Multi-point smooth control method and system for mechanical arm and robot equipment

Abstract

The invention relates to the technical field of mechanical arm control, and discloses a mechanical arm multi-point smooth control method and system and robot device.The method comprises the steps that based on positioning information of a visual system and preset parameters of a mounting assembly, Cartesian coordinates of a target point where an actuator at the tail end of a mechanical arm needs to reach are calculated in real time; the number of the target points is one or more; adopting a multi-time B-spline interpolation algorithm to generate a coherent path for the actuator to sequentially reach the target point; when the actuator moves from the current target point to the next target point, the motion parameters of the mechanical arm do not jump; and meanwhile, according to the dynamic variable quantity of the target point and the real-time load of the mechanical arm, an S-shaped acceleration and deceleration curve algorithm is used for adjusting motion parameters of the mechanical arm in real time. Through Cartesian space coherent motion control driven by the dynamic target point, the speed and acceleration of the mechanical arm are adjusted in real time, and the motion smoothness of the mechanical arm and the assembly installation precision are ensured.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of mechanical arm control, in particular to a mechanical arm multi-point smooth control method, system and robot device. BACKGROUND

[0002] In the automatic installation operation of photovoltaic modules, the installation robot manipulator needs to complete the multi-station actions such as module grabbing, positioning, and lamination. The six-axis manipulator sucks and carries the photovoltaic panel by means of the suction cup, and detects the installation datum in real time during the movement, such as the positioning hole on the guide rail, to realize the accurate alignment and installation of the panel. However, since the relative spatial relationship between the manipulator and the installation datum is always in a dynamic change state during the operation, the traditional navigation and positioning method based on fixed point is difficult to adapt to such unstructured operation scene.

[0003] The traditional navigation and positioning method based on fixed point usually relies on the pre-set static coordinate information, lacks the perception and response ability to the dynamic change of the environment, and has significant limitations in pose estimation and positioning accuracy. Firstly, the target component size difference leads to the dynamic adaptation of the target point; secondly, the rigid motion easily causes the component to knock or the installation precision deviation; finally, the fixed speed acceleration cannot cope with the dynamic change when the station is switched. SUMMARY

[0004] In order to solve the above technical problems, the present application discloses a mechanical arm multi-point smooth control method, system and robot device, which realizes real-time adjustment of the speed and acceleration of the manipulator through the continuous motion control of the Cartesian space under the dynamic target point driving, and ensures the motion smoothness of the manipulator and the installation precision of the component.

[0005] Specifically, the technical scheme of the present application is as follows: In the first aspect, the present application discloses a mechanical arm multi-point smooth control method, comprising the following steps: Based on the positioning information of the vision system and the pre-set parameters of the installation component, the Cartesian coordinates of the target points required to be reached by the actuator at the end of the manipulator are calculated in real time; the number of the target points is one or more; A multiple B-spline interpolation algorithm is used to generate a continuous path for the actuator to reach the target points in turn; so that when the actuator moves from the current target point to the next target point, the motion parameters of the manipulator have no jump; the motion parameters include the position, speed and acceleration of the manipulator; At the same time, according to the dynamic change amount of the target point and the real-time load of the manipulator, the S-shaped acceleration and deceleration curve algorithm is used to adjust the motion parameters of the manipulator in real time.

[0006] In some embodiments, the positioning information based on the vision system is used to calculate the Cartesian coordinates of the target point to which the end effector of the robot arm needs to reach in real time according to preset parameters of the mounting assembly, and the calculation specifically includes: The mounting reference of the photovoltaic module is photographed and recognized by an industrial camera, and the reference point coordinates of the mounting reference in the camera coordinate system are further obtained; The reference point coordinates recognized are converted from the camera coordinate system to the robot arm coordinate system based on a homographic matrix of the industrial camera relative to the robot arm coordinate system that is calibrated in advance, so that the Cartesian coordinates of the target point are obtained.

[0007] In some embodiments, the multi-point smooth control method of the robot arm further includes: The vision positioning information is collected in real time according to a preset positioning update period; The dynamic change amount of the target point is obtained by comparing the position of the photovoltaic module obtained in real time with the coordinates of the target point, and if the dynamic change amount is greater than a preset tolerance threshold, it is determined that the robot arm needs to be corrected, and a target point update instruction is triggered immediately.

[0008] In some embodiments, the S-shaped acceleration-deceleration curve algorithm is used to adjust the motion parameters of the robot arm in real time according to the dynamic change amount of the target point and the real-time load of the robot arm, and the adjustment specifically includes: The real-time load information of the robot arm is obtained by a sensor; The dynamic change amount of the target point and the real-time load information are substituted into a calculation model of the S-shaped acceleration-deceleration curve algorithm; The calculation model is configured to be constrained by the acceleration change rate, so that the calculation model can solve a set of motion parameters that best match the current motion state of the robot arm in real time.

[0009] In some embodiments, the calculation model of the S-shaped acceleration-deceleration curve algorithm adjusts the motion parameters based on the following formula: ; ; ; Wherein, is the real-time speed; a is the acceleration; is the acceleration-deceleration time; is the maximum speed; is the adjustment duration.

[0010] In some embodiments, the multi-point smooth control method of the robot arm further includes: When the Cartesian coordinate of the target point is detected, the motion parameters are re-planned; the acceleration of the mechanical arm is adjusted by the following relationship: ; Wherein, is the new acceleration after adjustment; is the current acceleration before adjustment; is the updated Cartesian coordinate of the target point; is the Cartesian coordinate of the target point before update; is the current position coordinate of the mechanical arm; is the load coefficient of the mechanical arm.

[0011] In some embodiments, the multiple B-spline interpolation algorithm is used to generate a continuous path for the actuators to reach the target points in sequence; specifically comprising: A cubic B-spline interpolation algorithm is used to generate a continuous path for the actuators to reach the target points in sequence; the coordinates of the path point P(t) at any time on the continuous path are: ; Wherein, k is the current interpolation segment index; is the cubic B-spline basis function; t∈[0,1]; The cubic B-spline basis function is expressed by the following formula: ; ; ; .

[0012] In a second aspect, the present application further discloses a mechanical arm multi-point smooth control system, which is used to realize the steps of the mechanical arm multi-point smooth control method in any of the above embodiments.

[0013] In some embodiments, the mechanical arm multi-point smooth control system comprises: A point determination module is configured to calculate the Cartesian coordinate of a target point required by an actuator at the end of the mechanical arm in real time based on the positioning information of a vision system and the preset parameters of a mounting assembly; the number of the target points is one or more; A path continuity module is configured to generate a continuous path for the executor to reach the target points in sequence by using a multiple B-spline interpolation algorithm, so that the motion parameters of the robot arm have no jump when the executor moves from the current target point to the next target point, and the motion parameters include the position, speed and acceleration of the robot arm. A parameter adjustment module is configured to use an S-shaped acceleration-deceleration curve algorithm to adjust the motion parameters of the robot arm in real time according to the dynamic change amount of the target points and the real-time load of the robot arm.

[0014] In a third aspect, the application also discloses a robot device, which comprises the robot arm multi-point smooth control system in any of the above embodiments.

[0015] Compared with the prior art, the application has at least one of the following beneficial effects: 1. The application solves the problems of poor rigidity and point adaptation of the robot arm in the installation of photovoltaic modules by combining dynamic target point generation, B-spline continuous path and S-shaped adaptive acceleration adjustment algorithm, and solves the problems of sensor measurement error, distance-related accuracy change and target point dynamic correction demand caused by motion process data optimization, and realizes the coordinated control of high precision and stability.

[0016] 2. The dynamic target point generation technology of the application realizes the rapid response to the real-time change of the target point according to the continuously updated measurement data of the visual sensor. It can effectively adapt to the installation requirements of photovoltaic modules of different specifications and ensure that the system always maintains high-precision positioning in the continuous optimization process.

[0017] 3. The multiple B-spline curve planning continuous and smooth path is combined with the S-shaped adaptive acceleration-deceleration algorithm to adjust the motion parameters in real time. Not only does it ensure the stability of the robot arm motion, but it also avoids the impact and vibration in the start-stop stage, and considers the real-time characteristics of the sensor data to realize the dynamic balance of motion accuracy and stability.

[0018] 4. The core control logic of the application is realized by formula and algorithm, forming a clear, certain and reusable control flow. It greatly reduces the complexity of system deployment and debugging in industrial field, and makes it possible to be applied in actual engineering. BRIEF DESCRIPTION OF DRAWINGS

[0019] The above characteristics, technical features, advantages and implementation modes of the application will be further described in the following preferred embodiments in a clear and easy-to-understand manner combined with the drawings.

[0020] Figure 1 is a step flowchart of an embodiment of the robot arm multi-point smooth control method of the application. Figure 2 This is a flowchart illustrating the steps of another embodiment of a multi-point smooth control method for a robotic arm according to this application; Figure 3 This is a flowchart illustrating the steps of another embodiment of a multi-point smooth control method for a robotic arm according to this application. Detailed Implementation

[0021] In the following description, specific details such as particular system architectures and techniques are set forth for illustrative purposes and not for limitation, in order to provide a thorough understanding of the embodiments of this application. However, those skilled in the art will understand that this application can also be implemented in other embodiments without these specific details. In other instances, detailed descriptions of well-known systems, apparatuses, circuits, and methods have been omitted so as not to obscure the description of this application with unnecessary detail.

[0022] It should be understood that, when used in this specification and the appended claims, the term "comprising" indicates the presence of the described features, integrals, steps, operations, elements and / or components, but does not exclude the presence or addition of one or more other features, integrals, steps, operations, elements, components and / or sets.

[0023] To keep the drawings concise, each figure only schematically shows the parts relevant to the invention, and these do not represent the actual structure of the product. Furthermore, to facilitate understanding, in some figures, only one of components with the same structure or function is schematically depicted, or only one is labeled. In this document, "one" not only means "only one," but can also mean "more than one."

[0024] It should also be further understood that the term “and / or” as used in this application specification and the appended claims means any combination of one or more of the associated listed items and all possible combinations, and includes such combinations.

[0025] Furthermore, in the description of this application, the terms "first," "second," etc., are used only to distinguish descriptions and should not be construed as indicating or implying relative importance.

[0026] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the specific implementation methods of this application will be described below with reference to the accompanying drawings. Obviously, the accompanying drawings described below are only some embodiments of this application. For those skilled in the art, other drawings and other implementation methods can be obtained based on these drawings without creative effort.

[0027] In automated photovoltaic panel installation scenarios, complex environments such as outdoor or large-scale photovoltaic power plants are typically encountered, characterized by densely packed installation bases, large spatial dimensions, and potential construction errors in the installation reference position. During installation, the robotic arm first reliably adsorbs and picks up the photovoltaic panel using a suction cup device on its end effector. Then, while moving along a guide rail or preset path, it uses vision sensors or other positioning devices to identify and track the dynamically changing installation reference in real time. After successfully positioning the reference, the robotic arm needs to adjust its posture in real time based on sensor feedback to precisely align the photovoltaic panel with the installation reference, ultimately completing the placement and installation of the panel.

[0028] During installation, the sensor measurement characteristics and motion data updates cause dynamic fluctuations in the accuracy of the target point. For example, industrial cameras and other vision sensors have inherent measurement errors and environmental noise, including light interference and lens distortion. Furthermore, their data accuracy is positively correlated with the distance between the robotic arm and the photovoltaic module: as the robotic arm approaches the target module, the camera's signal-to-noise ratio for the installation reference improves, and it captures detailed features more clearly, generating more accurate coordinate data. Simultaneously, the robotic arm continuously collects real-time data of the reference point through the vision system during its movement, and performs coordinate transformations and tool offset compensation. As the amount of data collected increases and the depth of feature analysis improves, the accuracy of the target point measurement continues to optimize. If the initial fixed point is still used, it will not meet the requirements for real-time high-precision installation.

[0029] Therefore, this application addresses the module installation robot by achieving Cartesian space coherent motion control driven by dynamic target points. By adjusting the speed and acceleration of the robotic arm in real time, it ensures smooth motion and installation accuracy, adapting to the installation requirements of photovoltaic modules of different specifications.

[0030] Reference manual attached Figure 1 As shown, an embodiment of a multi-point smooth control method for a robotic arm according to this application specifically includes the following steps: S100, based on the positioning information of the vision system and the preset parameters of the installation components, calculates in real time the Cartesian coordinates of the target point that the actuator at the end of the robotic arm needs to reach; the number of the target points is one or more.

[0031] Specifically, the end effector of the robotic arm includes, but is not limited to, suction cups, robotic arms, grippers, and other devices used for handling photovoltaic modules.

[0032] In a robotic arm motion control system, the target point that the actuator needs to reach refers to the designated position it must reach within the task space. Taking photovoltaic module installation as an example, the target point is determined by a pre-set installation benchmark, such as the center or edge alignment mark of the module positioning hole accurately identified by a vision system. The robotic arm end effector needs to move to the coordinate position of the target point in order to complete subsequent processes such as gripping, placing, or fastening.

[0033] S200, using multiple B-spline interpolation algorithms, generates a coherent path for the actuator to sequentially reach the target point; ensuring that the motion parameters of the robotic arm do not jump when the actuator moves from the current target point to the next target point; the motion parameters include the position, velocity, and acceleration of the robotic arm.

[0034] S300, based on the dynamic change of the target point and the real-time load of the robotic arm, the motion parameters of the robotic arm are adjusted in real time using an S-shaped acceleration / deceleration curve algorithm.

[0035] Traditional motion control methods require a trade-off between speed and accuracy. This application, however, solves the problems of rigidity and poor positional adaptability of robotic arms during photovoltaic module installation by combining dynamic target point generation with B-spline coherent paths and S-shaped adaptive acceleration adjustment algorithms. It also specifically addresses the need for dynamic target point correction caused by sensor measurement errors, distance-related accuracy variations, and motion process data optimization, achieving coordinated control of high precision and stability.

[0036] B-spline curves generate smooth paths with continuous curvature, geometrically avoiding the root cause of motion impact. S-curve acceleration programming, building upon this, ensures smooth changes in velocity and acceleration by constraining the rate of change of acceleration, further suppressing vibration in the time dimension. This reduces positioning errors caused by inertial impacts during start-up, stopping, and speed changes, thus improving cycle time while ensuring final positioning accuracy. The combination of these two techniques enables the robotic arm to track complex paths with extremely high stability, which is crucial for high-precision, vibration-sensitive operations such as photovoltaic module installation.

[0037] Based on the above embodiments, this application discloses another embodiment of a multi-point smooth control method for a robotic arm, wherein step S100 specifically includes the following sub-steps: S110: The installation reference of the photovoltaic module is captured and identified by an industrial camera, and the coordinates of the reference point of the installation reference in the camera coordinate system are further obtained.

[0038] S120, based on the pre-calibrated homogeneous transformation matrix of the industrial camera relative to the robotic arm coordinate system, the coordinates of the identified reference point are transformed from the camera coordinate system to the robotic arm coordinate system, thereby obtaining the Cartesian coordinates of the target point.

[0039] Specifically, the installation datum, serving as a spatial reference in the automated installation process, possesses key characteristics such as detectability, uniqueness, and determinism, thereby providing a stable and reliable pose reference for the robotic arm. Optionally, the installation datum includes, but is not limited to, guide rail positioning holes, positioning chips, or other markings.

[0040] In some implementations, the transformation from the homogeneous transformation matrix to the robot arm coordinate system is achieved using the following conversion formula: .

[0041] in, The coordinates of the target point in the robotic arm coordinate system include position and attitude information; This is the homogeneous transformation matrix of the camera relative to the robot arm coordinate system, containing rotation and translation parameters, which needs to be pre-calibrated; The coordinates of the reference point installed in the camera coordinate system; This refers to the end effector tool offset. Specifically, the end effector tool offset... It is determined by the size of the suction cup and the installation position, and is used to compensate for the influence of the tool length on the end position.

[0042] The Cartesian coordinates of the target point include six degrees of freedom (x, y, z, α, β, γ). The x, y, and z degrees of freedom represent translational motion along the X, Y, and Z axes, respectively, used to determine its spatial position. The α, β, and γ degrees of freedom represent rotational motion about these three axes, namely yaw, pitch, and roll, used to determine its attitude orientation.

[0043] During the actual installation of photovoltaic modules, due to factors such as robot movement, continuous updates of vision system positioning information, and real-time interference from environmental factors, the target point that the actuator needs to reach in the robotic arm coordinate system is not a fixed coordinate, but rather a relatively dynamic one. Therefore, it is necessary to achieve dynamic identification of the target point to ensure that the target point is consistent with the actual position of the module.

[0044] In some other embodiments, step S100 further includes a sub-step: S130: According to a preset positioning update cycle, visual positioning information is collected periodically. By comparing the real-time acquired position of the photovoltaic module with the current coordinates of the target point, the dynamic change of the target point is obtained. If the dynamic change exceeds a preset tolerance threshold, it is determined that the robotic arm needs to perform trajectory correction, and a target point update command is triggered.

[0045] Optionally, this embodiment will be described using a preset positioning update time of 0.1 seconds as an example. Combining the dynamic change characteristics of sensor accuracy with the data optimization requirements of the motion process, the reference point data collected by the vision system is read every 0.1 seconds. On the one hand, as the robotic arm approaches the component, the distance between the camera and the reference point shortens, effectively reducing measurement errors and noise interference; the newly collected data can correct the initial measurement deviation. On the other hand, continuous data collection can accumulate more reference point feature information, further improving coordinate calculation accuracy through multi-frame data fusion. Based on this, to ensure the real-time nature of the target point, the reference point data collected by the vision system is read every 0.1 seconds, comparing the deviation between the current target point and the latest reference point.

[0046] In some implementations, the expected deviation threshold is set to 0.3 mm. When the dynamic change of the target point, i.e., the actual deviation, is greater than 0.3 mm, the target point is immediately updated. If the deviation is less than or equal to 0.3 mm, the current target point remains unchanged to avoid motion fluctuations caused by frequent adjustments. Based on the real-time changes of the target point, this application plans the optimal motion trajectory online from the current position of the actuator to the latest target point. Even when dealing with continuously changing work scenarios, it can still ensure the smoothness, stability, and final execution accuracy of the entire motion process.

[0047] This application provides another embodiment of a multi-point smooth control method for a robotic arm. Based on any embodiment of the above method, step S200 specifically includes: A cubic B-spline interpolation algorithm is used to generate a coherent path for the actuator to sequentially reach the target point. The coordinates of the path point P(t) at any time on the coherent path are: .

[0048] Where k is the index of the current interpolation segment; It is a cubic B-spline basis function; t∈[0,1].

[0049] In this embodiment, it is assumed that the robotic arm has N dynamic target points, namely: , … Each dynamic target point's Cartesian coordinates includes six dimensions: x, y, z, α, β, and γ.

[0050] Optionally, the index k of the current interpolation segment can be in the range of 0 ≤ k ≤ n-4, ensuring that each interpolation segment contains 4 control points. The B-spline basis functions have 4 specific expressions: ; ; ; .

[0051] Compared to traditional linear interpolation, cubic B-spline interpolation ensures the continuity of the path's second derivative, i.e., acceleration, avoiding impacts to the robotic arm joints caused by sudden changes in velocity and acceleration. Secondly, it offers high path smoothness, effectively reducing the risk of bumps and knocks during photovoltaic module handling and adapting to the fragile nature of the modules. Finally, the interpolated path passes near the control point, accommodating minor adjustments to the target point due to improved sensor accuracy and data optimization, preventing path interruptions or jumps, and ensuring motion continuity unaffected by accuracy corrections.

[0052] This application provides another embodiment of a multi-point smooth control method for a robotic arm. Based on any embodiment of the above method, step S300 specifically includes the following steps.

[0053] S310, real-time load information of the robotic arm is obtained through sensors.

[0054] S320, Substitute the dynamic change of the target point and the real-time load information into the calculation model of the S-shaped acceleration / deceleration curve algorithm.

[0055] S330, the calculation model is configured to be constrained by the rate of change of acceleration, so that the calculation model can solve in real time for the set of motion parameters that best matches the current motion state of the robotic arm.

[0056] Specifically, the dynamic changes of the target point are analyzed in real time, and the real-time load information of the robotic arm is obtained through joint torque sensors or observers.

[0057] In some implementations, the dynamic change of the target point .in The updated target point coordinates; These are the coordinates of the target point before the update.

[0058] In practical implementation, the ideal load threshold for the robotic arm is 20~50kg. The dynamic change of the target point includes both adaptation adjustments caused by differences in component size and accuracy corrections resulting from improved sensor accuracy and multi-frame data fusion.

[0059] In other embodiments, the calculation model of the S-shaped acceleration / deceleration curve algorithm uses the following formula to adjust the motion parameters: ; ; .

[0060] in, 'a' represents real-time velocity; 'a' represents acceleration. For acceleration and deceleration time; Maximum speed; To adjust the duration.

[0061] Specifically, the acceleration / deceleration time t_a is positively correlated with the maximum speed and acceleration. This can be expressed by the following formula: The acceleration 'a' is dynamically adjusted according to the load; the greater the load, the smaller the acceleration.

[0062] In other implementations, if the actual load weight exceeds the ideal load threshold, the robot operates with pre-set motion parameters. For example, if the load is greater than 50 kg, a ≤ 0.5 m / s², and if the load is less than 20 kg, a ≤ 1.2 m / s², to avoid motion instability caused by excessive load. These motion parameters, adjusted in real time, are sent to the robot arm's underlying servo controller to precisely drive the joint motors, ensuring that the robot arm maintains smooth, fast, and accurate motion performance when facing dynamic targets and load changes.

[0063] Based on the above embodiments, this application discloses another embodiment of a multi-point smooth control method for a robotic arm. Step S300 further includes step S340: when the Cartesian coordinates of the target point are detected to be updated, the motion parameters are replanned. The acceleration of the robotic arm is adjusted using the following relationship: .

[0064] in, The adjusted new acceleration; The current acceleration before adjustment; The updated Cartesian coordinates of the target point; The Cartesian coordinates of the target point before the update; The coordinates of the current position of the robotic arm; The load factor of the robotic arm is denoted as .

[0065] Specifically, the load coefficient is collected in real time by a torque sensor, and its value ranges from 0.6 to 1.0. The larger the load, the smaller the coefficient.

[0066] In other implementations, the adjustment must ensure the impact of the robotic arm, i.e., the rate of change of acceleration ≤ 5 m / s³, to avoid motion impact.

[0067] Based on the same concept, this application also discloses a multi-point smoothing control system for a robotic arm. The system is used to implement the steps described in any of the above method embodiments. Specifically, one embodiment of the multi-point smoothing control system for a robotic arm in this application includes: The point determination module is configured to calculate the Cartesian coordinates of the target point that the actuator at the end of the robotic arm needs to reach in real time, based on the positioning information from the vision system and the preset parameters of the installation components. The number of target points can be one or more.

[0068] The path continuity module is configured to use a multiple B-spline interpolation algorithm to generate a continuous path for the actuator to sequentially reach the target points. This ensures that the motion parameters of the robotic arm do not change abruptly when the actuator moves from the current target point to the next target point. The motion parameters include the position, velocity, and acceleration of the robotic arm.

[0069] The parameter adjustment module is configured to adjust the motion parameters of the robotic arm in real time using an S-shaped acceleration / deceleration curve algorithm based on the dynamic changes of the target point and the real-time load of the robotic arm.

[0070] Specifically, the technical details of each module in this embodiment are the same as the steps described in any of the above-mentioned multi-point smooth control methods for robotic arms. This embodiment will not repeat the description.

[0071] On the other hand, this application also discloses a robotic device, which includes a multi-point smooth control system for a robotic arm as described in any of the above embodiments.

[0072] The multi-point smooth control method, system and robot device of this application have the same technical concept, and the technical details of the embodiments of the three are applicable to each other. In order to reduce repetition, they will not be described again here.

[0073] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the above-described division of program modules is merely an example. In practical applications, the above functions can be assigned to different program modules as needed, that is, the internal structure of the device can be divided into different program units or modules to complete all or part of the functions described above. The program modules in the embodiments can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one processing unit. The integrated unit can be implemented in hardware or as a software program unit. Furthermore, the specific names of the program modules are only for easy differentiation and are not intended to limit the scope of protection of this application.

[0074] Obviously, those skilled in the art can make various modifications and variations to this application without departing from the spirit and scope of this application. Therefore, if such modifications and variations fall within the scope of the claims of this application and their equivalents, this application also intends to include such modifications and variations.

Claims

1. A method for smooth multi-point control of a robotic arm, characterized in that, Includes the following steps: Based on the positioning information of the vision system and the preset parameters of the installation components, the Cartesian coordinates of the target point that the actuator at the end of the robotic arm needs to reach are calculated in real time; the number of the target points is one or more. A continuous path is generated by employing multiple B-spline interpolation algorithms to sequentially reach the target points, ensuring that the motion parameters of the robotic arm do not change abruptly when the actuator moves from the current target point to the next target point; the motion parameters include the position, velocity, and acceleration of the robotic arm. Meanwhile, based on the dynamic changes of the target point and the real-time load of the robotic arm, the motion parameters of the robotic arm are adjusted in real time using an S-shaped acceleration / deceleration curve algorithm.

2. The multi-point smooth control method for a robotic arm as described in claim 1, characterized in that, The aforementioned calculation of the Cartesian coordinates of the target point to be reached by the actuator at the end of the robotic arm, based on the positioning information from the vision system and the preset parameters of the installation components, specifically includes: The installation reference of the photovoltaic module is captured and identified by an industrial camera, and the coordinates of the reference point of the installation reference in the camera coordinate system are further obtained. Based on the pre-calibrated homogeneous transformation matrix of the industrial camera relative to the robotic arm coordinate system, the coordinates of the identified reference point are transformed from the camera coordinate system to the robotic arm coordinate system, thereby obtaining the Cartesian coordinates of the target point.

3. The multi-point smooth control method for a robotic arm as described in claim 2, characterized in that, Also includes: The location information is collected periodically according to a preset location update cycle; The dynamic change of the target point is obtained by comparing the real-time position of the photovoltaic module with the current coordinates of the target point. If the dynamic change exceeds a preset tolerance threshold, the robotic arm is determined to need trajectory correction, and a target point update command is triggered.

4. The multi-point smooth control method for a robotic arm as described in claim 3, characterized in that, The method of adjusting the motion parameters of the robotic arm in real time using an S-shaped acceleration / deceleration curve algorithm based on the dynamic change of the target point and the real-time load of the robotic arm specifically includes: The real-time load information of the robotic arm is obtained through sensors; The dynamic change of the target point and the real-time load information are substituted into the calculation model of the S-shaped acceleration / deceleration curve algorithm; The calculation model is configured to be constrained by the rate of change of acceleration, so that the calculation model can calculate in real time the set of motion parameters that best matches the current motion state of the robotic arm.

5. The multi-point smooth control method for a robotic arm as described in claim 4, characterized in that, The calculation model of the S-shaped acceleration / deceleration curve algorithm adjusts the motion parameters based on the following formula: ； ； ； in, 'a' represents real-time velocity; 'a' represents acceleration. For acceleration and deceleration time; Maximum speed; To adjust the duration.

6. The multi-point smooth control method for a robotic arm as described in claim 5, characterized in that, Also includes: When an update to the Cartesian coordinates of the target point is detected, the replanning of the motion parameters is triggered; The acceleration of the robotic arm is adjusted using the following formula; ； in, The adjusted new acceleration; The current acceleration before adjustment; The updated Cartesian coordinates of the target point; The Cartesian coordinates of the target point before the update; The coordinates of the current position of the robotic arm; The load factor of the robotic arm is denoted as .

7. A multi-point smooth control method for a robotic arm as described in any one of claims 1-6, characterized in that, The method of using multiple B-spline interpolation to generate a coherent path for the actuator to sequentially reach the target point includes: Using cubic B-spline interpolation, a coherent path is generated for the actuator to sequentially reach the target point; the coordinates of the path point P(t) at any time on the coherent path are: ； Where k is the index of the current interpolation segment; The basis functions are cubic B-spline functions; t∈[0,1]; The cubic B-spline basis function is expressed by the following formula: ； ； ； 。 8. A multi-point smooth control system for a robotic arm, characterized in that, The system is used to implement the steps of the multi-point smooth control method for a robotic arm as described in any one of claims 1-7.

9. A multi-point smooth control system for a robotic arm as described in claim 8, characterized in that, include: The point determination module is configured to calculate the Cartesian coordinates of the target point that the actuator at the end of the robotic arm needs to reach in real time based on the positioning information of the vision system and the preset parameters of the installation components; the number of the target points is one or more. The path continuity module is configured to use a multiple B-spline interpolation algorithm to generate a continuous path for the actuator to reach the target point sequentially; so that when the actuator moves from the current target point to the next target point, the motion parameters of the robotic arm do not change abruptly; the motion parameters include the position, velocity, and acceleration of the robotic arm. The parameter adjustment module is configured to adjust the motion parameters of the robotic arm in real time using an S-shaped acceleration / deceleration curve algorithm based on the dynamic changes of the target point and the real-time load of the robotic arm.

10. A robotic device, characterized in that, The robotic device includes a multi-point smooth control system for a robotic arm as described in claim 8 or 9.

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