A robot mirroring processing track planning method of a double-robot shot blasting device

Abstract

The present application relates to the technical field of robot collaborative processing, and more particularly to a robot mirror image processing trajectory planning method of a double-robot shot peening device, which comprises: discretely sampling a workpiece surface to form a trajectory point and calculating an effective topological energy receiving rate; constructing a shot peening jet volume energy field model containing a kinetic energy flux density function and a jet aerodynamic interference boundary model; calculating a reference energy flux of a master robot using the kinetic energy flux density function and the effective topological energy receiving rate, and establishing an energy flux topological balance equation that constrains the effective energy flux of a slave robot to be equal to the reference energy flux; solving a target state of the slave robot based on the equation, executing time-domain sliding mode avoidance if aerodynamic interference is detected based on the jet aerodynamic interference boundary model, and executing cross-parameter substitution compensation if kinematic singularity is detected. The present application realizes equivalent strengthening processing on asymmetric curved surfaces through physical-level energy topological balance.

Description

Technical Field

[0001] This invention relates to the field of robotic collaborative machining technology. More specifically, this invention relates to a method for planning the robotic mirror machining trajectory of a dual-robot shot peening equipment. Background Technology

[0002] In the aerospace and high-end equipment manufacturing fields, dual-robot mirror shot peening has become a key process for surface strengthening of large, complex, curved, thin-walled components such as wing panels and integral frame beams. The core logic of this process is to use two robots to synchronously follow the shot peening in spatially mirrored positions on both sides of the workpiece. The impact forces generated by the jets from both sides cancel each other out inside the workpiece, thus preventing macroscopic bending or torsional deformation of the thin-walled component due to unilateral stress. Currently, mainstream trajectory planning methods generally adopt a geometric position mirroring strategy. This involves directly generating the target trajectory of the slave robot from the tool coordinate system of the master robot through a mirror matrix transformation based on the workpiece's CAD model, attempting to achieve mechanical balance through geometric symmetry.

[0003] However, in practical engineering applications, existing planning methods based on pure geometric mirroring have serious limitations when dealing with components with varying curvatures. First, geometric symmetry does not equate to energy symmetry. Large, skin-like workpieces often exhibit asymmetrical curvature characteristics; for example, the leading edge of an airfoil may have a convex surface on one side and a gently concave surface on the other. According to the principles of gas jet dynamics, a convex structure causes the jet to diverge upon impact, resulting in a decrease in the effective kinetic energy flux per unit area; while a concave structure focuses the jet, leading to an increase in local energy density. If only geometric symmetry is maintained, the actual surface strengthening energy received on both sides of the workpiece will differ significantly. This microscopic energy imbalance, upon accumulation, leads to an asymmetry in the residual stress field within the workpiece, ultimately causing springback deformation after tooling removal, failing to meet high-precision forming requirements.

[0004] Secondly, existing planning algorithms lack the ability to dynamically perceive aerodynamic flow field disturbances. Shot peening jets are not ideal rays, but rather conical flow fields accompanied by high-pressure turbulent entrainment effects. When dual robots process workpiece edges, holes, or narrow cavities, although the robot arms do not collide, the high-speed airflow fields on both sides may converge and interfere spatially. This aerodynamic interference can disrupt the stability of the jet, leading to insufficient shot peening coverage or uncontrollable turbulence. Geometric coordinate-based planning methods cannot identify such conflicts at the physical boundaries of the flow field.

[0005] Furthermore, kinematic singularities are a rigid constraint limiting collaborative operations between two robots. When tracking complex curved surfaces, in order to forcibly satisfy geometric mirror relationships, the robot is often forced into extreme joint positions or singular pose regions. Under current technology, once a singularity is encountered, it can usually only be avoided by stopping processing or deviating from the predetermined path. This directly leads to discontinuities in processing or missed areas, severely affecting surface integrity. Summary of the Invention

[0006] To address the problems of energy reception imbalance, aerodynamic interference, and kinematic singularity limitations caused by the reliance on geometric mirroring in existing technologies, this invention proposes a robot mirroring machining trajectory planning method for a dual-robot shot peening equipment. This method includes the following steps:

[0007] The workpiece surface is discretized and sampled to form a series of trajectory points. The effective topological energy receiving rate is calculated by combining the curvature and angular characteristics of the trajectory points.

[0008] Construct a volumetric energy field model for a shot peening jet that includes the kinetic flux density function and the aerodynamic disturbance boundary model of the jet;

[0009] The reference energy flux of the main robot is calculated using the kinetic energy flux density function and the effective topological energy receiving rate, and an energy flux topological balance equation is established. The energy flux topological balance equation constrains the effective energy flux of the slave robot to be equal to the reference energy flux.

[0010] Based on the energy flux topological balance equation, the target state of the robot is solved in reverse. If regional overlap is detected based on the jet aerodynamic interference boundary model, the time-domain sliding mode avoidance strategy is activated to calculate the execution lag time. If the robot is detected to be in the kinematic singular domain, the cross-parameter substitution compensation strategy is activated to calculate the compensation amount of non-geometric process parameters.

[0011] Based on the control command stream generated from the target state of the robot, the two robots work together to achieve consistency in the effective impact kinetic energy flux on both sides of the workpiece.

[0012] This invention breaks away from the traditional misconception of geometric symmetry, i.e. stress symmetry, in terms of physical essence. By introducing a reference energy flux as a unified dimension, it directly solves the problem of energy reception imbalance caused by heterogeneous surfaces at the trajectory planning level. At the same time, the integrated interference avoidance and singularity compensation mechanism ensures the continuity and stability of dual robots in complex and constrained environments.

[0013] Preferably, the formula for calculating the kinetic energy flux density function is:

[0014]

[0015] In the formula, The index number of the trajectory point. Indicates the first The kinetic flux density values ​​at each trajectory point. Indicates the first The radial distance values ​​of each trajectory point from the central axis of the jet. Indicates the corresponding to the first The effective divergence radius of the jet beam at the target distance of each trajectory point. This represents the energy transfer efficiency coefficient. This indicates the shot peening air pressure value. This represents the mass flow rate of the projectile. This indicates the numerical value of high-pressure air density.

[0016] This invention no longer simplifies the jet as a homogeneous ray, but models it as a volumetric energy field conforming to a Gaussian distribution. It accurately quantifies the nonlinear decay law of energy density with respect to target distance and radial distance, providing an aerodynamic model benchmark for subsequent accurate energy balance calculations.

[0017] Preferably, the formula for calculating the effective topological energy receiver rate is:

[0018]

[0019] In the formula, Indicates the first Effective topological energy receiver rate of each trajectory point Indicates the first The jet impact angle value at each trajectory point Indicates the first The average principal curvature value of each trajectory point. Indicates the first The Gaussian curvature values ​​of each trajectory point Indicates the first The target distance value corresponding to each trajectory point.

[0020] This invention establishes a mapping relationship between the microscopic geometric features of a workpiece and its macroscopic physical energy, which can automatically identify the divergence loss caused by convex surfaces and the convergence gain caused by concave surfaces. It is the core calibration parameter for realizing physical-level mirror machining.

[0021] Preferably, the establishment of the energy flux topological balance equation specifically involves:

[0022] The energy flux function is obtained by multiplying the kinetic energy flux density function by the effective topological energy receiving rate. The energy flux of the main robot is calculated using the energy flux function and recorded as the reference energy flux.

[0023] The energy flux of the slave robot is set to be equal to the reference energy flux, thereby establishing an equation that includes the geometric position variables and process parameter variables of the slave robot as the energy flux topological balance equation.

[0024] This invention transforms the abstract requirements of mirror processing technology into mathematically reversible constraint equations, enabling the system to maintain a dynamic balance of energy input by adjusting other variables even when the geometric position cannot be strictly symmetrical.

[0025] Preferably, the jet aerodynamic interference boundary model defines an interference radius that expands with increasing target distance;

[0026] The detection based on the jet aerodynamic interference boundary model includes: calculating the Euclidean distance between the target point of the master robot and the target point of the slave robot, and comparing the Euclidean distance with the sum of the interference radii of the master and slave robots determined based on the jet aerodynamic interference boundary model. If the distance is less than the sum of the interference radii, it is determined that there is aerodynamic interference risk, and the time-domain sliding mode avoidance strategy is triggered.

[0027] Preferably, the temporal sliding mode avoidance strategy is as follows:

[0028] Keep the spatial path coordinates of the robot unchanged;

[0029] The minimum time difference required to offset the interference areas of the master and slave robots on the time axis is calculated, and this minimum time difference is superimposed on the timestamp of the slave robot as the execution lag time, thereby realizing a processing mode with spatial overlap but temporal separation.

[0030] This invention utilizes the dimension of time to resolve spatial conflicts, achieving physical isolation of the flow field through microsecond-level time misalignment without altering the shot peening coverage path.

[0031] Preferably, the cross-parameter substitution compensation strategy utilizes the energy sensitivity matrix to convert geometric position errors into compensation amounts for non-geometric process parameters. The calculation formula for the energy sensitivity matrix is ​​as follows:

[0032]

[0033] In the formula, To use robots to target the first Initial air pressure and flow rate values ​​for each trajectory point; To correspond to the target distance of the safety boundary The effective divergence radius of the jet at that location; For the first The energy sensitivity matrix of each trajectory point.

[0034] Preferably, the step of activating a cross-parameter substitution compensation strategy to calculate the compensation amount for non-geometric process parameters if the robot is detected to be in a kinematically singular domain specifically includes:

[0035] Calculate the condition number of the Jacobian matrix of the target pose of the robot and determine whether the condition number exceeds a preset safety threshold. If so, determine that the robot is in a kinematic singular domain and lock the geometric position of the robot at a safe boundary.

[0036] Calculate the difference between the actual energy flux caused by the locked position and the reference energy flux, i.e., the energy deficit; use the pseudo-inverse matrix of the energy sensitivity matrix to map the energy deficit to the shot peening mass flow rate increment and shot peening pressure increment of the robot, the shot peening mass flow rate increment and shot peening pressure increment are called the compensation amount of non-geometric process parameters.

[0037] This invention implements a control logic that compensates for energy loss caused by excessive distance or angular deviation when the robot cannot reach the ideal geometric position due to mechanical structural limitations. This greatly expands the robot's operational capabilities.

[0038] Preferably, the method further includes performing surface integrity constraints, specifically:

[0039] Predict the surface roughness value after a single impact based on contact mechanics theory;

[0040] If the surface roughness value exceeds the preset process allowable upper limit, the single high energy density scan trajectory will be broken down into multiple low energy density reciprocating scan trajectories, and the scan speed will be replanned while keeping the total cumulative energy flux unchanged.

[0041] Preferably, the method further includes performing data preprocessing:

[0042] Before trajectory planning, the original point cloud data of the workpiece surface is obtained using a 3D laser scanner;

[0043] The original point cloud data is denoised and smoothed, and the normal vector, principal curvature and Gaussian curvature of each discrete point are calculated based on the processed point cloud data.

[0044] The present invention has the following beneficial effects:

[0045] This invention accurately describes the different response characteristics of heterogeneous curved surfaces to jet energy by constructing a kinetic energy flux density function and an effective topological energy receiving rate model. By solving the energy flux topological balance equation, the target distance or process parameters from the robot can be dynamically adjusted according to the local curvature, ensuring that the effective strengthening energy received by both sides of the workpiece is strictly consistent, fundamentally eliminating the hidden danger of torsional deformation of large thin-walled parts caused by uneven stress input.

[0046] Furthermore, addressing the challenge of robots easily getting stuck in unusual postures during complex surface machining, this invention proposes a cross-parameter substitution compensation strategy based on an energy sensitivity matrix. When the robot cannot reach the ideal geometric position due to mechanical limitations, the algorithm can automatically calculate the energy deficit and map it as a compensation increment for air pressure or flow rate. This control logic for compensating for space constraints enables the dual-robot system to maintain high-quality operational capabilities even in confined spaces close to joint limits.

[0047] Furthermore, by introducing a jet aerodynamic interference boundary model and combining it with a time-domain sliding mode avoidance strategy, this invention can stagger the turbulent fields of the dual-jet streams in time through high-precision time-axis sliding mode control without changing the spatial processing path. This avoids shot peening intensity fluctuations caused by flow field interference and ensures the spatial continuity and integrity of the processing trajectory. Attached Figure Description

[0048] Figure 1 This is a flowchart illustrating the steps of a robot mirror processing trajectory planning method for a dual-robot shot peening equipment according to an embodiment of the present invention.

[0049] Figure 2 This is a comparison chart of adaptive adjustment of robot processing trajectory provided in an embodiment of the present invention. Detailed Implementation

[0050] Please see Figure 1 The diagram illustrates a flowchart of the robot mirror machining trajectory planning method for a dual-robot shot peening equipment provided in Embodiment 1. The method includes the following steps:

[0051] S1: Discretize the workpiece surface to form a series of trajectory points, and calculate the effective topological energy receiving rate by combining the curvature and angular characteristics of the trajectory points.

[0052] It should be noted that large, thin-walled aerospace components typically possess complex freeform surface features, such as the sharp curvature of the wing leading edge or the gentle transition at the wing root. This difference in geometry means that the energy reflection and absorption efficiencies vary drastically depending on where the jet strikes. Ignoring these topological differences and processing solely based on consistent geometric distances will lead to excessive energy dissipation at protruding areas and excessive energy accumulation at recessed areas, easily causing the workpiece to twist and deform after removal from the fixture. Therefore, the primary task of this step is to achieve digital feature extraction of the workpiece surface.

[0053] Preferably, as an example, the workpiece surface is discretized and sampled to form a series of trajectory points. The effective topological energy receiver rate is calculated by combining the curvature and angular characteristics of the trajectory points, including:

[0054] First, data acquisition and preprocessing are performed. Specifically, a high-precision 3D laser scanner is used to perform a full-field scan of the workpiece surface to obtain raw point cloud data. Since the raw point cloud data may contain noise caused by ambient light reflection, it is filtered for noise reduction and smoothed using Laplacian smoothing. Based on the processed clean point cloud data, a differential geometry algorithm is used to calculate the normal vector, principal curvature, and Gaussian curvature of each data point.

[0055] Next, the processed clean point cloud data is discretized and sampled to form a series of ordered trajectory points.

[0056] Finally, for each trajectory point, its effective topological energy receiver rate is calculated using the following formula:

[0057]

[0058] In the formula, Indicates the first Effective topological energy reception rate of each trajectory point; Indicates the first The jet impact angle value at each trajectory point; Indicates the first The average principal curvature value of each trajectory point; Indicates the first The Gaussian curvature values ​​of each trajectory point; Indicates the first The target distance value corresponding to each trajectory point.

[0059] It is understandable that when the workpiece surface is convex, It is a positive value, and as the convexity increases, As the value increases, the denominator term The value will be significantly greater than 1 and will increase accordingly, which will lead to a calculated reception rate. The reduction means that the convex structure accelerates the spatial dispersion of jet energy, resulting in a decrease in the proportion of energy actually intercepted per unit area.

[0060] When the workpiece surface is concave The value is negative, and it increases with concavity. As the absolute value increases, the value of the denominator will be less than 1, resulting in a decrease in the reception rate. This means that the concave structure creates a focusing and converging effect on the jet beam, leading to a superposition enhancement of local energy density.

[0061] when Increase, that is, when the jet is more tilted, the molecular term Decrease leads to reduced receiver rate The decrease indicates a loss of energy in the vertical component.

[0062] The above processing can automatically describe the risks of geometric symmetry but energy asymmetry, providing a data foundation for subsequent accurate compensation.

[0063] S2: Construct a volumetric energy field model for the shot peening jet that includes the kinetic flux density function and the jet aerodynamic disturbance boundary model.

[0064] It should be noted that in traditional dual-robot trajectory planning, the shot peening jet is often simplified into a geometric ray with no thickness, ignoring the volumetric effect and non-uniform energy distribution of the jet itself. This simplification means that the system cannot detect energy attenuation at the edge of the jet beam, nor can it predict the aerodynamic interference between the two jets in space. If conventional methods are used, it is very easy to lead to insufficient reinforcement in the edge region of the workpiece, or turbulent collision between the two jets in narrow areas, causing processing instability. Therefore, in order to solve the above-mentioned hidden dangers, it is necessary to introduce a volumetric energy field model based on the physical flow field.

[0065] Preferably, as an example, a shot peening jet volumetric energy field model is constructed, including the kinetic flux density function and the jet aerodynamic disturbance boundary model, comprising:

[0066] Using shot peening process parameters as input, a kinetic energy flux density function is constructed using aerodynamic principles. This kinetic energy flux density function satisfies the following relationship:

[0067]

[0068] In the formula, Indicates the first The kinetic energy flux density at each trajectory point; Indicates the energy transfer efficiency coefficient; This indicates the shot peening air pressure value of the robot. This represents the mass flow rate of the robot's projectiles. This indicates the numerical value of high-pressure air density; Indicates the corresponding to the first The effective divergence radius of the jet beam is the value of the target distance at each trajectory point. Indicates the first The radial distance of each trajectory point from the central axis of the jet is 0 during centering machining; Pi is a constant. It is a natural exponential function.

[0069] Understandably, when the target distance... As the volume increases, the jet beam widens, leading to Increase, thus increasing the denominator term It will increase exponentially, thus affecting the overall score. This significantly reduces the energy density, thus effectively describing the diffusion phenomenon where energy becomes increasingly scarce over greater distances.

[0070] when Increase, that is, when the sampling point deviates from the center of the jet, the numerator in the exponential term increases. To become a negative number with a larger absolute value, The function value drops sharply and approaches 0, thus effectively describing the Gaussian distribution characteristics where energy is mainly concentrated in the jet center and the edge energy decays rapidly.

[0071] Furthermore, in order to define the flow field disturbance, it is also necessary to define the jet aerodynamic disturbance boundary model, specifically: for the first... A trajectory point, defining its interference radius. satisfy: ,in is the turbulence expansion coefficient.

[0072] The volumetric energy field model of the shot peening jet is constructed by combining the volumetric energy field model of the shot peening jet and the kinetic energy flux density function.

[0073] S3: Calculate the reference energy flux of the master robot using the kinetic energy flux density function and the effective topological energy receiving rate, and establish an energy flux topological balance equation. The energy flux topological balance equation constrains the effective energy flux of the slave robot to be equal to the reference energy flux.

[0074] It's important to note that the core objective of dual-machine mirror machining is mechanical equilibrium. In heterogeneous surface scenarios, the master robot's operating state is fixed. However, if the slave robot simply replicates the master robot's geometric parameters, the different curvatures on both sides will lead to an imbalance in the actual input stress fields. To achieve physical equilibrium, it's essential to first determine how much effective energy the master robot is delivering.

[0075] Preferably, as an example, the reference energy flux of the main robot is calculated using the kinetic energy flux density function and the effective topological energy receiving rate, and an energy flux topological balance equation is established. This energy flux topological balance equation constrains the effective energy flux of the slave robot to be equal to the reference energy flux, including:

[0076] First, the product of the effective topological energy receiving rate and the kinetic energy flux density function is used as the energy flux function;

[0077] Because the master and slave robots operate synchronously, when the slave robot plans the... When the main robot is at the nth trajectory point, it is positioned on the surface of the workpiece. One main trajectory point.

[0078] Next, the process parameters of the main robot will be... Geometric features of the main trajectory points Substituting into the energy flux function, the baseline energy flux of the main robot at the i-th trajectory point is calculated as follows:

[0079]

[0080] In the formula, The main robot in the The baseline energy flux value for each trajectory point. These are the preset shot peening air pressure data and preset shot peening mass flow rate values ​​of the main robot, respectively. The shot peening air pressure value and shot peening mass flow rate are set values ​​in the process controller. The main robot in the The target distance value corresponding to each trajectory point is obtained by using an existing robot offline programming algorithm, taking the coordinates and normal vectors of point cloud data as the processing objects, and performing geometric offset calculation along the normal direction based on the preset shot peening process standard operating distance. The main robot in the The effective divergence radius of the jet beam is a numerical value of the target distance of each trajectory point. The effective divergence radius of the jet beam is obtained by simulating the diameter of the jet impact area of ​​a specific type of nozzle at different target distances using existing fluid dynamics simulation software, and calculating it based on the linear regression equation of jet diffusion fitted from the simulation data. The main robot in the The jet impact angle value at each trajectory point is determined by the angle between the axis and the normal obtained from the robot's inverse kinematics. The first and second parts of the machining surface corresponding to the main robot are respectively the first and second parts of the machining surface. The average principal curvature and Gaussian curvature values ​​of the trajectory points.

[0081] Subsequently, an energy flux topological balance equation will be constructed based on the fact that the robot's effective energy flux equals the baseline energy flux value, specifically:

[0082]

[0083] In the formula, The solutions to be found are the robot's solutions for the first... The values ​​of shot peening air pressure and shot peening mass flow rate at each trajectory point; For the solution to be found, the robot is targeting the first... The target distance value of each trajectory point; To use robots to target the first The effective divergence radius of the jet beam is the value of the target distance at each trajectory point, and the effective divergence radius of the jet beam varies with... The method for determining the variation is the same as the method for determining the effective divergence radius of the jet beam of the main robot; To use robots to target the first The jet impact angle values ​​for each trajectory point are determined using the same method as that used for the main robot. These are the first and second views of the workpiece surface facing the robot. The values ​​of the average principal curvature and Gaussian curvature of the trajectory points; The main robot in the The baseline energy flux value for each trajectory point.

[0084] Understandably, assuming the slave robot is processing a deeply concave region, its acceptance rate will significantly increase according to the aforementioned logic. In this case, if the slave robot uses the same parameters as the master robot, the product on the left side of the equation will be much greater than the product on the right side. This leads to over-peening. To maintain the equation, the equation requires a reduction in the robot's original energy intensity value. By solving in reverse, the system automatically derives instructions to reduce air pressure, shot peening mass flow rate, or increase target distance.

[0085] In summary, this method can automatically deduce the required compensation action based on the local shape differences of the workpiece, thereby ensuring that the effective energy injected into the material remains constant regardless of the shape of the workpiece.

[0086] S4: Based on the energy flux topological balance equation, the target state of the robot is solved in reverse. In the solution, the detection is performed based on the jet aerodynamic interference boundary model. If regional overlap is detected, the time-domain sliding mode avoidance strategy is activated to calculate the execution lag time. If the robot is detected to be in the kinematic singular domain, the cross-parameter substitution compensation strategy is activated to calculate the compensation amount of non-geometric process parameters.

[0087] Preferably, as an example, the target state of the robot is solved in reverse based on the energy flux topological balance equation. During the solution process, detection is performed based on the jet aerodynamic disturbance boundary model. If regional overlap is detected, a time-domain sliding mode avoidance strategy is activated to calculate the execution lag time. If the robot is detected to be in a kinematically singular domain, a cross-parameter substitution compensation strategy is activated to calculate the compensation amount for non-geometric process parameters, including:

[0088] Numerical optimization algorithms, such as the Newton-Raphson iterative method, are used to solve the topological balance equations of energy flux. This is particularly relevant for the first... During the process of solving for each trajectory point, the system executes the following two detection and correction strategies in parallel:

[0089] 1. Aerodynamic interference detection and time-domain sliding mode avoidance strategy.

[0090] Computation of the main robot and its second The TCP position corresponding to the trajectory point and the relationship between the robot and its first... Euclidean distance between the TCP positions corresponding to each trajectory point .

[0091] Simultaneously, based on the aforementioned jet aerodynamic interference boundary model, the master and slave robots were calculated respectively in the [missing information - likely a specific phase or time period]. Interference radius at each trajectory point and .

[0092] like Then determine the first There is a risk of aerodynamic interference at each trajectory point.

[0093] At this point, the system activates the time-domain sliding mode avoidance strategy and calculates the execution lag time. And add that time to the time from the robot's first... Timestamp of each trajectory point This enables a processing mode that overlaps spatially but separates temporally.

[0094] It is understandable that when the distance When the distance is less than a threshold, it indicates that the physical distance between the two robots is too close in space. A time lag is then introduced to address this. This allows for the elimination of processing interference through temporal misalignment when spaces overlap.

[0095] 2. Kinematic singularity detection and cross-parameter substitution compensation strategy: substitution compensation.

[0096] In solving the problem from the robot's perspective on the first... Target distance of each trajectory point If the calculated geometric pose causes the condition number of the Jacobian matrix of the robot to exceed a preset safety threshold, then the robot is determined to be in a kinematically singular domain. For example, the safety threshold is taken as... .

[0097] At this point, the robot's target distance will be forcibly locked at the safe boundary target distance. place, This represents the maximum non-singular distance that the robotic arm can reach in this posture.

[0098] because Forced to be fixed as This leads to the actual energy flux calculated by the equation. Less than the benchmark value This results in an energy deficit. .

[0099] To eliminate this loss, a cross-parameter substitution compensation strategy is initiated, using the energy sensitivity matrix to calculate the compensation amount from the robot's process parameters. The specific calculation method is as follows:

[0100]

[0101] Among them, the The relationship between the energy sensitivity matrix of each trajectory point is:

[0102]

[0103] In the formula, In order to target the Each trajectory point needs to be compensated for the incremental value of the shot peening air pressure from the robot; In order to target the Each trajectory point needs to be compensated for the incremental value of the shot peening mass flow rate from the robot; For matrix The pseudo-inverse matrix is ​​used to calculate the optimal compensation solution; For the first The energy loss value at each trajectory point; To use robots to target the first Initial air pressure and flow rate values ​​for each trajectory point; To correspond to the target distance of the safety boundary The effective divergence radius of the jet at that location, For the first The energy sensitivity matrix of each trajectory point; the elements in the first row of the matrix represent the partial derivatives of kinetic flux density with respect to air pressure; the elements in the second row of the matrix represent the partial derivatives of kinetic flux density with respect to flow rate. , These are collectively referred to as compensation amounts for non-geometric process parameters.

[0104] It is understandable that when a robot is forced to stop at a safe, distant location due to exotic limitations... At that time, the jet divergence radius Increases, causing the matrix to A smaller element value indicates decreased sensitivity, meaning a weaker energy gain per unit pressure. This is achieved using pseudo-inverse... During the calculation, a relatively large pressure increment will be automatically calculated. This means that the greater the distance, the lower the sensitivity, and the greater the air pressure required for system compensation. This logic precisely ensures that even if the robot cannot reach the ideal position, sufficient energy can be delivered to the workpiece surface by significantly increasing the air pressure, achieving lossless equivalence of the energy field.

[0105] S5: Generate a control command stream from the target state of the robot to drive the two robots to work together to achieve consistency of the effective impact kinetic energy flux on both sides of the workpiece.

[0106] Preferably, as an example, generating a control command stream from the target state of the robot to drive the two robots to work collaboratively to achieve consistency in the effective impact kinetic energy flux on both sides of the workpiece includes:

[0107] First, enforce integrity constraints, specifically:

[0108] Based on Hertz contact theory, using the compensated process parameters obtained after the solution ( Predict the surface roughness value after a single impact.

[0109] If the surface roughness value exceeds the preset upper limit allowed by the process, it indicates that the air pressure applied to compensate for the energy is too high and may damage the surface. At this time, a multi-pass disassembly strategy is triggered: the original high-energy scan is disassembled into several low-energy-density reciprocating scan trajectories.

[0110] Understandably, this strategy reduces the peak force of a single impact while increasing the number of scans, ensuring that the total injected energy remains constant. This addresses the risk of surface overspray that may arise when pursuing energy balance.

[0111] Next, a control command stream constrained by integrity is output to drive the dual robots to perform machining. At this point, the effective impact kinetic energy flux on both sides of the workpiece remains consistent throughout the entire machining process, thereby eliminating the source of deformation.

[0112] Figure 2The image shows a comparison of adaptive adjustments to the robot's machining trajectory. The gray wavy line represents the actual surface cross-sectional profile of the workpiece, while the red dashed line represents the robot's end effector trajectory generated using the traditional geometric mirroring method. It can be seen that this trajectory only maintains a geometrically constant spacing and does not consider the influence of curvature on the energy field. The green solid line represents the optimized trajectory generated using this invention. The green arrows indicate the active adjustment actions of this invention in different curvature regions.

[0113] As can be seen from the image, in the concave area on the left side of the workpiece, the green trajectory tends to rise actively compared to the red trajectory, in order to reduce the surface energy density and prevent overspraying.

[0114] In the convex region on the right side of the workpiece, the green trajectory exhibits an active downward pressure trend compared to the red trajectory, aiming to increase surface energy density and compensate for divergence losses. This figure visually demonstrates that the present invention breaks through the traditional geometric equidistant limitations and achieves trajectory reconstruction based on the physical energy field.

[0115] This concludes the embodiment.

[0116] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A robot mirroring processing trajectory planning method of a dual-robot shot blasting device, characterized in that, The method comprises the following steps: The workpiece surface is discretely sampled to form a series of trajectory points, and the effective topological energy receiving rate is calculated by combining the curvature and angle characteristics of the trajectory points, which satisfies: effective topological energy receiving rate of the first , , , jet impact angle value, average principal curvature value, Gaussian curvature value, corresponding target distance value of the first trajectory point​ A shot jet volume energy field model is constructed, which includes a kinetic energy flux density function and a jet aerodynamic interference boundary model; the kinetic energy flux density function is: an index number of a trajectory point, a kinetic energy flux density value at the th trajectory point, a radial distance value of the th trajectory point from the center axis of the jet, an effective divergence radius value of the jet beam corresponding to the target distance of the th trajectory point, an energy transfer efficiency coefficient, a jet pressure value, a projectile mass flow value, a high-pressure air density value; The reference energy flux of the master robot is calculated by using the kinetic energy flux density function and the effective topological energy receiving rate, and an energy flux topological balance equation is established, which is specifically: The kinetic energy flux density function is multiplied by the effective topological energy receiving rate to obtain an energy flux function, and the energy flux of the master robot is calculated as the reference energy flux; The energy flux of the slave robot is set to be equal to the reference energy flux, thereby establishing an equation relationship including the geometric position variables and process parameter variables of the slave robot as the energy flux topological balance equation; The energy flux topological balance equation constrains the effective energy flux of the slave robot to be equal to the reference energy flux; Based on the energy flux topological balance equation, the target state of the slave robot is inversely solved; in the solving process, if it is detected based on the jet aerodynamic interference boundary model that the regions overlap, a time domain sliding mode avoidance strategy is activated to calculate an execution lag time; if it is detected that the slave robot is in a kinematic singular domain, a cross-parameter substitution compensation strategy is activated to calculate a compensation amount of a non-geometric process parameter; The jet aerodynamic interference boundary model defines an interference radius that expands with the increase of the target distance; Based on the jet aerodynamic interference boundary model, detection is performed, including: calculating the Euclidean distance between the target point of the master robot and the target point of the slave robot, and comparing the Euclidean distance with the sum of the interference radii of the master and slave robots determined based on the jet aerodynamic interference boundary model; if the Euclidean distance is less than the sum of the interference radii, it is determined that there is a risk of aerodynamic interference, and the time domain sliding mode avoidance strategy is triggered; According to the target state of the slave robot, a control instruction stream is generated to drive the dual-robot cooperative operation to realize the consistency of the effective impact kinetic energy flux on both sides of the workpiece.

2. The method according to claim 1, wherein The time domain sliding mode avoidance strategy specifically includes: The spatial path coordinates of the slave robot are kept unchanged; A minimum time difference required for the interference regions of the master and slave robots to be staggered on the time axis is calculated, and the minimum time difference is added to the timestamp of the slave robot as an execution lag time, so as to realize a processing mode of spatial overlap but temporal separation.

3. The method of claim 1, wherein the method further comprises: The cross-parameter substitution compensation strategy converts the geometric position error into a compensation amount of a non-geometric process parameter by using an energy sensitivity matrix, and the calculation relationship of the energy sensitivity matrix is: wherein is the initial set pressure and flow rate value for the robot for the first trajectory point; is the effective jet beam divergence radius value corresponding to the safe margin standoff distance; is the energy sensitivity matrix for the first trajectory point.

4. The robot mirroring processing trajectory planning method of a dual-robot shot blasting device according to claim 3, characterized in that, If it is detected that the slave robot is in a kinematic singular domain, the cross-parameter substitution compensation strategy is activated to calculate a compensation amount of a non-geometric process parameter, which specifically includes: The condition number of the Jacobian matrix of the target pose of the slave robot is calculated, and it is determined whether the condition number exceeds a preset safety threshold; if yes, it is determined that the slave robot is in a kinematic singular domain and the geometric position of the slave robot is locked at a safety boundary. The energy loss is mapped to the increments of the shot mass flow rate and the shot gas pressure of the slave robot using the pseudo-inverse matrix of the energy sensitivity matrix, which are called the compensation amounts of the non-geometric process parameters.

5. The method of claim 1, wherein, The method further comprises performing a surface integrity constraint, specifically: predicting the surface roughness value after a single impact based on contact mechanics theory; if the surface roughness value exceeds the preset upper limit of the process, the single high-energy-density scanning track is divided into multiple low-energy-density reciprocating scanning tracks, and the scanning speed is re-planned while keeping the total cumulative energy flux unchanged.

6. The method of claim 1, wherein, The method further comprises performing data preprocessing: Before trajectory planning, the original point cloud data of the workpiece surface is obtained using a three-dimensional laser scanner; the original point cloud data is denoised and smoothed, and the normal vector, principal curvature and Gaussian curvature of each discrete point are calculated based on the processed point cloud data.

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