Tailstock type vertical take-off and landing unmanned aerial vehicle regulation and control method and device based on pipeline

Abstract

The invention discloses a pipeline-based tailstock type vertical take-off and landing unmanned aerial vehicle regulation and control method and device. The method comprises the following steps: acquiring an initial track according to a space model; according to the initial track, a target track and a variable radius pipeline are obtained through cubic spline fitting; according to the variable-radius pipeline, contour constraint and self-adaptive parameters are set; according to the target trajectory, the contour constraint and the adaptive parameter, constructing a target function; presetting sideslip angle constraints of the vertical take-off and landing unmanned aerial vehicle; according to the objective function, the contour constraint, the adaptive parameter and the sideslip angle constraint, constructing a pipeline-based model prediction contour control framework; wherein the model prediction contour control framework based on the pipeline is used for planning and controlling the vertical take-off and landing unmanned aerial vehicle. The method can improve the performance and robustness of vertical take-off and landing unmanned aerial vehicle regulation and control, and can be widely applied to the technical field of unmanned aerial vehicle control.

Description

Technical Field

[0001] The present invention relates to the technical field of UAV control, and in particular to a method and device for trajectory planning and control of a tail-sitter vertical takeoff and landing UAV based on a pipeline. Background Art

[0002] Currently, the trajectory planning and control scheme of aircraft generally makes a trajectory containing time information by considering the robot model and differential flatness at the front end, and then uses methods such as PID or MPC to track at the back end. However, for a vertical takeoff and landing fixed-wing aircraft, the non-linear aerodynamic force makes the model more complex. If this framework is still used, the fixed time information calculated based on the possibly mismatched model in the early stage may lead to error accumulation during later tracking, making it difficult to resist disturbances in real time. Moreover, the technical scheme based on differential flatness has strict conditions and requires cumbersome and precise planning calculations based on differential flatness, resulting in poor real-time performance. Summary of the Invention

[0003] In view of this, the main purpose of the embodiments of the present invention is to provide a method and device for trajectory planning and control of a tail-sitter vertical takeoff and landing UAV based on a pipeline, in order to solve at least one of the existing technical problems. The present invention can improve the performance and robustness of the trajectory planning and control of vertical takeoff and landing UAVs.

[0004] To achieve the above object, on the one hand, an embodiment of the present invention provides a method for trajectory planning and control of a tail-sitter vertical takeoff and landing UAV based on a pipeline, the method comprising:

[0005] Obtaining an initial trajectory according to a spatial model;

[0006] Obtaining a target trajectory and a variable-radius pipeline by cubic spline fitting according to the initial trajectory;

[0007] Setting contour constraints and adaptive parameters according to the variable-radius pipeline;

[0008] Constructing an objective function according to the target trajectory, the contour constraints and the adaptive parameters;

[0009] Presetting a sideslip angle constraint for the vertical takeoff and landing UAV;

[0010] Constructing a pipeline-based model predictive contour control framework according to the objective function, the contour constraints, the adaptive parameters and the sideslip angle constraint;

[0011] Wherein, the pipeline-based model predictive contour control framework is used for planning and controlling the vertical takeoff and landing UAV.

[0012] In some embodiments, the obtaining an initial trajectory according to a spatial model includes the following steps:

[0013] Generate a first trajectory based on a convex polyhedron corridor;

[0014] Or generate a second trajectory based on a signed distance field.

[0015] In some embodiments, generating the first trajectory based on the convex polyhedron corridor includes the following steps:

[0016] Perform a dilation operation on the obstacle size according to the fuselage size of the vertical takeoff and landing drone to generate environmental information;

[0017] Obtain an initial geometric path from the current position to the termination position through a path search algorithm;

[0018] Generate a convex polyhedron corridor according to the environmental information and the initial geometric path;

[0019] Construct a cost function according to the convex polyhedron corridor;

[0020] Generate the first trajectory according to the convex polyhedron corridor and the cost function.

[0021] In some embodiments, constructing the cost function according to the convex polyhedron corridor includes the following steps:

[0022] Obtain the minimum inscribed circle of the convex polyhedron corridor;

[0023] Obtain a first radius of the minimum inscribed circle, and use the length of the first radius as a first distance;

[0024] Obtain the outer normal vector of each face of the convex polyhedron corridor;

[0025] Obtain a preset plane formed by moving the first preset point along the outer normal vector into the interior of the convex polyhedron corridor by the first distance;

[0026] Obtain a second distance from the first preset point to the preset plane;

[0027] If the second distance is positive, use a smoothing loss function to calculate the cost and gradient to obtain the cost function.

[0028] In some embodiments, parameterize the first arc length of the first trajectory with a preset resolution to obtain first discrete data points;

[0029] Perform cubic spline fitting on the first discrete data points to obtain the target trajectory;

[0030] Obtain the first position of the vertical takeoff and landing drone at each second arc length on the target trajectory;

[0031] Obtain the first velocity direction of the first position.

[0032] Obtain a first cross-section perpendicular to the first velocity direction, and the first cross-section intersects the convex polyhedron corridor to form a convex polygon;

[0033] Take the shortest distance from the first position to each side of the convex polygon as the second radius;

[0034] Perform cubic spline fitting on the second radius with respect to the second arc length to obtain the variable-radius pipeline.

[0035] In some embodiments, the generating the second trajectory based on the signed distance field includes the following steps:

[0036] According to the fuselage size of the vertical takeoff and landing drone, perform dilation operation on the obstacle size to generate environmental information;

[0037] Obtain an initial geometric path from the current position to the termination position through a path search algorithm;

[0038] Construct a signed distance field according to the environmental information and the initial geometric path;

[0039] Perform trajectory planning in the signed distance field through the MINCO trajectory class to generate the second trajectory.

[0040] In some embodiments, the obtaining the target trajectory and the variable-radius pipeline by performing cubic spline fitting according to the initial trajectory includes the following steps:

[0041] Parameterize the third arc length of the second trajectory through a preset resolution to obtain second discrete data points;

[0042] Perform cubic spline fitting on the second discrete data points to obtain the target trajectory;

[0043] Take the third distance between the discrete second preset points on the target trajectory and the nearest obstacle as the third radius;

[0044] Perform cubic spline fitting on the third radius with respect to the third arc length of the target trajectory to obtain the variable-radius pipeline.

[0045] In some embodiments, the setting the contour constraint and the adaptive parameter according to the variable-radius pipeline includes the following steps:

[0046] Set the fourth arc length of the target trajectory as a preset trajectory;

[0047] Take the derivative of the variable-radius pipeline to obtain the derivative of the variable-radius pipeline;

[0048] Obtain the contour constraint according to the preset trajectory, the variable-radius pipeline, and the derivative of the variable-radius pipeline;

[0049] Obtain the maximum radius and the minimum radius of the target trajectory;

[0050] Obtain the maximum weight and the minimum weight of the flight speed of the vertical takeoff and landing unmanned aircraft;

[0051] Obtain the adaptive parameter according to the maximum radius, the minimum radius, the maximum weight, and the minimum weight;

[0052] In some embodiments, constructing the objective function according to the target trajectory, the contour constraint, and the adaptive parameter includes the following steps:

[0053] Set the fourth arc length of the target trajectory as the preset trajectory;

[0054] Constrain the current position of the vertical takeoff and landing unmanned aircraft through the contour constraint;

[0055] Obtain the tracking error between the current position of the vertical takeoff and landing unmanned aircraft and the preset trajectory, and obtain the longitudinal error and the lateral contour error;

[0056] Adjust the flight speed of the vertical takeoff and landing unmanned aircraft through the adaptive parameter;

[0057] Obtain the objective function according to the longitudinal error, the lateral contour error, the flight speed of the vertical takeoff and landing unmanned aircraft, and the state input change rate;

[0058] To achieve the above object, another aspect of the embodiments of the present invention provides a pipe-based tailstock type vertical takeoff and landing unmanned aircraft regulation and control device, and the device includes:

[0059] A first module, configured to obtain an initial trajectory according to a spatial model;

[0060] A second module, configured to obtain a target trajectory and a variable-radius pipeline through cubic spline fitting according to the initial trajectory;

[0061] A third module, configured to set a contour constraint and an adaptive parameter according to the variable-radius pipeline;

[0062] A fourth module, configured to construct an objective function according to the target trajectory, the contour constraint, and the adaptive parameter;

[0063] A fifth module, configured to preset a sideslip angle constraint of the vertical takeoff and landing unmanned aircraft;

[0064] The sixth module is used to construct a pipeline-based model predictive contour control framework according to the objective function, the contour constraint, the adaptive parameter, and the sideslip angle constraint;

[0065] wherein, the pipeline-based model predictive contour control framework is used to plan and control a vertical takeoff and landing unmanned aerial vehicle.

[0066] To achieve the above object, on the other hand, an embodiment of the present invention provides an electronic device, which includes a memory and a processor. The memory stores a computer program, and when the processor executes the computer program, it implements the aforementioned pipeline-based tail-sitter vertical takeoff and landing unmanned aerial vehicle planning and control method.

[0067] To achieve the above object, on the other hand, an embodiment of the present invention provides a computer-readable storage medium, which stores a computer program. When the computer program is executed by a processor, it implements the aforementioned pipeline-based tail-sitter vertical takeoff and landing unmanned aerial vehicle planning and control method.

[0068] To achieve the above object, on the other hand, an embodiment of the present invention provides a computer program product or a computer program. The computer program product or the computer program includes computer instructions, and the computer instructions are stored in a computer-readable storage medium. The processor of the computer device can read the computer instructions from the computer-readable storage medium, and when the processor executes the computer instructions, the computer device executes the aforementioned pipeline-based tail-sitter vertical takeoff and landing unmanned aerial vehicle planning and control method.

[0069] The embodiments of the present invention at least include the following beneficial effects: The present invention provides a pipeline-based tail-sitter vertical takeoff and landing unmanned aerial vehicle planning and control method and device. This solution obtains an initial trajectory through a spatial model; according to the initial trajectory, through cubic spline fitting, a target trajectory and a variable-radius pipeline are obtained, which reasonably describes the environmental information and can complete more complex obstacle avoidance tasks; according to the variable-radius pipeline, contour constraints are set to make obstacle avoidance more accurate, and an adaptive parameter mechanism is introduced, which can better balance flight speed and accuracy and improve the anti-interference performance; according to the target trajectory, the contour constraint, and the adaptive parameter, an objective function is constructed; the sideslip angle constraint of the vertical takeoff and landing unmanned aerial vehicle is preset to simplify the model and improve the real-time performance of the solution; according to the objective function, the contour constraint, the adaptive parameter, and the sideslip angle constraint, a pipeline-based model predictive contour control framework is constructed, which can improve the performance and robustness of the vertical takeoff and landing unmanned aerial vehicle planning and control. Description of the Drawings

[0070] To more clearly illustrate the technical solutions in the embodiments of the present invention, the following will briefly introduce the accompanying drawings required for the description of the embodiments. Obviously, the accompanying drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other accompanying drawings can be obtained based on these drawings.

[0071] Figure 1 is a flowchart of the tailstock type vertical takeoff and landing UAV regulation and control method based on pipelines provided by an embodiment of the present invention;

[0072] Figure 2 is a schematic structural diagram of a vertical takeoff and landing UAV provided by an embodiment of the present invention;

[0073] Figure 3 is a schematic diagram of the fuselage system of a vertical takeoff and landing UAV provided by an embodiment of the present invention;

[0074] Figure 4 is a schematic diagram of the front-end path planning trajectory and environmental information representation based on a convex polyhedron corridor provided by an embodiment of the present invention;

[0075] Figure 5 is a schematic diagram of the front-end path planning trajectory and environmental information representation based on a signed distance field provided by an embodiment of the present invention;

[0076] Figure 6 is a schematic diagram of the generated trajectory and pipeline-type environment representation provided by an embodiment of the present invention;

[0077] Figure 7 is a schematic diagram of the trajectory error and contour constraint provided by an embodiment of the present invention;

[0078] Figure 8 is a schematic diagram of the contour error and progress error provided by an embodiment of the present invention;

[0079] Figure 9 is a schematic diagram of the process framework of the overall VTOL regulation and control scheme based on pipelines provided by an embodiment of the present invention;

[0080] Figure 10 is a schematic diagram of the hardware structure of an electronic device provided by an embodiment of the present invention. Detailed implementation manners

[0081] In order to make the objectives, technical solutions and advantages of the present invention more clearly understood, the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention, but not to limit the present invention. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the embodiments of the present invention. They are only examples of devices and methods consistent with some aspects of the embodiments of the present invention detailed in the appended claims.

[0082] It should be noted that although functional modules are divided in the system schematic diagram and the logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in a different order from the module division in the system or the order in the flowchart. The terms "first / S100" and "second / S200" in the specification, claims and the above-mentioned drawings can be used herein to describe various concepts, but unless otherwise specified, these concepts are not limited by these terms. These terms are only used to distinguish one concept from another. For example, without departing from the scope of the embodiments of the present invention, the first information can also be referred to as the second information, and similarly, the second information can also be referred to as the first information. Depending on the context, the words "if" and "when" as used herein can be interpreted as "when...", "while...", or "in response to determining".

[0083] The terms "at least one", "a plurality of", "each", "any one", etc. used in the present invention, at least one includes one, two or more than two, a plurality of includes two or more than two, each refers to each of the corresponding plurality, and any one refers to any one of the plurality.

[0084] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those skilled in the technical field to which the present invention belongs. The terms used herein are only for the purpose of describing the embodiments of the present invention and are not intended to limit the present invention.

[0085] With the continuous development of unmanned technology, the application of rotor unmanned aerial vehicles (UAVs) is becoming more and more extensive, but the problem of its endurance has not been properly solved. Fixed-wing UAVs utilize the advantages of aerodynamics and have better endurance, and are more advantageous in both manned and cargo transportation, but they have higher requirements for takeoff and landing sites and cannot hover at any time. The tail-sitter vertical takeoff and landing UAV combines the advantages of high flight efficiency of fixed-wing UAVs and small dependence on takeoff and landing sites of rotor UAVs, and has broad application prospects. Completing its navigation task requires appropriate planning and control schemes.

[0086] For the trajectory planning and control scheme of quadrotors, a hierarchical approach is usually adopted. The trajectory is planned based on the differential flatness of the quadrotor, and then control methods such as proportional-integral-derivative controller (PID) or model predictive control (MPC) are used for tracking. For quadrotors, there is also a corridor-based model predictive contour controller (CMPCC) that uses the flight corridor as a hard safety constraint, takes into account environmental obstacle avoidance, and realizes the trajectory tracking of quadrotors. For vertical takeoff and landing fixed-wing (VTOL) aircraft, relatively advanced research also calculates the differential flatness of VTOL aircraft, designs the trajectory planning accordingly, and then uses MPC for tracking. For the tracking scheme of canard tail-sitter VTOL UAVs, a set of model predictive contour controllers (MPCC) realizes the trajectory tracking.

[0087] The current trajectory planning and control scheme of aircraft generally involves creating a trajectory containing time information by considering the robot model and differential flatness at the front end, and then using methods such as PID or MPC for tracking at the back end. However, for VTOL fixed-wing aircraft, the non-linear aerodynamic forces make the model more complex. If this framework is still used, the fixed time information calculated based on a possibly mismatched model in the early stage may lead to error accumulation during later tracking, making it difficult to resist disturbances in real time. Moreover, the technical scheme based on differential flatness has strict conditions, requires cumbersome and precise differential flatness-based planning calculations, has poor real-time performance, and not all aircraft models can be derived for differential flatness. Although the existing tracking scheme for canard tail-sitter VTOL UAVs only requires a geometric path, it tracks the UAV trajectory by manually specifying a reference fixed geometric path, without a high-level planning framework to calculate an excellent geometric path. And this algorithm does not consider the environment in real time to achieve obstacle avoidance, making it difficult to overcome complex environments. This algorithm is only limited to one tracking scheme. CMPCC takes into account environmental information compared to canard MPCC, but its trajectory and corridor are given in advance using Teach-repeat-replan. Its trajectory is not very close to the safe area, leaving too small a safety margin for tracking, and it is easy to rub against the edge of the corridor in narrow places, which is somewhat dangerous and does not make full use of the space. For UAVs, the safety of this method is relatively low. In addition, the characterization of its contour constraint is not precise enough, and it cannot make full use of the prior environmental information in the front area to generate a guiding prediction for how to track the trajectory.

[0088] In view of this, as Figure 1 shown, the embodiments of the present invention provide a trajectory planning and control method for canard tail-sitter VTOL UAVs based on a pipeline, which may include but is not limited to steps S100 to S600:

[0089] Step S100, obtaining an initial trajectory according to the space model;

[0090] Step S200, obtaining a target trajectory and a variable radius pipeline through cubic spline fitting according to the initial trajectory;

[0091] Step S300, setting contour constraints and adaptive parameters according to the variable radius pipeline;

[0092] Step S400, constructing an objective function according to the target trajectory, the contour constraint and the adaptive parameter;

[0093] Step S500, presetting the sideslip angle constraint of the vertical take-off and landing UAV;

[0094] Step S600, constructing a pipeline-based model prediction profile control framework according to the objective function, the profile constraint, the adaptive parameter and the sideslip angle constraint;

[0095] The pipeline-based model predictive contour control framework is used to plan and control vertical take-off and landing UAVs.

[0096] In steps S100 to S600 of some embodiments, a scheme of representing the environment as a pipeline is designed in the framework of planning and controlling the vertical take-off and landing UAV to describe the safe area, and a trajectory closer to the safe space in the environment and a larger pipeline generated around this trajectory are obtained through a spatial model. This not only reasonably describes the environmental information, can complete more complex obstacle avoidance tasks, but also leaves more position margins for later tracking. In addition, the path representation generated thereby is concise, does not contain time information, and does not require differential flatness, so it does not introduce mismatch errors in the front-end planning part, and all models are available. Because the pipeline is differentiable, a more accurate contour constraint is designed for the pipeline, which has a certain predictability for the future environment, and an adaptive parameter mechanism is introduced into the pipeline-based model predictive contour control scheme (Pipe based Model Predict Contouring Control, PMPCC), which can better balance the flight speed and accuracy, and has better anti-interference performance. In addition, the physical characteristics of the vertical take-off and landing UAV (VTOL) are used to introduce the sideslip angle constraint to simplify the model and ensure the real-time solution.

[0097] In some embodiments, for example Figure 2 If we study the vertical take-off and landing UAV shown in the figure, we can build Figure 3 The vertical take-off and landing UAV body shown in the figure constructs a mathematical model of the vertical take-off and landing UAV. Exemplarily, the mathematical model may include a motion mathematical model in a world coordinate system (world system) and an aerodynamic force in a carrier coordinate system (body system).

[0098] Mathematical model of motion: (world system)

[0099]

[0100] wherein, represents the derivative of the position of the UAV in the inertial coordinate system; v represents the flight speed of the UAV in the inertial coordinate system; R represents the attitude from the body coordinate system to the world coordinate system; a T represents the acceleration generated by the thrust; x b , y b , z b represent the coordinate axes of the body; represents the derivative of the flight speed of the UAV in the inertial coordinate system; g represents the acceleration due to gravity; represents the reciprocal of the mass of the UAV; f a represents the aerodynamic force in the carrier coordinate system.

[0101] Aerodynamic force in the carrier / body coordinate system (body system):

[0102]

[0103] wherein, f a represents the aerodynamic force in the carrier coordinate system; f ax , f ay , f az represent the components of the aerodynamic force on the airflow coordinate system; α represents the angle of attack of the UAV; β represents the sideslip angle; L represents the lift force on the UAV; D represents the drag force on the UAV; Y represents the sideslip force on the UAV; ρ 空 represents the air density; V represents the modulus of the airspeed in the inertial system ||v a ||; S represents the wing area; C L represents the lift coefficient; C D represents the drag coefficient; C Y represents the sideslip force coefficient; (·) T represents the transpose operation; w represents the wind speed in the inertial system; v represents the flight speed of the UAV in the inertial coordinate system; v a represents the airspeed in the inertial system; (·) B represents the body system; represents the airspeed in the body coordinate system; respectively represent the components of the airspeed v a in the body coordinate system on the x, y, and z axes.

[0104] Among them, the lift coefficient, drag coefficient, and sideslip force coefficient are usually non-linear functions calibrated through wind tunnel experiments.

[0105] Exemplarily, assuming that the aircraft model is symmetric about the X-Z plane of the body, the following expressions are obtained:

[0106]

[0107] Assuming coordinated flight, the sideslip angle β = 0, that is When there is no wind, the velocity in the y - direction under the aircraft body system is 0, and the sideslip force coefficient C Y (α,β)=0. The model can be simplified through this sideslip angle constraint.

[0108] In step S100 of some embodiments, based on the pipeline description of the safe area, trajectories closer to the safe space in the environment are generated through two different spatial model schemes. Optionally, the spatial model can be a convex polyhedron corridor or a signed distance field. Based on the convex polyhedron corridor, a first trajectory can be generated, and based on the signed distance field, a second trajectory can be generated. The first trajectory and the second trajectory are the initial trajectories.

[0109] In some embodiments, in the step of generating the first trajectory based on the convex polyhedron corridor, it may include but is not limited to steps S111 to S115:

[0110] Step S111, according to the body size of the vertical take - off and landing unmanned aerial vehicle, perform an inflation operation on the obstacle size to generate environmental information;

[0111] Step S112, obtain the initial geometric path from the current position to the termination position through a path - search algorithm;

[0112] Step S113, generate a convex polyhedron corridor according to the environmental information and the initial geometric path;

[0113] Step S114, construct a cost function according to the convex polyhedron corridor;

[0114] Step S115, generate the first trajectory according to the convex polyhedron corridor and the cost function.

[0115] In steps S111 to S113 of some embodiments, at the front end, the obstacles are inflated according to the body size of the unmanned aerial vehicle, and then the Rapidly - exploring Random Tree (RRT) or A* algorithm is used to search for the initial geometric path from the current position to the termination point position. Based on the environment of these obstacles, combined with the initial geometric path and the open - source project gcopter method, a convex polyhedron corridor is generated. These convex polyhedron corridors define the areas where the unmanned aerial vehicle can move in space, ensuring that the trajectory of the unmanned aerial vehicle not only meets the mission requirements but also does not violate the space constraints.

[0116] In steps S114 to S115 of some embodiments, by constructing a partial cost function optimized during the generation of the convex polyhedron corridor, according to the convex polyhedron corridor and the constructed cost function, a first trajectory as close as possible to the center of the convex polyhedron flight corridor is obtained.

[0117] In some embodiments, step S114 may include, but is not limited to, steps S1141 to S1146:

[0118] Step S1141, obtaining the minimum inscribed circle of the convex polyhedron corridor;

[0119] Step S1142, obtaining the first radius of the minimum inscribed circle and taking the length of the first radius as the first distance;

[0120] Step S1143, obtaining the outer normal vector of each face of the convex polyhedron corridor;

[0121] Step S1144, obtaining the preset plane formed by moving the first preset point along the outer normal vector into the interior of the convex polyhedron corridor by the first distance;

[0122] Step S1145, obtaining the second distance from the first preset point to the preset plane;

[0123] Step S1146, if the second distance is positive, calculating the cost and gradient using a smooth loss function to obtain the cost function.

[0124] In steps S1141 to S1146 of some embodiments, as Figure 4 shown, through the open-source project gcopter method of an efficient and versatile multi-rotor aircraft trajectory optimizer, the in-point of each convex polyhedron, that is, the center O of the minimum inscribed circle, can be obtained, and the first radius mindist of this minimum inscribed circle can also be obtained. The length of the first radius mindist is taken as the first distance. Exemplarily, when the first preset point on the preset flight trajectory is outside each face of the convex polyhedron, the cost can be calculated in the following manner:

[0125] 1. For each face of the convex polyhedron, calculate the outer normal vector normal of this face;

[0126] 2. Calculate the distance from the first preset point to the face obtained by moving mindisy into the convex polyhedron along the outer normal vector of this face, that is, first obtain the preset plane formed by moving the first preset point along the outer normal vector into the interior of the convex polyhedron by the first distance, and then obtain the second distance from this first preset point to this preset plane;

[0127] 3. Determine whether the second distance is positive. If the second distance is positive, calculate the cost and gradient using a smooth loss function.

[0128] Optionally, the second distance from the first preset point to the preset plane can be calculated through dot product and offset. The positive or negative value of the second distance indicates that the first preset point is on both sides of the preset plane. If the second distance is negative, it means that the first preset point is on the side of the preset plane facing the inside of the convex polyhedron; if the second distance is positive, it means that the first preset point is outside the convex polyhedron. The expression of the smooth loss function is as follows:

[0129]

[0130] In the formula, smoothedL1(μ, s) represents the smooth loss function; s represents the second distance from the first preset point to the preset plane; μ represents the preset segmentation interval, which is generally small.

[0131] Compared with the general method, the environmental obstacle cost at any position inside the corridor is consistently 0, and there is only a cost value outside the corridor, which causes the trajectory to easily approach the corridor edge and is not conducive to tracking. Through the above calculation methods of the cost and gradient of the cost function in the embodiments of the present invention, the trajectory can no longer be constrained inside the convex polyhedron, but can be as close as possible to the points inside the convex polyhedron, so as to obtain a trajectory as close as possible to the center of the flight corridor of the convex polyhedron. Since the embodiments of the present invention only use the geometric path information of the trajectory rather than time information, the resulting change in time optimization has no impact.

[0132] In some embodiments, in the step of generating the second trajectory based on the signed distance field, it may include but is not limited to steps S121 to S124:

[0133] Step S121, perform a dilation operation on the obstacle size according to the fuselage size of the vertical takeoff and landing unmanned aerial vehicle to generate environmental information;

[0134] Step S122, obtain the initial geometric path from the current position to the termination position through a path search algorithm;

[0135] Step S123, construct a signed distance field according to the environmental information and the initial geometric path;

[0136] Step S124, perform trajectory planning in the signed distance field through the MINCO trajectory class to generate the second trajectory.

[0137] In steps S121 to S124 of the game embodiment, at the front end, the obstacles are inflated according to the body size of the drone. Then, the Rapidly-exploring Random Tree (RRT) or A* algorithm is used to search for the initial geometric path from the current position to the termination point position. Next, based on the environment of the obstacles and in combination with the initial geometric path, an Euclidean Signed Distance Field (ESDF) is constructed. The MINCO trajectory class in the open-source project gcopter is used to plan a smooth second trajectory that is far from the obstacles in the signed distance field. In the MINCO (Minimum Control) trajectory class, the intermediate points and time vectors on the trajectory are used to parameterize the trajectory, which means that the trajectory can be generated and optimized by adjusting the positions of these intermediate points and the time assigned to each segment of the trajectory. For any given intermediate points and time vectors, a trajectory that satisfies the optimality conditions can be uniquely determined. Together, these intermediate points and time vectors define the global shape of the trajectory and the specific duration of each segment.

[0138] In step S200 of some embodiments, according to the initial trajectory, through cubic spline fitting, the target trajectory and the variable-radius pipeline can be obtained. Optionally, based on the first trajectory generated from the convex polyhedron corridor, through cubic spline fitting, the target trajectory and the variable-radius pipeline can be obtained; or based on the second trajectory generated from the signed distance field, through cubic spline fitting, the target trajectory and the variable-radius pipeline can be obtained.

[0139] In some embodiments, in the step of obtaining the target trajectory and the variable-radius pipeline through cubic spline fitting based on the first trajectory generated from the convex polyhedron corridor, it may include but is not limited to steps S211 to S217:

[0140] Step S211, parameterize the first arc length of the first trajectory with a preset resolution to obtain the first discrete data points;

[0141] Step S212, perform cubic spline fitting on the first discrete data points to obtain the target trajectory;

[0142] Step S213, obtain the first position of the vertical takeoff and landing drone at each second arc length on the target trajectory;

[0143] Step S214, obtain the first velocity direction of the first position;

[0144] Step S215, obtain the first cutting plane perpendicular to the first velocity direction, and the first cutting plane intersects the convex polyhedron corridor to form a convex polygon;

[0145] Step S216, take the shortest distance from the first position to each side of the convex polygon as the second radius;

[0146] Step S217: Perform cubic spline fitting on the second radius with respect to the second arc length to obtain the variable-radius pipeline.

[0147] In steps S211 to S217 of some embodiments, after generating the first trajectory based on the convex polyhedron corridor, perform arc length parameterization at a preset resolution, that is, parameterize the first arc length of the first trajectory to obtain the first discrete data points. Using cubic spline fitting on the first discrete data points, the target trajectory P(θ) can be obtained. Exemplarily, the following expression can be obtained using cubic spline fitting:

[0148] P(θ) = [X(θ) Y(θ) Z(θ)] T (6)

[0149] In the formula, P(θ) represents the target trajectory, which is the reference trajectory in the three-dimensional space used for backend tracking. It is composed of the reference trajectories in the three dimensions of X, Y, and Z, namely X(θ), Y(θ), and Z(θ). The independent variable is the arc length θ. At each second arc length θ on the target trajectory, obtain the first position P of the vertical takeoff and landing drone and the first velocity direction v at this first position. Then, at this first position, make a tangent plane Φ perpendicular to the first velocity direction. The tangent plane intersects with the convex polyhedron corridor to form a convex polygon. Take the shortest distance from the first position P to each side of the convex polygon as the second radius r. As Figure 4 shown, the second radius r is then the information representation of the environmental constraints received by this first position P. Perform cubic spline fitting on the second radius r with respect to the second arc length θ to obtain the variable-radius pipeline R(θ), and then the variable-radius pipeline as shown in Figure 6 can be obtained. Since the cubic spline is differentiable, the derivative P′(θ) of the target trajectory and the derivative R′(θ) of the variable-radius pipeline can also be obtained by differentiation.

[0150] In some embodiments, in the steps of obtaining the target trajectory and the variable-radius pipeline through cubic spline fitting for the second trajectory generated based on the signed distance field, it may include but is not limited to steps S221 to S224:

[0151] Step S221: Parameterize the third arc length of the second trajectory at a preset resolution to obtain the second discrete data points;

[0152] Step S222: Perform cubic spline fitting on the second discrete data points to obtain the target trajectory;

[0153] Step S223: Take the third distance between the discrete second preset points on the target trajectory and the nearest obstacle as the third radius;

[0154] Step S224: Perform cubic spline fitting on the third radius with respect to the third arc length of the target trajectory to obtain the variable-radius pipeline.

[0155] In steps S221 to S224 of some embodiments, after generating the second trajectory based on the signed distance field, arc length parameterization is performed according to a preset resolution, that is, parameterizing the third arc length θ of the second trajectory to obtain second discrete data points. Using cubic spline to fit the second discrete data points, similar to formula (6), the target trajectory P(θ) can be obtained. At the second preset point (i.e., the second position P of the vertical takeoff and landing unmanned aerial vehicle) discrete on the target trajectory, its ESDF value is obtained. This ESDF value is the third distance from the second position to the nearest obstacle, and the third distance is denoted as the third radius r. A sphere can be made at this second position with the third radius as the radius, and a safe area without obstacles as shown in Figure 5 can be obtained, where Figure 5 The horizontal and vertical coordinates of are the coordinates of the two-dimensional plane, and the unit can be denoted as meters (m). Therefore, using the third radius as the information representation of the environmental constraint received by the second position, performing cubic spline fitting on the third radius with respect to the third arc length, a variable radius pipe R(θ) can be obtained, and then a variable radius pipe as shown in Figure 6 can be obtained. Since the cubic spline is differentiable, the derivative P′(θ) of the target trajectory and the derivative R′(θ) of the variable radius pipe can also be obtained by taking the derivative.

[0156] In some alternative embodiments, a three-dimensional target trajectory P(θ) is optimized through two alternative schemes (based on convex polyhedron corridors and based on signed distance fields) to obtain a target trajectory closer to the safe space in the environment, and a larger pipe is generated around this trajectory to re-characterize the environment as a variable radius pipe R(θ), as shown in Figure 6 both taking the arc length θ as a variable.

[0157] In some embodiments, a controller framework for a pipe-based model predictive contour control scheme (PMPCC) is constructed, including obtaining the target trajectory and the variable radius pipe to be tracked, and also including the state variables selected by PMPCC, pipe-based contour constraints, pipe-based adaptive parameters, the objective function of the PMPCC controller, and VTOL sideslip angle constraints, which will be described in detail later.

[0158] In some embodiments, the state variables selected by PMPCC may include but are not limited to the following state variables:

[0159]

[0160] Among them, x is the state variable of the vertical takeoff and landing unmanned aerial vehicle; p, v, and q are the position, velocity, and quaternion of the world coordinate system; f tis the thrust; ω is the angular velocity; θ is the arc length; u is the control input quantity, which consists of the arc length change rate V θ , the thrust change rate df t , and the angular acceleration dω. Combining the aerodynamic data from the wind tunnel test and substituting the kinematic and dynamic formulas of the above motion mathematical model, the state equation can be obtained. Represent the third position of the vertical takeoff and landing UAV at time step k as p k =[x k , y k , z k T .

[0161] In some embodiments, step S300 may include but is not limited to steps S310 to S360:

[0162] Step S310, set the fourth arc length of the target trajectory as the preset trajectory;

[0163] Step S320, take the derivative of the variable radius pipeline to obtain the derivative of the variable radius pipeline;

[0164] Step S330, obtain the contour constraint according to the preset trajectory, the variable radius pipeline, and the derivative of the variable radius pipeline;

[0165] Step S340, obtain the maximum radius and the minimum radius of the target trajectory;

[0166] Step S350, obtain the maximum weight and the minimum weight of the flight speed of the vertical takeoff and landing UAV;

[0167] Step S360, obtain the adaptive parameter according to the maximum radius, the minimum radius, the maximum weight, and the minimum weight.

[0168] In steps S310 to S360 of some embodiments, as Figure 7 shown, in order to make the third position p k as much as possible in the cone representing the environmental constraint, that is, to make the lateral contour error less than the environmental radius R here, the following contour constraint is designed:

[0169]

[0170] Among them, in the contour constraint, the present invention embodiment uses the software package acados that can provide a fast and embedded system - applicable nonlinear optimal control solver to perform optimal control solution for formula (8), and this process is repeated in real time.

[0171] In the formula, represents the projection contour error obtained by projecting the third position onto the tangent plane;​ Represents the preset trajectory of the non-uniform pipe at; Represents the preset trajectory, referring to the preset trajectory in the current optimal control solution; θ linearized is the preset trajectory in the previous optimal control solution; R(θ linearized ) represents θ linearized of the non-uniform pipe at; R′(θ linearized ) represents θ linearized of the derivative of the radius of the non-uniform pipe at.

[0172] In the embodiment of the present invention, the non-uniform pipe is the complete space allowing the aircraft to fly. At each arc length θ, the pipe radius R(θ) and the radius change rate at that place, that is, the derivative R′(θ) of the pipe radius, can be obtained. Accordingly, the non-uniform pipe is approximated at that place. If the radius change rate at that place is not considered and only the pipe radius at that place is considered, then the pipe at that place is approximately barrel-shaped. If the radius change rate at that place is also considered, then the pipe at that place is approximately conical.

[0173] Since the pipe is differentiable, continuous R′(θ) can be obtained, which takes into account the trend of the cone to tighten or expand as θ changes, and simulates the morphological changes of the front area environment to a certain extent. This environmental constraint is more accurate than a pure barrel and has a certain predictability.

[0174] In the embodiment of the present invention, the weight coefficient of the arc length change rate V θ is denoted as ρ. This weight coefficient ρ has a preset maximum value and minimum value, and will be adaptively adjusted according to the maximum value and minimum value of the radius R of the entire variable-diameter uniform pipe. Where R is larger, that is, where the allowable aircraft activity range is wider, the weight coefficient ρ of the arc length change rate V θ will be a little larger, so that the flight speed of the aircraft will also be a little larger.

[0175] Exemplarily, the weight coefficient ρ of the arc length change rate V θ in the constructed objective function can be dynamically adjusted according to the variable-radius pipe R(θ), taking the maximum radius R max and the minimum radius R min of the entire target trajectory, taking the maximum weight ρ θ and the minimum weight ρ max of the arc length change rate V min , and arranging the weight coefficient ρ of each time step within the prediction range according to the preset trajectory θ linearizedThe radius R corresponding to the position is linearly remapped again, such that when R is large, the weight coefficient ρ is large, allowing the vertical takeoff and landing drone to travel at a faster speed. Conversely, when R is small, the weight coefficient ρ is small, and the vertical takeoff and landing drone travels at a slower speed. Then, the adaptive parameter weight ρ(θ) has the following expression:

[0176]

[0177] By introducing the adaptive parameter mechanism, the flight speed and accuracy can be better balanced, and the anti-interference performance is better.

[0178] In some embodiments, step S400 may include, but is not limited to, steps S410 to S450:

[0179] Step S410, setting the fourth arc length of the target trajectory as a preset trajectory;

[0180] Step S420, constraining the current position of the vertical takeoff and landing drone through the contour constraint;

[0181] Step S430, obtaining the tracking error between the current position of the vertical takeoff and landing drone and the preset trajectory, to obtain a longitudinal error and a lateral contour error;

[0182] Step S440, adjusting the flight speed of the vertical takeoff and landing drone through the adaptive parameter;

[0183] Step S450, obtaining the objective function according to the longitudinal error, the lateral contour error, the flight speed of the vertical takeoff and landing drone, and the state input change rate.

[0184] In standard MPC, the objective function is the distance difference between the position p of the drone at the prediction time step k k and its reference position p refer . The reference position p refer usually comes from the front-end trajectory with time information. Generally, timing starts from the start of tracking, and the position point corresponding to the moment on the trajectory is taken. While MPCC does not require the time information of the front-end trajectory, but uses the arc length information θ, and the position point it tracks is determined by the arc length θ. Theoretically, MPCC attempts to track the point on the trajectory that is closest to p k at the position p k . Since finding the closest point is an optimization process, to avoid nested optimization, in the embodiments of the present invention, θ is designed as a preset trajectory in the state space The tracking error at the current third position p k from is then as Figure 7 shown and is divided into a longitudinal error and the lateral profile error Exemplarily, take a preset trajectory and make a tangent plane perpendicular to the tangent line at that point p k Projecting onto the tangent plane can obtain and which can approximately represent the longitudinal error and the lateral profile error These two errors will be part of the objective function. Another part of the objective function is the arc length change rate V θ multiplied by the negative value of the weight, which can ensure that the aircraft has a certain traveling speed while ensuring a small tracking error. Additionally, the change rate dU k of the state input will also be part of the objective function to ensure the smoothness of the control input. Then, the expression of the following objective function can be obtained:

[0185]

[0186] where J represents the objective function; N is the prediction step; k is the current time step; e l (θ k ) is the tracking progress error at the arc length θ k at time step k; e c (θ k ) is the profile error at the arc length θ k at time step k; dU k is the input change rate at time step k, V θ is the arc length change rate; Q l , Q c , Q u , ρ are the weight coefficients of the four costs respectively.

[0187] In some embodiments, as Figure 8 shown, denote the current state point as P, P(θ k ) is the expected tracking point at step k, and the total error between the current state point and the expected tracking point is e = P - P(θ k ). Denote the unit tangent vector of the tangent line at the expected tracking point P(θ k ) as t k , then P′(θ k ) is the derivative of P(θ k ) with respect to θ at θ k , then there is:

[0188] e l (θ k ) = t k ·(P - P(θ k))

[0189] |e c (θ k )| = |t k ×(P - P(θ k )| (11)

[0190] By setting the upper bound of the decision variable θ to the total arc length of the entire target trajectory, the stop at the end point can be naturally completed. Exemplarily, for the decision variables in formula (7), i.e., the state quantity x and the control input quantity u of the vertical takeoff and landing unmanned aerial vehicle, upper bounds are imposed, so the upper bound of x is x max and the upper bound of u is u max , where θ max belongs to x max . In acados, setting the upper bound θ max of the arc length θ in the decision variables to the total arc length of the entire target trajectory means that the required traveled arc length θ cannot exceed the total arc length of the entire target trajectory, which can make the aircraft stop when tracking the trajectory to the end point.

[0191] In step S500 of some embodiments, in the study of the vertical takeoff and landing unmanned aerial vehicle analysis, using the physical characteristics of the vertical takeoff and landing unmanned aerial vehicle, it is assumed that the sideslip angle is 0, so the side force can be ignored, thereby simplifying the model, reducing the solution difficulty, and making the solution easier to complete in real time. Exemplarily, the constraint of the sideslip angle being 0 is imposed in the following way:

[0192]

[0193] where is the y-axis component of the airspeed v a in the body system in the inertial system. The inequality constraint can be realized by the external cost of acados, and acados is used for nonlinear optimization solution.

[0194] In step S600 of some embodiments, the pipeline-based model predictive contour control framework (PMPCC) is constructed by an objective function, a contour constraint, an adaptive parameter, and a sideslip angle constraint, and the pipeline-based model predictive contour control framework is used for planning and controlling the vertical takeoff and landing unmanned aerial vehicle.

[0195] Such as Figure 9As shown in the figure, a method for controlling a tail-sitter vertical takeoff and landing (VTOL) unmanned aerial vehicle (UAV) based on a pipeline according to an embodiment of the present invention designs a scheme for environmental characterization using a pipeline to describe a safe area. Two schemes (including a convex polyhedron corridor-based scheme and a signed distance field-based scheme) are used to generate a target trajectory P(θ) closer to the safe space in the environment, reconstruct the environmental characterization, obtain a larger pipeline R(θ) surrounding this trajectory, design more accurate contour constraints for backend tracking based on R(θ), introduce an adaptive parameter mechanism, use the PMPCC framework for tracking, and introduce a sideslip angle constraint using the physical characteristics of the VTOL to simplify the model. The required thrust a T and the angular velocity ω are calculated using acados, and the throttle and torque τ are calculated using the Px4 firmware at the bottom layer to track the thrust a T and the angular velocity ω in real time. In the Px4 firmware, the tracking of the thrust and the angular velocity is achieved through proportional gain K and PID control.

[0196] An embodiment of the present invention further provides a control device for a tail-sitter vertical takeoff and landing UAV based on a pipeline, which can implement the above-mentioned method for controlling a tail-sitter vertical takeoff and landing UAV based on a pipeline. The device includes:

[0197] A first module for obtaining an initial trajectory according to a spatial model;

[0198] A second module for obtaining a target trajectory and a variable-radius pipeline through cubic spline fitting based on the initial trajectory;

[0199] A third module for setting contour constraints and adaptive parameters according to the variable-radius pipeline;

[0200] A fourth module for constructing an objective function according to the target trajectory, the contour constraints, and the adaptive parameters;

[0201] A fifth module for presetting a sideslip angle constraint for the vertical takeoff and landing UAV;

[0202] A sixth module for constructing a pipeline-based model predictive contour control framework according to the objective function, the contour constraints, the adaptive parameters, and the sideslip angle constraint;

[0203] Among them, the pipeline-based model predictive contour control framework is used to plan and control the vertical takeoff and landing UAV.

[0204] It can be understood that the content in the above method embodiments is applicable to the device embodiments of the present invention. The functions specifically implemented by the device embodiments of the present invention are the same as those in the above method embodiments, and the beneficial effects achieved are also the same as those in the above method embodiments.

[0205] An embodiment of the present invention further provides an electronic device, which includes a processor and a memory. The memory stores a computer program, and when the processor executes the computer program, it implements the above-mentioned method for controlling a tail-sitting vertical takeoff and landing unmanned aerial vehicle based on a pipeline. The electronic device can be any intelligent terminal including a tablet computer, a vehicle-mounted computer, etc.

[0206] It can be understood that the content in the above method embodiments is applicable to the device embodiments of the present invention. The functions specifically implemented by the device embodiments of the present invention are the same as those of the above method embodiments, and the beneficial effects achieved are also the same as those of the above method embodiments.

[0207] Refer to Figure 10 , Figure 10 which schematically shows the hardware structure of an electronic device in another embodiment. The electronic device includes:

[0208] A processor 701, which can be implemented in ways such as a general-purpose CPU (Central Processing Unit), a microprocessor, an application-specific integrated circuit (ASIC), or one or more integrated circuits, and is used to execute relevant programs to implement the technical solutions provided by the embodiments of the present invention;

[0209] A memory 702, which can be implemented in forms such as a read-only memory (ROM), a static storage device, a dynamic storage device, or a random access memory (RAM). The memory 702 can store an operating system and other application programs. When implementing the technical solutions provided by the embodiments of this specification through software or firmware, the relevant program codes are stored in the memory 702 and are called by the processor 701 to execute a method for controlling a tail-sitting vertical takeoff and landing unmanned aerial vehicle based on a pipeline according to an embodiment of the present invention;

[0210] An input / output interface 703, which is used to implement information input and output;

[0211] A communication interface 704, which is used to implement communication interaction between the device and other devices, and can implement communication through a wired method (such as USB, network cable, etc.) or through a wireless method (such as a mobile network, WIFI, Bluetooth, etc.);

[0212] A bus 705, which transmits information between various components of the device (such as the processor 701, the memory 702, the input / output interface 703, and the communication interface 704);

[0213] Among them, the processor 701, the memory 702, the input / output interface 703, and the communication interface 704 are communicatively connected to each other inside the device through the bus 705.

[0214] An embodiment of the present invention also provides a computer-readable storage medium storing a computer program, which when executed by a processor implements the above-described method for controlling a tail-sitting vertical takeoff and landing unmanned aerial vehicle based on a pipeline.

[0215] It can be understood that the content in the above method embodiments is applicable to this storage medium embodiment. The functions specifically implemented by this storage medium embodiment are the same as those in the above method embodiments, and the beneficial effects achieved are also the same as those in the above method embodiments.

[0216] An embodiment of the present invention also provides a computer program product or a computer program, which includes computer instructions stored in a computer-readable storage medium. The processor of the computer device can read the computer instructions from the computer-readable storage medium, and when the processor executes the computer instructions, the computer device executes the above-described method for controlling a tail-sitting vertical takeoff and landing unmanned aerial vehicle based on a pipeline.

[0217] In summary, the method and device for controlling a tail-sitting vertical takeoff and landing unmanned aerial vehicle based on a pipeline in the embodiments of the present invention have the following advantages:

[0218] 1. The embodiment of the present invention is a complete planning and control solution, which provides two ways to obtain a trajectory closer to the safe space in the environment and generate a larger pipeline around this trajectory. This not only reasonably describes the environmental information, can complete more complex obstacle avoidance tasks, but also leaves more position margins for later tracking.

[0219] 2. Compared with the solution of using differential flatness for planning and then using MPC for tracking, the path representation generated by the embodiment of the present invention is more concise, does not fix the time information in advance, so it will not introduce mismatch errors in the front-end planning part, and has better real-time anti-interference ability. Without differential flatness, the cumbersome and demanding calculations are avoided, and it can be used for all models, with a wider application range.

[0220] 3. Compared with the CMPCC scheme of quadrotors, the trajectory of the embodiment of the present invention is closer to the safe area, makes full use of the space, leaves more safety margins for tracking, and avoids rubbing against the edge of the corridor in narrow places, with better safety.

[0221] 4. Compared with the CMPCC scheme of quadrotors, the environmental characterization of the pipeline in the embodiments of the present invention is differentiable. Utilizing this characteristic, a more precise conical contour constraint is designed, which can utilize the prior information in the front area to have a certain predictability of the future environment and avoid obstacles more precisely.

[0222] 5. The embodiments of the present invention introduce an adaptive parameter mechanism based on the pipeline, which can better balance flight speed and accuracy and has better anti-interference performance.

[0223] 6. The embodiments of the present invention utilize the physical characteristics of VTOL to introduce sideslip angle constraints to simplify the model and improve the real-time performance of the solution.

[0224] In some alternative embodiments, the functions / operations mentioned in the block diagrams may not occur in the order mentioned in the operation diagrams. For example, depending on the functions / operations involved, two consecutively shown blocks may actually be executed substantially simultaneously or the blocks can sometimes be executed in the reverse order. In addition, the embodiments presented and described in the flowcharts of the present invention are provided by way of example for the purpose of providing a more comprehensive understanding of the technology. The disclosed methods are not limited to the operations and logical flows presented herein. Alternative embodiments are foreseeable, where the order of various operations is changed and where the sub-operations described as part of a larger operation are executed independently.

[0225] Furthermore, although the present invention has been described in the context of functional modules, it should be understood that, unless otherwise stated to the contrary, one or more of the functions and / or features described may be integrated in a single physical device and / or software module, or one or more functions and / or features may be implemented in separate physical devices or software modules. It can also be understood that a detailed discussion of the actual implementation of each module is not necessary for understanding the present invention. More precisely, considering the attributes, functions, and internal relationships of the various functional modules in the devices disclosed herein, the actual implementation of the module will be understood within the ordinary skills of an engineer. Therefore, those skilled in the art can implement the present invention as set forth in the claims without undue experimentation. It can also be understood that the specific concepts disclosed are merely illustrative and are not intended to limit the scope of the present invention, which is determined by the full scope of the appended claims and their equivalents.

[0226] If the above-mentioned functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or a part of this technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in various embodiments of the present invention. The aforementioned storage medium includes: various media that can store program codes, such as USB flash drives, mobile hard disks, read-only memories (ROM, Read-Only Memory), random access memories (RAM, Random Access Memory), magnetic disks, or optical discs.

[0227] The logic and / or steps represented in the flowchart or described in other ways herein, for example, can be considered as a predefined sequence list of executable instructions for implementing logical functions, and can be specifically implemented in any computer-readable medium for use by an instruction execution system, apparatus, or device (such as a computer-based system, a system including a processor, or other systems that can fetch and execute instructions from the instruction execution system, apparatus, or device), or in combination with these instruction execution systems, apparatus, or devices. For the purposes of this specification, a "computer-readable medium" can be any device that can contain, store, communicate, propagate, or transport a program for use by or in combination with an instruction execution system, apparatus, or device.

[0228] More specific examples (non-exhaustive list) of computer-readable media include the following: electrical connection parts with one or more wirings (electronic devices), portable computer disk cartridges (magnetic devices), random access memories (RAM), read-only memories (ROM), erasable programmable read-only memories (EPROM or flash memories), fiber optic devices, and portable compact disc read-only memories (CDROM). Additionally, the computer-readable medium can even be paper or other suitable media on which the program can be printed, because the program can be obtained electronically, for example, by optically scanning the paper or other media, then editing, interpreting, or processing it in other suitable ways as necessary, and then storing it in a computer memory.

[0229] It should be understood that various parts of the present invention can be implemented by hardware, software, firmware, or a combination thereof. In the above embodiments, multiple steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented by hardware, as in another embodiment, any one or a combination of the following technologies well known in the art can be used: discrete logic circuits having logic gate circuits for implementing logic functions on data signals, application specific integrated circuits having appropriate combinational logic gate circuits, programmable gate arrays (PGAs), field programmable gate arrays (FPGAs), and the like.

[0230] In the description of this specification, the descriptions referring to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples", etc. mean that the specific features, structures, materials, or characteristics described in connection with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials, or characteristics described can be combined in any one or more embodiments or examples in a suitable manner.

[0231] Although the embodiments of the present invention have been shown and described, those of ordinary skill in the art can understand that various changes, modifications, substitutions, and variations can be made to these embodiments without departing from the principles and spirit of the present invention, and the scope of the present invention is defined by the claims and their equivalents.

[0232] The above has specifically described the preferred embodiments of the present invention, but the present invention is not limited to the described embodiments. Those skilled in the art can also make various equivalent deformations or substitutions without departing from the spirit of the present invention, and these equivalent deformations or substitutions are all included within the scope defined by the claims of the present invention.

Claims

1. A pipeline-based tail-seat vertical take-off and landing UAV regulation and control method, characterized in that: The following steps are involved: Obtaining initial trajectory according to the spatial model; According to the initial trajectory, a target trajectory and a variable radius pipeline are obtained by cubic spline fitting; According to the variable radius pipeline, setting contour constraints and adaptive parameters; Constructing an objective function according to the target trajectory, the contour constraint and the adaptive parameter; Pre-set sideslip angle constraints for vertical take-off and landing UAVs; Constructing a pipeline-based model prediction profile control framework according to the objective function, the profile constraint, the adaptive parameter, and the sideslip angle constraint; The pipeline-based model predictive contour control framework is used to plan and control vertical take-off and landing UAVs.

2. The pipeline-based tail-seat vertical take-off and landing UAV regulation and control method according to claim 1 is characterized in that: The step of obtaining the initial trajectory according to the space model comprises the following steps: Based on the convex polyhedral corridor, the first trajectory is generated; Alternatively, based on the signed distance field, a second trajectory is generated.

3. The pipeline-based tail-seat vertical take-off and landing UAV regulation and control method according to claim 2 is characterized in that: The method of generating a first trajectory based on the convex polyhedron corridor comprises the following steps: According to the fuselage size of the vertical take-off and landing UAV, an obstacle size is expanded to generate environmental information; Obtain the initial geometric path from the current position to the end position through the path search algorithm; Generate a convex polyhedron corridor according to the environmental information and the initial geometric path; Constructing a cost function according to the convex polyhedral corridor; The first trajectory is generated according to the convex polyhedral corridor and the cost function.

4. The pipeline-based tail-seat vertical take-off and landing UAV regulation and control method according to claim 3 is characterized in that: The cost function is constructed according to the convex polyhedron corridor, comprising the following steps: Obtaining the minimum inscribed circle of the convex polyhedron corridor; Obtaining a first radius of the minimum inscribed circle, and taking the length of the first radius as a first distance; Obtaining the external normal vector of each face of the convex polyhedron corridor; Acquire a preset plane formed by moving the first preset point along the external normal vector toward the inside of the convex polyhedron corridor by the first distance; Acquire a second distance from the first preset point to the preset plane; If the second distance is positive, a smooth loss function is used to calculate the cost and the gradient to obtain the cost function.

5. The pipeline-based tail-seat vertical take-off and landing UAV regulation and control method according to claim 2 is characterized in that: The method of obtaining a target trajectory and a variable radius pipeline by cubic spline fitting according to the initial trajectory includes the following steps: Parameterizing a first arc length of the first trajectory by a preset resolution to obtain a first discrete data point; Performing cubic spline fitting on the first discrete data points to obtain the target trajectory; Obtaining a first position of each vertical take-off and landing drone of a second arc length on the target trajectory; Obtaining a first speed direction of the first position; Acquire a first section perpendicular to the first velocity direction, wherein the first section intersects with the convex polyhedral corridor to form a convex polygon; Taking the shortest distance from the first position to each side of the convex polygon as the second radius; The variable radius pipe is obtained by performing cubic spline fitting on the second radius with respect to the second arc length.

6. The pipeline-based tail-seat vertical take-off and landing UAV regulation and control method according to claim 2 is characterized in that: The generating of the second trajectory based on the signed distance field comprises the following steps: According to the fuselage size of the vertical take-off and landing UAV, an obstacle size is expanded to generate environmental information; Obtain the initial geometric path from the current position to the end position through the path search algorithm; Constructing a signed distance field according to the environment information and the initial geometric path; Trajectory planning is performed in the signed distance field by using the MINCO trajectory class to generate the second trajectory.

7. The pipeline-based tail-seat vertical take-off and landing UAV regulation and control method according to claim 2 is characterized in that: The method of obtaining a target trajectory and a variable radius pipeline by cubic spline fitting according to the initial trajectory includes the following steps: Parameterizing the third arc length of the second trajectory by a preset resolution to obtain a second discrete data point; Performing cubic spline fitting on the second discrete data points to obtain the target trajectory; Taking a third distance between a discrete second preset point on the target trajectory and the nearest obstacle as a third radius; The variable radius pipeline is obtained by performing cubic spline fitting on the third radius with respect to the third arc length of the target trajectory.

8. The pipeline-based tail-seat vertical take-off and landing UAV regulation and control method according to claim 1 is characterized in that: The step of setting the profile constraints and the adaptive parameters according to the variable radius pipeline comprises the following steps: Setting the fourth arc length of the target trajectory as a preset trajectory; Derivative the variable radius pipeline to obtain a derivative of the variable radius pipeline; Obtaining the contour constraint according to the preset trajectory, the variable radius pipeline and a derivative of the variable radius pipeline; Obtaining the maximum radius and the minimum radius of the target trajectory; Obtain the maximum weight and the minimum weight of the flight speed of the vertical take-off and landing unmanned vehicle; The adaptive parameter is obtained according to the maximum radius, the minimum radius, the maximum weight and the minimum weight.

9. The pipeline-based tail-seat vertical take-off and landing UAV regulation and control method according to claim 1 is characterized in that: The objective function is constructed according to the target trajectory, the contour constraint and the adaptive parameter, comprising the following steps: Setting the fourth arc length of the target trajectory as a preset trajectory; By means of the contour constraint, constraining the current position of the vertical take-off and landing UAV; Obtaining a tracking error between the current position of the vertical take-off and landing UAV and the preset trajectory to obtain a longitudinal error and a lateral profile error; Adjusting the flight speed of the vertical take-off and landing UAV by using the adaptive parameters; The objective function is obtained according to the longitudinal error, the lateral profile error, the flight speed of the vertical take-off and landing UAV and the state input change rate.

10. A pipeline-based tail-seat vertical take-off and landing UAV control device, characterized in that: include: The first module is used to obtain an initial trajectory according to a spatial model; The second module is used to obtain a target trajectory and a variable radius pipeline according to the initial trajectory through cubic spline fitting; The third module is used to set the profile constraints and adaptive parameters according to the variable radius pipeline; A fourth module is used to construct an objective function according to the target trajectory, the contour constraint and the adaptive parameter; The fifth module is used to pre-set the sideslip angle constraints of the vertical take-off and landing UAV; A sixth module, configured to construct a pipeline-based model prediction profile control framework according to the objective function, the profile constraint, the adaptive parameter, and the sideslip angle constraint; The pipeline-based model predictive contour control framework is used to plan and control vertical take-off and landing UAVs.

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