; and determining the y-axis direction along the line-of-sight rotation coordinate system as the optimal maneuvering direction based on the expressions for the approach acceleration and the rate of change of line-of-sight angular momentum.

[0011] Optionally, proximity acceleration The expression is: ; in, Indicates the line-of-sight angular momentum; Indicates relative distance; Represents the environmental field constant; Indicates the leading angle of motion of a dynamic obstacle; This represents the magnitude of the position vector of a dynamic obstacle. and These represent the acceleration components of a high-speed moving object and a dynamic obstacle in the line-of-sight direction, respectively.

[0012] Optionally, the rate of change of line-of-sight angular momentum The expression is: ; in, This represents the angle between the y-axis of the line-of-sight rotation coordinate system and the position vector of the dynamic obstacle; and These represent the motion acceleration components of the high-speed moving object and the dynamic obstacle in the y-axis direction of the line-of-sight rotation coordinate system, respectively.

[0013] Optionally, the obstacle avoidance problem of a high-speed moving body is constructed as an optimal control problem with terminal constraints and energy constraints. By solving this optimal control problem, optimal obstacle avoidance control commands for the high-speed moving body are generated, including: Using the lateral line-of-sight angular velocity of the dynamic obstacle as the state variable, a state equation is established; where, the state equation... It is expressed as follows: ; in, Represents state variables; Represents the response coefficients of a dynamic obstacle motion model. Indicates the approximate speed. Indicates relative distance. and This represents the time-varying coefficient determined by the geometric relationship of relative motion. This indicates the lateral control acceleration of a high-speed moving body; Construct a performance index function with the objectives of maximizing the state variables at the terminal moment and minimizing the process control energy; the performance index function is expressed as follows: ; in, and Indicates the weighting coefficient. and These represent the initial and final moments of obstacle avoidance, respectively. Based on the Pontryagin minimum principle, the optimal control problem consisting of state equations and performance index functions is solved to obtain the optimal obstacle avoidance control strategy for the lateral direction of a high-speed moving body; the formula for the optimal obstacle avoidance control strategy is as follows: ; in, and For the reason , , , , , , , and Determined intermediate variables.

[0014] Optionally, When assuming a constant acceleration model for the dynamic obstacle, the state equation is modified as follows: ; in, This represents the compensation coefficient for the maneuverability of a high-speed moving body; Indicates the relevant angle; This represents the longitudinal line-of-sight angle; the generated optimal lateral obstacle avoidance control command is the command value based on the base model. times.

[0015] Optionally, based on the optimal maneuvering direction and the optimal obstacle avoidance control command, when preset conditions are met, the high-speed moving body is controlled so that it prioritizes using its driving force to adjust its maneuvering acceleration direction to coincide with the optimal maneuvering direction. This includes: determining the optimal obstacle avoidance control command value for the lateral direction of the high-speed moving body. Is it greater than its maximum available drive capability? ;like Then, the high-speed moving body is controlled using the optimal obstacle avoidance control command in the lateral direction, while its longitudinal path is controlled to make its total acceleration command direction approach the optimal maneuvering direction; if If the high-speed moving body is controlled, the driving force will be used to adjust its maneuvering acceleration direction to coincide with the optimal maneuvering direction.

[0016] Optionally, when it is impossible to determine the specific control strategy adopted by the dynamic obstacle, the optimal obstacle avoidance control command is updated to: control the high-speed moving body to apply its maximum available driving capability along the optimal maneuvering direction. Attached Figure Description

[0017] To more clearly illustrate the technical solutions in the embodiments or related technologies of this application, the accompanying drawings used in the description of the embodiments or related technologies of this application will be briefly introduced below. Obviously, the following drawings are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort. The drawings described herein are only used to explain this application and are not intended to limit this application.

[0018] Figure 1This is a flowchart of a dynamic obstacle avoidance control method for high-speed moving bodies based on a line-of-sight rotating coordinate system provided in one embodiment of this application; Figure 2 This is a schematic diagram of a dynamic obstacle avoidance control system for a high-speed moving body based on a line-of-sight rotation coordinate system, provided in another embodiment of this application; Figure 3 This is a schematic diagram of the structure of an electronic device provided in another embodiment of this application. Detailed Implementation

[0019] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the various embodiments of this application will be described in detail below with reference to the accompanying drawings. Those skilled in the art will understand that many technical details have been presented in the embodiments of this application to facilitate better understanding. However, the technical solutions claimed in this application can be implemented even without these technical details and various variations and modifications based on the following embodiments. The division of the following embodiments is for ease of description and should not constitute any limitation on the specific implementation of this application. The following embodiments can be combined with and referenced by each other without contradiction.

[0020] In modern transportation scenarios such as autonomous driving and intelligent logistics delivery, the dynamic obstacle avoidance capability of high-speed moving bodies (e.g., high-speed aircraft, autonomous vehicles, logistics drones, etc.) is crucial for ensuring traffic safety and improving transportation efficiency. However, in actual road or low-altitude flight environments, the vehicle is often in a complex and ever-changing perception environment (i.e., a scenario with incomplete perception information). This means it cannot obtain all the status information of surrounding vehicles or dynamic obstacles in real time and accurately, but can only rely on localized and noisy observation information (such as line-of-sight angles and relative distances obtained by vehicle-mounted radar or visual sensors). Existing technical solutions for dynamic obstacle avoidance mainly suffer from the following shortcomings: Some studies assume that the motion control strategies of surrounding obstacles (such as uniform motion, predetermined trajectories, etc.) are known and design obstacle avoidance strategies based on this assumption. However, in complex real-world traffic scenarios, the driving behavior of other road users is often unpredictable, rendering this assumption invalid and limiting the practicality of the designed control strategies. Furthermore, other studies employ intelligent algorithms based on deep learning and reinforcement learning to generate obstacle avoidance strategies. These methods typically require simplifying complex traffic dynamics models to a low-dimensional state space, involve complex reward function design, suffer from training convergence difficulties, and offer limited applicability to high-speed, high-dynamic traffic obstacle avoidance scenarios (such as emergency avoidance on highways).

[0021] Furthermore, most studies are based on two-dimensional planar collision avoidance models, which may fail for obstacles with strong maneuverability (such as vehicles suddenly changing lanes) due to their "standard collision avoidance geometry." When an obstacle approaches at high speed from the side, the vehicle's ability to provide effective maneuvering acceleration perpendicular to the line of sight in a two-dimensional plane may be insufficient. However, this does not mean that the vehicle's maneuverability perpendicular to the line of sight in three-dimensional space (such as three-dimensional traffic or UAV airspace containing vertical directions) is insufficient. Therefore, it is necessary to extend the research to three-dimensional nonlinear motion models. However, in three-dimensional space, there are countless directions perpendicular to the line of sight (on a plane with the line of sight as the normal vector). Choosing the optimal maneuvering direction that maximizes obstacle avoidance for the moving vehicle is a problem that has not yet been systematically solved by existing technologies.

[0022] In view of this, embodiments of this application propose a dynamic obstacle avoidance control method for high-speed moving bodies based on a line-of-sight rotating coordinate system. This method aims to solve the technical problem of how a moving body can select and track the optimal maneuvering direction in three-dimensional space without relying on prior knowledge of the obstacle motion model in scenarios with incomplete perception information, so as to achieve stable and energy-efficient dynamic obstacle avoidance.

[0023] One embodiment of this application proposes a dynamic obstacle avoidance control method for high-speed moving bodies based on a line-of-sight rotating coordinate system, applied to an electronic device. The electronic device can be a terminal or a server; this embodiment and subsequent embodiments will use a server as an example. The implementation details of the dynamic obstacle avoidance control method for high-speed moving bodies based on a line-of-sight rotating coordinate system proposed in this embodiment are described below. The following implementation details are provided for ease of understanding and are not essential for implementing this solution.

[0024] It should be noted that the core of this method lies in designing an optimal obstacle avoidance control strategy for high-speed moving bodies that can effectively counter obstacles using motion control strategies or constant acceleration models in scenarios where perception information is incomplete (i.e., it is impossible to obtain all states of surrounding dynamic obstacles in real time and accurately).

[0025] The specific process of the dynamic obstacle avoidance control method for high-speed moving bodies based on a line-of-sight rotating coordinate system proposed in this embodiment can be described as follows: Figure 1 As shown, it includes: Step 101: In scenarios with incomplete perception information, establish a nonlinear relative motion model between the high-speed moving body and surrounding dynamic obstacles, and analyze and determine the optimal maneuvering direction for the high-speed moving body to avoid dynamic obstacles in the line-of-sight rotation coordinate system.

[0026] Understandably, based on the concept of a line-of-sight rotating coordinate system, we can derive the expressions for the approach acceleration and line-of-sight angular momentum vectors that affect obstacle avoidance performance, and thus derive the optimal maneuvering obstacle avoidance direction.

[0027] For example, a high-speed mobile body can be a high-speed aircraft, a high-speed autonomous vehicle, or a logistics drone.

[0028] In one possible embodiment, step 101 includes: establishing a line-of-sight rotation coordinate system with the line-of-sight direction as the x-axis, the line-of-sight angular momentum direction as the z-axis, and the y-axis (defined by the cross product of the z-axis and the x-axis); deriving expressions for the approach acceleration and the rate of change of line-of-sight angular momentum between the high-speed moving body and the dynamic obstacle; and determining the y-axis direction along the line-of-sight rotation coordinate system as the optimal maneuvering direction based on the expressions for the approach acceleration and the rate of change of line-of-sight angular momentum.

[0029] For example, a dynamic model of the moving body and the dynamic obstacle in an inertial frame is established. Let the position vectors of the moving body and the obstacle be respectively... and The accelerations are respectively and And taking into account the influence of external environmental factors. The relative position vector between the two is... The index of the moving body-related vector is... The index of the obstacle-related vector is By deriving the equations of relative motion, we can obtain an expression for relative acceleration that includes the influence of environmental field coefficients and maneuvering acceleration (i.e., a nonlinear relative motion model).

[0030] To simplify the analysis, a line-of-sight rotation coordinate frame (LOS Rotation Coordinate Frame) is introduced. This coordinate system is defined based on the instantaneous line-of-sight direction: the x-axis is along the line-of-sight direction (…). The z-axis is along the direction of the line-of-sight angular momentum ( ,in, The y-axis is determined by the right-hand rule. In this coordinate system, complex two-dimensional geometric motion is decoupled into motion along the line of sight (x-axis) and in planes perpendicular to the line of sight (y-axis and z-axis).

[0031] By analyzing the projection of relative acceleration onto the line-of-sight rotation coordinate system, we can derive the expressions for two key physical quantities that directly affect obstacle avoidance performance: approach acceleration and the rate of change of line-of-sight angular momentum.

[0032] In one possible embodiment, proximity acceleration The expression is: ; in, Indicates the line-of-sight angular momentum; Indicates relative distance; Indicates environmental field constants (such as the influence of road slope, gravity difference, etc.); Indicates the leading angle of motion of a dynamic obstacle; This represents the magnitude of the position vector of a dynamic obstacle. and These represent the acceleration components of a high-speed moving object and a dynamic obstacle in the line-of-sight direction, respectively.

[0033] Approximate acceleration This refers to the relative acceleration component along the line of sight. Its expression indicates that for a moving body to successfully avoid an obstacle (i.e., for the relative distance to change from decreasing to increasing), it is necessary to... This acceleration consists of three parts: a centripetal term proportional to the square of the line-of-sight angular momentum, a gravitational difference term, and the difference in maneuvering acceleration between the two sides along the line-of-sight direction.

[0034] In one possible embodiment, the rate of change of line-of-sight angular momentum The expression is: ; in, This represents the angle between the y-axis of the line-of-sight rotation coordinate system and the position vector of the dynamic obstacle; and These represent the motion acceleration components of the high-speed moving object and the dynamic obstacle in the y-axis direction of the line-of-sight rotation coordinate system, respectively.

[0035] Rate of change of line-of-sight angular momentum Analysis shows that the line-of-sight angular momentum An increase in this value will significantly increase the centripetal term in the near-acceleration, thereby effectively promoting... The key to obstacle avoidance is achieving a change from negative to positive. Its rate of change is mainly affected by the difference in maneuvering acceleration between the moving object and the dynamic obstacle in the y-axis direction of the line-of-sight rotation coordinate system.

[0036] The specific derivation process is as follows: The relative velocity vector between the moving object and the obstacle can usually be decoupled to the approach velocity along the line of sight (and) (Same direction) and the normal velocity causing the rotation of the line of sight, perpendicular to the direction of the line of sight. The rate of change of the unit vector of relative distance in the direction of the line of sight is expressed as... It can be determined by the following formula: (1) At the same time, from the definition of the line-of-sight rotation coordinate system, we know that the direction vector of the y-axis is: (2) By comparing equations (1) and (2), it can be seen that the x-axis of the line-of-sight rotation coordinate system is related to the vector... Parallel and in the same direction. This means that using a line-of-sight rotation coordinate system decomposes the 3D geometric scene into two decoupled sub-motions: one along the z-axis and the other along the y-axis, simplifying the complexity of describing the 3D geometric scene.

[0037] The dynamic models of moving bodies and dynamic obstacles in an inertial frame can be derived through force analysis as follows: (3) In obstacle avoidance scenarios, the primary objective of a moving body is usually to maximize its relative position vector. Therefore, it is necessary to study Changes under motor acceleration.

[0038] (4) From equation (3), we can conclude that: (5) During the final approach phase, the dynamic obstacle is close to the moving body, and the nonlinear effects of the external environment (such as road slope) can be ignored. (6) Considering By performing the Taylor expansion of equation (6) and making a first-order approximation, we obtain: (7) The simplified equation (7) yields: (8) Equation (8) presents a three-dimensional obstacle avoidance geometric model between a dynamic obstacle and a moving body. This model considers the effects of gravity, thrust, and vehicle dynamics on speed, unlike the commonly used constant speed assumption. Equation (8) also shows that the main factors affecting obstacle avoidance by a moving body are gravity and maneuvering acceleration. Maneuvering acceleration, as the active control force of the moving body, when projected onto the line-of-sight rotation coordinate system: (9) The projection of the dynamic obstacle's acceleration onto the line-of-sight rotation coordinate system is: (10) Approach velocity can be decomposed into a vector along the line of sight. and the vector perpendicular to the line of sight Approach acceleration can also be decomposed into a vector along the line of sight. and the vector perpendicular to the line of sight Note that the vectors mentioned above only apply to the line-of-sight direction. The three vectors are in the same direction. The vector directions are not necessarily the same. By analyzing... Differentiate: (11) Multiply both sides of equation (8) by the relative position vector get: (12) From the above equation, the first term on the right can be rearranged as follows: (13) in, The leading angle of the dynamic obstacle is the angle of motion ahead. and The included angle.

[0039] The second item on the right is organized as follows: (14) The expression for the approach acceleration of the moving body is obtained by reorganizing: (15) Let be a scalar, representing the derivative of relative distance with respect to time, and it has a geometric relationship: (16) in, Relative velocity vector The angle between the line of sight and the direction of sight.

[0040] Based on the line-of-sight angular momentum The definition of , whose size can be expressed as: (17) According to equation (17), the first term in equation (15) can be expressed as: (18) Further refining the expression for approach acceleration, we get: (19) Based on the designed three-dimensional collision avoidance geometry scenario with vehicle dynamics constraints, when and As the relative distance between the two sides decreases, if the maneuvering energy of the moving body makes... , then when As the relative distance gradually increases, obstacle avoidance is successful. Equation (19) gives an explicit expression for the approach acceleration of the moving body and the obstacle. This explicit expression shows that the approach acceleration is not only related to the maneuvering acceleration of the moving body and the obstacle in the line of sight direction, but also affected by two acceleration components related to linear angular momentum and gravity.

[0041] When the second term in equation (19) is positive, the acceleration caused by gravity is superimposed in the same direction as the current maneuvering direction of the moving body. The gravity difference acceleration can enable the moving body to obtain a larger lateral or longitudinal displacement increment, which contributes to the obstacle avoidance of the moving body.

[0042] The acceleration related to the line-of-sight angular momentum, the first term in equation (19), plays a crucial role in increasing the approach acceleration. Once the line-of-sight angular momentum is sufficiently large, the effect of this term in increasing the approach acceleration becomes more pronounced as the minimum safe distance decreases, thus enabling... This leads to a collision with the obstacle; therefore, the influence of the moving body's maneuvering acceleration on the line-of-sight angular momentum will be analyzed next. Differentiating both sides, we obtain the following relationship: (20) because Equation (20) is further rearranged as follows: (twenty one) The first term in equation (21) can be simplified to: (twenty two) Since the cross product of vectors is zero, the second term in equation (21) is zero; since the relative acceleration is in the line-of-sight rotating coordinate system... The projection of the axis is The third term can be simplified to: (twenty three) The expression for the rate of change of the line-of-sight angular momentum is obtained by rearranging: (twenty four) Assumption ,in represent The angle between the moving body's position vector and the position vector is converted from equation (21) to: (25) Equation (25) shows that the factors affecting the change in line-of-sight angular momentum include the moving body and dynamic obstacles in the line-of-sight rotation coordinate system. The effects of gravity on directional acceleration. Gravity can increase or decrease line-of-sight angular momentum. For tracking schemes with a minimum safe distance of no more than 200m, the acceleration caused by gravity difference is on the order of 0.005g, having a smaller impact compared to the directional acceleration of moving bodies and dynamic obstacles. Along The directional acceleration has the greatest impact on the line-of-sight angular momentum. When the minimum safe distance is large, the influence of the maneuvering acceleration of the moving body and dynamic obstacles on the line-of-sight angular momentum is proportional to the relative distance.

[0043] From equations (19) and (25), it can be seen that only the moving body along the line of sight and along... The acceleration in the direction directly affects the minimum safe distance and the rotation of the line of sight, along... Directional acceleration does not directly affect the minimum safe distance and line-of-sight rotation, and thus contributes the least to obstacle avoidance.

[0044] Acceleration along the line of sight of a dynamic obstacle can reduce the approach speed until... This strategy is suitable for rear-end collision scenarios. However, it's difficult to satisfy the condition when the speed of the dynamic obstacle is greater than the speed of the moving object. As can be seen from equation (19), the acceleration along the line of sight is greater than... The directional acceleration has a much smaller impact on obstacle avoidance performance; the line-of-sight angular momentum is determined by... It is generated by acceleration in the direction.

[0045] Therefore, during the obstacle avoidance phase of the moving object, along Applying directional acceleration is the most effective obstacle avoidance strategy. It increases the angular momentum of the line of sight, thereby accelerating the rotation of the line of sight. This causes the angle between the obstacle's velocity and the line of sight to increase, thus reducing the approach speed until a certain point is satisfied. Obstacle avoidance was successful.

[0046] When a moving body maneuvers to avoid an obstacle, the more intense the line-of-sight rotation, the better the maneuver effect. Therefore, it is necessary to analyze the influence of the moving body's acceleration on the line-of-sight rotation. The line-of-sight rotation coordinate system is an instantaneous motion coordinate system. The direction is consistent with the line of sight. In the inertial coordinate system, the rates of change of the direction vectors of each axis of the rotating coordinate system are as follows: (26) In the formula: The absolute angular velocity of the line-of-sight rotating coordinate system relative to the inertial coordinate system is expressed as follows: (27) In the above formula, the matrix Represented as: (28) Defined by the line-of-sight rotation coordinate system, the rates of change of each axis are expressed as: (29) Substituting equation (29) into equation (27), we get: (30) Equation (30) gives an explicit expression for the angular velocity of the line-of-sight rotation coordinate system in relation to the gravitational and maneuvering accelerations of the dynamic obstacle and the moving body in the line-of-sight direction. This equation shows that when the moving body moves along... During directional maneuvers, it rotates the line-of-sight coordinate system along the line-of-sight direction, without directly changing the direction of the line of sight, and has no direct impact on the minimum safe distance. Directional acceleration is an ineffective obstacle avoidance strategy. Furthermore, circumventing... The angular velocity in the direction remains zero and is unaffected by the acceleration of the motor.

[0047] From the perspective of the observability of obstacle avoidance control information, along The key to obstacle avoidance strategies based on direction is to obtain the direction vector. .

[0048] (31) For a moving body that obtains dynamic obstacle state information via radar or vehicle-to-everything (V2X) communication, the calculation of equation (31) is a simple process. For a moving body using a machine vision sensor, only the angle information of the dynamic obstacle can be obtained, and the line-of-sight unit vector is measured in the platform coordinate system of the machine vision sensor. and its rate of change over time as follows: (32) In the formula: and These are the azimuth and elevation angles of the line-of-sight rotation coordinate system fixed on the dynamic obstacle, respectively.

[0049] Combining equations (31) and (32), it can be seen that along The obstacle avoidance strategy for the axis is based solely on the state information of the dynamic obstacle, without depending on the type and parameters of the dynamic obstacle control strategy. For a moving body that can only obtain the angle and angular velocity information of the dynamic obstacle, the optimal obstacle avoidance direction can also be determined based on the angle and angular velocity information. Note that the derivation results assume that the dynamic obstacle and moving body obstacle avoidance control and control system are working ideally, and do not consider the impact of response time on the minimum safe distance, but these factors do not change the form of the obstacle avoidance strategy.

[0050] Understandably, along Applying axial acceleration is the optimal strategy to increase line-of-sight angular momentum, thereby maximizing approach acceleration and achieving effective obstacle avoidance. Along... The maneuvering along the axis does not directly contribute to changing the line-of-sight angular momentum and approach velocity, and is therefore inefficient; The maneuverability along the axis (line of sight) is also far less effective than along the line of sight. The axis of maneuver. The optimal obstacle avoidance direction is the line-of-sight rotation coordinate system. Axial direction, such as Figure 2 As indicated by the black arrow in the middle.

[0051] Sure The axial direction only requires a line-of-sight unit vector. and its rate of change This is also feasible for moving bodies that can only obtain angle and angular velocity information (azimuth angle ζ and elevation angle η) through machine vision sensors, realizing optimal direction determination under incomplete perception information.

[0052] Step 102: Based on the principle of optimal control, under the premise of assuming that the dynamic obstacle adopts a known control strategy, the obstacle avoidance problem of the high-speed moving body is constructed into an optimal control problem with terminal constraints and energy constraints. By solving this optimal control problem, the optimal obstacle avoidance control command of the high-speed moving body is generated.

[0053] In determining the optimal maneuver direction (i.e.) After determining the axis, specific acceleration commands need to be generated in that direction. This step can assume that the obstacle uses a known control strategy, such as a motion control strategy or a bias motion control strategy, and treat the obstacle avoidance strategy problem as an optimal control problem with terminal constraints and energy minimization process constraints. The obstacle avoidance control strategy of the moving body is obtained by solving the optimal control problem.

[0054] For example, using an obstacle with a response coefficient of Taking the motion control strategy law as an example, in the horizontal plane of the line-of-sight rotation coordinate system, a relative motion equation is established to obtain the obstacle's line-of-sight angular rate. The dynamic equations are derived. This method constructs the obstacle avoidance control problem as an optimal control problem.

[0055] In one possible embodiment, the obstacle avoidance problem of a high-speed moving body is constructed as an optimal control problem with terminal constraints and energy constraints. By solving this problem, optimal obstacle avoidance control commands for the high-speed moving body are generated, including: Using the lateral line-of-sight angular velocity of the dynamic obstacle as the state variable, a state equation is established; where, the state equation... It is expressed as follows: ; in, Represents state variables; Represents the response coefficients of a dynamic obstacle motion model. Indicates the approximate speed. Indicates relative distance. and This represents the time-varying coefficient determined by the geometric relationship of relative motion. This indicates the lateral control acceleration of a high-speed moving body; Construct a performance index function with the objectives of maximizing the state variables at the terminal moment and minimizing the process control energy; the performance index function is expressed as follows: ; in, and Indicates the weighting coefficient. and These represent the initial and final moments of obstacle avoidance, respectively. Based on the Pontryagin minimum principle, the optimal control problem consisting of state equations and performance index functions is solved to obtain the optimal obstacle avoidance control strategy for the lateral direction of a high-speed moving body; the formula for the optimal obstacle avoidance control strategy is as follows: ; in, and For the reason , , , , , , , and Determined intermediate variables.

[0056] For example, and It is related to time, relative motion geometric parameters and response coefficients The relevant expression. This control strategy shows that the optimal command is proportional to the current line-of-sight rate, and dynamically balances the competing objectives of maximizing the terminal line-of-sight rate and minimizing control energy through coefficients.

[0057] In one possible embodiment, assuming the dynamic obstacle adopts a constant acceleration model, the state equation is modified as follows: ; in, This represents the compensation coefficient for the maneuverability of a high-speed moving body; Indicates the relevant angle; This represents the longitudinal line-of-sight angle; the generated optimal lateral obstacle avoidance control command is the command value based on the base model. times.

[0058] It is understandable that if a constant acceleration model is used for the dynamic obstacle, a multiplier factor related to the moving body's maneuver acceleration compensation coefficient can be introduced into the above-derived equations, resulting in a fixed multiplier in the control strategy. If the moving body cannot determine which control strategy the dynamic obstacle uses, the conservative strategy is to directly follow the optimal direction determined in step 101. Apply the maximum available driving force to the shaft.

[0059] The specific derivation process is as follows: From the equations of relative motion, in the transverse plane we have: (33) in, The line-of-sight azimuth angle of the moving object relative to the dynamic obstacle, subscript , These represent moving objects and dynamic obstacles, respectively. This refers to the relative distance.

[0060] make Differentiate both sides of equation (33): (34) The results were: (35) in, Let be the lateral accelerations of the dynamic obstacle and the high-speed moving body, respectively. After simplification, we obtain the expression for the derivative of the longitudinal line-of-sight angular rate of the dynamic obstacle with respect to the high-speed moving body under the motion control strategy law: (36) Equation (37) is the acceleration command for the constant acceleration model, where This is the compensation coefficient for the maneuverability of the moving body.

[0061] (37) The expression for the derivative of the line-of-sight angular rate of a dynamic obstacle with respect to a high-speed moving body under different motion control strategies can be derived. For example, when the dynamic obstacle adopts the motion control strategy of Equation (37), the expression for the derivative of the longitudinal line-of-sight angular rate of the obstacle with respect to a high-speed moving body is shown in Equation (38).

[0062] (38) The acceleration command for obstacle avoidance is typically generated based on the real-time motion state of the vehicle and the obstacle to complete the obstacle avoidance task. This is the core element in designing obstacle avoidance control strategies. Current research on dynamic obstacle avoidance control methods largely relies on optimal control theory. The design approach of this type of method is as follows: first, the dynamic obstacle avoidance control problem is transformed into an optimal control problem that includes terminal constraints and energy minimization process constraints; then, this problem is solved to derive a control strategy adapted to the obstacle-avoiding moving body.

[0063] The time-varying velocity does not affect the framework of the Pontryagin minimum principle; it is sufficient to substitute the time-varying term as a known quantity during the solution process. For dynamic obstacles using motion control strategies, a moving body model can be used. By the Pontryagin minimum principle, let the state variable be the lateral line-of-sight angular velocity of the dynamic obstacle: (39) The rationale for this design is that, when the predicted obstacle avoidance end time arrives, it is desirable for the line-of-sight angular velocity of the dynamic obstacle to be as large as possible, and the derivative of the state variable can be obtained as follows: (40) In the formula: Lateral acceleration of the moving body In the dynamic obstacle line-of-sight coordinate system The projected components of the axis.

[0064] From the coordinate transformation relationship, we get: (41) For ease of expression, let And let it be: (42) The expression for the state variable is obtained as follows: (43) When a high-speed moving body avoids obstacles, consider setting the line-of-sight angular velocity of the dynamic obstacle to be within... The longer the time interval, the better. Simultaneously, considering minimizing the energy consumption of high-speed moving bodies, the performance index function is selected as follows: (44) In the formula: and These represent the initial and final moments of obstacle avoidance, respectively.

[0065] Constructing the Hamiltonian function: (45) The regular equation is: (46) The transverse condition at the final time step is: (47) Solving from the performance index function and the Hamiltonian function, we get: (48) The extreme value condition is: (49) The acceleration of the obstacle avoidance command is: (50) The expression contains terminal state variables, which need to be solved first. Substituting equation (50) into equation (43), we have: (51) From the above formula arrive integral: (52) In the formula: (53) Therefore, we can solve this. The expression: (54) Substituting equation (54) into equations (47) and (50), we obtain the lateral obstacle avoidance control strategy based on optimal control as follows: (55) For longitudinal obstacle avoidance commands, since high-speed moving bodies have difficulty lifting themselves up under conditions of limited or no power during emergency obstacle avoidance, and their own capabilities cannot change the trajectory tilt angle from negative to positive, longitudinal acceleration commands are only used to adjust the direction of the total acceleration command closer to the y-axis direction of the line-of-sight rotating coordinate system.

[0066] For example, for dynamic obstacles using a constant acceleration model, following the above derivation process, it can be seen that the acceleration command of the lateral optimal obstacle avoidance control strategy only affects... The expression, that is, the optimal acceleration command for a dynamic obstacle using a basic motion control strategy is a multiple of the acceleration command for the dynamic obstacle under the motion control strategy. The value of this multiple is related to the coefficient of the compensation term for the maneuverability of a high-speed moving body in the constant acceleration model. Related.

[0067] If the moving body cannot determine the specific motion pattern of the obstacle, then the three-dimensional optimal obstacle avoidance control command will degenerate into applying the maximum available driving capability along the analyzed optimal obstacle avoidance direction, thereby achieving dynamic obstacle avoidance.

[0068] Step 103: Based on the optimal maneuvering direction and the optimal obstacle avoidance control command, when the preset conditions are met, control the high-speed moving body so that it prioritizes using the driving force to adjust its maneuvering acceleration direction to coincide with the optimal maneuvering direction.

[0069] In engineering implementation, the total acceleration command for the moving body is synthesized from lateral and longitudinal commands. The control logic of this method is as follows: First, command allocation is performed. Optimal obstacle avoidance control commands are used for the lateral plane. The longitudinal command is mainly used to adjust the attitude of the moving body, so that the direction of the synthesized total acceleration command is as close as possible to the aforementioned optimal maneuver direction ( Alignment (axis direction).

[0070] Subsequently, during flight, the magnitude of the optimal obstacle avoidance control command value is continuously calculated. With the maximum available driving capability of the moving body itself .

[0071] In one possible embodiment, based on the optimal maneuvering direction and the optimal obstacle avoidance control command, the high-speed moving body is controlled when preset conditions are met, so that it prioritizes using driving force to adjust its maneuvering acceleration direction to coincide with the optimal maneuvering direction. This includes: determining the optimal obstacle avoidance control command value in the lateral direction of the high-speed moving body. Is it greater than its maximum available drive capability? ;like Then, the high-speed moving body is controlled using the optimal obstacle avoidance control command in the lateral direction, while its longitudinal path is controlled to make its total acceleration command direction approach the optimal maneuvering direction; if If the high-speed moving body is controlled, the driving force will be used to adjust its maneuvering acceleration direction to coincide with the optimal maneuvering direction.

[0072] In one possible embodiment, when the specific control strategy employed by the dynamic obstacle cannot be determined, the optimal obstacle avoidance control command is updated to: control the high-speed moving body to apply its maximum available driving capability along the optimal maneuvering direction.

[0073] In summary, this invention utilizes the concept of a line-of-sight rotation coordinate system to analyze the optimal obstacle avoidance direction, aiming to generate a better obstacle avoidance strategy.

[0074] This application proposes a dynamic obstacle avoidance control method for high-speed moving bodies based on a line-of-sight rotating coordinate system. In scenarios with incomplete perception information, a nonlinear relative motion model between the high-speed moving body and surrounding dynamic obstacles is established. Under the line-of-sight rotating coordinate system, the optimal maneuvering direction for the high-speed moving body to avoid dynamic obstacles is analyzed and determined. Based on the optimal control principle, assuming the dynamic obstacles employ a known control strategy, the obstacle avoidance problem of the high-speed moving body is constructed as an optimal control problem with terminal constraints and energy constraints. By solving this optimal control problem, the optimal obstacle avoidance control command for the high-speed moving body is generated. Based on the optimal maneuvering direction and the optimal obstacle avoidance control command, when preset conditions are met, the high-speed moving body is controlled so that it prioritizes using its driving force to adjust its maneuvering acceleration direction to coincide with the optimal maneuvering direction. This scheme can solve the technical problem of how a moving body can select and track the optimal maneuvering direction in three-dimensional space without relying on prior knowledge of the obstacle motion model in scenarios with incomplete perception information, thereby achieving stable and energy-efficient dynamic obstacle avoidance.

[0075] In summary, the three-dimensional optimal obstacle avoidance control strategy designed in the embodiments of this application exhibits good obstacle avoidance performance regardless of the obstacle's control strategy. It can handle obstacles where the maximum driving force exceeds the maximum driving force of the moving body, even when using motion control strategies or extended motion control strategies. Compared to maneuvering obstacle avoidance, the three-dimensional optimal obstacle avoidance control strategy designed in this chapter is more stable due to the absence of a maneuvering cycle parameter. Simulation results show that this algorithm selects the optimal timing for maneuvering rather than the maximum amplitude, thereby achieving energy-optimal obstacle avoidance while satisfying physical constraints.

[0076] The steps described above are for clarity only. In implementation, they can be combined into one step, or some steps can be broken down into multiple steps, as long as they involve the same logical relationship, they are all within the scope of protection of this application. Adding insignificant modifications or introducing insignificant designs to the algorithm or process, without changing the core design of the algorithm and process, are also within the scope of protection of this application.

[0077] Another embodiment of this application proposes a dynamic obstacle avoidance control system for high-speed moving bodies based on a line-of-sight rotating coordinate system. The details of this dynamic obstacle avoidance control system are described below. The following content is for ease of understanding and is not essential for implementing this example. Figure 2 This is a schematic diagram of a high-speed moving body dynamic obstacle avoidance control system based on a line-of-sight rotating coordinate system proposed in this embodiment, including: The model building and analysis module 210 is used to build a nonlinear relative motion model between a high-speed moving body and surrounding dynamic obstacles in a scenario with incomplete perception information, and to analyze and determine the optimal maneuvering direction of the high-speed moving body to avoid dynamic obstacles in the line-of-sight rotation coordinate system. The problem construction and solution module 220 is used to construct the obstacle avoidance problem of high-speed moving bodies into an optimal control problem with terminal constraints and energy constraints based on the optimal control principle and assuming that the dynamic obstacle adopts a known control strategy. By solving this optimal control problem, the optimal obstacle avoidance control command of the high-speed moving body is generated. The control module 230 is used to control the high-speed moving body based on the optimal maneuvering direction and the optimal obstacle avoidance control command, when the preset conditions are met, so that it prioritizes using the driving force to adjust its maneuvering acceleration direction to coincide with the optimal maneuvering direction.

[0078] It is not difficult to see that this embodiment is a system embodiment corresponding to the above method embodiments, and this embodiment can be implemented in conjunction with the above method embodiments. The relevant technical details and technical effects mentioned in the above method embodiments are still valid in this embodiment, and will not be repeated here to reduce repetition. Accordingly, the relevant technical details mentioned in this embodiment can also be applied to the above method embodiments.

[0079] It is worth mentioning that all modules and units involved in this embodiment are logical modules. In practical applications, a logical unit can be a physical unit, a part of a physical unit, or a combination of multiple physical units. Furthermore, to highlight the innovative aspects of this application, this embodiment does not introduce units that are not closely related to solving the technical problems proposed in this application; however, this does not mean that other units do not exist in this embodiment.

[0080] Another embodiment of this application provides an electronic device, such as Figure 3 As shown, it includes: memory 31 and memory 32. The memory 31 stores instructions that the processor 32 can execute. When the processor 32 is configured to execute the instructions, the electronic device can realize a dynamic obstacle avoidance control method for high-speed moving bodies based on a line-of-sight rotation coordinate system as described in the above method embodiment.

[0081] The memory and processor are connected via a bus, which includes any number of interconnecting buses and bridges, connecting various circuits of one or more processors and the memory. The bus can also connect various other circuits such as peripheral devices, voltage regulators, and power management circuits, which are well known in the art and will not be described further herein. The bus interface provides an interface between the bus and the transceiver. The transceiver can be a single component or multiple components, such as multiple receivers and transmitters, providing a unit for communicating with various other devices over a transmission medium. Data processed by the processor is transmitted over the wireless medium via an antenna, which further receives data and transmits it to the processor.

[0082] The processor manages the bus and general processing, and also provides various functions, including timing, peripheral interfaces, voltage regulation, power management, and other control functions. Memory is used to store data used by the processor during operation.

[0083] Another embodiment of this application proposes a computer-readable storage medium storing a computer program that, when executed by a processor, can implement a dynamic obstacle avoidance control method for high-speed moving bodies based on a line-of-sight rotation coordinate system as described in the above method embodiments.

[0084] That is, those skilled in the art will understand that all or part of the steps in the above method embodiments can be implemented by a program instructing related hardware. The program is stored in a storage medium and includes several instructions to cause a device (such as a microcontroller, chip, etc.) or processor to execute all or part of the steps of the method described in the method embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory, random access memory, magnetic disks, or optical disks.

[0085] Those skilled in the art will understand that the above embodiments are specific implementations of this application, and in practical applications, various changes can be made in form and detail without departing from the spirit and scope of this application. For those skilled in the art, several improvements and modifications can be made without departing from the principles of this application, and these improvements and modifications are also considered to be within the scope of protection of this application.

Claims

1. A dynamic obstacle avoidance control method for high-speed moving bodies based on a line-of-sight rotating coordinate system, characterized in that, The method includes: In scenarios with incomplete perception information, a nonlinear relative motion model between a high-speed moving body and surrounding dynamic obstacles is established. Under the line-of-sight rotation coordinate system, the optimal maneuvering direction for the high-speed moving body to avoid dynamic obstacles is analyzed and determined. Based on the principle of optimal control, under the premise of assuming that the dynamic obstacle adopts a known control strategy, the obstacle avoidance problem of high-speed moving body is constructed as an optimal control problem with terminal constraints and energy constraints. By solving this optimal control problem, the optimal obstacle avoidance control command of high-speed moving body is generated. Based on the optimal maneuvering direction and the optimal obstacle avoidance control command, when the preset conditions are met, the high-speed moving body is controlled so that it prioritizes using the driving force to adjust its maneuvering acceleration direction to coincide with the optimal maneuvering direction.

2. The method according to claim 1, characterized in that, The process of analyzing and determining the optimal maneuvering direction for a high-speed moving body to avoid dynamic obstacles in a line-of-sight rotation coordinate system includes: Establish a line-of-sight rotation coordinate system with the line-of-sight direction as the x-axis, the line-of-sight angular momentum direction as the z-axis, and the y-axis defined by the cross product of the z-axis and the x-axis. Derive the expressions for the approach acceleration and the rate of change of line-of-sight angular momentum between a high-speed moving object and a dynamic obstacle; Based on the expressions for approach acceleration and the rate of change of line-of-sight angular momentum, the y-axis direction along the line-of-sight rotating coordinate system is determined as the optimal maneuver direction.

3. The method according to claim 2, characterized in that, Approximate acceleration The expression is: ； in, Indicates the line-of-sight angular momentum; Indicates relative distance; Represents the environmental field constant; Indicates the leading angle of motion of a dynamic obstacle; This represents the magnitude of the position vector of a dynamic obstacle. and These represent the acceleration components of a high-speed moving object and a dynamic obstacle in the line-of-sight direction, respectively.

4. The method according to claim 3, characterized in that, Rate of change of line-of-sight angular momentum The expression is: ； in, This represents the angle between the y-axis of the line-of-sight rotation coordinate system and the position vector of the dynamic obstacle; and These represent the motion acceleration components of the high-speed moving object and the dynamic obstacle in the y-axis direction of the line-of-sight rotation coordinate system, respectively.

5. The method according to claim 1, characterized in that, The process of constructing the obstacle avoidance problem of a high-speed moving body as an optimal control problem with terminal constraints and energy constraints, and generating optimal obstacle avoidance control commands for the high-speed moving body by solving this optimal control problem, includes: Using the lateral line-of-sight angular velocity of the dynamic obstacle as the state variable, a state equation is established; where, the state equation... It is expressed as follows: ； in, Represents state variables; Represents the response coefficients of a dynamic obstacle motion model. Indicates the approximate speed. Indicates relative distance. and This represents the time-varying coefficient determined by the geometric relationship of relative motion. This indicates the lateral control acceleration of a high-speed moving body; Construct a performance index function with the objectives of maximizing the state variables at the terminal moment and minimizing the process control energy; the performance index function is expressed as follows: ； in, and Indicates the weighting coefficient. and These represent the initial and final moments of obstacle avoidance, respectively. Based on the Pontryagin minimum principle, the optimal control problem consisting of state equations and performance index functions is solved to obtain the optimal obstacle avoidance control strategy for the lateral direction of a high-speed moving body; the formula for the optimal obstacle avoidance control strategy is as follows: ； in, and For the reason , , , , , , , and Determined intermediate variables.

6. The method according to claim 5, characterized in that, When assuming a constant acceleration model for the dynamic obstacle, the state equation is modified as follows: ； in, This represents the compensation coefficient for the maneuverability of a high-speed moving body; Indicates the relevant angle; This represents the longitudinal line-of-sight angle; the generated optimal lateral obstacle avoidance control command is the command value based on the base model. times.

7. The method according to claim 1, characterized in that, The control command based on the optimal maneuvering direction and optimal obstacle avoidance, when preset conditions are met, controls the high-speed moving body to prioritize using driving force to adjust its maneuvering acceleration direction to coincide with the optimal maneuvering direction, including: Determine the optimal obstacle avoidance control command value for the lateral movement of a high-speed moving body. Is it greater than its maximum available drive capability? ; like Then, the optimal obstacle avoidance control command is used to control the high-speed moving body laterally, while controlling its longitudinal channel so that the direction of its total acceleration command approaches the optimal maneuvering direction. like If the high-speed moving body is controlled, the driving force will be used to adjust its maneuvering acceleration direction to coincide with the optimal maneuvering direction.

8. The method according to claim 1, characterized in that, When the specific control strategy employed by the dynamic obstacle cannot be determined, the optimal obstacle avoidance control command is updated as follows: Control the high-speed moving body to apply its maximum available driving capacity along the optimal maneuvering direction.

9. An electronic device, characterized in that, include: The processor and memory, wherein the memory stores instructions that the processor can execute, and the processor is configured to, when executing the instructions, enable the electronic device to implement a dynamic obstacle avoidance control method for a high-speed moving body based on a line-of-sight rotating coordinate system as described in any one of claims 1 to 8.

10. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by the processor, it can implement a dynamic obstacle avoidance control method for high-speed moving bodies based on a line-of-sight rotating coordinate system as described in any one of claims 1 to 8.

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