Method, device and system for controlling aerial intelligent scheduling

Abstract

The application relates to the field of flight control technology and discloses a processing method, device and system for controlling aerial intelligent scheduling, which draws an initial global operation track for each aircraft through a global flight planning path, guarantees the orderliness of parallel execution of multiple tasks, is beneficial to improving overall operation efficiency, predicts a flight track based on real-time flight data, in advance, judges path conflicts and timely corrects the global operation track to perform an avoidance operation, reduces collision risks and improves the safety of collaborative operation; after the conflicts are removed, the newly planned path is converted into a continuous-time flight track, flight control instructions can be accurately executed, the smoothness and accuracy of track connection are improved and operation interruption is reduced; meanwhile, through error analysis of real-time flight data and the continuous track, attitude control is performed, flight deviation is accurately corrected, flight accuracy is ensured and the stability, accuracy, efficiency and safety of multi-aircraft collaborative operation are further improved.

Description

Technical Field

[0001] This invention relates to the field of flight control technology, and in particular to a processing method, apparatus and system for controlling intelligent air dispatch. Background Technology

[0002] In modern logistics and warehousing systems, unmanned aerial vehicles (UAVs) are gradually becoming an important tool for realizing intelligent cargo retrieval. Specifically, by being equipped with corresponding sensing systems and control algorithms, UAVs autonomously identify and grab goods in the warehouse environment, safely transporting them to their target locations, significantly improving logistics efficiency.

[0003] In reality, when cargo needs to be retrieved, aircraft typically fly along pre-set flight paths to the designated target location, pick up the cargo, and transport it to the corresponding location. To improve cargo transport efficiency, multiple aircraft often need to operate simultaneously. However, practice has shown that due to factors such as the operating environment and equipment wear and tear, flight path conflicts are prone to occur when operating based on pre-set flight paths. Once a conflict occurs, one aircraft often needs to stop flying and wait for the other to pass before continuing its flight. Therefore, existing multi-aircraft collaborative operations are inefficient and cannot adapt to complex operating environments. Thus, proposing a new intelligent aerial flight scheduling method to improve the efficiency and accuracy of multi-aircraft collaborative operations, thereby enhancing the safety of collaborative flight operations, is essential. Summary of the Invention

[0004] This invention provides a processing method, apparatus, and system for controlling intelligent air dispatch, which can improve the efficiency and accuracy of collaborative operations of multiple aircraft, thereby enhancing the collaborative safety of flight operations.

[0005] The first aspect of this invention discloses a processing method for controlling intelligent airborne scheduling. The method is applied to a multi-task operation scenario where multiple aircraft exist, each aircraft performing a corresponding task. The method includes: Control each of the aforementioned aircraft to perform the mission based on its global flight planning path, which is the planned flight path of the aircraft from its initial position to the target position to be reached; Collect first real-time flight data of each aircraft during the execution of the mission, and predict the target flight trajectory of each aircraft within the next preset time period based on the first real-time flight data of each aircraft; when it is determined that there is a flight path conflict according to the target flight trajectory of each aircraft, control all aircraft to perform flight avoidance operation according to the target flight trajectory of each aircraft. Once the flight conflict avoidance is detected to be resolved, the target flight planning path of each aircraft after the flight conflict avoidance is obtained, and based on the preset flight path parameters, the target flight planning path of each aircraft is converted into a continuous time flight trajectory, and the aircraft is controlled to continue to perform the mission based on the continuous time flight trajectory of each aircraft. Second real-time flight data of each aircraft is collected during the continued execution of the mission. Flight error analysis is performed on the second real-time flight data of each aircraft and the continuous time flight trajectory of the aircraft to obtain real-time flight parameter errors. Based on the real-time flight parameter errors of each aircraft, attitude control operations are performed on the aircraft during the continued execution of the mission.

[0006] As an optional implementation, in a first aspect of the present invention, the method further includes: The initial position and the target position to be traveled for each of the aircraft are obtained, and the environmental parameters of the current operating scenario of all the aircraft and the preset flight constraint parameters for all the aircraft are obtained. Based on the initial and target positions of all the aircraft, the environmental parameters of the current operation scenario, and the preset flight constraint parameters for all the aircraft, an initial flight planning path is generated for each aircraft. Based on the initial flight planning path of each aircraft, it is determined whether there is a path conflict with other aircraft during the execution of the mission according to its own initial flight planning path; when it is determined that there is no path conflict, the initial flight planning path of each aircraft is determined as the global flight planning path of that aircraft. When a path conflict is detected, the target path conflict is determined based on the initial flight planning paths of all the aircraft. Based on the target path conflict and the pre-determined mission urgency of each aircraft, the initial flight planning paths of all the aircraft are adjusted to obtain the adjusted flight planning paths of all the aircraft. The adjusted flight planning path of each aircraft is then determined as the global flight planning path of that aircraft.

[0007] As an optional implementation, in the first aspect of the present invention, generating an initial flight planning path for each of the aircraft based on the initial and target positions of all the aircraft, the environmental parameters of the current operational scenario, and preset flight constraint parameters for all the aircraft includes: Based on the environmental parameters of the current work scenario, a three-dimensional environmental map of the current work scenario is generated. The three-dimensional environmental map of the current work scenario is composed of multiple three-dimensional grid units with the same grid volume. Based on the initial and target positions of all the aircraft, the three-dimensional environment map of the current operation scenario, and the preset flight constraint parameters for all the aircraft, a global environment information matrix for all the aircraft is generated. Based on the global environment information matrix, path planning parameters matching all the aircraft are determined, and based on the three-dimensional environment map and the path planning parameters, an initial flight planning path for each aircraft is generated. The initial flight planning path for each aircraft consists of a sequence of multiple three-dimensional grid cells.

[0008] As an optional implementation, in the first aspect of the present invention, determining whether there is a path conflict with other aircraft during the execution of a mission according to the initial flight planning path of each aircraft includes: Based on the preset flight time window and the grid volume, a time-object occupancy table is set for each three-dimensional grid cell in the three-dimensional environment map of the current operation scene; Based on the time-object occupancy table, predict the flight time sequence required for each aircraft to fly from its initial position to the corresponding target position according to the aircraft's initial flight planning path. The flight time sequence of the aircraft is composed of the sub-time sequence of each three-dimensional grid cell corresponding to the aircraft's initial flight planning path. Based on the flight time sequence and initial flight planning path of each aircraft, the analysis is performed to determine the target three-dimensional grid cell that at least two aircraft pass through in the three-dimensional environment map of the current operation scenario during the mission execution, and the target time of each target aircraft passing through the target three-dimensional grid cell is determined, and the time difference between the target times of all the target aircraft is calculated. When it is determined that the elapsed time difference corresponding to the target three-dimensional grid unit is less than or equal to the preset elapsed time difference, it is determined that during the execution of the mission by all the aircraft according to their own initial flight planning paths, there is a path conflict with other aircraft; when it is determined that the elapsed time difference corresponding to the target three-dimensional grid unit is greater than the preset elapsed time difference, it is determined that during the execution of the mission by all the aircraft according to their own initial flight planning paths, there is no path conflict with other aircraft.

[0009] As an optional implementation, in a first aspect of the invention, predicting the target flight trajectory of each of the aircraft within a preset time period based on the first real-time flight data of each aircraft includes: The first real-time flight data of all the aircraft are fused and analyzed to obtain the real-time flight parameters of each aircraft, and based on the real-time flight parameters of each aircraft, the target flight trajectory of each aircraft in the next preset time period is predicted. The step of controlling all the aircraft to perform flight avoidance operations based on the target flight trajectory of each aircraft includes: Based on the target flight trajectory of each aircraft, analyze the flight conflict characteristics, and based on the flight conflict characteristics and the target flight trajectory of each aircraft, determine the flight conflict type that matches the flight conflict characteristics; The current state parameters of each of the aircraft are obtained, and the mission priority of each aircraft is analyzed based on the current state parameters of each aircraft. Based on the mission priority of each aircraft, a flight avoidance strategy for all the aircraft is determined. Based on the flight avoidance strategy, the flight conflict type, and the mission priority of each aircraft, flight avoidance parameters are generated for the aircraft that need to perform avoidance, wherein the mission priority of the aircraft that needs to perform avoidance is lower than the mission priority of the other aircraft. Based on the flight avoidance parameters of the avoidance aircraft and the target flight trajectories of all aircraft that do not need to be avoided, the avoidance aircraft is controlled to perform a flight avoidance operation.

[0010] As an optional implementation, in a first aspect of the present invention, the method further includes: During the process of controlling the avoidant aircraft to perform a flight avoidance operation, the avoidant aircraft is controlled to broadcast its current flight parameters to the other aircraft; The system controls other aircraft to receive the current flight parameters of the avoidance aircraft, determine the avoidance status of the avoidance aircraft based on the current flight parameters of the avoidance aircraft, and broadcast flight avoidance instructions to the avoidance aircraft based on the avoidance status of the avoidance aircraft. The system controls the avoidance aircraft to receive the flight avoidance command, and after receiving the flight avoidance command, controls the avoidance aircraft to send avoidance confirmation signals to other aircraft and ground stations.

[0011] As an optional implementation, in the first aspect of the present invention, the method of converting the target flight planning path of each of the aircraft into a continuous-time flight trajectory based on preset flight path parameters includes: For any of the aforementioned aircraft, the flight planning path of the aircraft is converted into a continuous time trajectory, and a time parameterization operation is performed on the continuous time trajectory of the aircraft to obtain the position parameters for each time point on the continuous time trajectory of the aircraft; based on the position parameters of each time point and the preset flight path parameters, a velocity planning operation is performed on the position parameters of each time point to obtain the continuous time flight trajectory of the aircraft. The step of controlling the attitude of each aircraft during its continued mission based on the real-time flight parameter error of each aircraft includes: For any of the aforementioned aircraft, based on the real-time flight parameter errors of the aircraft, analyze the desired attitude angle and total thrust requirement parameters that match the aircraft; perform attitude calculation and thrust allocation on the desired attitude angle and total thrust requirement parameters of the aircraft respectively to obtain the flight attitude parameters of the aircraft and the target rotation speed of each rotor; based on the flight attitude parameters of the aircraft and the target rotation speed of each rotor, perform attitude control operations on the aircraft during the continued execution of the mission.

[0012] A second aspect of the present invention discloses a processing device for controlling intelligent air dispatching. The device is applied to a multi-task operation scenario involving multiple aircraft, each aircraft performing a corresponding task. The device includes: The control module is used to control each of the aircraft to perform tasks based on its global flight planning path, which is the flight path planned for the aircraft from its initial position to the target position it needs to go to. The data acquisition module is used to collect the first real-time flight data of each of the aforementioned aircraft during the execution of the mission; The prediction module is used to predict the target flight trajectory of each of the aircraft within a preset time period based on the first real-time flight data of each aircraft. The control module is also used to control all the aircraft to perform flight avoidance operations based on the target flight trajectory of each aircraft when it is determined that there is a flight path conflict. The acquisition module is also used to acquire the target flight planning path of each of the aircraft after the flight conflict avoidance is resolved, when the flight conflict avoidance is detected to be resolved. The analysis module is used to convert the target flight planning path of each aircraft into a continuous-time flight trajectory based on preset flight path parameters, and to control the aircraft to continue to perform the mission based on the continuous-time flight trajectory of each aircraft. The acquisition module is also used to acquire second real-time flight data of each of the aircraft during the continued execution of the mission; The analysis module is also used to perform flight error analysis on the second real-time flight data of each aircraft and the continuous time flight trajectory of the aircraft to obtain the real-time flight parameter error; The control module is also used to perform attitude control operations on each aircraft during the continued execution of its mission, based on the real-time flight parameter errors of each aircraft.

[0013] As an optional implementation, in a second aspect of the present invention, the acquisition module is further configured to acquire the initial position and the target position to be traveled for each of the aircraft, and to acquire the environmental parameters of the current operating scenario of all the aircraft and the preset flight constraint parameters for all the aircraft. The device further includes: The generation module is used to generate an initial flight planning path for each of the aircraft based on the initial and target positions of all the aircraft, the environmental parameters of the current operation scenario, and the preset flight constraint parameters for all the aircraft. The prediction module is also used to determine, based on the initial flight planning path of each aircraft, whether there is a path conflict with other aircraft during the execution of the mission according to its own initial flight planning path; The determination module is used to determine the initial flight planning path of each aircraft as the global flight planning path of the aircraft when it is determined that there is no path conflict. The determining module is also used to determine the path conflict situation based on the initial flight planning paths of all the aircraft when it is determined that there is a path conflict situation; The adjustment module is used to perform adjustment operations on the initial flight planning paths of all the aircraft based on the target path conflict situation and the pre-determined mission urgency of each aircraft, so as to obtain the adjusted flight planning paths of all the aircraft. The determining module is further configured to determine the adjusted flight planning path of each of the aircraft as the global flight planning path of that aircraft.

[0014] As an optional implementation, in a second aspect of the invention, the generation module generates the initial flight planning path for each aircraft in a specific manner based on the initial and target positions of all the aircraft, the environmental parameters of the current operational scenario, and preset flight constraint parameters for all the aircraft, including: Based on the environmental parameters of the current work scenario, a three-dimensional environmental map of the current work scenario is generated. The three-dimensional environmental map of the current work scenario is composed of multiple three-dimensional grid units with the same grid volume. Based on the initial and target positions of all the aircraft, the three-dimensional environment map of the current operation scenario, and the preset flight constraint parameters for all the aircraft, a global environment information matrix for all the aircraft is generated. Based on the global environment information matrix, path planning parameters matching all the aircraft are determined, and based on the three-dimensional environment map and the path planning parameters, an initial flight planning path for each aircraft is generated. The initial flight planning path for each aircraft consists of a sequence of multiple three-dimensional grid cells.

[0015] As an optional implementation, in a second aspect of the invention, the specific method by which the prediction module determines whether there is a path conflict with other aircraft during the execution of a mission according to the initial flight planning path of each aircraft includes: Based on the preset flight time window and the grid volume, a time-object occupancy table is set for each three-dimensional grid cell in the three-dimensional environment map of the current operation scene; Based on the time-object occupancy table, predict the flight time sequence required for each aircraft to fly from its initial position to the corresponding target position according to the aircraft's initial flight planning path. The flight time sequence of the aircraft is composed of the sub-time sequence of each three-dimensional grid cell corresponding to the aircraft's initial flight planning path. Based on the flight time sequence and initial flight planning path of each aircraft, the analysis is performed to determine the target three-dimensional grid cell that at least two aircraft pass through in the three-dimensional environment map of the current operation scenario during the mission execution, and the target time of each target aircraft passing through the target three-dimensional grid cell is determined, and the time difference between the target times of all the target aircraft is calculated. When it is determined that the elapsed time difference corresponding to the target three-dimensional grid unit is less than or equal to the preset elapsed time difference, it is determined that during the execution of the mission by all the aircraft according to their own initial flight planning paths, there is a path conflict with other aircraft; when it is determined that the elapsed time difference corresponding to the target three-dimensional grid unit is greater than the preset elapsed time difference, it is determined that during the execution of the mission by all the aircraft according to their own initial flight planning paths, there is no path conflict with other aircraft.

[0016] As an optional implementation, in a second aspect of the invention, the prediction module predicts the target flight trajectory of each aircraft within a preset time period based on the first real-time flight data of each aircraft, including: The first real-time flight data of all the aircraft are fused and analyzed to obtain the real-time flight parameters of each aircraft, and based on the real-time flight parameters of each aircraft, the target flight trajectory of each aircraft in the next preset time period is predicted. The control module controls the specific methods by which all the aircraft perform flight avoidance operations based on the target flight trajectory of each aircraft, including: Based on the target flight trajectory of each aircraft, analyze the flight conflict characteristics, and based on the flight conflict characteristics and the target flight trajectory of each aircraft, determine the flight conflict type that matches the flight conflict characteristics; The current state parameters of each of the aircraft are obtained, and the mission priority of each aircraft is analyzed based on the current state parameters of each aircraft. Based on the mission priority of each aircraft, a flight avoidance strategy for all the aircraft is determined. Based on the flight avoidance strategy, the flight conflict type, and the mission priority of each aircraft, flight avoidance parameters are generated for the aircraft that need to perform avoidance, wherein the mission priority of the aircraft that needs to perform avoidance is lower than the mission priority of the other aircraft. Based on the flight avoidance parameters of the avoidance aircraft and the target flight trajectories of all aircraft that do not need to be avoided, the avoidance aircraft is controlled to perform a flight avoidance operation.

[0017] As an optional implementation, in a second aspect of the invention, the control module is further configured to, during the process of controlling the avoidant aircraft to perform a flight avoidance operation, control the avoidant aircraft to broadcast its current flight parameters to other aircraft; control other aircraft to receive the current flight parameters of the avoidant aircraft, determine the avoidance status of the avoidant aircraft based on the current flight parameters, and broadcast a flight avoidance command for the avoidant aircraft based on the avoidance status; control the avoidant aircraft to receive the flight avoidance command, and after receiving the flight avoidance command, control the avoidant aircraft to send a avoidance confirmation signal to other aircraft and ground stations.

[0018] As an optional implementation, in a second aspect of the invention, the specific method by which the analysis module converts the target flight planning path of each aircraft into a continuous-time flight trajectory based on preset flight path parameters includes: For any of the aforementioned aircraft, the flight planning path of the aircraft is converted into a continuous time trajectory, and a time parameterization operation is performed on the continuous time trajectory of the aircraft to obtain the position parameters for each time point on the continuous time trajectory of the aircraft; based on the position parameters of each time point and the preset flight path parameters, a velocity planning operation is performed on the position parameters of each time point to obtain the continuous time flight trajectory of the aircraft. The specific method by which the control module performs attitude control operations on each aircraft during the continued execution of its mission, based on the real-time flight parameter errors of each aircraft, includes: For any of the aforementioned aircraft, based on the real-time flight parameter errors of the aircraft, analyze the desired attitude angle and total thrust requirement parameters that match the aircraft; perform attitude calculation and thrust allocation on the desired attitude angle and total thrust requirement parameters of the aircraft respectively to obtain the flight attitude parameters of the aircraft and the target rotation speed of each rotor; based on the flight attitude parameters of the aircraft and the target rotation speed of each rotor, perform attitude control operations on the aircraft during the continued execution of the mission.

[0019] A third aspect of the present invention discloses another processing device for controlling intelligent air dispatching, the device being applied to a multi-task operation scenario in which multiple aircraft exist, each aircraft performing a corresponding task, the device comprising: Memory containing executable program code; A processor coupled to the memory; The processor invokes the executable program code stored in the memory to execute some or all of the steps in any of the methods described in the first aspect of the present invention, in order to perform scheduling operations on all the aircraft.

[0020] The fourth aspect of the present invention discloses a computer storage medium storing computer instructions, which, when invoked, are used to execute some or all of the steps in any of the methods described in the first aspect of the present invention to perform scheduling operations on all of the aircraft.

[0021] The fifth aspect of the present invention discloses a processing system for controlling intelligent air dispatching. The system is applied to a multi-task operation scenario in which there are multiple aircraft, each of which is used to perform a corresponding task. The system includes all the aircraft and a control terminal. The control terminal is used to perform some or all of the steps of the method described in any of the first aspects of the present invention to perform dispatching operations on all the aircraft.

[0022] Compared with the prior art, the present invention has the following beneficial effects: In this embodiment of the invention, in a multi-task operation scenario, there are multiple aircraft, each performing a corresponding task. Each aircraft is controlled to execute its task based on its global flight planning path, which is the planned flight path from its initial position to its desired target position. First real-time flight data of each aircraft during task execution is collected, and based on this data, the target flight trajectory of each aircraft within a preset time period is predicted. When a flight path conflict is determined based on the target flight trajectory of each aircraft, all aircraft are controlled to execute their tasks according to the target flight trajectory of each aircraft. The system performs flight avoidance maneuvers. Once the flight conflict avoidance is detected and resolved, it acquires the target flight planning path for each aircraft after the conflict avoidance is resolved. Based on preset flight path parameters, it converts the target flight planning path for each aircraft into a continuous-time flight trajectory. Based on the continuous-time flight trajectory of each aircraft, it controls the aircraft to continue performing the mission. It collects the second real-time flight data of each aircraft during the continued mission execution process and performs flight error analysis on the second real-time flight data and the continuous-time flight trajectory of each aircraft to obtain the real-time flight parameter error. Based on the real-time flight parameter error of each aircraft, it performs attitude control operations on the aircraft during the continued mission execution process. As can be seen, implementing this invention, by defining the initial global operational trajectory for each aircraft through global flight planning paths, ensures the orderly execution of multiple tasks in parallel, which is conducive to improving the overall operational efficiency of multiple tasks. Based on real-time flight data, it predicts the subsequent flight trajectory, can anticipate path conflicts in advance, and flexibly correct the global operational trajectory in a timely manner to perform avoidance operations, thereby avoiding the risk of aircraft collisions in the current operational scenario (such as in a warehouse space) from the source, and improving the safety of collaborative operations. After the conflict is resolved, the newly planned path is converted into a continuous time flight trajectory, ensuring that all flight control commands can be executed accurately, improving the smoothness and accuracy of aircraft flight trajectory connection, and reducing the interruption of multi-task operations. At the same time, through error analysis of real-time flight data and continuous trajectories, targeted attitude control is performed on the aircraft, accurately correcting flight deviations and ensuring the accuracy of aircraft flight in the current operational scenario, further improving the stability and accuracy of multi-aircraft collaborative operations, and thus comprehensively improving the efficiency, accuracy, and safety of aircraft collaborative operations in multi-task scenarios. Attached Figure Description

[0023] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0024] Figure 1 This is a flowchart illustrating a method for controlling intelligent air dispatching disclosed in an embodiment of the present invention; Figure 2 This is a flowchart illustrating another method for controlling intelligent air dispatching disclosed in an embodiment of the present invention; Figure 3 This is a schematic diagram of the structure of a processing device for controlling intelligent air dispatching disclosed in an embodiment of the present invention; Figure 4 This is a schematic diagram of the structure of another processing device for controlling intelligent air dispatching disclosed in an embodiment of the present invention; Figure 5 This is a schematic diagram of the structure of another processing device for controlling intelligent air dispatching disclosed in an embodiment of the present invention. Detailed Implementation

[0025] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. 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.

[0026] The terms "first," "second," etc., used in the specification, claims, and accompanying drawings of this invention are used to distinguish different objects, not to describe a specific order. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion. For example, a process, method, apparatus, product, or end that includes a series of steps or units is not limited to the listed steps or units, but may optionally include steps or units not listed, or may optionally include other steps or units inherent to these processes, methods, products, or ends.

[0027] In this document, the term "embodiment" means that a particular feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of the invention. The appearance of this phrase in various places throughout the specification does not necessarily refer to the same embodiment, nor is it a separate or alternative embodiment mutually exclusive with other embodiments. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with other embodiments.

[0028] This invention discloses a processing method, device, and system for controlling intelligent airborne scheduling. It defines initial global operational trajectories for each aircraft through global flight planning paths, ensuring the orderly execution of multiple tasks in parallel and improving overall operational efficiency. Based on real-time flight data, it predicts subsequent flight trajectories, anticipating path conflicts and flexibly correcting the global operational trajectory in a timely manner to perform avoidance maneuvers, thus mitigating the risk of aircraft collisions in the current operational scenario (such as within a warehouse space) and improving the safety of collaborative operations. After a conflict is resolved, the newly planned path is converted into a continuous-time flight trajectory, ensuring accurate execution of all flight control commands, improving the smoothness and accuracy of aircraft flight trajectory connections, and reducing interruptions in multi-task operations. Simultaneously, through error analysis of real-time flight data and continuous trajectories, targeted attitude control is performed on the aircraft, precisely correcting flight deviations and ensuring the accuracy of aircraft flight in the current operational scenario. This further improves the stability and accuracy of multi-aircraft collaborative operations, thereby comprehensively enhancing the efficiency, accuracy, and safety of aircraft collaborative operations in multi-task scenarios. Detailed descriptions follow.

[0029] Example 1 Please see Figure 1 , Figure 1 This is a flowchart illustrating a method for controlling intelligent air dispatching disclosed in an embodiment of the present invention. Figure 1 The described method can be applied to multi-task operation scenarios, such as logistics warehouse pickup and warehousing cargo transportation. In these scenarios, multiple aircraft operate, each performing a specific task. Figure 1 As shown, the method may include the following operations: 101. Controlling each aircraft to perform a task based on its global flight planning path, wherein the global flight planning path of each aircraft is the flight path planned for the aircraft from its initial position to the target position to be reached.

[0030] In this embodiment of the invention, the initial position and the target position to be reached can be determined according to the actual situation. For example, when it is necessary to pick up goods, the target position is the position of the goods; or when the goods have been picked up, the initial position is the position of the goods and the target position is the position where the goods need to be finally placed.

[0031] 102. Collect the first real-time flight data of each aircraft during the mission, and based on the first real-time flight data of each aircraft, predict the target flight trajectory of each aircraft within the next preset time period; when it is determined that there is a flight path conflict based on the target flight trajectory of each aircraft, control all aircraft to perform flight avoidance operations based on the target flight trajectory of each aircraft.

[0032] In this embodiment of the invention, for any aircraft, during the execution of a mission, it identifies the real-time positions of other aircraft using its binocular camera, identifies the distances between itself and other aircraft and surrounding obstacles using its lidar sensor, and broadcasts some or all of its first real-time flight data to other aircraft. Specifically, for any aircraft, its first real-time flight data includes, but is not limited to, real-time flight position data, real-time flight speed data, real-time flight acceleration data, real-time flight trajectory data, real-time position data of identified other aircraft, and real-time distance data between it and other aircraft.

[0033] In this embodiment of the invention, the specific value of the preset duration is not fixed, and can be 10 seconds, 15 seconds, etc. During the execution of the task, the prediction of the target flight trajectory can be a continuous process, that is, prediction can be performed according to a preset duration as a prediction cycle, and conflict judgment and attitude control operations can be executed. In other words, the global flight planning path is segmented for local conflict judgment and attitude control, so that the conflict situation and attitude control of each flight stage are more consistent with the actual situation, thereby improving the accuracy of local conflict judgment, improving the timeliness and accuracy of conflict resolution, and further improving the accuracy of aircraft attitude and thrust control, thereby improving the scheduling accuracy of multiple aircraft and improving the accuracy and safety of multi-aircraft collaborative operations.

[0034] In this embodiment of the invention, when it is determined that there is no flight path conflict, for any aircraft, its flight operation is controlled to be performed based on its target flight trajectory.

[0035] 103. After the flight conflict avoidance is detected to be resolved, the target flight planning path of each aircraft after the flight conflict avoidance is resolved is obtained, and based on the preset flight path parameters, the target flight planning path of each aircraft is converted into a continuous time flight trajectory, and the aircraft is controlled to continue to perform the mission based on the continuous time flight trajectory of each aircraft.

[0036] In this embodiment of the invention, the preset flight path parameters may include, but are not limited to, one or more of the following: preset flight path curvature, preset maximum tilt angle, and preset lateral acceleration.

[0037] 104. Collect the second real-time flight data of each aircraft during the continued execution of the mission, and perform flight error analysis on the second real-time flight data of each aircraft and the continuous time flight trajectory of the aircraft to obtain the real-time flight parameter error. Based on the real-time flight parameter error of each aircraft, perform attitude control operations on the aircraft during the continued execution of the mission.

[0038] In this embodiment of the invention, for any aircraft, its second real-time flight data includes, but is not limited to, real-time actual flight position, real-time flight speed, and real-time flight heading. These data are compared with the flight data at each time point in the continuous time flight trajectory of the aircraft to perform flight error analysis, thereby obtaining real-time flight parameter errors, such as flight position error, flight speed error, and flight heading error.

[0039] In this embodiment of the invention, for any aircraft, the aircraft outputs a pulse width modulation signal at a preset operating frequency (e.g., 400Hz) to adjust the motor speed of each rotor, thereby achieving precise control of rotor thrust. The duty cycle of the pulse width modulation signal is adjusted in real time according to the rotor motor speed. When the aircraft reaches its target location, such as the cargo location, it sends a control signal to the aircraft's robotic arm servo motor to drive the robotic arm to sequentially complete the cargo-retrieving actions of extending, gripping, and retracting the arm. According to a preset control cycle (e.g., 50ms), the aircraft's real-time flight position, real-time flight speed, real-time flight attitude, real-time flight battery level, robotic arm status, and other information are transmitted back to the ground station. The ground station displays the aircraft's flight status in real time, realizing full-process monitoring. When the aircraft successfully completes the cargo-retrieval action, it remains in a hovering state, waiting for the next round of task allocation from the ground station's central dispatch server. By precisely controlling the rotor thrust of the aircraft, the flight stability of the aircraft is improved. After reaching the cargo location, the robotic arm is driven to complete the automatic cargo retrieval. Multi-dimensional flight data is transmitted back according to the preset control cycle, enabling the ground station to monitor the entire process. After the cargo is retrieved, the aircraft hovers and waits for scheduling, which improves the controllability of multi-task operations, thereby improving the accuracy and safety of the aircraft cargo retrieval, and further improving the efficiency and safety of multi-aircraft collaborative operations.

[0040] It is evident that implementation Figure 1 The described method defines the initial global operational trajectory for each aircraft through global flight planning, ensuring the orderly execution of multiple tasks in parallel and improving the overall operational efficiency of multiple tasks. Based on real-time flight data, it predicts subsequent flight trajectories, anticipating path conflicts and flexibly correcting the global operational trajectory in a timely manner to perform avoidance operations. This mitigates the risk of aircraft collisions in the current operational scenario (such as within a warehouse space) from the source, improving the safety of collaborative operations. After the conflict is resolved, the newly planned path is converted into a continuous-time flight trajectory, ensuring that all flight control commands are executed accurately, improving the smoothness and accuracy of aircraft flight trajectory connections and reducing interruptions in multi-task operations. Simultaneously, through error analysis of real-time flight data and continuous trajectories, targeted attitude control is performed on the aircraft, precisely correcting flight deviations and ensuring the accuracy of aircraft flight in the current operational scenario. This further improves the stability and accuracy of multi-aircraft collaborative operations, thereby comprehensively improving the efficiency, accuracy, and safety of aircraft collaborative operations in multi-task scenarios.

[0041] In this embodiment of the invention, optionally, predicting the target flight trajectory of each aircraft within a preset time period based on the first real-time flight data of each aircraft includes: The first real-time flight data of all aircraft are fused and analyzed to obtain the real-time flight parameters of each aircraft. Based on the real-time flight parameters of each aircraft, the target flight trajectory of each aircraft in the next preset time period is predicted. This includes controlling all aircraft to perform flight avoidance maneuvers based on the target flight trajectory of each aircraft, including: Based on the target flight trajectory of each aircraft, analyze the characteristics of flight conflicts, and based on the characteristics of flight conflicts and the target flight trajectory of each aircraft, determine the type of flight conflict that matches the characteristics of flight conflicts. Obtain the current status parameters of each aircraft, analyze the mission priority of each aircraft based on the current status parameters of each aircraft, and determine the flight avoidance strategy for all aircraft based on the mission priority of each aircraft. Based on the flight avoidance strategy, flight conflict type, and mission priority of each aircraft, generate flight avoidance parameters for the aircraft that needs to perform avoidance, whose mission priority is lower than that of other aircraft. Based on the flight avoidance parameters of the avoidance vehicle and the target flight trajectories of all vehicles that do not need to be avoided, the avoidance vehicle is controlled to perform flight avoidance operations.

[0042] In this embodiment of the invention, the first real-time flight data of all aircraft are fused by Kalman filtering to obtain the real-time flight parameters of the aircraft, including but not limited to real-time flight position, real-time flight speed, and real-time flight acceleration; based on the real-time flight speed, real-time flight acceleration, and real-time flight position of the aircraft, the target flight trajectory of the aircraft in the next preset time period (e.g., 4 seconds) is predicted.

[0043] In this embodiment of the invention, flight conflict types include, but are not limited to, one of the following: follow-up conflict (i.e., a following aircraft chasing an preceding aircraft), edge conflict (i.e., there are intersecting paths between aircraft), loop conflict (i.e., multiple aircraft forming a loop deadlock, unable to fly), and vertex conflict (i.e., multiple aircraft appearing in the same position at the same time). Based on the target flight trajectory of each aircraft, the minimum vertical distance between any two aircraft is calculated. If this minimum vertical distance is less than a preset distance threshold, and the minimum vertical distance is expected to further shorten after a preset flight duration (e.g., 5 seconds), and this preset duration is less than a preset duration threshold (e.g., 8 seconds), a flight conflict is indicated. In the case of a flight conflict, based on the target flight trajectory and flight conflict characteristics (e.g., minimum vertical distance), a flight conflict type matching the flight conflict characteristics is determined. For example, if aircraft A accelerates and quickly approaches aircraft B in front, forming a follow-up conflict where the following aircraft chases the preceding aircraft.

[0044] In this embodiment of the invention, the current status parameters of each aircraft may optionally include, but are not limited to, multiple parameters such as mission urgency, remaining battery power, flight path completion (i.e., the distance already flown), and equipment load status. Different parameters correspond to different priority weights; for example, the priority weights of mission urgency, remaining battery power, flight path completion, and equipment load status decrease sequentially, and the sum of all priority weights equals 1.

[0045] In this embodiment of the invention, the optional flight avoidance parameters for the avoidance aircraft include, but are not limited to, avoidance direction and avoidance distance. Furthermore, avoidance speed may also be included. For example, if aircraft B is at its current flight position (9, 7, 3), it maintains a horizontal position and increases its altitude to 6m at a constant speed, while simultaneously reducing its speed by 50%. Aircraft B maintains a straight trajectory at the 6m altitude until the horizontal distance between it and aircraft A exceeds 5m, at which point the avoidance state is released.

[0046] As can be seen, the embodiments of the present invention can also improve the accuracy and reliability of flight parameter analysis by fusing and analyzing real-time flight data of each aircraft during mission execution, thereby predicting flight trajectories in the near future and anticipating flight conflicts in advance. When a flight conflict occurs, the characteristics of the flight conflict are analyzed to match the corresponding conflict type, and the mission priority of each aircraft is determined by combining the current state parameters of the aircraft. This improves the matching between avoidance strategies and actual conflict scenarios. Furthermore, by having low-priority aircraft avoid the original planned paths of high-priority aircraft while taking into account the original planned paths of high-priority aircraft, refined dynamic avoidance control is achieved. This is beneficial to improving the efficiency and accuracy of flight conflict elimination, further reducing the flight collision risk of multi-mission aircraft, and improving the execution accuracy and safety of multi-mission collaborative operations.

[0047] In an optional embodiment, the method may further include the following steps: During the execution of a mission, if two aircraft that have clashed are detected to have a path conflict again, the number of times the two aircraft have clashed is counted. Determine whether the number of conflicts is greater than or equal to the preset number of conflicts. If it is determined that it is greater than or equal to the preset number of conflicts, for any historical path conflict, calculate the conflict similarity between the historical path conflict and the current path conflict based on the flight conflict parameters of the historical path conflict and the flight conflict parameters of the current path conflict. Based on the similarity of each conflict, the flight avoidance parameters of the aircraft being avoided are corrected to obtain the corrected flight avoidance parameters.

[0048] In this optional embodiment, the preset number of conflicts can be fixed, such as 2 times, or it can be determined based on the length of the global flight planning path, in which case the preset number of conflicts is positively correlated with the length. The types of flight conflict parameters for both historical path conflicts and current path conflicts include, but are not limited to, the 3D grid cell where the conflict occurred, flight speed, and flight conflict type. Each type of flight conflict parameter has a corresponding conflict weight; for example, the conflict weights for 3D grid cell, flight speed, and conflict type are 0.4, 0.3, and 0.3, respectively. The more similar the flight conflict parameters, the higher the resulting conflict similarity.

[0049] As can be seen, implementing this optional embodiment, for two aircraft that repeatedly experience flight conflicts, first counts the number of conflicts. Once a preset value is reached, it calculates the similarity between the current conflict and historical conflicts based on parameters such as three-dimensional grid cells, flight speed, and flight conflict type, as well as corresponding weights. Finally, it combines the conflict similarity to correct the flight avoidance parameters, thereby improving the accuracy and reliability of the analysis of the flight avoidance parameters and further improving the accuracy and reliability of the avoidance operation. This reduces the probability of subsequent path conflicts and is conducive to further improving the accuracy and safety of multi-aircraft collaborative operations, and reducing the efficiency loss caused by repeated conflicts.

[0050] In this embodiment of the invention, optionally, based on preset flight path parameters, the target flight planning path of each aircraft is converted into a continuous-time flight trajectory, including: For any aircraft, the flight plan path of the aircraft is converted into a continuous time trajectory, and a time parameterization operation is performed on the continuous time trajectory of the aircraft to obtain the position parameters at each time point on the continuous time trajectory of the aircraft; based on the position parameters at each time point and the preset flight path parameters, a velocity planning operation is performed on the position parameters at each time point to obtain the continuous time flight trajectory of the aircraft.

[0051] In this embodiment of the invention, for any aircraft, the discrete flight nodes of the flight planning path are transformed into a continuous time trajectory. Based on its initial position, initial flight speed, the time sequence corresponding to each discrete flight node in the continuous time trajectory, and initial acceleration, and combined with the formula s(t)=s0+v0×t+0.5×a×t², a time parameterization operation is performed on the continuous time trajectory to obtain the position parameters (i.e., time sequence) for each time point on the aircraft's continuous time trajectory, such as the flight reference position at each time point. Here, s(t), s0, v0, t, and a represent the position parameter, initial position, initial speed, time point, and initial acceleration at each time point, respectively. Combined with preset flight path parameters (such as preset flight path curvature), a velocity planning operation is performed on the position parameters at each time point to obtain the aircraft's continuous time flight trajectory. For example, the speed is 2.0 m / s on a straight section, and the speed decreases to 1.5 m / s on a small curve section, with the acceleration always less than or equal to 5 m / s², and no sudden acceleration / deceleration.

[0052] As can be seen, the embodiments of the present invention can first convert the aircraft flight planning path into a continuous time trajectory, then perform time parameterization on it to obtain the position parameters at each time point on the trajectory, and then combine the position parameters with the preset flight path parameters to perform velocity planning at each time point, finally forming a continuous time flight trajectory. This realizes the accurate mapping of the flight trajectory from a discrete path to a continuous spatiotemporal trajectory, improves the smoothness and temporal consistency of the flight planning path, and helps to reduce the occurrence of flight planning path jumps or velocity abrupt changes, thereby further improving the stability and accuracy of flight control, and thus improving the safety and accuracy of flight operations.

[0053] In this embodiment of the invention, optionally, based on the real-time flight parameter error of each aircraft, attitude control operations are performed on the aircraft during the continued execution of the mission, including: For any aircraft, based on the real-time flight parameter error of the aircraft, analyze the desired attitude angle and total thrust requirement parameters that match the aircraft; perform attitude calculation and thrust allocation on the desired attitude angle and total thrust requirement parameters of the aircraft respectively to obtain the flight attitude parameters of the aircraft and the target rotation speed of each rotor; based on the flight attitude parameters of the aircraft and the target rotation speed of each rotor, perform attitude control operations on the aircraft during the continued execution of the mission.

[0054] In this embodiment of the invention, real-time error control is achieved through outer-loop PID (Proportional-Integral-Derivative) position control and inner-loop PID speed control of the aircraft. For example, in the outer-loop PID position control, Kp_pos=0.8, Ki_pos=0.15, Kd_pos=0.2; in the inner-loop PID speed control, Kp_vel=0.6, Ki_vel=0.1, Kd_vel=0.05. The desired attitude angle and total thrust requirement parameters of the real-time flight parameter error are output. Attitude calculation is performed on the desired attitude angle of the aircraft to obtain the desired torque corresponding to the desired attitude angle, i.e., the flight attitude parameters. Thrust is allocated according to the desired torque and total thrust requirement parameters to obtain the thrust of each rotor of the aircraft. The target rotational speed of each rotor is determined based on the thrust of each rotor. Specifically, the desired attitude angle includes the desired pitch angle, desired roll angle, and desired yaw angle, and their calculation formulas are as follows: θ_c=Kp_θ×e_θ+Ki_θ×∫e_θdt+Kd_θ× _θ; φ_c=Kp_φ×e_φ+Ki_φ×∫e_φdt+Kd_φ× _φ; ψ_c=Kp_ψ×e_ψ+Ki_ψ×∫e_ψdt+Kd_ψ× _ψ; In the formula, θ_c, Kp_θ, e_θ, Ki_θ, ∫e_θdt, Kd_θ, _θ represents the desired pitch angle, pitch angle proportional control gain, pitch angle error, pitch angle integral control gain, integral term of pitch angle error, differential term of pitch angle control gain, and differential term of pitch angle error, respectively; φ_c, Kp_φ, e_φ, Ki_φ, ∫e_φdt, Kd_φ, _φ represents the desired roll angle, roll angle proportional control gain, roll angle error, roll angle integral control gain, integral term of roll angle error, differential term of roll angle control gain, and differential term of roll angle error, respectively; ψ_c, Kp_ψ, e_ψ, Ki_ψ, ∫e_ψdt, Kd_ψ, _ψ represents the desired yaw angle, yaw angle proportional control gain, yaw angle error, yaw angle integral control gain, integral term of yaw angle error, yaw angle derivative control gain, and derivative term of yaw angle error, respectively.

[0055] In this embodiment of the invention, the thrust distribution and target rotational speed of each rotor are illustrated using a four-rotor aircraft as an example. The target rotational speed of each rotor is calculated using the following formula: Fi=C T ×ρ×ωi 2 ×R4 ; F1=F / 4+M_roll / (w×l)+M_pitch / (w×L); F2=F / 4-M_roll / (w×l)+M_pitch / (w×L); F3=F / 4+M_roll / (w×l)-M_pitch / (w×L); F4=F / 4-M_roll / (w×l)-M_pitch / (w×L).

[0056] Where i takes values ​​from 1 to 4, corresponding to 4 rotors; Fi is the thrust of the i-th rotor; ωi is the target rotational speed of the i-th rotor; C T ρ and R are the thrust coefficient (e.g., 0.01~0.02), air density, and rotor radius, respectively; F1, F2, F3, and F4 are the thrust of the four rotors, respectively; F is the total thrust requirement parameter; M_roll and M_pitch are the desired roll moment and desired pitch moment, respectively; w is the control coefficient, such as 2; L is the distance from the rotor center to the center of the aircraft fuselage, i.e., the lever arm length.

[0057] In this embodiment of the invention, during the execution of the mission, full-process fault detection and safety protection are performed. Specifically, the following measures are taken: real-time detection of whether sensor data is abnormal, such as sudden interruption of lidar data or visual positioning deviation; monitoring of the communication link between the aircraft and the ground station and between the aircraft; monitoring of the rotational speed and rotational speed deviation of each rotor; real-time collection of remaining battery power; monitoring of flight altitude, flight speed, flight distance (such as the minimum distance to the rack or obstacles), and flight attitude angle; if a fault occurs, the flight parameters are adjusted according to the fault situation; otherwise, the aircraft is controlled to fly normally according to the original flight plan trajectory.

[0058] As can be seen, the embodiments of the present invention can also match the desired attitude angle and total thrust requirement based on the real-time flight parameter error of the aircraft, and transform the abstract control requirements into specific flight attitude parameters and rotor speed through attitude calculation and thrust allocation, and perform attitude control based on the transformed flight attitude parameters, that is, rotor control based on the transformed rotor speed, which improves the accuracy of the correction of the aircraft's flight deviation, thereby increasing the probability of its stable flight along the planned path and reducing the risk of collision caused by attitude deviation. At the same time, it improves the accuracy and response efficiency of flight control, and further improves the stability and safety of the aircraft in the orderly conduct of flight collaborative operations in the current operation scenario.

[0059] In another alternative embodiment, the method may further include the following steps: During the flight avoidance operation, the control aircraft broadcasts its current flight parameters to other aircraft. Control other aircraft to receive the current flight parameters of the avoidance aircraft, determine the avoidance status of the avoidance aircraft based on the current flight parameters of the avoidance aircraft, and broadcast flight avoidance instructions to the avoidance aircraft based on the avoidance status of the avoidance aircraft; The control and avoidance aircraft receives flight avoidance instructions and, upon receiving such instructions, sends avoidance confirmation signals to other aircraft and ground stations.

[0060] In this embodiment of the invention, during mission execution, each aircraft broadcasts its real-time flight parameters, such as real-time flight position, real-time flight speed, real-time flight trajectory, and real-time flight altitude. During the avoidance process, the aircraft updates its own real-time flight parameters and broadcasts them to other aircraft. Other aircraft, upon receiving the real-time flight parameters from the avoidance aircraft, confirm the avoidance status and send a flight avoidance command back to the avoidance aircraft. Upon receiving the flight avoidance command, the avoidance aircraft sends a avoidance confirmation signal to the ground station and other aircraft. After completing the avoidance operation, it sends an avoidance completion signal to other aircraft and the ground station, while simultaneously connecting with its original global flight planning path.

[0061] As can be seen, implementing this optional embodiment, during the avoidance process, involves the aircraft needing to avoid the obstacle broadcasting real-time flight parameters to other aircraft that do not need to avoid the obstacle. This enables command interaction and signal feedback with other aircraft, establishing a real-time communication and coordination system between multiple aircraft and the ground station. This allows other aircraft and the ground station to accurately know the avoidance status of the aircraft, reducing the occurrence of further flight conflicts caused by information gaps and further improving the accuracy of flight avoidance operations, thereby enhancing the safety of multi-task coordinated execution. Furthermore, by having other aircraft provide targeted feedback on avoidance commands, the ground station simultaneously receives confirmation and completion signals, improving the accuracy of global monitoring and scheduling of the avoidance process. After the avoidance is completed, it seamlessly connects with the original global flight planning path, reducing operational interruptions and improving the response efficiency and coordination of multi-aircraft mission collaboration, further reducing the risk of flight conflicts in the current operational scenario.

[0062] Example 2 Please see Figure 2 , Figure 2 This is a flowchart illustrating another method for controlling intelligent air dispatching disclosed in an embodiment of the present invention. Figure 2 The described method can be applied to multi-task operation scenarios, such as logistics warehouse pickup and warehousing cargo transportation. In these scenarios, multiple aircraft operate, each performing a specific task. Figure 2As shown, the method may include the following operations: 201. Obtain the initial position and the target position to be traveled for each aircraft, and obtain the environmental parameters of the current operation scenario of all aircraft and the preset flight constraint parameters for all aircraft.

[0063] In this embodiment of the invention, the environmental parameters of the current operating scenario are related to the specific environmental type. For example, for a warehousing and transportation environment, the environmental parameters include, but are not limited to, spatial geometric parameters (used to determine flight boundaries) and facility layout parameters (used to delineate passable and no-fly zones). Furthermore, physical environmental parameters (which affect the performance of aircraft sensors and flight stability) may also be included. Spatial geometric parameters include, but are not limited to, basic dimensional constraints of the environmental space, such as warehouse length / width / height dimensions, aisle width, shelf height, aisle clearance height, flight altitude limits, and the three-dimensional coordinate range of each cargo area. Facility layout parameters include, but are not limited to, the three-dimensional distribution coordinates of shelves, column / beam positions, precise coordinates of cargo locations, charging pile / operating platform positions, no-fly zone areas (such as shelf columns and equipment areas), and the spatial boundaries of passable areas. Physical environmental parameters include, but are not limited to, warehouse temperature and humidity, air pressure, light intensity, airflow velocity, electromagnetic interference intensity, and ground / shelf reflectivity (affecting visual positioning). Preset flight constraint parameters are used to adapt to the rules for cooperation between warehousing operations and aircraft, including but not limited to the minimum safe flight distance between aircraft, the safe avoidance distance between shelves / obstacles and aircraft, and the time and space window restrictions for multi-aircraft operations.

[0064] 202. Based on the initial and target positions of all aircraft, the environmental parameters of the current operation scenario, and the preset flight constraint parameters for all aircraft, generate the initial flight planning path for each aircraft.

[0065] 203. Based on the initial flight planning path of each aircraft, determine whether there is a path conflict with other aircraft during the execution of the mission according to its own initial flight planning path; if it is determined that there is no path conflict, proceed to step 204; if it is determined that there is a path conflict, proceed to step 205.

[0066] 204. Determine the initial flight planning path of each aircraft as the global flight planning path for that aircraft.

[0067] In this embodiment of the invention, optionally, before determining the initial flight planning path or the adjusted flight planning path as the global flight planning path, the initial flight planning path or the flight planning path is analyzed by cubic spline interpolation using path nodes as interpolation points to obtain the corresponding continuous flight planning trajectory, eliminating right-angle turns between discrete nodes and ensuring the continuity of path curvature; then, the path curvature, speed change, and flight altitude corresponding to the aircraft flying on the continuous flight planning path are determined, and it is determined whether the path curvature is less than or equal to a preset turning curvature threshold, whether the speed change rate is less than or equal to a preset acceleration threshold, and whether the flight altitude is within the flight altitude limit range and does not exceed the limit. If so, the continuous flight planning path is smoothly fine-tuned, wherein the length of the fine-tuned continuous flight planning path is shorter than the path before fine-tuning, and finally, the fine-tuned path is determined as the global flight planning path. This method uses cubic spline interpolation to transform discrete paths into continuous smooth trajectories, eliminating right-angle turns, ensuring curvature continuity, and through constraint analysis, it can also shorten path length, reduce sudden acceleration / deceleration of the aircraft, and lower the aircraft's energy consumption. Furthermore, the output smooth path provides accurate and reliable data for subsequent hierarchical execution, thereby further improving the stability and efficiency of collaborative flight operations.

[0068] 205. Based on the initial flight planning paths of all aircraft, determine the target path conflict situation, and based on the target path conflict situation and the pre-determined mission urgency of each aircraft, perform adjustment operations on the initial flight planning paths of all aircraft to obtain the adjusted flight planning paths of all aircraft, and determine the adjusted flight planning path of each aircraft as the global flight planning path of that aircraft.

[0069] In this embodiment of the invention, optionally, the urgency of a mission can be analyzed through dimensions such as the mission urgency and remaining battery power of the aircraft. For example, the higher the mission urgency and / or the lower the remaining battery power, the higher the mission priority. In this case, the initial flight planning path of the aircraft is adjusted according to the target path conflict and mission priority. Alternatively, if the mission urgency is the same and the difference in remaining battery power between the aircraft is less than or equal to a preset battery power (e.g., 100 mAh), the mission priority is the same. In this case, the initial flight planning paths of each aircraft can be coordinated by a path offset method. There is no need for any one party to wait for the other to fly first. That is, the conflict position where the aircraft cause path conflict is determined, the aircraft that needs path adjustment is selected (e.g., randomly selected), and the position corresponding to the conflict position on the initial flight planning path of the aircraft is adjusted upward or downward based on the conflict position. The adjusted flight planning path is used as the global flight planning path of the aircraft, while the initial flight planning paths of other aircraft that do not need path adjustment remain unchanged and are used as the global flight planning paths of the other aircraft. For example, if aircraft A and B have a path conflict at grid cell G(10.0, 7.0, 2.5), and aircraft A's task priority is lower than aircraft B's, then aircraft A will wait for aircraft B to pass through grid cell G(10.0, 7.0, 2.5) first. This means adjusting the elapsed time corresponding to grid cell G(10.0, 7.0, 2.5) on aircraft A's initial flight planning path so that the adjusted elapsed time is later than the original elapsed time. This adjusted flight planning path will be used as aircraft A's global flight planning path, while aircraft B's initial flight planning path will be used as its global flight planning path. If aircraft A and B have the same task priority, then... Aircraft B adjusts its path by moving upwards by 0.5m from the first three grid cells of grid cell G(10.0,7.0,2.5) on its initial flight path, avoiding grid cell G(10.0,7.0,2.5). The resulting grid cells are M18(9.5,7.0,3.0)→M19(10.0,7.0,3.0)→M20(10.5,7.0,3.0). The remaining grid cells of its initial flight path remain unchanged, resulting in a new global flight path for aircraft B. The initial flight path of aircraft A is then determined as its global flight path. Neither aircraft A nor B needs to wait for the other to proceed. It should be noted that for situations with different mission priorities, a path offset method can also be used to coordinate the initial flight paths of each aircraft; however, in this case, the aircraft whose path is adjusted will be the one with the lower mission priority.

[0070] 206. Control each aircraft to perform its mission based on its global flight planning path.

[0071] 207. Collect the first real-time flight data of each aircraft during the mission, and based on the first real-time flight data of each aircraft, predict the target flight trajectory of each aircraft within the next preset time period; when it is determined that there is a flight path conflict based on the target flight trajectory of each aircraft, control all aircraft to perform flight avoidance operations based on the target flight trajectory of each aircraft.

[0072] 208. After the flight conflict avoidance is detected to be resolved, the target flight planning path of each aircraft after the flight conflict avoidance is resolved is obtained, and based on the preset flight path parameters, the target flight planning path of each aircraft is converted into a continuous time flight trajectory, and the aircraft is controlled to continue to perform the mission based on the continuous time flight trajectory of each aircraft.

[0073] 209. Collect the second real-time flight data of each aircraft during the continued execution of the mission, and perform flight error analysis on the second real-time flight data of each aircraft and the continuous time flight trajectory of the aircraft to obtain the real-time flight parameter error. Based on the real-time flight parameter error of each aircraft, perform attitude control operations on the aircraft during the continued execution of the mission.

[0074] It should be noted that for other related descriptions of steps 206-209, please refer to the detailed description of steps 101-104 in Embodiment 1, which will not be repeated here.

[0075] It is evident that implementation Figure 2The described method defines the initial global operational trajectory for each aircraft through global flight planning, ensuring the orderly execution of multiple tasks in parallel and improving the overall operational efficiency of multiple tasks. Based on real-time flight data, it predicts subsequent flight trajectories, anticipating path conflicts and flexibly correcting the global operational trajectory in a timely manner to perform avoidance operations, thus mitigating the risk of aircraft collisions in the current operational scenario (such as within a warehouse space) and improving the safety of collaborative operations. Furthermore, after a conflict is resolved, the newly planned path is converted into a continuous-time flight trajectory, ensuring the accurate execution of all flight control commands, improving the smoothness and accuracy of aircraft flight trajectory connections, and reducing interruptions in multi-task operations. Simultaneously, through error analysis of real-time flight data and continuous trajectories, targeted attitude control is performed on the aircraft, precisely correcting flight deviations and ensuring the accuracy of aircraft flight in the current operational scenario. This further improves the stability and accuracy of multi-aircraft collaborative operations, thereby comprehensively enhancing the efficiency, accuracy, and safety of aircraft collaborative operations in the current multi-task scenario. Furthermore, it can generate corresponding initial flight planning paths based on the aircraft's initial position, the required destination, environmental parameters, and flight constraint parameters. This ensures that the path planning aligns with the actual operational environment from the outset, improving the feasibility and adaptability of the flight planning paths. By detecting conflicts between initial flight planning paths in advance, potential path intersections can be avoided before the aircraft executes the mission, further reducing the impact of sudden conflicts on operations. In response to conflicts, the path can be adjusted based on mission urgency to determine the global flight planning path, achieving precise conflict resolution while also considering operational priorities, thus improving the efficiency of emergency missions. Each aircraft has its own dedicated conflict-free flight trajectory, improving the orderliness of multi-aircraft collaborative flight and enhancing the coordination and efficiency of parallel operations. At the same time, reducing the risk of flight collisions at the planning level further improves the safety of subsequent flight operations.

[0076] In this embodiment of the invention, optionally, an initial flight planning path for each aircraft is generated based on the initial and target positions of all aircraft, the environmental parameters of the current operational scenario, and preset flight constraint parameters for all aircraft, including: Based on the environmental parameters of the current work scenario, a 3D environment map of the current work scenario is generated. The 3D environment map of the current work scenario is composed of multiple 3D grid units with the same grid volume. Based on the initial and target positions of all aircraft, the 3D environment map of the current operation scenario, and the preset flight constraint parameters for all aircraft, a global environment information matrix for all aircraft is generated. Based on the global environmental information matrix, path planning parameters matching all aircraft are determined, and based on the 3D environmental map and path planning parameters, an initial flight planning path for each aircraft is generated. The initial flight planning path for each aircraft consists of a sequence of multiple 3D grid cells.

[0077] In this embodiment of the invention, optionally, path planning parameters matching all aircraft are determined based on the global environment information matrix. That is, the matching path planning algorithm is selected based on the complexity of the current operation scenario. For example, for a warehouse three-dimensional narrow space scenario, the Hybrid A-star algorithm is selected, which takes into account both path search efficiency and aircraft dynamic constraints (such as turning radius and acceleration limits).

[0078] In this embodiment of the invention, an initial flight planning path for each aircraft is generated based on a 3D environment map and path planning parameters. Specifically, for any aircraft, a single 3D grid cell is used as the search unit, and a hybrid A* algorithm is used to generate a corresponding initial flight planning path for each aircraft. The initial flight planning path is a sequence of discrete grid cells (nodes). For example, the initial flight planning path for aircraft A is: initial position (5.0, 3.0, 2.0) → N1 (5.5, 3.0, 2.0) → N2 (6.0, 3.0, 2.0) → … → N26 (18.0, 12.0, 4.0) (a total of 27 nodes, traveling straight along the aisle with elevation gain, no detours). During the algorithm's search process, no-fly zones on the rack pillars are automatically avoided, satisfying the turning radius constraint.

[0079] As can be seen, implementing the embodiments of the present invention can also generate a corresponding global environment information matrix by first establishing a three-dimensional environment map consistent with the actual scene, and then combining the initial position, the required destination and flight constraint parameters of each aircraft, and selecting the path planning algorithm that matches the environment, thereby calculating the initial flight planning path that matches each aircraft, improving the accuracy and reliability of the analysis of the initial flight planning path of the aircraft, which is conducive to improving the parallel and orderly execution of multiple tasks by each aircraft.

[0080] In this embodiment of the invention, optionally, based on the initial flight planning path of each aircraft, determining whether there is a path conflict with other aircraft during the execution of the mission according to their own initial flight planning path includes: Based on the preset flight time window and grid volume (i.e., the size of a single 3D grid cell), a time-object occupancy table is set for each 3D grid cell in the 3D environment map of the current operation scene; Based on the time-object occupancy table, predict the flight time sequence required for each aircraft to fly from its initial position to the corresponding target position according to the aircraft's initial flight planning path. The aircraft's flight time sequence consists of the sub-time sequence of each three-dimensional grid cell corresponding to the aircraft's initial flight planning path. Based on the flight time sequence and initial flight planning path of each aircraft, analyze the target three-dimensional grid cells in the three-dimensional environment map of the current operation scenario during the mission execution process, determine the target time of each target aircraft passing through the target three-dimensional grid cell, and calculate the time difference between the target times of all target aircraft. When it is determined that the elapsed time difference corresponding to the target 3D grid cell is less than or equal to the preset elapsed time difference, it is determined that there is a path conflict with other aircraft during the execution of the mission according to the initial flight planning path of all aircraft; when it is determined that the elapsed time difference corresponding to the target 3D grid cell is greater than the preset elapsed time difference, it is determined that there is no path conflict with other aircraft during the execution of the mission according to the initial flight planning path of all aircraft.

[0081] In this embodiment of the invention, optionally, the preset flight time window can be determined according to the complexity of the current operation scenario. For example, the more complex the environment, the smaller the time window. A time-object occupancy table is set for each three-dimensional grid cell in the three-dimensional environment map with a grid volume of 1 second and 0.5 m³. The estimated elapsed time (e.g., calculated based on an average speed of 2 m / s) corresponding to each path node (i.e., a single grid cell in the three-dimensional environment map) on the initial flight planning path of each aircraft is calculated to obtain the flight time sequence required for each aircraft to fly from its initial position to the corresponding target position. The flight time sequence and initial flight planning path of each aircraft are analyzed to obtain... If aircraft A passes through grid G(10.0,7.0,2.5) at t=12 seconds, and aircraft B also passes through the same grid G(10.0,7.0,2.5) at t=11 seconds, and their paths intersect at this grid, and the time difference between their passages is 1 second (greater than or equal to the preset time difference of 1 second), then it is determined to be an edge conflict, i.e., a cross-path conflict. The path intersection point G(10.0,7.0,2.5) is determined, and the time window is [11s,12s]. If the calculated conflict probability of the two aircraft arriving at the intersection point at the same time is 95%, which is greater than the preset conflict probability of 70%, then there is a path conflict between the two aircraft; otherwise, there is no path conflict.

[0082] As can be seen, implementing the embodiments of the present invention can also refine the spatiotemporal dimension of the current operation scenario by setting a time-object occupancy table for the grid cells of the 3D environment map and combining it with the flight time window. This upgrades path conflict detection from a simple spatial judgment to a dual spatiotemporal judgment, making the conflict detection dimension more comprehensive and further improving the accuracy and reliability of judging whether there are flight conflicts in the initial flight planning paths of each aircraft. Furthermore, based on the decomposition of flight time series by grid cells, it can accurately locate the target 3D grid cells that multiple aircraft pass through together and calculate the time difference of each aircraft's passage, further improving the accuracy of flight conflict identification and location. This provides accurate conflict information for subsequent path adjustments and reduces the risk of multi-aircraft collisions from the planning source.

[0083] Example 3 Please see Figure 3 , Figure 3 This is a schematic diagram of the structure of a processing device for controlling intelligent air dispatching disclosed in an embodiment of the present invention. Figure 3 The described device can be applied to multi-task operation scenarios, such as logistics warehouse pickup and warehousing cargo transportation. In these scenarios, multiple aircraft are involved, each performing a specific task. Figure 3 As shown, the device may include: a control module 301 for controlling each aircraft to perform a task based on its global flight planning path, wherein the global flight planning path of each aircraft is the flight path planned for the aircraft from its initial position to the target position to be reached.

[0084] The acquisition module 302 is used to acquire the first real-time flight data of each aircraft during the execution of its mission.

[0085] The prediction module 303 is used to predict the target flight trajectory of each aircraft within a preset time period based on the first real-time flight data of each aircraft.

[0086] The control module 301 is also used to control all aircraft to perform flight avoidance operations based on the target flight trajectory of each aircraft when it is determined that there is a flight path conflict.

[0087] The acquisition module 302 is also used to acquire the target flight planning path of each aircraft after the flight conflict avoidance is lifted.

[0088] The analysis module 304 is used to convert the target flight planning path of each aircraft into a continuous time flight trajectory based on preset flight path parameters, and to control the aircraft to continue to perform the mission based on the continuous time flight trajectory of each aircraft.

[0089] The acquisition module 302 is also used to acquire second real-time flight data of each aircraft as it continues to perform its mission.

[0090] The analysis module 304 is also used to perform flight error analysis on the second real-time flight data of each aircraft and the continuous time flight trajectory of the aircraft to obtain the real-time flight parameter error.

[0091] The control module 301 is also used to perform attitude control operations on the aircraft during the continued execution of the mission based on the real-time flight parameter error of each aircraft.

[0092] It is evident that implementation Figure 3 The described device defines initial global operational trajectories for each aircraft through global flight planning, ensuring the orderly execution of multiple tasks in parallel and improving the overall operational efficiency of multiple tasks. Based on real-time flight data, it predicts subsequent flight trajectories, anticipates path conflicts, and flexibly corrects the global operational trajectory in a timely manner to perform avoidance operations, mitigating the risk of aircraft collisions in the current operational scenario (such as within a warehouse space) from the source, thus improving the safety of collaborative operations. After a conflict is resolved, the newly planned path is converted into a continuous-time flight trajectory, ensuring that all flight control commands are executed accurately, improving the smoothness and accuracy of aircraft flight trajectory connections, and reducing interruptions in multi-task operations. Simultaneously, through error analysis of real-time flight data and continuous trajectories, targeted attitude control is performed on the aircraft, precisely correcting flight deviations and ensuring the accuracy of aircraft flight in the current operational scenario, further improving the stability and accuracy of multi-aircraft collaborative operations. Ultimately, this comprehensively improves the efficiency, accuracy, and safety of aircraft collaborative operations in current multi-task scenarios.

[0093] In an optional embodiment, such as Figure 3 As shown, the acquisition module 302 is also used to acquire the initial position and the target position to be reached for each aircraft, and to acquire the environmental parameters of the current operating scenario for all aircraft and the preset flight constraint parameters for all aircraft; such as Figure 4 As shown, the device may also include: a generation module 305, used to generate an initial flight planning path for each aircraft based on the initial and target positions of all aircraft, environmental parameters of the current operating scenario, and preset flight constraint parameters for all aircraft.

[0094] The prediction module 303 is also used to determine, based on the initial flight planning path of each aircraft, whether there is a path conflict with other aircraft during the execution of the mission according to its own initial flight planning path.

[0095] The determination module 306 is used to determine the initial flight planning path of each aircraft as the global flight planning path of the aircraft when it is determined that there is no path conflict.

[0096] The determination module 306 is also used to determine the target path conflict situation based on the initial flight planning paths of all aircraft when a path conflict is detected.

[0097] The adjustment module 307 is used to adjust the initial flight planning paths of all aircraft based on the target path conflict situation and the pre-determined mission urgency of each aircraft, so as to obtain the adjusted flight planning paths of all aircraft.

[0098] The determination module 306 is also used to determine the adjusted flight planning path of each aircraft as the global flight planning path of that aircraft.

[0099] As can be seen, implementing this optional embodiment generates a corresponding initial flight planning path by using the aircraft's initial position, the desired destination, environmental parameters, and flight constraint parameters. This ensures that the path planning aligns with the actual operational environment from the outset, improving the feasibility and adaptability of the flight planning path. Furthermore, by detecting conflicts between initial flight planning paths in advance, potential path intersections can be avoided before the aircraft executes the mission, further reducing the impact of sudden conflicts during flight on operations. In response to conflicts, the path is adjusted based on the mission urgency to determine the global flight planning path, achieving precise conflict resolution while also considering operational priorities, thus improving the efficiency of emergency missions. Moreover, each aircraft has its own dedicated conflict-free flight trajectory, improving the orderliness of multi-aircraft collaborative flight and enhancing the coordination and efficiency of parallel operations. Simultaneously, reducing the risk of flight collisions at the planning level further improves the safety of subsequent flight operations.

[0100] In this optional embodiment, such as Figure 4 As shown, the generation module 305 generates the initial flight planning path for each aircraft in a specific way based on the initial and target positions of all aircraft, the environmental parameters of the current operating scenario, and the preset flight constraint parameters for all aircraft. This includes: Based on the environmental parameters of the current work scenario, a 3D environment map of the current work scenario is generated. The 3D environment map of the current work scenario is composed of multiple 3D grid units with the same grid volume. Based on the initial and target positions of all aircraft, the 3D environment map of the current operation scenario, and the preset flight constraint parameters for all aircraft, a global environment information matrix for all aircraft is generated. Based on the global environmental information matrix, path planning parameters matching all aircraft are determined, and based on the 3D environmental map and path planning parameters, an initial flight planning path for each aircraft is generated. The initial flight planning path for each aircraft consists of a sequence of multiple 3D grid cells.

[0101] As can be seen, implementing this optional embodiment can also generate a corresponding global environmental information matrix by first establishing a three-dimensional environmental map consistent with the actual scene, and then combining the initial position, the required destination, and flight constraint parameters of each aircraft. It can also select a path planning algorithm that is compatible with the environment, thereby calculating an initial flight planning path that matches each aircraft. This improves the accuracy and reliability of the analysis of the initial flight planning path of the aircraft, which is conducive to improving the parallel and orderly execution of multiple tasks by each aircraft.

[0102] In this optional embodiment, such as Figure 4 As shown, the prediction module 303 determines, based on the initial flight planning path of each aircraft, whether there are path conflicts with other aircraft during the execution of the mission according to their own initial flight planning paths, in the following specific ways: Based on the preset flight time window and grid volume, a time-object occupancy table is set for each 3D grid cell in the 3D environment map of the current operation scene; Based on the time-object occupancy table, predict the flight time sequence required for each aircraft to fly from its initial position to the corresponding target position according to the aircraft's initial flight planning path. The aircraft's flight time sequence consists of the sub-time sequence of each three-dimensional grid cell corresponding to the aircraft's initial flight planning path. Based on the flight time sequence and initial flight planning path of each aircraft, analyze the target three-dimensional grid cells in the three-dimensional environment map of the current operation scenario during the mission execution process, determine the target time of each target aircraft passing through the target three-dimensional grid cell, and calculate the time difference between the target times of all target aircraft. When it is determined that the elapsed time difference corresponding to the target 3D grid cell is less than or equal to the preset elapsed time difference, it is determined that there is a path conflict with other aircraft during the execution of the mission according to the initial flight planning path of all aircraft; when it is determined that the elapsed time difference corresponding to the target 3D grid cell is greater than the preset elapsed time difference, it is determined that there is no path conflict with other aircraft during the execution of the mission according to the initial flight planning path of all aircraft.

[0103] As can be seen, implementing this optional embodiment can also refine the spatiotemporal dimension of the current operation scenario by setting a time-object occupancy table for the grid cells of the 3D environment map and combining it with the flight time window. This upgrades path conflict detection from a simple spatial judgment to a dual spatiotemporal judgment, making the conflict detection dimension more comprehensive and further improving the accuracy and reliability of judging whether there are flight conflicts in the initial flight planning paths of each aircraft. Furthermore, based on the decomposition of flight time series by grid cells, it can accurately locate the target 3D grid cells that multiple aircraft pass through together and calculate the time difference of each aircraft's passage, further improving the accuracy of flight conflict identification and location. This provides accurate conflict information for subsequent path adjustments and reduces the risk of multi-aircraft collisions from the planning source.

[0104] In this optional embodiment, such as Figure 3 Or such as Figure 4 As shown, the prediction module 303 predicts the target flight trajectory of each aircraft within a preset time period based on the first real-time flight data of each aircraft, including: The first real-time flight data of all aircraft are fused and analyzed to obtain the real-time flight parameters of each aircraft. Based on the real-time flight parameters of each aircraft, the target flight trajectory of each aircraft in the next preset time period is predicted. The control module 301 controls the specific methods by which all aircraft perform flight avoidance operations based on the target flight trajectory of each aircraft, including: Based on the target flight trajectory of each aircraft, analyze the characteristics of flight conflicts, and based on the characteristics of flight conflicts and the target flight trajectory of each aircraft, determine the type of flight conflict that matches the characteristics of flight conflicts. Obtain the current status parameters of each aircraft, analyze the mission priority of each aircraft based on the current status parameters of each aircraft, and determine the flight avoidance strategy for all aircraft based on the mission priority of each aircraft. Based on the flight avoidance strategy, flight conflict type, and mission priority of each aircraft, the flight avoidance parameters of the aircraft that need to perform avoidance are generated, and the mission priority of the aircraft that need to perform avoidance is lower than the mission priority of other aircraft. Based on the flight avoidance parameters of the avoidance vehicle and the target flight trajectories of all vehicles that do not need to be avoided, the avoidance vehicle is controlled to perform flight avoidance operations.

[0105] As can be seen, implementing this optional embodiment improves the accuracy and reliability of flight parameter analysis by fusing and analyzing real-time flight data of each aircraft during mission execution. This allows for the prediction of short-term flight trajectories and the anticipation of flight conflicts. When a flight conflict occurs, the characteristics of the conflict are analyzed to match the corresponding conflict type. Combined with the current state parameters of the aircraft, the mission priority of each aircraft is determined, improving the matching between avoidance strategies and actual conflict scenarios. Furthermore, by having lower-priority aircraft avoid the conflict while taking into account the original planned paths of higher-priority aircraft, refined dynamic avoidance control is achieved. This is beneficial for improving the efficiency and accuracy of flight conflict elimination, further reducing the risk of flight collisions among multi-mission aircraft, and improving the accuracy and safety of multi-mission collaborative operations.

[0106] In another alternative embodiment, such as Figure 3 Or such as Figure 4 As shown, the control module 301 is also used to control the avoidant aircraft to broadcast its current flight parameters to other aircraft during the flight avoidance operation; control other aircraft to receive the current flight parameters of the avoidant aircraft, determine the avoidance status of the avoidant aircraft based on the current flight parameters of the avoidant aircraft, and broadcast flight avoidance instructions to the avoidant aircraft based on the avoidance status of the avoidant aircraft; control the avoidant aircraft to receive the flight avoidance instructions, and after receiving the flight avoidance instructions, control the avoidant aircraft to send avoidance confirmation signals to other aircraft and ground stations.

[0107] As can be seen, implementing this optional embodiment, during the avoidance process, involves the aircraft needing to avoid the obstacle broadcasting real-time flight parameters to other aircraft that do not need to avoid the obstacle. This facilitates command interaction and signal feedback with other aircraft, establishing a real-time communication and coordination system between multiple aircraft and the ground station. This allows other aircraft and the ground station to accurately know the avoidance status of the aircraft, reducing the occurrence of further flight conflicts caused by information gaps and further improving the accuracy of the avoidance operation, thereby enhancing the safety of multi-task coordinated execution. Furthermore, by having other aircraft provide targeted avoidance commands, the ground station simultaneously receives confirmation and completion signals, improving the accuracy of global monitoring and scheduling of the avoidance process. After the avoidance is completed, it seamlessly connects with the original global flight planning path, reducing operational interruptions and improving the response efficiency and coordination of multi-aircraft task collaboration, further reducing the risk of flight conflicts in the current operational scenario.

[0108] In yet another alternative embodiment, such as Figure 3 Or such as Figure 4 As shown, the analysis module 304, based on preset flight path parameters, converts the target flight planning path of each aircraft into a continuous-time flight trajectory in the following specific ways: For any aircraft, the flight plan path of the aircraft is converted into a continuous time trajectory, and a time parameterization operation is performed on the continuous time trajectory of the aircraft to obtain the position parameters at each time point on the continuous time trajectory of the aircraft; based on the position parameters at each time point and the preset flight path parameters, a velocity planning operation is performed on the position parameters at each time point to obtain the continuous time flight trajectory of the aircraft. Furthermore, the control module 301, based on the real-time flight parameter errors of each aircraft, specifies the manner in which it performs attitude control operations on the aircraft during the continued execution of the mission, including: For any aircraft, based on the real-time flight parameter error of the aircraft, analyze the desired attitude angle and total thrust requirement parameters that match the aircraft; perform attitude calculation and thrust allocation on the desired attitude angle and total thrust requirement parameters of the aircraft respectively to obtain the flight attitude parameters of the aircraft and the target rotation speed of each rotor; based on the flight attitude parameters of the aircraft and the target rotation speed of each rotor, perform attitude control operations on the aircraft during the continued execution of the mission.

[0109] As can be seen, implementing this optional embodiment can first convert the aircraft's flight planning path into a continuous time trajectory, then parameterize it in time to obtain the position parameters at each time point on the trajectory. Subsequently, combining the position parameters with preset flight path parameters, velocity planning is performed at each time point, ultimately forming a continuous time flight trajectory. This achieves a precise mapping of the flight trajectory from a discrete path to a continuous spatiotemporal trajectory, improving the smoothness and temporal consistency of the flight planning path. This helps reduce jumps or sudden changes in velocity during flight planning, thereby further improving the stability and accuracy of flight control, and ultimately enhancing the safety and accuracy of flight operations. Furthermore, based on the real-time flight parameter errors of the aircraft, the desired attitude angle and total thrust requirements are matched. Through attitude calculation and thrust allocation, abstract control requirements are transformed into specific flight attitude parameters and rotor speeds. Attitude control is then performed based on the transformed flight attitude parameters, i.e., rotor control is performed based on the transformed rotor speeds. This improves the accuracy of correcting aircraft flight deviations, thereby increasing the probability of stable flight along the planned path and reducing the risk of collisions caused by attitude deviations. At the same time, it improves the accuracy and response efficiency of flight control, further enhancing the stability and safety of the aircraft in the current operational scenario for orderly collaborative flight operations.

[0110] Example 4 Please see Figure 5 , Figure 5 This is a schematic diagram of the structure of another processing device for controlling intelligent air dispatching disclosed in an embodiment of the present invention. Figure 5The described device can be applied to multi-task operation scenarios, such as logistics warehouse pickup and warehousing cargo transportation. In these scenarios, multiple aircraft are involved, each performing a specific task. Figure 5 As shown, the device may include: Memory 401 storing executable program code; Processor 402 coupled to memory 401; The processor 402 calls the executable program code stored in the memory 401 to execute some or all of the steps in the processing method for controlling intelligent air dispatching disclosed in either Embodiment 1 or Embodiment 2 of the present invention, so as to perform dispatching operations on all aircraft.

[0111] Example 5 This invention discloses a computer storage medium storing computer instructions. When these computer instructions are invoked, they are used to execute some or all of the steps in any of the processing methods for intelligent air dispatching disclosed in Embodiment 1 or Embodiment 2 of this invention, so as to perform dispatching operations on all aircraft.

[0112] Example 6 This invention discloses a processing system for controlling intelligent airborne scheduling. This system is applied to multi-task operation scenarios, such as logistics cargo retrieval scenarios and warehouse cargo transportation scenarios. In these multi-task operation scenarios, multiple aircraft are involved, each performing a corresponding task. The system includes all aircraft and a control terminal. The control terminal executes some or all steps of the processing method for controlling intelligent airborne scheduling disclosed in either Embodiment 1 or Embodiment 2 of this invention to perform scheduling operations on all aircraft.

[0113] The apparatus and system embodiments described above are merely illustrative. The modules described as separate components may or may not be physically separate. The components shown as modules may or may not be physical modules; that is, they may be located in one place or distributed across multiple network modules. 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.

[0114] Through the detailed description of the above embodiments, those skilled in the art can clearly understand that each implementation method 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, including read-only memory (ROM), random access memory (RAM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), one-time programmable read-only memory (OTPROM), electrically-erasable programmable read-only memory (EEPROM), compact disc read-only memory (CD-ROM) or other optical disc storage, disk storage, magnetic tape storage, or any other computer-readable medium that can be used to carry or store data.

[0115] Finally, it should be noted that the above embodiments are merely preferred embodiments of the present invention and are only used to illustrate the technical solutions of the present invention, 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. Such 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. A processing method for controlling aerial intelligent scheduling, the method being applied to a multi-task operation scenario, a plurality of aircrafts being present in the multi-task operation scenario, each of the aircrafts being used to perform a corresponding task, and the method is characterized in that, The method includes: Control each of the aforementioned aircraft to perform the mission based on its global flight planning path, which is the planned flight path of the aircraft from its initial position to the target position to be reached; Collect first real-time flight data of each aircraft during the execution of the mission, and predict the target flight trajectory of each aircraft within the next preset time period based on the first real-time flight data of each aircraft; when it is determined that there is a flight path conflict according to the target flight trajectory of each aircraft, control all aircraft to perform flight avoidance operation according to the target flight trajectory of each aircraft. Once the flight conflict avoidance is detected to be resolved, the target flight planning path of each aircraft after the flight conflict avoidance is obtained, and based on the preset flight path parameters, the target flight planning path of each aircraft is converted into a continuous time flight trajectory, and the aircraft is controlled to continue to perform the mission based on the continuous time flight trajectory of each aircraft. The system collects second real-time flight data for each aircraft during the continued execution of its mission, performs flight error analysis on the second real-time flight data of each aircraft and the continuous time flight trajectory of the aircraft to obtain real-time flight parameter errors, and performs attitude control operations on the aircraft during the continued execution of its mission based on the real-time flight parameter errors of each aircraft. The method further includes: The initial position and the target position to be traveled for each of the aircraft are obtained, and the environmental parameters of the current operating scenario of all the aircraft and the preset flight constraint parameters for all the aircraft are obtained. Based on the initial and target positions of all the aircraft, the environmental parameters of the current operation scenario, and the preset flight constraint parameters for all the aircraft, an initial flight planning path is generated for each aircraft. Based on the initial flight planning path of each aircraft, it is determined whether there is a path conflict with other aircraft during the execution of the mission according to its own initial flight planning path; when it is determined that there is no path conflict, the initial flight planning path of each aircraft is determined as the global flight planning path of that aircraft. When a path conflict is detected, the target path conflict is determined based on the initial flight planning paths of all the aircraft. Based on the target path conflict and the pre-determined mission urgency of each aircraft, the initial flight planning paths of all the aircraft are adjusted to obtain the adjusted flight planning paths of all the aircraft. The adjusted flight planning path of each aircraft is then determined as the global flight planning path of that aircraft. The step of determining whether there are path conflicts with other aircraft during the execution of tasks according to the initial flight planning path of each aircraft includes: Based on the preset flight time window and grid volume, a time-object occupancy table is set for each three-dimensional grid cell in the three-dimensional environment map of the current operation scenario; Based on the time-object occupancy table, predict the flight time sequence required for each aircraft to fly from its initial position to the corresponding target position according to the aircraft's initial flight planning path. The flight time sequence of the aircraft is composed of the sub-time sequence of each three-dimensional grid cell corresponding to the aircraft's initial flight planning path. Based on the flight time sequence and initial flight planning path of each aircraft, the analysis is performed to determine the target three-dimensional grid cell that at least two aircraft pass through in the three-dimensional environment map of the current operation scenario during the mission execution, and the target time of each target aircraft passing through the target three-dimensional grid cell is determined, and the time difference between the target times of all the target aircraft is calculated. When it is determined that the elapsed time difference corresponding to the target three-dimensional grid unit is less than or equal to the preset elapsed time difference, it is determined that during the execution of the mission by all the aircraft according to their own initial flight planning paths, there is a path conflict with other aircraft; when it is determined that the elapsed time difference corresponding to the target three-dimensional grid unit is greater than the preset elapsed time difference, it is determined that during the execution of the mission by all the aircraft according to their own initial flight planning paths, there is no path conflict with other aircraft.

2. The method according to claim 1, characterized in that, The process of generating an initial flight planning path for each aircraft based on the initial and target positions of all the aircraft, the environmental parameters of the current operational scenario, and preset flight constraint parameters for all the aircraft includes: Based on the environmental parameters of the current work scenario, a three-dimensional environmental map of the current work scenario is generated. The three-dimensional environmental map of the current work scenario is composed of multiple three-dimensional grid units with the same grid volume. Based on the initial and target positions of all the aircraft, the three-dimensional environment map of the current operation scenario, and the preset flight constraint parameters for all the aircraft, a global environment information matrix for all the aircraft is generated. Based on the global environment information matrix, path planning parameters matching all the aircraft are determined, and based on the three-dimensional environment map and the path planning parameters, an initial flight planning path for each aircraft is generated. The initial flight planning path for each aircraft consists of a sequence of multiple three-dimensional grid cells.

3. The method according to claim 1 or 2, characterized in that, The method of predicting the target flight trajectory of each aircraft within a preset time period based on the first real-time flight data of each aircraft includes: The first real-time flight data of all the aircraft are fused and analyzed to obtain the real-time flight parameters of each aircraft, and based on the real-time flight parameters of each aircraft, the target flight trajectory of each aircraft in the next preset time period is predicted. The step of controlling all the aircraft to perform flight avoidance operations based on the target flight trajectory of each aircraft includes: Based on the target flight trajectory of each aircraft, analyze the flight conflict characteristics, and based on the flight conflict characteristics and the target flight trajectory of each aircraft, determine the flight conflict type that matches the flight conflict characteristics; The current state parameters of each of the aircraft are obtained, and the mission priority of each aircraft is analyzed based on the current state parameters of each aircraft. Based on the mission priority of each aircraft, a flight avoidance strategy for all the aircraft is determined. Based on the flight avoidance strategy, the flight conflict type, and the mission priority of each aircraft, flight avoidance parameters are generated for the aircraft that need to perform avoidance, wherein the mission priority of the aircraft that needs to perform avoidance is lower than the mission priority of the other aircraft. Based on the flight avoidance parameters of the avoidance aircraft and the target flight trajectories of all aircraft that do not need to be avoided, the avoidance aircraft is controlled to perform a flight avoidance operation.

4. The method according to claim 3, characterized in that, The method further includes: During the process of controlling the avoidant aircraft to perform a flight avoidance operation, the avoidant aircraft is controlled to broadcast its current flight parameters to the other aircraft; The system controls other aircraft to receive the current flight parameters of the avoidance aircraft, determine the avoidance status of the avoidance aircraft based on the current flight parameters of the avoidance aircraft, and broadcast flight avoidance instructions to the avoidance aircraft based on the avoidance status of the avoidance aircraft. The system controls the avoidance aircraft to receive the flight avoidance command, and after receiving the flight avoidance command, controls the avoidance aircraft to send avoidance confirmation signals to other aircraft and ground stations.

5. The method according to any one of claims 1, 2, and 4, characterized in that, The process of converting the target flight plan path of each aircraft into a continuous-time flight trajectory based on preset flight path parameters includes: For any of the aforementioned aircraft, the flight planning path of the aircraft is converted into a continuous time trajectory, and a time parameterization operation is performed on the continuous time trajectory of the aircraft to obtain the position parameters for each time point on the continuous time trajectory of the aircraft; based on the position parameters of each time point and the preset flight path parameters, a velocity planning operation is performed on the position parameters of each time point to obtain the continuous time flight trajectory of the aircraft. The step of controlling the attitude of each aircraft during its continued mission based on the real-time flight parameter error of each aircraft includes: For any of the aforementioned aircraft, based on the real-time flight parameter errors of the aircraft, analyze the desired attitude angle and total thrust requirement parameters that match the aircraft; perform attitude calculation and thrust allocation on the desired attitude angle and total thrust requirement parameters of the aircraft respectively to obtain the flight attitude parameters of the aircraft and the target rotation speed of each rotor; based on the flight attitude parameters of the aircraft and the target rotation speed of each rotor, perform attitude control operations on the aircraft during the continued execution of the mission.

6. A processing device for controlling intelligent airborne dispatching, the device being applied to a multi-task operation scenario, wherein multiple aircraft exist in the multi-task operation scenario, each aircraft being used to perform a corresponding task, characterized in that, The apparatus is used to implement the processing method for controlling intelligent air dispatch as described in any one of claims 1-5, the apparatus comprising: The control module is used to control each of the aircraft to perform tasks based on its global flight planning path, which is the flight path planned for the aircraft from its initial position to the target position it needs to go to. The data acquisition module is used to collect the first real-time flight data of each of the aforementioned aircraft during the execution of the mission; The prediction module is used to predict the target flight trajectory of each of the aircraft within a preset time period based on the first real-time flight data of each aircraft. The control module is also used to control all the aircraft to perform flight avoidance operations based on the target flight trajectory of each aircraft when it is determined that there is a flight path conflict. The acquisition module is also used to acquire the target flight planning path of each of the aircraft after the flight conflict avoidance is resolved, when the flight conflict avoidance is detected to be resolved. The analysis module is used to convert the target flight planning path of each aircraft into a continuous-time flight trajectory based on preset flight path parameters, and to control the aircraft to continue to perform the mission based on the continuous-time flight trajectory of each aircraft. The acquisition module is also used to acquire second real-time flight data of each of the aircraft during the continued execution of the mission; The analysis module is also used to perform flight error analysis on the second real-time flight data of each aircraft and the continuous time flight trajectory of the aircraft to obtain the real-time flight parameter error; The control module is also used to perform attitude control operations on each aircraft during the continued execution of its mission, based on the real-time flight parameter errors of each aircraft.

7. A processing device for controlling intelligent airborne dispatching, the device being applied to a multi-task operation scenario, wherein multiple aircraft exist in the multi-task operation scenario, each aircraft being used to perform a corresponding task, characterized in that, The device includes: Memory containing executable program code; A processor coupled to the memory; The processor calls the executable program code stored in the memory to execute the processing method for controlling intelligent air dispatch as described in any one of claims 1-5, so as to perform dispatch operations on all the aircraft.

8. A processing system for controlling intelligent airborne dispatching, the system being applied to a multi-task operation scenario, wherein multiple aircraft exist in the multi-task operation scenario, each aircraft being used to perform a corresponding task, characterized in that, The system includes all the said aircraft and a control terminal, the control terminal being used to execute the processing method for intelligent air dispatching as described in any one of claims 1-5, so as to perform dispatching operations on all the said aircraft.

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