Cooperative take-off and landing control system and method for unmanned vehicle and unmanned aerial vehicle

Abstract

The invention discloses a cooperative take-off and landing control system and method for an unmanned vehicle and an unmanned aerial vehicle, and relates to the technical field of unmanned aerial vehicles, the system comprises a dynamic positioning module, the dynamic positioning module is used for collecting multi-dimensional data of the unmanned aerial vehicle and the unmanned vehicle, and the multi-dimensional data specifically comprises bandwidth signal data, visual image data, geomagnetic intensity data and auxiliary data; relative positioning between the unmanned aerial vehicle and the unmanned vehicle is achieved according to the collected data, and real-time position data of the unmanned aerial vehicle and the unmanned vehicle are obtained and transmitted; through accurate positioning and adjustment, the unmanned aerial vehicle can reach a designated position more accurately, distribution failure caused by positioning deviation is avoided, the success rate of logistics distribution is improved, when the similarity is high, the unmanned aerial vehicle directly returns to a safe height without adjustment, continuous flight of the unmanned aerial vehicle in an unsafe environment is effectively avoided, and the safety of logistics distribution is improved. The safety risks of collision, falling and the like are reduced, and the safety of the unmanned aerial vehicle and the container is protected.

Description

Technical Field

[0001] The present invention relates to the field of unmanned aerial vehicle (UAV) technology, and more particularly to a coordinated take-off and landing control system and method for an unmanned vehicle and a UAV. Background Art

[0002] With the acceleration of urbanization and the booming development of e-commerce, the demand for urban logistics and distribution is increasing. Traditional logistics and distribution methods have many pain points in instant delivery scenarios, especially in the final delivery link. These problems have seriously affected delivery efficiency and service quality. To meet the existing delivery needs within cities, unmanned vehicles and drones are used for precise delivery in high-rise buildings. During the delivery process, the drone lands on the unmanned vehicle and first moves to an area close to the delivery location. Then the drone takes off for further precise delivery. In urban environments, high-rise buildings create the so-called urban canyon effect, which blocks and reflects GPS signals, significantly reducing positioning accuracy and causing drift of up to 3-5 meters. Precise landing at the terminal is crucial for drones, as only landing at the designated location can ensure safe delivery of cargo containers. However, inaccurate GPS positioning makes it difficult for drones to achieve precise landings, increasing delivery risks and costs. Urban traffic conditions are complex and ever-changing, and the docking locations of delivery vehicles often change. This dynamic change poses great difficulties for drone takeoff and landing, because drones need to adjust their flight paths and takeoff and landing postures in real time according to the location of the vehicle. Traditional drone control systems are difficult to adapt to this rapidly changing environment, resulting in a high takeoff and landing failure rate, which affects delivery efficiency. Summary of the Invention

[0003] To solve the above problems, the present invention provides a coordinated take-off and landing control system and method for an unmanned vehicle and a drone.

[0004] The present invention provides a coordinated take-off and landing control system for an unmanned vehicle and a drone, comprising a dynamic positioning module. The dynamic positioning module is used to collect multi-dimensional data of the drone and the unmanned vehicle, the multi-dimensional data specifically including bandwidth signal data, visual image data, geomagnetic intensity data, and auxiliary data. The module then achieves relative positioning between the drone and the unmanned vehicle based on the collected data, obtains real-time position data of the drone and the unmanned vehicle, and transmits the data. A path planning module, which is used to receive the multi-dimensional data collected by the dynamic positioning module and the real-time position data of the UAV and the unmanned vehicle, and determine whether the cargo box of the UAV landing gear is tilted; The path planning module is also used to adjust the operating path of the drone when the cargo box of the drone landing gear is tilted, so that the cargo box can be transported smoothly; the collaborative module is used to collaboratively control the drone and the unmanned vehicle based on the multi-dimensional data of the dynamic positioning module and the real-time position data of the drone and the unmanned vehicle, and collaboratively control the operating parameters of the unmanned vehicle and the drone when the cargo box of the drone landing gear is tilted.

[0005] Preferably, the dynamic positioning module includes a data acquisition unit, a data fusion unit and a positioning solution unit: The data acquisition unit includes a positioning base station, which is arranged at the four corners of the unmanned vehicle and the front of the drone, and also includes a geomagnetic intensity detector, which is installed at the bottom of the drone.

[0006] Preferably, the specific working steps of the dynamic positioning module are as follows: With the center of mass of the UAV as the origin, a local coordinate system is established, and the positioning base stations at the four corners of the UAV are marked as 、 、 and , the coordinates of the four positioning base stations are 、 、 and ; Drone as signal source Signal, positioning base stations at the four corners of the unmanned vehicle 、 、 and Receive the signals transmitted by the drones respectively and record the arrival time of the signals in turn 、 、 and , calculate the relative distances between the drone and the four base stations; The specific calculation formula is: , calculate and obtain the relative distance between the drone and the positioning base station ,in is the speed of light, is the time when the signal reaches the i-th positioning base station, is the time it takes for the signal to reach the jth base station, Specifically 、 and ; According to the three time differences, three equations are established to solve the position of the drone. ; According to the above method, the position of the drone and the relative position coordinates of the unmanned vehicle and the drone are calculated every time period and transmitted as the real-time position data of the drone and the unmanned vehicle.

[0007] Preferably, the specific working steps of the dynamic positioning module also include the following: When unmanned vehicles and drones arrive at designated locations for delivery, a gridded geomagnetic map is constructed in the work area, and the three components of the geomagnetic intensity are recorded at each grid point. 、 and ;It should be noted that the range of the gridded geomagnetic map is 5m×5m; Specifically ; During the delivery flight of the drone, the geomagnetic intensity is measured in real time through the geomagnetic intensity detector. , where each measurement point The corresponding coordinates are the previously obtained position of the drone , real-time measurement of geomagnetic intensity Specifically include , respectively represent the north component, east component and vertical component of the geomagnetic intensity; Then according to the real-time position of the drone Find the geomagnetic map The corresponding points in ; By formula , calculate the similarity between the geomagnetic data currently measured by the drone and the map data ,in Specifically include , respectively represent the north component, east component and vertical component of the geomagnetic intensity; If the similarity Less than or equal to 25 , it is determined that the currently measured geomagnetic data matches the map data successfully; otherwise, it is determined that the match is unsuccessful, and a signal is transmitted to the path planning module for adjustment.

[0008] Preferably, the specific working steps of the dynamic positioning module also include the following: A pressure sensor array is placed on the drone landing gear, specifically a 16 by 16 grid, to monitor the pressure distribution in real time and obtain the pressure value of each grid point. ; Then according to the formula Calculate the center of mass offset of the cargo box on the UAV landing gear ,in For the The pressure value at each grid point, and is the coordinate of the i-th grid point; Offset to the center of mass of the container To judge, if the center of mass of the cargo box is offset If the center of mass of the cargo box is less than 0.02m, it is judged as level one. If the center of mass of the container is less than 0.05m and greater than 0.02m, it is judged as level 2. If it is greater than or equal to 0.05m, it is judged as level three; The judgment result is transmitted as a signal to the path planning module.

[0009] Preferably, the specific steps of the path planning module include the following: Receive the signal from the dynamic positioning module that the match is unsuccessful, and further determine the similarity Is it located at 25 and 50 Between, if yes, then according to the formula; ; Calculate the lateral offset compensation of the UAV , longitudinal offset compensation and height adjustment ,in is the north component of the geomagnetic intensity measured by the drone in real time, is the north component of the corresponding grid point in the geomagnetic map, is the eastward component of the geomagnetic intensity measured by the drone in real time. is the eastward component of the geomagnetic intensity at the corresponding grid point in the geomagnetic map; Compensation for lateral deviation of the drone , longitudinal offset compensation and height adjustment , to adjust the position of the drone accordingly; If the similarity Not located at 25 and 50 The similarity between Greater than or equal to 50 , a control signal is generated to make the drone return to a safe altitude.

[0010] Preferably, the specific steps of the path planning module also include the following: Receive the judgment result from the dynamic positioning module, if the center of mass offset of the cargo box If it is judged as level one, no adjustment is required; If the center of mass of the container is offset If it is judged as level 2, the cargo box offset compensation is performed. The specific steps are: first, obtain the center of mass offset of the cargo box from the pressure sensor array ,include Quantity and y Quantity , construct the rotation matrix according to the yaw angle of the drone , according to the formula: ; Calculate the adjusted posture of the drone ,in is the initial posture of the drone, and the posture after adjustment of the drone Adjust the current drone's attitude; If the center of mass of the container is offset If it is judged as level 3, the drone will be controlled to spiral down. The specific trajectory is as follows: ; Calculate the spiral descent trajectory of the drone 、 and It should be noted that A function representing the change in the position of the drone on the x-axis over time. As time increases, the position of the drone on the x-axis gradually moves closer to the center point and oscillates at a frequency of 4π. Also need to follow the formula , get the maximum acceleration of the drone, and limit the acceleration of the drone during the spiral descent to no more than .

[0011] Preferably, the specific steps of the collaboration module include the following: The power of the drone is provided by four motors installed at the four corners, with the center of mass offset of the cargo box. When it is judged to be level 2 or level 3, the thrust of the four motors of the drone is redistributed. The specific steps include: first, according to the formula ; Calculate the thrust of the four motors to redistribute the thrust of the four motors of the drone, where 、 、 and is the thrust vector of the four motors, It is the pseudo-inverse matrix of the power distribution matrix, which is used to distribute the control instructions to the four motors. for Control force in the axial direction, for Control force in the axial direction, for Control force in the axial direction, The compensation matrix includes 0.2, 0.2, 0.1 and 0 in order to adjust the center of mass offset of the cargo box. impact.

[0012] Preferably, the specific steps of the collaborative module also include the following Formulate the speed adjustment strategy of the unmanned vehicle according to the status of the drone, specifically: ; Represents the center of mass offset of the cargo box Judged as level 2, Represents the center of mass offset of the cargo box Judged as level three, Represents the center of mass offset of the cargo box It is judged as level one, is the initial speed of the unmanned vehicle, Represents the adjusted speed of the autonomous vehicle; Then according to the formula Get the angle adjustment value of the unmanned vehicle , adjust the driving angle according to the angle adjustment value of the unmanned vehicle, where The center of mass of the container is Axis offset, Indicates that the center of mass of the container is Axis offset, specifically the offset of the center of mass of the container get.

[0013] The present invention also proposes a coordinated take-off and landing control method for an unmanned vehicle and a drone, comprising the following steps: Step 1: Real-time perception of the UAV's motion status, prediction of the UAV's landing trajectory, and dynamic adjustment of the flight path. When geomagnetic matching fails, triggering lateral / longitudinal offset compensation or returning to a safe altitude to avoid collision risks caused by positioning drift. Step 2: Deploy grid pressure sensors on the drone landing gear to calculate the center of mass offset of the cargo box in real time and determine the center of mass offset in a graded manner; Step 3: When the cargo box tilts, the thrust of the four motors is adjusted through pseudo-inversion of the power distribution matrix to offset the impact of the center of mass offset. The speed and driving angle of the unmanned vehicle are adjusted according to the state of the cargo box to avoid the cargo box from overturning due to sharp turns or high-speed driving.

[0014] Beneficial Effects: Through precise positioning and adjustment, drones can reach designated locations more accurately, avoiding delivery failures caused by positioning deviations and improving the success rate of logistics delivery. When the similarity is high, drones return directly to a safe altitude without making adjustments, effectively preventing drones from continuing to fly in unsafe environments, reducing safety risks such as collisions and falls, and protecting the safety of drones and cargo containers. This path planning strategy based on similarity judgment enables drones to fly stably and reliably in complex and changing urban environments, improving the reliability and stability of the entire logistics delivery system. By adjusting the speed and angle of the unmanned vehicle based on the cargo box's center of mass offset, accidents such as collisions and rollovers caused by high-speed or erroneous driving when the cargo box is unstable can be effectively avoided. This ensures the safety of both the unmanned vehicle and the cargo box, and enables the unmanned vehicle to better collaborate with the drone. During drone delivery flights or takeoffs and landings, the unmanned vehicle can adjust its driving state based on the cargo box's state, ensuring precise docking and stable coordination between the two, improving the overall efficiency and reliability of logistics delivery. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Figure 1 It is a flow chart of the system of the present invention. DETAILED DESCRIPTION

[0016] like Figure 1 As shown: A coordinated take-off and landing control system for an unmanned vehicle and a drone, including a dynamic positioning module, which is used to collect multi-dimensional data of the drone and the unmanned vehicle, the multi-dimensional data specifically including bandwidth signal data, visual image data, geomagnetic intensity data and auxiliary data, and realize relative positioning between the drone and the unmanned vehicle based on the collected data, obtain real-time position data of the drone and the unmanned vehicle, and transmit it; relative positioning mainly provides high-precision position information for the precise take-off and landing of the drone and the dynamic docking of the unmanned vehicle. By integrating multiple positioning technologies, the dynamic positioning module can determine the relative position and posture of the drone and the unmanned vehicle in real time in a complex urban environment, ensuring that the two always maintain an accurate relative position relationship during the collaborative work process, thereby realizing efficient and reliable logistics distribution; The dynamic positioning module determines the relative position of the drone and the unmanned vehicle. The drone needs to achieve precise landing and takeoff in the dynamic environment of the unmanned vehicle, while the unmanned vehicle needs to make real-time adjustments based on the drone's position information to ensure smooth docking. The dynamic positioning module provides real-time information such as the relative coordinates, speed, and attitude between the drone and the unmanned vehicle through precise measurement and calculation, providing key data support for their collaborative work. A path planning module, which is used to receive the multi-dimensional data collected by the dynamic positioning module and the real-time position data of the UAV and the unmanned vehicle, and determine whether the cargo box of the UAV landing gear is tilted; The path planning module is also used to adjust the drone's operating path when the cargo box of the drone's landing gear tilts, so that the cargo box can be transported smoothly. It should be noted that the path planning module can effectively receive multi-dimensional data and real-time location data, and judge the tilt state of the cargo box, providing key support for the safe flight of the drone, ensuring that the cargo box remains stable during transportation, reducing the risk of damage to the cargo box, and improving transportation reliability. When the cargo box tilts, the drone's operating path is adjusted in time, the flight route is optimized, and possible obstacles and interference areas are avoided to ensure that the drone arrives at its destination smoothly, thereby improving the success rate and efficiency of delivery and saving flight time and energy consumption. A collaborative module, which is used to collaboratively control the drone and the unmanned vehicle based on the multidimensional data from the dynamic positioning module and the real-time location data of the drone and the unmanned vehicle, and to collaboratively control the operating parameters of the unmanned vehicle and the drone when the cargo box of the drone landing gear tilts. It should be noted that the collaborative module collaboratively controls the drone and the unmanned vehicle based on the multidimensional data and real-time location data, adjusts the operating parameters of both parties when the cargo box tilts, and achieves close cooperation between the two during the logistics and delivery process, ensuring the smooth handover of the cargo box from the drone to the unmanned vehicle, improving delivery efficiency and accuracy, and reducing waiting time and operational complexity; It should be noted that in urban environments, due to the influence of factors such as buildings and signal interference, traditional positioning technology is difficult to achieve accurate landing of drones. The dynamic positioning module can achieve centimeter-level positioning accuracy in complex urban environments by integrating multiple technologies such as ultra-wideband positioning, vision-assisted positioning and geomagnetic anomaly matching. As an unmanned vehicle moves, its position and posture constantly change, placing higher demands on the positioning and takeoff and landing of drones. The dynamic positioning module can sense the motion state of the unmanned vehicle in real time and adjust the positioning and flight path of the drone accordingly, ensuring that the drone maintains a precise relative position in the dynamic environment of the unmanned vehicle, enabling dynamic docking and collaborative work. In complex urban environments, a single positioning technology often fails to meet the requirements of high precision and high stability. The dynamic positioning module, through multi-source data fusion, combines the high precision of positioning, the real-time nature of visual positioning, and the stability of geomagnetic matching. It can provide reliable and stable positioning information under various complex conditions, ensuring that the collaborative work of drones and unmanned vehicles is not affected by environmental factors, thereby improving the overall performance and reliability of the system.

[0017] As an optional embodiment: the dynamic positioning module includes a data acquisition unit, a data fusion unit and a positioning solution unit: The data acquisition unit includes a positioning base station, which is deployed at the four corners of the unmanned vehicle and the front of the drone, and a geomagnetic intensity detector, which is installed at the bottom of the drone. It should be noted that the ultra-wideband positioning base station calculates the position of the drone by transmitting and receiving UWB signals to achieve high-precision relative positioning. The geomagnetic intensity detector is composed of a 3-axis magnetometer, which is used to detect the geomagnetic intensity in real time, construct a geomagnetic intensity map, and achieve high-precision positioning through geomagnetic anomaly matching technology. The inertial measurement unit includes a gyroscope and an accelerometer, which are used to measure the acceleration and angular velocity of the drone. Collect multi-source data from unmanned vehicles and drones to provide a basis for subsequent positioning and navigation.

[0018] As an optional embodiment: the specific working steps of the dynamic positioning module are as follows: With the center of mass of the UAV as the origin, a local coordinate system is established, and the positioning base stations at the four corners of the UAV are marked as 、 、 and , the coordinates of the four positioning base stations are 、 、 and ; Drone as signal source Signal, positioning base stations at the four corners of the unmanned vehicle 、 、 and Receive the signals transmitted by the drones respectively and record the arrival time of the signals in turn 、 、 and , calculate the relative distances between the drone and the four base stations; The specific calculation formula is: , calculate and obtain the relative distance between the drone and the positioning base station ,in is the speed of light, is the time when the signal reaches the i-th positioning base station, is the time it takes for the signal to reach the jth base station, Specifically 、 and ; According to the three time differences, three equations are established to solve the position of the drone. ; According to the above method, the position of the drone and the relative position coordinates of the unmanned vehicle and drone are calculated at intervals and transmitted as the real-time position data of the drone and unmanned vehicle. It should be noted that this is mainly to solve the problem of insufficient accuracy of traditional GPS positioning technology in complex environments such as urban canyon effects, ensuring that the drone can accurately land at the designated location of the unmanned vehicle, thereby improving the efficiency and safety of logistics distribution; The advantage of using positioning base station signals to determine relative distance is that it does not rely on satellite signals. Instead, it calculates the distance by directly receiving the signals transmitted by the drone through ground base stations. This method can effectively avoid signal obstruction and reflection by high-rise buildings, reducing positioning errors. In addition, by receiving signals from multiple base stations simultaneously, multiple equations can be formed for solution. This dynamic positioning module, which uses signals from positioning base stations to determine relative distance, has significantly improved GPS positioning accuracy due to the urban canyon effect. It can provide drones with highly accurate positioning information even in GPS-restricted environments, ensuring precise takeoff and landing, as well as dynamic docking, in urban areas. This is crucial for logistics and delivery, as accurate drone landing on unmanned vehicles ensures safe delivery of cargo boxes, avoiding delivery failures or delays caused by inaccurate positioning. This reduces delivery risks and costs, and improves the efficiency and reliability of the entire logistics system.

[0019] As an optional embodiment: the specific working steps of the dynamic positioning module also include the following: It should be noted that the geomagnetic field is a stable natural physical field, which is not affected by human interference and occlusion, and can provide an independent positioning reference to enhance the robustness of the positioning system. During long-term flight or in complex environments, the errors of the inertial navigation system will gradually accumulate. Geomagnetic matching can correct these accumulated errors by matching with the geomagnetic reference map, thereby improving navigation accuracy. Especially in environments where satellite signals are limited or missing, such as urban canyons and tunnels, by installing geomagnetic intensity detectors, constructing geomagnetic intensity maps and matching the geomagnetic intensity data measured by drones in real time, the position of the drone can be calibrated to improve positioning accuracy and reliability; When unmanned vehicles and drones arrive at designated locations for delivery, a gridded geomagnetic map is constructed in the work area, and the three components of the geomagnetic intensity are recorded at each grid point. 、 and ;It should be noted that the range of the gridded geomagnetic map is 5m×5m; Specifically ; During the delivery flight of the drone, the geomagnetic intensity is measured in real time through the geomagnetic intensity detector. , where each measurement point The corresponding coordinates are the previously obtained position of the drone , real-time measurement of geomagnetic intensity Specifically include , respectively represent the north component, east component and vertical component of the geomagnetic intensity; Then according to the real-time position of the drone Find the geomagnetic map The corresponding points in ; By formula , calculate the similarity between the geomagnetic data currently measured by the drone and the map data ,in Specifically include , respectively represent the north component, east component and vertical component of the geomagnetic intensity; If the similarity Less than or equal to 25 , it is determined that the currently measured geomagnetic data matches the map data successfully; otherwise, it is determined that the match is unsuccessful, and the signal is transmitted to the path planning module for adjustment. It should be noted that by comparing the geomagnetic intensity measured by the drone in real time with the data in the geomagnetic map, the current position of the drone can be determined, thereby achieving high-precision positioning. When the match is unsuccessful, the signal is transmitted to the path planning module for adjustment, ensuring that the drone can adjust its flight path based on real-time geomagnetic information, avoid possible interference areas or obstacles, and ensure the safety and smoothness of flight. The matching of geomagnetic data can help the drone perceive changes in the surrounding environment, such as the influence of buildings and metal structures on geomagnetism, so as to better adapt to complex urban environments and improve the reliability of delivery. In the case of urban canyon effects causing GPS signals to be blocked and reflected, the use of geomagnetic matching technology can effectively improve the positioning accuracy of the drone, avoid delivery failures or delays caused by inaccurate GPS signals, and ensure that the cargo boxes can be delivered accurately and safely. By matching geomagnetic data with map data, the drone can fly and locate stably in complex and changing urban environments, reducing the risk of system failures caused by environmental factors and improving the reliability and stability of the entire logistics distribution system.

[0020] As an optional embodiment: the specific working steps of the dynamic positioning module also include the following: A pressure sensor array is placed on the drone landing gear, specifically a 16 by 16 grid, to monitor the pressure distribution in real time and obtain the pressure value of each grid point. ; Then according to the formula Calculate the center of mass offset of the cargo box on the UAV landing gear ,in For the The pressure value at each grid point, and is the coordinate of the i-th grid point; Offset to the center of mass of the container To judge, if the center of mass of the cargo box is offset If the center of mass of the cargo box is less than 0.02m, it is judged as level one. If the center of mass of the container is less than 0.05m and greater than 0.02m, it is judged as level 2. If it is greater than or equal to 0.05m, it is judged as level three; The judgment result is transmitted as a signal to the path planning module. It should be noted that by deploying a pressure sensor array on the drone landing gear, monitoring the pressure distribution in real time and calculating the center of mass offset of the cargo box, it is possible to achieve real-time monitoring and evaluation of the drone's cargo status. Specifically, the role and purpose of this judgment include obtaining the pressure distribution of the cargo box on the drone landing gear in real time through the pressure sensor array, being able to promptly detect whether the cargo box is offset or tilted during transportation, ensuring the stability and safety of the cargo box, and making graded judgments based on the size of the center of mass offset, so as to provide different levels of early warning information. Level 1 indicates that the cargo box is in good condition, level 2 indicates that attention is needed, and level 3 indicates that immediate action needs to be taken. This hierarchical warning mechanism helps to adjust the flight attitude or path in a timely manner to avoid flight accidents caused by cargo box deviation. The judgment results are transmitted to the path planning module, so that the drone can adjust the flight parameters such as flight attitude and speed according to the real-time status of the cargo box to ensure flight stability and safety and improve the success rate of delivery. By real-time monitoring of the center of mass deviation of the cargo box, the cargo box deviation problem can be discovered and handled in a timely manner to avoid the drone imbalance or fall caused by the instability of the cargo box, thereby ensuring the safety of the cargo box during transportation.

[0021] As an optional embodiment, the specific steps of the path planning module include the following: Receive the signal from the dynamic positioning module that the match is unsuccessful, and further determine the similarity Is it located at 25 and 50 Between, if yes, then according to the formula; ; Calculate the lateral offset compensation of the UAV , longitudinal offset compensation and height adjustment ,in is the north component of the geomagnetic intensity measured by the drone in real time, is the north component of the corresponding grid point in the geomagnetic map, is the eastward component of the geomagnetic intensity measured by the drone in real time. is the eastward component of the geomagnetic intensity at the corresponding grid point in the geomagnetic map; Compensation for lateral deviation of the drone , longitudinal offset compensation and height adjustment , to adjust the position of the drone accordingly; If the similarity Not located at 25 and 50 The similarity between Greater than or equal to 50 , a control signal is generated to make the drone return to a safe height. It should be noted that the safe height is set in advance and is set according to the building height of the delivery area, which is generally higher than the average building height; It should also be noted that through precise positioning and adjustment, drones can reach designated locations more accurately, avoid delivery failures due to positioning deviations, and improve the success rate of logistics delivery. When the similarity is high, no adjustment is made and the drone directly returns to a safe altitude, effectively avoiding the drone's continued flight in an unsafe environment, reducing safety risks such as collisions and falls, and protecting the safety of drones and cargo boxes. This path planning strategy based on similarity judgment enables drones to fly stably and reliably in complex and changeable urban environments, improving the reliability and stability of the entire logistics distribution system.

[0022] As an optional embodiment, the specific steps of the path planning module further include the following: Receive the judgment result from the dynamic positioning module, if the center of mass offset of the cargo box If it is judged as level one, no adjustment is required; If the center of mass of the container is offset If it is judged as level 2, the cargo box offset compensation is performed. The specific steps are: first, obtain the center of mass offset of the cargo box from the pressure sensor array ,include Quantity and the y component , construct the rotation matrix according to the yaw angle of the drone , according to the formula: ; Calculate the adjusted posture of the drone ,in is the initial posture of the drone, and the posture after adjustment of the drone Adjust the current drone's attitude; If the center of mass of the container is offset If it is judged as level 3, the drone will be controlled to spiral down. The specific trajectory is as follows: ; Calculate the spiral descent trajectory of the drone 、 and It should be noted that A function representing the change in the position of the drone on the x-axis over time. As time increases, the position of the drone on the x-axis gradually moves closer to the center point and oscillates at a frequency of 4π. It should be noted that A function representing the change in the position of the drone on the y-axis over time. As time increases, the position of the drone on the y-axis gradually moves closer to the center point and oscillates at a frequency of 4π. A function that represents the change of the drone's position on the z-axis over time. As time increases, the drone's position on the z-axis gradually decreases until it reaches the target height; in, is the radius of the spiral descent, is the total time of spiral descent, is the current time, 、 and The initial position of the UAV, the real-time position of the UAV before spiral descent get; Also need to follow the formula ， Get the maximum acceleration of the drone, and limit the acceleration of the drone during the spiral descent to no more than It should be noted that the initial attitude of the drone is obtained by the gyroscope installed on the drone. The solution for adjusting the attitude of the drone is as follows: by comparing the current attitude of the drone with the target attitude, the deviation between the two is used to calculate the appropriate control amount through the PID control algorithm to drive the motor to adjust the attitude of the drone; The attitude of the drone at any moment can be represented by the roll angle, pitch angle, and yaw angle. For each degree of freedom, it is a second-order system, and PID control is used for these three angles respectively. For roll angle control, the attitude error signal and error rate of the multi-rotor drone are first obtained, and then the control quantity of each motor is obtained through the improved PID control algorithm and transmitted to the corresponding motor. The attitude of the drone is adjusted by changing the speed of the motor to eliminate the attitude error as much as possible, thus forming a two-level closed-loop control.

[0023] As an optional embodiment: the specific steps of the collaboration module include the following: The power of the drone is provided by four motors installed at the four corners, with the center of mass offset of the cargo box. When it is judged to be level 2 or level 3, the thrust of the four motors of the drone is redistributed. The specific steps include: first, according to the formula ; Calculate the thrust of the four motors to redistribute the thrust of the four motors of the drone, where 、 、 and is the thrust vector of the four motors, It is the pseudo-inverse matrix of the power distribution matrix, which is used to distribute the control instructions to the four motors. for Control force in the axial direction, for Control force in the axial direction, for Control force in the axial direction, The compensation matrix includes 0.2, 0.2, 0.1 and 0 in order to adjust the center of mass offset of the cargo box. It should be noted that when the center of mass of the drone shifts, the compensation term will adjust the control command to make the drone generate additional force or torque to offset the impact of the shift. For example, if the center of mass shifts forward, will increase, causing the drone to tilt backward to regain balance.

[0024] As an optional embodiment: the specific steps of the collaborative module also include the following Formulate the speed adjustment strategy of the unmanned vehicle according to the status of the drone, specifically: ; Represents the center of mass offset of the cargo box Judged as level 2, Represents the center of mass offset of the cargo box Judged as level three, Represents the center of mass offset of the cargo box It is judged as level one, is the initial speed of the unmanned vehicle, Represents the adjusted speed of the autonomous vehicle; Then according to the formula Get the angle adjustment value of the unmanned vehicle , adjust the driving angle according to the angle adjustment value of the unmanned vehicle, where The center of mass of the container is Axis offset, Indicates that the center of mass of the container is Axis offset, specifically the offset of the center of mass of the container It should be noted that by adjusting the speed and angle of the unmanned vehicle based on the cargo box's center of mass offset, it is possible to effectively avoid safety accidents such as collisions and rollovers caused by the unmanned vehicle driving at high speed or driving incorrectly when the cargo box is unstable, thereby ensuring the safety of the unmanned vehicle and the cargo box, and enabling the unmanned vehicle to work better with the drone. During the drone's delivery flight or takeoff and landing, the unmanned vehicle can promptly adjust its driving state based on the cargo box's state, ensuring precise docking and stable cooperation between the two, improving the overall efficiency and reliability of logistics delivery. Appropriate speed and angle adjustment can reduce the impact and shaking caused by the unmanned vehicle's unstable driving on the cargo box, reduce the risk of damage to the cargo box during transportation, and protect the integrity and safety of the cargo box. In urban environments, road conditions and surrounding environments are complex and changeable. Through this flexible speed and angle adjustment strategy, the unmanned vehicle can better adapt to various complex situations, ensuring stable driving and smooth completion of cargo box delivery tasks in different environments.

[0025] The present invention also proposes a coordinated take-off and landing control method for an unmanned vehicle and a drone, comprising the following steps: Step 1: Real-time perception of the UAV's motion status, prediction of the UAV's landing trajectory, and dynamic adjustment of the flight path. When geomagnetic matching fails, triggering lateral / longitudinal offset compensation or returning to a safe altitude to avoid collision risks caused by positioning drift. Step 2: Deploy grid pressure sensors on the drone landing gear to calculate the center of mass offset of the cargo box in real time and determine the center of mass offset in a graded manner; Step 3: When the cargo box tilts, the thrust of the four motors is adjusted through pseudo-inversion of the power distribution matrix to offset the impact of the center of mass offset. The speed and driving angle of the unmanned vehicle are adjusted according to the state of the cargo box to avoid the cargo box from overturning due to sharp turns or high-speed driving.

[0026] Working principle: The dynamic positioning module interacts with the UWB signals of the drone through the UWB base stations deployed at the four corners of the unmanned vehicle, uses the time difference ranging algorithm to calculate the relative distance in real time, and integrates geomagnetic matching technology; The module senses the motion status of the unmanned vehicle in real time, predicts the landing trajectory of the drone, and dynamically compensates for positioning deviations caused by building obstructions and multipath effects. When geomagnetic matching fails, it triggers lateral / longitudinal offset compensation or controls the drone to return to a safe altitude to avoid collision risks caused by positioning drift. A 16×16 grid pressure sensor array is deployed on the drone's landing gear to calculate the cargo box's center of mass offset in real time. The offset is graded: Level 1 offset: The cargo box is stable and no adjustment is required; Level 2 offset: The drone's attitude is adjusted through a rotation matrix to compensate for cargo box tilt; Level 3 offset: A spiral descent trajectory is triggered, limiting acceleration to ≤5m / s² to ensure a safe landing. The collaborative module uses pseudo-inverse power distribution matrix to redistribute the thrust of the drone's four motors, offsetting the impact of center of mass shift. It also adjusts the speed and driving angle of the drone based on the cargo box's status to prevent the box from tipping over during sharp turns or high-speed driving. Data synchronization is ensured through dual redundant communication links, and system robustness is ensured by triggering hovering or emergency braking when the main link is interrupted. This solution significantly improves the reliability and efficiency of urban logistics distribution through high-precision dynamic positioning, hierarchical response mechanism and multi-platform collaborative optimization.

[0027] The above are only preferred embodiments of the present invention. The scope of protection of the present invention is not limited to the above embodiments. All technical solutions that fall within the scope of protection of the present invention are within the scope of protection of the present invention. It should be pointed out that for ordinary technical personnel in this technical field, certain improvements and modifications that do not depart from the principles of the present invention should also be considered as the scope of protection of this template.

Claims

1. A coordinated take-off and landing control system for unmanned vehicles and drones, characterized in that: It includes a dynamic positioning module, which is used to collect multi-dimensional data of the UAV and the unmanned vehicle, the multi-dimensional data specifically including bandwidth signal data, visual image data, geomagnetic intensity data and auxiliary data, and realize the relative positioning between the UAV and the unmanned vehicle based on the collected data, obtain the real-time position data of the UAV and the unmanned vehicle, and transmit it; A path planning module, which is used to receive the multi-dimensional data collected by the dynamic positioning module and the real-time position data of the UAV and the unmanned vehicle, and determine whether the cargo box of the UAV landing gear is tilted; The path planning module is also used to adjust the flight path of the drone when the cargo box of the drone landing gear is tilted, so that the cargo box is transported smoothly; A collaborative module is used to collaboratively control the drone and the unmanned vehicle based on the multi-dimensional data of the dynamic positioning module and the real-time position data of the drone and the unmanned vehicle, and to collaboratively control the operating parameters of the unmanned vehicle and the drone when the cargo box of the drone landing gear is tilted.

2. The coordinated take-off and landing control system for an unmanned vehicle and a drone according to claim 1, characterized in that: The dynamic positioning module includes a data acquisition unit, a data fusion unit and a positioning solution unit: The data acquisition unit includes a positioning base station, which is arranged at the four corners of the unmanned vehicle and the front of the drone, and also includes a geomagnetic intensity detector, which is installed at the bottom of the drone.

3. The coordinated take-off and landing control system for an unmanned vehicle and a drone according to claim 2, characterized in that: The specific working steps of the dynamic positioning module are as follows: With the center of mass of the UAV as the origin, a local coordinate system is established, and the positioning base stations at the four corners of the UAV are marked as 、 、 and , the coordinates of the four positioning base stations are 、 、 and ; Drone as signal source Signal, positioning base stations at the four corners of the unmanned vehicle 、 、 and Receive the signals transmitted by the drones respectively and record the arrival time of the signals in turn 、 、 and , calculate the relative distances between the drone and the four base stations; The specific calculation formula is: , calculate and obtain the relative distance between the drone and the positioning base station ,in is the speed of light, is the time when the signal reaches the i-th positioning base station, is the time it takes for the signal to reach the jth base station, Specifically 、 and ; According to the three time differences, three equations are established to solve the position of the drone. ; According to the above method, the position of the drone and the relative position coordinates of the unmanned vehicle and the drone are calculated every time period and transmitted as the real-time position data of the drone and the unmanned vehicle.

4. The coordinated take-off and landing control system for an unmanned vehicle and a drone according to claim 3, characterized in that: The specific working steps of the dynamic positioning module also include the following: When unmanned vehicles and drones arrive at designated locations for delivery, a gridded geomagnetic map is constructed in the work area, and the three components of the geomagnetic intensity are recorded at each grid point. 、 and ;It should be noted that the range of the gridded geomagnetic map is 5m×5m; Specifically ; During the delivery flight of the drone, the geomagnetic intensity is measured in real time through the geomagnetic intensity detector. , where each measurement point The corresponding coordinates are the previously obtained position of the drone , real-time measurement of geomagnetic intensity Specifically include , respectively represent the north component, east component and vertical component of the geomagnetic intensity; Then according to the real-time position of the drone Find the geomagnetic map The corresponding points in ; By formula , calculate the similarity between the geomagnetic data currently measured by the drone and the map data ,in Specifically include , respectively represent the north component, east component and vertical component of the geomagnetic intensity; If the similarity Less than or equal to 25 , it is determined that the currently measured geomagnetic data matches the map data successfully; otherwise, it is determined that the match is unsuccessful, and a signal is transmitted to the path planning module for adjustment.

5. The coordinated take-off and landing control system for an unmanned vehicle and a drone according to claim 3, characterized in that: The specific working steps of the dynamic positioning module also include the following: A pressure sensor array is placed on the drone landing gear, specifically a 16 by 16 grid, to monitor the pressure distribution in real time and obtain the pressure value of each grid point. ; Then according to the formula Calculate the center of mass offset of the cargo box on the UAV landing gear ,in For the The pressure value at each grid point, and is the coordinate of the i-th grid point; Offset to the center of mass of the container To judge, if the center of mass of the cargo box is offset If the center of mass of the cargo box is less than 0.02m, it is judged as level one. If the center of mass of the container is less than 0.05m and greater than 0.02m, it is judged as level 2. If it is greater than or equal to 0.05m, it is judged as level three; The judgment result is transmitted as a signal to the path planning module.

6. The coordinated take-off and landing control system for an unmanned vehicle and a drone according to claim 4, characterized in that: The specific steps of the path planning module include the following: Receive the signal from the dynamic positioning module that the match is unsuccessful, and further determine the similarity Is it located at 25 and 50 Between, if yes, then according to the formula; ； Calculate the lateral offset compensation of the drone , longitudinal offset compensation and height adjustment ,in is the north component of the geomagnetic intensity measured by the drone in real time, is the north component of the corresponding grid point in the geomagnetic map, is the eastward component of the geomagnetic intensity measured by the drone in real time, is the eastward component of the geomagnetic intensity at the corresponding grid point in the geomagnetic map; Compensation for lateral deviation of the drone , longitudinal offset compensation and height adjustment , to adjust the position of the drone accordingly; If the similarity Not located at 25 and 50 The similarity between Greater than or equal to 50 , a control signal is generated to make the drone return to a safe altitude.

7. The coordinated take-off and landing control system for an unmanned vehicle and a drone according to claim 5, characterized in that: The specific steps of the path planning module also include the following: Receive the judgment result from the dynamic positioning module, if the center of mass offset of the cargo box If it is judged as level one, no adjustment is required; If the center of mass of the container is offset If it is judged as level 2, the cargo box offset compensation is performed. The specific steps are: first, obtain the center of mass offset of the cargo box from the pressure sensor array ,include Quantity and y Quantity , construct the rotation matrix according to the yaw angle of the drone , according to the formula: ； Calculate the adjusted posture of the drone ,in is the initial posture of the drone, and the posture after adjustment of the drone Adjust the current drone's attitude; If the center of mass of the container is offset If it is judged as level 3, the drone will be controlled to spiral down. The specific trajectory is as follows: ； Calculate the spiral descent trajectory of the drone 、 and It should be noted that A function representing the change in the position of the drone on the x-axis over time. As time increases, the position of the drone on the x-axis gradually moves closer to the center point and oscillates at a frequency of 4π. Also need to follow the formula , get the maximum acceleration of the drone, and limit the acceleration of the drone during the spiral descent to no more than .

8. The coordinated take-off and landing control system for an unmanned vehicle and a drone according to claim 7, characterized in that: The specific steps of the collaborative module include the following: The power of the drone is provided by four motors installed at the four corners, with the center of mass offset of the cargo box. When it is judged to be level 2 or level 3, the thrust of the four motors of the drone is redistributed. The specific steps include: first, according to the formula ; The thrust of the four motors is redistributed by calculating the thrust of the four motors of the drone, where 、 、 and is the thrust vector of the four motors, It is the pseudo-inverse matrix of the power distribution matrix, which is used to distribute the control instructions to the four motors. for Control force in the axial direction, for Control force in the axial direction, for Control force in the axial direction, The compensation matrix includes 0.2, 0.2, 0.1 and 0 in order to adjust the center of mass offset of the cargo box. impact.

9. The coordinated take-off and landing control system for an unmanned vehicle and a drone according to claim 8, characterized in that: The specific steps of the collaborative module also include the following Formulate the speed adjustment strategy of the unmanned vehicle according to the status of the drone, specifically: ； Represents the center of mass offset of the cargo box Judged as level 2, Represents the center of mass offset of the cargo box Judged as level three, Represents the center of mass offset of the cargo box It is judged as level one, is the initial speed of the unmanned vehicle, Represents the adjusted speed of the autonomous vehicle; Then according to the formula Get the angle adjustment value of the unmanned vehicle , adjust the driving angle according to the angle adjustment value of the unmanned vehicle, where The center of mass of the container is Axis offset, The center of mass of the container is Axis offset, specifically the offset of the center of mass of the container get.

10. A coordinated take-off and landing control method for an unmanned vehicle and a drone, applicable to a coordinated take-off and landing control system for an unmanned vehicle and a drone as claimed in any one of claims 1 to 9, characterized in that: The following steps are involved: Step 1: Real-time perception of the UAV's motion status, prediction of the UAV's landing trajectory, and dynamic adjustment of the flight path. When geomagnetic matching fails, triggering lateral / longitudinal offset compensation or returning to a safe altitude to avoid collision risks caused by positioning drift. Step 2: Deploy grid pressure sensors on the drone landing gear to calculate the center of mass offset of the cargo box in real time and determine the center of mass offset in a graded manner; Step 3: When the cargo box tilts, the thrust of the four motors is adjusted through pseudo-inversion of the power distribution matrix to offset the impact of the center of mass offset. The speed and driving angle of the unmanned vehicle are adjusted according to the state of the cargo box to avoid the cargo box from overturning due to sharp turns or high-speed driving.

Images