Unmanned aerial vehicle control method, electronic device

Abstract

The application discloses a kind of unmanned plane control method, electronic equipment, method includes: in response to task execution instruction, determine target working mode;If target working mode is whole machine mode, control multiple unmanned plane modules are in reconfiguration state, and reconfiguration is target flight configuration, and obtain the first flight parameter of target flight configuration, according to the first flight parameter to each unmanned plane module in target flight configuration is controlled respectively;If target working mode is sub-machine mode, control multiple unmanned plane modules are in disassembly state, and obtain the second flight parameter of each unmanned plane module, according to the second flight parameter to the corresponding unmanned plane module is controlled.The method not only can realize the individual control of multiple unmanned plane modules, but also can realize the control of multiple unmanned plane modules as a whole, and then the automatic building, transformation, decomposition and other tasks of configuration can be realized, and the stable control of configuration can be realized.

Description

Technical Field

[0001] This invention relates to the field of aircraft technology, and in particular to a method for controlling unmanned aerial vehicles (UAVs) and electronic equipment. Background Technology

[0002] Modular drones can be reconfigured to form different configurations. After the configuration is determined, the aircraft is typically built, transformed, and decomposed manually, resulting in low automation. Furthermore, after the configuration is built, control is usually performed on each module individually, which may lead to configuration instability. Summary of the Invention

[0003] This invention aims to at least partially solve one of the technical problems in related technologies. Therefore, the purpose of this invention is to propose a drone control method and electronic device to achieve tasks such as automatic configuration building, transformation, and decomposition, as well as stable control of the configuration.

[0004] To achieve the above objectives, an embodiment of the first aspect of the present invention provides a method for controlling an unmanned aerial vehicle (UAV), the method comprising: responding to a task execution command, determining a target operating mode; if the target operating mode is a whole-machine mode, controlling multiple UAV modules to be in a reconfiguration state and reconfiguring them into a target flight configuration, and acquiring first flight parameters of the target flight configuration, and controlling each UAV module in the target flight configuration according to the first flight parameters; if the target operating mode is a split-machine mode, controlling multiple UAV modules to be in a decomposed state, acquiring second flight parameters of each UAV module, and controlling the corresponding UAV module according to the second flight parameters.

[0005] In addition, the UAV control method of the above embodiments of the present invention may also have the following additional technical features:

[0006] According to one embodiment of the present invention, the first flight parameters include the actual coordinate position, actual linear velocity, actual roll-pitch-yaw attitude, and actual angular velocity of the target flight configuration. The step of controlling each UAV module in the target flight configuration according to the first flight parameters includes: generating a thrust distribution matrix based on the actual coordinate position, actual linear velocity, actual roll-pitch-yaw attitude, and actual angular velocity of the target flight configuration; and controlling each UAV module in the target flight configuration according to the thrust distribution matrix.

[0007] According to one embodiment of the present invention, generating a thrust distribution matrix based on the actual coordinate position, actual linear velocity, actual roll-pitch-yaw attitude, and actual angular velocity of the target flight configuration includes: calculating a first difference between the actual coordinate position of the target flight configuration and a first target coordinate position, a second difference between the actual linear velocity of the target flight configuration and the first target linear velocity, and calculating a third difference based on the actual roll-pitch-yaw attitude of the target flight configuration and the first target roll-pitch-yaw attitude; calculating a fourth difference based on the actual roll-pitch-yaw attitude, actual angular velocity, and the first target roll-pitch-yaw attitude and the first target angular velocity; performing PID control based on the first difference and the second difference to obtain a translation distribution matrix, and performing PID control based on the third difference and the fourth difference to obtain a rotation distribution matrix; and obtaining the thrust distribution matrix based on the translation distribution matrix and the rotation distribution matrix.

[0008] According to an embodiment of the present invention, the translation assignment matrix and the rotation assignment matrix are respectively represented by the following formulas:

[0009]

[0010]

[0011] Among them, u X u Ω Let these represent the translation assignment matrix and the rotation assignment matrix, respectively. K represents the target linear acceleration and the target angular acceleration, respectively. X1 ,K X2 ,K X3 K represents the proportional coefficient, integral coefficient, and derivative coefficient of the translational dimension PID control for the target flight configuration, respectively. Ω1 ,K Ω2 ,K Ω3 denoted by , respectively, the proportional coefficient, integral coefficient, and derivative coefficient of the rotational dimension PID control of the target flight configuration, and t represents time; This represents the first difference. These represent the coordinate position of the first target and the actual coordinate position of the target's flight configuration, respectively. This represents the second difference. These represent the linear velocity of the first target and the actual linear velocity of the target's flight configuration, respectively. This represents the third difference. This represents the fourth difference. R(·), [·] represent the actual roll-pitch-yaw attitude, actual angular velocity, first target roll-pitch-yaw attitude, and first target angular velocity of the target flight configuration, respectively. ∨ These represent the transformation from Euler angles to the standard rotation matrix, and the total moment of inertia of the target flight configuration to... The mapping.

[0012] According to one embodiment of the present invention, the second flight parameter includes the actual tilt angle and the actual twist angle of the UAV module. Controlling the UAV module according to the second flight parameter includes: calculating a fifth difference between the actual tilt angle and the target tilt angle of the UAV module, and a sixth difference between the actual twist angle and the target twist angle of the UAV module; performing PID control based on the fifth difference to obtain a tilt control quantity, and performing PID control based on the sixth difference to obtain a twist control quantity; generating a control torque based on the tilt control quantity and the twist control quantity, and controlling the UAV module according to the control torque.

[0013] According to an embodiment of the present invention, the tilt control amount and the torsion control amount are respectively expressed by the following formulas:

[0014]

[0015]

[0016] in, Let k represent the tilt control quantity and torsion control quantity of the i-th UAV module, respectively. α1 ,k α2 ,k α3 Let k represent the proportional coefficient, integral coefficient, and derivative coefficient of the tilt dimension PID control for the i-th UAV module, respectively. β1 ,k β2 ,k β3 Let these represent the proportional coefficient, integral coefficient, and derivative coefficient of the torsional dimension PID control for the i-th UAV module, respectively. This represents the fifth difference. These represent the actual tilt angle and the target tilt angle of the i-th UAV module, respectively. This represents the sixth difference. Let represent the actual twist angle and the target twist angle of the i-th UAV module, respectively, and t represent time.

[0017] According to one embodiment of the present invention, the control torque is expressed by the following formula:

[0018]

[0019]

[0020]

[0021] in, These represent the control torques of the i-th UAV module in the x, y, and z directions, respectively. Let x, y, and z represent the moments of inertia of the i-th UAV module in the x, y, and z directions, respectively.

[0022] According to an embodiment of the present invention, the target flight configuration is obtained by: acquiring the mass and moment of inertia of each UAV module, wherein each UAV module has multiple docking surfaces; initializing UAV formation structure categories and iteration parameters according to the number of UAV modules, wherein the iteration parameters include the number of UAV formation structure categories, a maximum number of iterations, a first quantity limit, a second quantity limit, a deformation probability, and a convergence count; for each UAV formation structure in the initial UAV formation structure category, calculating the performance score of the UAV formation structure based on the mass, moment of inertia, and connection status of the docking surfaces of each UAV module in the UAV formation structure; and in each iteration cycle, selecting the first number of UAVs with larger performance scores from the current UAV formation structure category. A limited number of UAV formation structures are designated as competing UAV formation structures. For each competing UAV formation structure, a deformation operation is performed on it according to the deformation probability to obtain a second limited number of deformed UAV formation structures. The performance score of each deformed UAV formation structure is calculated, and the current UAV formation structure category is updated using the deformed UAV formation structures for the next iteration cycle until the iteration termination condition is met. The iteration termination condition is obtained based on the maximum number of iterations and the number of convergences. The updated UAV formation structure category obtained in the iteration cycle that meets the iteration termination condition is taken as the final UAV formation structure category, and one of the final UAV formation structure categories is selected as the target flight configuration.

[0023] To achieve the above objectives, an embodiment of the second aspect of the present invention provides an electronic device including a memory, a processor, and a computer program stored in the memory, wherein the computer program, when executed by the processor, implements the above-described unmanned aerial vehicle (UAV) control method.

[0024] The UAV control method and electronic device of this invention, upon receiving a task execution command, first determines the target operating mode. If the target operating mode is a whole-machine mode, multiple UAV modules are controlled to be in a reconfiguration state and reconfigured into the target flight configuration. First flight parameters of the target flight configuration are acquired, and each UAV module in the target flight configuration is controlled separately according to the first flight parameters. If the target operating mode is a split-machine mode, multiple UAV modules are controlled to be in a decomposed state, and second flight parameters of each UAV module are acquired. The corresponding UAV modules are controlled according to the second flight parameters. Therefore, not only can multiple UAV modules be controlled individually, but multiple UAV modules can also be controlled as a whole, thereby enabling tasks such as automatic configuration building, transformation, and decomposition, as well as stable control of the configuration.

[0025] Additional aspects and advantages of the invention will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. Attached Figure Description

[0026] Figure 1 This is a flowchart of the reconstructing method of the UAV module according to an embodiment of the present invention;

[0027] Figure 2 This is a schematic diagram of the structure of an example drone module of the present invention;

[0028] Figure 3 This is a schematic diagram of an example flight configuration of the present invention;

[0029] Figure 4 This is a schematic diagram illustrating an example of the UAV formation structure categories and the performance scores of each UAV formation structure in this invention.

[0030] Figures 5(a)-5(d) This is a flowchart illustrating an example of the present invention of a deformation operation on a competing drone array structure;

[0031] Figure 6 This is a flowchart of the unmanned aerial vehicle (UAV) control method according to an embodiment of the present invention;

[0032] Figure 7 This is a schematic diagram of the control system of the unmanned aerial vehicle module according to an embodiment of the present invention;

[0033] Figure 8 This is a structural block diagram of an electronic device according to an embodiment of the present invention. Detailed Implementation

[0034] Embodiments of the present invention are described in detail below, examples of which are illustrated in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and intended to explain the present invention, and should not be construed as limiting the present invention.

[0035] The drone control method and electronic device of the present invention are described below with reference to the accompanying drawings.

[0036] It should be noted that to effectively control the flight configuration of multiple UAV modules, it is necessary to know the controllable flight configurations of each UAV module. Therefore, the reconfiguration method of UAV modules will be explained first.

[0037] Figure 1 This is a flowchart of a method for reconstructing a drone module according to an embodiment of the present invention. Figure 1 As shown, the reconfiguration method for the UAV module includes:

[0038] S101, obtain the number of UAV modules and the mass and moment of inertia of each UAV module, wherein the UAV module has multiple docking surfaces.

[0039] In this embodiment, the drone module includes a drone and a frame. The drone can move with multiple degrees of freedom within the frame, which has multiple docking surfaces for connecting and reconfiguring the various drone modules. The structures of the drone modules can be the same or different, primarily differing in the payload they carry. For example, the payload could be a camera, a robotic arm, a leakage current detector, a gas detector, etc., resulting in variations in the mass and moment of inertia of each drone module.

[0040] For example, such as Figure 2 As shown, the drone can be connected to the central frame via a 2-DOF passive gimbal mechanism, with no rotation angle limitation, and can be used as an omnidirectional thrust generator. This quadcopter drone includes a flight control board, a quadcopter deck, a power distribution board, brushless motors (which can be four), propellers, etc. The brushless motors drive the propellers, and the motor speed is controlled by an electronic speed controller. It is powered by a battery (such as a 14.8V lithium battery).

[0041] See Figure 2 The frame may be equipped with a locking mechanism to lock the torsional degree of freedom (β) of the drone. The locking mechanism can lock the passive rotation support to prevent the drone from tilting (α). When the locking mechanism is activated, the drone module can be treated as a rigid body and fly as a normal quadcopter.

[0042] See Figure 2The frame of the drone module is a cube with a side length of l. The frame includes a carbon fiber tube and a connecting structure. The connecting structure has grooves or protrusions. An electromagnet can be provided on the corresponding connecting structure to facilitate the connection between modules. The magnetism (including positive magnetism, negative magnetism, and non-magnetism) of the electromagnet can be controlled by the connecting controller, which is powered by a battery.

[0043] S102, based on the number of UAV modules, initialize the UAV formation structure category and iteration parameters, wherein the iteration parameters include the number of UAV formation structure categories, the maximum number of iterations, the first quantity limit, the second quantity limit, the deformation probability, and the number of convergences.

[0044] Specifically, a UAV module can connect to other UAV modules through its docking surface. Let the number of UAV modules be n. The larger the value of n, the more flight configurations (represented by UAV array structures) can be obtained, the larger the number of UAV array structure categories that can be initialized, and the larger the maximum number of iterations, the first quantity limit, the second quantity limit, the deformation probability, and the number of convergences can also be, so as to improve the effectiveness of the iteration results.

[0045] The drone formation structure can be a tree structure, such as... Figure 3 As shown in the image.

[0046] S103, for each UAV formation structure in the initial UAV formation structure category, calculate the performance score of the UAV formation structure based on the mass, moment of inertia and connection status of each UAV module in the UAV formation structure.

[0047] Specifically, after n UAV modules are docked, a flight configuration can be formed. Each UAV module can still act as an omnidirectional thrust generator after docking, giving the resulting multi-rotor flight configuration the potential for overdrive, thereby achieving better maneuverability in position and orientation tracking than individual UAV modules.

[0048] For example, to represent the overall flight configuration, the four docking surfaces of the UAV module are defined as f1, f2, f3, and f4, as follows: Figure 3 As shown. See also Figure 3 F w F represents the world coordinate system. S This represents the coordinate system in which the flight configuration is located. The coordinate position of the flight configuration is defined as X. S =[x S ,y S ,z S ] T Roll-pitch-yaw attitude is defined as Angular velocity is defined as Ω S =[p S ,qS ,r S ] T F iS d represents the center of the i-th UAV module. i =[x i ,y i [0] represents the position coordinates of the i-th UAV module.

[0049] For ease of description, see Figure 3 After encoding each UAV module, the first UAV module is defined as the root node of the UAV array structure. Based on this root node, an assembly relationship matrix A(S) can be obtained to represent the UAV array structure. In the assembly relationship matrix A(S), each row represents a UAV module, and each column represents the mating surface of that module. A can be used to... i,j =k indicates that the j-th docking surface of the i-th UAV module is connected to the k-th UAV module.

[0050] S104. In each iteration cycle, select the top 100 drone formation structures with the highest performance scores from the current drone formation structure category. These are denoted as competitive drone formation structures. For each competitive drone formation structure, perform a deformation operation on it according to the deformation probability to obtain a second 1000 deformed drone formation structures.

[0051] S105, calculate the performance score of each deformable UAV formation structure, and update the current UAV formation structure category using the deformable UAV formation structure to proceed with the next iteration until the iteration termination condition is met. The iteration termination condition is obtained based on the maximum number of iterations and the number of convergences.

[0052] S106, the updated UAV array structure category obtained by the iteration cycle that satisfies the iteration termination condition is used as the flight configuration of the reconstructed UAV module.

[0053] In some embodiments of the present invention, calculating the performance score of the UAV array structure includes: obtaining the coordinate positions of each UAV module in the UAV array structure based on the connection status of each UAV module in the UAV array structure and the coordinate positions of the UAV module at the root node; calculating the geometric center position of the UAV array structure based on the coordinate positions and mass of each UAV module in the UAV array structure, and calculating the relative positions between the coordinate positions of each UAV module in the structure tree and the geometric center position; constructing an objective function based on the relative positions and the rotational inertia of each UAV module; solving for the maximum value of the objective function, and using the maximum value as the performance score of the UAV array structure.

[0054] For example, the geometric center of the UAV formation can be calculated using the following formula:

[0055]

[0056] Where d0 represents the geometric center position, The mass of the UAV array structure is represented by n, and the number of UAV modules is represented by m. i Let d represent the mass of the i-th UAV module. i This represents the position coordinates of the i-th UAV module.

[0057] Specifically, the coordinates of the UAV module at the root node (e.g., d1 = [0,0,0]) and the connection relationships between the UAV modules are known, as are the step size matrices of the connected UAV modules. The coordinates d of other UAV modules can be calculated recursively. i Then, considering the quality of each drone module, the following method was used: The geometric center of the UAV formation can be obtained. By translating the geometric center to the origin, the position coordinates of each UAV module are correspondingly translated, yielding the relative position d. i =d i -d0. Afterwards, an objective function can be constructed based on the relative positions and the rotational inertia of each UAV module; the maximum value of the objective function is then calculated, and this maximum value is used as the performance score of the UAV formation structure.

[0058] In some embodiments of the present invention, an objective function is constructed based on the relative positions and the rotational inertia of each UAV module, including: obtaining the total rotational inertia of the UAV formation structure based on the relative positions and the rotational inertia of each UAV module; constructing an objective matrix based on the total rotational inertia and the relative positions; and constructing an objective function based on the objective matrix.

[0059] For example, the objective function can be expressed as follows:

[0060]

[0061] in, Represents the target matrix. Let be a skew-symmetric matrix representing the relative position of the i-th UAV module. J represents the total moment of inertia. i Let x represent the moment of inertia of the i-th UAV module. i y i Let x and y represent the x and y coordinates of the i-th UAV module relative to its geometric center, respectively, and cond(·) represent the condition number of the matrix. σ max (·) denotes the largest singular value of the matrix.

[0062] Specifically, for a flight configuration consisting of n UAV modules, its translational motion mechanics model can be described as follows:

[0063]

[0064] Where M represents the total mass of the flight configuration. This indicates that the flight configuration is linear acceleration, where g represents gravitational acceleration. The tilt angle α of the i-th UAV module represents... i and twist angle β i The function, T i This represents the magnitude of the thrust generated by the i-th UAV module.

[0065] The rotational dynamics model of the flight configuration can be described as follows:

[0066]

[0067] in, Represents the total moment of inertia. It is the angular acceleration of the flight configuration.

[0068] Combining the above translational mechanics model and rotational dynamics model, we can obtain:

[0069]

[0070] in, This represents the 6-DOF matrix corresponding to the flight configuration.

[0071] Using the method of force decomposition, it is defined as an intermediate variable. in, Will The nonlinear relationship in the equation is transformed into a linear variable to obtain:

[0072]

[0073] in, This represents a constant allocation matrix with full row rank.

[0074] Therefore, F can be used as the system input to analyze the flight configuration from a linear dynamics perspective. The actual tilt angle α of each UAV module... i Twist angle β i and thrust T i It can be calculated using inverse kinematics through F.

[0075] To optimize flight configuration and generate a high-energy-efficiency over-actuated platform, dynamic equations (including the assignment matrix W and the total moment of inertia J) can be used. S From a control perspective, the objective function is designed. For the optimization problem of flight configuration, it can be represented by the following optimization structure:

[0076]

[0077] st rank(W) = 6

[0078]

[0079] S(d1,…,d n ) = 1

[0080] in, As the optimization objective, it is defined as minimizing the required thrust energy exponent ||T|| for all possible desired acceleration commands. 2 The constraint rank(W) = 6 is to implement overdrive, constraint To ensure that the geometric center of the flight configuration is located at the origin, the constraint S(d1,…,d n The setting is 1 to ensure that all drone modules are not connected in an overlapping manner.

[0081] Since the allocation matrix W can be expressed by the following formula:

[0082]

[0083] in, It is d i The skew-symmetric matrix, I3, represents an identity matrix of size 3, indicating that translational dynamics are independent of the configuration. Therefore, the optimization problem described above can focus only on the rotational dynamics, i.e., the total moment of inertia is related to the flight configuration-related structures. In this case, the objective matrix can be constructed. Therefore, the optimization objective in the above optimization structure can be simplified to:

[0084]

[0085] in, Representation matrix The Moore-Penrose inverse matrix, σ max (·) denotes the largest singular value of the matrix.

[0086] The optimization problem described above can then be transformed into a combinatorial optimization problem, as follows:

[0087]

[0088] That is, to maximize the objective function, in the objective function The full driving constraints were considered, including rank(W) = 6; Characterized thrust minimization, including

[0089] For each drone formation structure within the drone formation structure category, its objective function can be obtained. By maximizing the objective function, the performance score of the corresponding drone formation structure can be obtained. For example, such as... Figure 4 As shown, the performance scores of a flight configuration consisting of five UAV modules are presented. Figure 4 (a) has the lowest performance score due to insufficient drive. Figure 4 The middle (f) has a symmetrical structure and has the highest performance score.

[0090] In some embodiments of the present invention, the competitive drone formation structure is deformed according to the deformation probability to obtain a second number of deformable drone formation structures, including: generating a random number within a preset range, wherein the value of the deformation probability is within the preset range; when the random number is less than the deformation probability, the competitive drone formation structure is deformed to obtain a second number of deformable drone formation structures.

[0091] For example, the deformation probability can be set to a value within a preset range of 0 to 1, such as 0.6. When performing a deformation operation, a random number between 0 and 1 is first generated, and this random number is compared with the deformation probability to determine whether to perform the deformation operation. For example, if the generated random number is 0.4, which is less than 0.6, it can be assumed that the performance score after deformation may exceed that of the competing drone formation structure. Therefore, a deformation operation is performed to generate more drone formation structures for selection.

[0092] In some embodiments, the deformation operation of the competitive UAV formation structure includes: randomly selecting two connected docking surfaces in the competitive UAV formation structure and disconnecting them to obtain a first sub-formation group and a second sub-formation group; randomly selecting an idle docking surface on the first sub-formation group, denoted as the first idle docking surface, and randomly selecting an idle docking surface on the second sub-formation group, denoted as the second idle docking surface; and connecting the first idle docking surface and the second idle docking surface to obtain the deformed UAV formation structure.

[0093] For example, as shown in Figure 5(a), the competitive UAV formation structure includes 5 nodes (i.e., UAV modules), denoted as ①, ②, ③, ④, and ⑤. The 5 nodes are connected in a chain, and adjacent nodes are connected by docking surfaces f1 and f3. The two docking surfaces of this competitive UAV formation structure are randomly selected as docking surface f1 (denoted as 3,1) of node ③ and docking surface f3 (denoted as 4,3) of node ④. This can be represented by a matrix. As shown in Figure 5(b), the selected docking surfaces in Figure 5(a) are broken to obtain the first subarray group (including nodes ①, ②, and ③) and the second subarray group (including nodes ④ and ⑤). The free docking surfaces of the first subarray group can be represented by matrix LF, and the free docking surfaces of the second subarray group can be represented by matrix RF, as detailed below:

[0094]

[0095] As shown in Figure 5(c), an idle docking surface is randomly selected on the first sub-array group, denoted as the first idle docking surface L = [3,4], which is the docking surface f4 of node ③; and an idle docking surface is randomly selected on the second sub-array group, denoted as the second idle docking surface R = [4,3], which is the docking surface f3 of node ④. The first idle docking surface L = [3,4] and the second idle docking surface R = [4,3] are connected to obtain the deformable UAV array structure shown in Figure 5(c).

[0096] In some embodiments of the present invention, after obtaining the deformable UAV formation structure, the method further includes: rotating the smaller sub-formation group in the first sub-formation group and the second sub-formation group to obtain a rotated UAV formation structure; determining whether there is module position overlap in the rotated UAV formation structure; if not, then using the rotated UAV formation structure as the final deformable UAV formation structure.

[0097] For example, after obtaining the deformable UAV formation structure shown in Figure 5(c), if the degrees of freedom directions of the UAV modules in the first sub-formation group are different from those in the second sub-formation group, then the sub-formation groups can be rotated. To reduce control complexity, the smaller sub-formation groups in the first and second sub-formation groups can be rotated to obtain a rotated UAV formation structure. As shown in Figure 5(d), the second sub-formation group including nodes ④ and ⑤ is rotated. After rotation, the docking surface f4 of node ③ is connected to the docking surface f2 of node ④, and the docking surface f4 of node ④ is connected to the docking surface f2 of node ⑤, thereby making the degrees of freedom directions of each UAV module in the structure tree the same, which facilitates subsequent control.

[0098] It should be noted that if the rotated UAV formation structure has overlapping module positions, then this rotating UAV formation structure is unreasonable and should be discarded. If it does not exist, then the UAV formation structure category will be updated for the next iteration.

[0099] In some embodiments of the present invention, the UAV control method further includes: when the random number is greater than or equal to the deformation probability, updating the current tree structure category using the corresponding competing UAV formation structure.

[0100] Specifically, if the random number is greater than or equal to the deformation probability, it can be assumed that even if the competitive drone formation structure is deformed, the performance score after deformation will not exceed that of the competitive drone formation structure. Therefore, the competitive drone formation structure will not be deformed, and it will be directly used to update the current tree structure category.

[0101] By using the above-mentioned UAV module reconstruction method, the flight configuration is represented by the UAV array structure. An iterative algorithm is used to solve the reconstruction optimization problem. During the iteration process, custom deformation operations are performed and the performance score of the corresponding UAV array structure is calculated based on the mass and rotational inertia of each UAV module. This can achieve effective flight configuration based on the reconstruction of a large number of UAV modules and improve computational efficiency.

[0102] Once a valid flight configuration is obtained, one of them can be selected as the target flight configuration.

[0103] Figure 6 This is an embodiment of the drone control method of the present invention. For example... Figure 6 As shown, the method includes:

[0104] S601, in response to task execution instructions, determines the target operating mode.

[0105] S602, if the target working mode is the whole machine mode, then control multiple UAV modules to be in a reconfiguration state and reconfigure them into the target flight configuration, and obtain the first flight parameters of the target flight configuration, and control each UAV module in the target flight configuration according to the first flight parameters.

[0106] S603, if the target working mode is the sub-machine mode, then control multiple UAV modules to be in a decomposed state, and obtain the second flight parameters of each UAV module, and control the corresponding UAV module according to the second flight parameters.

[0107] Specifically, steps S601 to S603 can be executed by a remote controller, which can wirelessly communicate with each UAV module to transmit data (including flight parameters and control parameters). After receiving the mission execution command, the remote controller can first determine the target's operating mode. For example... Figure 8 As shown, if the target operating mode is the whole-machine mode, multiple UAV modules can be reconfigured via connectors on the frame (such as in-flight docking reconfiguration), and the reconfigured shape will be the target flight configuration. Of course, this reconfiguration can also be performed by a human. In this case, it is only necessary to control the UAV modules to maintain the reconfigured state, i.e., the docking surfaces are locked. Then, the target flight configuration is treated as a whole, and the first flight parameters are obtained, such as the actual coordinate position X. S Actual linear velocity Actual roll-pitch-yaw attitude Θ S and actual angular velocity ΩS Then, based on the first flight parameters, each UAV module in the target flight configuration is controlled separately. If the target working mode is a split-system mode, multiple UAV modules are controlled to be in a decomposed state. For example, if the current state is reconfiguration, the docking surface is unlocked to decompose the UAV modules. After that, the second flight parameters of each UAV module are obtained, such as the actual tilt angle and the actual twist angle, and the corresponding UAV module is controlled based on the second flight parameters.

[0108] It should be noted that if the target operating mode is the whole-machine mode, and the current flight configuration is not the target flight configuration, the current flight configuration can be decomposed first, and then reassembled according to the target flight configuration. The decomposition and assembly process can be controlled separately for each UAV module in the sub-machine mode.

[0109] Therefore, it is possible not only to control multiple UAV modules individually, but also to control multiple UAV modules as a whole, thereby enabling tasks such as automatic configuration building, transformation, and decomposition, as well as stable control of the configuration.

[0110] In some embodiments of the present invention, the first flight parameters include the actual coordinate position, actual linear velocity, actual roll-pitch-yaw attitude, and actual angular velocity of the target flight configuration. Controlling each UAV module in the target flight configuration according to the first flight parameters includes: generating a thrust distribution matrix based on the actual coordinate position, actual linear velocity, actual roll-pitch-yaw attitude, and actual angular velocity of the target flight configuration; and controlling each UAV module in the target flight configuration according to the thrust distribution matrix.

[0111] In some embodiments of the present invention, generating a thrust distribution matrix based on the actual coordinate position, actual linear velocity, actual roll-pitch-yaw attitude, and actual angular velocity of the target flight configuration includes: calculating a first difference between the actual coordinate position of the target flight configuration and the first target coordinate position, a second difference between the actual linear velocity of the target flight configuration and the first target linear velocity, and calculating a third difference based on the actual roll-pitch-yaw attitude of the target flight configuration and the first target roll-pitch-yaw attitude; calculating a fourth difference based on the actual roll-pitch-yaw attitude and actual angular velocity of the target flight configuration, the first target roll-pitch-yaw attitude, and the first target angular velocity; performing PID control based on the first and second differences to obtain a translation distribution matrix, and performing PID control based on the third and fourth differences to obtain a rotation distribution matrix; and obtaining the thrust distribution matrix based on the translation distribution matrix and the rotation distribution matrix.

[0112] Specifically, according to the description of the above reconstruction process This invention proposes a feedback linearization controller that uses a dual integrator to characterize the dynamic model of a nonlinear system, and obtains the following equation:

[0113]

[0114] This formula is the thrust distribution matrix, and we can obtain...

[0115] In some embodiments of the present invention, the translation assignment matrix and the rotation assignment matrix are respectively represented by the following formulas:

[0116]

[0117]

[0118] Among them, u X u Ω These represent the translation assignment matrix and the rotation assignment matrix, respectively. K represents the target linear acceleration and the target angular acceleration, respectively. X1 ,K X2 ,K X3 K represents the proportional, integral, and derivative coefficients of the PID control in the translation dimension of the target flight configuration, respectively. Ω1 ,K Ω2 ,K Ω3 denoted by , respectively, the proportional coefficient, integral coefficient, and derivative coefficient of the PID control in the rotational dimension of the target flight configuration, and t represents time; Indicates the first difference. These represent the coordinate position of the first target and the actual coordinate position of the target's flight configuration, respectively. This represents the second difference. These represent the linear velocity of the first target and the actual linear velocity of the target's flight configuration, respectively. This represents the third difference. This represents the fourth difference. R(·), [·] represent the actual roll-pitch-yaw attitude, actual angular velocity, first target roll-pitch-yaw attitude, and first target angular velocity of the target flight configuration, respectively. ∨ Represent the transformation from Euler angles to the standard rotation matrix, and the total moment of inertia of the target flight configuration to... The mapping.

[0119] Specifically, upon obtaining u X u Ω Then, the thrust distribution matrix can be obtained using the above thrust distribution matrix formula.

[0120] In some embodiments of the present invention, the second flight parameters include the actual tilt angle and the actual torsion angle of the UAV module. Controlling the UAV module according to the second flight parameters includes: calculating a fifth difference between the actual tilt angle and the target tilt angle of the UAV module, and a sixth difference between the actual torsion angle and the target torsion angle of the UAV module; performing PID control based on the fifth difference to obtain a tilt control quantity, and performing PID control based on the sixth difference to obtain a torsion control quantity; generating a control torque based on the tilt control quantity and the torsion control quantity, and controlling the UAV module according to the control torque.

[0121] In some embodiments of the present invention, the tilt control amount and the torsion control amount are respectively expressed by the following formulas:

[0122]

[0123]

[0124] in, Let k represent the tilt control quantity and torsion control quantity of the i-th UAV module, respectively. α1 ,k α2 ,k α3 Let k represent the proportional coefficient, integral coefficient, and derivative coefficient of the tilt dimension PID control for the i-th UAV module, respectively. β1 ,k β2 ,k β3 Let these represent the proportional coefficient, integral coefficient, and derivative coefficient of the torsional dimension PID control for the i-th UAV module, respectively. This represents the fifth difference. These represent the actual tilt angle and the target tilt angle of the i-th UAV module, respectively. This represents the sixth difference. Let represent the actual twist angle and the target twist angle of the i-th UAV module, respectively, and t represent time.

[0125] After obtaining the tilt control quantity and torsion control quantity to generate the control torque, the control torque can be obtained through the following formula:

[0126]

[0127]

[0128]

[0129] in, These represent the control torques of the i-th UAV module in the x, y, and z directions, respectively. Let x, y, and z represent the moments of inertia of the i-th UAV module in the x, y, and z directions, respectively.

[0130] For example, for a quadcopter module, the thrust required for each propeller can be calculated using the following linear quadcopter dynamics model:

[0131]

[0132] Where sat(·) represents the saturation function, Let be a constant, 'a' be the arm length of the quadcopter module, and 'c' be a constant. Γ =K Γ / K T , where K is a constant. Γ ,K T These are the propeller drag coefficient and propeller thrust coefficient, respectively. w represents the thrust generated by the j-th propeller of the i-th UAV module, where j = 1, 2, 3, 4. i,j This represents the angular velocity command of the j-th propeller of the i-th UAV module, which can be converted into a pulse width modulation (PWM) signal to drive the motor.

[0133] Figure 8 This is a structural block diagram of an electronic device according to an embodiment of the present invention.

[0134] like Figure 8 As shown, the electronic device 500 includes a processor 501 and a memory 503. The processor 501 and the memory 503 are connected, for example, via a bus 502. Optionally, the electronic device 500 may also include a transceiver 504. It should be noted that in practical applications, the transceiver 504 is not limited to one type, and the structure of this electronic device 500 does not constitute a limitation on the embodiments of the present invention.

[0135] Processor 501 may be a CPU (Central Processing Unit), a general-purpose processor, a DSP (Digital Signal Processor), an ASIC (Application Specific Integrated Circuit), a FPGA (Field Programmable Gate Array), or other programmable logic devices, transistor logic devices, hardware components, or any combination thereof. It may implement or execute the various exemplary logic blocks, modules, and circuits described in connection with this disclosure. Processor 501 may also be a combination that implements computational functions, such as a combination of one or more microprocessors, a combination of a DSP and a microprocessor, etc.

[0136] Bus 502 may include a pathway for transmitting information between the aforementioned components. Bus 502 may be a PCI (Peripheral Component Interconnect) bus or an EISA (Extended Industry Standard Architecture) bus, etc. Bus 502 can be divided into address bus, data bus, control bus, etc. For ease of representation, Figure 8 The bus is represented by a single thick line, but this does not mean that there is only one bus or one type of bus.

[0137] The memory 503 stores a computer program corresponding to the UAV control method of the above embodiments of the present invention. This computer program is executed by the processor 501. The processor 501 executes the computer program stored in the memory 503 to implement the content shown in the foregoing method embodiments.

[0138] Among them, electronic devices 500 include, but are not limited to: mobile terminals such as mobile phones, laptops, digital radio receivers, PDAs (personal digital assistants), PADs (tablet computers), PMPs (portable multimedia players), and in-vehicle terminals (such as in-vehicle navigation terminals), as well as fixed terminals such as digital TVs and desktop computers. Figure 8 The electronic device 500 shown is merely an example and should not be construed as limiting the functionality and scope of use of the embodiments of the present invention.

[0139] It should be noted that the logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as a sequenced list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by, or in conjunction with, an instruction execution system, apparatus, or device (such as a computer-based system, a processor-included system, or other system that can fetch and execute instructions from, an instruction execution system, apparatus, or device). For the purposes of this specification, "computer-readable medium" can be any means that can contain, store, communicate, propagate, or transmit programs for use by, or in conjunction with, an instruction execution system, apparatus, or device. More specific examples (a non-exhaustive list) of computer-readable media include: an electrical connection having one or more wires (electronic device), a portable computer disk drive (magnetic device), random access memory (RAM), read-only memory (ROM), erasable and editable read-only memory (EPROM or flash memory), fiber optic devices, and portable optical disc read-only memory (CDROM). Alternatively, the computer-readable medium may be paper or other suitable media on which the program can be printed, since the program can be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, interpreting, or otherwise processing as necessary, and then stored in a computer memory.

[0140] It should be understood that various parts of the present invention can be implemented in hardware, software, firmware, or a combination thereof. In the above embodiments, multiple steps or methods can be implemented in software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, it can be implemented using any one or a combination of the following techniques known in the art: discrete logic circuits having logic gates for implementing logical functions on data signals, application-specific integrated circuits (ASICs) having suitable combinational logic gates, programmable gate arrays (PGAs), field-programmable gate arrays (FPGAs), etc.

[0141] In the description of this specification, references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of the invention. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples.

[0142] In the description of this invention, it should be understood that the terms "center," "longitudinal," "lateral," "length," "width," "thickness," "upper," "lower," "front," "rear," "left," "right," "vertical," "horizontal," "top," "bottom," "inner," "outer," "clockwise," "counterclockwise," "axial," "radial," and "circumferential" indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. They are used only for the convenience of describing this invention and simplifying the description, and are not intended to indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on this invention.

[0143] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one of that feature. In the description of this invention, "a plurality of" means at least two, such as two, three, etc., unless otherwise explicitly specified.

[0144] In this invention, unless otherwise explicitly specified and limited, the terms "installation," "connection," "linking," and "fixing," etc., should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral part; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; they can refer to the internal communication of two components or the interaction between two components, unless otherwise explicitly limited. Those skilled in the art can understand the specific meaning of the above terms in this invention according to the specific circumstances.

[0145] In this invention, unless otherwise explicitly specified and limited, "above" or "below" the second feature can mean that the first feature is in direct contact with the second feature, or that the first feature is in indirect contact with the second feature through an intermediate medium. Furthermore, "above," "over," and "on top" of the second feature can mean that the first feature is directly above or diagonally above the second feature, or simply that the first feature is at a higher horizontal level than the second feature. "Below," "below," and "under" the second feature can mean that the first feature is directly below or diagonally below the second feature, or simply that the first feature is at a lower horizontal level than the second feature.

[0146] Although embodiments of the present invention have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting the present invention. Those skilled in the art can make changes, modifications, substitutions and variations to the above embodiments within the scope of the present invention.

Claims

1. A method for controlling an unmanned aerial vehicle (UAV), characterized in that, The method includes: In response to task execution instructions, determine the target operating mode; If the target operating mode is the whole machine mode, then control multiple UAV modules to be in a reconfiguration state and reconfigure them into the target flight configuration, and obtain the first flight parameters of the target flight configuration, and control each UAV module in the target flight configuration according to the first flight parameters; The first flight parameters include the actual coordinate position, actual linear velocity, actual roll-pitch-yaw attitude, and actual angular velocity of the target flight configuration. The step of controlling each UAV module in the target flight configuration according to the first flight parameters includes: A thrust distribution matrix is ​​generated based on the actual coordinate position, actual linear velocity, actual roll-pitch-yaw attitude, and actual angular velocity of the target flight configuration. The thrust allocation matrix is ​​used to control each of the unmanned aerial vehicle (UAV) modules in the target flight configuration. If the target working mode is the split-unit mode, then the multiple UAV modules are controlled to be in a split state, and the second flight parameters of each UAV module are obtained. The corresponding UAV module is controlled according to the second flight parameters. The second flight parameters include the actual tilt angle and actual twist angle of the UAV module. Controlling the UAV module based on the second flight parameters includes: Calculate the fifth difference between the actual tilt angle of the UAV module and the target tilt angle, and the sixth difference between the actual twist angle of the UAV module and the target twist angle; The tilt control quantity is obtained by performing PID control based on the fifth difference, and the torsional control quantity is obtained by performing PID control based on the sixth difference. A control torque is generated based on the tilt control amount and the torsion control amount, and the UAV module is controlled based on the control torque.

2. The UAV control method according to claim 1, characterized in that, The generation of the thrust distribution matrix based on the actual coordinate position, actual linear velocity, actual roll-pitch-yaw attitude, and actual angular velocity of the target flight configuration includes: Calculate the first difference between the actual coordinate position of the target flight configuration and the coordinate position of the first target, the second difference between the actual linear velocity of the target flight configuration and the linear velocity of the first target, and calculate the third difference based on the actual roll-pitch-yaw attitude of the target flight configuration and the roll-pitch-yaw attitude of the first target. Calculate the fourth difference based on the actual roll-pitch-yaw attitude and actual angular velocity of the target flight configuration, the roll-pitch-yaw attitude of the first target, and the angular velocity of the first target. PID control is performed based on the first difference and the second difference to obtain a translation allocation matrix, and PID control is performed based on the third difference and the fourth difference to obtain a rotation allocation matrix; The thrust allocation matrix is ​​obtained based on the translation allocation matrix and the rotation allocation matrix.

3. The UAV control method according to claim 2, characterized in that, The translation assignment matrix and the rotation assignment matrix are respectively represented by the following formulas: in, , Let these represent the translation assignment matrix and the rotation assignment matrix, respectively. , These represent the target's linear acceleration and angular acceleration, respectively. These represent the proportional coefficient, integral coefficient, and derivative coefficient of the PID control in the translation dimension of the target flight configuration, respectively. denoted by , respectively, the proportional coefficient, integral coefficient, and derivative coefficient of the rotational dimension PID control of the target flight configuration, and t represents time; , representing the first difference, These represent the coordinate position of the first target and the actual coordinate position of the target's flight configuration, respectively. , representing the second difference, These represent the linear velocity of the first target and the actual linear velocity of the target's flight configuration, respectively. , representing the third difference, , representing the fourth difference, These represent the actual roll-pitch-yaw attitude, actual angular velocity, first target roll-pitch-yaw attitude, and first target angular velocity of the target flight configuration, respectively. These represent the transformation from Euler angles to the standard rotation matrix, and the total moment of inertia of the target flight configuration to... The mapping.

4. The UAV control method according to claim 1, characterized in that, The tilt control amount and the torsion control amount are respectively expressed by the following formulas: in, , Let these represent the tilt control value and the torsion control value of the i-th UAV module, respectively. Let represent the proportional coefficient, integral coefficient, and derivative coefficient of the tilt dimension PID control for the i-th UAV module, respectively. Let these represent the proportional coefficient, integral coefficient, and derivative coefficient of the torsional dimension PID control for the i-th UAV module, respectively. , representing the fifth difference, These represent the actual tilt angle and the target tilt angle of the i-th UAV module, respectively. This represents the sixth difference. Let represent the actual twist angle and the target twist angle of the i-th UAV module, respectively, and t represent time.

5. The UAV control method according to claim 4, characterized in that, The control torque is expressed by the following formula: in, These represent the control torques of the i-th UAV module in the x, y, and z directions, respectively. Let x, y, and z represent the moments of inertia of the i-th UAV module in the x, y, and z directions, respectively.

6. The UAV control method according to claim 1, characterized in that, The target flight configuration is obtained in the following manner: The mass and moment of inertia of each of the aforementioned UAV modules are obtained, wherein each UAV module has multiple docking surfaces; Based on the number of UAV modules, initialize the UAV formation structure category and iteration parameters, wherein the iteration parameters include the number of UAV formation structure categories, the maximum number of iterations, a first quantity limit, a second quantity limit, the deformation probability, and the number of convergences; For each UAV formation structure in the initial UAV formation structure category, the performance score of the UAV formation structure is calculated based on the mass, moment of inertia, and connection status of the docking surfaces of each UAV module in the UAV formation structure. In each iteration cycle, select the top 100 drone formations with the highest performance scores from the current drone formation structure category, and denot them as competitive drone formations. For each competitive drone formation, perform a deformation operation on the competitive drone formation according to the deformation probability to obtain the second 1000 deformed drone formations. Calculate the performance score of each of the deformable UAV formation structures, and update the current UAV formation structure category using the deformable UAV formation structure to perform the next iteration until the iteration termination condition is met, wherein the iteration termination condition is obtained based on the maximum number of iterations and the number of convergences; The updated UAV formation structure category obtained after the iteration cycle that satisfies the iteration termination condition is taken as the final UAV formation structure category, and one of the final UAV formation structure categories is selected as the target flight configuration.

7. An electronic device comprising a memory, a processor, and a computer program stored in the memory, characterized in that, When the computer program is executed by the processor, it implements the unmanned aerial vehicle control method according to any one of claims 1-6.

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