Single-person intelligent dynamic sunshade method and system based on unmanned aerial vehicle

Abstract

The invention relates to the field of Internet of Things equipment control, and provides a single-person intelligent dynamic sunshade method and system based on an unmanned aerial vehicle. The method comprises the steps of calculating a target hovering height according to a user height parameter and a preset following distance parameter, controlling an unmanned aerial vehicle to take off to the target hovering height and completing unfolding of a sunshade; performing spatial positioning on the user; inputting the user space positioning data and the inertial measurement data into a Kalman filter for fusion to obtain a user state estimation result; according to a user state estimation result, performing prediction calculation on a future moving position of the user through a prediction algorithm to obtain a predicted target position; setting a tracking target, and generating a flight control instruction to drive the unmanned aerial vehicle. The system comprises an unmanned aerial vehicle flying platform, a functional assembly and a sunshade umbrella module comprising an umbrella cover assembly with a top drainage hole. According to the invention, the accuracy and stability of sunshade following are improved.

Description

Technical Field

[0001] This invention belongs to the field of Internet of Things (IoT) device control technology, and particularly relates to a single-person intelligent dynamic sunshade method and system based on drones. Background Technology

[0002] Currently, people's demands for comfort during outdoor activities are increasing. Sunshade is one of the most common needs in outdoor activities, and there is a great deal of demand for sunshade in daily life scenarios, as well as in professional work scenarios such as construction supervision, farmland inspection, and mobile vendors.

[0003] Existing sunshade solutions require the user's hands and rely on their independent operation, greatly limiting the user's freedom to perform other activities while seeking shade. Overcoming the aerodynamic interference caused by the downdraft of drones on the load of sunshades, enabling stable flight of drones carrying sunshades, and accurately following moving users to provide continuous and reliable dynamic sunshade services has become a pressing technical problem to be solved in this field. Summary of the Invention

[0004] In view of the shortcomings of the prior art, the purpose of the invention is to provide a single-person intelligent dynamic sunshade method and system based on drones.

[0005] This invention provides a single-person intelligent dynamic sunshade method based on a drone, comprising:

[0006] S1: Obtain user height parameters and preset follow distance parameters, calculate target hovering height based on user height parameters and preset follow distance parameters, control the drone to take off to the target hovering height and complete the deployment of the sunshade;

[0007] S2: Use the UWB ultra-wideband positioning module and laser rangefinder to perform spatial positioning of the user and obtain user spatial positioning data;

[0008] S3: The user space positioning data and inertial measurement data are input into a Kalman filter for fusion to obtain the user state estimation result;

[0009] S4: Based on the user state estimation results, the user's future movement location is predicted and calculated using a prediction algorithm to obtain the predicted target location;

[0010] S5: Using the predicted target position as the tracking target, generate flight control commands to drive the drone carrying the sunshade to move above the predicted target position, thereby achieving dynamic sunshade following.

[0011] According to the present invention, a single-person intelligent dynamic sunshade method based on an unmanned aerial vehicle (UAV) is provided, step S1 further includes:

[0012] S11: Receive the height value input by the user and obtain the user's height parameters;

[0013] S12: Summate the user's height parameter with the preset following distance parameter to obtain the target hovering height;

[0014] S13: Generate takeoff control commands based on the target hovering height, control the UAV to ascend vertically to the target hovering height, and then send a parachute deployment signal.

[0015] According to the present invention, a single-person intelligent dynamic sunshade method based on an unmanned aerial vehicle (UAV) is provided, step S2 further includes:

[0016] S21: Bilateral two-way ranging is performed between the airborne UWB anchor point module and the user's UWB tag module, and the user's horizontal coordinates and first altitude difference data relative to the UAV are calculated using the time difference of arrival algorithm.

[0017] S22: Utilizes a laser time-of-flight sensor to measure the distance from the drone to the user's head, obtaining vertical distance data;

[0018] S23: Perform a consistency check on the first height difference data and the vertical distance data. When the deviation exceeds a preset threshold, replace the first height difference data with the vertical distance data to obtain the corrected height difference data.

[0019] S24: Combine the horizontal coordinates with the corrected height difference data to form user spatial positioning data.

[0020] According to the present invention, a single-person intelligent dynamic sunshade method based on an unmanned aerial vehicle (UAV) is provided, step S3 further includes:

[0021] S31: Synchronously collect the user's spatial positioning data, the drone's body attitude data output by the drone's inertial measurement unit, and the user's motion data output by the user terminal's inertial measurement unit;

[0022] S32: Construct a state vector containing position, velocity and acceleration components, and use the state vector as the state variable of the Kalman filter;

[0023] S33: Based on the uniform acceleration motion model, the state vector is predicted and updated to obtain the predicted state vector;

[0024] S34: Using the user space positioning data as observations, update the predicted state vector by observation, and obtain the optimal state vector at the current moment through optimal weighted fusion;

[0025] S35: Extract the optimal position estimate, instantaneous velocity vector, and instantaneous acceleration vector from the optimal state vector to form the user state estimation result.

[0026] According to the present invention, a single-person intelligent dynamic sunshade method based on an unmanned aerial vehicle (UAV) is provided, step S4 further includes:

[0027] S41: Substitute the optimal position estimate, instantaneous velocity vector, and instantaneous acceleration vector from the user state estimation result into the uniform acceleration motion model to calculate the baseline predicted position after a preset time window;

[0028] S42: Perform threshold judgment on the angular velocity component in the user motion data. When the angular velocity amplitude exceeds the steering judgment threshold, extract the steering intention feature.

[0029] S43: Calculate the steering angle offset based on the steering intention characteristics and the motion state sequence within the historical time window;

[0030] S44: Using the predicted reference position as the reference point, the trajectory is corrected according to the steering angle offset and the predicted turning radius calculated from the instantaneous velocity vector to obtain the predicted target position.

[0031] This invention also provides a single-person intelligent dynamic sunshade system based on a drone, comprising:

[0032] Unmanned aerial vehicle (UAV) flight platforms are used to provide flight power and carry functional components;

[0033] The sunshade module includes an umbrella canopy assembly, an umbrella rib structure, an opening and closing mechanism, and a damping universal joint. The top of the umbrella canopy assembly is provided with a drainage hole, and the damping universal joint connects the sunshade module to the UAV flight platform.

[0034] The functional components include:

[0035] The spatial positioning module includes an airborne UWB anchor point module and a laser ranging sensor. The airborne UWB anchor point module is used to perform bilateral two-way ranging with the user's UWB tag module to obtain horizontal coordinates and altitude difference data. The laser ranging sensor is used to measure the vertical distance data from the UAV to the user's head.

[0036] The state fusion module is used to input the positioning data and inertial measurement data obtained by the spatial positioning module into a Kalman filter for fusion processing to obtain the user state estimation result.

[0037] The predictive control module is used to calculate the predicted target position based on the user state estimation result using a prediction algorithm, and generate flight control commands to drive the UAV flight platform to move above the predicted target position.

[0038] According to the present invention, a single-person intelligent dynamic sunshade system based on an unmanned aerial vehicle (UAV) is provided, wherein the UAV flight platform includes:

[0039] The fuselage frame is made of carbon fiber composite material or aerospace-grade aluminum alloy, and is equipped with a six-rotor layout structure and a fully enclosed rotor guard.

[0040] The propulsion system, including multiple brushless motors, an electronic speed controller, and a propeller, is used to provide lift and power response for flight.

[0041] The flight control unit includes a main controller and an inertial measurement unit. The main controller runs a real-time operating system, and the inertial measurement unit includes a three-axis gyroscope and a three-axis accelerometer.

[0042] The energy system includes a lithium polymer battery pack and a battery management system, wherein the battery management system is used to monitor the battery power and report the remaining power information to the flight control unit via a communication interface.

[0043] According to the present invention, a single-person intelligent dynamic sunshade system based on an unmanned aerial vehicle (UAV) is provided, wherein the sunshade module includes:

[0044] The umbrella assembly adopts a conical or frustoconical structure. The umbrella surface is made of high-density nylon or polyester fiber fabric treated with UV protection and waterproof coating. A circular drainage hole is opened at the top of the umbrella surface.

[0045] The umbrella rib structure adopts a space truss structure without a central bar. The main umbrella ribs and secondary spokes are connected by micro hinges to form a triangular mechanical structure, which is used to execute the umbrella surface to form a sunshade structure.

[0046] The opening and closing mechanism includes a torsion spring, a miniature DC servo motor, a winch, and a high-strength nylon cable. The torsion spring provides power for opening the umbrella, and the servo motor drives the winch to close the umbrella via the cable.

[0047] The connection mechanism includes a quick-release module and the damping universal joint. The quick-release module integrates electrical contacts for supplying power to the servo motor and transmitting control signals. The damping universal joint provides deflection freedom and has a built-in damping oil cavity for absorbing high-frequency vibrations.

[0048] According to the present invention, a single-person intelligent dynamic sunshade system based on an unmanned aerial vehicle (UAV) is provided, wherein the functional components further include:

[0049] The aerodynamic stability control module is used to guide the downwash airflow of the UAV along the umbrella surface through the umbrella assembly, release the downwash airflow through the vent holes, and dampen and attenuate the high-frequency vibration caused by airflow disturbance through the damping universal joint. When vibration characteristics caused by crosswind are detected, the motor output of the power system of the UAV flight platform is adjusted to generate a reverse torque for wind disturbance control.

[0050] According to the present invention, a single-person intelligent dynamic sunshade system based on an unmanned aerial vehicle (UAV) is provided, wherein the functional components further include:

[0051] The safety monitoring module is used to continuously monitor the communication link status between the UAV and the user terminal, the remaining power output of the UAV flight platform's energy system, and the signal quality of the positioning data acquired by the spatial positioning module.

[0052] When the duration of continuous packet loss in the communication link exceeds the first time threshold, the drone flight platform is controlled to hover in place.

[0053] When the packet loss duration exceeds the second time threshold, the opening and closing mechanism is triggered to retract the parachute and control the UAV flight platform to return to the initial positioning point to perform landing.

[0054] When the remaining battery power is detected to be lower than the first battery power threshold, a battery power warning signal is generated; when the remaining battery power is lower than the second battery power threshold, the opening and closing mechanism is automatically triggered to retract the parachute and control the UAV flight platform to perform the return landing process.

[0055] This invention provides a single-person intelligent dynamic sunshade method and system based on a drone. First, by employing a spatial positioning scheme combining an ultra-wideband (UWB) positioning module and a laser rangefinder, it can acquire the user's three-dimensional spatial coordinates with centimeter-level accuracy in complex outdoor environments, unaffected by lighting conditions, providing a reliable data foundation for subsequent precise following. Second, this invention uses a Kalman filter algorithm to fuse multi-source sensor data, effectively filtering out positioning noise and measurement errors to obtain a smooth and stable user state estimate, avoiding drone jitter caused by instantaneous sensor fluctuations. Furthermore, this invention, based on a kinematic prediction model and a turning intention recognition prediction algorithm, enables the drone to predict the user's movement trajectory and fly to the predicted location in advance, fundamentally eliminating following delay and achieving a natural and smooth accompanying flight experience. Users will not feel any lag in the sunshade when walking quickly or turning.

[0056] The sunshade module provided by this invention uses an umbrella assembly with a top vent design to cleverly transform the downwash airflow from the drone into a guide channel, significantly reducing the pressure difference and vortex generated by the airflow impact. Combined with the passive absorption of high-frequency vibration by the damped universal joint and the synergistic effect of the active anti-wind disturbance control algorithm, it completely solves the stability problem of large-area loads under the drone, enabling the system to maintain stable operation under different wind speed conditions.

[0057] In addition, the present invention provides a multi-level security monitoring mechanism that monitors communication status, power status and signal quality in real time. It can promptly implement protective measures such as hovering, parachute retraction and return to home when abnormal situations occur, ensuring the reliability and safety of the system under various emergencies and providing users with a safe and reliable guarantee for use. Attached Figure Description

[0058] The accompanying drawings are for illustrative purposes only and are not intended to limit the invention. Throughout the drawings, the same reference numerals denote the same parts. It is obvious that the drawings described below are merely some embodiments of the present invention, and those skilled in the art can obtain other drawings based on these drawings.

[0059] Figure 1 A schematic diagram of a single-person intelligent dynamic sunshade method based on an unmanned aerial vehicle (UAV) provided in an embodiment of the present invention;

[0060] Figure 2 A schematic diagram of the overall structure of a single-person intelligent dynamic sunshade system based on an unmanned aerial vehicle (UAV) provided in an embodiment of the present invention;

[0061] Figure 3 This invention provides a schematic diagram of the functional components in a drone-based single-person intelligent dynamic sunshade system.

[0062] Reference numerals: 1. Unmanned aerial vehicle (UAV) flight platform; 2. Sunshade module; 100. Spatial positioning module; 200. State fusion module; 300. Predictive control module. Detailed Implementation

[0063] To enable those skilled in the art to better understand the technical solutions in the embodiments of the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. It should be understood that these descriptions are merely exemplary and are not intended to limit the scope of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0064] Furthermore, descriptions of well-known structures and techniques are omitted in the following description to avoid unnecessarily obscuring the concepts disclosed in this invention.

[0065] In the description of this invention, it should be noted that, unless otherwise explicitly specified and limited, the terms "center," "upper," "lower," "left," "right," "vertical," "horizontal," "inner," and "outer," etc., indicating orientation or positional relationships based on the orientation or positional relationships shown in the accompanying drawings, are only for the convenience of describing the invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation, and therefore should not be construed as a limitation of the invention. Furthermore, the terms "first," "second," and "third" are used for descriptive purposes only and should not be construed as indicating or implying relative importance. The terms "installed," "connected," and "linked" should be interpreted broadly; for example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; and they can refer to the internal communication of two components. Those skilled in the art can understand the specific meaning of the above terms in this invention based on the specific circumstances.

[0066] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. When the following description relates to the drawings, unless otherwise indicated, the same numerals in different drawings denote the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present invention. Rather, they are merely examples of methods and systems consistent with some aspects of the invention as detailed in the appended claims.

[0067] The embodiments of the present invention are described below with reference to the figures.

[0068] like Figure 1 As shown, this invention provides a single-person intelligent dynamic sunshade method based on a drone, comprising:

[0069] S1: Obtain user height parameters and preset follow distance parameters, calculate target hovering height based on user height parameters and preset follow distance parameters, control the drone to take off to the target hovering height and complete the deployment of the sunshade.

[0070] Step S1 further includes:

[0071] S11: Receive the height value input by the user and obtain the user's height parameters.

[0072] In one specific embodiment, the user opens a dedicated app on their smartphone, and the device management interface automatically searches for and discovers nearby drone devices via Bluetooth Low Energy protocol. After pairing and binding, the app guides the phone and drone to establish a Wi-Fi Direct connection as the main data link.

[0073] Subsequently, the app interface prompts the user to input their height information. The user enters their specific height value via the numeric keypad. The app encapsulates this value into a height parameter data packet and sends it to the drone's flight control system via a Wi-Fi link. Upon receiving the packet, the flight control system stores the value in its memory register as the user's height parameter. The app also provides a follow distance option, allowing the user to select a preset value of 20 cm, 25 cm, or 30 cm. Once selected, this value serves as the preset follow distance parameter and is also sent to the flight control system via a Wi-Fi link for storage.

[0074] S12: Summing the user's height parameter with the preset following distance parameter to obtain the target hovering height.

[0075] Furthermore, the flight control system reads the user's height parameters and preset follow distance parameters from the memory register, performs an addition operation to add the two together, and the result is the target hovering altitude. Subsequently, the flight control system writes this target hovering altitude value into the flight mission queue as the altitude control target during takeoff. At the same time, the flight control system records the current GPS coordinates and barometer readings as the takeoff origin, which is stored as the Home point for subsequent return-to-home positioning.

[0076] S13: Generate takeoff control commands based on the target hovering height, control the UAV to ascend vertically to the target hovering height, and then send a parachute deployment signal.

[0077] In step S13, the flight control system generates a takeoff control command, which includes a vertical climb mode indicator and a target hovering altitude value. Subsequently, the flight control system sends a PWM signal to the electronic speed controller, driving the six brushless motors to synchronously increase their speed, and the UAV begins to ascend vertically. During the ascent, the flight control system reads barometer data and inertial measurement unit data at a frequency of 100Hz. The barometer data is converted into a relative altitude value after temperature compensation and sea-level pressure correction.

[0078] After obtaining the relative altitude value, the flight control system compares the relative altitude value with the target hovering altitude in real time. When the relative altitude value reaches the target hovering altitude minus 0.5 meters as the pre-deceleration altitude, the flight control system reduces the motor speed to achieve deceleration and climbing. When the difference between the relative altitude value and the target hovering altitude is less than 0.1 meters, the flight control system switches to hovering mode and adjusts the motor output through the PID control algorithm to maintain a stable altitude.

[0079] After hovering and stabilizing, the flight control system sends a parachute deployment PWM signal to the servo motor control pin of the parachute module. Upon receiving the signal, the servo motor releases the locking mechanism, and the pre-compressed torsion spring releases energy to push the parachute ribs to unfold radially. The mechanical latch at the end of the parachute ribs automatically engages and triggers a micro switch in the fully deployed position. The change in the state of the micro switch generates a level signal that is fed back to the flight control system. Upon receiving this feedback signal, the flight control system confirms that the parachute deployment is complete.

[0080] S2: The user's spatial positioning is achieved through the UWB ultra-wideband positioning module and the laser rangefinder, and the user's spatial positioning data is obtained.

[0081] Step S2 further includes:

[0082] S21: The user's horizontal coordinates and first altitude difference data relative to the UAV are calculated by using the airborne UWB anchor point module and the user's UWB tag module for bilateral two-way ranging and the time difference of arrival algorithm.

[0083] Furthermore, the airborne UWB anchor module provided by this invention integrates four UWB receiving antennas, fixed to the bottom of the drone in a square geometric layout with an antenna spacing of 15 cm. The user-carried UWB tag module is built into a smartphone or dedicated wristband, serving as the signal transmitter. The UWB tag module transmits nanosecond-level pulse signals at fixed time intervals. The four antennas of the airborne UWB anchor module receive these pulse signals respectively. Due to the different spatial distances between the four antennas and the tag, there is a nanosecond-level time difference in the arrival time of the pulse signal at each antenna. A high-precision timer built into the UWB anchor module records the precise timestamp of the pulse signal received by each antenna, and the arrival time difference data is obtained by calculating the difference between the four timestamps.

[0084] The invention employs a bilateral, two-way ranging protocol. After the tag transmits a signal, it waits for the anchor point's response. Upon receiving the signal, the anchor point immediately sends a response signal. The tag records the round-trip time, and the anchor point similarly records the processing delay time. Both parties eliminate the impact of clock deviations through data exchange. Subsequently, the invention establishes a set of spatial geometric equations based on the time difference of arrival data. This set of equations includes the distance relationship between the tag and the four antennas. Solving this set of equations using the least squares method yields the tag's coordinates in a three-dimensional coordinate system with the anchor point as the origin. These coordinates include the X-coordinate in the forward / backward direction, the Y-coordinate in the left / right direction, and the Z-coordinate in the vertical direction. The X and Y coordinates form the horizontal coordinates, and the Z-coordinate represents the first height difference data.

[0085] S22: Utilizes a laser time-of-flight sensor to measure the distance from the drone to the user's head, obtaining vertical distance data.

[0086] Furthermore, the laser time-of-flight sensor is installed at the center of the bottom of the drone. The transmitter emits modulated laser pulses directly downwards. These pulses travel at the speed of light and are reflected upon encountering the user's head or shoulder. The reflected light is captured by the sensor's receiver. The sensor's built-in high-speed timing circuit accurately measures the round-trip time of the laser pulse from emission to reception. This time value is multiplied by the speed of light and divided by 2 to obtain the one-way distance from the sensor to the reflecting surface, which is the vertical distance data. The sensor continuously emits laser pulses at a frequency of 50Hz and calculates the distance. After each calculation, the vertical distance data is transmitted to the main controller of the flight control system via the I2C bus.

[0087] S23: Perform a consistency check on the first height difference data and the vertical distance data. When the deviation exceeds a preset threshold, replace the first height difference data with the vertical distance data to obtain the corrected height difference data.

[0088] In step S23, the flight control system simultaneously receives the first altitude difference data and the vertical distance data. Theoretically, these two sets of data should be consistent, both representing the vertical distance between the UAV and the user. Subsequently, this invention calculates the difference between the two sets of data, subtracting the vertical distance data from the first altitude difference data to obtain the deviation value. Then, this invention sets a preset threshold of 5 centimeters. When the absolute value of the deviation is less than the preset threshold, the two sets of data are considered to be in good agreement, and the first altitude difference data is retained as the corrected altitude difference data. When the absolute value of the deviation is greater than or equal to the preset threshold, it is determined that the UWB measurement data may be affected by multipath interference or signal obstruction. This invention prioritizes the direct measurement result of laser ranging, replacing the first altitude difference data with the vertical distance data, and using the replaced value as the corrected altitude difference data.

[0089] S24: Combine the horizontal coordinates with the corrected height difference data to form user spatial positioning data.

[0090] In step S24, the present invention combines the X and Y coordinate values ​​from the horizontal coordinates obtained in step S21 with the corrected altitude difference data obtained in step S23 to form a three-dimensional vector. The three components of this three-dimensional vector represent the user's distance relative to the UAV in the forward / backward, left / right, and vertical directions, respectively. This three-dimensional vector is the user's spatial positioning data. Finally, the present invention packages the three components of the user's spatial positioning data into a data frame. The data frame contains timestamp information to identify the acquisition time of the positioning data. Subsequently, the data frame is written into the positioning data buffer queue of the flight control system for subsequent state fusion processing.

[0091] S3: The user space positioning data and inertial measurement data are input into a Kalman filter for fusion to obtain the user state estimation result.

[0092] Step S3 further includes:

[0093] S31: Synchronously collect the user's spatial positioning data, the drone's body attitude data output by the drone's inertial measurement unit, and the user's motion data output by the user terminal's inertial measurement unit.

[0094] In step S31, the flight control system reads the latest user space positioning data from the positioning data buffer queue. This data includes three component values: X coordinate, Y coordinate, and corrected altitude difference data, as well as a timestamp.

[0095] In addition, the UAV's inertial measurement unit continuously outputs three-axis gyroscope data and three-axis accelerometer data at a frequency of 200Hz. The three-axis gyroscope data includes the roll angular velocity around the X-axis, the pitch angular velocity around the Y-axis, and the yaw angular velocity around the Z-axis. The three-axis accelerometer data includes the acceleration components in the X, Y, and Z directions in the body coordinate system. The flight control system reads these data and calculates the UAV's roll angle, pitch angle, and yaw angle through attitude calculation algorithms. These three angle values ​​constitute the body attitude data.

[0096] At the same time, the inertial measurement unit built into the user's mobile phone also collects triaxial acceleration and triaxial angular velocity at a frequency of 100Hz. The mobile app packages this raw data into user motion data and sends it to the flight control system in real time via Wi-Fi link.

[0097] After receiving user motion data, the flight control system synchronizes and aligns it with user spatial positioning data and aircraft attitude data according to timestamps. For data with incompletely consistent timestamps, a linear interpolation method is used to generate interpolated data for the corresponding time, ensuring that the three sets of data are strictly aligned in the time dimension. Finally, the flight control system writes the aligned three sets of data into the fusion processing input buffer.

[0098] S32: Construct a state vector containing position, velocity, and acceleration components, and use the state vector as the state variable of the Kalman filter.

[0099] In step S32, the present invention constructs a nine-dimensional state vector. The first three components of the state vector are position components, representing the user's X position, Y position and Z position in three-dimensional space, respectively. The fourth to sixth components are velocity components, representing the user's velocity in the X, Y and Z directions, respectively. The seventh to ninth components are acceleration components, representing the user's acceleration in the X, Y and Z directions, respectively.

[0100] This invention uses the nine-dimensional state vector as the state variable of the Kalman filter, allocates a nine-element array in the flight control system memory to store the current value of the state vector, and constructs a 9×9-dimensional state covariance matrix. The diagonal elements of the covariance matrix represent the uncertainty of each state component, and the off-diagonal elements represent the correlation between different state components.

[0101] Finally, this invention initializes the state covariance matrix as a diagonal matrix, and sets the initial uncertainty of the diagonal elements according to the sensor accuracy. The initial uncertainty of the position component is set to 0.05 meters, the initial uncertainty of the velocity component is set to 0.1 meters per second, and the initial uncertainty of the acceleration component is set to 0.2 meters per second squared.

[0102] S33: Based on the uniform acceleration motion model, the state vector is predicted and updated to obtain the predicted state vector.

[0103] In step S33, this invention establishes a state transition relationship based on a uniform acceleration motion model, which assumes that the user moves with constant acceleration within a short time interval. Specifically, the flight control system records the timestamp of the last filter update and the timestamp of the current moment; the difference between the two is the time interval Δt. According to the law of uniform acceleration motion, the predicted position is equal to the previous position plus the previous velocity multiplied by the time interval, plus the previous acceleration multiplied by half the square of the time interval; the predicted velocity is equal to the previous velocity plus the previous acceleration multiplied by the time interval; and the predicted acceleration is assumed to remain constant and equal to the previous acceleration.

[0104] Subsequently, this invention expresses these relationships as a state transition matrix, which is a 9×9 dimensional matrix with 1s on the main diagonal, Δt as the element in the velocity column corresponding to the position row, 0.5Δt squared as the element in the acceleration column corresponding to the position row, and Δt as the element in the acceleration column corresponding to the velocity row. This invention multiplies the state transition matrix on the left by the state vector from the previous time step to obtain the predicted state vector.

[0105] Meanwhile, this invention updates the state covariance matrix by multiplying the state transition matrix by the state covariance matrix on the left and right, and then adding the process noise covariance matrix to obtain the prediction covariance matrix. The process noise covariance matrix reflects the uncertainty of the motion model, and the process noise of the acceleration component is set to 0.5 m / s².

[0106] S34: Using the user space positioning data as observations, update the predicted state vector by observation, and obtain the optimal state vector at the current moment through optimal weighted fusion.

[0107] In step S34, the present invention uses the three components of the user's spatial positioning data as observation values ​​to construct a three-dimensional observation vector. This observation vector includes X-coordinates, Y-coordinates, and corrected height difference data. Subsequently, the present invention establishes an observation matrix, which is a 3×9 dimensional matrix. The first column of the first row has an element of 1 and the rest are 0; the second column of the second row has an element of 1 and the rest are 0; and the third column of the third row has an element of 1 and the rest are 0. This matrix indicates that the observation value corresponds only to the position component in the state vector.

[0108] Subsequently, this invention constructs an observation noise covariance matrix, which is a 3×3 diagonal matrix. The diagonal elements are set according to the measurement accuracy of UWB and laser ranging. The observation noise at the horizontal position is set to 0.05 meters, and the observation noise at the vertical position is set to 0.02 meters.

[0109] The present invention then calculates the Kalman gain matrix, which is equal to the prediction covariance matrix multiplied by the transpose of the observation matrix, multiplied by the observation matrix multiplied by the prediction covariance matrix multiplied by the transpose of the observation matrix, plus the inverse matrix of the observation noise covariance matrix.

[0110] After constructing the aforementioned matrix, this invention multiplies the observation matrix by the predicted state vector to obtain the predicted observation value, subtracts the predicted observation value from the actual observation vector to obtain the observation residual, multiplies the Kalman gain matrix by the observation residual to obtain the state correction, and adds the state correction to the predicted state vector to obtain the optimal state vector at the current time. Simultaneously, this invention updates the state covariance matrix by subtracting the Kalman gain matrix from the identity matrix, multiplying it by the observation matrix, and then multiplying it by the predicted covariance matrix to obtain the updated covariance matrix.

[0111] S35: Extract the optimal position estimate, instantaneous velocity vector, and instantaneous acceleration vector from the optimal state vector to form the user state estimation result.

[0112] Furthermore, in step S35, the present invention extracts the first to third elements from the optimal state vector at the current moment. These three elements are the optimal estimates of the X position, Y position, and Z position, respectively, and combine these three values ​​into a three-dimensional vector as the optimal position estimate. The present invention extracts the fourth to sixth elements. These three elements are the optimal estimates of the X velocity, Y velocity, and Z velocity, respectively, and combine these three values ​​into a three-dimensional vector as the instantaneous velocity vector. The present invention extracts the seventh to ninth elements. These three elements are the optimal estimates of the X acceleration, Y acceleration, and Z acceleration, respectively, and combine these three values ​​into a three-dimensional vector as the instantaneous acceleration vector.

[0113] Finally, this invention packages the optimal position estimate, instantaneous velocity vector, and instantaneous acceleration vector into a data structure. This data structure is appended with the timestamp of the current moment. The entire data structure is the user state estimation result. This invention writes the result into the input buffer of the prediction algorithm.

[0114] S4: Based on the user state estimation results, the user's future movement location is predicted and calculated using a prediction algorithm to obtain the predicted target location.

[0115] Step S4 further includes:

[0116] S41: Substitute the optimal position estimate, instantaneous velocity vector, and instantaneous acceleration vector from the user state estimation result into the uniform acceleration motion model to calculate the baseline predicted position after a preset time window.

[0117] Furthermore, this invention reads the three component values ​​of the optimal position estimate from the user state estimation result, as well as the three component values ​​of the instantaneous velocity vector and the three component values ​​of the instantaneous acceleration vector. Subsequently, this invention sets a preset time window of 0.4 seconds, which is determined based on a combination of the user's typical walking speed and the system response delay.

[0118] Then, the present invention uses a uniform acceleration motion model to calculate the position after a preset time window. The reference predicted position component in the X direction is equal to the X-direction component of the optimal position estimate plus the X-direction component of the instantaneous velocity vector multiplied by 0.4, plus the X-direction component of the instantaneous acceleration vector multiplied by 0.4 squared and divided by 2. The reference predicted position components in the Y and Z directions are obtained using the same calculation method.

[0119] After calculation, the present invention combines the reference predicted position components in three directions into a three-dimensional vector, which is the reference predicted position, representing the spatial coordinates that the user will reach after 0.4 seconds if they continue to move along the current movement trend.

[0120] S42: Perform threshold judgment on the angular velocity component in the user motion data. When the angular velocity amplitude exceeds the steering judgment threshold, extract the steering intention feature.

[0121] This invention extracts three-axis angular velocities from user motion data: the roll angular velocity ω_x around the X-axis, the pitch angular velocity ω_y around the Y-axis, and the yaw angular velocity ω_z around the Z-axis. This invention calculates the magnitude of the three-axis angular velocities, which is equal to the square root of the sum of the squares of the three angular velocity components. This invention sets a steering determination threshold of 30 degrees per second, which is statistically determined based on the steering characteristics of a normal human walking. This invention compares the calculated angular velocity magnitude with the steering determination threshold; when the angular velocity magnitude is greater than 30 degrees per second, it determines that the user has a steering intention. This invention further analyzes the sign and magnitude of the yaw angular velocity ω_z; a positive ω_z value indicates a left turn intention, and a negative ω_z value indicates a right turn intention. The absolute value of ω_z reflects the degree of steering aggression. This invention packages the steering direction, angular velocity magnitude, and yaw angular velocity into a steering intention feature, which includes a steering presence flag, a steering direction flag, and a steering intensity value.

[0122] S43: Calculate the steering angle offset based on the steering intention characteristics and the motion state sequence within the historical time window.

[0123] This invention maintains a historical time window of the motion state sequence of the most recent 2 seconds, stored in a circular buffer with a capacity of 200 elements, each element recording the user's state estimation result at a given moment. This invention extracts the most recent 20 elements from the buffer and calculates the projection direction angle of the instantaneous velocity vector on the horizontal plane. The direction angle is obtained by calculating the ratio of V_y to V_x using the arctangent function. This invention performs linear fitting on these 20 direction angles; the fitting slope reflects the rate of change of the direction angle, i.e., the historical average value of the steering angular velocity. This invention weights and fuses the current yaw angular velocity ω_z with the historical average steering angular velocity, with weighting coefficients of 0.7 and 0.3. The fusion result is used as the corrected steering angular velocity. This invention multiplies the corrected steering angular velocity by a preset time window of 0.4 seconds to obtain the steering angle offset. This offset represents the user's expected steering angle relative to the current direction of motion within the next 0.4 seconds, in radians.

[0124] S44: Using the predicted reference position as the reference point, the trajectory is corrected according to the steering angle offset and the predicted turning radius calculated from the instantaneous velocity vector to obtain the predicted target position.

[0125] This invention extracts the horizontal component from the instantaneous velocity vector, then calculates the horizontal velocity, and subsequently calculates the predicted turning radius based on the steering angle offset and the horizontal velocity. The turning radius is equal to the horizontal velocity divided by the steering angle offset divided by a preset time window.

[0126] Subsequently, this invention establishes a local coordinate system starting from the reference predicted position. The origin of this coordinate system is the reference predicted position, and the X-axis points to the horizontal projection direction of the current instantaneous velocity vector. This invention calculates the arc trajectory based on the steering angle offset. The center of the arc is located perpendicular to the current velocity direction and at a distance equal to the turning radius. The starting point of the arc is the reference predicted position, and the central angle corresponding to the arc is equal to the steering angle offset.

[0127] After setting the arc, this invention calculates the coordinates of the arc's endpoint. The X-coordinate of this endpoint in the local coordinate system is equal to the sine of the turning radius multiplied by the steering angle offset, and the Y-coordinate is equal to the cosine of the turning radius multiplied by 1 minus the steering angle offset. The sign of the Y-coordinate is determined based on the steering direction. Finally, this invention transforms the endpoint coordinates from the local coordinate system back to the global coordinate system. The transformation process includes rotation and translation transformations. The rotation angle is the current velocity direction angle, and the translation amount is the reference predicted position coordinates. The transformed coordinates are the predicted target position, which comprehensively considers the user's linear movement trend and steering intention.

[0128] S5: Using the predicted target position as the tracking target, generate flight control commands to drive the drone carrying the sunshade to move above the predicted target position, thereby achieving dynamic sunshade following.

[0129] In step S5, the present invention uses the three component values ​​of the predicted target position as the target coordinates for flight control. These coordinates represent the spatial position that the UAV should reach in the UAV's body coordinate system. Subsequently, the present invention calculates the position error vector between the current UAV position and the predicted target position. The three components of this error vector are the X-direction error, Y-direction error, and Z-direction error.

[0130] After calculating the error, this invention inputs the position error vector into a PID controller. The PID controller includes a proportional, integral, and derivative component. The proportional component calculates the error and multiplies it by the proportional coefficient; the integral component accumulates the historical error and multiplies it by the integral coefficient; and the derivative component calculates the rate of change of the error and multiplies it by the derivative coefficient. The outputs of the three components are added together to obtain the control quantity. Simultaneously, this invention calculates the pitch and roll angles that the UAV should adopt based on the control quantities in the X and Y directions, and calculates the total throttle based on the control quantity in the Z direction.

[0131] This invention converts the desired pitch angle, desired roll angle, and total throttle into PWM signals for six motors. The conversion process takes into account the layout and rotation direction of the six rotors. The PWM difference between the front and rear motors generates pitch torque, the PWM difference between the left and right motors generates roll torque, and the average PWM value of all motors controls the total lift.

[0132] Finally, the invention sends the calculated six PWM signals to six electronic speed controllers through the flight control output pins. The electronic speed controllers adjust the speed of the corresponding brushless motors according to the PWM duty cycle. The coordinated change of the speed of the six motors drives the drone to move towards the predicted target position. The sunshade module carried by the drone moves synchronously with the drone, and the projection of the sunshade always covers the user's head.

[0133] like Figure 2 and Figure 3 As shown, the present invention also provides a single-person intelligent dynamic sunshade system based on a drone, comprising:

[0134] Unmanned aerial vehicle (UAV) flight platform 1, used to provide flight power and carry functional components;

[0135] The sunshade module 2 includes an umbrella canopy assembly, an umbrella rib structure, an opening and closing mechanism, and a damping universal joint. The top of the umbrella canopy assembly is provided with a drainage hole, and the damping universal joint connects the sunshade module 2 to the UAV flight platform 1.

[0136] The functional components include:

[0137] The spatial positioning module 100 includes an airborne UWB anchor point module and a laser ranging sensor. The airborne UWB anchor point module is used to perform bilateral bidirectional ranging with the user's UWB tag module to obtain horizontal coordinates and height difference data. The laser ranging sensor is used to measure the vertical distance data from the UAV to the user's head.

[0138] The state fusion module 200 is used to input the positioning data and inertial measurement data acquired by the spatial positioning module 100 into a Kalman filter for fusion processing to obtain the user state estimation result.

[0139] The prediction control module 300 is used to calculate the predicted target position based on the user state estimation result using a prediction algorithm, and generate flight control commands to drive the UAV flight platform 1 to move above the predicted target position.

[0140] Furthermore, the UAV-based single-person intelligent dynamic sunshade system provided by this invention comprises two main parts: a UAV flight platform and a sunshade module, as well as multiple functional components installed on the UAV flight platform. The UAV flight platform, serving as the power foundation and aerial transport platform for the entire system, is responsible for providing flight capability, bearing all loads, and executing flight commands. The sunshade module is connected to the UAV flight platform via a damped universal joint and suspended below the UAV, providing sunshade for the user. The functional components include a spatial positioning module, a state fusion module, a predictive control module, and the aforementioned aerodynamic stability control module and safety monitoring module. These multiple modules work together to achieve automatic tracking and stable sunshade for the user.

[0141] The spatial positioning module includes an airborne UWB anchor module and a laser rangefinder. The airborne UWB anchor module employs a UWB system with a bilateral, bidirectional ranging DS-TWR algorithm. The user end is a smartphone supporting UWB functionality or a dedicated miniature UWB tag, which can be integrated into a wristband or lanyard as a signal transmitter. The airborne UWB anchor module carries at least four UWB receiving antennas, arranged in a specific geometric layout, such as a square, to form a miniature positioning base station. During operation, by calculating the minute time difference (TDoA) between the arrival of the UWB pulse signal at different antennas on the drone, the absolute 3D spatial vector of the tag (i.e., the user) relative to the drone's anchor point is calculated, including the precise distance and angle in front / back, left / right, and up / down directions, with an accuracy of ±5cm. UWB technology has strong resistance to multipath interference, good penetration, and is unaffected by ambient light, providing stable, reliable, and high-refresh-rate positioning data.

[0142] The laser rangefinder uses a laser time-of-flight (ToF) sensor, mounted vertically downwards on the bottom of the drone. This sensor continuously and directly measures the vertical distance from the bottom of the drone to the user's head or shoulder. The flight controller cross-validates the altitude calculated by UWB with the distance measured directly by ToF. If there is a significant discrepancy between the two data points, for example, due to a brief obstruction of the UWB signal, the system prioritizes the more direct ToF data as the basis for maintaining a safe altitude.

[0143] The unmanned aerial vehicle (UAV) flight platform 1 includes:

[0144] The fuselage frame is made of carbon fiber composite material or aerospace-grade aluminum alloy, and is equipped with a six-rotor layout structure and a fully enclosed rotor guard.

[0145] The propulsion system, including multiple brushless motors, an electronic speed controller, and a propeller, is used to provide lift and power response for flight.

[0146] The flight control unit includes a main controller and an inertial measurement unit. The main controller runs a real-time operating system, and the inertial measurement unit includes a three-axis gyroscope and a three-axis accelerometer.

[0147] The energy system includes a lithium polymer battery pack and a battery management system, wherein the battery management system is used to monitor the battery power and report the remaining power information to the flight control unit via a communication interface.

[0148] Furthermore, the fuselage frame utilizes carbon fiber composite materials or aerospace-grade aluminum alloy as the main frame material, with T700 grade carbon fiber composites being the preferred choice, meeting structural strength and stiffness requirements while achieving extreme lightweighting. The fuselage frame is configured with a six-rotor layout, which provides power redundancy, meaning that a controlled landing can still be achieved even if a single motor fails. A fully enclosed rotor guard is installed around the fuselage frame, made of tough and lightweight PP plastic material, with an aerodynamically optimized structure to minimize its impact on flight efficiency.

[0149] The power system comprises six brushless motors, six electronic speed controllers, and six propellers. The brushless motors are high-KV external rotor brushless motors, providing sufficient lift power density and rapid torque response. The electronic speed controllers utilize 32-bit ESC with high refresh rates, ensuring that flight control commands are accurately and quickly transmitted to the motors. The propellers employ carbon fiber or nylon composite blades specifically designed for quiet operation and efficiency, with their diameter and pitch calculated to match the total weight of the UAV plus the parasol system and the desired maneuverability.

[0150] The flight control unit includes a main controller and an inertial measurement unit (IMU). The main controller is powered by a high-performance 32-bit microprocessor, preferably an ARM Cortex-M7, running a real-time operating system (RTOS). The IMU includes a high-precision three-axis gyroscope and a three-axis accelerometer for sensing the UAV's attitude, angular velocity, and acceleration. Furthermore, the system preferably incorporates multiple IMU sensors for redundancy. The flight control unit also includes a barometer for measuring relative altitude, a compass / magnetometer for heading reference, and a GNSS module for global position information to initialize positioning, enable one-click return-to-home, and implement geofencing functions.

[0151] The energy system includes a lithium polymer or lithium-ion battery pack and a battery management system. The battery pack voltage platform is selectable between 11.1V (3S) and 14.8V (4S), with capacities ranging from 2000mAh to 4000mAh. The battery management system is responsible for battery charge and discharge management, power monitoring, short-circuit protection, and overcharge and over-discharge protection. It also reports accurate remaining power information to the flight control unit in real time via an SMBus communication interface. The system comes with a portable fast-charging box that supports fast-charging protocols and can fully charge the battery in one hour.

[0152] The sunshade module 2 includes:

[0153] The umbrella assembly adopts a conical or frustoconical structure. The umbrella surface is made of high-density nylon or polyester fiber fabric treated with UV protection and waterproof coating. A circular drainage hole is opened at the top of the umbrella surface.

[0154] The umbrella rib structure adopts a space truss structure without a central bar. The main umbrella ribs and secondary spokes are connected by micro hinges to form a triangular mechanical structure, which is used to execute the umbrella surface to form a sunshade structure.

[0155] The opening and closing mechanism includes a torsion spring, a miniature DC servo motor, a winch, and a high-strength nylon cable. The torsion spring provides power for opening the umbrella, and the servo motor drives the winch to close the umbrella via the cable.

[0156] The connection mechanism includes a quick-release module and the damping universal joint. The quick-release module integrates electrical contacts for supplying power to the servo motor and transmitting control signals. The damping universal joint provides deflection freedom and has a built-in damping oil cavity for absorbing high-frequency vibrations.

[0157] Furthermore, the canopy assembly adopts a conical or frustum-shaped design. Its aerodynamic shape effectively guides rather than resists the downwash airflow from the drone. A circular vent with a diameter of 80-120mm is located at the top of the canopy, allowing most of the downwash airflow to pass smoothly, greatly reducing vortex and pressure drag caused by airflow impacting the flat canopy surface. Additionally, the canopy is made of high-density nylon or polyester fiber fabric with a UPF 50+ UV protection and waterproof coating, and the fabric weight is less than 80g / m². 2 .

[0158] The umbrella rib structure employs a space truss structure without a central strut, consisting of 4-6 main ribs and 8-12 secondary spokes interwoven to form a stable triangular mechanical structure. The main ribs are made of carbon fiber tubing, while the secondary spokes use thinner carbon fiber rods. All connection points utilize micro-CNC aluminum alloy hinges and stainless steel pins to ensure smooth operation and durability. All ribs can be folded and secured to form a compact cylindrical shape.

[0159] The opening and closing mechanism includes a torsion spring, a miniature DC servo motor, a winch, and a high-strength nylon cable. The torsion spring, with its preload design, serves as the primary power source for deployment, ensuring rapid and reliable opening. A mechanical self-locking latch is located at the fully deployed position of the parachute ribs, emitting a click to confirm locking and prevent accidental closure during flight. The miniature DC servo motor drives the miniature winch, which, via the high-strength nylon cable, synchronously pulls the ends of all main parachute ribs to overcome spring force and retract the parachute. The servo motor receives PWM control signals directly from the UAV flight controller via cable.

[0160] The connection mechanism includes a quick-release module and a damping universal joint. The quick-release module employs a mechanical quick-release design similar to a camera hot shoe or dovetail groove, allowing users to install and remove the umbrella module in seconds. The quick-release interface integrates electrical contacts for powering the servo motor and sending control signals. The damping universal joint is the core component between the quick-release module and the umbrella, providing ±10° to ±15° of deflection freedom. The ball joint's head structure is encapsulated in a chamber filled with high-viscosity silicone-based damping oil, passively absorbing and suppressing high-frequency, small-amplitude swaying caused by gusts or sudden movements, making the umbrella's attitude changes smoother and gentler rather than directly and rigidly transmitted to the drone.

[0161] The functional components also include:

[0162] The aerodynamic stability control module is used to guide the downwash airflow of the UAV along the umbrella surface through the umbrella assembly, release the downwash airflow through the vent holes, and dampen and attenuate the high-frequency vibration caused by airflow disturbance through the damping universal joint. When vibration characteristics caused by crosswind are detected, the motor output of the power system of the UAV flight platform 1 is adjusted to generate a reverse torque for wind disturbance control.

[0163] Furthermore, the aerodynamic stabilization control module guides the downwash airflow from the drone along the canopy using the conical canopy structure of the sunshade module, and releases the downwash airflow through the vent holes at the top of the canopy. The aerodynamic shape of the conical canopy effectively guides the airflow, and the vent holes with a diameter of 80-120mm allow most of the downwash airflow to pass smoothly, greatly reducing vortex and pressure drag caused by airflow impact, fundamentally solving the problem of severe canopy swaying caused by the drone's downwash airflow.

[0164] The damping universal joint dampens and attenuates high-frequency vibrations caused by airflow disturbances. The universal joint ball joint structure is encapsulated in a chamber filled with high-viscosity silicone-based damping oil, passively absorbing and suppressing high-frequency small-amplitude swaying caused by gusts or sudden movements, making the umbrella's attitude changes smoother and gentler.

[0165] When vibration characteristics caused by crosswinds are detected, the aerodynamic stability control module adjusts the motor output of the UAV flight platform's power system to generate a reverse torque for wind disturbance control. The wind disturbance control algorithm can identify canopy swaying caused by crosswinds and actively counteracts the swaying by adjusting the UAV's attitude and power output to generate a reverse control torque, thus maintaining overall system stability.

[0166] The conical umbrella canopy of this invention, combined with the top drainage hole design, the passive absorption of the damping universal joint, and the active wind disturbance control algorithm, works synergistically to solve the stability problem of large-area loads under drones.

[0167] The functional components also include:

[0168] The safety monitoring module is used to continuously monitor the communication link status between the UAV and the user terminal, the remaining power output of the UAV flight platform 1's energy system, and the signal quality of the positioning data acquired by the spatial positioning module. When the duration of continuous packet loss in the communication link exceeds a first time threshold, the module controls the UAV flight platform 1 to hover in place. When the duration of packet loss exceeds a second time threshold, the module triggers the opening and closing mechanism to retract the parachute and controls the UAV flight platform 1 to return to the initial positioning point to land. When the remaining power is detected to be lower than a first power threshold, a power warning signal is generated. When the remaining power is lower than a second power threshold, the module automatically triggers the opening and closing mechanism to retract the parachute and controls the UAV flight platform 1 to perform the return landing procedure.

[0169] Furthermore, the safety monitoring module of this invention continuously monitors three key parameters: the communication link status between the UAV and the user terminal, the remaining power output of the UAV flight platform's energy system, and the signal quality of the positioning data acquired by the spatial positioning module.

[0170] Regarding the communication link status, the drone flight controller and the mobile app continuously communicate via heartbeat packets. When the duration of continuous packet loss exceeds a first time threshold (e.g., 500 milliseconds), the safety monitoring module controls the drone flight platform to automatically hover in place and issues an alarm via the app to attempt reconnection. When the packet loss duration exceeds a second time threshold (e.g., 5 seconds), the safety monitoring module triggers the opening and closing mechanism to execute the parachute retraction procedure, controlling the drone flight platform 1 to climb to a safe altitude (e.g., 10 meters) and return to the Home point (the recorded last user location) for automatic descent.

[0171] Regarding the remaining battery power, the battery management system monitors the battery power SoC in real time and reports it to the flight control unit via the communication interface. When the remaining battery power is detected to be lower than the first battery power threshold, such as 20%, the safety monitoring module generates a battery power warning signal, and the App sends a voice and vibration alarm to the user, prompting them to prepare for landing due to low battery. When the remaining battery power is lower than the second battery power threshold, such as 10%, the safety monitoring module automatically triggers the opening and closing mechanism to retract the parachute and controls the UAV flight platform to perform the return landing procedure, which is the same as the secondary response to communication interruption.

[0172] Regarding the quality of positioning data signals, the flight controller compares the consistency between UWB data and ToF data. If the UWB signal suddenly changes or is lost, but the ToF data is stable, the system prioritizes trusting the ToF data to maintain the current altitude as the primary objective. At the same time, it attempts to maintain tracking for a short period based on dead reckoning using the last IMU data transmitted from the mobile phone and issues an alarm to the user.

[0173] Furthermore, the safety monitoring module also monitors data from the forward obstacle avoidance sensors. When an obstacle is detected to the side or in the distance ahead, it automatically plans an alternative route. When an obstacle that cannot be bypassed, such as a tree branch, is detected at close range directly ahead, the drone hovers urgently and issues an alarm, awaiting user intervention or the removal of the obstacle.

[0174] In addition, the system provided by this invention has a mechanical stop in the universal joint connection mechanism to strictly limit the maximum descent height of the umbrella, ensuring that even if all systems fail, the umbrella will never physically contact the user.

[0175] This invention can actively guide and release the downwash airflow of the drone and passively absorb wind disturbance vibrations, thereby overcoming the severe swaying problem caused by traditional planar umbrellas. This makes it possible for drones to carry large-area sunshades for stable and reliable flight. This invention adopts a fusion scheme of UWB+ToF+predictive algorithm to achieve centimeter-level, low-latency user tracking. The predictive capability provided allows the drone to anticipate user movement and achieve smooth escort flight rather than lagging pursuit. In addition, by combining multi-level fault safety strategies such as communication interruption, low battery, and sensor redundancy, this invention constructs a highly robust safety system for near-human flight, greatly improving product reliability and user trust.

[0176] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the embodiments of the present invention, and are not intended to limit them. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention. Any changes or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in the present invention should be included within the protection scope of the present invention.

Claims

1. A single-person intelligent dynamic sunshade method based on unmanned aerial vehicles (UAVs), characterized in that, include: S1: Obtain user height parameters and preset follow distance parameters, calculate target hovering height based on user height parameters and preset follow distance parameters, control the drone to take off to the target hovering height and complete the deployment of the sunshade; S2: Use the UWB ultra-wideband positioning module and laser rangefinder to perform spatial positioning of the user and obtain user spatial positioning data; S3: The user space positioning data and inertial measurement data are input into a Kalman filter for fusion to obtain the user state estimation result; S4: Based on the user state estimation results, the user's future movement location is predicted and calculated using a prediction algorithm to obtain the predicted target location; S5: Using the predicted target position as the tracking target, generate flight control commands to drive the drone carrying the sunshade to move above the predicted target position, thereby achieving dynamic sunshade following.

2. The single-person intelligent dynamic sunshade method based on a drone according to claim 1, characterized in that, Step S1 further includes: S11: Receive the height value input by the user and obtain the user's height parameters; S12: Summate the user's height parameter with the preset following distance parameter to obtain the target hovering height; S13: Generate takeoff control commands based on the target hovering height, control the UAV to ascend vertically to the target hovering height, and then send a parachute deployment signal.

3. The single-person intelligent dynamic sunshade method based on a drone according to claim 1, characterized in that, Step S2 further includes: S21: Bilateral two-way ranging is performed between the airborne UWB anchor point module and the user's UWB tag module, and the user's horizontal coordinates and first altitude difference data relative to the UAV are calculated using the time difference of arrival algorithm. S22: Utilizes a laser time-of-flight sensor to measure the distance from the drone to the user's head, obtaining vertical distance data; S23: Perform a consistency check on the first height difference data and the vertical distance data. When the deviation exceeds a preset threshold, replace the first height difference data with the vertical distance data to obtain the corrected height difference data. S24: Combine the horizontal coordinates with the corrected height difference data to form user spatial positioning data.

4. A single-person intelligent dynamic sunshade method based on a drone according to claim 1, characterized in that, Step S3 further includes: S31: Synchronously collect the user's spatial positioning data, the drone's body attitude data output by the drone's inertial measurement unit, and the user's motion data output by the user terminal's inertial measurement unit; S32: Construct a state vector containing position, velocity and acceleration components, and use the state vector as the state variable of the Kalman filter; S33: Based on the uniform acceleration motion model, the state vector is predicted and updated to obtain the predicted state vector; S34: Using the user space positioning data as observations, update the predicted state vector by observation, and obtain the optimal state vector at the current moment through optimal weighted fusion; S35: Extract the optimal position estimate, instantaneous velocity vector, and instantaneous acceleration vector from the optimal state vector to form the user state estimation result.

5. A single-person intelligent dynamic sunshade method based on a drone according to claim 4, characterized in that, Step S4 further includes: S41: Substitute the optimal position estimate, instantaneous velocity vector, and instantaneous acceleration vector from the user state estimation result into the uniform acceleration motion model to calculate the baseline predicted position after a preset time window; S42: Perform threshold judgment on the angular velocity component in the user motion data. When the angular velocity amplitude exceeds the steering judgment threshold, extract the steering intention feature. S43: Calculate the steering angle offset based on the steering intention characteristics and the motion state sequence within the historical time window; S44: Using the predicted reference position as the reference point, the trajectory is corrected according to the steering angle offset and the predicted turning radius calculated from the instantaneous velocity vector to obtain the predicted target position.

6. A single-person intelligent dynamic sunshade system based on an unmanned aerial vehicle (UAV), characterized in that, include: Unmanned aerial vehicle (UAV) flight platforms are used to provide flight power and carry functional components; The sunshade module includes an umbrella canopy assembly, an umbrella rib structure, an opening and closing mechanism, and a damping universal joint. The top of the umbrella canopy assembly is provided with a drainage hole, and the damping universal joint connects the sunshade module to the UAV flight platform. The functional components include: The spatial positioning module includes an airborne UWB anchor point module and a laser ranging sensor. The airborne UWB anchor point module is used to perform bilateral two-way ranging with the user's UWB tag module to obtain horizontal coordinates and altitude difference data. The laser ranging sensor is used to measure the vertical distance data from the UAV to the user's head. The state fusion module is used to input the positioning data and inertial measurement data obtained by the spatial positioning module into a Kalman filter for fusion processing to obtain the user state estimation result. The predictive control module is used to calculate the predicted target position based on the user state estimation result using a prediction algorithm, and generate flight control commands to drive the UAV flight platform to move above the predicted target position.

7. A single-person intelligent dynamic sunshade system based on a drone according to claim 6, characterized in that, The unmanned aerial vehicle (UAV) flight platform includes: The fuselage frame is made of carbon fiber composite material or aerospace-grade aluminum alloy, and is equipped with a six-rotor layout structure and a fully enclosed rotor guard. The propulsion system, including multiple brushless motors, an electronic speed controller, and a propeller, is used to provide lift and power response for flight. The flight control unit includes a main controller and an inertial measurement unit. The main controller runs a real-time operating system, and the inertial measurement unit includes a three-axis gyroscope and a three-axis accelerometer. The energy system includes a lithium polymer battery pack and a battery management system, wherein the battery management system is used to monitor the battery power and report the remaining power information to the flight control unit via a communication interface.

8. A single-person intelligent dynamic sunshade system based on a drone according to claim 6, characterized in that, The sunshade module includes: The umbrella assembly adopts a conical or frustoconical structure. The umbrella surface is made of high-density nylon or polyester fiber fabric treated with UV protection and waterproof coating. A circular drainage hole is opened at the top of the umbrella surface. The umbrella rib structure adopts a space truss structure without a central bar. The main umbrella ribs and secondary spokes are connected by micro hinges to form a triangular mechanical structure, which is used to execute the umbrella surface to form a sunshade structure. The opening and closing mechanism includes a torsion spring, a miniature DC servo motor, a winch, and a high-strength nylon cable. The torsion spring provides power for opening the umbrella, and the servo motor drives the winch to close the umbrella via the cable. The connection mechanism includes a quick-release module and the damping universal joint. The quick-release module integrates electrical contacts for supplying power to the servo motor and transmitting control signals. The damping universal joint provides deflection freedom and has a built-in damping oil cavity for absorbing high-frequency vibrations.

9. A single-person intelligent dynamic sunshade system based on an unmanned aerial vehicle (UAV) according to claim 6, characterized in that, The functional components also include: The aerodynamic stability control module is used to guide the downwash airflow of the UAV along the umbrella surface through the umbrella assembly, release the downwash airflow through the vent holes, and dampen and attenuate the high-frequency vibration caused by airflow disturbance through the damping universal joint. When vibration characteristics caused by crosswind are detected, the motor output of the power system of the UAV flight platform is adjusted to generate a reverse torque for wind disturbance control.

10. A single-person intelligent dynamic sunshade system based on a drone according to claim 6, characterized in that, The functional components also include: The safety monitoring module is used to continuously monitor the communication link status between the UAV and the user terminal, the remaining power output of the UAV flight platform's energy system, and the signal quality of the positioning data acquired by the spatial positioning module. When the duration of continuous packet loss in the communication link exceeds the first time threshold, the drone flight platform is controlled to hover in place. When the packet loss duration exceeds the second time threshold, the opening and closing mechanism is triggered to retract the parachute and control the UAV flight platform to return to the initial positioning point to perform landing. When the remaining battery power is detected to be lower than the first battery power threshold, a battery power warning signal is generated; when the remaining battery power is lower than the second battery power threshold, the opening and closing mechanism is automatically triggered to retract the parachute and control the UAV flight platform to perform the return landing process.

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