A robot carbon fiber winding trajectory planning method and device

Abstract

This application proposes a method and apparatus for planning the trajectory of carbon fiber winding in a robot, relating to the field of carbon fiber winding technology. The method includes: collecting key winding data at the current moment through the robot's online sensing system; generating theoretical control data for the next moment using a geodesic algorithm; constructing a trajectory planning objective function and constraints; substituting the key winding data at the current moment into the constraints to determine whether trajectory correction is triggered; when trajectory correction is not triggered, the robot winds the carbon fiber according to the theoretical control data for the next moment; when trajectory correction is triggered, substituting the key winding data at the current moment into the trajectory planning objective function, solving it using a quadratic programming QP solver to obtain incremental control data for the next moment; correcting the theoretical control data for the next moment based on the incremental control data to obtain corrected control data for the next moment; and then winding the carbon fiber according to the corrected control data for the next moment.

Description

Technical Field

[0001] This application relates to the field of carbon fiber winding technology, and in particular to a method and apparatus for planning the trajectory of carbon fiber winding for robots. Background Technology

[0002] Carbon fiber winding involves winding continuous fibers or tapes impregnated with resin onto a mandrel according to specific rules, followed by curing and demolding. The rapid development of industrial robotics technology has accelerated the application of robotics in traditional fiber winding processes. Compared to traditional CNC winding machines, integrating robots into winding equipment offers advantages such as high repeatability, large processing space, high flexibility, and diverse functions.

[0003] However, in the process of trajectory planning, existing carbon fiber winding robots do not simultaneously consider trajectory deviation, tension stability and speed smoothness in the trajectory objective function design, and do not consider multiple constraints when solving for corrections, resulting in insufficient control accuracy of carbon fiber winding and affecting the quality of carbon fiber workpieces. Summary of the Invention

[0004] To address the aforementioned problems, in a first aspect, the present invention provides a method for planning the trajectory of carbon fiber winding in a robot, comprising: The robot's online sensing system collects key entanglement data at the current moment, and the geodesic algorithm generates theoretical control data for the next moment. Construct the objective function and constraints for trajectory planning, and substitute the current entanglement key data into the constraints to determine whether trajectory correction is triggered. When trajectory correction is not triggered, the robot performs carbon fiber winding according to the theoretical control data for the next moment; When trajectory correction is triggered, the current winding key data is substituted into the trajectory planning objective function and solved by a quadratic programming QP solver to obtain the incremental control data for the next moment. The theoretical control data for the next moment is corrected based on the incremental control data for the next moment to obtain the corrected control data for the next moment. The robot winds the carbon fiber according to the corrected control data for the next moment.

[0005] In one embodiment, the online sensing system includes a tension sensor, a line laser profile scanner, a high-resolution industrial camera, and a speed sensor. The online sensing system of the robot collects key entanglement data at the current moment, including: The actual fiber tension is collected in real time by a tension sensor, the point cloud data of the winding profile is collected in real time by a line laser profile scanner, the image of the winding area is collected in real time by a high-resolution industrial camera, and the actual fiber output speed is collected in real time by a speed sensor. The actual winding thickness is obtained by performing coordinate transformation and thickness extraction on the point cloud data of the winding profile. Trajectory points are extracted from the point cloud data of the winding profile and the image of the winding area to obtain the actual trajectory point set; The actual winding speed, actual winding offset, actual average offset, and actual fiber slip ratio are calculated based on the actual trajectory point set. The actual trajectory point set, actual winding thickness, actual fiber tension, actual fiber exit speed, actual winding speed, actual winding offset, actual average offset, and actual fiber slip ratio at the current moment constitute the key winding data at the current moment.

[0006] In one embodiment, the theoretical control data includes a theoretical trajectory point set, a theoretical winding speed, and a theoretical winding acceleration.

[0007] In one embodiment, constructing the trajectory planning objective function and constraints includes: A trajectory deviation term is constructed based on the offset increment, a tension stability term is constructed based on the tension increment, and a velocity smoothing term is constructed based on the acceleration increment. The trajectory deviation term, tension stability term, and velocity smoothing term are weighted and summed to construct the trajectory planning objective function; Set the maximum offset, the safe tension range, the maximum slip ratio, and the theoretical winding thickness of the workpiece; The following constraints are used: the actual average offset is less than or equal to the maximum offset; the actual fiber tension is within the tension safety range; the actual fiber slip ratio is less than or equal to the maximum slip ratio; and the actual winding thickness is less than or equal to the theoretical winding thickness of the workpiece.

[0008] In one embodiment, the step of substituting the current entanglement key data into the constraint conditions to determine whether trajectory correction is triggered includes: If the actual average offset, actual fiber tension, actual fiber slip ratio, and actual winding thickness all meet the constraint conditions, then it is determined that trajectory correction will not be triggered; otherwise, it is determined that trajectory correction will be triggered.

[0009] In one embodiment, substituting the current entanglement key data into the trajectory planning objective function and solving it using a quadratic programming QP solver to obtain the incremental control data for the next time step includes: Obtain the actual winding offset, actual fiber tension, actual average offset, actual fiber slip ratio, and actual winding thickness from the key winding data at the current moment; Substitute the actual winding offset into the trajectory deviation term, and the actual fiber tension into the tension stability term; Under the constraints, the optimal offset increment, optimal tension increment, and optimal acceleration increment that minimize the objective function of trajectory planning are calculated by a quadratic programming QP solver. The optimal trajectory point increment set is obtained by calculating the trajectory point increment based on the optimal offset increment; the optimal velocity increment is obtained by calculating the velocity increment based on the optimal tension increment. The incremental control data for the next moment consists of the optimal trajectory point increment set, the optimal velocity increment, and the optimal acceleration increment.

[0010] In one embodiment, the step of correcting the theoretical control data for the next time step based on the incremental control data for the next time step to obtain the corrected control data for the next time step includes: Obtain the optimal trajectory point increment set, optimal velocity increment, and optimal acceleration increment from the incremental control data at the next moment; The theoretical trajectory point set is corrected by modifying the optimal trajectory point increment set to obtain the corrected trajectory point set; The corrected winding speed is obtained by correcting the theoretical winding speed using the optimal speed increment; The corrected winding acceleration is obtained by correcting the theoretical winding acceleration using the optimal acceleration increment; The correction control data for the next moment consists of the correction trajectory point set, the correction winding speed, and the correction winding acceleration.

[0011] Secondly, the present invention provides a robot carbon fiber winding trajectory planning device for implementing the aforementioned robot carbon fiber winding trajectory planning method, the device comprising: The data acquisition module is used to collect key entanglement data at the current moment through the robot's online sensing system, and to generate theoretical control data for the next moment through geodesic algorithms; The correction judgment module is used to construct the trajectory planning objective function and constraints, and substitute the current entanglement key data into the constraints to determine whether trajectory correction is triggered. The theoretical control module is used to ensure that the robot winds carbon fiber according to the theoretical control data for the next moment when trajectory correction is not triggered. The trajectory correction module is used to substitute the current winding key data into the trajectory planning objective function when trajectory correction is triggered. The objective function is solved by a quadratic programming QP solver to obtain the incremental control data for the next moment. The theoretical control data for the next moment is corrected based on the incremental control data for the next moment to obtain the corrected control data for the next moment. The robot winds the carbon fiber according to the corrected control data for the next moment.

[0012] Thirdly, the present invention provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the robot carbon fiber winding trajectory planning method.

[0013] Fourthly, the present invention provides a non-transitory computer-readable storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the robot carbon fiber winding trajectory planning method.

[0014] The present invention has the following beneficial effects: 1. The trajectory planning objective function constructed in this invention simultaneously considers trajectory deviation, tension stability, and velocity smoothness, with clear safety boundaries under constraints. This avoids fiber breakage caused by sudden tension changes and prevents loosening of the winding layer caused by velocity fluctuations, ensuring the consistency of parameters during multi-layer winding. Under the constraints, the trajectory planning objective function is solved by a quadratic programming QP solver. While considering multiple constraints, the control correction amount is accurately calculated, significantly reducing the geometric error of the winding layer and greatly improving the control accuracy of carbon fiber winding.

[0015] 2. The trajectory deviation term locks in geometric accuracy, the tension stability term ensures fiber stress safety, and the speed smoothness term avoids motion impact. The weighted summation allows for flexible adjustment of priorities according to process requirements, achieving the optimal synergy of accuracy, stability, and smoothness in the trajectory planning objective function. The safety thresholds for offset, tension, slip ratio, and thickness are clearly defined to eliminate potential quality hazards such as fiber breakage, excessive trajectory deviation, and excessive winding thickness from the source, ensuring that every key indicator is within a controllable range and further improving the control accuracy of carbon fiber winding.

[0016] 3. Within the preset constraints, the quadratic programming QP solver efficiently finds the incremental combination that minimizes the objective function of trajectory planning, achieving synergistic optimization of trajectory accuracy, tension stability, and speed smoothness, while ensuring that the correction does not exceed the safety threshold; the incremental control data covers the three core control dimensions of trajectory points, velocity, and acceleration, and can simultaneously correct position deviation, velocity matching degree, and motion stability, thereby improving the correction efficiency and accuracy of robot trajectory. Attached Figure Description

[0017] To more clearly illustrate the technical solutions in the embodiments or related technologies of this application, the accompanying drawings used in the description of the embodiments or related technologies will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0018] Figure 1 This is a flowchart of a method according to an embodiment of the present invention; Figure 2 This is a structural diagram of the device according to an embodiment of the present invention. Detailed Implementation

[0019] To enable those skilled in the art to better understand the technical solutions in this specification, the technical solutions in the embodiments of this specification will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments.

[0020] The terminology used in the following embodiments of this application is for the purpose of describing particular embodiments only and is not intended to be limiting of this application. As used in the specification of this application, the singular expressions “a,” “an,” “the,” “the,” “the,” and “this” are intended to include the plural expressions as well, unless the context clearly indicates otherwise. It should also be understood that the term “and / or” as used in this application refers to and includes any or all possible combinations of one or more of the listed items.

[0021] Hereinafter, the terms "first" and "second" are used for descriptive purposes only and should not be construed as implying or suggesting relative importance or implicitly indicating the number of indicated technical features. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature, and in the description of the embodiments of this application, unless otherwise stated, "multiple" means two or more.

[0022] To enable those skilled in the art to better understand the technical solution of the present invention, the present invention will be further described in detail below with reference to the accompanying drawings.

[0023] Reference Figure 1 This invention provides a method for planning the trajectory of carbon fiber winding for a robot, comprising: The S100 collects key entanglement data at the current moment through the robot's online sensing system and generates theoretical control data for the next moment through a geodesic algorithm.

[0024] In some embodiments, the online sensing system includes a tension sensor, a line laser profile scanner, a high-resolution industrial camera, and a speed sensor. The online sensing system of the robot collects key entanglement data at the current moment, including: The actual fiber tension is collected in real time by a tension sensor, the point cloud data of the winding profile is collected in real time by a line laser profile scanner, the image of the winding area is collected in real time by a high-resolution industrial camera, and the actual fiber output speed is collected in real time by a speed sensor. The actual winding thickness is obtained by performing coordinate transformation and thickness extraction on the point cloud data of the winding profile. Trajectory points are extracted from the point cloud data of the winding profile and the image of the winding area to obtain the actual trajectory point set; The actual winding speed, actual winding offset, actual average offset, and actual fiber slip ratio are calculated based on the actual trajectory point set. The actual trajectory point set, actual winding thickness, actual fiber tension, actual fiber exit speed, actual winding speed, actual winding offset, actual average offset, and actual fiber slip ratio at the current moment constitute the key winding data at the current moment.

[0025] In some embodiments, the robotic fiber winding system mainly includes a robot, a fiber unwinding machine, a winding tool at the robot's end effector, a mandrel, an industrial computer, and an online sensing system. The installation location and function of the online sensing system are as follows: A speed sensor is integrated into the end of the fiber unwinding machine's guide wheel shaft to acquire the fiber unwinding linear speed. A tension sensor is installed between the fiber unwinding machine and the robot's end effector winding tool to acquire tension information. A line laser profile scanner and a high-resolution industrial camera are integrated into the side of the robot's end effector winding tool via a lightweight, high-rigidity bracket, ensuring that both the laser scanning surface and the camera's field of view cover the winding contact area, and avoiding obstruction by the end effector. The line laser profile scanner is used to construct a high-precision three-dimensional profile of the winding layer. The high-resolution industrial camera, in conjunction with a high-frequency auxiliary light source, is used to capture the highlight texture and edge features of the black carbon fiber surface. Both are jointly calibrated to establish a strict spatial rigid body transformation relationship.

[0026] Tension sensors are installed on the fiber path between the fiber feeding machine and the robot's end-effector winding tool to capture tension fluctuation data in real time during fiber transmission, with a sampling frequency of no less than 100Hz. A line laser profile scanner and a high-resolution industrial camera are integrated on the side of the end-effector winding tool through a lightweight, high-rigidity bracket, ensuring that the laser scanning surface and the camera's field of view completely cover the winding contact area and avoiding obstruction by the end effector. The industrial camera is equipped with a high-frequency auxiliary light source to clearly capture the highlight texture and edges of the black carbon fiber. The fiber output line speed is collected in real time by the speed detection module built into the fiber feeding machine and transmitted synchronously to the industrial control computer.

[0027] The point cloud data of the profile acquired by the line laser contour scanner is first transformed to the robot coordinate system using a dual transformation matrix from the flange coordinate system to the robot base coordinate system and from the laser sensor coordinate system to the flange coordinate system. Then, a clustering algorithm based on Euclidean distance is used to segment the point cloud, filter out the point cloud contour of the wound fiber bundle, and extract the Z-axis coordinate value of the contour in the robot coordinate system, which is the actual winding thickness at the current position. .

[0028] By combining the joint extrinsic parameter calibration results of the line laser profile scanner and the industrial camera, the theoretical trajectory points are projected onto the camera pixel coordinate system, and an M×N region of interest (ROI) is constructed centered on these points. The Canny operator edge detection + sub-pixel thinning algorithm is used on the ROI image to accurately extract the pixel coordinates of the left and right edges of the fiber bundle, and the pixel coordinates of the fiber center are calculated. Then, using the camera intrinsic parameter inverse matrix, the transformation matrix from the laser coordinate system to the camera coordinate system, and the laser depth value, the pixel coordinates are converted into spatial coordinates in the robot coordinate system, forming the actual trajectory point set. .

[0029] Actual winding speed Take the spatial Euclidean distance between two adjacent points in the actual trajectory point set, and divide it by the fixed sampling period Δt, i.e. , For the k-th trajectory point in the actual trajectory point set, It is the (k-1)th trajectory point in the actual trajectory point set; By performing spatiotemporal matching between the actual trajectory point set and the corresponding theoretical trajectory point set, the spatial Euclidean distance between each corresponding point is calculated, which is the actual winding offset of the trajectory point. The actual average offset is obtained by calculating the arithmetic mean of the offsets of all single points within a single control cycle. .

[0030] Tension information is collected and transmitted to the industrial control computer in real time, and the tension sensor reads the actual fiber tension in real time. .

[0031] The actual fiber output speed is read by the speed sensor of the fiber feeding machine. It is transmitted to the industrial control computer in real time.

[0032] By using the actual trajectory point coordinates and the real-time position of the guide hole of the winding tool, the direction vector β of the fiber suspension segment is calculated. Combined with the surface normal vector n of the corresponding point of the mandrel, the angle α between the two is solved, and the actual fiber slip ratio S=sinα.

[0033] The actual trajectory point set, actual winding thickness, actual fiber tension, actual fiber exit speed, actual winding speed, actual winding offset, actual average offset, and actual fiber slip rate obtained in the above steps are packaged according to the control cycle time sequence to form the key winding data at the current moment. This data is then transmitted to the host computer via serial communication for subsequent judgment and optimization.

[0034] In some embodiments, the theoretical control data includes a theoretical trajectory point set, a theoretical winding speed, and a theoretical winding acceleration.

[0035] In some embodiments, a 3D CAD model of the mandrel is imported as a reference surface. A geodesic algorithm is used to plan the single-layer winding trajectory. The spacing between trajectory points is set according to the curvature distribution of the mandrel surface. The spacing between points in areas with large curvature is ≤5mm, and in areas with gentle curvature it is ≤10mm, ensuring that the fiber completely covers the mandrel surface. Through inverse kinematics solution, the trajectory points on the surface are converted into a set of spatial coordinates in the robot's base coordinate system, forming a theoretical trajectory point set. If it is a multi-layer winding, the equivalent mandrel model needs to be updated based on the measured average thickness of the previous layer, and the above steps are repeated on the new model to generate the theoretical trajectory point set for the next layer.

[0036] Based on the characteristics of the fiber material and process requirements, the theoretical winding speed is set. Combined with the core mold contour features, speed attenuation is applied to complex areas such as abrupt curvature changes and sharp corners to prevent fiber slippage; at the same time, the theoretical winding speed is matched with the fiber exit line speed to meet the tension stability requirements.

[0037] To avoid sudden changes in fiber tension caused by robot motion impact, an S-shaped acceleration / deceleration curve is used to set the theoretical winding acceleration. Set a maximum acceleration threshold and control the acceleration to smoothly transition in the initial segment, velocity switching segment and the final segment of the trajectory, so as to ensure that the theoretical velocity change is continuous without sudden changes, and to form complete theoretical control data in conjunction with the theoretical trajectory point set and theoretical winding velocity.

[0038] S200 constructs the trajectory planning objective function and constraints, and substitutes the current entanglement key data into the constraints to determine whether trajectory correction is triggered.

[0039] In some embodiments, constructing the trajectory planning objective function and constraints includes: A trajectory deviation term is constructed based on the offset increment, a tension stability term is constructed based on the tension increment, and a velocity smoothing term is constructed based on the acceleration increment. The trajectory deviation term, tension stability term, and velocity smoothing term are weighted and summed to construct the trajectory planning objective function; Set the maximum offset, the safe tension range, the maximum slip ratio, and the theoretical winding thickness of the workpiece; The following constraints are used: the actual average offset is less than or equal to the maximum offset; the actual fiber tension is within the tension safety range; the actual fiber slip ratio is less than or equal to the maximum slip ratio; and the actual winding thickness is less than or equal to the theoretical winding thickness of the workpiece.

[0040] In some embodiments, the trajectory deviation term is expressed as an offset increment Δ With the core, the trajectory deviation term The expression is , Δ = ,in This is the actual winding offset. This is the preset theoretical winding offset. The square of the Euclidean norm is used to minimize this index, ensuring the overlap between the actual trajectory and the theoretical trajectory and reducing geometric deviation.

[0041] The tension stability term is constructed based on the tension increment ΔT. The expression is ,in The actual fiber tension, This is a preset reference tension; this indicator is used to suppress tension fluctuations and maintain fiber tension stable at the reference tension. nearby.

[0042] The velocity smoothing term uses the acceleration increment ΔA as the variable. The expression is By constraining the magnitude of acceleration changes, sudden changes in robot motion speed are avoided, thus reducing the impact on fiber winding stability.

[0043] The objective function for trajectory planning is obtained by weighted summation of the three indicators. ,in , and This is a weighting coefficient, set according to process requirements, such as when winding large filament bundles. =0.4、 =0.4、 =0.2, prioritizing trajectory accuracy and tension stability.

[0044] Maximum offset Based on fiber specifications, the value for 48K and above large-tow carbon fibers is 0.3-0.8mm; tension safety range. Based on fiber breaking strength settings, such as 0.5-2N; maximum slip ratio. Set to 0.1-0.2 to avoid severe fiber slippage affecting molding quality; theoretical winding thickness of the workpiece. The target value for the total thickness of the multi-layer winding is set according to the product design requirements.

[0045] In some embodiments, substituting the current entanglement key data into the constraint conditions to determine whether trajectory correction is triggered includes: If the actual average offset, actual fiber tension, actual fiber slip ratio, and actual winding thickness all meet the constraint conditions, then it is determined that trajectory correction will not be triggered; otherwise, it is determined that trajectory correction will be triggered.

[0046] In some embodiments, the principle of "pass if all conditions are met" is adopted. The industrial control computer compares the parameters in the order of offset → tension → slip ratio → winding thickness. If all four parameters meet the above constraint criteria, it is determined that trajectory correction is not triggered, and the robot continues to execute the next control cycle motion along the current theoretical trajectory.

[0047] The principle of triggering if any parameter is not satisfied is adopted. If any parameter exceeds the constraint range, it is immediately determined to trigger trajectory correction, the execution of theoretical trajectory is suspended, and the subsequent process of solving multiple constraint objective functions and adjusting trajectory increments is started.

[0048] If any sensor data in the online sensing module is missing, such as a blurry camera image or no feedback from the tension sensor, the corresponding parameter is assumed to not meet the constraint conditions, and trajectory correction is directly triggered. At the same time, the industrial control computer issues a sensor abnormality warning signal to ensure that the winding process does not lead to quality risks due to data failure.

[0049] When trajectory correction is not triggered, the S300 robot performs carbon fiber winding according to the theoretical control data for the next moment.

[0050] In some embodiments, after determining that trajectory correction will not be triggered, the host computer immediately sends the pre-generated theoretical control data for the next control cycle to the robot controller in real time via serial communication, with the data transmission delay controlled within 5ms.

[0051] After receiving the data, the robot controller analyzes the theoretical acceleration according to the S-shaped acceleration and deceleration curve, and drives the end winding tool to move continuously along the theoretical trajectory point set to ensure a smooth transition of movement speed and avoid impacting the fiber. During the movement, it feeds back its own joint position and speed information to the industrial control computer in real time for spatiotemporal matching of subsequent cycle data. The fiber feeding machine maintains a stable output of the current fiber feed line speed to match the robot's theoretical winding speed.

[0052] If the current winding is the i-th layer and is not yet complete, the next control cycle will still use the theoretical control data of the i-th layer; if the i-th layer is completed and the total thickness does not reach the theoretical winding thickness of the workpiece, the theoretical control data of the (i+1)-th layer will be generated after updating the equivalent mandrel based on the average thickness of this layer, and the subsequent operation will be performed according to the new theoretical control data.

[0053] When trajectory correction is triggered, the S400 substitutes the current winding key data into the trajectory planning objective function, solves it through a quadratic programming QP solver, obtains the incremental control data for the next moment, corrects the theoretical control data for the next moment based on the incremental control data for the next moment, and obtains the corrected control data for the next moment. The robot then winds the carbon fiber according to the corrected control data for the next moment.

[0054] In some embodiments, substituting the current entanglement key data into the trajectory planning objective function and solving it using a quadratic programming QP solver to obtain the incremental control data for the next time step includes: Obtain the actual winding offset, actual fiber tension, actual average offset, actual fiber slip ratio, and actual winding thickness from the key winding data at the current moment; Substitute the actual winding offset into the trajectory deviation term, and the actual fiber tension into the tension stability term; Under the constraints, the optimal offset increment, optimal tension increment, and optimal acceleration increment that minimize the objective function of trajectory planning are calculated by a quadratic programming QP solver. The optimal trajectory point increment set is obtained by calculating the trajectory point increment based on the optimal offset increment; the optimal velocity increment is obtained by calculating the velocity increment based on the optimal tension increment. The incremental control data for the next moment consists of the optimal trajectory point increment set, the optimal velocity increment, and the optimal acceleration increment.

[0055] In some embodiments, the actual winding offset is... Substitute the trajectory deviation term Actual fiber tension Substituting the tension stability term Constraints are set according to the process, and the actual average offset is... Maximum offset Actual fiber tension ∈ Tension safety range Actual fiber slip ratio S Maximum slip ratio Actual winding thickness Theoretical winding thickness of the workpiece The objective function of trajectory planning The input constraints are given to the quadratic programming QP solver, and the solution cycle satisfies... ,in To maximize the winding speed, quickly output the objective function for trajectory planning. Minimum optimal offset increment Optimal tension increment Optimal acceleration increment .

[0056] Optimal Trajectory Point Increment Set By using the optimal offset increment The calculations are performed by converting to a spatial coordinate system to ensure accurate deviation compensation for each trajectory point; the optimal velocity increment is obtained. based on and The calculation yielded that, This refers to the actual fiber output speed. This refers to the actual winding speed. , This is a speed correction coefficient, used to achieve synchronized matching between tension and speed.

[0057] The calculated optimal trajectory point increment set Optimal speed increment Optimal acceleration increment The data is packaged according to the control cycle sequence to form incremental control data for the next moment, ensuring that the robot can directly call it for trajectory correction.

[0058] In some embodiments, the step of correcting the theoretical control data for the next time step based on the incremental control data for the next time step to obtain the corrected control data for the next time step includes: Obtain the optimal trajectory point increment set, optimal velocity increment, and optimal acceleration increment from the incremental control data at the next moment; The theoretical trajectory point set is corrected by modifying the optimal trajectory point increment set to obtain the corrected trajectory point set; The corrected winding speed is obtained by correcting the theoretical winding speed using the optimal speed increment; The corrected winding acceleration is obtained by correcting the theoretical winding acceleration using the optimal acceleration increment; The correction control data for the next moment consists of the correction trajectory point set, the correction winding speed, and the correction winding acceleration.

[0059] In some embodiments, based on the optimal trajectory point increment set, the theoretical trajectory point set is spatially corrected point by point, and for each theoretical trajectory point P... theory_i The corresponding offset increment Δδ is superimposed along the normal vector direction of the theoretical trajectory at that point. i The corrected trajectory point P is obtained. correct_i After point-by-point correction, a complete set of corrected trajectory points P is formed. correct Based on the optimal velocity increment ΔV, the theoretical winding velocity V is... theory A linear correction is performed, and the correction formula is: V correct =V theory +ΔV,V correct To correct the winding speed, based on the optimal acceleration increment ΔA, the theoretical winding acceleration A is adjusted. theory Make corrections, the correction formula is: A correct =A theory +ΔA,A correct To correct for winding acceleration.

[0060] The robot controller receives the next moment's correction control data via serial communication, including the correction trajectory point set, correction winding speed, and correction winding acceleration; it parses the data into a robot-adaptive format and aligns it with the time stamp to ensure that the data accurately matches the current control cycle.

[0061] The controller uses a cubic B-spline interpolation algorithm based on the corrected trajectory point set to generate a continuous and smooth motion trajectory, avoiding abrupt changes between trajectory points; combined with the corrected winding acceleration planning S-shaped acceleration and deceleration curve, the corrected winding speed transitions smoothly from the current speed without impact fluctuations.

[0062] The robot's end-effector winding tool moves along the corrected trajectory after interpolation, and the joint position and speed are fed back to the controller in real time. The motion accuracy is adjusted in a closed loop to ensure that the deviation between the actual trajectory and the corrected trajectory point set is ≤0.1mm.

[0063] The fiber feeding machine adjusts the output speed of the yarn in real time according to the correction winding speed to ensure that the output speed matches the correction winding speed; the tension sensor continuously monitors the actual tension, and if it deviates from the safe tension range, it helps to stabilize the tension by fine-tuning the output speed.

[0064] Reference Figure 2 This invention provides a robot carbon fiber winding trajectory planning device 20 for implementing a robot carbon fiber winding trajectory planning method. The device includes: The data acquisition module 21 is used to collect key entanglement data at the current moment through the robot's online sensing system and generate theoretical control data for the next moment through the geodesic algorithm. The correction judgment module 22 is used to construct the trajectory planning objective function and constraints, and substitute the current entanglement key data into the constraints to determine whether trajectory correction is triggered. Theoretical control module 23 is used to allow the robot to wind carbon fiber according to the theoretical control data of the next moment when trajectory correction is not triggered. The trajectory correction module 24 is used to substitute the current winding key data into the trajectory planning objective function when trajectory correction is triggered, solve it through a quadratic programming QP solver, obtain the incremental control data for the next moment, correct the theoretical control data for the next moment based on the incremental control data for the next moment, obtain the corrected control data for the next moment, and the robot winds the carbon fiber according to the corrected control data for the next moment.

[0065] This application provides an electronic device, including a processor and a memory; the memory stores a computer program, wherein the computer program, when executed by the processor, implements the robot carbon fiber winding trajectory planning method of any of the above schemes.

[0066] Specifically, the processor may include, for example, a general-purpose microprocessor, an instruction set processor and / or an associated chipset and / or a special-purpose microprocessor (e.g., an application-specific integrated circuit (ASIC)), etc. The processor may also include onboard memory for caching purposes. The processor may be a single processing unit or multiple processing units for performing different actions of the method flow according to embodiments of this application.

[0067] Memory can be any medium capable of containing, storing, transmitting, propagating, or transmitting instructions. For example, memory can include, but is not limited to, electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices, instruments, or propagation media. Specific examples of memory include: magnetic storage devices such as magnetic tape or hard disk drives (HDDs); optical storage devices such as optical discs (CD-ROMs); and also random access memory (RAM) or flash memory; and / or wired / wireless communication links.

[0068] This application also provides a computer-readable medium storing a computer program that, when executed by a processor, implements the robot carbon fiber winding trajectory planning method of any of the above-described schemes. This computer-readable medium may be included in the device / apparatus / system described in the above embodiments; or it may exist independently and not assembled into the device / apparatus / system. The aforementioned computer-readable medium carries one or more programs, which, when executed, implement the method as described in the embodiments of this application.

[0069] According to embodiments of this application, a computer-readable medium may be a computer-readable signal medium or a computer-readable storage medium, or any combination thereof. A computer-readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of a computer-readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination thereof. In this application, a computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, apparatus, or device. In this application, a computer-readable signal medium may include a data signal propagated in baseband or as part of a carrier wave, carrying computer-readable program code. Such propagated data signals may take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. Computer-readable signal media can also be any computer-readable medium other than computer-readable storage media, which can send, propagate, or transmit a program for use by or in connection with an instruction execution system, apparatus, or device. The program code contained on the computer-readable medium can be transmitted using any suitable medium, including but not limited to: wireless, wired, optical fiber, radio frequency signals, etc., or any suitable combination thereof.

[0070] Those skilled in the art will understand that the features described in the various embodiments and / or claims of this application can be combined and / or combined in various ways, even if such combinations or combinations are not explicitly described in this application. In particular, the features described in the various embodiments and / or claims of this application can be combined and / or combined in various ways without departing from the spirit and teachings of this application. All such combinations and / or combinations fall within the scope of this application. Therefore, the scope of this application should not be limited to the above embodiments, but should be defined not only by the appended claims, but also by their equivalents. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the protection scope of this application.

Claims

1. A method for planning the trajectory of carbon fiber winding in a robot, characterized in that, include: The robot's online sensing system collects key entanglement data at the current moment, and the geodesic algorithm generates theoretical control data for the next moment. Construct the objective function and constraints for trajectory planning, and substitute the current entanglement key data into the constraints to determine whether trajectory correction is triggered. When trajectory correction is not triggered, the robot performs carbon fiber winding according to the theoretical control data for the next moment; When trajectory correction is triggered, the current winding key data is substituted into the trajectory planning objective function and solved by a quadratic programming QP solver to obtain the incremental control data for the next moment. The theoretical control data for the next moment is corrected based on the incremental control data for the next moment to obtain the corrected control data for the next moment. The robot winds the carbon fiber according to the corrected control data for the next moment.

2. The robot carbon fiber winding trajectory planning method according to claim 1, characterized in that, The online sensing system includes a tension sensor, a line laser profile scanner, a high-resolution industrial camera, and a speed sensor. The robot's online sensing system collects key entanglement data at the current moment, including: The actual fiber tension is collected in real time by a tension sensor, the point cloud data of the winding profile is collected in real time by a line laser profile scanner, the image of the winding area is collected in real time by a high-resolution industrial camera, and the actual fiber output speed is collected in real time by a speed sensor. The actual winding thickness is obtained by performing coordinate transformation and thickness extraction on the point cloud data of the winding profile. Trajectory points are extracted from the point cloud data of the winding profile and the image of the winding area to obtain the actual trajectory point set; The actual winding speed, actual winding offset, actual average offset, and actual fiber slip ratio are calculated based on the actual trajectory point set. The actual trajectory point set, actual winding thickness, actual fiber tension, actual fiber exit speed, actual winding speed, actual winding offset, actual average offset, and actual fiber slip ratio at the current moment constitute the key winding data at the current moment.

3. The robot carbon fiber winding trajectory planning method according to claim 1, characterized in that, The theoretical control data includes the theoretical trajectory point set, theoretical winding speed, and theoretical winding acceleration.

4. The robot carbon fiber winding trajectory planning method according to claim 2, characterized in that, The objective function and constraints for trajectory planning include: A trajectory deviation term is constructed based on the offset increment, a tension stability term is constructed based on the tension increment, and a velocity smoothing term is constructed based on the acceleration increment. The trajectory deviation term, tension stability term, and velocity smoothing term are weighted and summed to construct the trajectory planning objective function; Set the maximum offset, the safe tension range, the maximum slip ratio, and the theoretical winding thickness of the workpiece; The following constraints are used: the actual average offset is less than or equal to the maximum offset; the actual fiber tension is within the tension safety range; the actual fiber slip ratio is less than or equal to the maximum slip ratio; and the actual winding thickness is less than or equal to the theoretical winding thickness of the workpiece.

5. The robot carbon fiber winding trajectory planning method according to claim 4, characterized in that, The step of substituting the current key entanglement data into the constraint conditions to determine whether trajectory correction is triggered includes: If the actual average offset, actual fiber tension, actual fiber slip ratio, and actual winding thickness all meet the constraint conditions, then it is determined that trajectory correction will not be triggered; otherwise, it is determined that trajectory correction will be triggered.

6. The robot carbon fiber winding trajectory planning method according to claim 4, characterized in that, The step of substituting the current entanglement key data into the trajectory planning objective function and solving it through a quadratic programming QP solver to obtain the incremental control data for the next time step includes: Obtain the actual winding offset, actual fiber tension, actual average offset, actual fiber slip ratio, and actual winding thickness from the key winding data at the current moment; Substitute the actual winding offset into the trajectory deviation term, and the actual fiber tension into the tension stability term; Under the constraints, the optimal offset increment, optimal tension increment, and optimal acceleration increment that minimize the objective function of trajectory planning are calculated by a quadratic programming QP solver. The optimal trajectory point increment set is obtained by calculating the trajectory point increment based on the optimal offset increment; the optimal velocity increment is obtained by calculating the velocity increment based on the optimal tension increment. The incremental control data for the next moment consists of the optimal trajectory point increment set, the optimal velocity increment, and the optimal acceleration increment.

7. The robot carbon fiber winding trajectory planning method according to claim 3, characterized in that, The step of correcting the theoretical control data for the next time step based on the incremental control data for the next time step to obtain the corrected control data for the next time step includes: Obtain the optimal trajectory point increment set, optimal velocity increment, and optimal acceleration increment from the incremental control data at the next moment; The theoretical trajectory point set is corrected by modifying the optimal trajectory point increment set to obtain the corrected trajectory point set; The corrected winding speed is obtained by correcting the theoretical winding speed using the optimal speed increment; The corrected winding acceleration is obtained by correcting the theoretical winding acceleration using the optimal acceleration increment; The correction control data for the next moment consists of the correction trajectory point set, the correction winding speed, and the correction winding acceleration.

8. A robot carbon fiber winding trajectory planning device, used to implement the robot carbon fiber winding trajectory planning method as described in any one of claims 1 to 7, characterized in that, The device includes: The data acquisition module is used to collect key entanglement data at the current moment through the robot's online sensing system, and to generate theoretical control data for the next moment through geodesic algorithms; The correction judgment module is used to construct the trajectory planning objective function and constraints, and substitute the current entanglement key data into the constraints to determine whether trajectory correction is triggered. The theoretical control module is used to ensure that the robot winds carbon fiber according to the theoretical control data for the next moment when trajectory correction is not triggered. The trajectory correction module is used to substitute the current winding key data into the trajectory planning objective function when trajectory correction is triggered. The objective function is solved by a quadratic programming QP solver to obtain the incremental control data for the next moment. The theoretical control data for the next moment is corrected based on the incremental control data for the next moment to obtain the corrected control data for the next moment. The robot winds the carbon fiber according to the corrected control data for the next moment.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the program, it implements the robot carbon fiber winding trajectory planning method as described in any one of claims 1 to 7.

10. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the robot carbon fiber winding trajectory planning method as described in any one of claims 1 to 7.

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