A Stepper Motor-Based Control Method and System for Ring-Type Mechanical Grippers

Abstract

This invention discloses a method and system for controlling a ring-shaped mechanical gripper based on a stepper motor. The invention relates to the field of gripping control technology and includes the following steps: obtaining the gripping width of the target mechanical gripper and dividing it into several candidate gripping regions along the length of the object to be gripped; collecting surface structure feature data of each region; evaluating stability scores based on these feature data and the distance between each region and the object's center of gravity, and arranging them in descending order to form a sequence of candidate gripping regions; determining the maximum gripping force of each region sequentially and calculating the minimum gripping pressure for stable gripping; comparing the minimum gripping pressure with the maximum gripping force to determine regions that meet the gripping conditions; gripping with the minimum gripping pressure in regions that meet the conditions; setting the tightening step length of the stepper motor; and dynamically adjusting the gripping pressure based on vibration and slippage parameters during transportation, thereby achieving efficient and stable gripping control.

Description

Technical Field

[0001] This invention relates to the field of clamping control technology, specifically to a method and system for clamping control of a ring-shaped mechanical gripper based on a stepper motor. Background Technology

[0002] With the rapid development of modern automation and robotics, electric gripper systems are increasingly widely used in industrial manufacturing, material handling, and service robots. The gripping stability and accuracy of electric grippers directly affect the processing quality of workpieces and production efficiency. Traditional mechanical clamps often rely on pneumatic or hydraulic systems for clamping. While these systems perform well in terms of clamping force, they have many problems. First, the control of pneumatic and hydraulic systems is relatively complex, requiring the support of complex air or hydraulic power sources, which increases the cost and maintenance difficulty of the system. Simultaneously, leaks may occur in pneumatic and hydraulic systems during operation, leading to unstable clamping force, making workpieces prone to slippage or detachment during clamping, thus affecting production efficiency and product quality.

[0003] With the continuous advancement of stepper motor technology, stepper motor-driven electric gripper systems are gradually becoming an emerging gripping solution. Stepper motors possess excellent precise positioning capabilities and control response speeds, making them suitable for gripping applications requiring high precision and stability. However, in practical applications, accurately controlling the stepper motor's operation and providing real-time feedback on the gripping status remains a technical challenge. Existing control methods often rely solely on set operating parameters, failing to effectively consider potential errors and nonlinear factors that may exist during actual motor operation. This results in inaccurate judgment of the gripping status, thereby affecting gripping quality.

[0004] In the prior art, CN107498573A discloses a stepper motor-driven electric gripper control method and an electric gripper driven by a stepper motor. Specifically, it includes a method for gripping a workpiece based on calculated electromagnetic torque; or a method for determining the gripper's clamping state by calculating the difference between the theoretical and actual running distance of the motor and comparing it with a set threshold. The provided method can quickly control the gripper to hold the workpiece, effectively improving the stability and accuracy of the gripping. However, this solution does not consider how to select the gripping area, which may lead to uneven distribution of clamping force and affect the gripping effect. In addition, the method of determining the gripping state based on the difference between the theoretical and actual running distance only uses the position error threshold, ignoring the subtle changes in the relative movement of the gripped object during the gripping process. During the gripping process, it is impossible to make dynamic adjustments based on the relative movement of the gripped object, thus reducing the accuracy and effectiveness of the gripping effect.

[0005] The information disclosed in the background section is only intended to enhance the understanding of the background of this disclosure, and therefore may include information that does not constitute prior art known to those skilled in the art. Summary of the Invention

[0006] The purpose of this invention is to provide a method and system for controlling a ring-shaped mechanical gripper based on a stepper motor, so as to solve the problems mentioned in the background art.

[0007] To achieve the above objectives, the present invention provides the following technical solution:

[0008] A method for controlling a ring-shaped mechanical gripper based on a stepper motor, comprising the following steps:

[0009] The clamping width of the target encircling mechanical claw is obtained. Based on the clamping width of the target encircling mechanical claw, the object to be clamped is divided into several clamping candidate regions along the length direction of the object to be clamped, and the surface structure feature data of each clamping candidate region is collected.

[0010] Based on the surface structure feature data of each gripping candidate region and the distance between each gripping candidate region and the center of gravity of the object to be gripped, the stability score of each gripping candidate region is evaluated. Based on the stability score of each gripping candidate region, the gripping candidate regions are arranged in descending order to form a sequence of gripping candidate regions.

[0011] Based on the order of the candidate gripping regions, the maximum gripping force that each candidate gripping region can withstand is determined sequentially. Based on the weight of the object to be gripped, the minimum gripping pressure that ensures stable gripping at each candidate gripping region is calculated. The minimum gripping pressure is compared with the maximum gripping force that can be withstood to determine the final gripping position.

[0012] The object to be clamped is clamped at the clamping position with the minimum clamping pressure. The tightening step length of the stepper motor is set, and the minimum clamping pressure is dynamically adjusted according to the vibration and slippage parameters of the object to be clamped during transportation to complete the clamping control.

[0013] Furthermore, the clamping width of the target encircling mechanical claw specifically refers to the clamping surface width of the target encircling mechanical claw;

[0014] Based on the gripping width of the target encircling robotic gripper, the object to be gripped is divided into several gripping candidate regions along the length direction of the object to be gripped. The specific logic is as follows: a sliding window is set with the gripping width of the target encircling robotic gripper, and the gripping width is the width of the sliding window. One end of the sliding window is set on the edge of the object to be gripped along the length direction of the object to be gripped. The sliding window is controlled to move along the length direction of the object to be gripped in increments of 2 units. Each time it moves, the area where the sliding window is located is recorded as a gripping candidate region. This continues until after a certain movement, the remaining length of the surface of the object to be gripped is less than the width of the sliding window, at which point the movement stops, and several gripping candidate regions are obtained during the entire movement process.

[0015] Surface structure feature data of each clamping candidate region are collected. The surface structure feature data specifically includes: the degree of undulation of the surface of each clamping candidate region and the surface roughness of the clamping candidate region.

[0016] Furthermore, the logic for evaluating the stability score of each candidate gripping region is as follows: The surface flatness coefficient of each candidate gripping region is calculated based on its surface structure feature data. This surface flatness coefficient is used to characterize the gripping difficulty of the candidate region. Based on the surface flatness coefficient and the distance between each candidate gripping region and the center of gravity of the object to be gripped, a comprehensive stability score for each candidate gripping region is calculated. The specific formula for calculating the surface flatness coefficient is as follows:

[0017] ;

[0018] In the formula, Let be the surface smoothness coefficient of the i-th candidate region. Let be the normalized value of the maximum fluctuation difference of the i-th pinch candidate region. Let be the normalized average roughness value of the i-th candidate region. and These are the weighting coefficients for the roughness and maximum fluctuation difference of the candidate region, respectively. ,and and All are greater than 0, where i is the index of the candidate region to be selected;

[0019] The maximum fluctuation difference of the i-th candidate region is specifically defined as the difference between the highest and lowest points on the surface of the i-th candidate region. The logic for obtaining the normalized value of the maximum fluctuation difference of the i-th candidate region is as follows: calculate the difference between the highest and lowest points of all candidate regions, determine the maximum difference, and normalize the maximum fluctuation difference of each candidate region by using the maximum difference. Specifically, the ratio of the maximum fluctuation difference of each candidate region to the maximum difference is used as the normalized value of the maximum fluctuation difference.

[0020] The average roughness of the selected candidate regions is used to characterize the undulation of the region. The formula used to calculate the normalized value of the average roughness of the i-th selected candidate region is as follows:

[0021] ;

[0022] In the formula, Let be the average roughness of the i-th candidate region. The maximum roughness of all candidate regions to be gripped, where the average roughness of the i-th candidate region is... The specific method for obtaining the roughness is as follows: Several detection sub-regions are randomly selected from the surface of the i-th candidate gripping region, and the average roughness of all detection sub-regions is calculated. This average roughness is then used as the average roughness of the candidate gripping region. The formula used to calculate the average roughness of all detection sub-regions is as follows:

[0023] ;

[0024] In the formula, Let be the roughness of the j-th detection sub-region within the surface of the i-th candidate gripping region, where j is the index of the detection sub-region. , This represents the total number of randomly selected detection sub-regions on the surface of the candidate region.

[0025] Furthermore, the formula used to calculate the stability score of each candidate region is as follows:

[0026] ;

[0027] In the formula, The stability score for the i-th candidate region is given. This represents the distance from the center of gravity of the i-th candidate gripping region to the center of gravity of the object to be gripped. Specifically, it refers to the straight-line distance from the center of gravity of the i-th candidate gripping region to the center of gravity of the object to be gripped. This represents the maximum distance from the center of gravity of the object to be grabbed across all candidate grabbing regions.

[0028] Based on the stability score of each candidate region, the candidate regions are sorted and formed into a sequence of candidate regions in descending order.

[0029] Furthermore, the logic for determining the maximum clamping force that each clamping candidate region can withstand based on the material characteristics of each clamping candidate region is as follows: construct a finite element model of each clamping candidate region, and through finite element analysis, determine the pressure that the object to be clamped experiences when the deformation of each clamping candidate region reaches the maximum irreversible deformation, and take this pressure as the maximum clamping force that the corresponding clamping candidate region can withstand.

[0030] The formula used to calculate the minimum clamping pressure for stable clamping, based on the weight of the object to be clamped, is as follows:

[0031] ;

[0032] In the formula, Let g be the weight of the object to be grasped. To determine the minimum clamping pressure for gripping the candidate region, The friction coefficient is used to select the candidate region.

[0033] Furthermore,

[0034] Following the sequence of candidate clamping regions, the minimum clamping pressure and the maximum clamping force that each candidate region can withstand are compared sequentially to determine whether each candidate region meets the clamping condition. The first candidate region that meets the clamping condition is designated as the final clamping position. Specifically, the clamping condition is that the product of the minimum clamping pressure and the maximum adjustment range of the candidate region is less than the maximum clamping force that the candidate region can withstand. The formula underlying this clamping condition is as follows:

[0035] ;

[0036] In the formula, For the maximum adjustment range, The maximum clamping force that the candidate region can withstand is yz, where yz is greater than 1.

[0037] Furthermore, the logic for dynamically adjusting the minimum clamping pressure based on the vibration and sliding parameters of the object to be clamped during transportation is as follows: The vibration parameters of the object to be clamped specifically refer to the vibration acceleration. The clamping pressure is increased by one tightening step length through a stepper motor. The maximum vibration acceleration and maximum sliding distance during transportation under the current clamping state are detected. It is determined whether the maximum vibration acceleration and maximum sliding distance fall within the preset corresponding safety range. If they both fall within the corresponding safety range, transportation is carried out with the current clamping pressure. If they do not both fall within the corresponding safety range, the clamping pressure is increased again by one tightening step length through a stepper motor on the current clamping pressure. It is further determined whether the maximum vibration acceleration and maximum sliding distance both fall within the corresponding safety range. This iterative operation is performed until the determined clamping pressure is met.

[0038] This invention also provides a stepper motor-based ring-type mechanical gripper control system, which is used to execute the above-mentioned stepper motor-based ring-type mechanical gripper control method, including:

[0039] The gripping region planning module is used to obtain the gripping width of the target encircling mechanical claw. Based on the gripping width of the target encircling mechanical claw, the object to be gripped is divided into several gripping candidate regions along the length direction of the object to be gripped, and the surface structure feature data of each gripping candidate region is collected.

[0040] The clamping force analysis module is used to evaluate the stability score of each clamping candidate region based on the surface structure feature data of each clamping candidate region and the distance between each clamping candidate region and the center of gravity of the object to be clamped. Based on the stability score of each clamping candidate region, the clamping candidate regions are arranged in descending order to form a clamping candidate region sequence.

[0041] The clamping area replacement module is used to determine the maximum clamping force that each clamping candidate area can withstand based on the order of the clamping candidate area sequence, and to calculate the minimum clamping pressure to ensure stable clamping at each clamping candidate area based on the gravity of the object to be clamped, and to compare the minimum clamping pressure with the maximum clamping force that can be withstood to determine the final clamping position.

[0042] The clamping force dynamic adjustment module is used to clamp the object to be clamped at the clamping position with the minimum clamping pressure. It sets the tightening step length of the stepper motor and dynamically adjusts the minimum clamping pressure according to the vibration and slippage parameters of the object to be clamped during transportation to complete the clamping control.

[0043] Compared with the prior art, the beneficial effects of the present invention are:

[0044] First, by obtaining the gripping width of the target encircling mechanical claw and dividing the object into several gripping candidate areas along its length, and combining the surface structure characteristics of each area for comprehensive evaluation, the area with the highest stability score is selected as the optimal gripping area, which effectively improves the gripping stability and reduces the risk of gripping failure.

[0045] Secondly, during the gripping process, the maximum gripping force that can be withstood is determined based on the material characteristics of the optimal gripping area. After determining the maximum gripping force that each candidate gripping area can withstand, the minimum gripping pressure required is calculated in combination with the weight of the object to be gripped. This further ensures the stability of the gripping, enables more precise control of the gripping force, and ensures that the gripping force matches the weight of the object in actual operation, avoiding the risk of the object slipping due to insufficient gripping force. At the same time, the mechanism for dynamically adjusting the minimum gripping pressure allows the mechanical gripper to respond to changes such as vibration and slippage in real time during transportation, significantly improving the robustness and adaptability of the overall gripping system, effectively preventing the object from slipping and being damaged, improving the safety of gripping, and also helping to maintain the stability of the object during transportation, thereby reducing the occurrence of accidents. Attached Figure Description

[0046] Figure 1This is a schematic diagram of the overall method flow of the present invention;

[0047] Figure 2 The curve fitting the distance from the center of gravity of the object to be clamped to the stability score;

[0048] Figure 3 The fitted curve of normalized average roughness value versus surface smoothness coefficient;

[0049] Figure 4 A graph showing the relationship between the normalized value of the maximum undulation difference and the surface smoothness coefficient;

[0050] Figure 5 This is a schematic diagram of the overall system structure of the present invention. Detailed Implementation

[0051] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to specific embodiments.

[0052] It should be noted that, unless otherwise defined, the technical or scientific terms used in this invention should have the ordinary meaning understood by one of ordinary skill in the art to which this invention pertains. The terms "first," "second," and similar terms used in this invention do not indicate any order, quantity, or importance, but are merely used to distinguish different components. Terms such as "comprising" or "including" mean that the element or object preceding the word encompasses the elements or objects listed following the word and their equivalents, without excluding other elements or objects. Terms such as "connected" or "linked" are not limited to physical or mechanical connections, but can include electrical connections, whether direct or indirect. Terms such as "upper," "lower," "left," and "right" are used only to indicate relative positional relationships; when the absolute position of the described object changes, the relative positional relationship may also change accordingly.

[0053] Example:

[0054] Please see Figures 1-4 The present invention provides a technical solution:

[0055] A method for controlling a ring-shaped mechanical gripper based on a stepper motor, comprising the following steps:

[0056] Step 1: Obtain the gripping width of the target gripping manipulator. Based on the gripping width of the target gripping manipulator, divide the object to be gripped into several gripping candidate regions along the length direction of the object to be gripped, and collect the surface structure feature data of each gripping candidate region.

[0057] The clamping width of the target encircling mechanical claw specifically refers to the clamping surface width of the target encircling mechanical claw;

[0058] The specific method used to obtain the clamping width of the target encircling robotic gripper is as follows: use precision measuring tools such as calipers and micrometers to actually measure the robotic gripper. During the measurement, ensure that the clamping surface is in an unclamped state to avoid errors caused by deformation. If there is a 3D model of the robotic gripper, computer-aided design (CAD) software such as SolidWorks and AutoCAD can be used for measurement. In the software, directly select the clamping width of the target encircling robotic gripper for accurate measurement.

[0059] Based on the gripping width of the target encircling robotic gripper, the object to be gripped is divided into several gripping candidate areas along the length direction of the object to be gripped. The specific logic is as follows: a sliding window is set with the gripping width of the target encircling robotic gripper, and the gripping width is the width of the sliding window. One end of the sliding window is set on one side of the edge of the object to be gripped along the length direction of the object to be gripped. The sliding window is controlled to move along the length direction of the object to be gripped in increments of 2 units. Each time it moves, the area where the sliding window is located is recorded as a gripping candidate area. The movement stops when the remaining length of the surface of the object to be gripped is less than the width of the sliding window after a certain movement. Several gripping candidate areas are obtained during the entire movement process, where the 2 units are specifically 2 centimeters.

[0060] Collect surface structure feature data for each candidate gripping region. The surface structure feature data specifically includes: the degree of undulation of the surface of each candidate gripping region and the surface roughness of the candidate gripping region.

[0061] The specific methods for obtaining the surface undulation of the candidate area to be gripped are as follows: The surface undulation reflects the overall shape change and height difference of the object's surface, which is mainly determined by measuring the contour characteristics of the surface. A 3D scanner is used to perform a non-contact scan of the candidate area to be gripped, generating a 3D model of the surface. The point cloud data generated by the scan is used to analyze the range of surface height variation, i.e., the difference between the maximum and minimum height, thereby obtaining the undulation. Alternatively, a laser profilometer is used to measure the vertical distance change of the surface along a certain direction to generate a surface contour. The maximum height difference and average height change of the contour line are calculated by software to obtain the surface undulation.

[0062] The specific method for obtaining the surface roughness of the candidate area is as follows: Surface roughness reflects the fineness of the microstructure of an object's surface. It is usually determined by measuring the texture characteristics of the surface or the small-scale height changes of the surface. A roughness measuring instrument, such as a portable surface roughness meter, is used to measure the surface micro-texture through contact or non-contact methods; or optical interferometry is used to measure the micro-height changes of the surface through light wave interference, generate a micro-height distribution map of the surface, and calculate the roughness parameters.

[0063] Step 2: Based on the surface structure feature data of each gripping candidate region and the distance between each gripping candidate region and the center of gravity of the object to be gripped, evaluate the stability score of each gripping candidate region. Based on the stability score of each gripping candidate region, form a sequence of gripping candidate regions by arranging them in descending order.

[0064] The logic behind evaluating the stability score of each candidate gripping region is as follows: The surface flatness coefficient of each candidate gripping region is calculated based on its surface structure feature data. This coefficient is used to characterize the gripping difficulty of the candidate region. Finally, the stability score of each candidate gripping region is calculated by combining the surface flatness coefficient with the distance between the candidate region and the center of gravity of the object to be gripped. The specific formula for calculating the surface flatness coefficient is as follows:

[0065] ;

[0066] In the formula, Let be the surface smoothness coefficient of the i-th candidate region. Let be the normalized value of the maximum fluctuation difference of the i-th pinch candidate region. Let be the normalized average roughness value of the i-th candidate region. and These are the weighting coefficients for the roughness and maximum fluctuation difference of the candidate region, respectively. ,and and All are greater than 0, where i is the index of the candidate region to be selected;

[0067] It should be noted that the surface flatness coefficient of the i-th candidate region is... This tool is used to characterize the ease of gripping a candidate region, primarily quantifying its surface features for comparison with other candidate regions. It comprehensively considers two dimensions: surface roughness and surface undulation, helping to determine whether the object is prone to slippage during gripping, whether the gripping force is sufficient, and the stability of the contact. A higher value indicates a more stable contact and a lower difficulty in clamping.

[0068] Surface roughness is an important indicator of surface microstructure. Higher roughness results in greater surface friction and stronger clamping stability. Therefore, the normalized average roughness value of the i-th clamping candidate region is... and Proportional, using the square root of the average roughness normalized value of the i-th pinch candidate region to... Calculate the flatness factor to emphasize its impact on clamping stability;

[0069] Surface undulation difference is an important indicator of macroscopic surface characteristics, reflecting shape changes on a large scale. The maximum undulation difference typically represents the overall height difference between convex and concave areas on the surface of the gripping candidate region, i.e., the difference between the maximum and minimum heights. This directly affects the contact quality between the robotic gripper and the object surface. A large surface height difference means that the gripping surface of the robotic gripper may not be able to fully conform to the object surface during contact, leading to uneven force distribution or unstable gripping. In this case, gripping difficulty increases and stability decreases. A relatively flat surface means that the robotic gripper can make more uniform contact with the object surface, thereby enhancing gripping stability and reducing the risk of slippage or loosening. Therefore, the normalized value of the maximum undulation difference of the i-th gripping candidate region is... Inversely proportional, through logarithmic transformation The normalized value of the largest fluctuation difference is processed to reduce its influence. The logarithmic function property means that for smaller fluctuation differences, the increase in influence is small, while for larger fluctuation differences, the influence gradually decreases, reflecting a non-linear relationship.

[0070] The maximum fluctuation difference of the i-th candidate region is specifically defined as the difference between the highest and lowest points on the surface of the i-th candidate region. The logic for obtaining the normalized value of the maximum fluctuation difference of the i-th candidate region is as follows: calculate the difference between the highest and lowest points of all candidate regions, determine the maximum difference, and normalize the maximum fluctuation difference of each candidate region by using the maximum difference. Specifically, the ratio of the maximum fluctuation difference of each candidate region to the maximum difference is used as the normalized value of the maximum fluctuation difference.

[0071] The average roughness of the selected candidate regions is used to characterize the undulation of the region. The formula used to calculate the normalized value of the average roughness of the i-th selected candidate region is as follows:

[0072] ;

[0073] In the formula, Let be the average roughness of the i-th candidate region. The maximum roughness of all candidate regions to be gripped, where the average roughness of the i-th candidate region is... The specific method for obtaining the roughness is as follows: Several detection sub-regions are randomly selected from the surface of the i-th candidate gripping region, and the average roughness of all detection sub-regions is calculated. This average roughness is then used as the average roughness of the candidate gripping region. The formula used to calculate the average roughness of all detection sub-regions is as follows:

[0074] ;

[0075] In the formula, Let be the roughness of the j-th detection sub-region within the surface of the i-th candidate gripping region, where j is the index of the detection sub-region. , The total number of detection sub-regions randomly selected on the surface of the candidate gripping region; where the roughness and undulation degree mentioned above specifically refer to the undulation degree and roughness of the contact gripping surface between the target encircling mechanical claw and each candidate gripping region.

[0076] The formula used to calculate the stability score of each candidate region is as follows:

[0077] ;

[0078] In the formula, The stability score for the i-th candidate region is given. This represents the distance from the center of gravity of the i-th candidate gripping region to the center of gravity of the object to be gripped. Specifically, it refers to the straight-line distance from the center of gravity of the i-th candidate gripping region to the center of gravity of the object to be gripped. This represents the maximum distance from the center of gravity of the object to be grabbed across all candidate grabbing regions.

[0079] It should be noted that, Indicates the first A stability score is given for each candidate gripping region. This score aims to comprehensively evaluate the potential stability of each candidate gripping region during the gripping process, specifically characterizing it by combining the surface flatness coefficient and the distance to the center of gravity of the object to be gripped. A larger value indicates a more stable selection of candidate regions and a higher selection priority.

[0080] A high surface flatness coefficient This means that the candidate region for gripping is of good quality, has high stability, and is relatively easy to grip. and Proportional;

[0081] When the candidate gripping area is located far from the object's center of gravity, the gripping force applied at that location will generate a larger torque. Torque is the product of force and distance; the greater the distance, the larger the torque generated by the applied force. During gripping, a larger torque may cause the object to rotate or tilt, increasing the risk of slipping or falling. In this case, gripping stability is compromised. The object's center of gravity is the center of its mass distribution. If the gripping point is too far from the center of gravity, the object may be more prone to losing balance under gravity. Especially when the object is irregular or has a complex shape, the gripping point needs to be chosen close to the center of gravity to ensure that the object does not tilt or flip during gripping. A gripping area that is far away may cause the object's center of gravity to not coincide with the line of action of the gripping force, thus affecting overall stability. Therefore, the farther the distance, the lower the stability score. and Inversely proportional, by normalizing the distance to the maximum distance This allows for comparison of the impact of distance between different candidate regions.

[0082] Based on the stability score of each candidate region, the candidate regions are sorted and formed into a sequence of candidate regions in descending order.

[0083] Step 3: Based on the order of the candidate clamping regions, determine the maximum clamping force that each candidate clamping region can withstand. Based on the weight of the object to be clamped, calculate the minimum clamping pressure that ensures stable clamping at each candidate clamping region. Compare the minimum clamping pressure with the maximum clamping force that can be withstood to determine the final clamping position.

[0084] The logic behind determining the maximum clamping force that each clamping candidate region can withstand based on the material characteristics of each clamping candidate region is as follows: construct a finite element model of each clamping candidate region, and through finite element analysis, determine the pressure that the object to be clamped experiences when the deformation of each clamping candidate region reaches the maximum irreversible deformation, and take this pressure as the maximum clamping force that the corresponding clamping candidate region can withstand.

[0085] The specific steps include: determining the material properties of each part of the object to be clamped, such as elastic modulus, yield strength, and Poisson's ratio; using computer-aided design (CAD) software, such as SolidWorks or AutoCAD, to create a three-dimensional geometric model of the object and clamping device, including the shape, size, and relative position of the clamping area; inputting physical parameters such as elastic modulus, yield strength, and Poisson's ratio into the finite element software based on material characteristic data to ensure that the model reflects the mechanical behavior of the actual material; setting fixed boundary conditions for the model according to the actual situation; fixing the bottom of the object or the support part of the clamping device; applying uniform pressure to the stress area; running finite element analysis to calculate parameters such as stress, strain, and deformation during the pressure application process.

[0086] The formula used to calculate the minimum clamping pressure for stable clamping, based on the weight of the object to be clamped, is as follows:

[0087] ;

[0088] In the formula, Let g be the weight of the object to be grasped. To determine the minimum clamping pressure for gripping the candidate region, The friction coefficient of the candidate gripping area refers to the friction coefficient between the target encircling mechanical claw and the contact gripping surface of each candidate gripping area.

[0089] It's important to note that during clamping, to prevent the object from slipping, its weight must be overcome. For the object to remain stationary, the frictional force generated during clamping must be greater than or equal to its resistance to gravity. This formula is based on the principle of frictional equilibrium. Insufficient clamping pressure may cause the frictional force to be unable to overcome gravity, resulting in unstable clamping and the object slipping or falling off. Calculating the minimum required clamping pressure ensures the safety and stability of the clamping process.

[0090] The specific method for obtaining the friction coefficient of the candidate region is as follows: the value of the friction coefficient is usually listed in the material's technical manual, engineering standards, and scientific literature. The friction coefficients of many common materials such as metals, plastics, and rubber with different surfaces such as smooth, rough, and coated surfaces have been extensively studied and recorded, or the friction coefficients are measured through friction tests.

[0091] Following the sequence of candidate clamping regions, the minimum clamping pressure and the maximum clamping force that each candidate region can withstand are compared sequentially to determine whether each candidate region meets the clamping condition. The first candidate region that meets the clamping condition is designated as the final clamping position. Specifically, the clamping condition is that the product of the minimum clamping pressure and the maximum adjustment range of the candidate region is less than the maximum clamping force that the candidate region can withstand. The formula underlying this clamping condition is as follows:

[0092] ;

[0093] In the formula, For the maximum adjustment range, This represents the maximum clamping force that the candidate area can withstand, where yz is greater than 1. The specific value can be set based on expert experience, generally between 1.2 and 1.8. The logic behind this setting is as follows: During transportation, external environmental interference may affect the clamping situation. Since clamping is performed with minimum clamping pressure, increasing the clamping pressure is necessary to achieve stable transportation when the clamping situation is affected. Therefore, the maximum adjustment range is used... As a control margin, it ensures that increasing the clamping pressure during transportation will not cause deformation of the object being clamped.

[0094] According to the order of the candidate clamping regions, the minimum clamping pressure of each candidate clamping region is calculated in turn, and it is determined in turn whether the clamping condition is met. If the clamping condition is met, the current candidate clamping region is the final clamping position; otherwise, the current candidate clamping region is changed. Specifically, the current clamping region is changed in turn according to the candidate clamping region sequence until the clamping condition is met.

[0095] Step 4: Clamp the object to be clamped at the clamping position with the minimum clamping pressure, set the tightening step length of the stepper motor, and dynamically adjust the minimum clamping pressure according to the vibration and slippage parameters of the object to be clamped during transportation to complete the clamping control.

[0096] The logic for dynamically adjusting the minimum clamping pressure based on the vibration and sliding parameters of the object to be clamped during transportation is as follows: The vibration parameters of the object to be clamped specifically refer to the vibration acceleration. The clamping pressure is increased by one tightening step length through a stepper motor. The maximum vibration acceleration and maximum sliding distance during transportation under the current clamping state are detected. It is determined whether the maximum vibration acceleration and maximum sliding distance fall within the preset corresponding safety range. If they both fall within the corresponding safety range, transportation is carried out with the current clamping pressure. If they do not both fall within the corresponding safety range, the clamping pressure is increased again by one tightening step length through a stepper motor on the current clamping pressure. It is further determined whether the maximum vibration acceleration and maximum sliding distance both fall within the corresponding safety range. This iterative operation is performed until the determined clamping pressure is met.

[0097] The preset corresponding safety range includes a vibration acceleration safety range and a slip distance safety range. The minimum value of each range is 0, and the maximum value is set by the maximum vibration acceleration and slip distance corresponding to the actual transportation without safety issues.

[0098] By monitoring the vibration acceleration and sliding distance of the object to be clamped in real time, the clamping pressure can be dynamically adjusted, ensuring that the clamping force is always within a safe and effective range. This significantly enhances clamping stability and reduces the risk of the object sliding or falling during transportation due to vibration or external impact. The logic of dynamically adjusting the clamping pressure ensures that the clamping force does not exceed the maximum bearing capacity of the clamping candidate area, avoiding structural damage or material fatigue caused by excessive clamping force. During clamping, the tightening step size of the stepper motor can precisely control the changes in clamping force. By increasing the clamping pressure only when necessary, unnecessary energy consumption can be effectively reduced, avoiding energy waste caused by over-clamping.

[0099] Please see Figure 5 The present invention also provides a stepper motor-based ring-type mechanical gripper clamping control system, wherein the stepper motor-based ring-type mechanical gripper clamping control system is used to execute the above-mentioned stepper motor-based ring-type mechanical gripper clamping control method, including:

[0100] The gripping region planning module is used to obtain the gripping width of the target encircling mechanical claw. Based on the gripping width of the target encircling mechanical claw, the object to be gripped is divided into several gripping candidate regions along the length direction of the object to be gripped, and the surface structure feature data of each gripping candidate region is collected.

[0101] The clamping force analysis module is used to evaluate the stability score of each clamping candidate region based on the surface structure feature data of each clamping candidate region and the distance between each clamping candidate region and the center of gravity of the object to be clamped. Based on the stability score of each clamping candidate region, the clamping candidate regions are arranged in descending order to form a clamping candidate region sequence.

[0102] The clamping region replacement module is used to determine the maximum clamping force that each clamping candidate region can withstand in sequence based on the order of the clamping candidate region sequence. Using the maximum clamping force that can withstand as a constraint, the minimum clamping pressure for stable clamping is calculated based on the gravity of the object to be clamped. Based on the comparison between the minimum clamping pressure and the maximum clamping force that can withstand, the clamping candidate regions that meet the clamping conditions are determined.

[0103] The clamping force dynamic adjustment module is used to clamp the object to be clamped with the minimum clamping pressure in the clamping candidate area that meets the clamping conditions. It sets the tightening step length of the stepper motor and dynamically adjusts the minimum clamping pressure according to the vibration and sliding parameters of the object to be clamped during transportation to complete the clamping control.

[0104] The above formulas are all dimensionless calculations. The formulas are derived from software simulations based on a large amount of collected data to obtain the most recent real-world results. The preset parameters in the formulas are set by those skilled in the art according to the actual situation.

[0105] The above embodiments can be implemented, in whole or in part, by software, hardware, firmware, or any other combination thereof. When implemented in software, the above embodiments can be implemented, in whole or in part, as a computer program product. Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented by electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution.

[0106] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment, depending on actual needs.

[0107] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any changes or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application.

Claims

1. A stepping motor-based ring-type mechanical gripper clamping control method, characterized by, The specific steps include: Obtaining the clamping width of the target ring-shaped mechanical claw, based on the clamping width of the target ring-shaped mechanical claw, dividing the object to be clamped into a plurality of clamping candidate regions along the length direction of the object to be clamped, and collecting surface structure feature data of each clamping candidate region; According to the surface structure feature data of each clamping candidate region, in combination with the distance between each clamping candidate region and the center of gravity of the object to be clamped, the stability score of each clamping candidate region is evaluated, and based on the stability score of each clamping candidate region, a clamping candidate region sequence is formed in descending order; Based on the order of the clamping candidate region sequence, the maximum clamping force that each clamping candidate region can withstand is determined in sequence, and based on the gravity of the object to be clamped, the minimum clamping pressure required to ensure stable clamping at each clamping candidate region is calculated, and the minimum clamping pressure is compared with the maximum clamping force that can be Withstood, the final clamping position is determined; The object to be clamped is clamped at the clamping position with the minimum clamping pressure, the tightening step of the stepping motor is set, and the minimum clamping pressure is dynamically adjusted according to the vibration and slip parameters of the object to be clamped in the transportation process to complete the clamping control; The clamping width of the target ring-shaped mechanical claw specifically refers to the clamping face width of the target ring-shaped mechanical claw; Based on the clamping width of the target ring-shaped mechanical claw, the object to be clamped is divided into a plurality of clamping candidate regions along the length direction of the object to be clamped. The logic is as follows: a sliding window is set with the clamping width of the target ring-shaped mechanical claw, the clamping width is the width of the sliding window, one end of the sliding window is set on one side of the edge of the object to be clamped in the length direction, the sliding window is controlled to move along the length direction of the object to be clamped by 2 unit lengths each time, and each time the sliding window is moved, the region where the sliding window is located is recorded as a clamping candidate region. Until after a certain movement, the remaining length of the surface of the object to be clamped is less than the width of the sliding window, stop moving, and obtain a plurality of clamping candidate regions in the entire movement process; The surface structure feature data of each clamping candidate region includes the degree of fluctuation of the surface of each clamping candidate region and the surface roughness of the clamping candidate region; The logic for evaluating the stability score of each clamping candidate region is as follows: the surface flatness coefficient of each clamping candidate region is calculated based on the surface structure feature data of each clamping candidate region, the clamping difficulty of the clamping candidate region is represented according to the surface flatness coefficient, and the stability score of each clamping candidate region is calculated in combination with the distance between each clamping candidate region and the center of gravity of the object to be clamped according to the surface flatness coefficient. The formula for calculating the surface flatness coefficient is: wherein, is the surface flatness coefficient of the i-th clamped candidate region, is the maximum undulation difference normalized value of the i-th clamped candidate region, is the average roughness normalized value of the i-th clamped candidate region, and are the weight coefficients of the roughness and the maximum undulation difference of the clamped candidate region, respectively, wherein , and and are both greater than 0, and i is the index of the clamped candidate region. The maximum fluctuation difference of the ith clamping candidate region is specifically defined as the difference between the highest point and the lowest point in the surface of the ith clamping candidate region, and the logic for obtaining the maximum fluctuation difference normalization value of the ith clamping candidate region is as follows: the difference between the highest point and the lowest point of all clamping candidate regions is calculated, the maximum difference value is determined, and the maximum fluctuation difference of each clamping candidate region is normalized by the maximum difference value. Specifically, the ratio of the maximum fluctuation difference of each clamping candidate region to the maximum difference value is taken as the maximum fluctuation difference normalization value. The average roughness of the clamping candidate region is used to represent the fluctuation degree of the region, and the formula for calculating the average roughness normalization value of the ith clamping candidate region is: In the formula, is the average roughness of the i-th clamping candidate region, is the maximum roughness of all clamping candidate regions, wherein the average roughness of the i-th clamping candidate region The specific acquisition manner is that a plurality of detection sub-regions are randomly selected on the surface of the i-th clamping candidate region, and the average roughness of all detection sub-regions is calculated, and the average roughness is taken as the average roughness of the clamping candidate region. The formula for calculating the average roughness of all detection sub-regions is: In the formula, is the roughness of the jth detection sub-region in the ith clip candidate region surface, wherein j is the index of the detection sub-region, , is the total number of randomly selected detection sub-regions on the clip candidate region surface. The formula for calculating the stability score of each clamping candidate region is: In the formula, is the stability score of the i-th grasp candidate region, is the distance from the i-th grasp candidate region to the center of gravity of the object to be grasped, specifically, the straight-line distance from the center of gravity of the i-th grasp candidate region to the center of gravity of the object to be grasped, is the maximum value of the distance from the center of gravity of the object to be grasped among all grasp candidate regions; Based on the stability score of each clamping candidate region, the clamping candidate regions are sorted in descending order to form a clamping candidate region sequence.

2. The method according to claim 1, wherein the method is characterized by: The logic for determining the maximum clamping force that each clamping candidate region can withstand based on the material characteristics of each clamping candidate region is as follows: a finite element model of each clamping candidate region is constructed, the pressure that the deformation of each clamping candidate region of the object to be clamped reaches the maximum irreversible deformation is determined through finite element analysis, and this pressure is taken as the maximum clamping force that the corresponding clamping candidate region can withstand. The formula for calculating the minimum clamping pressure based on the gravity of the object to be clamped is: wherein is the weight of the object to be gripped, is the minimum gripping pressure of the gripping candidate region, is the friction coefficient of the gripping candidate region.

3. The method according to claim 2, wherein the method is characterized by: According to the order of the clamping candidate region sequence, the minimum clamping pressure and the maximum clamping force that each clamping candidate region can withstand are compared in turn to determine whether each clamping candidate region meets the clamping condition. The first clamping candidate region that meets the clamping condition is the final clamping position. The clamping condition is specifically that the product of the minimum clamping pressure and the maximum adjustment amplitude of the clamping candidate region is less than the maximum clamping force that the clamping candidate region can withstand. The formula for the clamping condition is: wherein is the maximum adjustment amplitude, is the maximum gripping force that can be sustained by the candidate region, wherein yz is greater than 1.

4. The method of claim 3, wherein the method further comprises: The logic for dynamically adjusting the minimum clamping pressure based on the vibration and slip parameters of the object to be clamped during transportation is as follows: the vibration parameter of the object to be clamped is specifically the vibration acceleration, the clamping pressure is increased by one tightening step through the stepping motor, the maximum vibration acceleration and the maximum slip distance during transportation under the current clamping state are detected, and it is determined whether the maximum vibration acceleration and the maximum slip distance fall within the corresponding safety interval. If both fall within the corresponding safety interval, the current clamping pressure is used for transportation. If neither falls within the corresponding safety interval, the clamping pressure is increased by one tightening step through the stepping motor again, and it is further determined whether the maximum vibration acceleration and the maximum slip distance fall within the corresponding safety interval. The iteration operation is performed in turn until the determination of the clamping pressure is satisfied.

5. A stepper motor based wraparound gripper clamping control system, characterized by: The ring-type mechanical gripper clamping control system based on the stepping motor is used to execute the ring-type mechanical gripper clamping control method based on the stepping motor in any one of claims 1-4, which comprises: The clamping region planning module is configured to obtain a clamping width of the target ring-type mechanical gripper, divide the object to be clamped into a plurality of clamping candidate regions along a length direction of the object to be clamped based on the clamping width of the target ring-type mechanical gripper, and collect surface structure feature data of each clamping candidate region; The clamping force analysis module is configured to evaluate a stability score of each clamping candidate region according to the surface structure feature data of each clamping candidate region and a distance between each clamping candidate region and a gravity center of the object to be clamped, and form a clamping candidate region sequence in a descending order based on the stability score of each clamping candidate region; The clamping region replacement module is configured to determine a maximum clamping force that can be borne by each clamping candidate region in a sequence of the clamping candidate region sequence, calculate a minimum clamping pressure for ensuring stable clamping at each clamping candidate region based on a gravity of the object to be clamped, and determine a final clamping position by comparing the minimum clamping pressure with the maximum clamping force that can be borne. The clamping force dynamic adjustment module is configured to clamp the object to be clamped at the final clamping position with the minimum clamping pressure, set a tightening step length of a stepping motor, and dynamically adjust the minimum clamping pressure according to vibration and slip parameters of the object to be clamped in a transportation process to complete clamping control.

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