Nonlinear stable hoisting method and system for mounting unmanned aerial vehicle in restricted environment

Abstract

This invention discloses a nonlinear stable hoisting method and system for mounting a drone in a confined environment. The method involves constructing a three-dimensional model of the confined environment; planning and marking the mounting trajectory in a world coordinate system based on the constructed three-dimensional model; obtaining a predicted trajectory of a quadcopter drone based on the drone's motion model according to the mounting trajectory; the quadcopter drone moving according to the obtained predicted trajectory, thus moving the mounted drone within the confined environment; when the drone directly moves the mounted drone, it flies in an open environment according to a flight path generated based on the planned mounting path, moving the tool within the confined environment. This achieves normal drone flight while simultaneously enabling normal tool movement within the confined environment, expanding the application of rotary-wing drones in the power sector and solving the problem of inconvenient movement of mounted drones in confined environments.

Description

Technical Field

[0001] This invention relates to the field of unmanned aerial vehicle (UAV) hoisting control technology, and in particular to a nonlinear stable hoisting method and system for hoisting UAVs in confined environments. Background Technology

[0002] Rotary-wing drones are frequently used for power line inspection, fault diagnosis, and tool delivery. For example, power facilities are widely distributed and the lines are complex. Manual inspection often suffers from low efficiency and safety hazards. Rotary-wing drones, on the other hand, can be equipped with high-definition cameras and sensors to achieve real-time monitoring and fault diagnosis of power lines, greatly improving the efficiency and accuracy of inspections.

[0003] During tool transport, the equipment is carried by a sling-mounted tool beneath the drone. Utilizing the flexibility and versatility of the sling-mounted quadcopter drone, rapid load transport is achieved. However, sometimes limited transport space is caused by power equipment layout. When using a rotary-wing drone for transport, the load needs to be moved between power equipment. Furthermore, since the quadcopter drone's load-carrying system is an underactuated system, its control is more complex than the flight control of a standard quadcopter. The increased sway angle between the load and the drone body intensifies the system's coupling, making direct controller control of the load impossible. Instead, the load's angle is indirectly controlled through the quadcopter's position control. This process is particularly challenging when the load is in a confined environment. When moving, the drone needs to follow a certain trajectory to prevent collisions. However, due to the aforementioned coupling relationship, currently, drones and loads are generally moved within a restricted environment. This only applies when the restricted environment is large enough to accommodate the drone. When the restricted environment is unsuitable for drones, the current practice is for both the drone and the load to move outside the restricted environment. The scenario of a drone outside the restricted environment driving a load inside the restricted environment has not yet occurred. When a drone flies in an open environment and the tool moves in a restricted environment, the drone cannot move normally within the restricted environment, thus limiting the application of rotary-wing drones in the power sector. Summary of the Invention

[0004] This invention addresses the shortcomings of existing technologies by providing a nonlinear stable hoisting method for suspending drones in confined environments. The method involves back-calculating the predicted trajectory of the drone by constructing a hoisting drone motion model, and then using the drone to move along the corresponding trajectory to achieve the smooth transfer of the suspended object in the confined environment.

[0005] To solve the above-mentioned technical problems, the present invention provides a technical solution: a nonlinear stable hoisting method for mounting a UAV in a confined environment, the steps of which are:

[0006] S1. Construct a three-dimensional model of the constrained environment;

[0007] S2. Based on the constructed 3D model, plan and mark the mounting motion trajectory in the world coordinate system;

[0008] S3. Based on the mounted operating trajectory, obtain the predicted operating trajectory of the UAV through the dynamic model of the mounted rotary-wing UAV;

[0009] S4. The drone moves according to the obtained predicted trajectory, driving the payload to move in the confined environment.

[0010] Furthermore, in step S1, the method for constructing the three-dimensional model of the confined environment is as follows: image information of the confined environment is obtained through sensors, and then a three-dimensional model of the confined environment is constructed in the world coordinate system, and the specific coordinates of each component in the confined environment are obtained.

[0011] Furthermore, in step S2, the method for obtaining the mounting motion trajectory is as follows:

[0012] Each component in the confined environment is treated as an obstacle point, and a starting point, ending point, obstacle avoidance inflection point, and working position are set. The coordinates and attitude of each point are recorded.

[0013] After automatic path planning using path planning software, a time dimension is added to generate time-series trajectory points with continuous motion, no impact, and velocity / acceleration constraints.

[0014] Furthermore, in step S3, the process of constructing the dynamic model of the mounted rotary-wing UAV is as follows:

[0015] Based on the dynamic model of the rotary-wing UAV, a dynamic model of the mounted rotary-wing UAV is constructed according to the positional relationship between the quadcopter UAV and the sling in the world coordinate system. The trajectory of the sling is used as the control input of the rotary-wing UAV. The predicted trajectory of the sling and the sling angle at each path point are obtained according to the dynamic model of the mounted rotary-wing UAV. Based on the geometric positional relationship between the sling and the UAV, combined with the predicted trajectory of the sling, the sling angle at each path point and twice the length of the sling cable, the predicted trajectory of the UAV is obtained by reverse calculation based on the dynamic model of the mounted rotary-wing UAV.

[0016] Furthermore, in step S3, the dynamic model of the sling-mounted rotary-wing UAV is as follows:

[0017]

[0018] In the formula, For the generalized coordinates of system displacement and load swing angle, Represents the generalized forces acting on the system. Represents the resistance experienced by the system. Let be the system's inertia matrix. For the centripetal-Cole force matrix of the system, Let be the potential energy matrix of the system.

[0019] Furthermore, in the process of obtaining the predicted running trajectory of the load: based on the improved active disturbance rejection controller, the disturbances with large fluctuations are first adaptively estimated in advance, and then added to the controller to reduce the estimation error. In addition, a sway reduction part is added to actively reduce the sway angle of the suspended load, thereby increasing robustness.

[0020] Furthermore, the improvement process of active disturbance rejection control is as follows: a smooth trajectory is used to replace the tracking differentiator TD, and the smooth trajectory is used to eliminate the disturbance caused by the trajectory change; at the same time, an anti-sway part is added. The anti-sway part collects the load sway angle signal in real time and outputs a compensation control quantity to the UAV control system to eliminate the load sway angle of the quadcopter UAV load-bearing system.

[0021] To address the aforementioned technical problems, another technical solution provided by this invention is: an uncertainty-aware edge reconstruction system based on a priori guidance of a diffusion model, characterized by comprising:

[0022] Environment model construction module: Obtains image information of the confined environment through sensors, then constructs a 3D model of the confined environment in the world coordinate system, and obtains the specific coordinates of each component in the confined environment;

[0023] Mounting a motion trajectory acquisition module: Each component in the restricted environment is used as an obstacle point, and a start point, end point, obstacle avoidance inflection point, and working position are set. The coordinates and attitude of each point are recorded. After automatic path planning using path planning software, a time dimension is added to generate a time-series trajectory point with continuous motion, no impact, and velocity / acceleration constraints.

[0024] The module for constructing the motion model of the suspended UAV: ​​Based on the dynamic model of the rotary-wing UAV, a dynamic model of the suspended rotary-wing UAV is constructed according to the positional relationship between the quadcopter UAV and the suspension in the inertial coordinate system;

[0025] The UAV predicted flight trajectory acquisition module: uses the mounted flight trajectory as the control input of the rotorcraft UAV, and obtains the predicted flight trajectory of the mounted rotorcraft UAV based on the dynamic model of the mounted rotorcraft UAV; based on the geometric positional relationship between the mounted and the UAV, combined with the predicted flight trajectory of the mounted, the mounted deflection angle at each path point, and twice the length of the mounted cable, the predicted flight trajectory of the UAV is obtained by back-calculation based on the dynamic model of the mounted rotorcraft UAV; the improved active disturbance rejection controller uses a smooth trajectory instead of the tracking differentiator TD, and adds an anti-sway component to eliminate the load sway angle.

[0026] To solve the above-mentioned technical problems, another technical solution provided by the present invention is: an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that the processor implements the steps of the method described above when executing the computer program.

[0027] To solve the above-mentioned technical problems, another technical solution provided by the present invention is: a computer-readable storage medium storing a computer program thereon, characterized in that the computer program, when executed by a processor, implements the steps of the method described above.

[0028] The beneficial effects of this invention are as follows:

[0029] This application first plans the mounting and movement path based on the restricted environment. Then, using the planned mounting and movement path as input, it obtains the mounting deflection angle through an established UAV mounting model. Based on the mounting rope length and the positional relationship between the UAV and the mounting in inertial coordinates, it obtains the corresponding UAV trajectory. Finally, the UAV's movement enables the mounting to move along the set trajectory. When the UAV directly drives the mounting, it flies in an open environment according to the flight path generated based on the planned mounting path, driving the tool to move in the restricted environment. This allows the UAV to fly normally outside the restricted environment while enabling the tool to move normally in the restricted environment, expanding the application of rotary-wing UAVs in the power field and solving the problem of inconvenient movement of the mounting in restricted environments. In the process of obtaining the mounting deflection angle, an improved active disturbance rejection controller is used to proactively estimate large disturbances in advance, then incorporates them into the controller to reduce estimation errors. An anti-sway component is added to actively eliminate the sway angle of the mounted load, increasing robustness and ensuring that the sway angle meets the set safety range. This prevents excessive deflection angle from affecting the flight stability of the UAV, while also incorporating uncertainties to reduce the impact of the external environment on the UAV trajectory.

[0030] To make the above and other objects, features and advantages of the present invention more apparent and understandable, preferred embodiments are described below in detail with reference to the accompanying drawings. Attached Figure Description

[0031] To more clearly illustrate the technical solutions in this invention or the prior art, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only seven of the drawings in this invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0032] Figure 1 This is a flowchart of the method described in this invention.

[0033] Figure 2This is a three-dimensional schematic diagram of the UAV mounting system of the present invention.

[0034] Figure 3 This is a control flowchart of the improved active disturbance rejection controller of the present invention.

[0035] Figure 4 The diagram shows an experimental comparison of the positions of the controller and the comparison controller designed for this invention.

[0036] Figure 5 Experimental diagram comparing the swing angles of the controller and the comparison controller designed for this invention.

[0037] Figure 6 An experimental diagram showing the attitude comparison between the controller designed for this invention and the comparison controller.

[0038] Figure 7 This is a diagram illustrating the spiral trajectory tracking of the present invention. Detailed Implementation

[0039] Embodiments of the present invention will now be described in more detail with reference to the accompanying drawings. While some embodiments of the invention are shown in the drawings, it should be understood that the invention can be implemented in various forms and should not be construed as limited to the embodiments set forth herein. Rather, these embodiments are provided to provide a more thorough and complete understanding of the invention. It should be understood that the accompanying drawings and embodiments are for illustrative purposes only and are not intended to limit the scope of protection of the invention.

[0040] It should be understood that the various steps described in the method embodiments of the present invention may be performed in different orders and / or in parallel. Furthermore, the method embodiments may include additional steps and / or omit the steps shown. The scope of the present invention is not limited in this respect.

[0041] The names of the messages or information exchanged between the multiple devices in the embodiments of the present invention are for illustrative purposes only and are not intended to limit the scope of these messages or information.

[0042] Example

[0043] like Figure 1-7 As shown, a nonlinear stable hoisting method for mounting a UAV in a confined environment includes the following steps:

[0044] S1. Construct a three-dimensional model of the constrained environment;

[0045] S2. Based on the constructed 3D model, plan and mark the mounting motion trajectory in the world coordinate system;

[0046] S3. Based on the mounted operating trajectory, obtain the predicted operating trajectory of the UAV through the dynamic model of the mounted rotary-wing UAV;

[0047] S4. The drone moves according to the obtained predicted trajectory, driving the payload to move in the confined environment.

[0048] In step S1, the three-dimensional model of the confined environment is constructed as follows: image information of the confined environment is obtained through sensors, and then a three-dimensional model of the confined environment is constructed in the world coordinate system, and the specific coordinates of each component in the confined environment are obtained.

[0049] The sensor can be a lidar, an RGB-D camera, etc., and then the 3D image is converted to world coordinates through coordinate transformation.

[0050] In step S2, the method for obtaining the mounting motion trajectory is as follows:

[0051] Each component in the confined environment is treated as an obstacle point, and a starting point, ending point, obstacle avoidance inflection point, and working position are set. The coordinates and attitude of each point are recorded.

[0052] After automatic path planning using path planning software, a time dimension is added to generate time-series trajectory points that are continuous, shock-free, and have velocity / acceleration constraints; these points can then be used as input to control the movement of the UAV.

[0053] Path planning software can be used, such as NAP3D and Maven.

[0054] In step S3, the process of constructing the dynamic model of the mounted rotary-wing UAV is as follows:

[0055] Based on the dynamic model of the rotorcraft UAV, a dynamic model of the mounted rotorcraft UAV is constructed according to the positional relationship between the quadcopter UAV and the sling in the world coordinate system. The trajectory of the sling is used as the desired path of the rotorcraft UAV for control input. The predicted trajectory of the sling and the sling angle at each path point are obtained according to the dynamic model of the mounted rotorcraft UAV. The predicted trajectory of the UAV is obtained by back-calculating the predicted trajectory of the sling, the sling angle at each path point, and twice the length of the sling cable according to the dynamic model of the mounted rotorcraft UAV. The multiple of the sling cable length can also be 3 times, 4 times, etc., depending on the requirements, but 2 times is preferred. The 2 times sling cable length is used to define the safe distance between the UAV and the sling, ensuring that the back-calculated UAV trajectory will not interfere with the sling, and matching the calculation range of the sling angle.

[0056] The specific steps for constructing the dynamic model of a mounted rotary-wing UAV are as follows:

[0057] Construct a world coordinate system {E}, a quadcopter UAV body coordinate system {B}, and a load-bearing coordinate system {L}. Then, transform the UAV body coordinate system and the load-bearing coordinate system to the world coordinate system using a transformation matrix.

[0058] World coordinate system {E}( The world coordinate system is fixed to the ground, which is considered a plane, and serves as the system's fixed reference coordinate system. The origin of the world coordinate system... This is considered the takeoff position for the UAV's sling-mounted system. The world coordinate system is based on the vertical direction away from the Earth's center. The axis follows the right-hand rule.

[0059] Body coordinate system {B}( The coordinate system is fixed to the fuselage, and its coordinate axes rotate with the fuselage. The origin of the fuselage coordinate system is... The shaft coincides with the load suspension point. Always pointing towards the machine head, shaft Always pointing to the left side of the machine and perpendicular to The axis is always in the same direction as the resultant force generated by the rotor of the aircraft, and the coordinate system follows the right-hand rule.

[0060] Suspended load coordinate system {L}( )origin and Coincident, axis , , Parallel to , , Three axes, axis and Same direction, axis , respectively with the shaft , Reverse. Define the load cable in... Projection on the plane and axis The included angle is The load cable is in Projection on the plane and axis The included angle is .

[0061] The attitude of the quadcopter drone in the world coordinate system is expressed using Euler angles. , The pitch angle, For roll angle, This is the yaw angle.

[0062] Assuming the world coordinate system and the body coordinate system coincide in the initial state, after the quadcopter UAV moves, the position vector in the world coordinate system {E} will be transformed using a transformation matrix. Convert the position vector in the body coordinate system {B} to a position vector in the body coordinate system {B}, or convert the position vector in the body coordinate system {B} using a transformation matrix. Convert the position vector to the world coordinate system {E}, and convert the transformation matrix between the world coordinate system and the body coordinate system. As shown below:

[0063]

[0064] Transformation matrix from load coordinate system {L} to body coordinate system {B} As shown below:

[0065]

[0066] Based on the transformation matrix above, the position of the suspended load in the body coordinate system is expressed as follows:

[0067]

[0068]

[0069]

[0070] In the formula, This represents the initial position of the suspended load in the load coordinate system. This refers to the length of the load cable.

[0071] A 3D schematic diagram of the drone mounting system is shown below. Figure 2 As shown. Based on the flight conditions of the quadcopter UAV, the dynamic model of the mounted rotary-wing UAV satisfies the following conditions:

[0072] The fuselage of the quadcopter drone is considered a rigid body, and the angle between each arm is π / 2. The quadcopter drone is fixed in the body coordinate system, and its center of mass and load suspension point are both located at the center of the drone. In both the world coordinate system and the body coordinate system, the suspended load is always below the drone, and the angle between the suspended load cable and the drone satisfies... ,and The cable suspending the load is initially considered a rigid body of fixed length and its mass is ignored; the load is considered a point mass.

[0073] Based on Euler-Lagrange dynamics theory, the dynamic model of the mounted rotor UAV is constructed as follows:

[0074]

[0075] In the formula, For the generalized coordinates of system displacement and load swing angle, Represents the generalized forces acting on the system. This represents the resistance the system experiences in all directions. Let be the system's inertia matrix. For the centripetal-Cole force matrix of the system, Let be the potential energy matrix of the system.

[0076]

[0077]

[0078]

[0079] In the formula, For the quality of drones, For mounting weight, For the length of the load-bearing cable, It is the acceleration due to gravity; , , , , These represent the x-axis displacement, y-axis displacement, z-axis displacement of the rotary-wing UAV, and the load cable displacement. Projection on the plane and axis The angle of the load cable in Projection on the plane and axis The included angle; , , These are the force components of the rotary-wing UAV along the x, y, and z directions, respectively; , , These represent the air resistance of the system in the x, y, and z directions, respectively. , , This represents the drag coefficient of the system in all directions.

[0080] Because air resistance or sudden load changes are unavoidable during operation, , , Abbreviated as , , Redefining , , , Representing variables The determined part in To represent the uncertain part of the variable, the uncertain term is expressed as:

[0081]

[0082] The dynamic model of the sling-mounted rotary-wing UAV constructed above is updated as follows:

[0083] .

[0084] In this process, the payload's operational trajectory is used as the desired path for the rotorcraft UAV as the control input. The rotorcraft UAV flies along the desired path. The predicted operational trajectory of the payload is obtained based on the dynamic model of the mounted rotorcraft UAV and the payload deflection angle at each path point.

[0085] Based on the improved active disturbance rejection controller, the disturbance with large fluctuations is first adaptively estimated in advance, and then added to the controller to reduce the estimation error. In addition, a sway reduction part is added to actively reduce the sway angle of the suspended load, thereby increasing robustness.

[0086] like Figure 3 As shown, the controller consists of two parts: an outer loop position and sway controller and an inner loop attitude controller. The outer loop controller uses an improved active disturbance rejection control to control the position of the quadcopter UAV, the sway angle of the suspended load, and eliminate disturbances under varying load conditions. The inner loop control uses a combination of backstepping and an extended state observer to control the attitude of the quadcopter UAV. The desired attitude angle is obtained from the outer loop controller.

[0087] The process of actively eliminating sway in the improved active disturbance rejection control is as follows: a smooth trajectory is used to replace the tracking differentiator TD, and a sway elimination part is added to eliminate the load sway angle of the quadcopter UAV load-bearing system.

[0088] Design an acceleration trajectory in the following form:

[0089]

[0090] In the formula, , , These represent quadcopter drones in , , The total expected acceleration trajectory in three directions; , , These represent quadcopter drones in , , The expected acceleration trajectories of displacement in three directions are used to generate a smooth trajectory that allows the quadcopter UAV to reach the target position. , , These represent quadcopter drones in , , The three-directional anti-sway components are used to adjust the trajectory in real time according to the sway angle of the current suspended load in order to eliminate the sway angle.

[0091] First, to facilitate the elimination of sway trajectory , , The design assumes the desired trajectory of position acceleration. , , The value is zero:

[0092]

[0093] Construct a nonnegative Lyapunov function of the following form:

[0094]

[0095] Taking the first reciprocal of both sides of the above equation with respect to time, we obtain the following result:

[0096]

[0097] To ensure the non-negative Lyapunov function converges to the desired control objective, the above equation is non-positive; here, the desired anti-oscillation trajectory is chosen. , , The value is:

[0098]

[0099] Desired Displacement Trajectory , , As shown below:

[0100]

[0101] In the formula, for , , ; for Target location in the direction and express Maximum permissible speed and acceleration in direction, Used for adjustment Initial acceleration in the direction.

[0102] The trajectory has the following properties:

[0103]

[0104] In the formula, .

[0105] Finally, based on the desired anti-oscillation trajectory and the desired displacement trajectory, the anti-oscillation trajectory is obtained as follows:

[0106]

[0107] The process of eliminating disturbances in the improvement of active disturbance rejection control is as follows: the total disturbance is estimated by a linearly extended state observer, and the estimated value is fed back to eliminate the disturbance.

[0108] The design of the extended state observer takes the x-direction as an example:

[0109]

[0110] In the formula, This represents the gain of the system output, and its value is determined with reference to the specific model. The representative system is Directional control amount, The representative system is Internal disturbances in direction, Represents external disturbances to the system. This represents the total disturbance of the system.

[0111] Taking the x-direction as an example, design a linearly extended state observer of the following form:

[0112]

[0113] In the formula, Representative for , and external disturbances State estimates; , The gain of the linearly extended state observer, when expanded, is given by the following equation:

[0114]

[0115] The state error feedback control law is as follows:

[0116] The purpose of the extended state observer is to enable Approaching , Approaching , Approaching Then, new control variables can be designed:

[0117]

[0118] New control quantity replace Substituting into the extended state observer, we get:

[0119]

[0120] It can be seen that when Sometimes, This eliminates disturbances in the system.

[0121] The nonlinear state error feedback control law (NLSEF) is constructed as follows:

[0122]

[0123] In the formula, , It is a nonlinear function. , , for The parameters of the function.

[0124] To estimate the variation in suspended load, undetermined mass variations in the system are considered. Assuming the system parameters are undefined, the control law for the variation in mounted mass is as follows:

[0125] .

[0126] The desired value of the attitude controller is given by the position controller, and its form is as follows:

[0127]

[0128] The attitude angle controller for a quadrotor UAV designed based on the anti-stepping method is shown in the following equation:

[0129]

[0130] In the formula, , , These represent the total disturbances in their respective loops.

[0131] The controller and method designed in this application will be experimentally verified below.

[0132] In the MATLAB / Simulink simulation environment, a comparative experiment was conducted using a classic PID controller and a dual-loop PID controller to verify the control performance of the controller designed in this chapter. The data is shown in Table 1. And set the initial position of the quadcopter drone. .

[0133]

[0134] , , This determines the time required for the trajectory to reach the target location, and is related to... Together, they determine the effect of sway angle suppression. , , , ,in .

[0135] For the state error feedback control law, select , , , , ,in .

[0136] For a linearly extended state observer, select bandwidth .

[0137] For the attitude controller, select , ,in .

[0138] The parameters of a classic PID controller are: , , , , , , ,in , .

[0139] The parameters of the dual-loop PID controller are: , , , , , , ,in ,

[0140] The three sets of controllers are positioned at the same target. The following simulation comparison yielded the following results: Figure 4 Figure 5 , Figure 6 As shown in the figure, the swing angle amplitude of the suspended load designed in this application is slightly better than that of the dual-loop PID controller, and the attitude swing angle amplitude is slightly better than that of the PID controller. Furthermore, the swing frequency of the suspended load swing angle and attitude angle of the controller designed in this application is significantly smaller than that of the comparative controller, which can effectively suppress the swing of the suspended load with a stable attitude and has good control performance.

[0141] A trajectory tracking simulation was performed on the mounting system of the drone. Initially, the quadcopter drone was located at the origin (0,0,0). The simulation time was 35 seconds, and the altitude was set... At the 5th second, the trajectories of X and Y are set as follows: , The simulation was performed with a fixed step size of 0.001s, and the simulation results are shown in the figure. As can be seen from the figure, Figure 7 The image shows the 3D trajectory tracking curve during the trajectory tracking process. It can be seen that when the UAV drives the payload to track the set trajectory of the payload, the payload tracking trajectory can fly along the desired trajectory.

[0142] Based on the same inventive concept, this invention also provides an uncertainty-aware edge reconstruction system guided by a priori diffusion model, characterized by comprising:

[0143] Environment model construction module: Obtains image information of the confined environment through sensors, then constructs a 3D model of the confined environment in the world coordinate system, and obtains the specific coordinates of each component in the confined environment;

[0144] Mounting a motion trajectory acquisition module: Each component in the restricted environment is used as an obstacle point, and a start point, end point, obstacle avoidance inflection point, and working position are set. The coordinates and attitude of each point are recorded. After automatic path planning using path planning software, a time dimension is added to generate a time-series trajectory point with continuous motion, no impact, and velocity / acceleration constraints.

[0145] The module for constructing the motion model of the suspended UAV: ​​Based on the dynamic model of the rotary-wing UAV, a dynamic model of the suspended rotary-wing UAV is constructed according to the positional relationship between the quadcopter UAV and the suspension in the inertial coordinate system;

[0146] The UAV predicted flight trajectory acquisition module uses the mounted flight trajectory as the control input for the rotorcraft UAV. Based on the dynamic model of the mounted rotorcraft UAV, it obtains the predicted flight trajectory of the mounted UAV and the mounted deflection angle at each path point. By using the predicted flight trajectory of the mounted UAV, the mounted deflection angle at each path point, and twice the length of the mounted cable, it back-calculates the predicted flight trajectory of the UAV based on the dynamic model of the mounted rotorcraft UAV.

[0147] In this application, the other technical features of the uncertainty-aware edge reconstruction system based on diffusion model prior guidance are the same as those disclosed in the above method embodiments, and will not be repeated here.

[0148] Based on the same inventive concept, the present invention also provides an electronic device, which may include a processor and a memory.

[0149] Furthermore, the processor can be a general-purpose processor, such as a central processing unit (CPU), digital signal processor (DSP), application-specific integrated circuit (ASIC), field-programmable gate array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components, capable of implementing or executing the methods, steps, and logic block diagrams disclosed in the embodiments of this application. The general-purpose processor can be a microprocessor or any conventional processor. The steps of the methods disclosed in the embodiments of this application can be directly manifested as being executed by a hardware processor, or executed by a combination of hardware and software modules within the processor.

[0150] Furthermore, memory, as a non-volatile computer-readable storage medium, can be used to store non-volatile software programs, non-volatile computer-executable programs, and modules. Memory can include at least one type of storage medium, such as flash memory, hard disk, multimedia card, card-type memory, random access memory (RAM), static random access memory (SRAM), programmable read-only memory (PROM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), magnetic memory, magnetic disk, optical disk, etc. Memory is any other medium capable of carrying or storing desired program code in the form of instructions or data structures that can be accessed by a computer, but is not limited thereto. The memory in the embodiments of this application can also be a circuit or any other device capable of implementing storage functions for storing program instructions and / or data.

[0151] Based on the same inventive concept, this application also provides a computer-readable storage medium storing a computer program that can be executed by a processor to implement the above-described method.

[0152] The technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a readable computer storage medium and includes several instructions / computer programs to cause an Internet of Things device (which may be a personal computer, server, or network terminal, etc.) or processor to execute all or part of the steps of the methods of the various embodiments of this application. The aforementioned storage medium includes various media such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks, as well as electronic terminals such as computers, mobile phones, laptops, tablets, and cameras that have the aforementioned storage media.

[0153] The description of the execution process of program data in a computer-readable storage medium can be found in the descriptions in the various method embodiments of this application above, and will not be repeated here.

[0154] Note that the above description is merely a preferred embodiment of the present invention and the technical principles employed. Those skilled in the art will understand that the present invention is not limited to the specific embodiments described herein, and various obvious changes, readjustments, and substitutions can be made without departing from the scope of protection of the present invention. Therefore, although the present invention has been described in detail through the above embodiments, the present invention is not limited to the above embodiments, and may include many other equivalent embodiments without departing from the concept of the present invention, the scope of which is determined by the scope of the appended claims.

Claims

1. A nonlinear stable hoisting method for mounting a UAV in a confined environment, comprising the following steps: S1. Construct a 3D model of the constrained environment; S2. Based on the constructed 3D model, plan and mark the mounting motion trajectory in the world coordinate system; S3. Based on the mounted operating trajectory, obtain the predicted operating trajectory of the quadcopter drone through the dynamic model of the mounted rotary-wing drone; S4, the quadcopter drone moves according to the obtained predicted trajectory, driving the payload to move in the confined environment.

2. The nonlinear stable hoisting method for mounting a UAV in a confined environment according to claim 1, characterized in that: In step S1, the construction method of the three-dimensional model of the confined environment is as follows: image information of the confined environment is obtained through sensors, and then a three-dimensional model of the confined environment is constructed in the world coordinate system, and the specific coordinates of each component in the confined environment are obtained.

3. The nonlinear stable hoisting method for mounting a UAV in a confined environment according to claim 1, characterized in that: In step S2, the method for obtaining the mounted motion trajectory is as follows: Each component in the confined environment is treated as an obstacle point, and a starting point, ending point, obstacle avoidance inflection point, and working position are set. The coordinates and attitude of each point are recorded. After automatic path planning using path planning software, a time dimension is added to generate time-series trajectory points with continuous motion, no impact, and velocity / acceleration constraints.

4. The nonlinear stable hoisting method for mounting a UAV in a confined environment according to claim 1, characterized in that: In step S3, the process of constructing the dynamic model of the mounted rotary-wing UAV is as follows: Based on the quadcopter UAV dynamic model, a mounted rotor UAV dynamic model is constructed according to the positional relationship between the quadcopter UAV and the sling in the world coordinate system; the mounted trajectory is used as the desired path of the rotor UAV for control input, and the predicted trajectory of the mounted UAV and the mounted deflection angle at each path point are obtained according to the mounted rotor UAV dynamic model. Based on the geometric positional relationship between the mount and the UAV, combined with the predicted trajectory of the mount, the mount deflection angle at each path point, and twice the length of the mount cable, the predicted trajectory of the UAV is obtained by inverse calculation using the dynamic model of the mounted rotor UAV.

5. A nonlinear stable hoisting method for mounting a UAV in a confined environment according to claim 4, characterized in that: In step S3, the dynamic model of the mounted rotary-wing UAV is as follows: In the formula, For the generalized coordinates of system displacement and load swing angle, Represents the generalized forces acting on the system. Represents the resistance experienced by the system. Let be the system's inertia matrix. For the centripetal-Cole force matrix of the system, Let be the potential energy matrix of the system.

6. A nonlinear stable hoisting method for mounting a UAV in a confined environment according to claim 4, characterized in that: In step S3, during the process of obtaining the predicted running trajectory of the load: according to the improved active disturbance rejection controller, the disturbance with large fluctuations is first adaptively estimated in advance, and then added to the controller to reduce the estimation error. In addition, a sway reduction part is added to actively reduce the sway angle of the suspended load, thereby increasing robustness.

7. The nonlinear stable hoisting method for mounting a UAV in a confined environment according to claim 6, characterized in that: The improvement process of the active disturbance rejection controller is as follows: a smooth trajectory is used to replace the tracking differentiator TD. The smooth trajectory is used to eliminate the disturbance caused by the sudden change in trajectory. At the same time, an anti-sway part is added. The anti-sway part collects the load sway angle signal in real time and outputs a compensation control quantity to the UAV control system to eliminate the load sway angle of the quadcopter UAV load-bearing system.

8. A nonlinear stable hoisting system for mounting unmanned aerial vehicles (UAVs) in a confined environment, characterized by: include: Environment model construction module: Obtains image information of the confined environment through sensors, then constructs a 3D model of the confined environment in the world coordinate system, and obtains the specific coordinates of each component in the confined environment; Mounting a motion trajectory acquisition module: Each component in the restricted environment is used as an obstacle point, and a start point, end point, obstacle avoidance inflection point, and working position are set. The coordinates and attitude of each point are recorded. After automatic path planning using path planning software, a time dimension is added to generate a time-series trajectory point with continuous motion, no impact, and velocity / acceleration constraints. The module for constructing the motion model of the suspended UAV: ​​Based on the dynamic model of the rotary-wing UAV, a dynamic model of the suspended rotary-wing UAV is constructed according to the positional relationship between the quadcopter UAV and the suspension in the inertial coordinate system; The UAV predicted flight trajectory acquisition module uses the mounted flight trajectory as the control input for the rotorcraft UAV. Based on the dynamic model of the mounted rotorcraft UAV, it obtains the predicted flight trajectory of the mounted payload and the payload deflection angle at each path point. Based on the geometric positional relationship between the payload and the UAV, combined with the predicted flight trajectory of the payload, the payload deflection angle at each path point, and twice the length of the payload cable, it back-calculates the predicted flight trajectory of the UAV based on the dynamic model of the mounted rotorcraft UAV. The improved active disturbance rejection controller uses a smooth trajectory instead of the tracking differentiator TD and adds an anti-sway component to eliminate the load sway angle.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the steps of the method according to any one of claims 1 to 7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 7.

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