A method and system for center of mass compensation control of a flying dual arm system

Abstract

The application provides a center of mass compensation control method and system of a flying dual-arm system, relates to the automatic control technical field of a nonlinear underactuated electromechanical system, and establishes a mechanical arm kinematics model according to the measured dual-arm geometric parameters; the momentum theorem of a particle system is used to establish a UAV dynamics model; a disturbance observer is designed to construct a nonlinear disturbance compensation controller; the state feedback signal of the flying dual-arm system is acquired in real time, the nonlinear disturbance compensation controller is used to calculate the control signal for accurately positioning the UAV to a target position, and the accurate positioning of the UAV is completed; the application uses the momentum theorem to establish the dynamics model of the UAV without any linearization operation, accurately estimates the influence on the UAV by designing the disturbance observer, improves the positioning accuracy of the flying dual-arm system on the basis of solving the influence of the dual-arm and the movement of the dual-arm on the UAV, and thus effectively and safely controls the flying dual-arm system.

Description

Technical Field

[0001] This invention belongs to the field of automatic control technology for nonlinear underactuated electromechanical systems, and particularly relates to a centroid compensation control method and system for a flight dual-arm system. Background Technology

[0002] The statements in this section are merely background information related to the present invention and do not necessarily constitute prior art.

[0003] Unmanned aerial vehicles (UAVs) are unmanned aircraft capable of takeoff, landing, and takeoff. They can perform challenging tasks such as reconnaissance, surveillance, transmission, transportation, and communication in complex environments. They have advantages such as low cost, no casualties, low wear and tear, and reusability, and are currently used in military, civilian, and scientific research fields. UAVs are developing towards miniaturization, intelligence, and specialization, and have also received support from various sectors and market investment, with increasing spending on them from all sides.

[0004] Based on their mechanical design, drones can be divided into three main categories: fixed-wing, flapping-wing, and rotary-wing. Currently, the application technologies of fixed-wing and rotary-wing drones are relatively mature and widely used in daily life. However, flapping-wing drones are still under development due to limitations in manufacturing materials and sensors. Among them, rotary-wing drones have strong maneuverability and good flexibility, and are smaller in size, making them the most widely used. They play a significant role in many areas such as search and rescue, cargo transportation, and forest fire monitoring. At the same time, compared to ground mobile robots, which have been studied earlier and more extensively, rotary-wing drones have greater maneuverability and flexibility, are less restricted by terrain and topography, and can greatly expand their working range.

[0005] The combination of drones and robotic arms has immense research value and application prospects. Unmanned aerial manipulators (UAVs) can extend the operational range to three-dimensional aerial space compared to ground-based mobile robots, while also significantly expanding the operational capabilities and application scope of UAVs. In other words, UAVs can expand their applicability from passive scenarios, such as search and rescue and surveillance, to active scenarios, such as construction, assembly, and grasping. Due to the diversity of required tasks, most researchers choose to independently design and assemble UAVs instead of using commercially available robotic arms. Zhang et al. designed a UAV system for grasping moving objects, consisting of a six-rotor and a seven-DOF robotic arm. Besides serial robotic arms, parallel robotic arms are also developing rapidly. Kamel et al. designed a UAV system composed of parallel robotic arms, which offers higher control precision but requires a smaller workspace.

[0006] Limited by the operational capabilities and flexibility of a single arm, it is difficult to complete the required tasks in many scenarios with just one arm, such as grasping large objects and opening and closing valves. Suarez et al. proposed a lightweight flying dual-arm operating system with low rotational inertia, which is similar to a human arm but is flexible, lightweight, and easy to assemble, and can realize the function of grasping large objects. Lippiello et al. proposed three image-based visual impedance controllers for flying dual-arm systems, which allow flying dual-arm systems equipped with cameras and force / torque sensors to perform physical interactions.

[0007] Compared to single-arm flying systems, dual-arm flying systems have more complex coupling, and the drone is more severely affected by the robotic arm. Only by properly handling this impact can the system operate safely and stably. Existing control methods cannot guarantee that the dual-arm flying system can complete its intended tasks smoothly and efficiently, and cannot effectively control the dual-arm flying system. Summary of the Invention

[0008] To overcome the shortcomings of the prior art, this invention provides a centroid compensation control method and system for a dual-arm flight system. By utilizing the momentum theorem to establish a dynamic model of the UAV without any linearization operations, and designing a disturbance observer to accurately estimate the impact on the UAV, this invention improves the positioning accuracy of the dual-arm flight system by addressing the influence of the dual arms' presence and motion on the UAV, thereby achieving effective and safe control of the dual-arm flight system.

[0009] To achieve the above objectives, one or more embodiments of the present invention provide the following technical solutions:

[0010] The first aspect of this invention provides a method for center-of-gravity compensation control of a flight dual-arm system;

[0011] A method for center-of-gravity compensation control of a flight dual-arm system includes:

[0012] Based on the measured geometric parameters of the two arms, a kinematic model of the robotic arm is established;

[0013] Based on the kinematic model of the robotic arm, considering the influence of the robotic arm's motion on the center of mass of the UAV, a dynamic model of the UAV is established using the momentum theorem for a system of particles.

[0014] Based on the UAV dynamics model, a disturbance observer is designed and a nonlinear disturbance compensation controller is constructed.

[0015] The system acquires the status feedback signals of the dual-arm flight system in real time, and uses a nonlinear disturbance compensation controller to calculate the control signal that will accurately position the UAV to the target location. Driven by the control signal, the UAV achieves precise positioning.

[0016] Furthermore, the geometric parameters of the dual arms include the distance between two adjacent joints in the robotic arm;

[0017] Based on the geometric parameters of the two arms, a DH parameter table is constructed to obtain the coordinate transformation matrix between the coordinate systems of each joint, and the kinematic model of the robotic arm is then calculated as follows:

[0018]

[0019] in, It is the transformation matrix between joint coordinate systems. B r i 1 , i r i 1 The centroids of the i-th joint in the body coordinate system F are respectively B and joint coordinate system F i 1 The position below.

[0020] Furthermore, based on the momentum theorem for a system of particles, the dynamic model of the UAV is established as follows:

[0021]

[0022] Where, m t =m b +m r +m l The total mass of the flight twin-arm system, W p B Indicates the flight dual-arm system in the world coordinate system F W The following position coordinates, Yes W p B By taking the second derivative, we obtain the acceleration. W R B Indicates the flight dual-arm system in the world coordinate system F W The rotation matrix is ​​given by e3, where e3 represents the unit vector [0, 0, 1]. T g is the acceleration due to gravity, and U is the control signal of the flight arm system, U = [U x U y U z ] T U x U y U z These are the control signals for the x-axis, y-axis, and z-axis, respectively, F. d τ d This indicates the force and torque disturbances caused by the robotic arm on the drone.

[0023] Furthermore, the disturbance observer is:

[0024]

[0025]

[0026] in, This is an estimate of d, where d represents the portion of the estimate of the impact of the dual arms on the UAV using a disturbance observer. It is a positive definite gain matrix, and ζ is an auxiliary variable.

[0027] Furthermore, the nonlinear disturbance compensation controller is:

[0028]

[0029] in, Indicates the positional error of the drone. It is a positive definite diagonal gain matrix. f is a positive definite diagonal gain matrix. c This indicates the compensable disturbance experienced by the drone. This represents the estimated value output by the disturbance observer.

[0030] Furthermore, the state feedback signal includes the UAV pose and the system's center of mass position.

[0031] A second aspect of the present invention provides a center-of-gravity compensation control system for a flight dual-arm system.

[0032] A center-of-gravity compensation control system for a dual-arm flight system includes a robotic arm model building module, a drone model building module, a compensation controller building module, and a drone positioning control module.

[0033] The robotic arm model building module is configured to: establish a kinematic model of the robotic arm based on the measured geometric parameters of the two arms;

[0034] The drone model building module is configured to: establish a drone dynamics model based on the kinematic model of the robotic arm, considering the influence of the robotic arm's motion on the drone's center of mass, and using the momentum theorem for a system of particles;

[0035] The compensation controller building module is configured to: design a disturbance observer and build a nonlinear disturbance compensation controller based on the UAV dynamics model;

[0036] The UAV positioning and control module is configured to: acquire the status feedback signal of the flight dual-arm system in real time, use a nonlinear disturbance compensation controller to calculate the control signal to accurately position the UAV to the target position, and complete the accurate positioning of the UAV under the drive of the control signal.

[0037] A third aspect of the present invention provides a flight dual-arm system.

[0038] A dual-arm flight system includes a drone and a robotic arm consisting of a servo motor and connectors. The robotic arm is a dual-arm system, and each robotic arm contains five joints, which are, from top to bottom, shoulder-yaw, shoulder-pitch, elbow-pitch, wrist-roll, and wrist-pitch.

[0039] The drone includes an onboard computer and a flight control unit. The onboard computer communicates with the flight control unit. The onboard computer uses the centroid compensation control method of the dual-arm flight system described in the first aspect of the present invention to calculate the control signal that accurately positions the drone to the target position, and inputs the control signal into the driver of the flight control unit to complete the accurate positioning of the drone.

[0040] The fourth aspect of the present invention provides a computer-readable storage medium having a program stored thereon, which, when executed by a processor, implements the steps of the centroid compensation control method for a flight dual-arm system as described in the first aspect of the present invention.

[0041] The fifth aspect of the present invention provides an electronic device including a memory, a processor, and a program stored in the memory and executable on the processor, wherein the processor executes the program to implement the steps of a center-of-gravity compensation control method for a flight dual-arm system as described in the first aspect of the present invention.

[0042] The above one or more technical solutions have the following beneficial effects:

[0043] Currently, most flying robotic arm systems are operated by a single arm, which often fails to perform well when faced with tasks such as grasping large objects. This invention takes a dual-arm flying system as the research object, designs a dual-arm structure, concentrates the mass mainly in the upper area to reduce the inertia of the two arms, which can greatly expand the operation capability and application range, and establishes an accurate mathematical model.

[0044] Compared to a single-arm flight control system, the presence and movement of the two arms in a dual-arm flight system have a more significant impact on the UAV. To address this issue, this invention proposes a centroid compensation controller based on a disturbance observer, which can achieve precise positioning of the UAV and ensure the safety and stability of the system while completing the required tasks.

[0045] This invention is expected to be further applied to large unmanned helicopters, which has great practical significance.

[0046] Advantages of additional aspects 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

[0047] The accompanying drawings, which form part of this invention, are used to provide a further understanding of the invention. The illustrative embodiments of the invention and their descriptions are used to explain the invention and do not constitute an improper limitation of the invention.

[0048] Figure 1 This is a hardware structure diagram of the flight dual-arm system of the first embodiment.

[0049] Figure 2 This is a flowchart of the method in the second embodiment.

[0050] Figure 3 This is a diagram of the experimental platform for the second embodiment.

[0051] Figure 4(a) is a time position diagram of the UAV positioning experiment in the second embodiment.

[0052] Figure 4(b) is a time thrust diagram in the UAV positioning experiment of the second embodiment.

[0053] Figure 5 This is a system architecture diagram of the third embodiment. Detailed Implementation

[0054] The present invention will be further described below with reference to the accompanying drawings and embodiments.

[0055] It should be noted that the following detailed descriptions are exemplary and intended to provide further explanation of the invention; unless otherwise specified, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains.

[0056] It should be noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit the exemplary embodiments of the present invention; as used herein, the singular form is intended to include the plural form as well, unless the context clearly indicates otherwise; furthermore, it should be understood that when the terms “comprising” and / or “including” are used in this specification, they indicate the presence of features, steps, operations, devices, components and / or combinations thereof.

[0057] Example 1

[0058] This embodiment discloses a dual-arm flying system, the hardware structure of which is flexibly operable as follows: Figure 1 As shown, it includes a drone and two arms consisting of servos and connectors.

[0059] To expand the grasping and manipulating capabilities of the flying robotic arm system, a single arm was replaced with two arms. The mass of the arms is mainly concentrated in the upper shoulder area. This ingenious mechanical structure design can reduce the inertia of the system, thereby reducing the impact of the two arms on the drone.

[0060] The left and right arms are composed of ten servo motors and connectors. The robotic arms mimic the joint configuration of the human arm. Each arm contains five joints, or five degrees of freedom, from top to bottom: shoulder-yaw, shoulder-pitch, elbow-pitch, wrist-roll, and wrist-pitch. The joint and servo motor models and parameters are shown in Table 1 below.

[0061] Table 1 Joint and Servo Parameter Table

[0062] Shoulder-Yaw XM540-W150 8.9 165 Shoulder-up / down XM540-W270 12.9 165 Elbow-Pitch XM540-W150 8.9 165 Wrist-Roll AX-18A 1.8 56 Wrist-Pitch AX-18A 1.8 56

[0063] The drone is selected as a rotorcraft, including but not limited to quadcopters. It can be replaced with a hexacopter or octocopter of similar size. In this embodiment, the quadcopter drone selected is a quadcopter drone with a wheelbase of 550mm. The drone includes an onboard computer and a PixHawk flight control unit. The onboard computer and the flight control unit communicate with each other through the MAVLINK protocol.

[0064] The onboard computer uses the centroid compensation control method of a flight dual-arm system disclosed in Embodiment 2 to calculate the control signal that accurately positions the UAV to the target position, and inputs the control signal into the driver of the flight control unit to complete the accurate positioning of the UAV.

[0065] Example 2

[0066] This embodiment discloses a centroid compensation control method for a dual-arm flight system, the control objective of which is to accurately position the UAV to the target location.

[0067] like Figure 2As shown, a centroid compensation control method for a flight dual-arm system includes:

[0068] Step S201: Establish a kinematic model of the robotic arm based on the measured geometric parameters of the two arms.

[0069] The joint angles in a robotic arm are expressed as follows: in, Let k represent the angle of the i-th joint from top to bottom, namely shoulder-yaw, shoulder-pitch, elbow-pitch, wrist-roll, and wrist-pitch. k=1 represents the right arm, and k=2 represents the left arm. For ease of description, the following simplified expression is defined:

[0070]

[0071] Measure the geometric parameters of the two arms, that is, the distance between two adjacent joints in the robotic arm, such as... Figure 1 The numbers l1, l2, l3, and l4 are shown in the diagram.

[0072] Taking the right arm as an example, the DH parameter table is constructed as shown in Table 2 below.

[0073] Table 2 DH Parameter Table

[0074]

[0075] The transformation matrix between two adjacent joint coordinate systems can be obtained through the DH parameter table. Let the center of mass of the i-th joint be located in the body coordinate system F. B and joint coordinate system F i 1 The positions below are respectively B r i 1 and i r i 1 Based on the kinematics of the robotic arm, the transformation relationship between the two positions can be obtained:

[0076]

[0077] in, The body coordinate system F represents the right arm. B With the coordinate system F of the i-th joint i 1 The transformation matrix between them F represents the coordinate system of the (i-1)th joint of the right arm and the coordinate system of the ith joint. i 1 The transformation matrix between them.

[0078] Taking the time derivative of the above equation, we obtain the following equation:

[0079]

[0080] in, In body coordinate system F B The velocity of the center of mass of the i-th joint. This represents the joint angle vector of the right arm. It is q 1 Perform the first derivative. In the body coordinate system F B Jacobian matrix of the i-th joint of the robotic arm.

[0081] Step S202: Based on the kinematic model of the robotic arm, considering the influence of the robotic arm's motion on the center of mass of the UAV, and using the momentum theorem of a system of particles, establish a dynamic model of the UAV.

[0082] When modeling the dynamics of a quadcopter UAV, it can be regarded as a six-degree-of-freedom rigid body and modeled using the Newton-Euler equations or the Lagrange method. However, for a flying biplane system, the motion of the arms will cause the system's center of mass to change. Therefore, the momentum theorem for a system of particles is used to construct the UAV's dynamics model.

[0083] Suppose there is any point 'a' on the flying two-arm system, the formula for calculating the system momentum P is as follows:

[0084]

[0085] Where, m b m r m l Let r represent the masses of the drone, right arm, and left arm, respectively. a This indicates that point a is in the world coordinate system F. W The absolute position below, It is for r a Taking the first derivative and applying the momentum theorem for a system of particles, the dynamic model of the UAV can be obtained as follows:

[0086]

[0087] Where, m t =m b +m r +m l For the total mass of the flight twin-arm system, W p B The flight dual-arm system is represented in the world coordinate system F. W The following position coordinates, Yes W p B By taking the second derivative, we obtain the acceleration. W R B The flight dual-arm system is represented in the world coordinate system F.W The rotation matrix is ​​given by e3, where e3 represents the unit vector [0, 0, 1]. T g is the acceleration due to gravity, and U is the control signal of the flight arm system. x U y U z ] T U x U y U z These are the control signals for the x-axis, y-axis, and z-axis, respectively, F. d τ d F represents the force and torque disturbances caused by the robotic arm on the drone. d The specific formula is as follows:

[0088]

[0089] in, B ω B This indicates that the UAV is in the body coordinate system F B angular velocity at the bottom, Represents angular velocity B ω B Taking the first derivative, we obtain the acceleration. B r oc This indicates that the center of mass of the flight twin-arm system lies in the body coordinate system F. B The lower position, Indicates the position of the center of mass B r oc By performing the first derivative, the velocity of the flight twin-arm system can be obtained. Indicates the position of the center of mass B r oc By performing second-order differentiation, the acceleration of the flight dual-arm system is obtained, and the specific calculation formula is as follows:

[0090]

[0091] in, B r i 1 , B r i 2 Let F represent the centroids of the i-th joints of the right and left arms in the body coordinate system. B The lower position, These represent the coordinates in the body coordinate system F. B The velocities of the centers of mass at the i-th joints of the right and left arms, m i This represents the mass of the i-th joint.

[0092] Step S203: Based on the UAV dynamics model, design a disturbance observer and construct a nonlinear disturbance compensation controller.

[0093] The dynamic model formula (5) of the UAV is rewritten in the following form:

[0094]

[0095] Where u represents the control signal to be calculated, and f c This represents the disturbance generated by the dual arms that can be directly compensated for. d requires the use of a disturbance observer to estimate the impact of the dual arms on the UAV.

[0096] First, design the disturbance observer, which takes the following form:

[0097]

[0098] in, It is an estimate of d. It is a positive definite gain matrix, ζ is an auxiliary variable, and the error variable e between the actual position and the target position is defined as:

[0099]

[0100] Where p = [x, y, z], p d =[x d ,y d ,z d Let ] represent the actual position of the UAV and the target position, respectively. Next, define the filtered signal s:

[0101]

[0102] in, It is a positive definite diagonal gain matrix.

[0103] The Lyapunov candidate functions are selected as follows:

[0104]

[0105] Differentiate formula (12) with respect to time:

[0106]

[0107] Based on this, the following nonlinear disturbance compensation controller is designed:

[0108]

[0109] Where u represents the control signal to be calculated, s represents the filter signal, and f c This represents the disturbance generated by the dual arms that can be directly compensated for. The part 'd' that requires an disturbance observer to estimate the impact of the dual arms on the UAV is the latter. It is a positive definite diagonal gain matrix. It is a positive definite diagonal gain matrix.

[0110] Step S204: Acquire the status feedback signal of the flight dual-arm system in real time, and use the nonlinear disturbance compensation controller to calculate the control signal to accurately position the UAV to the target position. Driven by the control signal, the UAV is accurately positioned.

[0111] Specifically, obtaining the drone's pose B ω B and the location of the system's centroid B r oc Based on the nonlinear disturbance compensation controller shown in formula (14), the final control signal u is calculated and input into the driver of the flight control unit to complete the precise positioning of the UAV.

[0112] To verify the effectiveness of the method, a test experiment was conducted on the centroid compensation control method of this embodiment. A Raspberry Pi running a 64-bit Ubuntu 18.04 operating system was installed on a quadcopter drone, which was connected to the ground station via 5G band WIFI. The experimental platform is shown in the attached figure. Figure 3 As shown; the main physical parameters of the dual-arm flight system are m b =3.1kg,m r =m l =1.0kg, g=9.8kg·m / s 2 m b m r m l These represent the masses of the drone, right arm, and left arm, respectively; the target position of the drone is set to...

[0113] The control gain of the centroid compensation control method in this embodiment is:

[0114] KΓ+1=diag([8.5,8.5,9.5])

[0115] K+Γ=diag([8.5,8.5,9.5])

[0116] Λ=diag([0.3,0.3,0.4])

[0117] Figure 4 shows the corresponding UAV positioning experiment results. The UAV position corresponds to x, y, z, and the input system control signal is U. x U y U zThe thrust is in the x, y, and z axes. The solid line represents the method of this embodiment, the dotted line represents the traditional method, and the dashed line represents the desired position. As can be seen from the figure, the error between the solid line and the dashed line is smaller than the error between the dotted line and the dashed line. Therefore, the centroid compensation control method of this embodiment can drive the UAV to the target position and the positioning is more accurate.

[0118] In summary, this invention not only proposes a physical structure for a flexible and operable dual-arm operating system, but also demonstrates that the proposed controller can significantly reduce the impact of the robotic arm on the UAV, enabling high-precision positioning of the UAV.

[0119] Example 3

[0120] This embodiment discloses a center of mass compensation control system for a flight dual-arm system;

[0121] like Figure 5 As shown, a center-of-gravity compensation control system for a dual-arm flying system includes a robotic arm model building module, a drone model building module, a compensation controller building module, and a drone positioning control module.

[0122] The robotic arm model building module is configured to: establish a kinematic model of the robotic arm based on the measured geometric parameters of the two arms;

[0123] The UAV model building module is configured to: establish a UAV dynamic model based on the kinematic model of the robotic arm, considering the influence of the robotic arm's motion on the center of mass of the UAV, and using the momentum theorem of a system of particles;

[0124] The compensation controller building module is configured to: design a disturbance observer and build a nonlinear disturbance compensation controller based on the UAV dynamics model;

[0125] The UAV positioning and control module is configured to: acquire the status feedback signal of the flight dual-arm system in real time, use a nonlinear disturbance compensation controller to calculate the control signal to accurately position the UAV to the target position, and complete the accurate positioning of the UAV under the drive of the control signal.

[0126] Example 4

[0127] The purpose of this embodiment is to provide a computer-readable storage medium.

[0128] A computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of a centroid compensation control method for a flight dual-arm system as described in Embodiment 2 of this disclosure.

[0129] Example 5

[0130] The purpose of this embodiment is to provide an electronic device.

[0131] An electronic device includes a memory, a processor, and a program stored in the memory and executable on the processor. When the processor executes the program, it implements the steps in the center-of-gravity compensation control method for a flight dual-arm system as described in Embodiment 2 of this disclosure.

[0132] The above description is merely a preferred embodiment of the present invention and is not intended to limit the invention. Various modifications and variations can be made to the present invention by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A method for center-of-gravity compensation control of a flight dual-arm system, characterized in that, include: Based on the measured geometric parameters of the two arms, a kinematic model of the robotic arm is established; Based on the kinematic model of the robotic arm, considering the influence of the robotic arm's motion on the center of mass of the UAV, a dynamic model of the UAV is established using the momentum theorem for a system of particles. Based on the UAV dynamics model, a disturbance observer is designed and a nonlinear disturbance compensation controller is constructed. The system acquires the status feedback signal of the flight dual-arm system in real time, and uses a nonlinear disturbance compensation controller to calculate the control signal that will accurately position the UAV to the target position. Driven by the control signal, the UAV is accurately positioned. The dynamic model of the UAV, established by combining the momentum theorem for a system of particles, is shown below: in, The total mass of the flight twin-arm system, Indicates the flight dual-arm system in the world coordinate system The following position coordinates, Yes By taking the second derivative, we obtain the acceleration. Indicates the flight dual-arm system in the world coordinate system The rotation matrix below, Represents a unit vector , It is the acceleration due to gravity. These are control signals for the flight boom system. , They are respectively axis, shaft and Control signals in the axial direction, This indicates the force and torque disturbances caused by the robotic arm on the drone; The nonlinear disturbance compensation controller is: in, Indicates the positional error of the drone. It is a positive definite diagonal gain matrix. It is a positive definite diagonal gain matrix. This indicates the compensable disturbance experienced by the drone. This represents the estimated value output by the disturbance observer.

2. The centroid compensation control method for a flight dual-arm system as described in claim 1, characterized in that, The geometric parameters of the dual arms include the distance between two adjacent joints in the robotic arm; Based on the geometric parameters of the two arms, a DH parameter table is constructed to obtain the coordinate transformation matrix between the coordinate systems of each joint, and the kinematic model of the robotic arm is then calculated as follows: in, It is the transformation matrix between joint coordinate systems. , The first The center of mass of each joint in the body coordinate system and joint coordinate system The position below.

3. The centroid compensation control method for a flight dual-arm system as described in claim 1, characterized in that, The disturbance observer is: in, Yes The estimate, This section represents the estimation of the impact of the dual arms on the drone using a disturbance observer. It is a positive definite gain matrix. It is an auxiliary variable.

4. The centroid compensation control method for a flight dual-arm system as described in claim 1, characterized in that, The status feedback signal includes the UAV pose and the position of the system's center of mass.

5. A center-of-gravity compensation control system for a flight dual-arm system, characterized in that, The centroid compensation control method for a dual-arm flight system as described in any one of claims 1-4 includes a robotic arm model building module, a UAV model building module, a compensation controller building module, and a UAV positioning control module. The robotic arm model building module is configured to: establish a kinematic model of the robotic arm based on the measured geometric parameters of the two arms; The drone model building module is configured to: establish a drone dynamics model based on the kinematic model of the robotic arm, considering the influence of the robotic arm's motion on the drone's center of mass, and using the momentum theorem for a system of particles; The compensation controller building module is configured to: design a disturbance observer and build a nonlinear disturbance compensation controller based on the UAV dynamics model; The UAV positioning and control module is configured to: acquire the status feedback signal of the flight dual-arm system in real time, use a nonlinear disturbance compensation controller to calculate the control signal to accurately position the UAV to the target position, and complete the accurate positioning of the UAV under the drive of the control signal.

6. A dual-arm flight system, comprising a drone, a robotic arm consisting of servo motors and connectors, characterized in that, The robotic arm consists of two arms, each containing five joints, from top to bottom: shoulder-yaw, shoulder-pitch, elbow-pitch, wrist-roll, and wrist-pitch. The drone includes an onboard computer and a flight control unit. The onboard computer communicates with the flight control unit. The onboard computer uses the center of mass compensation control method of a dual-arm flight system as described in any one of claims 1-4 to calculate the control signal that accurately positions the drone to the target position. The control signal is then input into the driver of the flight control unit to complete the precise positioning of the drone.

7. A computer-readable storage medium having a program stored thereon, characterized in that, When executed by the processor, the program implements the steps in the centroid compensation control method for a flight dual-arm system as described in any one of claims 1-4.

8. An electronic device, comprising a memory, a processor, and a program stored in the memory and executable on the processor, characterized in that, When the processor executes the program, it implements the steps in the centroid compensation control method for a flight dual-arm system as described in any one of claims 1-4.

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