Emergency control method and system for composite wing unmanned aerial vehicle

Abstract

The invention provides an emergency control method and system for a composite wing unmanned aerial vehicle. The method comprises the following steps: acquiring airspace traffic situation sensing data, and determining position information of the composite wing unmanned aerial vehicle in a complex airspace with communication delay or communication link interruption; generating a first control parameter matched with the dynamic obstacle avoidance path according to the position information; adjusting the first control parameter according to the flight attitude parameter and the target attitude parameter to generate a second control parameter; when it is detected that a communication link is interrupted, signal modulation and clustering coding processing are carried out on the second control parameter, and a distributed relay transmission signal in an ad hoc network mode is generated, so that an initial route control instruction is optimized through a node jump strategy and a priority routing allocation strategy of the distributed relay transmission signal; emergency route replanning and flight attitude cooperative control of the composite wing unmanned aerial vehicle in a communication failure state are realized; according to the invention, multi-aircraft cooperative emergency route planning and flight control of the composite-wing unmanned aerial vehicle in a complex airspace with an interrupted communication link and without an external instruction are realized.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of emergency control, and in particular to an emergency control method and system for a compound wing unmanned aerial vehicle. BACKGROUND

[0002] In a complex airspace environment, the compound wing unmanned aerial vehicle may be caused by electromagnetic interference, meteorological mutation or hardware failure when performing tasks, resulting in communication link interruption or serious delay. In such a sudden situation, the compound wing unmanned aerial vehicle needs to perceive the dynamic obstacle distribution in real time and maintain flight stability under the premise of lacking external instruction support, while relying on limited communication resources to complete autonomous route adjustment, which puts high requirements on the emergency response capability and multi-modal control strategy of the system.

[0003] At present, a specific existing scheme adopts a real-time obstacle avoidance and path planning technology based on a centralized communication architecture, which receives sensor data of the compound wing unmanned aerial vehicle in real time through a ground control center, generates an obstacle avoidance path by using a global path planning algorithm, and issues control instructions through a high-bandwidth communication link. However, the existing scheme has significant defects, for example, it is highly dependent on real-time communication of the central node, and once the communication link is interrupted, the global path planning and instruction issuing function will be disabled, and the compound wing unmanned aerial vehicle will be in a passive state without autonomous decision-making capability, which is difficult to meet the emergency control requirements in the communication failure scenario in the complex airspace; the static obstacle map cannot adapt to the dynamic changes of the airspace environment, and lacks a multi-level obstacle avoidance priority layering mechanism, which is prone to path oscillation or collision risk in dense obstacle scenarios, etc. SUMMARY

[0004] The present application provides an emergency control method and system for a compound wing unmanned aerial vehicle, to solve the problems in the prior art that it is difficult to meet the emergency control requirements in the communication failure scenario in the complex airspace; it cannot adapt to the dynamic changes of the airspace environment, and is prone to path oscillation or collision risk in dense obstacle scenarios, etc.

[0005] In a first aspect, the present application provides an emergency control method for a compound wing unmanned aerial vehicle, comprising: acquiring airspace traffic situation awareness data to determine the position information of the compound wing unmanned aerial vehicle in a complex airspace with communication delay or communication link interruption; According to the position information, the geometric boundary of the emergency obstacle avoidance area is drawn to calculate a dynamic obstacle avoidance path, and a first control parameter matching the dynamic obstacle avoidance path is generated; According to the axial deviation value of the flight attitude parameter and the target attitude parameter of the compound wing unmanned aerial vehicle, the first control parameter is adjusted to generate a second control parameter, and the second control parameter is used to maintain the emergency flight stability of the compound wing unmanned aerial vehicle; When a communication link interruption is detected, the second control parameter is subjected to signal modulation and cluster coding to generate a distributed relay transmission signal in self-organizing network mode. By using the node hopping strategy and priority routing allocation strategy of the distributed relay transmission signal, the initial route control command of the compound wing UAV is optimized to obtain the target control command, so as to realize the emergency route replanning and flight attitude cooperative control of the compound wing UAV in the case of communication failure.

[0006] Optionally, based on the location information, the geometric boundaries of the emergency obstacle avoidance area are defined to calculate a dynamic obstacle avoidance path and generate first control parameters matching the dynamic obstacle avoidance path, including: Obtain the spatial distribution of airspace obstacles in the complex airspace, and combine the location information to delineate the geometric boundaries of the emergency obstacle avoidance area; Based on the shape and distance parameters of the geometric boundary, a multi-level safety buffer zone is constructed with the position of the compound wing UAV as the starting point. Each level of the multi-level safety buffer zone corresponds to a different obstacle avoidance priority. The candidate paths within the multi-level safety buffer zone that have the least conflict with the flight direction of the compound wing UAV are selected step by step, and the dynamic obstacle avoidance path is determined based on the curvature continuity and path length of the candidate paths. Based on the heading angle change rate, altitude offset, and speed adjustment of the dynamic obstacle avoidance path, the control surface deflection angle and thruster distribution ratio of the compound wing UAV are adjusted to generate the first control parameters.

[0007] Optionally, the spatial distribution of airspace obstacles in the complex airspace is obtained, and the geometric boundaries of the emergency obstacle avoidance area are delineated based on the location information, including: The three-dimensional spatial coordinate set of airspace obstacles perceived in real time by the compound wing UAV in the complex airspace is obtained. The three-dimensional spatial coordinate set includes the position information, size parameters and motion direction parameters of the airspace obstacles. Based on the set of three-dimensional spatial coordinates, the spatial distribution of the airspace obstacles is spatially topologically segmented to generate multiple sub-regions, wherein the boundary of each sub-region is determined by the coordinates of the vertex of the largest outer geometry of the adjacent airspace obstacles. Based on the relative distance between the position information of the compound wing UAV and the sub-region, target sub-regions that conflict with the flight direction of the compound wing UAV are filtered out, and the target sub-regions are marked as key conflict areas; Boundary fitting is performed on the coordinates of the circumscribed geometric vertices of the airspace obstacles in the critical conflict area to generate the geometric boundary of the emergency obstacle avoidance area.

[0008] Optionally, based on the axial deviation between the flight attitude parameters of the compound-wing UAV and the target attitude parameters, the first control parameters are adjusted to generate the second control parameters, including: Calculate the axial deviation between the flight attitude parameters of the compound wing UAV and the target attitude parameters, wherein the flight attitude parameters include pitch angle, roll angle and yaw angle; Based on the amplitude and directional components of the axial deviation value, the control amount of the control surface deflection angle in the first control parameter is adjusted to generate the adjusted control surface deflection angle, so that the deflection direction of the flaps and ailerons of the compound wing UAV is consistent with the compensation direction of the directional component. Based on the adjusted control surface deflection angle, the thrust distribution ratio of the first control parameter is adjusted synchronously to generate the adjusted thrust distribution ratio of the thruster, so that the torque distribution of the compound wing UAV on the pitch axis, roll axis and yaw axis matches the correction requirements of the amplitude component. The adjusted control surface deflection angle is compensated by the adjusted thrust distribution ratio of the propeller to generate the second control parameter.

[0009] Optionally, when a communication link interruption is detected, the second control parameters are subjected to signal modulation and clustering coding to generate a distributed relay transmission signal in the ad hoc network mode, including: When a communication link interruption is detected, the frequency band adaptation characteristics of the second control parameter are extracted to perform signal waveform conversion on the second control parameter, generate a modulation signal that matches the channel characteristics of different frequency bands, and extract the frequency band feature parameters of the modulation signal. Based on the channel stability index and signal attenuation threshold in the frequency band characteristic parameters, the modulated signal is divided into multiple data clusters, wherein each data cluster contains redundancy check information, cluster identification information and priority identification. Based on the cluster identifier and priority identifier of each data cluster, and combined with the link quality parameters and node load parameters of adjacent compound-wing UAV nodes in the node topology of the self-organizing network mode, a transmission path weight value is assigned to each data cluster to generate a transmission path sequence. Based on the transmission path sequence, the data clusters are transmitted in a time-series scheduling manner through a relay forwarding mechanism between adjacent composite wing UAV nodes, generating a distributed relay transmission signal in the self-organizing network mode. During the transmission process, lost or damaged data clusters are retransmitted in real time according to the redundancy check information.

[0010] Optionally, the initial flight path control commands of the compound-wing UAV are optimized through the node hopping strategy and priority routing allocation strategy of the distributed relay transmission signal to obtain target control commands, including: The heading angle correction, altitude correction, and speed correction are extracted from the route parameters in the distributed relay transmission signal, and the execution weight corresponding to each correction is determined based on the priority identifier. Based on the execution weights and the flight attitude parameters of the compound wing UAV, multi-axis coupling calculations are performed on the heading angle correction, altitude correction, and speed correction to generate initial route control commands. Based on the node switching strategy of the distributed relay transmission signal, the real-time position parameters of adjacent compound wing UAV nodes, and the link quality parameters, the heading angle change rate, altitude offset, and speed adjustment in the initial route control command are adjusted to generate an optimized route control command. The execution order of the optimized route control command is hierarchically divided according to the priority routing allocation strategy of the distributed relay transmission signal to generate the target control command.

[0011] Secondly, the present invention provides an emergency control system for a compound-wing unmanned aerial vehicle (UAV), comprising: The acquisition module is used to acquire airspace traffic situational awareness data to determine the location information of the compound-wing UAV in complex airspace with communication delays or communication link interruptions. The identification module is used to delineate the geometric boundary of the emergency obstacle avoidance area based on the location information, calculate the dynamic obstacle avoidance path, and generate a first control parameter that matches the dynamic obstacle avoidance path. The adjustment module is used to adjust the first control parameter and generate a second control parameter based on the axial deviation between the flight attitude parameters of the compound wing UAV and the target attitude parameters. The second control parameter is used to maintain the emergency flight stability of the compound wing UAV. The processing module is used to perform signal modulation and clustering encoding on the second control parameters when a communication link interruption is detected, so as to generate a distributed relay transmission signal in the self-organizing network mode. The optimization module is used to optimize the initial route control command of the compound-wing UAV through the node hopping strategy and priority routing allocation strategy of the distributed relay transmission signal, and obtain the target control command, so as to realize the emergency route replanning and flight attitude cooperative control of the compound-wing UAV in the state of communication failure.

[0012] Thirdly, the present invention provides a computing device, including a processing component and a storage component; the storage component stores one or more computer instructions; the one or more computer instructions are invoked and executed by the processing component to implement an emergency control method for a compound-wing unmanned aerial vehicle as described in the first aspect above.

[0013] Fourthly, the present invention provides a computer storage medium storing a computer program, which, when executed by a computer, implements an emergency control method for a compound-wing unmanned aerial vehicle as described in the first aspect.

[0014] This invention involves acquiring airspace traffic situational awareness data to determine the location information of a compound-wing UAV in complex airspace with communication delays or interruptions. Based on the location information, the geometric boundaries of an emergency obstacle avoidance area are delineated to calculate a dynamic obstacle avoidance path, generating a first control parameter matching the dynamic obstacle avoidance path. The first control parameter is adjusted based on the axial deviation between the flight attitude parameters of the compound-wing UAV and the target attitude parameters to generate a second control parameter, which is used to maintain the emergency flight stability of the compound-wing UAV. When a communication link interruption is detected, the second control parameter undergoes signal modulation and cluster coding to generate a distributed relay transmission signal in a self-organizing network mode. The initial route control command of the compound-wing UAV is optimized using the node hopping strategy and priority routing allocation strategy of the distributed relay transmission signal to obtain the target control command, thereby achieving emergency route replanning and coordinated flight attitude control of the compound-wing UAV in a communication failure state. This invention achieves real-time precise positioning of a compound-wing UAV in complex airspace by fusing multi-source sensing data, providing dynamic environmental input for subsequent obstacle avoidance and path planning, thus solving the problem of insufficient environmental adaptability caused by the reliance on static maps in traditional solutions. It constructs geometric boundaries based on real-time obstacle distribution, generating aerodynamically coupled dynamic obstacle avoidance paths, preventing a disconnect between path planning and the maneuverability of the compound-wing UAV, and overcoming control oscillations caused by unexecutable paths or frequent adjustments in traditional solutions. Through dynamic feedback adjustment of flight attitude deviations, it corrects control surface and thrust control parameters in real time, ensuring attitude stability during path tracking and resolving the risk of flight instability caused by the separation of path and attitude in traditional hierarchical control. In communication failure scenarios, it achieves distributed transmission and fault-tolerant retransmission of control signals through multi-band redundant communication and cluster coding technology, overcoming the single-point failure bottleneck of traditional centralized communication architectures. Based on node jump and priority routing strategies, it dynamically optimizes route commands, enabling autonomous route adjustment and multi-aircraft collaborative control after communication interruption, solving the problem of route freezing or conflict caused by communication dependence in traditional solutions. Furthermore, by sensing the spatial distribution of obstacles in real time, a multi-level safety buffer is constructed to filter candidate paths. Dynamic obstacle avoidance paths are generated by combining path curvature continuity and path length optimization. Path parameters are then mapped to control surfaces and thrust control commands, achieving deep coupling between path planning and physical control. This multi-level safety buffer system improves obstacle avoidance decision-making efficiency in complex airspaces, avoiding path oscillations or local optima traps in dense obstacle scenarios compared to traditional solutions. By generating smooth obstacle avoidance trajectories based on path curvature continuity and combining dynamic allocation of control surfaces and thrust, the system ensures that path parameters match the aerodynamic characteristics of the compound-wing UAV, resolving control delay or overshoot issues caused by the disconnect between path planning and execution in traditional solutions.

[0015] These or other aspects of the invention will become more apparent from the following description of the embodiments. Attached Figure Description

[0016] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0017] Figure 1 A flowchart of an emergency control method for a compound-wing unmanned aerial vehicle provided by the present invention is shown; Figure 2 A schematic diagram of the structure of an emergency control system for a compound-wing unmanned aerial vehicle provided by the present invention is shown; Figure 3 A schematic diagram of the structure of a computing device provided by the present invention is shown. Detailed Implementation

[0018] To enable those skilled in the art to better understand the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings.

[0019] In some of the processes described in the specification, claims, and accompanying drawings of this invention, multiple operations appearing in a specific order are included. However, it should be clearly understood that these operations may not be executed in the order they appear herein, or may be executed in parallel. The operation numbers, such as 101, 102, etc., are merely used to distinguish different operations and do not represent any execution order. Furthermore, these processes may include more or fewer operations, and these operations may be executed sequentially or in parallel. It should be noted that the descriptions such as "first," "second," etc., in this document are used to distinguish different messages, devices, modules, etc., and do not represent a sequential order, nor do they limit "first" and "second" to different types.

[0020] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0021] To address the challenges of emergency control for compound-wing unmanned aerial vehicles (UAVs) in complex airspace under conditions of communication link interruption or severe delay, this invention overcomes the dependence on a central node in traditional centralized architectures by integrating real-time situational awareness and ad hoc network communication technologies. Building upon the limitations of existing technologies in achieving real-time dynamic obstacle avoidance path generation, dynamic adjustment of attitude control parameters, and autonomous route reconstruction after communication failure, this invention utilizes a distributed transmission architecture combining multi-level iterative optimization of control parameters and clustered coding with node switching strategies. This enables the compound-wing UAV to generate adaptive obstacle avoidance paths based on dynamic obstacle boundary recognition even without external command support. Simultaneously, attitude deviation compensation and priority routing allocation strategies achieve coordinated control of flight stability and route replanning, effectively resolving key issues such as system response lag, path conflicts, and decision blind spots in communication interruption scenarios.

[0022] Figure 1 A flowchart of an emergency control method for a compound-wing unmanned aerial vehicle (UAV) according to an embodiment of the present invention is provided, such as... Figure 1 As shown, the method includes: Step 101: Acquire airspace traffic situational awareness data to determine the location information of the compound-wing UAV in complex airspace with communication delays or communication link interruptions; In this step, airspace traffic situational awareness data refers to multi-dimensional data collected by airborne sensors, including obstacle location, size, direction of movement, and airspace terrain features, used to reflect the real-time airspace environment status. Complex airspace refers to a three-dimensional airspace environment with dynamic obstacles, electromagnetic interference, weather disturbances, and communication delays or interruptions, requiring highly adaptive control strategies to cope with. Location information refers to the three-dimensional coordinates of the compound-wing UAV obtained based on multi-source data fusion, including longitude, latitude, and altitude parameters.

[0023] In this embodiment of the invention, airspace traffic situational awareness data is acquired through multi-source data fusion technology of airborne radar, lidar and visual sensors. The data includes the location, size, movement trajectory of airspace obstacles and airspace terrain features. The data is then fused and aligned in real time based on the extended Kalman filter algorithm to calculate the precise position information of the compound wing UAV in complex airspace.

[0024] Step 102: Based on the location information, delineate the geometric boundary of the emergency obstacle avoidance area to calculate the dynamic obstacle avoidance path and generate a first control parameter that matches the dynamic obstacle avoidance path; In this step, the emergency obstacle avoidance zone refers to the hazardous airspace area centered on the compound-wing UAV that requires real-time obstacle avoidance. The geometric boundary refers to the continuous polygonal boundary fitted by the vertex coordinates of the circumscribed cube of the airspace obstacle, used to define the obstacle avoidance decision range. The dynamic obstacle avoidance path refers to the executable path generated based on the optimal combination of heading angle, altitude, and speed, using a path planning algorithm. The first control parameter refers to the physical control command that maps the path parameters to the control surface deflection angle and the thruster thrust distribution ratio.

[0025] In this embodiment of the invention, based on the location information, the spatial distribution of airspace obstacles is topologically segmented using the Delaunay triangulation algorithm to generate the geometric boundary of the emergency obstacle avoidance area composed of the coordinates of the circumscribed geometric vertices of the airspace obstacles; the path planning algorithm searches for the optimal dynamic obstacle avoidance path within this geometric boundary by comprehensively considering the rate of change of heading angle, altitude offset, and speed adjustment; and the control surface deflection angle and thruster thrust distribution ratio are adjusted based on this path to generate the first control parameters.

[0026] Step 103: Based on the axial deviation between the flight attitude parameters of the compound wing UAV and the target attitude parameters, adjust the first control parameter to generate the second control parameter. The second control parameter is used to maintain the emergency flight stability of the compound wing UAV. In this step, flight attitude parameters refer to the pitch, roll, and yaw angle data parameters measured in real time by attitude sensors. Target attitude parameters refer to the preset target values ​​of pitch, roll, and yaw angles required for stable flight of the compound-wing UAV. The second control parameter refers to the amplitude components and directional differences between the flight attitude parameters and the target attitude parameters on the pitch, roll, and yaw axes. Emergency flight stability refers to the compound-wing UAV's ability to maintain balanced flight under communication failure or environmental disturbances.

[0027] In this embodiment of the invention, the axial deviation between the flight attitude parameters and the target attitude parameters of the compound wing UAV is calculated in real time using a quaternion attitude calculation algorithm; and the control surface deflection angle and thrust distribution ratio in the first control parameters are dynamically adjusted based on a fuzzy PID control algorithm to generate a second control parameter for maintaining the emergency flight stability of the compound wing UAV.

[0028] Step 104: When a communication link interruption is detected, the second control parameter is subjected to signal modulation and cluster coding to generate a distributed relay transmission signal in the self-organizing network mode; In this step, the self-organizing network mode refers to the distributed communication network architecture autonomously constructed by the nodes of the compound-wing UAV, without relying on a central node. Distributed relay transmission signal refers to the communication signal that achieves fault-tolerant transmission through multi-node hopping and redundancy verification.

[0029] In this embodiment of the invention, when a communication link interruption is detected, the second control parameter is converted into a multi-band signal waveform using orthogonal frequency division multiplexing technology, and the signal is clustered and encoded using low-density parity check code to generate a self-organizing network mode distributed relay transmission signal containing redundancy check information, cluster identification information, and priority identification.

[0030] Step 105: Optimize the initial route control command of the compound wing UAV through the node hopping strategy and priority routing allocation strategy of the distributed relay transmission signal to obtain the target control command, so as to realize the emergency route replanning and flight attitude cooperative control of the compound wing UAV in the state of communication failure. In this step, the node hopping strategy refers to a communication routing mechanism that dynamically selects the next-hop node based on path weight. The priority routing allocation strategy is a decision rule that allocates data transmission priority based on link quality and node load. The route control command refers to flight control commands that include heading angle, altitude, and speed adjustments. The target control command refers to the final executable control command after spatiotemporal alignment and priority sorting. The communication failure state refers to the operating mode in which the communication link between the compound-wing UAV and the ground control center or other nodes is interrupted.

[0031] In this embodiment of the invention, a node jump strategy is dynamically allocated based on the shortest path algorithm. Combined with the real-time position parameters and link quality parameters of adjacent compound wing UAV nodes, the initial route control command is adjusted to obtain an optimized route control command. The optimized route control command is then reconstructed through the distributed relay transmission signal to generate the target control command, thereby realizing route replanning and multi-axis attitude collaborative control under communication failure conditions.

[0032] This invention enables autonomous obstacle avoidance and route generation for compound-wing UAVs in complex airspace through multi-source perception data fusion and dynamic path planning. Based on attitude deviation feedback adjustment and distributed communication reconstruction, it breaks through the traditional solution's dependence on the communication of the central node, solves the core defects such as the disconnect between path planning and execution, poor adaptability to static environment, and low efficiency of multi-aircraft collaboration, and improves emergency response capability and flight stability in communication failure scenarios.

[0033] Taking a compound-wing UAV operating in complex mountainous airspace encountering strong electromagnetic interference and experiencing communication interruption as an example, the system first collects real-time data on the position and movement of airspace obstacles using onboard sensors. Multi-source fusion is then used to determine the UAV's own coordinates and generate the geometric boundary of the emergency obstacle avoidance zone. After planning a dynamic obstacle avoidance path using a path planning algorithm, the heading angle change rate is converted into aileron deflection commands, the altitude offset is mapped to elevator control, and the speed adjustment is allocated to the thrust ratio of the thrusters, generating the first control parameter. The current pitch angle deviation is measured using attitude sensors, and a fuzzy PID algorithm is used to dynamically adjust the control surface deflection angle, generating the second control parameter. After communication interruption, orthogonal frequency division multiplexing (OFDM) technology and low-density parity-check codes are used to convert the second control parameter into a distributed relay transmission signal, which is transmitted to the target node through a node-hopping strategy between adjacent compound-wing UAVs. Upon receiving the signal, the route command is reconstructed based on a priority routing strategy, and spatiotemporal alignment is performed using real-time flight attitude parameters. Finally, a target control command is generated, achieving autonomous obstacle avoidance, route replanning, and attitude stabilization control, enabling a safe return to base under communication failure conditions.

[0034] This invention provides a specific embodiment. Step 102 involves defining the geometric boundaries of the emergency obstacle avoidance area based on the location information, calculating the dynamic obstacle avoidance path, and generating first control parameters matching the dynamic obstacle avoidance path. This specifically includes the following steps: Step 201: Obtain the spatial distribution of airspace obstacles in the complex airspace, and delineate the geometric boundaries of the emergency obstacle avoidance area based on the location information; In this step, airspace obstacles refer to dynamic or static objects in the flight airspace of the compound-wing UAV, including other aircraft, buildings, and mountains. Spatial distribution refers to the topological structure generated based on the three-dimensional coordinate set of airspace obstacles, reflecting the relative positions and geometric relationships between obstacles. The emergency obstacle avoidance zone refers to the dangerous airspace range centered on the compound-wing UAV that requires real-time obstacle avoidance, and its boundary is determined by the extended space of the airspace obstacles.

[0035] In this embodiment of the invention, the three-dimensional coordinates, dimensions, and motion velocity parameters of all airspace obstacles in a complex airspace are obtained through the fusion sensing technology of millimeter-wave radar and lidar, forming a three-dimensional spatial coordinate set. Based on the three-dimensional spatial coordinate set, the coordinates of the circumscribed cube vertices of adjacent airspace obstacles are connected using the Delaunay triangulation algorithm to generate the geometric boundary of an emergency obstacle avoidance area composed of multiple convex polygons. The coordinates of the vertices of the geometric boundary are matched with the maximum extension space of the airspace obstacles.

[0036] Step 202: Based on the shape and distance parameters of the geometric boundary, construct a multi-level safety buffer zone starting from the position of the compound wing UAV. Each level of the multi-level safety buffer zone corresponds to a different obstacle avoidance priority. In this step, the distance parameter refers to the straight-line distance between the geometric boundary vertex of the airspace obstacle and the position of the compound-wing UAV, used for buffer zone hierarchy division. A multi-level safety buffer zone refers to concentric annular regions centered on the compound-wing UAV and divided according to distance, with each level corresponding to a different collision avoidance response level. Obstacle avoidance priority refers to the decision weight set according to the hierarchy of the multi-level safety buffer zones: Level 1 safety buffer > Level 2 safety buffer > Level 3 safety buffer.

[0037] In this embodiment of the invention, a multi-level safety buffer zone is constructed based on the Euclidean distance between the polygon vertex coordinates of the geometric boundary and the position of the compound-wing UAV (i.e., the straight-line distance from the vertex of the airspace obstacle to the position of the compound-wing UAV). The first-level buffer zone (0-5 meters) corresponds to the highest obstacle avoidance priority, the second-level buffer zone (5-15 meters) corresponds to the medium priority, and the third-level buffer zone (15-30 meters) corresponds to the low priority. The boundary of each level of buffer zone is generated by offsetting the obstacle vertex coordinates outward at equal distances, and the offset distance is the radius of the buffer zone at that level.

[0038] Step 203: Select the candidate path with the least conflict with the flight direction of the compound wing UAV within the multi-level safety buffer zone step by step, and determine the dynamic obstacle avoidance path based on the curvature continuity and path length of the candidate path. In this step, the candidate path refers to the alternative obstacle avoidance trajectory initially screened within the multi-level buffer, which must satisfy the condition of minimizing directional conflicts.

[0039] In this embodiment of the invention, a directional conflict evaluation function is used, namely the cosine value of the angle between the flight direction vector and the candidate path vector, to progressively filter candidate paths in the buffer and select paths with a cosine value greater than 0.95; the candidate paths are smoothed by cubic B-spline curves to ensure curvature continuity, so that the curvature change rate of the path is less than 0.1 rad or m², and finally the shortest and curvature-continuous path is selected as the dynamic obstacle avoidance path.

[0040] Step 204: Based on the heading angle change rate, altitude offset, and speed adjustment of the dynamic obstacle avoidance path, adjust the control surface deflection angle and thruster distribution ratio of the compound wing UAV to generate the first control parameters. In this step, the heading angle change rate refers to the change in heading angle per unit length of the dynamic obstacle avoidance path (unit: degrees or meters), determining the control surface deflection amplitude. Altitude offset refers to the vertical difference (unit: meters) between the target altitude on the dynamic obstacle avoidance path and the current altitude of the compound-wing UAV. Speed ​​adjustment refers to the scalar difference (unit: meters or seconds) between the target speed on the dynamic obstacle avoidance path and the current speed of the compound-wing UAV. Control surface deflection angle refers to the physical deflection angle (unit: degrees) controlling the ailerons or elevators, linearly mapped to the heading angle change rate or altitude offset. Thruster thrust distribution ratio refers to the thrust percentage of each thruster in a multi-thrust system, with a total thrust of 100%, dynamically correlated with the speed adjustment.

[0041] In this embodiment of the invention, the heading angle change rate of the dynamic obstacle avoidance path is mapped to the aileron deflection angle, i.e., the heading angle change rate × 0.8 coefficient; the altitude offset is mapped to the elevator deflection angle, i.e., the altitude offset × 0.5 coefficient; the speed adjustment is allocated to the thrust ratio of the thrusters, i.e., the thrust ratio of the left thruster = 50% + adjustment amount × 0.3, and the right thruster is complementary, thus generating the first control parameter.

[0042] The embodiments of the present invention address the shortcomings of traditional solutions, such as poor adaptability to static environments, low efficiency of obstacle avoidance decision-making, and unexecutable paths, by using spatially distributed geometric boundary generation, multi-level buffer priority layering, path filtering with curvature continuity constraints, and physical control parameter mapping. This significantly improves the obstacle avoidance success rate and control stability in dense obstacle scenarios.

[0043] This invention provides a specific embodiment, step 201, obtaining the spatial distribution of airspace obstacles in the complex airspace, and delineating the geometric boundary of the emergency obstacle avoidance area based on the location information, specifically including the following steps: Step 211: Obtain the set of three-dimensional spatial coordinates of airspace obstacles perceived in real time by the compound wing UAV in the complex airspace. The set of three-dimensional spatial coordinates includes the position information, size parameters and motion direction parameters of the airspace obstacles. In this step, the three-dimensional spatial coordinate set refers to the spatial location dataset of airspace obstacles obtained through sensor fusion, which includes longitude, latitude, elevation coordinates, as well as size parameters (length, width, height) and motion direction parameters (velocity vector and azimuth angle).

[0044] In this embodiment of the invention, a set of three-dimensional spatial coordinates of all airspace obstacles in a complex airspace is collected in real time through data fusion technology of airborne millimeter-wave radar, lidar and binocular vision sensor. This set includes the latitude, longitude and elevation position information, length, width and height parameters and motion direction vector (velocity and direction angle) of the airspace obstacles. A spatiotemporal synchronization algorithm is used to align the multi-sensor data coordinate system to generate a set of three-dimensional spatial coordinates of airspace obstacles with unified timestamps.

[0045] Step 212: Based on the set of three-dimensional spatial coordinates, perform spatial topological segmentation on the spatial distribution of the airspace obstacles to generate multiple sub-regions, wherein the boundary of each sub-region is determined by the coordinates of the vertex of the largest outer geometry of the adjacent airspace obstacles; In this step, a sub-region refers to a local cluster generated based on the spatial topological segmentation of airspace obstacles. Its boundary is jointly defined by the vertices of the largest circumscribed geometry of the obstacles within the cluster, reflecting the dense area of ​​local obstacles. The coordinates of the vertices of the largest circumscribed geometry refer to the coordinates of the 8 (or 4) corner points of the smallest circumscribed cube (or sphere) that encloses the airspace obstacles, and are used to quantify the spatial occupancy range of the airspace obstacles.

[0046] In this embodiment of the invention, a spatial topology network of airspace obstacles is constructed based on a three-dimensional spatial coordinate set using the Delaunay triangulation algorithm. Airspace obstacles with Euclidean distances less than a set threshold are clustered into the same sub-region. The boundary of each sub-region is determined by the coordinates of the largest outer cube vertex of all airspace obstacles contained therein, such as taking the smallest outer envelope polyhedron vertex of the outer cube vertices of all airspace obstacles.

[0047] Step 213: Based on the relative distance between the position information of the composite wing UAV and the sub-region, filter out the target sub-regions that conflict with the flight direction of the composite wing UAV, and mark the target sub-regions as key conflict areas; In this step, relative distance refers to the Euclidean distance from the current position coordinates of the compound-wing UAV to the centroid of the sub-region, used for conflict zone screening. The target sub-region refers to the sub-region with an angle of less than 45° to the flight direction of the compound-wing UAV and a relative distance less than the safety threshold, representing a high-risk area that requires priority obstacle avoidance.

[0048] In this embodiment of the invention, the relative distance between the position information of the compound-wing UAV and the centroid of each sub-region is calculated using the following formula: The algorithm evaluates the relationship between the flight direction and the sub-region: if the angle between the flight direction vector of the compound wing UAV and the vector pointing to the centroid of the sub-region is less than 45°, it is determined to be a flight direction conflict; all conflicting sub-regions are selected as target sub-regions and marked as key conflict areas.

[0049] Step 214: Perform boundary fitting on the circumscribed geometric vertex coordinates of the airspace obstacles in the critical conflict area to generate the geometric boundary of the emergency obstacle avoidance area; In this step, the critical conflict region refers to the high-priority obstacle avoidance decision area formed by merging the target sub-regions, and its boundary needs to be generated separately. The circumscribed geometry vertex coordinates refer to the set of corner coordinates of the smallest circumscribed cube of the airspace obstacle, such as the 8 vertices of the cube, used for geometric boundary calculation.

[0050] In this embodiment of the invention, the coordinates of the circumscribed geometric vertices of all airspace obstacles within the critical conflict area are extracted, and the convex hull algorithm is used to fit the boundary of the vertex set to generate the geometric boundary of the emergency obstacle avoidance area composed of a continuous sequence of polygon vertices. The boundary vertices are stored as closed polygons in clockwise order.

[0051] This invention achieves rapid locking of key obstacle avoidance areas by using a three-dimensional spatial coordinate set combined with topology segmentation and dynamic filtering mechanism for directional conflicts; it also improves the real-time performance and accuracy of obstacle avoidance decisions in complex airspace by generating compact geometric boundaries based on convex hull fitting, thus solving the problem of delayed obstacle avoidance response caused by environmental modeling lag and global computational redundancy in traditional solutions.

[0052] This invention provides a specific embodiment. Step 103 involves adjusting the first control parameter and generating the second control parameter based on the axial deviation between the flight attitude parameters of the compound-wing UAV and the target attitude parameters. This specifically includes the following steps: Step 301: Calculate the axial deviation between the flight attitude parameters of the compound wing UAV and the target attitude parameters, wherein the flight attitude parameters include pitch angle, roll angle and yaw angle; In this step, pitch angle refers to the angle between the longitudinal axis of the compound-wing UAV and the horizontal plane; a positive value indicates the nose is up, reflecting a climb or dive attitude. Roll angle refers to the angle between the transverse axis of the compound-wing UAV and the horizontal plane; a positive value indicates the right wing is tilted down, reflecting a roll attitude. Yaw angle refers to the angle between the projection of the longitudinal axis of the UAV onto the horizontal plane and true north, reflecting the heading. Flight attitude parameters refer to the real-time attitude data set composed of pitch, roll, and yaw angles. Target attitude parameters refer to preset stable flight state reference values, such as 0° pitch, 0° roll, and yaw target heading angle. Axial deviation value refers to the algebraic difference between the flight attitude parameters and the target attitude parameters on the pitch, roll, and yaw axes.

[0053] In this embodiment of the invention, the pitch angle, roll angle, and yaw angle of the compound-wing UAV are collected in real time by an airborne inertial measurement unit to form flight attitude parameters. Based on preset target attitude parameters, such as the pitch angle 0°, roll angle 0°, and yaw angle θ required for stable flight, the axial deviation value is calculated using the Euler angle deviation formula. Specifically: pitch axis deviation value = current pitch angle - target pitch angle; roll axis deviation value = current roll angle - target roll angle; yaw axis deviation value = current yaw angle - target yaw angle.

[0054] Step 302: Based on the amplitude component and direction component of the axial deviation value, adjust the control amount of the control surface deflection angle in the first control parameter to generate the adjusted control amount of the control surface deflection angle so that the deflection direction of the flaps and ailerons of the compound wing UAV is consistent with the compensation direction of the direction component. In this step, the amplitude component refers to the absolute value of the axial deviation, reflecting the severity of the attitude deviation. The directional component refers to the sign of the axial deviation value, + or -, indicating the direction of deviation correction, including up or down, left or right. The control surface deflection angle control quantity refers to the command value (unit: degrees) for controlling the deflection angle of the flaps and ailerons. The adjusted control surface deflection angle control quantity refers to the control surface control command value corrected by feedback of the axial deviation value. The compensation direction refers to the control surface deflection direction determined based on the directional component; for example, a positive deviation requires downward deflection of the flaps.

[0055] In this embodiment of the invention, the axial deviation value is decomposed into amplitude and directional components. Based on the fuzzy control rule base, the control amount of the control surface deflection angle in the first control parameter is dynamically adjusted. Specifically, according to the directional component, the compensation direction is adjusted: if the directional component is positive, the control surface deflection amount is increased; if it is negative, it is decreased. According to the amplitude component, the adjustment range is adjusted: the larger the amplitude, the larger the control surface adjustment range. The adjusted control surface deflection angle is generated to ensure that the deflection direction of the flaps and ailerons is consistent with the compensation direction.

[0056] Step 303: Based on the adjusted control surface deflection angle, synchronously adjust the thrust distribution ratio of the first control parameter to generate the adjusted thrust distribution ratio of the thruster, so that the torque distribution of the compound wing UAV on the pitch axis, roll axis and yaw axis matches the correction requirements of the amplitude component. In this step, the thrust distribution ratio refers to the percentage thrust allocated to each thruster in a multi-thruster system, totaling 100%. The adjusted thrust distribution ratio refers to the thrust distribution command value after torque balance adjustment. Pitch, roll, and yaw axes refer to the three-dimensional control axes corresponding to the longitudinal, transverse, and vertical axes of the fuselage, respectively. Torque distribution refers to the aerodynamic torque values ​​(unit: N·m) on the three axes, which must match the attitude deviation amplitude. Correction requirement refers to the target torque value calculated based on the amplitude components, such as 4 N·m of torque required for every 1° deviation.

[0057] In this embodiment of the invention, based on the adjusted control angle of the control surfaces, the thrust distribution ratio of the propellers is synchronously adjusted through the torque balance equation. Specifically: pitch axis torque = front propeller thrust × front arm - rear propeller thrust × rear arm; roll axis torque = left propeller thrust × left arm - right propeller thrust × right arm; yaw axis torque = (left propeller thrust - right propeller thrust) × yaw arm; the thrust ratio of each propeller is adjusted to match the three-axis torque distribution with the correction requirements of the amplitude components (e.g., a pitch axis deviation amplitude of 5° requires a pitch torque of 20 N·m), thereby generating the adjusted thrust distribution ratio of the propellers.

[0058] Step 304: Compensate the adjusted control surface deflection angle with the adjusted thrust distribution ratio of the propeller to generate the second control parameter; In this embodiment of the invention, the adjusted control surface deflection angle and the adjusted thrust distribution ratio of the propeller are input into the multi-axis collaborative controller. The weighted superposition algorithm (such as control surface weight 0.6 + thrust weight 0.4) is used for compensation calculation to generate the second control parameter that integrates control surface and thrust control commands.

[0059] This invention achieves deep synergy between control surface control and thrust distribution through component decoupling and dynamic feedback adjustment of axial deviation values: control surface deflection is adjusted based on directional components to avoid attitude instability caused by incorrect directional correction; thrust distribution of the propeller is quantized according to amplitude components to eliminate torque conflicts caused by the separation of control surface and thrust control in traditional schemes; and the problem of response lag of single control quantity is solved by merging control surface and thrust commands through weighted compensation calculation.

[0060] This invention provides a specific embodiment. Step 104 involves performing signal modulation and cluster coding on the second control parameters when a communication link interruption is detected, to generate a distributed relay transmission signal in self-organizing network mode. This specifically includes the following steps: Step 401: When a communication link interruption is detected, extract the frequency band adaptation characteristics of the second control parameter to perform signal waveform conversion on the second control parameter, generate a modulation signal that matches the channel characteristics of different frequency bands, and extract the frequency band feature parameters of the modulation signal; In this step, frequency band adaptation characteristics refer to the adaptability requirements of the second control parameter to the communication frequency band, including minimum bandwidth requirements, maximum tolerable delay, and anti-interference level (i.e., signal-to-interference-plus-noise ratio threshold), used to match channel characteristics. Frequency band channel characteristics refer to the physical layer attributes of different communication frequency bands, including multipath delay, Doppler shift, and path loss models for the 2.4GHz band (strong diffraction capability but susceptible to interference) and the 5.8GHz band (large bandwidth but fast attenuation). Frequency band characteristic parameters refer to the physical layer indicators of the modulated signal, including channel signal-to-noise ratio (in dB), frequency response flatness (dB / Hz), and bandwidth utilization (i.e., actual bandwidth / theoretical bandwidth).

[0061] In this embodiment of the invention, the frequency band adaptation characteristics of the second control parameter are extracted by a spectrum analysis algorithm, and the signal waveform of the second control parameter is converted using orthogonal frequency division multiplexing (OFDM) technology: the high-speed data stream is divided into multiple subcarriers, and the subcarrier modulation mode is dynamically allocated according to the channel fading characteristics (such as multipath delay and Doppler shift) of the 2.4GHz / 5.8GHz band to generate a modulation signal that matches the channel characteristics of different frequency bands; at the same time, the frequency band characteristic parameters of the modulation signal are extracted.

[0062] Step 402: Based on the channel stability index and signal attenuation threshold in the frequency band characteristic parameters, the modulated signal is divided into multiple data clusters, wherein each data cluster contains redundancy check information, cluster identification information and priority identification. In this step, the modulation signal refers to the conversion of digital control parameters into an analog waveform signal suitable for wireless transmission. The channel stability index is a parameter quantifying channel reliability, defined as the probability that the signal-to-noise ratio fluctuation range is <3dB within one consecutive second, used for clustering decisions. The signal attenuation threshold refers to the minimum signal strength (in dBm) that the receiver can decode; below this value, clustering redundancy protection must be triggered. A data cluster refers to a data unit containing a payload, redundancy check information, cluster identification information (i.e., frequency band ID + cluster sequence number), and priority identifier. Redundancy check information refers to error correction codes generated based on Reed-Solomon coding, capable of recovering up to 2 bytes of erroneous data. Cluster identification information refers to an 8-bit code (including the high 4 bits of the frequency band ID + the low 4 bits of the cluster sequence number), used for data cluster reassembly and routing. The priority identifier refers to a 4-bit binary number (0-15), with smaller values ​​indicating higher priority; level 0 represents an emergency attitude control command.

[0063] In this embodiment of the invention, based on the channel stability index (signal-to-noise ratio > 20dB for stability) and signal attenuation threshold (received signal strength > -90dBm) in the frequency band characteristic parameters, the modulated signal is divided into multiple data clusters using a data clustering algorithm: each data cluster contains a 32-byte payload, with 16-bit cyclic redundancy check information, 8-bit cluster identification information and 4-bit priority identifier added, generating a data cluster set with a redundant structure.

[0064] Step 403: Based on the cluster identifier and priority identifier of each data cluster, and combined with the link quality parameters and node load parameters of adjacent composite wing UAV nodes in the node topology of the self-organizing network mode, assign transmission path weight values ​​to each data cluster to generate a transmission path sequence. In this step, node topology refers to the spatial distribution diagram of the composite-wing UAV nodes in the ad hoc network, including node IDs, location coordinates, and a list of neighboring nodes. Link quality parameters refer to the reliability indicators of the communication link, represented by a triplet: Link Quality Parameter = (Bit Error Rate, Delay, Packet Loss Rate), where the bit error rate < 10%. -6 This is a high-quality link. Node load parameters refer to the real-time resource status of the compound-wing UAV nodes, represented by a triplet: Node load parameter = (Node CPU utilization, Node memory utilization). A node CPU utilization of <70% indicates low load. Transmission path weight values ​​quantify the quality of the transmission path, calculated based on bit error rate, latency, node CPU utilization, and node memory utilization. Transmission path sequence refers to the node hop sequence allocated to the data cluster, arranged in descending order of weight values.

[0065] In this embodiment of the invention, the target transmission node of the data cluster is determined based on the node topology of the ad hoc network mode and the cluster identification information. The adjacent nodes in the ad hoc network node topology are traversed to obtain the link quality parameters and node load parameters of each target transmission node. The transmission path weight value of each candidate path is calculated based on the formula: Transmission path weight value = (1 / bit error rate) × (1 / 0.01 delay) × (1-0.01 node CPU utilization) × (1-0.01 node memory utilization) × weight coefficient corresponding to the priority identifier, where the bit error rate is the proportion of the number of erroneous bits per unit time to the total number of transmitted bits, and the value range is [0,1]; the delay is the round-trip time (ms) of the signal transmission between nodes; the packet loss rate is the proportion of data packets lost during transmission, and the value range is [0,1]. The transmission path sequence is generated by arranging the transmission path weight values ​​in descending order, such as the transmission path sequence [path1, path2, ..., pathN], where path1 is the next-hop node with the highest transmission path weight value.

[0066] Step 404: Based on the transmission path sequence, the data clusters are transmitted in a time-series scheduling manner through a relay forwarding mechanism between adjacent composite wing UAV nodes to generate a distributed relay transmission signal in the self-organizing network mode. During the transmission process, lost or damaged data clusters are retransmitted in real time according to the redundancy check information. In this step, the relay forwarding mechanism refers to the transmission of data hop by hop between nodes according to the path sequence. If the receiver verifies the data, it forwards it to the next hop; if it fails, it requests a retransmission.

[0067] In this embodiment of the invention, based on the transmission path sequence, a time-series scheduling algorithm is adopted to transmit a set of data clusters through a relay forwarding mechanism between adjacent compound-wing UAV nodes: the sending node sends data clusters within the transmission window, the receiving node verifies the integrity through redundancy check information (if the cyclic redundancy check fails, a negative acknowledgment retransmission is triggered), and the lost clusters are retransmitted in real time; after all data clusters arrive at the target node, they are reassembled into a distributed relay transmission signal.

[0068] This invention improves the reliability of control signal transmission in communication interruption scenarios through frequency band adaptive modulation, stability-driven intelligent clustering, load-aware dynamic routing, and fault-tolerant transmission with redundancy verification. Specifically, it addresses the problem of single-band failure in interference environments in traditional solutions; dynamically adjusts redundancy strength based on channel stability to optimize resource utilization; avoids transmission bottlenecks caused by node overload and reduces end-to-end latency; and quickly recovers lost data through verification information to ensure the reachability of critical control commands.

[0069] This invention provides a specific embodiment. Step 105 involves optimizing the initial flight path control command of the compound-wing UAV through the node hopping strategy and priority routing allocation strategy of the distributed relay transmission signal to obtain the target control command. This specifically includes the following steps: Step 501: Extract the heading angle correction, altitude correction, and speed correction from the route parameters in the distributed relay transmission signal, and determine the execution weight corresponding to each correction based on the priority identifier; In this step, the heading angle correction refers to the flight control data packet encapsulated in the distributed relay transmission signal, containing three core fields: heading angle correction (unit: degrees), altitude correction (unit: meters), and speed correction (unit: meters per second). The altitude correction refers to the change in heading angle to be adjusted (positive value for right turn, negative value for left turn), calculated based on the difference between the target heading and the current heading. The speed correction refers to the change in vertical altitude to be adjusted (positive value for climb, negative value for descent), determined by the difference between the target altitude and the actual altitude. The execution weight refers to the correction coefficient (0.1-1.0) assigned according to the command priority; higher priority means greater weight. This includes the weights for heading angle correction, altitude correction, and speed correction, used to quantify the urgency of different corrections.

[0070] In this embodiment of the invention, the route parameters in the distributed relay transmission signal are extracted by the signal parsing module. Based on the priority identifier (such as a 4-bit binary value) in the signal packet header, a preset weight mapping table is queried (where priority 0-15 corresponds to weight 1.0-0.1) to determine the execution weight of the heading angle correction, altitude correction and speed correction. For example, the heading angle correction weight of priority 0 is 1.0, the altitude correction weight is 0.8 and the speed correction weight is 0.6.

[0071] Step 502: Based on the execution weight and the flight attitude parameters of the compound wing UAV, perform multi-axis coupling calculations on the heading angle correction, altitude correction, and speed correction to generate initial route control commands; In this step, the initial route control command refers to the primary control command generated through multi-axis collaborative optimization, which includes three command parameters: heading angle change rate (unit: degrees / second), altitude offset (unit: meters), and speed adjustment (unit: meters / second).

[0072] In this embodiment of the invention, execution weights (including heading angle correction weights, altitude correction weights, and speed correction weights) and flight attitude parameters (including pitch angle, roll angle, and yaw angle) are input into a multi-axis co-optimizer for coupled calculation. Specifically: First, multi-axis control quantities are allocated to obtain pitch axis allocation, roll axis allocation, and yaw axis allocation; combined with the attitude deviation vector, coupling compensation is performed to obtain heading angle coupling correction, altitude coupling correction, and speed coupling correction; the heading angle change rate = heading angle coupling correction ÷ control period; the altitude coupling correction is generated as the altitude offset, and the speed coupling correction is generated as the speed adjustment; finally, an initial route control command containing the heading angle change rate, altitude offset, and speed adjustment is generated, which can eliminate control conflicts.

[0073] Step 503: Based on the node switching strategy of the distributed relay transmission signal, the real-time position parameters of adjacent compound wing UAV nodes, and the link quality parameters, adjust the heading angle change rate, altitude offset, and speed adjustment in the initial route control command to generate an optimized route control command; In this step, the rate of change of heading angle refers to the rate at which the heading angle changes per unit time; for example, 3° / s means turning 3 degrees per second, determining the turning sensitivity. Altitude offset refers to the instantaneous difference between the target altitude and the actual altitude; for example, +20 meters means a climb of 20 meters is required. Speed ​​adjustment refers to the instantaneous difference between the target speed and the actual speed; for example, +5 m / s means an acceleration of 5 m / s is required. Optimized route control commands refer to the dynamically adjusted control commands (α', h', v') based on node status, adapting to the real-time communication environment.

[0074] In this embodiment of the invention, the next hop node is selected according to the node hopping strategy. Combining the real-time position parameters (including longitude, latitude, and altitude) of the node with the link quality parameters: heading angle change rate adjustment: if the horizontal offset of the node is >50 meters, then α = α × (1 + offset distance / 100); altitude offset adjustment: if the node altitude difference is >20 meters, then h = h + altitude difference × 0.5; speed adjustment: if the link delay is >100 ms, then v = v × (1 - delay / 200); and an optimized route control command (α', h', v') is generated.

[0075] Step 504: The execution order of the optimized route control command is hierarchically divided according to the priority routing allocation strategy of the distributed relay transmission signal to generate the target control command; In this embodiment of the invention, the optimized route control commands are hierarchically divided based on the priority routing allocation strategy: Level 1 (emergency obstacle avoidance command): α' change rate > 5° / s or |h'| > 30 meters; Level 2 (route correction command): 2° / s < α' ≤ 5° / s or 10 meters < |h'| ≤ 30 meters; Level 3 (speed optimization command): α' ≤ 2° / s and |h'| ≤ 10 meters; the target control command sequence is generated according to the hierarchical order.

[0076] This invention addresses the shortcomings of traditional solutions, such as the disconnect between flight path instructions and the real-time environment, conflicts in the execution of multiple instructions, and delayed emergency response, through priority-driven weight allocation, attitude-coupled multi-axis optimization, node-adaptive parameter adjustment, and hierarchical instruction sequencing based on urgency. Specifically, it optimizes instruction parameters in real time based on node position and link quality to improve adaptability to complex airspace; avoids conflicts between heading, altitude, and speed corrections through weight allocation and coupled calculation; and ensures that high-priority instructions are executed first, reducing the risk of collisions.

[0077] This invention provides a specific embodiment. Step 502 involves performing multi-axis coupling calculations on the heading angle correction, altitude correction, and speed correction based on the execution weights and the flight attitude parameters of the compound-wing UAV, to generate initial route control commands. This specifically includes the following steps: Step 511: Based on the execution weight, the heading angle correction, altitude correction, and speed correction are respectively allocated to the control channels of the pitch axis, roll axis, and yaw axis of the compound wing UAV, and the correction allocation ratio corresponding to each control channel is generated. In this step, the control channel refers to the independent control link of the three-axis attitude of the compound wing UAV, including the pitch axis (controlling the elevator), roll axis (controlling the ailerons), and yaw axis (controlling the rudder), used to receive the allocated corrections. The correction allocation ratio refers to the intermediate parameters that distribute the heading angle, altitude, and speed corrections proportionally to the three-axis control channels according to the execution weights, reflecting the intensity of the correction demand of each channel.

[0078] In this embodiment of the invention, based on the execution weights of the heading angle correction, altitude correction, and speed correction, the heading angle correction, altitude correction, and speed correction are respectively allocated to the pitch axis control channel, roll axis control channel, and yaw axis control channel of the compound wing UAV through weighted allocation calculation: Specifically, altitude correction × altitude correction weight = pitch axis allocation, heading angle correction × 0.5 heading correction weight = roll axis allocation, heading angle correction × 0.5 heading correction weight = yaw axis allocation, and finally, a corresponding correction allocation ratio consisting of the pitch axis allocation, roll axis allocation, and yaw axis allocation is generated.

[0079] Step 512: Calculate the attitude deviation vector between the flight attitude parameters of the compound wing UAV and the target attitude parameters; In this step, the attitude deviation vector refers to a three-dimensional vector composed of pitch deviation, roll deviation, and yaw deviation values, which quantifies the direction and magnitude of the deviation between the current attitude and the target attitude parameters.

[0080] In this embodiment of the invention, the deviations between the current pitch angle, current roll angle, and current yaw angle of the compound wing UAV and the target pitch angle, target roll angle, and target yaw angle are calculated in real time using a quaternion attitude calculation algorithm: current pitch angle - target pitch angle = pitch deviation value, current roll angle - target roll angle = roll deviation value, current yaw angle - target yaw angle = yaw deviation value. These three deviation components constitute a three-dimensional attitude deviation vector.

[0081] Step 513: Based on the correlation between the correction amount allocation ratio and the attitude deviation vector, perform multi-axis coupling calculation on the heading angle correction amount, altitude correction amount and speed correction amount to generate the heading angle coupling correction amount, altitude coupling correction amount and speed coupling correction amount; In this step, the correlation refers to the mathematical mapping rule between the correction allocation ratio and the attitude deviation vector, used to eliminate multi-axis control conflicts. The yaw angle coupling correction refers to the yaw correction value after attitude deviation compensation, eliminating the interference of roll deviation on yaw control. The altitude coupling correction refers to the altitude correction value that incorporates pitch deviation compensation, suppressing the impact of pitch attitude changes on altitude adjustment. The speed coupling correction refers to the speed correction value that superimposes the yaw deviation effect, dynamically adjusting speed requirements based on yaw deviation.

[0082] In this embodiment of the invention, a mathematical relationship is established between the set of correction amount allocation ratios and the attitude deviation vector: Specifically, the yaw axis allocation amount - 0.3 times the roll deviation value = the heading angle coupling correction amount, the pitch axis allocation amount + 0.2 pitch deviation value = the altitude coupling correction amount, and the speed correction amount × (1 + 0.1 times the absolute value of the yaw deviation) = the speed coupling correction amount. This coupling calculation eliminates multi-axis control conflicts.

[0083] Step 514: Superimpose the heading angle coupling correction, altitude coupling correction, and speed coupling correction on multiple axes to generate the initial route control command; In this embodiment of the invention, the heading angle coupling correction is divided by the unit time to convert it into the initial heading angle change rate. The altitude coupling correction is directly used as the initial altitude offset, and the speed coupling correction is directly used as the initial speed adjustment. These three parameters are integrated by a multi-axis superposition controller to finally generate an initial route control command that includes the initial heading angle change rate, the initial altitude offset, and the initial speed adjustment.

[0084] First, the physical quantity conversion of the coupling correction is performed. Specifically, the heading angle coupling correction needs to be converted into the heading angle change rate. The specific conversion method is: heading angle change rate = heading angle coupling correction ÷ control cycle; the altitude coupling correction is directly used as the altitude offset; the speed coupling correction is directly used as the speed adjustment. After the conversion is completed, a weighted superposition algorithm is used to superimpose the parameters on multiple axes. The specific rules are as follows: New heading angle change rate = original heading angle change rate × first weight coefficient + 0.3 × altitude offset × second weight coefficient - 0.2 × speed adjustment × third weight coefficient; New altitude offset = original altitude offset × fourth weight coefficient + 0.1 × original heading angle change rate × fifth weight coefficient; New speed adjustment = original speed adjustment × sixth weight coefficient - 0.15 × original heading angle change rate × seventh weight coefficient + 0.05 × original altitude offset × eighth weight coefficient. The first to eighth weight coefficients are preset according to the aerodynamic characteristics of the compound wing UAV. For example, the first weight coefficient can be 0.8, the second weight coefficient can be 0.2, and the third weight coefficient can be 0.1. After the above processing, the initial route control command is presented in a triplet structure as (new rate of change of heading angle, new altitude offset, new speed adjustment), where the new rate of change of heading angle is used to characterize the rate of heading adjustment; the new altitude offset is used to characterize the target altitude offset; and the new speed adjustment is used to characterize the target speed adjustment.

[0085] This invention addresses the mutual interference between heading, altitude, and speed control quantities during coupled execution by dynamically correcting the allocation ratio using attitude deviation vectors; it enhances the control robustness of compound-wing UAVs under disturbances such as turbulence and crosswinds by adjusting the coupling correction amount based on real-time attitude deviation; and it reduces the response delay of traditional hierarchical control architecture by generating directly executable initial route control commands through physical quantity conversion.

[0086] Figure 2 This invention provides a schematic diagram of the structure of an emergency control system for a compound-wing unmanned aerial vehicle (UAV) according to an embodiment of the present invention. Figure 2 As shown, the system includes: The acquisition module 21 is used to acquire airspace traffic situational awareness data to determine the location information of the compound wing UAV in complex airspace with communication delays or communication link interruptions. The identification module 22 is used to delineate the geometric boundary of the emergency obstacle avoidance area based on the location information, calculate the dynamic obstacle avoidance path, and generate a first control parameter that matches the dynamic obstacle avoidance path. The adjustment module 23 is used to adjust the first control parameter and generate a second control parameter based on the axial deviation between the flight attitude parameters of the compound wing UAV and the target attitude parameters. The second control parameter is used to maintain the emergency flight stability of the compound wing UAV. Processing module 24 is used to perform signal modulation and clustering coding on the second control parameters when a communication link interruption is detected, to generate a distributed relay transmission signal in self-organizing network mode; The optimization module 25 is used to optimize the initial route control command of the compound wing UAV through the node jumping strategy and priority routing allocation strategy of the distributed relay transmission signal, and obtain the target control command, so as to realize the emergency route replanning and flight attitude cooperative control of the compound wing UAV in the state of communication failure.

[0087] Figure 2 The aforementioned emergency control system for a compound-wing unmanned aerial vehicle can perform... Figure 1 The implementation principle and technical effects of the emergency control method for a compound-wing UAV described in the illustrated embodiment will not be repeated here. The specific methods by which each module and unit of the emergency control system for a compound-wing UAV in the above embodiments perform operations have been described in detail in the embodiments related to this method, and will not be elaborated upon here.

[0088] In one possible design, Figure 2 An emergency control system for a compound-wing unmanned aerial vehicle (UAV) of the embodiment shown can be implemented as a computing device, such as... Figure 3 As shown, the computing device may include a storage component 31 and a processing component 32; The storage component 31 stores one or more computer instructions, wherein the one or more computer instructions are invoked and executed by the processing component 32.

[0089] The processing component 32 is used for the above Figure 1 An emergency control method for a compound-wing unmanned aerial vehicle (UAV) according to the embodiment described above.

[0090] The processing component 32 may include one or more processors to execute computer instructions to complete all or part of the steps in the above-described method. Alternatively, the processing component may be implemented as one or more application-specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field-programmable gate arrays (FPGAs), controllers, microcontrollers, microprocessors, or other electronic components to perform the above-described method.

[0091] Storage component 31 is configured to store various types of data to support operations at the terminal. The storage component can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic storage, flash memory, magnetic disk, or optical disk.

[0092] Of course, computing devices may also include other components, such as input or output interfaces, display components, communication components, etc.

[0093] Input or output interfaces provide interfaces between processing components and peripheral interface modules, which can be output devices, input devices, etc.

[0094] The communication components are configured to facilitate wired or wireless communication between computing devices and other devices.

[0095] The computing device can be a physical device or an elastic computing host provided by a cloud computing platform. In this case, the computing device can refer to a cloud server, and the aforementioned processing components, storage components, etc., can be basic server resources rented or purchased from the cloud computing platform.

[0096] This invention also provides a computer storage medium storing a computer program, which, when executed by a computer, can perform the above-described functions. Figure 1 An emergency control method for a compound-wing unmanned aerial vehicle (UAV) according to the embodiment shown.

[0097] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0098] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Those skilled in the art can understand and implement this without any creative effort.

[0099] Through the above description of the embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus necessary general-purpose hardware platforms, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solutions, in essence or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM or RAM, magnetic disk, optical disk, etc., including several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods described in the various embodiments or some parts of the embodiments.

[0100] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. An emergency control method for a compound-wing unmanned aerial vehicle (UAV), characterized in that, include: Acquire airspace traffic situational awareness data to determine the location information of compound-wing UAVs in complex airspace with communication delays or communication link interruptions; Based on the location information, the geometric boundary of the emergency obstacle avoidance area is delineated to calculate the dynamic obstacle avoidance path and generate a first control parameter that matches the dynamic obstacle avoidance path. Based on the axial deviation between the flight attitude parameters of the compound wing UAV and the target attitude parameters, the first control parameter is adjusted to generate the second control parameter, which is used to maintain the emergency flight stability of the compound wing UAV. When a communication link interruption is detected, the frequency band adaptation characteristics of the second control parameter are extracted to convert the signal waveform of the second control parameter, generate a modulation signal that matches the channel characteristics of different frequency bands, and extract the frequency band feature parameters of the modulation signal. Based on the channel stability index and signal attenuation threshold in the frequency band feature parameters, combined with the link quality parameters and node load parameters of adjacent compound wing UAV nodes in the node topology of the self-organizing network mode, a distributed relay transmission signal in the self-organizing network mode is generated. By using the node hopping strategy and priority routing allocation strategy of the distributed relay transmission signal, the initial route control command of the compound wing UAV is optimized to obtain the target control command, so as to realize the emergency route replanning and flight attitude cooperative control of the compound wing UAV in the case of communication failure.

2. The method according to claim 1, characterized in that, Based on the channel stability index and signal attenuation threshold in the frequency band characteristic parameters, and combined with the link quality parameters and node load parameters of adjacent compound-wing UAV nodes in the node topology of the ad hoc network mode, a distributed relay transmission signal in the ad hoc network mode is generated, including: Based on the channel stability index and signal attenuation threshold in the frequency band characteristic parameters, the modulated signal is divided into multiple data clusters, wherein each data cluster contains redundancy check information, cluster identification information and priority identification. Based on the cluster identifier and priority identifier of each data cluster, and combined with the link quality parameters and node load parameters of adjacent compound-wing UAV nodes in the node topology of the self-organizing network mode, a transmission path weight value is assigned to each data cluster to generate a transmission path sequence. Based on the transmission path sequence, the data clusters are transmitted in a time-series scheduling manner through a relay forwarding mechanism between adjacent composite wing UAV nodes, generating a distributed relay transmission signal in the self-organizing network mode. During the transmission process, lost or damaged data clusters are retransmitted in real time according to the redundancy check information.

3. The method according to claim 1, characterized in that, By optimizing the node hopping strategy and priority routing allocation strategy of the distributed relay transmission signal, the initial flight path control command of the compound-wing UAV is obtained, including the target control command: The heading angle correction, altitude correction, and speed correction are extracted from the route parameters in the distributed relay transmission signal, and the execution weight corresponding to each correction is determined based on the priority identifier. Based on the execution weights and the flight attitude parameters of the compound wing UAV, multi-axis coupling calculations are performed on the heading angle correction, altitude correction, and speed correction to generate initial route control commands. Based on the node switching strategy of the distributed relay transmission signal, the real-time position parameters of adjacent compound wing UAV nodes, and the link quality parameters, the heading angle change rate, altitude offset, and speed adjustment in the initial route control command are adjusted to generate an optimized route control command. The execution order of the optimized route control command is hierarchically divided according to the priority routing allocation strategy of the distributed relay transmission signal to generate the target control command.

4. The method according to claim 3, characterized in that, Based on the execution weights and the flight attitude parameters of the compound-wing UAV, multi-axis coupled calculations are performed on the heading angle correction, altitude correction, and speed correction to generate initial route control commands, including: Based on the execution weights, the heading angle correction, altitude correction, and speed correction are respectively allocated to the control channels of the pitch axis, roll axis, and yaw axis of the compound wing UAV, generating a correction allocation ratio corresponding to each control channel; Calculate the attitude deviation vector between the flight attitude parameters of the compound wing UAV and the target attitude parameters; Based on the correlation between the correction allocation ratio and the attitude deviation vector, multi-axis coupling calculations are performed on the heading angle correction, altitude correction, and velocity correction to generate the heading angle coupling correction, altitude coupling correction, and velocity coupling correction. The heading angle coupling correction, altitude coupling correction, and speed coupling correction are superimposed on multiple axes to generate the initial route control command.

5. The method according to claim 1, characterized in that, Based on the location information, the geometric boundaries of the emergency obstacle avoidance area are defined to calculate the dynamic obstacle avoidance path, and first control parameters matching the dynamic obstacle avoidance path are generated, including: Obtain the spatial distribution of airspace obstacles in complex airspace, and combine the location information to delineate the geometric boundaries of the emergency obstacle avoidance area; Based on the shape and distance parameters of the geometric boundary, a multi-level safety buffer zone is constructed with the position of the compound wing UAV as the starting point. Each level of the multi-level safety buffer zone corresponds to a different obstacle avoidance priority. The candidate paths within the multi-level safety buffer zone that have the least conflict with the flight direction of the compound wing UAV are screened step by step, and a dynamic obstacle avoidance path is determined based on the curvature continuity and path length of the candidate paths. Based on the heading angle change rate, altitude offset, and speed adjustment of the dynamic obstacle avoidance path, the control surface deflection angle and thrust distribution ratio of the compound wing UAV are adjusted to generate the first control parameters.

6. The method according to claim 5, characterized in that, Obtain the spatial distribution of airspace obstacles in the complex airspace, and, in conjunction with the location information, delineate the geometric boundaries of the emergency obstacle avoidance area, including: The three-dimensional spatial coordinate set of airspace obstacles perceived in real time by the compound wing UAV in the complex airspace is obtained. The three-dimensional spatial coordinate set includes the position information, size parameters and motion direction parameters of the airspace obstacles. Based on the set of three-dimensional spatial coordinates, the spatial distribution of the airspace obstacles is spatially topologically segmented to generate multiple sub-regions, wherein the boundary of each sub-region is determined by the coordinates of the vertex of the largest outer geometry of the adjacent airspace obstacles. Based on the relative distance between the position information of the compound wing UAV and the sub-region, target sub-regions that conflict with the flight direction of the compound wing UAV are filtered out, and the target sub-regions are marked as key conflict areas; Boundary fitting is performed on the coordinates of the circumscribed geometric vertices of the airspace obstacles in the critical conflict area to generate the geometric boundary of the emergency obstacle avoidance area.

7. The method according to claim 1, characterized in that, Based on the axial deviation between the flight attitude parameters of the compound-wing UAV and the target attitude parameters, the first control parameter is adjusted to generate the second control parameter, including: Calculate the axial deviation between the flight attitude parameters of the compound wing UAV and the target attitude parameters, wherein the flight attitude parameters include pitch angle, roll angle and yaw angle; Based on the amplitude and directional components of the axial deviation value, the control amount of the control surface deflection angle in the first control parameter is adjusted to generate the adjusted control surface deflection angle, so that the deflection direction of the flaps and ailerons of the compound wing UAV is consistent with the compensation direction of the directional component. Based on the adjusted control surface deflection angle, the thrust distribution ratio of the first control parameter is adjusted synchronously to generate the adjusted thrust distribution ratio of the thruster, so that the torque distribution of the compound wing UAV on the pitch axis, roll axis and yaw axis matches the correction requirements of the amplitude component. The adjusted control surface deflection angle is compensated by the adjusted thrust distribution ratio of the propeller to generate the second control parameter.

8. An emergency control system for a compound-wing unmanned aerial vehicle (UAV), characterized in that, include: The acquisition module is used to acquire airspace traffic situational awareness data to determine the location information of the compound-wing UAV in complex airspace with communication delays or communication link interruptions. The identification module is used to delineate the geometric boundary of the emergency obstacle avoidance area based on the location information, calculate the dynamic obstacle avoidance path, and generate a first control parameter that matches the dynamic obstacle avoidance path. The adjustment module is used to adjust the first control parameter and generate a second control parameter based on the axial deviation between the flight attitude parameters of the compound wing UAV and the target attitude parameters. The second control parameter is used to maintain the emergency flight stability of the compound wing UAV. The processing module is used to extract the frequency band adaptation characteristics of the second control parameter when a communication link interruption is detected, to perform signal waveform conversion on the second control parameter, generate a modulation signal that matches the channel characteristics of different frequency bands, and extract the frequency band feature parameters of the modulation signal. Based on the channel stability index and signal attenuation threshold in the frequency band feature parameters, combined with the link quality parameters and node load parameters of adjacent compound wing UAV nodes in the node topology of the self-organizing network mode, a distributed relay transmission signal in the self-organizing network mode is generated. The optimization module is used to optimize the initial route control command of the compound-wing UAV through the node hopping strategy and priority routing allocation strategy of the distributed relay transmission signal, and obtain the target control command, so as to realize the emergency route replanning and flight attitude cooperative control of the compound-wing UAV in the state of communication failure.

9. A computing device, characterized in that, It includes a processing component and a storage component; the storage component stores one or more computer instructions; the one or more computer instructions are invoked and executed by the processing component to implement an emergency control method for a compound-wing unmanned aerial vehicle as described in any one of claims 1 to 7.

10. A computer storage medium, characterized in that, The device contains a computer program that, when executed by a computer, implements an emergency control method for a compound-wing unmanned aerial vehicle as described in any one of claims 1 to 7.

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