Full-automatic intelligent car loader stacking method

Abstract

The application discloses a full-automatic intelligent car loader stacking method, and relates to the technical field of data analysis.The method comprises the following steps: obtaining cargo attribute information, vehicle parameter information and transportation demand information; performing package arrangement strategy analysis based on the cargo attribute information, the vehicle parameter information and the transportation demand information to obtain an initial package arrangement strategy; performing gripping pose analysis of a plurality of grippers in the intelligent car loader based on the initial package arrangement strategy; performing cargo stacking debugging based on the gripping pose and the initial package arrangement strategy, and detecting a gap accumulation ratio and a height error in the cargo stacking debugging process; adjusting the initial package arrangement strategy and the gripping pose based on the gap accumulation ratio and the height error to obtain a target package arrangement strategy and a target gripping pose, and the intelligent car loader performs cargo stacking according to the target package arrangement strategy and the target gripping pose.The application can effectively prevent displacement, collision and damage of the cargo during transportation, and provides solid protection for cargo safety.

Description

Technical Field

[0001] This invention relates to the field of data analysis technology, and in particular to a fully automated intelligent loading machine palletizing method. Background Technology

[0002] With the rapid development of the logistics industry, traditional manual loading methods suffer from low efficiency, high labor intensity, and poor safety. Existing automated loading equipment mostly employs fixed packing logic, which cannot dynamically adapt to changes in vehicle type, cargo specifications, and loading requirements, resulting in low space utilization. Furthermore, existing automated loading equipment lacks the ability to detect and adjust the status of goods and vehicles, easily leading to risks of cargo tipping or overloading. Traditional equipment is difficult to adapt to various packing types, limiting its application scope. Therefore, existing automated loading equipment has shortcomings in packing strategies and cargo handling considerations, affecting the reliability of cargo palletizing, failing to effectively improve loading efficiency and safety, and also incurring high operating costs. Summary of the Invention

[0003] The purpose of this invention is to overcome the shortcomings of the prior art. This invention provides a fully automatic intelligent loading and palletizing method that can effectively prevent goods from shifting, colliding and being damaged during transportation, thus providing solid protection for the safety of goods.

[0004] To address the aforementioned technical problems, this invention provides a fully automated intelligent loading and palletizing method, the method comprising: Obtain cargo attribute information, vehicle parameter information, and transportation demand information, and perform a packing strategy analysis based on the cargo attribute information, vehicle parameter information, and transportation demand information to obtain an initial packing strategy; Based on the initial packing strategy, the grasping poses of several grippers in the intelligent loading machine are analyzed to obtain the grasping poses. Based on the grasping pose and initial packing strategy, cargo palletizing is debugged, and the cumulative gap ratio and height error are detected during the cargo palletizing debugging process. The initial packing strategy and gripping pose are adjusted based on the gap accumulation ratio and height error to obtain the target packing strategy and target gripping pose. The intelligent loading machine then stacks the goods according to the target packing strategy and target gripping pose.

[0005] Optionally, obtaining cargo attribute information, vehicle parameter information, and transportation demand information includes: Obtain cargo attribute information and transportation demand information from the order database; The measurement trajectory is set, and the ranging sensor is controlled to measure the vehicle parameters according to the measurement trajectory to obtain vehicle parameter information.

[0006] Optionally, the step of performing a packing strategy analysis based on the cargo attribute information, vehicle parameter information, and transportation demand information to obtain an initial packing strategy includes: Based on transportation demand information and cargo attribute information, several target goods to be palletized are identified; Based on cargo attribute information and vehicle parameter information, a packing strategy analysis is performed on several target goods to be stacked to obtain an initial packing strategy.

[0007] Optionally, the step of analyzing the packing strategy for several target goods to be palletized based on cargo attribute information and vehicle parameter information to obtain an initial packing strategy includes: Based on cargo attribute information and vehicle parameter information, palletizing parameters are analyzed to obtain initial palletizing parameters; The initial packing strategy is determined based on the initial palletizing parameters.

[0008] Optionally, the step of analyzing palletizing parameters based on cargo attribute information and vehicle parameter information to obtain initial palletizing parameters includes: Set the loading mode, and determine the horizontal arrangement width, vertical arrangement width, horizontal row width, vertical row width, horizontal column gap ratio, and horizontal column stacking cumulative ratio based on the cargo attribute information and vehicle parameter information combined with the loading mode; Set horizontal and vertical slot patterns; Determine the safe distance between the carriage and the grab handle collision avoidance distance; Based on the horizontal row width, vertical row width, horizontal row width, vertical row width, horizontal column gap ratio, and horizontal column stacking cumulative ratio, combined with the horizontal row gap pattern and the vertical column gap pattern, the initial stacking parameters are determined using the car body safety distance and the grab handle anti-collision distance.

[0009] Optionally, the step of analyzing the grasping poses of several grippers in the intelligent loading machine based on the initial packing strategy to obtain the grasping poses includes: Obtain the gripper parameters of each gripper and determine the safe distance based on the initial pack sorting strategy; Determine the central position of the cargo based on cargo attribute information; Based on the gripper parameters, safety distance, and the center position of the cargo, the gripping posture of several grippers in the intelligent loading machine is analyzed to obtain the gripping posture.

[0010] Optionally, the step of adjusting the cargo palletizing based on the grasping pose and the initial packing strategy, and detecting the cumulative gap ratio and height error during the cargo palletizing adjustment process, includes: Input the capture pose and initial packing strategy into the preset program for cargo palletizing debugging; During the cargo palletizing debugging process, the cumulative ratio of column gaps and the cumulative ratio of row gaps are calculated for each layer of cargo palletizing, and the cumulative gap ratio is determined based on the cumulative ratio of column gaps and the cumulative ratio of row gaps. Height error is detected based on a height detection program.

[0011] Optionally, adjusting the initial bag-sorting strategy and grasping pose based on the gap accumulation ratio and height error to obtain the target bag-sorting strategy and target grasping pose includes: The number of rows and columns to be increased is determined based on the cumulative gap ratio, and the padding parameters are determined based on the height error; Set the overflow range, received data, compressed data, and dropped data in the column, and determine the stacked data; Based on the number of rows increased, the number of columns increased, the padding parameters, the overflow range on the column, the received packet data, the compressed packet data, the dropped packet data, and the stacked packet data, the initial packet sorting strategy and the grabbing pose are adjusted to obtain the target packet sorting strategy and the target grabbing pose.

[0012] Optionally, determining the overlay data includes: Calculate the overlapping area of ​​the packages and determine the cumulative ratio of horizontal stacked packages based on the overlapping area; Based on the cumulative stacking ratio of the horizontal rows, stacking data is analyzed to obtain stacking data.

[0013] Optionally, the intelligent loading machine performs cargo palletizing according to the target packing strategy and target grasping pose, including: Based on the target packet sorting strategy and target grasping pose generation control instructions; Based on the control commands, the intelligent loading machine uses several grippers to place several target goods to be stacked into the vehicle.

[0014] In this embodiment of the invention, an initial packing strategy is determined based on cargo attribute information, vehicle parameter information, and transportation demand information. The gripping postures of several grippers in the intelligent loading machine are analyzed based on the initial packing strategy. Cargo palletizing is then debugged based on the gripping postures and the initial packing strategy. During the cargo palletizing debugging process, the cumulative gap ratio and height error are detected. Based on the cumulative gap ratio and height error, the initial packing strategy and gripping posture are adjusted. The intelligent loading machine palletizes cargo according to the target packing strategy and target gripping posture. The packing analysis process is simple and smooth, greatly shortening loading time, improving logistics efficiency, and ensuring that goods can reach their destination in a timely manner. Using this target packing strategy for cargo palletizing can fully utilize the vehicle's space potential, making the cargo placement compact and orderly, reducing space waste, lowering transportation costs, and effectively preventing cargo displacement, collisions, and damage during transportation, providing solid protection for cargo safety. Attached Figure Description

[0015] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0016] Figure 1 This is a flowchart illustrating the fully automated intelligent loading and palletizing method in an embodiment of the present invention. Figure 2 This is a flowchart illustrating a fully automated intelligent loading and palletizing method according to another embodiment of the present invention. Figure 3 This is a rendering of the loading mode in an embodiment of the present invention; Figure 4 This is a rendering of the horizontal slit pattern in an embodiment of the present invention; Figure 5 This is a rendering of the vertical slit pattern in an embodiment of the present invention; Figure 6 This is an illustration of the effect of filling the shape by adding rows in an embodiment of the present invention; Figure 7 This is a diagram illustrating the effect of flattening the shape by adding columns in an embodiment of the present invention. Figure 8 This is a rendering of the padding bag in an embodiment of the present invention; Figure 9 This is a diagram illustrating the effect of compressing the package in an embodiment of the present invention. Detailed Implementation

[0017] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. 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.

[0018] Example 1: Please refer to Figure 1 , Figure 1 This is a flowchart illustrating the fully automated intelligent loading and palletizing method according to an embodiment of the present invention. The method includes: S11: Obtain cargo attribute information, vehicle parameter information, and transportation demand information, and perform a packing strategy analysis based on the cargo attribute information, vehicle parameter information, and transportation demand information to obtain an initial packing strategy; In the specific implementation of this invention, cargo attribute information, vehicle parameter information, and transportation demand information are obtained. Based on the transportation demand information and cargo attribute information, several target cargoes to be palletized are determined. Based on the cargo attribute information and vehicle parameter information, palletizing parameter analysis is performed to obtain initial palletizing parameters. Based on the initial palletizing parameters, an initial packing strategy is determined, which can more comprehensively consider the rationality of packing.

[0019] S12: Based on the initial packing strategy, analyze the grasping poses of several grippers in the intelligent loading machine to obtain the grasping poses; In the specific implementation of this invention, the gripper parameters of each gripper are obtained, the safety distance is determined based on the initial packing strategy, and the gripping posture of several grippers in the intelligent loading machine is analyzed by the gripper parameters, safety distance and the middle position of the goods to avoid damage when gripping the goods.

[0020] S13: Based on the grasping pose and initial packing strategy, perform cargo palletizing debugging, and detect the cumulative gap ratio and height error during the cargo palletizing debugging process; In the specific implementation of this invention, cargo palletizing is debugged based on the grasping pose and the initial packing strategy. During the cargo palletizing debugging process, the cumulative gap ratio and height error are detected by the corresponding program. The packing strategy and grasping pose are adjusted in real time based on the detected parameters to improve loading efficiency and safety.

[0021] S14: Based on the gap accumulation ratio and height error, the initial packing strategy and grasping pose are adjusted to obtain the target packing strategy and target grasping pose. The intelligent loading machine stacks goods according to the target packing strategy and target grasping pose.

[0022] In the specific implementation of this invention, the number of rows and columns to be added is determined by the cumulative gap ratio, the padding parameters are determined based on the height error, the overflow range on the column, the receiving data, the pressing data, and the throwing data are set, and the stacking data is determined. Based on the above data, the initial packing strategy and the grasping pose are adjusted to obtain the target packing strategy and the target grasping pose. The intelligent loading machine stacks goods according to the target packing strategy and the target grasping pose, which can fully tap the potential of vehicle space, make the goods placed compactly and orderly, reduce space waste, reduce transportation costs, and effectively prevent the goods from shifting, colliding and being damaged during transportation, providing a solid protection for the safety of the goods.

[0023] In this embodiment of the invention, an initial packing strategy is determined based on cargo attribute information, vehicle parameter information, and transportation demand information. The gripping postures of several grippers in the intelligent loading machine are analyzed based on the initial packing strategy. Cargo palletizing is then debugged based on the gripping postures and the initial packing strategy. During the cargo palletizing debugging process, the cumulative gap ratio and height error are detected. Based on the cumulative gap ratio and height error, the initial packing strategy and gripping posture are adjusted. The intelligent loading machine palletizes cargo according to the target packing strategy and target gripping posture. The packing analysis process is simple and smooth, greatly shortening loading time, improving logistics efficiency, and ensuring that goods can reach their destination in a timely manner. Using this target packing strategy for cargo palletizing can fully utilize the vehicle's space potential, making the cargo placement compact and orderly, reducing space waste, lowering transportation costs, and effectively preventing cargo displacement, collisions, and damage during transportation, providing solid protection for cargo safety.

[0024] Example 2: Please refer to Figure 2 , Figure 2 This is a flowchart illustrating a fully automated intelligent loading and palletizing method according to another embodiment of the present invention, the method comprising: S201: Obtain cargo attribute information, vehicle parameter information, and transportation demand information, and perform a packing strategy analysis based on the cargo attribute information, vehicle parameter information, and transportation demand information to obtain an initial packing strategy; In the specific implementation of this invention, the acquisition of cargo attribute information, vehicle parameter information, and transportation demand information includes: acquiring cargo attribute information and transportation demand information based on the order database; setting a measurement trajectory, controlling the ranging sensor to measure the vehicle parameters according to the measurement trajectory, and obtaining vehicle parameter information.

[0025] Furthermore, the step of performing packing strategy analysis based on the cargo attribute information, vehicle parameter information, and transportation demand information to obtain an initial packing strategy includes: determining several target goods to be palletized based on transportation demand information and cargo attribute information; and performing packing strategy analysis on the several target goods to be palletized based on cargo attribute information and vehicle parameter information to obtain an initial packing strategy.

[0026] Furthermore, the step of performing packing strategy analysis on several target goods to be palletized based on cargo attribute information and vehicle parameter information to obtain an initial packing strategy includes: performing palletizing parameter analysis based on cargo attribute information and vehicle parameter information to obtain initial palletizing parameters; and determining an initial packing strategy based on the initial palletizing parameters.

[0027] Furthermore, the step of analyzing palletizing parameters based on cargo attribute information and vehicle parameter information to obtain initial palletizing parameters includes: setting a loading mode; determining the horizontal arrangement width, vertical arrangement width, horizontal row width, vertical row width, horizontal column gap ratio, and horizontal stacking ratio based on the cargo attribute information and vehicle parameter information combined with the loading mode; setting horizontal gap mode and vertical gap mode; determining the safe distance between the carriages and the anti-collision distance of the grab handles; and determining the initial palletizing parameters based on the horizontal arrangement width, vertical arrangement width, horizontal row width, vertical row width, horizontal column gap ratio, and horizontal stacking ratio combined with the horizontal gap mode and vertical gap mode, using the safe distance between the carriages and the anti-collision distance of the grab handles.

[0028] Specifically, cargo attribute information and transportation demand information are obtained from the order database. Cargo attribute information includes dimensions and weight, while transportation demand information includes priority and timeliness. A measurement trajectory is set, and the ranging sensor is controlled to measure vehicle parameters according to the trajectory. A high-precision laser ranging sensor is controlled to move along the planned trajectory. The vehicle's parking position, cargo compartment length and width, and sideboard height are obtained by combining the changes in laser return values ​​with the current axis position, thus obtaining vehicle parameter information. Based on the transportation demand information and cargo attribute information, several target goods to be palletized are determined. A loading mode is set; by switching program parameters, intelligent loading under various conditions can be achieved. Switching parameters controls different loading modes. The effect of the loading mode is shown in the figure. Figure 3 As shown, this includes full horizontal packing, full vertical packing, first and last vertical packing, first row vertical packing, and last row vertical packing. Based on the cargo attribute information and vehicle parameter information, combined with the loading mode, the horizontal arrangement width, vertical arrangement width, horizontal row width, vertical row width, horizontal column gap ratio, and horizontal column stacking cumulative ratio are determined. Horizontal row width and vertical arrangement width: set the pack length, which can be retrieved from the recipe and used to calculate the number of packs per row in the horizontal packing and the number of packs per column in the vertical packing. Horizontal arrangement width and vertical row width: set the pack width, which can be retrieved from the recipe and used to calculate the number of packs per column in the horizontal packing and the number of packs per row in the vertical packing. Horizontal column gap ratio: calculated by dividing the vehicle width by the pack length when calculating the number of packs per row in the horizontal packing. If there is a gap and the gap is greater than the pack length multiplied by the ratio, the number of packs per row is increased by one, which can increase the number of packs and make full use of space. Horizontal column stacking cumulative ratio: the maximum overlap ratio when stacking packs, which can control the degree of overlap. Horizontal column gap mode and vertical column gap mode are set, such as... Figure 4 As shown, the horizontal gap pattern includes either a fixed gap or a uniform distribution when calculating the pack arrangement, such as... Figure 5As shown, the longitudinal gap pattern includes selecting a fixed gap or uniform distribution for the longitudinal rows during packing calculation. The safe distance between the carriages and the anti-collision distance of the grab handles are determined, and the packing space in the carriages is obtained by taking these factors into account. Based on the horizontal row width, vertical row width, horizontal row width, vertical row width, horizontal gap ratio, and horizontal stacking cumulative ratio, combined with the horizontal gap pattern and the longitudinal gap pattern, the initial stacking parameters are determined using the safe distance between the carriages and the anti-collision distance of the grab handles. These parameters together constitute the initial stacking parameters. Based on these initial stacking parameters, the initial packing strategy is determined and input into the operating system to obtain the initial packing strategy.

[0029] S202: Based on the initial packing strategy, analyze the grasping poses of several grippers in the intelligent loading machine to obtain the grasping poses; In the specific implementation of this invention, the step of analyzing the grasping pose of several grippers in the intelligent loading machine based on the initial packing strategy to obtain the grasping pose includes: acquiring the gripper parameters of each gripper and determining a safety distance based on the initial packing strategy; determining the center position of the cargo based on cargo attribute information; and analyzing the grasping pose of several grippers in the intelligent loading machine based on the gripper parameters, safety distance, and center position of the cargo to obtain the grasping pose.

[0030] Specifically, the gripper parameters of each gripper are obtained. The intelligent loading machine can have four grippers, with fixed front-to-back positions. Four grippers are more efficient for stacking large batches of neatly arranged bags. The gripper parameters include the length, width, and front-to-back position of the grippers. A safety distance is determined based on the initial bag arrangement strategy. The safety distance is determined according to the bag placement strategy (lower placement and higher placement) during bag arrangement calculation. The center position of the goods is determined based on the cargo attribute information. Based on the gripper parameters, safety distance, and center position of the goods, the gripping pose analysis of several grippers in the intelligent loading machine is performed. The gripper parameters, safety distance, and center position of the goods are input into the gripping pose analysis model to obtain the gripping pose.

[0031] S203: Based on the grasping pose and initial packing strategy, perform cargo palletizing debugging, and detect the cumulative gap ratio and height error during the cargo palletizing debugging process; In the specific implementation of this invention, the step of adjusting the cargo palletizing based on the grasping pose and the initial packing strategy, and detecting the cumulative gap ratio and height error during the cargo palletizing adjustment process, includes: inputting the grasping pose and the initial packing strategy into a preset program for cargo palletizing adjustment; calculating the cumulative ratio of column gaps and the cumulative ratio of row gaps for each layer of cargo palletizing during the cargo palletizing adjustment process, and determining the cumulative gap ratio based on the cumulative ratio of column gaps and the cumulative ratio of row gaps; and detecting the height error based on a height detection program.

[0032] Specifically, the captured pose and initial packing strategy are input into a preset program for cargo palletizing debugging. During cargo palletizing debugging, the cumulative ratio of column gaps and the cumulative ratio of row gaps are calculated for each layer of cargo palletizing. Based on these cumulative ratios, the cumulative gap ratio is determined. The cumulative column gap ratio indicates that if uneven gaps in fixed column packing accumulate to a certain number of layers, a significant drop will occur. The cumulative row gap ratio indicates that if uneven gaps in fixed row packing accumulate to a certain number of layers, a significant drop will occur. Height errors are detected using a height detection program.

[0033] S204: Determine the number of rows and columns to be increased based on the cumulative gap ratio, and determine the padding parameters based on the height error; In the specific implementation of this invention, such as Figure 6 As shown, uneven gaps in the fixed horizontal row packing can accumulate to a certain number of layers, resulting in a noticeable drop. In this case, an additional row is added to that layer to smooth out the shape, thus determining the number of rows to add. Figure 7 As shown, uneven gaps in the fixed-row packing with longitudinal seams can accumulate to a certain number of layers, resulting in a significant drop. In this case, an additional column is added to that layer to smooth out the shape; this determines the number of columns to add. The padding parameters are determined based on the height error, as follows: Figure 8 As shown, if padding is calculated to be necessary, the padding layer is moved down to the designated layer for pre-positioning for greater stability. Calculations are performed separately for layers below and above the sideboards, and the accumulated height is cleared after padding. Using the padding function can detect accumulated height errors caused by overlapping, adding padding at the alarm layer to regulate the loading shape. The padding layer can be moved to the designated layer for pre-positioning. When placing the bags, follow the rule of placing them on both sides first, then in the middle, ensuring a stacked shape with lower sides and a higher middle when overlapping occurs, preventing disorder and bag slippage / tipping.

[0034] S205: Set the overflow range, received packet data, compressed packet data, and dropped packet data in the column, and determine the stacked packet data; In a specific implementation of this invention, determining the stacked package data includes: calculating the overlapping area of ​​the packages and determining the cumulative ratio of horizontal stacked packages based on the overlapping area; and performing stacked package data analysis based on the cumulative ratio of horizontal stacked packages to obtain the stacked package data.

[0035] Specifically, the settings include the overflow range above the loading bar, pack collection data, pack pressing data, and pack throwing data. The overflow range above the loading bar height allows setting an overflow distance when packs exceed the height of the loading bar, reasonably increasing the number of packs. The upper layer gradually collects packs, creating a more stable inward slope. Turning it off maintains a consistent safe distance between the top and bottom of the loading bar. The pack collection function allows selection of whether the top layer of packs is gradually collected and placed in the center of the loading compartment, supporting collection at the front, rear, or both ends of the compartment. The stacked shape forms a trapezoidal inward slope, preventing tipping. The pack pressing effect is as follows... Figure 9As shown, the packing function allows for optional activation. Reducing the number of packs in the top row by one and placing them in the center gap results in a more aesthetically pleasing and robust structure. When loading to the top layer, the packing data allows for scientific packing, reducing the number of pack rows by one and placing them between the two rows above, achieving staggered packing. The stacked shape at the top of the carriage presents a trapezoidal inward shape, further enhancing the aesthetics and sturdiness of the structure. The pack throwing function, due to the fit between the specialized grippers and the pack length and width, allows for the first or last row of packs to be thrown when packs are arranged horizontally. In this case, the first and last row packs are placed according to the material safety distance, which is less than the gripper frame safety distance, increasing packing space. When packs are arranged vertically, the side row pack throwing function can be activated. In this case, the vertical packs on both sides are placed according to the material safety distance, which is less than the gripper frame safety distance, increasing packing space. Setting the pack throwing function during pack placement effectively avoids the gripper's downward collision point, increasing the gripper's range of motion, thus safely and effectively increasing the packing space in the carriage, shortening the axle's back-and-forth travel, saving twice the positioning time, and significantly improving loading efficiency. The overlapping area of ​​the packages is calculated, and the cumulative stacking ratio for each row is determined based on this area. This ratio represents the maximum overlap ratio during stacking, allowing control over the degree of overlap. Stacking data is analyzed based on this cumulative stacking ratio to check the stacking function. If the overlapping area is smaller than this set value, the layer is considered flat and without deformation. If the overlapping area is larger than this set value, it is multiplied by the ratio and added to the cumulative total. Once the cumulative total reaches the set value, a new row is added on each side of the layer to smooth out the shape, thus obtaining the stacking data.

[0036] S206: Based on the number of rows increased, the number of columns increased, the padding parameters, the overflow range on the column, the package receiving data, the package pressing data, the package throwing data, and the package stacking data, the initial package arrangement strategy and the grasping pose are adjusted to obtain the target package arrangement strategy and the target grasping pose. The intelligent loading machine performs cargo palletizing according to the target package arrangement strategy and the target grasping pose.

[0037] In a specific implementation of the present invention, the intelligent loading machine palletizes goods according to the target packing strategy and the target grasping pose, including: generating control instructions based on the target packing strategy and the target grasping pose; and controlling several grippers of the intelligent loading machine to place several target goods to be palletized into the vehicle based on the control instructions.

[0038] Specifically, the initial packing strategy and grasping pose are adjusted based on the increase in rows and columns, padding parameters, overflow range in columns, pack receiving data, pack pressing data, pack throwing data, and pack stacking data to obtain the target packing strategy and target grasping pose. Control commands are then generated based on these target packing strategy and target grasping pose. Based on these control commands, several grippers of the intelligent loading machine are controlled to place several target goods to be palletized into the vehicle. The control commands are transmitted to the intelligent loading machine, which, according to the control commands, controls four grippers to place several target goods to be palletized into the vehicle. It can safely grip 25 kg, 40 kg, and 50 kg capacity bags without breaking them. Differential belts are used to separate multiple connected goods. The robotic arm grasps the middle position of the goods and adjusts the palletizing state according to the length and width dimensions of the goods. Specific adjustments need to be made based on the palletizing position set according to the truck size. Reasonable loading reduces vehicle empty load rate and transportation frequency, thereby reducing energy consumption and carbon emissions, contributing to green logistics.

[0039] In this embodiment of the invention, an initial packing strategy is determined based on cargo attribute information, vehicle parameter information, and transportation demand information. The gripping postures of several grippers in the intelligent loading machine are analyzed based on the initial packing strategy. Cargo palletizing is then debugged based on the gripping postures and the initial packing strategy. During the cargo palletizing debugging process, the cumulative gap ratio and height error are detected. Based on the cumulative gap ratio and height error, the initial packing strategy and gripping posture are adjusted. The intelligent loading machine palletizes cargo according to the target packing strategy and target gripping posture. The packing analysis process is simple and smooth, greatly shortening loading time, improving logistics efficiency, and ensuring that goods can reach their destination in a timely manner. Using this target packing strategy for cargo palletizing can fully utilize the vehicle's space potential, making the cargo placement compact and orderly, reducing space waste, lowering transportation costs, and effectively preventing cargo displacement, collisions, and damage during transportation, providing solid protection for cargo safety.

[0040] Those skilled in the art will understand that all or part of the steps in the various methods of the above embodiments can be implemented by a program instructing related hardware. The program can be stored in a computer-readable storage medium, which may include: read-only memory (ROM), random access memory (RAM), magnetic disk or optical disk, etc.

[0041] Furthermore, the above provides a detailed description of a fully automatic intelligent loading and palletizing method provided by the embodiments of the present invention. Specific examples have been used to illustrate the principles and implementation methods of the present invention. The description of the above embodiments is only for the purpose of helping to understand the method and core ideas of the present invention. At the same time, for those skilled in the art, there will be changes in the specific implementation methods and application scope based on the ideas of the present invention. Therefore, the content of this specification should not be construed as a limitation of the present invention.

Claims

1. A fully automated intelligent loading machine palletizing method, characterized in that, The method includes: Obtain cargo attribute information, vehicle parameter information, and transportation demand information, and perform a packing strategy analysis based on the cargo attribute information, vehicle parameter information, and transportation demand information to obtain an initial packing strategy; Based on the initial packing strategy, the grasping poses of several grippers in the intelligent loading machine are analyzed to obtain the grasping poses. Based on the grasping pose and initial packing strategy, cargo palletizing is debugged, and the cumulative gap ratio and height error are detected during the cargo palletizing debugging process. The initial packing strategy and gripping pose are adjusted based on the gap accumulation ratio and height error to obtain the target packing strategy and target gripping pose. The intelligent loading machine then stacks the goods according to the target packing strategy and target gripping pose.

2. The fully automated intelligent loading machine palletizing method according to claim 1, characterized in that, The acquisition of cargo attribute information, vehicle parameter information, and transportation demand information includes: Obtain cargo attribute information and transportation demand information from the order database; The measurement trajectory is set, and the ranging sensor is controlled to measure the vehicle parameters according to the measurement trajectory to obtain vehicle parameter information.

3. The fully automated intelligent loading machine palletizing method according to claim 1, characterized in that, The initial cargo allocation strategy is obtained by analyzing the cargo attribute information, vehicle parameter information, and transportation demand information, including: Based on transportation demand information and cargo attribute information, several target goods to be palletized are identified; Based on cargo attribute information and vehicle parameter information, a packing strategy analysis is performed on several target goods to be stacked to obtain an initial packing strategy.

4. The fully automated intelligent loading machine palletizing method according to claim 3, characterized in that, The initial packing strategy is obtained by analyzing the packing strategy of several target goods to be palletized based on cargo attribute information and vehicle parameter information, including: Based on cargo attribute information and vehicle parameter information, palletizing parameters are analyzed to obtain initial palletizing parameters; The initial packing strategy is determined based on the initial palletizing parameters.

5. The fully automated intelligent loading machine palletizing method according to claim 4, characterized in that, The process of analyzing palletizing parameters based on cargo attribute information and vehicle parameter information to obtain initial palletizing parameters includes: Set the loading mode, and determine the horizontal arrangement width, vertical arrangement width, horizontal row width, vertical row width, horizontal column gap ratio, and horizontal column stacking cumulative ratio based on the cargo attribute information and vehicle parameter information combined with the loading mode; Set horizontal and vertical slot patterns; Determine the safe distance between the carriage and the grab handle collision avoidance distance; Based on the horizontal row width, vertical row width, horizontal row width, vertical row width, horizontal column gap ratio, and horizontal column stacking cumulative ratio, combined with the horizontal row gap pattern and the vertical column gap pattern, the initial stacking parameters are determined using the car body safety distance and the grab handle anti-collision distance.

6. The fully automated intelligent loading machine palletizing method according to claim 1, characterized in that, The step of analyzing the grasping poses of several grippers in the intelligent loading machine based on the initial package sorting strategy to obtain the grasping poses includes: Obtain the gripper parameters of each gripper and determine the safe distance based on the initial pack sorting strategy; Determine the central position of the cargo based on cargo attribute information; Based on the gripper parameters, safety distance, and the center position of the cargo, the gripping posture of several grippers in the intelligent loading machine is analyzed to obtain the gripping posture.

7. The fully automated intelligent loading machine palletizing method according to claim 1, characterized in that, The process of adjusting cargo palletizing based on the grasping pose and initial packing strategy, including detecting the cumulative gap ratio and height error during cargo palletizing adjustment, includes: Input the capture pose and initial packing strategy into the preset program for cargo palletizing debugging; During the cargo palletizing debugging process, the cumulative ratio of column gaps and the cumulative ratio of row gaps are calculated for each layer of cargo palletizing, and the cumulative gap ratio is determined based on the cumulative ratio of column gaps and the cumulative ratio of row gaps. Height error is detected based on a height detection program.

8. The fully automated intelligent loading machine palletizing method according to claim 1, characterized in that, The step of adjusting the initial bag-sorting strategy and grasping pose based on the gap accumulation ratio and height error to obtain the target bag-sorting strategy and target grasping pose includes: The number of rows and columns to be increased is determined based on the cumulative gap ratio, and the padding parameters are determined based on the height error; Set the overflow range, received packet data, compressed packet data, and dropped packet data in the column, and determine the stacked packet data; Based on the number of rows increased, the number of columns increased, the padding parameters, the overflow range on the column, the received packet data, the compressed packet data, the dropped packet data, and the stacked packet data, the initial packet sorting strategy and the grabbing pose are adjusted to obtain the target packet sorting strategy and the target grabbing pose.

9. The fully automated intelligent loading machine palletizing method according to claim 8, characterized in that, The determination of the stacked data includes: Calculate the overlapping area of ​​the packages and determine the cumulative ratio of horizontal stacked packages based on the overlapping area; Based on the cumulative stacking ratio of the horizontal rows, stacking data is analyzed to obtain stacking data.

10. The fully automated intelligent loading machine palletizing method according to claim 1, characterized in that, The intelligent loading machine palletizes goods according to the target packing strategy and target grasping pose, including: Based on the target packet sorting strategy and target grasping pose generation control instructions; Based on the control commands, the intelligent loading machine uses several grippers to place several target goods to be stacked into the vehicle.

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