Robot dynamic polishing path planning method, device, equipment, storage medium and program product

Abstract

The application discloses a robot dynamic polishing path planning method, device, equipment, storage medium and program product, and the method comprises the following steps: collecting polishing motion data in the process that a robot polishing device polishes a test steel plate; analyzing the relative motion relationship between the robot polishing device and the test steel plate based on the polishing motion data, and generating a periodic polishing path of the robot polishing device according to the relative motion information, wherein the periodic polishing path comprises a transverse movement path and an oblique movement path of the robot polishing device in a polishing period; obtaining steel plate parameters of a steel plate to be polished and robot parameters of the robot polishing device, constructing a dynamic polishing model based on the steel plate parameters and the robot parameters, and solving the dynamic polishing model, and planning a dynamic polishing path according to the dynamic polishing solving result and the periodic polishing path, so that the polishing efficiency in a dynamic scene is effectively improved, the polishing quality of a dynamic workpiece is ensured, and the workpiece polishing reliability is improved.

Description

Technical Field

[0001] This invention relates to the field of robotics, and in particular to a method, apparatus, equipment, storage medium, and program product for dynamic grinding path planning in robots. Background Technology

[0002] In recent years, robotic polishing technology has been widely used in industrial manufacturing. Many methods exist for robotic polishing paths, but these paths are primarily designed for static objects. For example, path planning methods are mainly divided into two categories: offline planning based on workpiece geometry models and online planning based on real-time sensing. Both of these methods perform well in polishing static workpieces (such as castings and molds), achieving uniform coverage and high-quality surface treatment through preset paths.

[0003] In practice, many objects being ground are dynamic, requiring consideration of the robot's relative motion. For example, in steel mills, strip steel is ground continuously during production to improve efficiency, with the robot grinding the strip without stopping. Therefore, current methods cannot effectively handle grinding scenarios involving dynamic workpieces, resulting in lower grinding efficiency and quality, and failing to ensure that the required grinding area of ​​the steel plate is sufficiently and effectively ground. Summary of the Invention

[0004] The main objective of this invention is to provide a method, apparatus, equipment, storage medium, and program product for robot dynamic grinding path planning, which aims to solve the technical problem that the existing technology cannot effectively cope with the grinding scenarios of dynamic workpieces, resulting in low grinding efficiency and grinding quality of dynamic workpieces, and failing to ensure that the required grinding area of ​​the steel plate is fully and effectively ground.

[0005] To achieve the above objectives, the present invention provides a method for dynamic grinding path planning of a robot, the method comprising the following steps:

[0006] Collect grinding motion data during the grinding test of steel plates by the robot grinding device;

[0007] The relative motion relationship between the robot grinding device and the test steel plate is analyzed based on the grinding motion data to obtain relative motion information;

[0008] The periodic grinding path of the robot grinding device is generated based on the relative motion information. The periodic grinding path includes the lateral movement path and the diagonal movement path of the robot grinding device within the grinding cycle.

[0009] The steel plate parameters to be polished and the robot parameters of the robot polishing device are obtained. The steel plate parameters include the target polishing size, the steel plate movement direction and the steel plate movement speed. The robot parameters include the polishing stone size and the robot movement speed of the robot polishing device.

[0010] A dynamic grinding model is constructed based on the steel plate parameters and the robot parameters, and the dynamic grinding model is solved to obtain the dynamic grinding solution results.

[0011] Dynamic grinding path planning is performed based on the dynamic grinding solution results and the periodic grinding path.

[0012] Optionally, the step of constructing a dynamic grinding model based on the steel plate parameters and the robot parameters, and solving the dynamic grinding model to obtain the dynamic grinding solution results, includes:

[0013] The constraint relationship between the robot grinding device and the steel plate to be ground is determined based on the steel plate parameters and the robot parameters.

[0014] A dynamic polishing model is constructed based on the aforementioned constraints:

[0015]

[0016] Where d represents the lateral movement distance of the robot when the robot grinding device moves laterally for grinding, L represents the effective grinding length of the steel plate to be ground when the robot grinding device moves laterally for grinding, w1 represents the effective width of the grinding stone, and w2 represents the target grinding width of the steel plate to be ground.

[0017] The dynamic grinding model is solved to obtain the dynamic grinding solution results.

[0018] Optionally, the constraint relationships include: lateral movement time constraint relationship, lateral movement grinding dimension constraint relationship, oblique movement time constraint relationship, periodic movement number constraint relationship, and periodic grinding dimension constraint relationship;

[0019] The lateral movement time constraint and the lateral movement grinding dimension constraint are the constraint relationships between the robot grinding device and the steel plate to be ground during lateral movement grinding. The lateral movement time constraint includes:

[0020]

[0021] The lateral movement grinding dimension constraint relationship includes:

[0022] d+x1=L

[0023] The oblique movement time constraint relationship is the constraint relationship between the robot grinding device and the steel plate to be ground when the robot grinding device moves obliquely for grinding. The oblique movement time constraint relationship includes:

[0024]

[0025] The periodic motion number constraint relationship and the periodic grinding size constraint relationship are the constraint relationships of the robot grinding device within the grinding cycle. The periodic motion number constraint relationship includes:

[0026]

[0027] The periodic grinding dimension constraint relationship includes:

[0028] N1(x2+x1)=d

[0029] Wherein, v1 represents the moving speed of the steel plate to be ground, v2 represents the moving speed of the robot grinding device, x1 represents the moving distance of the steel strip to be ground when the robot grinding device moves laterally for grinding, x2 represents the moving distance of the steel strip to be ground when the robot grinding device moves obliquely for grinding, N1 represents the number of grinding movements within half a grinding cycle, and the grinding movement includes lateral grinding movement superimposed with oblique grinding movement.

[0030] Optionally, the dynamic grinding solution results include a first movement distance solution, a second movement distance solution, and a third movement distance solution for the robot's lateral movement distance; the step of solving the dynamic grinding model to obtain the dynamic grinding solution results includes:

[0031] The effective grinding length of the steel plate to be ground is determined based on the constraint relationship when the robot grinding device moves laterally to grind.

[0032] The dynamic polishing model is broken down into multiple coefficient models, which include:

[0033] k1 = 2L(w1 + w2)

[0034]

[0035] Based on the effective grinding length, the multiple coefficient models are solved to obtain the dynamic grinding solution results:

[0036]

[0037] Where k1, k2, k3, and k4 represent the coefficient model, d1, d2, and d3 represent the first, second, and third movement distance solutions, respectively, and m, n, u, v, and Let i and y represent the intermediate variables in the coefficient model, respectively, and let i represent the imaginary number.

[0038] Optionally, the dynamic grinding solution results also include the first effective grinding length solution results and the second effective grinding length solution results for the effective grinding length of the steel plate to be ground when the robot grinding device moves laterally for grinding; the step of solving the dynamic grinding model to obtain the dynamic grinding solution results includes:

[0039] The lateral movement distance of the robot during the lateral movement of the robot grinding device is determined according to the aforementioned constraint relationship.

[0040] The dynamic polishing model is broken down into multiple coefficient models, which include:

[0041]

[0042] The dynamic grinding solution is obtained by solving the multiple coefficient models based on the robot's lateral movement distance:

[0043]

[0044] Where, k 11 k 12 and k 13 L represents the coefficient model, respectively. 1,2 L represents the result of dynamic polishing solution. 1,2 This includes the solution results for the first effective grinding length and the second effective grinding length.

[0045] Optionally, the step of planning the dynamic grinding path based on the dynamic grinding solution and the periodic grinding path includes:

[0046] Based on the dynamic grinding solution results, the lateral movement time constraint relationship and the lateral movement grinding dimension constraint relationship between the robot grinding device and the steel plate to be ground during lateral movement grinding, the robot moving speed of the robot grinding device is determined as follows:

[0047]

[0048] The required grinding cycle is determined based on the cyclic grinding path, the target grinding size of the steel plate to be ground, and the effective grinding length of the steel plate to be ground when the robot grinding device moves laterally for grinding. The target grinding size includes the target grinding length and the target grinding width.

[0049]

[0050] Where N2 represents the grinding cycle required for the robot grinding device to complete the grinding of the steel plate to be ground, and l represents the target grinding length of the steel plate to be ground.

[0051] Dynamic grinding path planning is performed based on the required grinding cycle and the grinding path of the cycle.

[0052] Furthermore, to achieve the above objectives, the present invention also proposes a robot dynamic grinding path planning device, the robot dynamic grinding path planning device comprising:

[0053] The data acquisition module is used to collect grinding motion data during the grinding test of the steel plate by the robot grinding device;

[0054] The motion analysis module is used to analyze the relative motion relationship between the robot grinding device and the test steel plate based on the grinding motion data, and to obtain relative motion information;

[0055] The periodic path analysis module is used to generate the periodic grinding path of the robot grinding device based on the relative motion information. The periodic grinding path includes the lateral movement path and the diagonal movement path of the robot grinding device within the grinding cycle.

[0056] The parameter acquisition module is used to acquire the steel plate parameters to be polished and the robot parameters of the robot polishing device. The steel plate parameters include the target polishing size, the steel plate movement direction and the steel plate movement speed. The robot parameters include the polishing stone size and the robot movement speed of the robot polishing device.

[0057] The model solving module is used to construct a dynamic grinding model based on the steel plate parameters and the robot parameters, and to solve the dynamic grinding model to obtain the dynamic grinding solution results.

[0058] The dynamic path planning module is used to plan the dynamic grinding path based on the dynamic grinding solution and the periodic grinding path.

[0059] In addition, to achieve the above objectives, this application also proposes a robot dynamic polishing path planning device, the device comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, the computer program being configured to implement the steps of the robot dynamic polishing path planning method described above.

[0060] In addition, to achieve the above objectives, this application also proposes a computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps of the robot dynamic grinding path planning method described above.

[0061] In addition, to achieve the above objectives, this application also provides a computer program product, which includes a computer program that, when executed by a processor, implements the steps of the robot dynamic grinding path planning method described above.

[0062] This invention collects grinding motion data during the grinding of a test steel plate by a robotic grinding device. Based on this data, it analyzes the relative motion relationship between the robotic grinding device and the test steel plate to obtain relative motion information. Then, it generates a periodic grinding path for the robotic grinding device based on this relative motion information. This periodic grinding path includes the lateral and diagonal movement paths of the robotic grinding device within a grinding cycle. The invention also obtains the steel plate parameters and the robot parameters of the robotic grinding device. The steel plate parameters include the target grinding size, the steel plate movement direction, and the steel plate movement speed. The robot parameters include the grinding stone size and the robot movement speed. Based on these steel plate parameters and the target grinding path, the invention further develops a grinding process. A dynamic grinding model is constructed using robot parameters, and the model is solved to obtain dynamic grinding results. Based on these results and the periodic grinding path, dynamic grinding path planning is performed. This invention improves the dynamic synchronization performance of the robot during grinding by analyzing the relative motion between the robot grinding device and the test steel plate, generating a periodic grinding path based on the relative motion information. Furthermore, by planning the dynamic grinding path based on the results and the periodic grinding path, the efficiency of dynamic scene grinding is effectively improved, ensuring the grinding quality of dynamic workpieces, enhancing workpiece grinding reliability, ensuring that the actual grinding area of ​​the workpiece meets process requirements, and effectively avoiding uneven grinding and missed grinding issues. Attached Figure Description

[0063] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, for those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0064] Figure 1 This is a schematic diagram of the structure of the robot dynamic grinding path planning device in the hardware operating environment involved in the embodiments of the present invention;

[0065] Figure 2 This is a flowchart illustrating an embodiment of the robot dynamic polishing path planning method of the present invention;

[0066] Figure 3 This is a top view of the grinding stone and steel plate of the robot grinding device in one embodiment of the robot dynamic grinding path planning method of the present invention.

[0067] Figure 4 This is a schematic diagram of the lateral movement and polishing process of the polishing stone in a robot polishing device according to an embodiment of the robot dynamic polishing path planning method of the present invention.

[0068] Figure 5 This is a schematic diagram of the oblique movement of the polishing stone in a robot polishing device in one embodiment of the robot dynamic polishing path planning method of the present invention.

[0069] Figure 6 This is a schematic diagram of a periodic grinding path in one embodiment of the robot dynamic grinding path planning method of the present invention;

[0070] Figure 7 This is a structural block diagram of an embodiment of the robot dynamic grinding path planning device of the present invention.

[0071] The realization of the objective, functional features and advantages of the present invention will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0072] It should be understood that the specific embodiments described herein are for illustrative purposes only and are not intended to limit the scope of the invention.

[0073] Reference Figure 1 , Figure 1 This is a schematic diagram of the structure of a robot dynamic grinding path planning device in the hardware operating environment of the embodiment of the present invention.

[0074] like Figure 1 As shown, the robot's dynamic grinding path planning device may include: a processor 1001, such as a central processing unit (CPU), a communication bus 1002, a user interface 1003, a network interface 1004, and a memory 1005. The communication bus 1002 is used to enable communication between these components. The user interface 1003 may include a display screen or an input unit such as a keyboard; optionally, the user interface 1003 may also include a standard wired interface or a wireless interface. The network interface 1004 may optionally include a standard wired interface or a wireless interface (such as a Wireless-Fidelity (Wi-Fi) interface). The memory 1005 may be high-speed random access memory (RAM) or stable non-volatile memory (NVM), such as a disk storage device. Optionally, the memory 1005 may also be a storage device independent of the aforementioned processor 1001.

[0075] Those skilled in the art will understand that Figure 1 The structure shown does not constitute a limitation on the robot's dynamic grinding path planning device, and may include more or fewer components than shown, or combine certain components, or have different component arrangements.

[0076] like Figure 1 As shown, the memory 1005, which is a computer-readable storage medium, may include an operating system, a network communication module, a user interface module, and a robot dynamic grinding path planning program.

[0077] exist Figure 1 In the robot dynamic polishing path planning device shown, the network interface 1004 is mainly used for data communication with the network server; the user interface 1003 is mainly used for data interaction with the user; the processor 1001 and memory 1005 in the robot dynamic polishing path planning device of the present invention can be set in the robot dynamic polishing path planning device, and the robot dynamic polishing path planning device calls the robot dynamic polishing path planning program stored in the memory 1005 through the processor 1001 and executes the robot dynamic polishing path planning method provided in the embodiment of the present invention.

[0078] This invention provides a method for dynamic grinding path planning in robots, referring to... Figure 2 , Figure 2 This is a flowchart illustrating an embodiment of the robot dynamic grinding path planning method of the present invention.

[0079] In this embodiment, the robot dynamic polishing path planning method includes the following steps:

[0080] Step S10: Collect grinding motion data during the grinding test of the steel plate by the robot grinding device.

[0081] It should be understood that the executing entity of this embodiment can be a computing service device with data processing, network communication, and program execution functions, such as a robot control terminal, or a terminal electronic device capable of realizing the above functions. The following description uses a robot dynamic grinding path planning device (planning device) as an example to illustrate this embodiment and the subsequent embodiments.

[0082] It should be noted that the robotic grinding device can be a grinding stone at the end of a robotic arm, or it can be other types of robots with grinding functions. The test steel plate mentioned above can be a dynamic steel plate. During the grinding process of the robotic grinding device, the test steel plate can move at a constant speed in any horizontal direction to simulate the dynamic grinding scenario in the workpiece production process. The robotic grinding device can perform lateral grinding and oblique grinding on the test steel plate.

[0083] It should be noted that the grinding motion data can be the relevant motion data collected during the grinding test of the steel plate by the grinding test robot grinding device, including robot motion data and steel plate motion data. The robot motion data may include robot motion speed, robot motion direction and robot movement distance, etc., while the steel plate motion data may include steel plate motion speed, steel plate movement distance and steel plate movement direction, etc.

[0084] For example, grinding motion data may include robot movement speed, steel plate movement speed, the distance the grinding stone connected to the end moves when the robot grinding device moves laterally, the distance the steel plate moves when the robot grinding device moves laterally, the effective grinding length of the steel plate when the robot grinding device moves laterally, the effective width of the grinding stone, the width of the steel plate to be ground, the length of the steel plate to be ground, and the distance the steel plate moves when the robot grinding device moves obliquely.

[0085] In some embodiments, the process of the robotic grinding device grinding the test steel plate can be referred to Figure 3 , Figure 4 and Figure 5 , Figure 3 A top-view diagram of the grinding stone and steel plate of the robotic grinding device. Figure 4 This is a schematic diagram of the lateral movement of the polishing stone in a robotic polishing device. Figure 5 This diagram illustrates the oblique movement of a grinding stone in a robotic grinding device. Here, d represents the distance the grinding stone moves at its end during lateral movement; x1 represents the distance the steel plate moves during lateral movement; L represents the effective length of the steel plate being ground during lateral movement; w1 represents the effective width of the grinding stone; w2 represents the width of the steel plate to be ground; l represents the length of the steel plate to be ground; and x2 represents the distance the steel plate moves during oblique movement.

[0086] In some embodiments, the robotic grinding device may be equipped with a multi-axis industrial robot (such as a 6-axis articulated robot) with grinding tools (such as grinding stones, grinding wheels or polishing heads) installed at its end. The process of the robotic grinding device grinding the test steel plate may simulate the dynamic steel plate in actual production, moving at a constant speed along the horizontal direction or the x-axis via a conveyor belt or moving platform.

[0087] In some embodiments, the planning equipment can collect grinding motion data during the grinding test steel plate process of the robot grinding device through sensors and data acquisition systems. For example, it can collect point cloud data of the robot end in real time through a laser sensor to determine the three-dimensional position and movement speed of the robot end; capture the surface state of the grinding area through a vision sensor to determine the effective grinding marks; and monitor the changes in contact force and pressure at the end of the robot grinding device during the grinding process through a torque sensor to determine the grinding pressure parameters corresponding to effective grinding.

[0088] Step S20: Analyze the relative motion relationship between the robot grinding device and the test steel plate based on the grinding motion data to obtain relative motion information.

[0089] In some embodiments, the planning device may preprocess the collected grinding motion data, such as performing noise filtering, coordinate system transformation, and data alignment on the grinding motion data.

[0090] It should be noted that relative motion information may include velocity synchronization error, trajectory deviation, relative displacement, coverage, etc.

[0091] In some embodiments, the planning device can draw the three-dimensional movement trajectory of the robot end-effector grinding device in the steel plate coordinate system based on the pre-processed grinding motion data, and generate the displacement curve of the steel plate in the X-axis direction over time. Based on the robot's three-dimensional movement trajectory and the displacement curve of the steel plate over time, the displacement of the robot end-effector grinding device relative to the steel plate is calculated, thereby obtaining the relative displacement between the robot end-effector and the steel plate.

[0092] In some embodiments, the planning device calculates the speed of the robot end effector in the X and Y axis directions and analyzes the synchronization error between the speed of the robot end effector and the steel plate in the X and Y axis directions.

[0093] In some embodiments, the planning device can plot a scatter plot between contact force and relative displacement, analyze the coupling relationship between force and displacement, and optimize the path if the contact force fluctuates greatly and the end-effector path planning of the surface robot fails to effectively move the steel plate.

[0094] In some embodiments, the planning device can use surface topography data recorded by a vision system, combined with the robot trajectory, to calculate the coverage of the polished area, identify uncovered or over-polished areas, and optimize path planning.

[0095] Step S30: Generate the periodic grinding path of the robot grinding device based on the relative motion information.

[0096] It should be noted that the cyclic grinding path includes the lateral movement path and the diagonal movement path of the robot grinding device within the grinding cycle. In some embodiments, the planning device can divide the target area of ​​the steel plate to be ground into multiple sub-regions, where each sub-region requires one grinding cycle to be ground, and one grinding cycle includes multiple grinding movements.

[0097] Understandably, the planned equipment can be combined Figure 3 , Figure 4 and Figure 5 The grinding process is shown, and the relative motion relationship between the robotic grinding device and the test steel plate is analyzed by combining grinding motion data to generate regular grinding motion, i.e., to obtain a periodic grinding path, which is then referred to... Figure 6 , Figure 6 This is a schematic diagram of the cyclic polishing path, in which, Figure 6 The solid and dashed lines form a grinding path for one cycle. The arrows indicate the direction of the robot's end effector movement, with its horizontal movement direction opposite to that of the steel plate. Point A is the starting and ending point of the robot arm's end effector movement. The first half of the cycle is defined as A→B→K→L, and the second half as L→M→N→A. A movement from A to B is considered one horizontal movement, and a movement from B to C is considered one diagonal movement. One horizontal movement plus one diagonal movement constitutes one grinding motion. A grinding cycle corresponds to a grinding path that includes multiple grinding motions, i.e., the robot arm's end effector moves in a specific direction... Figure 6 If the lateral and diagonal superposition motions constitute one motion, then N1 one-time motions are required within half a cycle:

[0098]

[0099] Step S40: Obtain the steel plate parameters to be ground and the robot parameters of the robot grinding device.

[0100] It should be noted that the steel plate parameters include the target grinding size, the steel plate movement direction, and the steel plate movement speed, and the robot parameters include the grinding stone size of the robot grinding device and the robot movement speed.

[0101] In some embodiments, the planning device can collect physical property parameters, motion parameters, and geometric parameters of the steel plate to be ground, as well as motion parameters, power parameters, and sensor parameters of the robot grinding device.

[0102] Step S50: Construct a dynamic grinding model based on the steel plate parameters and the robot parameters, and solve the dynamic grinding model to obtain the dynamic grinding solution results.

[0103] It should be noted that the dynamic grinding model can be a polynomial mathematical model for the dynamic grinding path planning of the robotic grinding device. In some embodiments, the planning device can determine the grinding constraints of the robotic grinding device in the dynamic grinding process based on the steel plate parameters and robot parameters, construct polynomial equations based on the grinding constraints, compare the solutions of the polynomial equations, and obtain the dynamic grinding solution results.

[0104] Furthermore, in order to improve polishing efficiency and polishing quality, step S50 above may include:

[0105] Step S51: Determine the constraint relationship between the robot grinding device and the steel plate to be ground based on the steel plate parameters and the robot parameters;

[0106] Step S52: Construct a dynamic polishing model based on the aforementioned constraint relationships;

[0107] Step S53: Solve the dynamic grinding model to obtain the dynamic grinding solution results.

[0108] It should be noted that the dynamic polishing model can be a polynomial mathematical model built based on constraint relationships:

[0109]

[0110] Where d represents the lateral movement distance of the robot when the robot grinding device moves laterally for grinding, L represents the effective grinding length of the steel plate to be ground when the robot grinding device moves laterally for grinding, w1 represents the effective width of the grinding stone, and w2 represents the target grinding width of the steel plate to be ground.

[0111] Furthermore, in order to accurately construct the dynamic grinding model and improve grinding accuracy, the constraints include: lateral movement time constraints, lateral movement grinding dimension constraints, oblique movement time constraints, periodic movement number constraints, and periodic grinding dimension constraints.

[0112] The lateral movement time constraint relationship and the lateral movement grinding size constraint relationship are the constraint relationships between the robot grinding device and the steel plate to be ground when the robot grinding device moves laterally to grind.

[0113] Reference Figure 6 The robotic polishing device from Figure 6 When point A moves laterally to point B, the robot and the steel plate move in equal time. Therefore, the lateral movement time constraint relationship includes:

[0114]

[0115] The lateral movement grinding dimension constraint relationship includes:

[0116] d+x1=L

[0117] The oblique movement time constraint relationship is the constraint relationship between the robot grinding device and the steel plate to be ground when the robot grinding device moves obliquely to grind.

[0118] Reference Figure 6 The robotic polishing device from Figure 6 When point B moves to point C, the time taken for the robot and the steel plate to move is equal. The oblique movement time constraint relationship includes:

[0119]

[0120] The constraints on the number of periodic motions and the constraints on the periodic grinding dimensions are the constraints on the robot grinding device within the grinding cycle, as referred to... Figure 6 , Figure 6 The grinding robot moves from point A to point B and then to point C, constituting one grinding motion (lateral movement plus diagonal movement). The constraints on the number of cyclic movements include:

[0121]

[0122] When the robotic polishing device moves from point A to point L, there is a periodic polishing dimension constraint relationship, which includes:

[0123] N1(x2+x1)=d

[0124] Wherein, v1 represents the moving speed of the steel plate to be ground, v2 represents the moving speed of the robot grinding device, x1 represents the moving distance of the steel strip to be ground when the robot grinding device moves laterally for grinding, x2 represents the moving distance of the steel strip to be ground when the robot grinding device moves obliquely for grinding, N1 represents the number of grinding movements within half a grinding cycle, and the grinding movement includes lateral grinding movement superimposed with oblique grinding movement.

[0125] It is understandable that by combining the above formulas for the lateral movement time constraint, the lateral movement grinding dimension constraint, the oblique movement time constraint, the periodic movement number constraint, and the periodic grinding dimension constraint, the dynamic grinding model can be obtained:

[0126]

[0127] Furthermore, in order to accurately solve the dynamic grinding model under different scenarios, the dynamic grinding solution results include the first movement distance solution result, the second movement distance solution result, and the third movement distance solution result of the robot's lateral movement distance. In some embodiments, the above step S53 may include:

[0128] Step S531: Determine the effective grinding length of the steel plate to be ground when the robot grinding device moves laterally to grind according to the constraint relationship;

[0129] Step S532: Decompose the dynamic polishing model to obtain multiple coefficient models;

[0130] Step S533: Solve the multiple coefficient models based on the effective grinding length to obtain the dynamic grinding solution results.

[0131] It should be noted that in some embodiments, the effective grinding width w1 of the robotic grinding device and the width w2 of the steel plate to be ground are both known. Therefore, by simply providing a value either the effective grinding length L of the steel plate to be ground during the lateral movement of the robotic grinding device or the lateral movement distance d of the robot during the lateral movement of the robotic grinding device, the values ​​of all other variables can be obtained. In this embodiment, we assume that the value of L is given, and then the other value d is used as a variable, i.e., given L, we calculate d. The above coefficient model includes:

[0132] k1 = 2L(w1 + w2)

[0133]

[0134] The above-described solution to the multiple coefficient models based on the effective grinding length can include the following radical solutions:

[0135]

[0136] Where d1, d2, and d3 represent three solutions to d, with the complex part being:

[0137]

[0138] Other intermediate variables are:

[0139]

[0140] Where k1, k2, k3, and k4 represent the coefficient model, d1, d2, and d3 represent the first, second, and third movement distance solutions, respectively, and m, n, u, v, and Let i and y represent the intermediate variables in the coefficient model, respectively, and let i represent the imaginary number.

[0141] In some embodiments, if d is a known quantity and L is to be calculated, the dynamic grinding solution result further includes the first effective grinding length solution result and the second effective grinding length solution result of the effective grinding length of the steel plate to be ground when the robot grinding device moves laterally for grinding; the above step S53 may include:

[0142] Step S5301: Determine the lateral movement distance of the robot during the lateral movement of the robot grinding device for grinding based on the constraint relationship;

[0143] Step S5302: Decompose the dynamic polishing model to obtain multiple coefficient models;

[0144] Step S5303: Solve the multiple coefficient models based on the robot's lateral movement distance to obtain the dynamic grinding solution results.

[0145] It should be noted that the coefficient model includes:

[0146]

[0147]

[0148] The above solution to the multiple coefficient models is based on the robot's lateral movement distance, where the two roots of the equations can be expressed as:

[0149]

[0150] Where, k 11 k 12 and k 13 L represents the coefficient model, respectively. 1,2 L represents the result of dynamic polishing solution. 1,2 Including the solution results of the first effective grinding length and the second effective grinding length, the movement distance d at the end of the robotic arm should be within the workspace range; otherwise, the robotic arm cannot reach it.

[0151] Step S60: Perform dynamic grinding path planning based on the dynamic grinding solution results and the periodic grinding path.

[0152] In some embodiments, there may be multiple results in the dynamic grinding solution. In order to determine the optimal path, the planning device may use a genetic algorithm or a particle swarm optimization algorithm to optimize the dynamic grinding solution and obtain the optimal solution. Based on the optimal solution and the periodic grinding path, dynamic grinding path planning is performed to determine the grinding cycle, grinding torque and dynamic grinding path. Based on the grinding cycle, grinding torque and dynamic grinding path, the grinding device at the end of the robot is controlled to perform dynamic grinding of the steel plate to be ground.

[0153] Furthermore, in order to accurately plan the dynamic polishing path, in some embodiments, step S60 above may include:

[0154] The robot movement speed of the robot grinding device is determined based on the dynamic grinding solution results, the lateral movement time constraint relationship and the lateral movement grinding size constraint relationship between the robot grinding device and the steel plate to be ground during lateral movement grinding.

[0155] The required grinding cycle is determined based on the cycle grinding path, the target grinding size of the steel plate to be ground, and the effective grinding length of the steel plate to be ground when the robot grinding device moves laterally for grinding.

[0156] Dynamic grinding path planning is performed based on the required grinding cycle and the grinding path of the cycle.

[0157] It should be noted that the target grinding dimensions include the target grinding length and the target grinding width. The movement speed of the steel plate can be acquired by the on-site program, and is usually a fixed uniform speed value.

[0158] The robot's movement speed is calculated using the following formula:

[0159]

[0160] The robotic polishing device needs to complete N² cycles before stopping. The required polishing cycle is calculated using the following formula:

[0161]

[0162] Where N2 represents the grinding cycle required for the robot grinding device to complete the grinding of the steel plate to be ground, and l represents the target grinding length of the steel plate to be ground.

[0163] This embodiment collects grinding motion data during the grinding of a test steel plate by a robotic grinding device. Based on this data, it analyzes the relative motion relationship between the robotic grinding device and the test steel plate to obtain relative motion information. A periodic grinding path is generated based on this information, including the lateral and diagonal movement paths of the robotic grinding device within a grinding cycle. The steel plate parameters and the robot parameters of the robotic grinding device are obtained. The steel plate parameters include the target grinding size, the direction of movement, and the speed of movement. The robot parameters include the size of the grinding stone and the robot's movement speed. Based on these steel plate parameters and the target grinding size, the relative motion relationship between the robotic grinding device and the test steel plate is analyzed to obtain relative motion information. A dynamic grinding model is constructed using the robot parameters, and the model is solved to obtain dynamic grinding results. Based on these results and the periodic grinding path, dynamic grinding path planning is performed. This embodiment improves the robot's dynamic synchronization performance during grinding by analyzing the relative motion between the robot grinding device and the test steel plate, generating a periodic grinding path based on the relative motion information. Furthermore, the dynamic grinding path planning based on the results and the periodic grinding path effectively improves the grinding efficiency in dynamic scenarios, ensures the grinding quality of dynamic workpieces, enhances workpiece grinding reliability, ensures that the actual grinding area of ​​the workpiece meets process requirements, and effectively avoids uneven grinding and missed grinding issues.

[0164] Furthermore, this embodiment of the invention also proposes a computer-readable storage medium storing a robot dynamic polishing path planning program, which, when executed by a processor, implements the steps of the robot dynamic polishing path planning method described above.

[0165] The computer-readable storage medium provided in this application may be, for example, a USB flash drive, but is not limited to, electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices, or any combination thereof. More specific examples of computer-readable storage media may include, but are not limited to: electrical connections having one or more wires, portable computer disks, hard disks, 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 devices, magnetic storage devices, or any suitable combination thereof. In this embodiment, the 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, system, or device. The program code contained on the computer-readable storage medium may be transmitted using any suitable medium, including but not limited to: wires, optical cables, RF (Radio Frequency), etc., or any suitable combination thereof.

[0166] The aforementioned computer-readable storage medium may be included in the robot dynamic grinding path planning device; or it may exist independently and not be assembled into the robot dynamic grinding path planning device.

[0167] Furthermore, this invention also proposes a computer program product, including a robot dynamic polishing path planning program, which, when executed by a processor, implements the steps of the robot dynamic polishing path planning method as described above.

[0168] The specific implementation of the computer program product of the present invention is basically the same as the embodiments of the above-described robot dynamic grinding path planning method, and will not be repeated here.

[0169] Reference Figure 7 , Figure 7 This is a structural block diagram of an embodiment of the robot dynamic grinding path planning device of the present invention.

[0170] like Figure 7 As shown, the robot dynamic grinding path planning device proposed in this embodiment of the invention includes:

[0171] Data acquisition module 10 is used to collect grinding motion data during the grinding test of the steel plate by the robot grinding device;

[0172] Motion analysis module 20 is used to analyze the relative motion relationship between the robot grinding device and the test steel plate based on the grinding motion data, and to obtain relative motion information;

[0173] The periodic path analysis module 30 is used to generate the periodic grinding path of the robot grinding device based on the relative motion information. The periodic grinding path includes the lateral movement path and the diagonal movement path of the robot grinding device within the grinding cycle.

[0174] The parameter acquisition module 40 is used to acquire the steel plate parameters of the steel plate to be polished and the robot parameters of the robot polishing device. The steel plate parameters include the target polishing size, the steel plate movement direction and the steel plate movement speed. The robot parameters include the polishing stone size and the robot movement speed of the robot polishing device.

[0175] The model solving module 50 is used to construct a dynamic grinding model based on the steel plate parameters and the robot parameters, and to solve the dynamic grinding model to obtain the dynamic grinding solution results.

[0176] The dynamic path planning module 60 is used to plan the dynamic grinding path based on the dynamic grinding solution and the periodic grinding path.

[0177] This embodiment collects grinding motion data during the grinding of a test steel plate by a robotic grinding device. Based on this data, it analyzes the relative motion relationship between the robotic grinding device and the test steel plate to obtain relative motion information. A periodic grinding path is generated based on this information, including the lateral and diagonal movement paths of the robotic grinding device within a grinding cycle. The steel plate parameters and the robot parameters of the robotic grinding device are obtained. The steel plate parameters include the target grinding size, the direction of movement, and the speed of movement. The robot parameters include the size of the grinding stone and the robot's movement speed. Based on these steel plate parameters and the target grinding size, the relative motion relationship between the robotic grinding device and the test steel plate is analyzed to obtain relative motion information. A dynamic grinding model is constructed using the robot parameters, and the model is solved to obtain dynamic grinding results. Based on these results and the periodic grinding path, dynamic grinding path planning is performed. This embodiment improves the robot's dynamic synchronization performance during grinding by analyzing the relative motion between the robot grinding device and the test steel plate, generating a periodic grinding path based on the relative motion information. Furthermore, the dynamic grinding path planning based on the results and the periodic grinding path effectively improves the grinding efficiency in dynamic scenarios, ensures the grinding quality of dynamic workpieces, enhances workpiece grinding reliability, ensures that the actual grinding area of ​​the workpiece meets process requirements, and effectively avoids uneven grinding and missed grinding issues.

[0178] The robot dynamic grinding path planning device provided in this application, employing the robot dynamic grinding path planning method in the above embodiments, can solve the technical problem of robot dynamic grinding path planning. Compared with the prior art, the beneficial effects of the robot dynamic grinding path planning device provided in this application are the same as those of the robot dynamic grinding path planning method provided in the above embodiments, and other technical features in the robot dynamic grinding path planning device are the same as those disclosed in the methods of the above embodiments, and will not be repeated here.

[0179] It should be understood that the above are merely illustrative examples and do not constitute any limitation on the technical solutions of the present invention. In specific applications, those skilled in the art can make settings as needed, and the present invention does not impose any restrictions on this.

[0180] It should be noted that the workflow described above is merely illustrative and does not limit the scope of protection of this invention. In practical applications, those skilled in the art can select some or all of the workflow to achieve the purpose of this embodiment according to actual needs, and no restrictions are imposed here.

[0181] In addition, for technical details not described in detail in this embodiment, please refer to the robot dynamic grinding path planning method provided in any embodiment of the present invention, which will not be repeated here.

[0182] It should be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or system that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or system. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or system that includes that element.

[0183] The sequence numbers of the above embodiments of the present invention are for descriptive purposes only and do not represent the superiority or inferiority of the embodiments.

[0184] Through the above description of the embodiments, those skilled in the art can clearly understand that the methods of the above embodiments can be implemented by means of software plus necessary general-purpose hardware platforms. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium (such as read-only memory / random access memory, magnetic disk, optical disk) and includes several instructions to cause a terminal device (which may be a mobile phone, computer, server, air conditioner, or network device, etc.) to execute the methods described in the various embodiments of the present invention.

[0185] The above are merely preferred embodiments of the present invention and do not limit the scope of the patent. Any equivalent structural or procedural transformations made based on the description and drawings of the present invention, or direct or indirect applications in other related technical fields, are similarly included within the scope of patent protection of the present invention.

Claims

1. A method for dynamic grinding path planning in robots, characterized in that, The robot dynamic polishing path planning method includes: Collect grinding motion data during the grinding test of steel plates by the robot grinding device; The relative motion relationship between the robot grinding device and the test steel plate is analyzed based on the grinding motion data to obtain relative motion information; The periodic grinding path of the robot grinding device is generated based on the relative motion information. The periodic grinding path includes the lateral movement path and the diagonal movement path of the robot grinding device within the grinding cycle. The steel plate parameters to be polished and the robot parameters of the robot polishing device are obtained. The steel plate parameters include the target polishing size, the steel plate movement direction and the steel plate movement speed. The robot parameters include the polishing stone size and the robot movement speed of the robot polishing device. A dynamic grinding model is constructed based on the steel plate parameters and the robot parameters, and the dynamic grinding model is solved to obtain the dynamic grinding solution results. Dynamic grinding path planning is performed based on the dynamic grinding solution results and the periodic grinding path. The process of constructing a dynamic grinding model based on the steel plate parameters and the robot parameters, and solving the dynamic grinding model to obtain the dynamic grinding solution results includes: The constraint relationship between the robot grinding device and the steel plate to be ground is determined based on the steel plate parameters and the robot parameters. A dynamic polishing model is constructed based on the aforementioned constraints: in, This indicates the lateral movement distance of the robot during the lateral movement of the grinding device. This indicates the effective grinding length of the steel plate to be ground when the robot grinding device moves laterally for grinding. This indicates the effective width of the polishing stone. Indicates the target grinding width of the steel plate to be ground; The dynamic grinding model is solved to obtain the dynamic grinding solution results.

2. The robot dynamic grinding path planning method as described in claim 1, characterized in that, The constraints include: lateral movement time constraints, lateral movement grinding dimension constraints, oblique movement time constraints, periodic movement number constraints, and periodic grinding dimension constraints. The lateral movement time constraint and the lateral movement grinding dimension constraint are the constraint relationships between the robot grinding device and the steel plate to be ground during lateral movement grinding. The lateral movement time constraint includes: The lateral movement grinding dimension constraint relationship includes: The oblique movement time constraint relationship is the constraint relationship between the robot grinding device and the steel plate to be ground when the robot grinding device moves obliquely for grinding. The oblique movement time constraint relationship includes: The periodic motion number constraint relationship and the periodic grinding size constraint relationship are the constraint relationships of the robot grinding device within the grinding cycle. The periodic motion number constraint relationship includes: The periodic grinding dimension constraint relationship includes: in, This indicates the speed at which the steel plate to be ground moves. This indicates the robot's moving speed in the robotic polishing device. This indicates the distance the steel strip to be ground moves when the robot grinding device moves laterally for grinding. This indicates the distance the steel strip to be ground moves when the robot grinding device moves obliquely. This indicates the number of grinding movements within half a grinding cycle, wherein the grinding movements include lateral grinding movement superimposed with oblique grinding movement.

3. The robot dynamic grinding path planning method as described in claim 2, characterized in that, The dynamic grinding solution results include the first, second, and third lateral movement distance solutions for the robot; the process of solving the dynamic grinding model to obtain the dynamic grinding solution results includes: The effective grinding length of the steel plate to be ground is determined based on the constraint relationship when the robot grinding device moves laterally to grind. The dynamic polishing model is broken down into multiple coefficient models, which include: Based on the effective grinding length, the multiple coefficient models are solved to obtain the dynamic grinding solution results: in, , , and These represent the coefficient models, , and These represent the results of the first, second, and third movement distances, respectively. , , , and These represent the intermediate variables in the coefficient model. Represents an imaginary number.

4. The robot dynamic grinding path planning method as described in claim 2, characterized in that, The dynamic grinding solution results also include the first effective grinding length solution results and the second effective grinding length solution results for the effective grinding length of the steel plate to be ground when the robot grinding device moves laterally for grinding; the process of solving the dynamic grinding model to obtain the dynamic grinding solution results includes: The lateral movement distance of the robot during the lateral movement of the robot grinding device is determined according to the aforementioned constraint relationship. The dynamic polishing model is broken down into multiple coefficient models, which include: The dynamic grinding solution is obtained by solving the multiple coefficient models based on the robot's lateral movement distance: in, , and These represent the coefficient models, This represents the result of the dynamic polishing solution. This includes the solution results for the first effective grinding length and the second effective grinding length.

5. The robot dynamic grinding path planning method as described in any one of claims 1 to 4, characterized in that, The dynamic grinding path planning based on the dynamic grinding solution and the periodic grinding path includes: Based on the dynamic grinding solution results, the lateral movement time constraint relationship and the lateral movement grinding dimension constraint relationship between the robot grinding device and the steel plate to be ground during lateral movement grinding, the robot moving speed of the robot grinding device is determined as follows: The required grinding cycle is determined based on the cyclic grinding path, the target grinding size of the steel plate to be ground, and the effective grinding length of the steel plate to be ground when the robot grinding device moves laterally for grinding. The target grinding size includes the target grinding length and the target grinding width. in, This indicates the time required for the robotic grinding device to complete the grinding process on the steel plate to be ground. Indicates the target grinding length of the steel plate to be ground; Dynamic grinding path planning is performed based on the required grinding cycle and the grinding path of the cycle.

6. A robot dynamic grinding path planning device, characterized in that, The device is configured to implement the robot dynamic polishing path planning method as described in claim 1, wherein the robot dynamic polishing path planning device comprises: The data acquisition module is used to collect grinding motion data during the grinding test of the steel plate by the robot grinding device; The motion analysis module is used to analyze the relative motion relationship between the robot grinding device and the test steel plate based on the grinding motion data, and to obtain relative motion information; The periodic path analysis module is used to generate the periodic grinding path of the robot grinding device based on the relative motion information. The periodic grinding path includes the lateral movement path and the diagonal movement path of the robot grinding device within the grinding cycle. The parameter acquisition module is used to acquire the steel plate parameters to be polished and the robot parameters of the robot polishing device. The steel plate parameters include the target polishing size, the steel plate movement direction and the steel plate movement speed. The robot parameters include the polishing stone size and the robot movement speed of the robot polishing device. The model solving module is used to construct a dynamic grinding model based on the steel plate parameters and the robot parameters, and to solve the dynamic grinding model to obtain the dynamic grinding solution results. The dynamic path planning module is used to plan the dynamic grinding path based on the dynamic grinding solution and the periodic grinding path.

7. A robotic dynamic grinding path planning device, characterized in that, The robot dynamic polishing path planning device includes: a memory, a processor, and a robot dynamic polishing path planning program stored in the memory and executable on the processor, wherein the robot dynamic polishing path planning program is configured to implement the robot dynamic polishing path planning method as described in any one of claims 1 to 5.

8. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a robot dynamic polishing path planning program, which, when executed by a processor, implements the robot dynamic polishing path planning method as described in any one of claims 1 to 5.

9. A computer program product, characterized in that, The computer program product includes a robot dynamic polishing path planning program, which, when executed by a processor, implements the steps of the robot dynamic polishing path planning method as described in any one of claims 1 to 5.

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