A palletizing method and a palletizing workstation

Abstract

The present application relates to the technical field of stacking robots, and particularly relates to a stacking method and a stacking workstation, and the present application effectively prevents potential risks such as over-limit operation, overload, positioning error and the like of a mechanical arm through a multi-stage security verification mechanism and dynamic closed-loop control. In particular, the adaptive speed reduction reset, abnormal pop-up prompt and one-key calibration function reduce the possibility of operation errors and equipment damage, guarantee the safe and stable operation in the man-machine cooperation environment, and at the same time reduce the downtime caused by faults.

Description

Technical Field

[0001] This invention relates to the field of palletizing robot technology, and in particular to a palletizing method and a palletizing workstation thereof. Background Technology

[0002] Currently, palletizing is the process of stacking packages, containers, or bulk materials onto pallets according to preset rules, and it is a key link in the logistics and manufacturing fields. Its core value lies in maximizing stacking density to reduce storage / transportation space and standardizing specifications to facilitate automated handling.

[0003] However, the current technology for palletizing materials has the following technical problems:

[0004] 1. Traditional palletizing systems lack effective active protection mechanisms, relying solely on passive protection measures such as emergency stop buttons. These measures cannot predict the risk of joint overload or exceeding limits during robotic arm movement. This passive protection method leads to frequent hardware damage such as robotic arm collisions and motor burnouts. Furthermore, fault location is difficult, often requiring engineers to disassemble and debug on-site, causing prolonged production line downtime and resulting in significant economic losses.

[0005] 2. The existing palletizing system uses a rigid gripping strategy, which is difficult to adapt to the complex and ever-changing characteristics of materials. The fixed vacuum pressure and gripping angle cannot cope with common situations in actual production, such as the expansion of cartons due to moisture and oil stains on the surface of metal cans, resulting in a high failure rate for gripping irregularly shaped materials. In addition, the debugging data and the system lack effective linkage, and parameters need to be reconfigured every time production lines are changed. Cross-model adaptation is time-consuming and seriously affects production efficiency.

[0006] 3. Traditional palletizing systems have limited human-machine interfaces, failing to provide visualized configuration and status feedback for palletizing parameters, making it difficult for operators to intuitively grasp the palletizing progress. Furthermore, the robotic arm's reset process lacks intelligent control, posing safety hazards during zeroing operations, and the cumbersome anomaly handling procedures increase operational difficulty and the risk of errors.

[0007] Existing technologies lack effective closed-loop optimization mechanisms, and debugging parameters cannot be back-synchronized to the system. This results in repeated debugging for each anomaly handling, hindering the accumulation of experience and continuous system optimization. These problems severely restrict the efficiency and quality improvement of palletizing operations. Therefore, a palletizing method and its workstation that can solve the above problems are needed. Summary of the Invention

[0008] This invention provides a palletizing method and its palletizing workstation. Through a multi-level safety verification mechanism (servo enable status detection, joint position compliance verification, and real-time vacuum pressure monitoring) and dynamic closed-loop control (load feedback linkage adjustment trajectory, automatic pause and calibration for position exceeding limits), this invention effectively prevents potential risks such as robotic arm over-limit operation, overload, and positioning errors. In particular, adaptive speed reduction and reset, abnormal pop-up prompts, and one-click calibration functions reduce the possibility of operational errors and equipment damage, ensuring safe and stable operation in a human-machine collaborative environment, while also reducing downtime due to malfunctions.

[0009] The technical solution adopted by the present invention to solve the above-mentioned technical problems is as follows:

[0010] A palletizing method includes the following steps:

[0011] Step S1: Configure stack type parameters and provide visual feedback on status through the human-computer interaction interface, including:

[0012] The encoder parameters and motion constraints of the multi-axis robot arm are automatically loaded according to the selected model.

[0013] Edit multi-layer palletizing styles in the visual interface, and dynamically distinguish the palletizing status of completed and incomplete materials through preset labels;

[0014] Step S2: Perform multi-level safety verification and multi-axis robot arm reset control, including:

[0015] Check the servo system enable status of the multi-axis robot and the compliance of the robot arm joint positions;

[0016] When the robotic arm of the multi-axis robot triggers the zero-return operation, an interactive confirmation process is generated based on the real-time position deviation. After confirmation, the robotic arm of the multi-axis robot is reset using an adaptive deceleration algorithm.

[0017] Step S3: Dynamic closed-loop control and real-time anomaly monitoring, including:

[0018] The motion trajectory of the robotic arm of a multi-axis robot is adjusted based on the linkage between global velocity parameters and load feedback signals.

[0019] The position coordinate accuracy of the adsorption mechanism is checked in real time. If the accuracy exceeds the limit, a calibration command is triggered and the task is paused.

[0020] Step S4: Dynamically adjust the robotic arm grasping strategy of the multi-axis robot based on the material status;

[0021] Step S5: Correct the abnormal motion parameters of the multi-axis robot through the manual debugging mode in the human-machine interface, and synchronize the debugged motion parameters back to the stack configuration system to achieve closed-loop optimization.

[0022] Furthermore, step S1 specifically includes:

[0023] Step S1-1: Load the encoder disk size and the joint limit parameters of the multi-axis robot arm according to the selected model;

[0024] Step S1-2: In the touch-screen human-machine interface, define the material layout by dragging and dropping. If the distance between adjacent materials is less than the safety threshold, it will be automatically highlighted in red.

[0025] Steps S1-3: Generate yellow markers for materials that have been palletized, and retain white markers for materials that have not been palletized. The display can be switched according to the layer number of each palletized layer.

[0026] Furthermore, step S2 includes:

[0027] Step S2-1: When checking the servo enable status of the multi-axis robot, simultaneously check the vacuum pressure value of the suction mechanism at the end of the multi-axis robot arm. If the pressure is abnormal, start-up is prohibited.

[0028] Step S2-2: After triggering the zero-return operation, a pop-up window displays the deviation distance between the current position of the multi-axis robot arm and the zero position, as well as the estimated zero-return time.

[0029] Step S2-3: During the zeroing process, if the joint position exceeds the limit, the zeroing process will be paused and a pop-up window will display the number of the joint that exceeded the limit.

[0030] Furthermore, step S3 includes the following sub-steps:

[0031] Step S3-1: Adjust the motion acceleration of the multi-axis robot's robotic arm in real time according to the global velocity parameters of the multi-axis robot, and calculate the remaining task time;

[0032] Step S3-2: Monitor the load current. If it exceeds the limit for 3 consecutive seconds, automatically reduce the speed of the multi-axis robot's robotic arm to a safe value and generate a warning log.

[0033] Step S3-3: Collect the actual position coordinates of the adsorption mechanism. If the deviation from the preset position coordinates exceeds ±50mm, the abnormal point will be highlighted.

[0034] Step S3-4: After pausing the task, perform a one-click calibration through the human-machine interface. After the calibration is completed, the multi-axis robot will automatically resume operation.

[0035] Furthermore, step S4 includes:

[0036] Step S4-1: The material size is identified in real time by the laser profile sensor, the material weight is estimated by the end force sensor of the adsorption mechanism, and the surface characteristics of the material are judged based on the vacuum pressure fluctuation and leakage rate of the adsorption mechanism.

[0037] Step S4-2: Dynamically adjust the vacuum pressure threshold of the adsorption mechanism and the gripping angle of the multi-axis robot arm according to the material size, material weight and material surface characteristics.

[0038] Step S4-3: Encrypt and store the updated parameters and synchronize them to the stack configuration system.

[0039] Furthermore, step S5 includes:

[0040] Step S5-1: In manual debugging mode, switch to tool coordinate system to control the movement of the multi-axis robot arm, and limit the jogging speed of the multi-axis robot arm to 10%-30% of the global speed of the multi-axis robot;

[0041] Step S5-2: After debugging, generate a parameter modification comparison report, which is then hash-encrypted and synchronized to the stack configuration system.

[0042] A palletizing workstation includes a support frame, a base, and a multi-axis robot. The base is fixedly connected to the support frame and has a touch-screen human-machine interface and control buttons installed on it. The multi-axis robot is mounted on the base and has an adsorption mechanism for gripping and placing materials installed on it.

[0043] Furthermore, a multi-axis robot is a robot with multiple robotic arms connected in sequence.

[0044] The advantages of this invention are:

[0045] 1. This invention effectively prevents potential risks such as excessive operation, overload, and positioning errors of the robotic arm through a multi-level safety verification mechanism (servo enable status detection, joint position compliance verification, and real-time vacuum pressure monitoring) and dynamic closed-loop control (load feedback linkage adjustment trajectory, automatic pause and calibration when position exceeds limits). In particular, the adaptive deceleration reset, abnormal pop-up prompts, and one-click calibration functions reduce the possibility of operational errors and equipment damage, ensuring safe and stable operation in a human-machine collaborative environment, while also reducing downtime caused by malfunctions.

[0046] 2. The palletizing method provided by this invention deeply integrates real-time perception and dynamic decision-making. Utilizing laser contour sensors, end effector force sensors, and vacuum pressure data, the system can identify material size, weight, and surface characteristics in real time, and dynamically adjust the gripping strategy accordingly, significantly improving the robot's adaptability to different materials and its gripping success rate. Simultaneously, the linked adjustment of global speed and load feedback, strategy updates based on material state, and closed-loop optimization of debugging parameters enable the system to continuously learn and optimize, allowing it to cope with more complex real-world working conditions. Attached Figure Description

[0047] To more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the specific embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0048] Figure 1 This is a schematic diagram of the palletizing workstation in this invention;

[0049] like Figure 1 As shown, it includes: support frame 1, base 2, touch-screen human-machine interface 3, control buttons 4, multi-axis robot 5, and adsorption mechanism 6. Detailed Implementation

[0050] The technical solution of the present invention will now be clearly and completely described with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0051] Example 1:

[0052] This invention provides a palletizing method, comprising the following steps: Step S1: Configuring pallet type parameters and providing status visualization feedback through a human-machine interface, including: automatically loading pallet parameters and motion constraints of the multi-axis robot 5's robotic arm according to the selected model; editing multi-layer palletizing styles in the visualization interface and dynamically distinguishing the palletizing status of completed and incomplete materials through preset identifiers; Step S2: Performing multi-level safety verification and resetting control of the multi-axis robot 5's robotic arm, including: detecting the servo system enable status of the multi-axis robot 5 and the compliance of the robotic arm joint positions of the multi-axis robot 5; when the robotic arm of the multi-axis robot 5 triggers a zero-return operation, based on the real-time position deviation... The process involves generating an interactive confirmation process, followed by an adaptive deceleration algorithm to reset the robotic arm of the multi-axis robot 5. Step S3 involves dynamic closed-loop control and real-time anomaly monitoring, including: adjusting the robotic arm trajectory of the multi-axis robot 5 based on global speed parameters and load feedback signals; verifying the position coordinate accuracy of the adsorption mechanism 6 in real time, triggering a calibration command and pausing the task if the accuracy exceeds the limit; Step S4 involves dynamically adjusting the robotic arm gripping strategy of the multi-axis robot 5 based on the material status; Step S5 involves correcting the abnormal motion parameters of the multi-axis robot 5 through manual debugging mode in the human-machine interface, and then synchronizing the debugged motion parameters back to the stack configuration system to achieve closed-loop optimization.

[0053] The human-machine interface for configuring palletizing parameters and providing visual feedback on operational status refers to achieving parameter setting and visualization of operating status through a graphical user interface. Specifically, a touchscreen combined with a PLC communication protocol enables bidirectional data transmission, mapping equipment operating data to interface elements in real time. This feature solves the problems of complex parameter configuration and opaque operating status in traditional methods. Multi-level safety verification and robotic arm reset control involves constructing multiple protection mechanisms through servo system status detection, joint position verification, and vacuum pressure monitoring. Specifically, Hall effect sensors combined with encoder feedback achieve closed-loop position detection. This feature addresses the lack of predictive risk assessment for robotic arm movement by reducing the probability of equipment damage through real-time hardware status monitoring. Dynamic closed-loop control and real-time anomaly monitoring involve dynamically adjusting the motion trajectory and performing position accuracy verification based on load feedback. Specifically, a PID controller adjusts the motor speed, and a laser rangefinder performs coordinate calibration. This feature addresses motion trajectory deviations through real-time parameter adjustment, ensuring stable palletizing accuracy. Dynamic adjustment of the robotic arm's gripping strategy based on material status involves optimizing gripping parameters in real time based on sensor data. Specifically, laser contour sensors and force sensors are deployed to collect material physical properties, and fuzzy control algorithms are used to adjust the adsorption pressure. This feature addresses the poor adaptability of fixed-fetching strategies by enabling dynamic decision-making driven by multi-dimensional data. Specifically, the manual debugging mode's reverse synchronization to the stack configuration system allows for system-level data updates after manual parameter intervention. This can be achieved by establishing a real-time communication link between debugging parameters and the database using the OPC UA protocol. This feature forms a closed-loop optimization mechanism through human-machine collaboration, enhancing the system's adaptability across different operating conditions.

[0054] The core innovation of this invention lies in the construction of an intelligent palletizing control system that integrates multi-level safety protection, dynamic parameter adjustment, and two-way data linkage. Through a triple mechanism of real-time hardware status monitoring, adaptive material characteristic grasping, and human-machine collaborative parameter optimization, it systematically solves the problems of insufficient prediction of robotic arm movement risks and rigid grasping strategies, thereby achieving simultaneous improvement in equipment protection and operational efficiency.

[0055] The working process and principle of this invention are as follows: First, the palletizing parameters are configured and the status is visualized and fed back through a human-machine interface. Based on the selected machine model, the palletizing parameters and the motion constraints of the multi-axis robot 5 are automatically loaded. The multi-layer palletizing style is edited in the visualization interface, and preset labels dynamically distinguish the palletizing status of completed and incomplete materials. This step ensures the correct configuration of system parameters and real-time visualization monitoring of the status.

[0056] Next, multi-level safety verification and robotic arm reset control of multi-axis robot 5 are performed. The servo system enable status of multi-axis robot 5 and the compliance of the robotic arm joint positions are checked. When a zero-return operation is triggered, an interactive confirmation process is generated based on the real-time position deviation. After confirmation, an adaptive deceleration algorithm completes the robotic arm reset. This step ensures the safety and accuracy of robot operation.

[0057] Then, dynamic closed-loop control and real-time anomaly monitoring are implemented. The robot arm's trajectory is adjusted in conjunction with global speed parameters and load feedback signals, and the position coordinate accuracy of the adsorption mechanism 6 is verified in real time. If the accuracy exceeds the limits, a calibration command is triggered and the task is paused. This step achieves real-time optimization and anomaly handling of the robot's motion.

[0058] Furthermore, the robotic arm's gripping strategy is dynamically adjusted based on the material's state. This step improves the system's adaptability to different materials.

[0059] Finally, abnormal motion parameters are corrected through manual debugging mode in the human-computer interaction interface, and the debugged motion parameters are then back-synchronized to the stack configuration system to achieve closed-loop optimization. This step ensures continuous system optimization and parameter consistency.

[0060] As a preferred embodiment, the solution of the present invention is implemented as follows:

[0061] On the human-machine interface, after the operator selects a specific model, the system automatically loads the corresponding encoder parameters and robotic arm motion constraints. For example, the encoder size is 1200mm×1000mm, the range of motion of joint 1 of the robotic arm is -180° to +180°, and the range of motion of joint 2 is -90° to +90°, etc.

[0062] In the visual interface, material layout is defined by dragging and dropping. The system automatically calculates the spacing between adjacent materials and performs a safety check. Materials that have been palletized are displayed in yellow, while those that have not been palletized remain white. Operators can view the palletizing status of different layers using the layer number switching button.

[0063] Before initiating the palletizing task, the system first checks the servo system's enable status and the robotic arm's joint positions. If an anomaly is detected, such as a joint exceeding its limit, the system will display a warning and prevent the task from starting.

[0064] When the zero-return operation is triggered, the system calculates the deviation between the current position and the zero position and displays the estimated zero-return time. After operator confirmation, the robotic arm resets using an adaptive deceleration method, with the speed gradually increasing as the deviation decreases.

[0065] During the palletizing process, the system continuously monitors the load feedback signal. If a sudden increase in load is detected, the system will automatically reduce the movement speed of the robotic arm. At the same time, the position coordinates of the adsorption mechanism 6 are checked in real time. If the deviation exceeds a preset threshold, the system will pause the task and trigger a calibration process.

[0066] The system collects material information in real time through sensors, such as size, weight, and surface properties. Based on this data, it dynamically adjusts the adsorption pressure and gripping angle to adapt to different types of materials.

[0067] In case of any abnormality, the operator can enter manual debugging mode via the human-machine interface. In this mode, the robotic arm's movement speed is limited to 10%-30% of the global speed to ensure safety. After debugging, the modified parameters will be automatically synchronized to the stacking configuration system for subsequent task optimization.

[0068] Through the above solutions, this invention achieves comprehensive safety protection and dynamic optimization of the palletizing process. A multi-level safety verification mechanism effectively prevents the risk of the robotic arm exceeding its limits and overloading, reducing the probability of equipment damage. Dynamic closed-loop control and real-time anomaly monitoring improve the system's stability and reliability. Dynamic gripping strategy adjustments based on material status enhance adaptability to different materials and reduce gripping failure rates. Visual feedback and manual debugging functions of the human-machine interface simplify the operation process and shorten fault handling time. Automatic parameter synchronization and closed-loop optimization mechanisms improve the system's learning ability and long-term performance. These improvements work together to significantly enhance the safety, efficiency, and flexibility of the palletizing system, solving problems such as safety hazards, poor adaptability, and maintenance difficulties inherent in traditional palletizing methods.

[0069] The present invention further proposes specific steps for configuring pallet parameters through a touch-screen human-machine interface 3: loading the pallet size and robotic arm joint limit parameters according to the selected model; defining the material layout through drag-and-drop operation in the touch-screen human-machine interface 3, and automatically marking red if the distance between adjacent materials is less than the safety threshold; generating yellow marks for materials that have been palletized, and retaining white marks for materials that have not been palletized, and supporting switching the display according to the layer number of each palletized layer.

[0070] Among them, when loading the pallet size, the pallet size parameters corresponding to the model are matched by a preset database; the limit parameters of the robotic arm joints include the rotation angle range of each axis; the drag operation is implemented through graphical controls; the coordinate data of the material layout is mapped to the palletizing coordinate system in real time; the safety threshold is set according to 1.2 times the size of the material and the size of the robotic arm end effector; color marking is implemented by covering a semi-transparent layer; the layer number switching is triggered by the drop-down menu to refresh the interface.

[0071] Specifically, operators drag and drop material icons to the target location on the touchscreen interface, and the system calculates the edge spacing between adjacent materials in real time. When the spacing is less than the safety threshold, the adjacent area is automatically highlighted in red and a warning box pops up to prevent interference from the robotic arm during operation due to overly dense layout. After completing a single layer of palletizing, the system updates the corresponding material layer to yellow, while unfinished parts remain white. Operators can view the status of each layer individually through the layer number drop-down menu. For example, when the safety threshold is set to 50mm, if the spacing between two materials is 45mm, the interface immediately highlights it in red and prohibits confirmation of the operation, requiring adjustment to meet compliance before continuing. Thus, through graphical interaction and dynamic feedback, the error rate of manual configuration is reduced, and the efficiency of visual management of multi-layer palletizing is improved.

[0072] As a preferred embodiment, the solution of the present invention is implemented as follows:

[0073] In the touch-screen human-machine interface 3, the encoder parameters and the motion constraints of the multi-axis robot 5 are automatically loaded according to the selected model. Specifically, the system retrieves the corresponding encoder size information from the database based on the selected model, such as a length, width, and height of 1200mm, 1000mm, and 150mm respectively. At the same time, the system loads the joint limit parameters of the multi-axis robot 5 for that model, for example, the rotation angle range of the first axis is -170° to +170°, and the rotation angle range of the second axis is -90° to +130°.

[0074] Furthermore, operators define material layouts on the interface by dragging and dropping. The system calculates the distance between adjacent materials in real time, and when the distance is less than a preset safety threshold (e.g., 50mm), it automatically marks the corresponding location in red to indicate potential risks.

[0075] In addition, the system generates a yellow mark for materials that have been palletized, and retains a white mark for materials that have not been palletized. Operators can switch between displaying the palletizing status of different layers using interface buttons. For example, when selecting to display layer 3, the interface only shows the material layout and completion status of that layer.

[0076] Through the above technical solution, this invention achieves rapid loading and visual configuration of palletizing parameters. This improves operational efficiency and reduces human error. Simultaneously, the dynamic marking function allows operators to intuitively grasp the palletizing progress, facilitating timely adjustments to the production plan. The safety distance indicator mechanism effectively prevents collision risks caused by unreasonable material layout, enhancing overall production safety.

[0077] The present invention further proposes that when detecting the servo enable state of the multi-axis robot 5, the vacuum pressure value of the adsorption mechanism 6 at the end of the multi-axis robot 5 arm should be checked simultaneously. If the pressure is abnormal, the start-up should be prohibited. After triggering the zero-return operation, a pop-up window should be displayed to show the deviation distance between the current position of the multi-axis robot 5 arm and the zero position, as well as the estimated zero-return time. During the zero-return process, if the joint position exceeds the limit, the zero-return should be paused and the number of the joint that exceeds the limit should be displayed in a pop-up window.

[0078] The vacuum pressure value is detected by a pressure sensor, and the pressure threshold is preset according to the adsorption mechanism model 6. The pop-up display includes digital deviation, three-dimensional coordinate difference graph and countdown progress bar. The joint position over-limit judgment is based on the real-time comparison of joint encoder data and preset safety range.

[0079] Specifically, a vacuum pressure monitoring module is embedded in the servo enable status detection phase. When the detected pressure value is lower than the set threshold, the power output is immediately cut off to prevent starting with a fault. After the zero-return operation is initiated, the system automatically calculates the Euclidean distance between the end of the robotic arm and the zero reference point, and generates an estimated time display interface based on the movement speed of each axis. During the reset movement, the encoder data of each joint is collected in real time and compared with the stored safe position parameters. When any joint angle exceeds the safe range, the movement is immediately interrupted and an error code pop-up window containing the joint number is generated. The pressure abnormality prohibition start mechanism prevents material drop accidents caused by the failure of the adsorption mechanism 6; the deviation distance and time display allow the operator to predict the time cost of the reset process; the joint over-limit rapid positioning function shortens the troubleshooting time and avoids damage to the mechanical structure due to continuous erroneous movement.

[0080] As a preferred embodiment, the solution of the present invention is implemented as follows:

[0081] When detecting the servo enable status of the multi-axis robot 5, the vacuum pressure value of the end-effector adsorption mechanism 6 of the multi-axis robot 5 is simultaneously checked. If the pressure is abnormal, startup is prohibited. Specifically, the status feedback signal of the servo driver detects whether the servo system is enabled, while simultaneously collecting data from the vacuum pressure sensor of the end-effector adsorption mechanism 6. When the servo system is detected to be enabled and the vacuum pressure value is within the preset range, the robot is allowed to start operation. If the vacuum pressure is lower than the set threshold, the system will issue an alarm and prevent the robot from starting to prevent grasping failure.

[0082] After triggering the homing operation, a pop-up window displays the deviation distance between the current position and the zero position of the multi-axis robot's 5-arm manipulator, as well as the estimated homing time. For example, the current angle of each joint is read by the encoder and compared with the preset zero angle to calculate the spatial position deviation. Based on the maximum speed and acceleration parameters of each joint, the time required for homing is estimated. This information is presented in a pop-up window through the human-machine interface, making it easy for the operator to understand the homing process.

[0083] During the homing process, if a joint position exceeds its limit, the homing process is paused and a pop-up window displays the number of the joint that exceeded the limit. In practice, the system monitors the position feedback of each joint in real time. Once a joint exceeds its safety limit, an emergency stop signal is immediately triggered. At the same time, a warning window pops up on the human-machine interface, clearly identifying the specific joint number that exceeded the limit, guiding maintenance personnel to quickly locate the problem.

[0084] Through the above technical solutions, this invention achieves multi-level safety verification and intelligent zero-return control. Dual checks of servo enable status and vacuum pressure effectively prevent the robot from accidentally starting under abnormal conditions. Real-time position monitoring and over-limit protection during the zero-return process reduce the risk of mechanical collisions. Simultaneously, intuitive information feedback enhances the operator's perception of the equipment status, helping to promptly detect and handle abnormal situations, thus improving the overall system's safety and reliability.

[0085] This invention further proposes to adjust the acceleration of the robotic arm in real time based on global speed parameters and calculate the remaining task time; monitor the load current, and if it exceeds the limit for 3 consecutive seconds, automatically reduce the speed of the robotic arm to a safe value and generate a warning log; collect the actual position coordinates of the adsorption mechanism 6, and highlight the abnormal point when the deviation from the preset position coordinates exceeds ±50mm; after pausing the task, perform one-click calibration through the human-machine interface, and automatically resume operation after calibration.

[0086] The linkage adjustment between global speed parameters and the robotic arm's motion acceleration is achieved through a servo drive control algorithm. The remaining task time is dynamically calculated based on the current speed and the remaining path length. Load current monitoring employs a sliding time window mechanism; if the current value exceeds the rated value within three consecutive sampling cycles, a speed reduction command is triggered, with the reduction magnitude adjusted in stages according to the over-limit ratio. Position coordinate deviation detection utilizes data fusion from a laser rangefinder and encoder; when the absolute value of the deviation exceeds 50mm, the abnormal point is marked with a flashing red indicator on the human-machine interface. A one-click calibration command activates a preset coordinate correction program, driving the robotic arm to move along the reference path and update the position parameters.

[0087] Specifically, during the robotic arm's movement, the servo system collects the load current data of each joint motor in real time. When the load current exceeds the safety threshold for more than 3 seconds, the control module automatically reduces the robotic arm's movement speed to 50%-70% of its original speed and records the over-limit time and speed reduction ratio in the log. The position coordinates of the adsorption mechanism 6 are fed back in real time by a high-precision sensor. If an X / Y axis deviation exceeding ±50mm is detected, the system immediately pauses the task and highlights the offset direction and distance on the visual interface. After the operator clicks the calibration button on the touchscreen, the robotic arm sequentially performs origin return, reference point alignment, and coordinate parameter update. After calibration, it automatically resumes the palletizing task from the pause point.

[0088] As a preferred embodiment, the solution of the present invention is implemented as follows:

[0089] The robotic arm's acceleration is adjusted in real time based on global speed parameters, and the remaining task time is calculated. Specifically, the maximum acceleration of each joint is dynamically calculated by reading the global speed parameter values ​​set by the system. For example, when the global speed parameter is 80%, the upper limit of acceleration for each joint is set to 80% of the rated value. At the same time, based on the current acceleration and remaining workload, the time required to complete the task is estimated in real time and displayed on the human-machine interface.

[0090] The system monitors the load current, and if it exceeds the limit for 3 consecutive seconds, it automatically reduces the speed of the robotic arm to a safe value and generates a warning log. In practice, the system samples the current value of each joint motor every 100 milliseconds. If the current value of a certain joint exceeds 120% of the rated value for 30 consecutive samples, the automatic speed reduction mechanism is triggered. During speed reduction, the global speed parameter is reduced to 50% of its original value, and the overload time, joint number, and other information are recorded in the system log.

[0091] The actual position coordinates of the adsorption mechanism 6 are collected. If the deviation from the preset position coordinates exceeds ±50mm, the abnormal point is highlighted. Furthermore, a laser rangefinder is used to measure the distance between the end of the adsorption mechanism 6 and the reference surface in real time. When the difference between the measured value and the theoretical value exceeds ±50mm, the point is marked in red in the 3D model of the human-machine interface and flashes as a warning.

[0092] After pausing the task, a one-click calibration is performed via the human-machine interface. Once calibration is complete, the robotic arm automatically resumes operation. Specifically, after the operator clicks the "one-click calibration" button, the system automatically executes the following steps: First, the robotic arm moves to a preset calibration reference point; then, the coordinates of the reference point are precisely located using a vision system; finally, the kinematic parameters of the robotic arm are automatically corrected based on the deviation between the actual and theoretical coordinates. After calibration, the system automatically returns to its pre-pause working state. Through the above technical solution, this invention achieves real-time monitoring and adaptive adjustment of the robotic arm's movement. This improves the safety and stability of the palletizing process. Furthermore, the automatic deceleration and one-click calibration functions reduce the need for manual intervention and enhance the system's autonomous operation capability. Simultaneously, real-time position coordinate verification and visualization of abnormal points enable operators to quickly identify and handle potential problems, thereby improving the efficiency of fault diagnosis and handling.

[0093] The present invention further proposes to identify the material size in real time by using a laser contour sensor, estimate the material weight by using the end force sensor of the adsorption mechanism 6, and judge the material surface characteristics based on the vacuum pressure fluctuation and leakage rate of the adsorption mechanism 6; dynamically adjust the vacuum pressure threshold of the adsorption mechanism 6 and the gripping angle of the robotic arm based on the material size, weight and surface characteristics; and encrypt and store the updated parameters and synchronize them to the stack configuration system.

[0094] The system includes a laser contour sensor installed at the end of the robotic arm, which generates 3D point cloud data by scanning the material's outline and calculates the material's length, width, and height in real time; an end force sensor integrated into the flange of the adsorption mechanism 6, which collects axial pressure data at the moment of grasping and converts it into material weight; a vacuum pressure sensor monitors the internal pressure change curve of the adsorption mechanism 6 and, combined with a leakage rate threshold, determines whether the material surface is smooth or porous; the vacuum pressure threshold is set based on the material weight and surface roughness, and the grasping angle is dynamically adjusted according to the length-to-width ratio of the material to ensure that the adsorption surface is aligned with the material's center of gravity; encrypted storage uses the AES-256 algorithm to encrypt parameter files and transmits encrypted data packets to the database of the stack configuration system via the industrial Ethernet protocol.

[0095] Specifically, the laser contour sensor scans the material surface at a rate of 50 frames per second, generates point cloud data, and then reconstructs the three-dimensional model of the material through a triangulation algorithm, outputting dimensional data to the control unit; the end force sensor records the pressure peak when the adsorption mechanism 6 contacts the material, and calculates the material weight by combining it with preset acceleration parameters; the vacuum pressure sensor monitors the pressure of the adsorption pipeline with a sampling period of 10ms, and determines that there is a leak when the pressure drop rate exceeds 0.5kPa / s; the control unit adjusts the horizontal gripping angle of the robotic arm according to the material size, and adopts a diagonal gripping mode when the material aspect ratio is greater than 2:1; the vacuum pressure threshold is set according to weight grade, for example, -60kPa is set for materials under 1kg, and -80kPa is set for materials between 1-5kg; the updated parameters are encrypted and written to the database, and the corresponding encrypted parameter file is automatically called when changing production lines, decrypted and loaded into the robotic arm control system.

[0096] As a preferred embodiment, the solution of the present invention is implemented as follows:

[0097] A laser profile sensor is mounted at the end of the multi-axis robot 5's robotic arm for real-time scanning of the material's outline. An end-effector force sensor is integrated into the adsorption mechanism 6 to measure the material's weight. The adsorption mechanism 6 is equipped with a pressure sensor to monitor vacuum pressure fluctuations.

[0098] Material dimensions are calculated using data scanned by a laser profile sensor. Material weight is obtained by subtracting the weight of the adsorption mechanism 6 from the value of the end force sensor. Material surface characteristics are determined based on vacuum pressure fluctuations and leakage rates; fluctuations greater than 5% and leakage rates exceeding 10% / min are considered rough surfaces.

[0099] Based on the identification results, the system automatically adjusts the parameters: for materials with larger dimensions, the vacuum pressure threshold is increased by 10%; for materials weighing more than 5kg, the robotic arm gripping angle is changed to 45°; for materials with rough surfaces, the vacuum pressure threshold is increased by 20%.

[0100] The updated parameters are stored using the AES-256 encryption algorithm and synchronized to the pallet configuration system server via HTTPS. The pallet configuration system receives the encrypted data, decrypts it, and updates the capture strategy for the corresponding material type.

[0101] This invention enables real-time sensing of material characteristics and dynamic adjustment of the gripping strategy. Laser contour sensors, end-effector force sensors, and vacuum pressure monitoring provide comprehensive material information, allowing the system to accurately identify the size, weight, and surface characteristics of different materials. Based on this real-time data, the system automatically optimizes the vacuum pressure threshold and gripping angle, significantly improving its adaptability to various materials. Especially for materials that are large, heavy, or have rough surfaces, appropriate parameter adjustments effectively reduce the risk of gripping failures and drops. Furthermore, encrypted parameter storage and synchronization mechanisms ensure data security while enabling strategy sharing between different devices, improving the overall system's learning ability and adaptability. This closed-loop optimization method greatly enhances the flexibility and reliability of the palletizing process, reduces the need for manual intervention, and increases production efficiency.

[0102] The present invention further proposes that in manual debugging mode, the movement of the robotic arm of the multi-axis robot 5 is controlled by switching to the tool coordinate system, and the jogging speed of the robotic arm of the multi-axis robot 5 is limited to 10%-30% of the global speed of the multi-axis robot 5; after debugging, a parameter modification comparison report is generated and synchronized to the stacking configuration system after hash encryption.

[0103] Among them, the tool coordinate system control uses the suction mechanism 6 at the end of the robotic arm as the origin of the coordinate system to ensure the accuracy of motion parameter adjustment during the debugging process; the jog speed limit range is dynamically calculated based on global speed parameters to avoid collisions or positioning deviations caused by excessive speed during manual operation; the parameter modification comparison report generates a log file containing the modification time, operator, and specific value by comparing the data differences before and after debugging; the hash encryption uses the SHA-256 algorithm to perform irreversible encryption processing on the report to ensure the security of data transmission and storage.

[0104] Specifically, in manual debugging mode, the jogging speed of the robotic arm is limited to 10%-30% of the global speed. For example, when the global speed is 100mm / s, the upper limit of the jogging speed is 30mm / s. By reducing the movement speed, debugging accuracy is improved and the risk of misoperation is reduced. After debugging, the system automatically generates a comparison report containing parameters such as position, acceleration, and gripping angle before and after modification. A unique verification code is generated by encrypting the report using a hash algorithm to prevent data tampering. The encrypted report is synchronized to the stack configuration system. After parsing, the system updates the parameter database of the corresponding model, realizing closed-loop optimization between debugging data and system configuration. This process avoids errors that may occur when manually recording parameters, and at the same time, the encryption mechanism ensures the security of data during cross-system transmission, shortening the parameter configuration time when switching between different models.

[0105] As a preferred embodiment, the solution of the present invention is implemented as follows:

[0106] In manual adjustment mode, the movement of the multi-axis robot 5's robotic arm is controlled using the tool coordinate system. Specifically, the operator selects the "manual adjustment" option through the touch-screen human-machine interface 3, and the system automatically switches to the tool coordinate system. In this mode, the operator can directly control the position and orientation of the robotic arm's end effector without needing to consider the movement of each joint.

[0107] Furthermore, the system limits the robotic arm's jogging speed to 10%-30% of the global speed. For example, if the global speed is set to 100mm / s, the maximum jogging speed in manual adjustment mode is limited to 10-30mm / s. This speed limiting mechanism effectively prevents the risk of collisions caused by operational errors.

[0108] After debugging, the system automatically generates a parameter modification comparison report. This report records in detail the parameter changes before and after debugging, including but not limited to the position, speed, and acceleration of each joint of the robotic arm. This allows the operator to clearly understand the specific modifications made during the debugging process.

[0109] Finally, the system hashes and encrypts the generated parameter modification report. The encrypted data is then transmitted to the pallet configuration system via the internal network security, ensuring synchronized parameter updates. This encryption and synchronization mechanism ensures the security and consistency of parameter modifications. Through the above technical solution, this invention achieves precise debugging and parameter optimization of a multi-axis robot 5-palletizing system. Tool coordinate system control and speed limiting in manual debugging mode improve debugging accuracy and security. The generation and encryption synchronization of parameter modification comparison reports ensure the traceability of debugging results and system consistency. This closed-loop optimization mechanism significantly improves the adaptability and stability of the palletizing system, effectively solving the problems of cumbersome and inefficient parameter debugging in traditional palletizing systems.

[0110] The present invention further proposes a palletizing workstation, including a support frame 1, a base 2 and a multi-axis robot 5. The base 2 is fixedly connected to the support frame 1. A touch-screen human-machine interface 3 and control buttons 4 are installed on the base 2. The multi-axis robot 5 is installed on the base 2 and an adsorption mechanism 6 for gripping and placing materials is installed on the multi-axis robot 5.

[0111] The fixed connection between the support frame 1 and the base 2 forms a rigid load-bearing structure, ensuring the stability of the multi-axis robot 5 during operation. The touch-screen human-machine interface 3 is integrated into the operating surface of the base 2, supporting the input of stacking parameters and real-time status visualization. The control button 4 is linked with the touch interface and is used for start, pause, and reset operations. The multi-axis robot 5 communicates with the touch interface through the internal cable of the base 2, receives motion commands, and feeds back operating data. The adsorption mechanism 6 is installed on the end effector of the multi-axis robot 5 and is connected to an external air source through a vacuum pipeline. Its gripping surface is equipped with a pressure sensor to monitor the adsorption status.

[0112] Specifically, operators set the number of palletizing layers, material size, and safety thresholds via the touch-screen human-machine interface 3, and the system automatically generates the corresponding robotic arm motion trajectory. When the multi-axis robot 5 performs palletizing tasks, the controller built into the base 2 collects real-time vacuum pressure data from the adsorption mechanism 6 and dynamically displays the pressure curve via the touch interface. When an abnormal pressure is detected, the control button 4 triggers an emergency stop signal, stopping the multi-axis robot 5 and locking its current state. The adsorption mechanism 6 adjusts the vacuum pressure threshold according to the material surface characteristics; for example, it increases the pressure to -80kPa to -90kPa for rough-surfaced cartons, while using -70kPa to -75kPa for smooth metal cans. The base 2 has internal heat dissipation channels to ensure that the temperature rise of the multi-axis robot 5's servo motor does not exceed 45℃ during continuous operation. During debugging, the touch interface is switched to manual mode, and the control button 4 is used to adjust the position of the robotic arm's end effector in a jogging manner, with the position error controlled within ±1mm. The corrected parameters are automatically synchronized to the pallet configuration system.

[0113] As a preferred embodiment, the solution of the present invention is implemented as follows:

[0114] A palletizing workstation includes a support frame 1, a base 2, and a multi-axis robot 5. The base 2 is fixedly connected to the support frame 1 by bolts. A touch-screen human-machine interface 3 and control buttons 4 are installed on the base 2. The touch-screen human-machine interface 3 uses a 10.4-inch capacitive screen with a resolution of 1024x768 pixels. The control buttons 4 include function buttons for start, stop, and emergency stop. The multi-axis robot 5 is mounted on the base 2 and is a 6-axis articulated robot. An adsorption mechanism 6 for gripping and placing materials is installed at the end of the multi-axis robot 5. The adsorption mechanism 6 adopts a vacuum suction cup structure, including four suction cups with a diameter of 60mm. Through the above technical solution, this invention achieves a compact and easy-to-operate palletizing workstation. The fixed connection between the support frame 1 and the base 2 provides a stable foundation, ensuring the accuracy of the multi-axis robot 5's operation. The touch-screen human-machine interface 3 and control buttons 4 facilitate parameter setting and real-time monitoring by operators. The combined application of the multi-axis robot 5 and the adsorption mechanism 6 improves the flexibility and efficiency of palletizing operations. The overall design meets the requirements of industrial automated production lines for the palletizing process, effectively improving production efficiency.

[0115] Figure 1 This is a schematic diagram of the palletizing workstation in this invention, as shown below. Figure 1 As shown, the present invention further proposes a multi-axis robot 5, which is a robot with multiple sequentially connected robotic arms, forming a multi-axis linkage structure.

[0116] Multiple robotic arms connected in sequence form a continuous motion chain through joints. The rotation axes of each robotic arm are staggered at preset angles, and high-precision reducers are installed at the connection points between adjacent robotic arms. Furthermore, the end effector is rigidly connected to the adsorption mechanism 6 via a flange. The flange surface is provided with an array of positioning pin holes, and a vacuum suction cup assembly is arranged on the bottom surface of the adsorption mechanism 6. The spacing between the suction cups corresponds to the array of positioning pin holes.

[0117] Specifically, the sequentially connected robotic arms adopt a six-axis serial structure, with each axis corresponding to the rotation of the base 2, the pitch of the upper arm, the extension of the elbow, the rotation of the wrist, the rotation of the end effector, and the posture adjustment function of the adsorption mechanism 6. The drive motors of each robotic arm transmit torque through harmonic reducers, with the reduction ratio set in the range of 1:120 to 1:160. When performing palletizing tasks, the rotation axis of the base 2 drives the subsequent robotic arms to rotate as a whole. The pitch axis of the upper arm and the extension axis of the elbow work together to form a lifting motion in the vertical plane, and the wrist rotation axis and the end effector rotation axis work together to adjust the spatial posture of the adsorption mechanism 6. The adsorption mechanism 6 can be quickly replaced through an array of positioning pin holes, and the vacuum suction cup assembly selects the corresponding mounting hole position according to the material size. This structure achieves six degrees of freedom motion of the end effector through multi-axis spatial decoupling. When gripping irregularly shaped materials, the adsorption angle and gripping height can be adjusted simultaneously, improving the spatial adaptability of the palletizing process.

[0118] As a preferred embodiment, the present invention is implemented as follows: The palletizing workstation includes a support frame 1 and a rectangular welded base 2, with the base 2 rigidly connected to the support frame 1 via anchor bolts. The multi-axis robot 5 consists of six rotary joint robotic arms, each connected via a harmonic reducer, and equipped with a vacuum adsorption mechanism 6 at its end. The first robotic arm is fixedly connected to the flange of the base 2, and the second to sixth robotic arms are sequentially connected in series via crossed roller bearings. Each joint is equipped with an absolute encoder for position feedback. The touch-screen human-machine interface 3 uses an industrial-grade capacitive screen, embedded in the operating side of the base 2. The control buttons 4 include a green start button and a red emergency stop button, connected to a PLC controller via a waterproof connector.

[0119] This invention effectively solves the technical defect of traditional palletizing robotic arms, which have insufficient degrees of freedom of motion, resulting in a limited operating range. The six-axis serial robotic arm structure enables the end effector to have six degrees of freedom of motion in space, achieving oblique gripping and three-dimensional obstacle avoidance of complex pallet shapes. The combination of harmonic reducers and crossed roller bearings between the robotic arms enhances axial load-bearing capacity while ensuring transmission accuracy and avoiding mechanical vibration during continuous multi-joint movement. Therefore, this workstation can adapt to the multi-layer staggered palletizing requirements of pallets of different sizes, significantly reducing the risk of material collisions caused by insufficient robotic arm range of motion.

[0120] This invention further proposes a palletizing workstation, including a support frame 1, a base 2, and a multi-axis robot 5. The base 2 is fixedly connected to the support frame 1. A touch-screen human-machine interface 3 and control buttons 4 are installed on the base 2. The multi-axis robot 5 is mounted on the base 2 and has an adsorption mechanism 6 for gripping and placing materials. The multi-axis robot 5 is a robot with multiple sequentially connected robotic arms. Specifically, the base 2 is bolted to the support frame 1, and a counterweight is welded to the bottom of the support frame 1 to reduce the risk of center of gravity shift. The touch-screen human-machine interface 3 communicates with the controller of the multi-axis robot 5 via a CAN bus. The control buttons 4 are waterproof membrane switches, with speed adjustment and emergency stop function keys. Absolute encoders are installed at the joints of the six robotic arms of the multi-axis robot 5. The end effector is connected to the adsorption mechanism 6 via a quick-change interface. The suction cup array is made of silicone, and the vacuum generator is controlled by a solenoid valve. The cascaded structure of the six robotic arms enables the end effector to achieve a movement range of ±1500mm, ±800mm, and ±600mm in the XYZ axes, respectively. The suction mechanism 6 can avoid obstacles based on a preset path when gripping materials. When performing multi-layer palletizing tasks, the robotic arms adjust the gripping angle through multi-joint linkage, the suction cup array automatically selects the number of cups to open according to the material size, and the vacuum pressure threshold is set from -60kPa to -80kPa.

[0121] As a preferred embodiment, the present invention is implemented as follows: The multi-axis robot 5 is composed of a base joint, an upper arm rotation joint, a lower arm pitch joint, and a wrist rotation joint connected in series. The base joint is bolted to the base 2 via a flange. Power transmission is achieved between the joints using harmonic reducers. The arm body of each robotic arm is made of hollow aluminum alloy profile, and servo motor drive circuits and vacuum pipelines are arranged inside. Furthermore, the end of the wrist rotation joint is equipped with a flange mounting surface, which is connected to the adsorption mechanism 6 via a quick-connect coupling to achieve air circuit communication. The axial positioning pin of the quick-connect coupling adopts a conical self-locking structure.

[0122] This invention effectively improves the rigidity and positioning accuracy of the kinematic chain of a multi-axis robotic arm. The hollow aluminum alloy arm body reduces rotational inertia while ensuring structural strength, and the conical self-locking quick-connect joint ensures the sealing reliability of the air circuit connection. The multi-stage series configuration of the harmonic reducer enables the robotic arm to achieve both large-area spatial coverage and precise control of the attitude angle of the end-effector adsorption mechanism 6 during palletizing operations, thereby avoiding positioning errors caused by cumulative joint errors and ensuring the verticality requirements of material stacking in multi-layer palletizing operations.

[0123] The present invention further proposes a multi-axis robot as a robot having multiple robotic arms connected in sequence.

[0124] Multiple robotic arms are installed in series, with the end of each arm connected to the head of the next arm via a rotary joint, forming a chain structure. Each robotic arm is equipped with an independent servo drive module, and each drive module communicates with the central controller via a bus. The joint rotation angle range of the robotic arms is set to ±180 degrees, and the end arms are equipped with adsorption mechanisms 6. Anti-collision sensors are installed between adjacent robotic arms to monitor the distance in real time and limit the movement trajectory.

[0125] Specifically, the central controller decomposes the motion paths of each robotic arm according to the preset palletizing trajectory and calculates the target angles of each joint using inverse kinematics algorithms. When the end effector 6 needs to reach a specific position, multiple robotic arms coordinate to adjust their angles, expanding the working coverage area. For example, when the palletizing height exceeds the lifting limit of a single arm, the lower robotic arm maintains a fixed angle, while the upper robotic arms unfold sequentially to form a stepped structure. The anti-collision sensor triggers a deceleration signal when the distance between the robotic arms is less than 50 mm, and the central controller replans the path. Thus, the coordinated movement of multiple robotic arms can achieve precise control of multiple degrees of freedom within a limited space, avoiding motion dead zones and improving the stacking efficiency of complex pallet types.

[0126] As a preferred embodiment, the present invention is implemented as follows: The multi-axis robot 5 consists of multiple robotic arms connected in sequence. Each robotic arm is interconnected via rotary joints, and a vacuum adsorption mechanism 6 is installed at its end. The rotary joints are driven by servo motors. The multiple robotic arms correspond to multiple degrees of freedom of motion, forming a continuous motion chain in the base coordinate system. Furthermore, each robotic arm has an absolute encoder built into its joint to provide real-time position signals to the control system, forming a fully closed-loop motion control. The present invention achieves multi-degree-of-freedom spatial attitude adjustment capability by forming a motion chain structure with multiple robotic arms connected in sequence. This structure allows the adsorption mechanism 6 to approach materials at any angle, avoiding the problem of gripping path interference caused by the limitation of a single motion plane. At the same time, the redundant degree-of-freedom design of the robotic arms can automatically avoid joint limit areas, maintain trajectory continuity and positioning accuracy in complex stacking scenarios, and effectively reduce the gripping failure rate caused by insufficient range of motion of the robotic arms.

[0127] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A palletizing method, characterized in that, Includes the following steps: Step S1: Configure stack type parameters and provide visual feedback on status through the human-computer interaction interface, including: The encoder parameters and the motion constraints of the multi-axis robot (5) are automatically loaded according to the selected model. Edit multi-layer palletizing styles in the visual interface, and dynamically distinguish the palletizing status of completed and incomplete materials through preset labels; Step S2: Perform multi-level safety verification and robotic arm reset control of the multi-axis robot (5), including: The servo system enable status of the multi-axis robot (5) and the compliance of the joint position of the robotic arm of the multi-axis robot (5) are checked. When the robotic arm of the multi-axis robot (5) triggers the zero-return operation, an interactive confirmation process is generated based on the real-time position deviation. After confirmation, the robotic arm of the multi-axis robot (5) is reset using an adaptive deceleration algorithm. Step S3: Dynamic closed-loop control and real-time anomaly monitoring, including: The motion trajectory of the robotic arm of the multi-axis robot (5) is adjusted based on the linkage between global speed parameters and load feedback signals. The position coordinate accuracy of the adsorption mechanism (6) is checked in real time. If the accuracy exceeds the limit, a calibration command is triggered and the task is paused. Step S4: Dynamically adjust the gripping strategy of the multi-axis robot (5) based on the material state; Step S5: Correct the abnormal motion parameters of the multi-axis robot (5) through manual debugging mode in the human-machine interface, and synchronize the debugged motion parameters back to the stack configuration system to achieve closed-loop optimization.

2. The palletizing method according to claim 1, characterized in that, Step S1 specifically includes: Step S1-1: Load the encoder disk size and the joint limit parameters of the multi-axis robot (5) according to the selected model; Step S1-2: In the touch-screen human-machine interface (3), define the material layout by dragging and dropping. If the distance between adjacent materials is less than the safety threshold, it will be automatically highlighted in red. Steps S1-3: Generate yellow markers for materials that have been palletized, and retain white markers for materials that have not been palletized. The display can be switched according to the layer number of each palletized layer.

3. The palletizing method according to claim 1, characterized in that, Step S2 includes: Step S2-1: When checking the servo enable status of the multi-axis robot (5), simultaneously check the vacuum pressure value of the adsorption mechanism (6) at the end of the robotic arm of the multi-axis robot (5). If the pressure is abnormal, start-up is prohibited. Step S2-2: After triggering the zero-return operation, a pop-up window displays the deviation distance between the current position of the multi-axis robot (5) arm and the zero position, as well as the estimated zero-return time. Step S2-3: During the zeroing process, if the joint position exceeds the limit, the zeroing process will be paused and a pop-up window will display the number of the joint that exceeded the limit.

4. The palletizing method according to claim 1, characterized in that, Step S3 includes the following sub-steps: Step S3-1: Adjust the motion acceleration of the robotic arm of the multi-axis robot (5) in real time according to the global velocity parameters of the multi-axis robot (5), and calculate the remaining task time; Step S3-2: Monitor the load current. If it exceeds the limit for 3 consecutive seconds, automatically reduce the speed of the multi-axis robot (5) to a safe value and generate a warning log. Step S3-3: Collect the actual position coordinates of the adsorption mechanism (6). If the deviation from the preset position coordinates exceeds ±50mm, the abnormal point will be highlighted. Step S3-4: After pausing the task, perform one-click calibration through the human-machine interface. After calibration, the multi-axis robot (5) will automatically resume operation.

5. A palletizing method according to claim 1, characterized in that, Step S4 includes: Step S4-1: The material size is identified in real time by the laser profile sensor, the material weight is estimated by the end force sensor of the adsorption mechanism (6), and the surface characteristics of the material are judged based on the vacuum pressure fluctuation and leakage rate of the adsorption mechanism (6). Step S4-2: Dynamically adjust the vacuum pressure threshold of the adsorption mechanism (6) and the gripping angle of the robotic arm of the multi-axis robot (5) according to the material size, material weight and material surface characteristics; Step S4-3: Encrypt and store the updated parameters and synchronize them to the stack configuration system.

6. The palletizing method according to claim 1, characterized in that, Step S5 includes: Step S5-1: In manual debugging mode, switch to tool coordinate system control of the movement of the multi-axis robot (5) arm, and limit the jogging speed of the multi-axis robot (5) arm to 10%-30% of the global speed of the multi-axis robot (5); Step S5-2: After debugging, generate a parameter modification comparison report, which is then hash-encrypted and synchronized to the stack configuration system.

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