Lifting control method and system of pallet fork and forklift

Abstract

The invention provides a fork lifting control method and system and a forklift, and relates to the technical field of fork control. The fork lifting control method comprises the steps that the current operation height of a fork is obtained in real time; according to the received lifting control instruction, the pallet fork is controlled to operate at a first speed, when the pallet fork operates until the current operation height is within a preset range of a preset goods shelf height, the pallet fork is controlled to operate at a second speed, and the second speed is smaller than the first speed; the preset shelf height is obtained based on the lifting control instruction; in the process that the pallet fork runs at the second speed, the actual target height is determined according to the real-time image in front of the pallet fork; and the pallet fork is controlled to run to the actual target height. The fork aligning device has the beneficial effects that manual fork aligning is not needed, the requirement for operators is lowered, and meanwhile the fork aligning operation efficiency and accuracy are effectively improved.

Description

Technical Field

[0001] This invention relates to the field of fork control technology, and in particular to a forklift lifting control method, system, and forklift. Background Technology

[0002] In modern logistics and warehousing systems, manual forklifts (also known as manual or electric forklifts) are an indispensable part of daily operations. To improve operational efficiency and accuracy, especially when handling palletized goods, the introduction of automated control and intelligent systems is gradually becoming a trend.

[0003] While existing technologies provide one-click layer selection for forklifts, allowing operators to quickly select and switch to a specified layer with simple operations to improve picking efficiency, fixed layer height values ​​are typically set during height pre-selection. In real-world applications, the height of shelves on the same layer within the same warehouse may vary. Furthermore, goods may need to be retrieved from or placed on the shelves, leading to differences in the actual forklift travel height. This necessitates manual fork alignment after the forks reach the designated layer to ensure accurate insertion into the shelf, demanding high operator skill and resulting in low fork alignment efficiency and accuracy. Summary of the Invention

[0004] To address the problems existing in the prior art, the present invention provides a method for controlling the lifting of forks, comprising:

[0005] Get the current running height of the forks in real time;

[0006] The forks are controlled to run at a first speed according to the received lifting control command, and when the current running height is within a preset range of the preset shelf height, the forks are controlled to run at a second speed, which is less than the first speed. The preset shelf height is obtained based on the lifting control command.

[0007] During the operation of the forks at the second speed, the actual target height is determined based on the real-time image in front of the forks;

[0008] Control the forks to move to the actual target height.

[0009] Preferably, upon receiving the lifting control command, the method further includes:

[0010] The first running direction is obtained by processing the current running height and the preset shelf height;

[0011] Determine whether the first running direction is consistent with the second running direction indicated by the lifting control command:

[0012] If so, then respond to the lifting control command to control the forks to run at the first speed;

[0013] If not, the lifting control command will not be responded to.

[0014] Preferably, the operation of the forks further includes:

[0015] When there is cargo on the forks and the forks are currently in a lowered state, or when there is no cargo on the forks, obstacles in the fork's running path are identified. If the identification result indicates that there are obstacles in the fork's running path, the forks are controlled to stop moving and an alarm is triggered.

[0016] Preferably, identifying obstacles in the fork travel path includes:

[0017] The system performs image recognition on the real-time image, and when it recognizes that there are goods on the shelf in front of the forks that protrude towards the forks and overlap with the running path, or when it recognizes a pedestrian, it outputs the recognition result indicating that there is an obstacle in the running path of the forks.

[0018] Preferably, when identifying that there are goods stored on the shelf in front of the forks, the method further includes:

[0019] The first horizontal distance from which the goods protrude from the shelf is obtained based on the real-time image recognition, and the second horizontal distance from the edge of the forks facing the shelf to the shelf is obtained.

[0020] When the first horizontal distance is greater than the second horizontal distance, it indicates that goods protruding towards the forks and overlapping with the running path are detected on the shelf in front of the forks.

[0021] Preferably, determining the actual target height based on the real-time image in front of the forks includes:

[0022] Identify the current task type;

[0023] When the current task type is a pickup task, the vertical height difference between the center of the pallet hole on the target shelf and the fork contained in the real-time image is identified and calculated;

[0024] When the current task type is a delivery task, the vertical height difference between the top edge of the target shelf and the fork in the real-time image is identified and calculated.

[0025] The actual target height is obtained by processing the difference between the current operating height and the vertical height.

[0026] Preferably, identifying the current task type includes:

[0027] The real-time image is subjected to image recognition, and when the image recognition result indicates that there is no goods on the forks, the current task type is the picking task, and when the image recognition result indicates that there are goods on the forks, the current task type is the placing task.

[0028] Preferably, after controlling the forks to operate at the second speed, the method further includes:

[0029] When the actual target height is determined, the forks are controlled to run at a third speed until they stop at the actual target height;

[0030] The third speed is less than the second speed.

[0031] The present invention also provides a lifting control system for forks, including a processor and a memory, wherein the memory includes a computer storage medium, and the processor executes the above-described lifting control method when executing the computer storage medium.

[0032] The present invention also provides a forklift, including the above-described lifting control system.

[0033] The above technical solution has at least the following advantages or beneficial effects:

[0034] 1) Based on the preset shelf height, when the current running height of the forks is close to the preset shelf height, the actual target height can be re-determined according to the collected real-time images, so that the forks can accurately run to the actual target height without manual fork alignment, reducing the requirements for operators while effectively improving the efficiency and accuracy of fork alignment.

[0035] 2) By monitoring the consistency between the running direction required to reach the preset shelf height and the running direction of the received lifting control command, the task will only start when the correct lifting control command is received, otherwise no action will be responded to, thus achieving foolproof and avoiding accidents caused by misoperation.

[0036] 3) During the lifting and lowering of the forks, if an obstacle is detected in the running path, the forks can be stopped and an alarm will be triggered, ensuring operational safety. Attached Figure Description

[0037] Figure 1 A flowchart illustrating a method for controlling the lifting of forks is provided in a preferred embodiment of the present invention.

[0038] Figure 2 In a preferred embodiment of the present invention, a side view of the mounting positions of the ranging sensor, the image acquisition device, and the control box, and a partial enlarged view of the ranging sensor are shown.

[0039] Figure 3 In a preferred embodiment of the present invention, a top view shows the mounting positions of the ranging sensor, the image acquisition device, and the control box.

[0040] Figure 4 This is a schematic diagram of the interactive interface of the control box in a preferred embodiment of the present invention.

[0041] Figure 5 In a preferred embodiment of the present invention, a flowchart is shown in which the fork running direction is monitored when a lifting control command is received.

[0042] Figure 6 In a preferred embodiment of the present invention, a schematic diagram of the field of view of the image acquisition device when a forklift picks up a pallet;

[0043] Figure 7 This is a schematic diagram of the field of view of the image acquisition device when a forklift places a pallet, as described in a preferred embodiment of the present invention. Detailed Implementation

[0044] The present invention will now be described in detail with reference to the accompanying drawings and specific embodiments. The present invention is not limited to this embodiment; other embodiments that conform to the spirit of the present invention may also fall within the scope of the present invention.

[0045] In a preferred embodiment of the present invention, based on the above-mentioned problems existing in the prior art, a method for controlling the lifting of forks is provided, such as... Figure 1 As shown, it includes:

[0046] Get the current running height of the forks in real time;

[0047] The forks are controlled to run at a first speed according to the received lifting control command. When the current running height is within a preset range of the preset shelf height, the forks are controlled to run at a second speed, which is less than the first speed. The preset shelf height is obtained based on the lifting control command.

[0048] While the forks are moving at the second speed, the actual target height is determined based on the real-time image in front of the forks;

[0049] Control the forks to move to the actual target height.

[0050] Specifically, the following explanation uses the application of forks on forklifts as an example to illustrate this technical solution. Figure 2As shown, in this embodiment, a ranging sensor 1 can be used to detect the current operating height of the fork 3 in real time. The ranging sensor 1 is a laser ranging sensor, installed at a fixed position on the bottom side of the vehicle body. A laser reflector 11 is installed on the fork 3 corresponding to the position of the laser ranging sensor. The laser reflector 11 can move with the fork 3. Preferably, the laser reflector 11 is installed directly above the laser ranging sensor to ensure that the laser emitted by the laser ranging sensor during lifting can reach the same position on the laser reflector 11, thereby detecting the current operating height of the fork 3. It is understood that the ranging sensor 1 is not limited to a laser ranging sensor; other ranging sensors can be used as needed. Furthermore, the positions of the laser ranging sensor and the laser reflector 11 can be interchanged. That is, the laser reflector 11 can be installed at a fixed position on the bottom side of the vehicle body, and the laser ranging sensor can be installed on the fork 3, moving with the fork 3 and located directly above the laser reflector 11. Furthermore, if the encoder data inside the forklift 2 can be obtained, the stroke data of the forks output by the encoder can also be converted into height data for use, so as to realize the real-time detection of the current operating height. In this case, it is not necessary to install a distance sensor 1 separately, which further saves costs.

[0051] In summary, it can be seen that the current operating height of the forks can be obtained from the ranging sensor, or by first obtaining the fork stroke data from the forklift's encoder and then converting it into height data. Alternatively, the current operating height can be calculated by first obtaining the fork's operating time and speed, and then further calculating the fork stroke. No specific method is specified here.

[0052] In one implementation method, the following can be adopted: Figure 3 An image acquisition device 5, mounted on the forks 3, acquires real-time images of the area in front of the forks 3. A control box 4, mounted on the forklift 2, then controls the lifting and lowering of the forks 3 based on the current operating height and the real-time images. The image acquisition device 5 can move with the forks 3 without interfering with their normal operation. During normal operation, the real-time images acquired by the image acquisition device 5 include real-time images of objects in front of the forks 3, such as shelves or pallets. Therefore, while the forks are moving at the second speed, the actual target height is determined based on the real-time image data of the area in front of the forks acquired by the image acquisition device 5.

[0053] Specifically, the control box 4 is preferably installed on the manual operating platform of the forklift 2, and the control box 4 is preferably provided with, for example, Figure 4 The interactive interface shown, including but not limited to a display screen, is used to display the current running height (e.g., Figure 4 The 200 (in inches) and the preset shelf height, which varies with the number of shelf layers, are as follows: Figure 4In the interface, buttons A, B, C, D, and E at the bottom represent different shelf levels. The upward arrow on the right side of the interface indicates the raise control button, and the downward arrow indicates the lower control button. In practical applications, operators can press the corresponding shelf level button on the control box 4 to select the preset shelf height, and then press the corresponding raise or lower control button to generate the corresponding lifting control command output to the forks 3, thereby controlling the forks 3 to operate accordingly.

[0054] In actual operation, the operator needs to manually press the aforementioned up or down control button. This can lead to unexpected situations, such as pressing the down control button when the shelf needs to be raised to the preset height, or pressing the up control button when the shelf needs to be lowered to the preset height. Therefore, in a preferred embodiment of the present invention, upon receiving a lifting control command, such as... Figure 5 As shown, it also includes:

[0055] The first running direction is obtained by processing the current running height and the preset shelf height;

[0056] Determine whether the first running direction is consistent with the second running direction indicated by the lifting control command:

[0057] If so, the lifting control command will be executed to control the forks to run at the first speed.

[0058] If not, the lifting control command will not be responded to.

[0059] Specifically, the first operating direction is obtained based on the current operating height and the preset shelf height, including: when the current operating height is higher than the preset shelf height, the first operating direction is a downward direction; when the current operating height is lower than the preset shelf height, the first operating direction is an upward direction.

[0060] In this embodiment, by providing the above-mentioned foolproof mechanism, the fork 3 will only be controlled to perform the corresponding movement when the first running direction of the fork should be consistent with the second running direction indicated by the operator's up control button or down control button. Otherwise, no response will be made, that is, the up control button or down control button pressed by the operator will be determined to be an invalid command, which effectively avoids unexpected situations and ensures operational safety.

[0061] Furthermore, the image acquisition device 5 is preferably a camera, consisting of... Figure 6 As can be seen, when there is no cargo on fork 3, the camera's field of view covers both the upper and lower areas in front of fork 3. Therefore, regardless of whether fork 3 is in an ascending or descending state, the real-time images captured by the camera can identify whether there are obstacles in the operating path. Figure 6As can be seen, when there is cargo on the fork 3, the camera's field of view can cover the lower area in front of the fork 3, while the upper area is limited and almost completely blocked. Therefore, only when the fork 3 is in the lowering state can the camera's real-time images be used to identify whether there are obstacles on the running path.

[0062] Therefore, in this embodiment, the operation of the forks also includes:

[0063] When there is cargo on the forks and the forks are currently in a lowered state, or when there is no cargo on the forks, obstacles in the fork's running path are identified. If the identification result indicates that there are obstacles in the fork's running path, the forks are controlled to stop moving and an alarm is triggered.

[0064] Among them, identifying obstacles in the forklift's running path includes:

[0065] The system performs image recognition on real-time images. When it detects goods on the shelf in front of the forks that protrude towards the forks and overlap with the running path, or when it detects a pedestrian, it outputs a recognition result indicating that there is an obstacle in the running path of the forks.

[0066] Specifically, in this embodiment, based on the forklift's operating environment, obstacles on the fork's running path are divided into two categories:

[0067] In the first scenario, the obstacle is goods. Here, "goods" refers to goods already stored on the shelf. However, due to improper placement or other reasons, goods located at the edge of the shelf may protrude. If a significant portion of the goods protrudes, it will overlap with the transport path, causing interference during both picking and placing. Therefore, in this embodiment, when identifying goods stored on the shelf in front of the forks, the process further includes:

[0068] The first horizontal distance of the goods protruding from the shelf is obtained based on real-time image recognition, and the second horizontal distance of the edge of the forks facing the shelf from the shelf is obtained.

[0069] When the first horizontal distance is greater than the second horizontal distance, it indicates that goods protruding towards the forks and overlapping with the running path are detected on the shelf in front of the forks.

[0070] In one embodiment, the goods and the shelf on which they are placed in the real-time image can be identified separately, and the pixel size (width or height) of the two in the real-time image can be counted separately. Based on the pre-calibrated focal length of the camera and the actual size (width or height) of the goods and the shelf, the first distance between the camera and the goods and the second distance between the camera and the shelf can be calculated using the principle of triangle similarity. The difference between the two is the first horizontal distance mentioned above.

[0071] This involves pre-collecting multiple standard images containing goods and shelves, and labeling the location and category of the goods and shelves in each standard image. Then, using the standard images as input and the corresponding location and category of the goods and shelves as output, a neural network model is trained. Based on the neural network model, the goods in the real-time image and the shelves on which they are placed can be identified.

[0072] In the second scenario, the obstacle is a pedestrian. Pedestrians usually refer to warehouse staff who need to pass in front of the shelves. Considering that forklifts are usually close to the shelves when picking up or placing goods, in order to ensure personnel safety, as long as a pedestrian is identified in the real-time image, regardless of how far away from the forks they are, it is considered that there is an obstacle on the operating path.

[0073] Specifically, in this embodiment, by recognizing the real-time images acquired by the image acquisition device 5, it is possible to promptly detect safety hazards such as obstacles obstructing the fork 3 during its lifting process, and simultaneously control the fork 3 to stop moving while issuing an alarm to promptly remind the operator to check, thus ensuring operational safety.

[0074] Furthermore, considering that the shelf heights of different shelves in the same warehouse may differ, or that the insertion height of the forks 3 may differ depending on whether goods are placed on the same shelf or not, if the forks 3 are controlled to operate according to the preset shelf height, the height of the forks 3 may not match the height required for picking up or placing goods, resulting in the inability to pick up or place goods. Therefore, it is necessary to fine-tune the actual target height according to the actual application scenario. Specifically, in a preferred embodiment of the present invention, determining the actual target height based on the real-time image in front of the forks includes:

[0075] Identify the current task type;

[0076] When the current task type is a pickup task, identify and calculate the vertical height difference between the center of the pallet hole on the target shelf and the fork contained in the real-time image;

[0077] When the current task type is a delivery task, identify and calculate the vertical height difference between the top edge of the target shelf and the fork in the real-time image.

[0078] The actual target height is obtained by processing the difference between the current operating height and the vertical height.

[0079] Specifically, in this embodiment, during the operation of the fork 3, when the current operating height of the fork 3 is close to the preset shelf height, image recognition is performed on different targets according to the current task type to calculate the vertical height difference between the fork and the target position, and then the final actual target height is determined based on the vertical height difference. It can be understood that the preset shelf height configured in the control box 4 is only the height of the shelf layer, providing a general height range to indicate which layer the fork 3 should stop at; the actual target height is the precise height at which the fork 3 ultimately needs to stop.

[0080] When the current task type is a pickup task, that is, when there is no goods on fork 3, such as... Figure 6 As shown, the goods to be retrieved are placed on a pallet, which is then placed on a shelf. The pallet needs to be removed together with the goods. Therefore, it's necessary to identify the center of the pallet hole on the target shelf. Once this hole is identified, the target point becomes the height of the center of the pallet hole, and the previously preset shelf height becomes invalid. For example, if the preset shelf height for this layer is 1.5m, image recognition might result in the fork 3 stopping at a height of 1.51m, meaning a vertical height difference of 0.01m is required for accurate insertion of the goods. When the current task type is a placement task, meaning there are goods on the pallet on the fork 3, as shown... Figure 7 As shown, the goods need to be placed on the shelf along with the pallet. Therefore, it is necessary to identify the top edge of the target shelf.

[0081] Preferably, after determining the target for identification based on the current task type, if the image acquisition device 5 and the fork 3 are on the same horizontal plane, such as Figure 6 and Figure 7 As shown, the vertical height difference can be the vertical height between the target being identified and the image acquisition device 5 itself. If the image acquisition device is not installed on the same horizontal plane as the fork 3, it needs to be able to capture both the fork and the target being identified simultaneously. Therefore, the spatial distance between the fork and the target being identified can be calculated based on the image distance between the fork and the target in the real-time image, which is the aforementioned vertical height difference.

[0082] Furthermore, identifying the current task type includes:

[0083] The system performs image recognition on real-time images. When the image recognition result indicates that there is no goods on the forks, the current task type is a pickup task. When the image recognition result indicates that there are goods on the forks, the current task type is a delivery task.

[0084] Specifically, such as Figure 6 and Figure 7 As shown, when there is cargo on the fork 3, part of the field of view of the image acquisition device 5 is blocked. In other words, the image acquisition device 5 can capture images of part of the cargo, and thus can identify the current task type based on the real-time image.

[0085] In a preferred embodiment of the present invention, after controlling the forks to operate at the second speed, the method further includes:

[0086] When the actual target height is determined, control the forks to run at the third speed until they stop at the actual target height;

[0087] The third speed is less than the second speed.

[0088] In one embodiment, the forks can be controlled to run at different speeds by outputting response voltage values. Specifically, a first voltage value can be output when a lifting control command is received to control the forks to run at a first speed, a second voltage value can be output when the current running height is within a preset range to control the forks to run at a second speed, and a third voltage value can be output when the actual target height is determined to control the forks to run at a third speed.

[0089] The magnitudes of the aforementioned first, second, and third voltage values, and their corresponding first, second, and third speeds, can be correlated with varying speeds; either a faster speed corresponds to a larger voltage value, or a slower speed corresponds to a larger voltage value. No limitation is imposed here. The first and second speeds can be pre-set fixed speeds, while the third speed is not a fixed preset speed but is related to the vertical height difference. Preferably, the smaller the vertical height difference, the slower the third speed. Correspondingly, the third voltage value may not be a fixed voltage value.

[0090] Furthermore, when the fork 3 moves close to the preset shelf height, i.e., within a preset range of the preset shelf height, it is preferable to control the fork 3 to decelerate. If it is rising, the approach to the target height will be slower; if it is descending, the approach to the target height will be slower. This preset range can be set according to needs, such as 20cm from the preset shelf height. After entering this preset range, the movement of the fork 3 slows down to facilitate image recognition.

[0091] In practical applications, considering the differences in response speed among different forklifts, different deceleration schemes can be implemented:

[0092] For forklifts with a fast response speed, the forks can be decelerated once when they reach a preset operating height within a preset range. This means that the first speed can be adjusted to the second speed, which can make the forks stop accurately at the actual target height.

[0093] For forklifts with slow response times, if deceleration is only performed once when entering the preset range, the slow response may prevent it from immediately decelerating to the second speed, which may cause the forks to rush out and stop above the actual target height. Based on this, the deceleration granularity can be further refined, that is, decelerating to the third speed again when the actual target height is determined, so that the forks can be accurately stopped at the actual target height.

[0094] Understandably, the specific deceleration scheme is not limited to the two schemes mentioned above. It can be adjusted according to the applicability of different forklifts. The overall deceleration scheme is that the speed decreases as you get closer to the actual target height, so that the forks can eventually stop accurately at the actual target height.

[0095] The present invention also provides a lifting control system for forks, including a processor and a memory, wherein the memory includes a computer storage medium, and the processor executes the above-described lifting control method when executing the computer storage medium.

[0096] The present invention also provides a forklift, including the above-described lifting control system.

[0097] The above description is merely a preferred embodiment of the present invention and does not limit the implementation and protection scope of the present invention. Those skilled in the art should realize that any equivalent substitutions and obvious changes made using the content of this specification and illustrations should be included within the protection scope of the present invention.

Claims

1. A lift control method of a fork characterized by, The method comprises: obtaining a current running height of the fork in real time; controlling the fork to run at a first speed according to a received lifting control instruction, and controlling the fork to run at a second speed when the fork runs to the current running height within a preset range of a preset shelf height, the second speed being less than the first speed, and the preset shelf height being obtained based on the lifting control instruction; during the running of the fork at the second speed, determining an actual target height based on a real-time image in front of the fork; and controlling the fork to run to the actual target height.

2. The lift control method of claim 1, wherein When the lifting control instruction is received, the method further comprises: processing a first running direction based on the current running height and the preset shelf height; determining whether the first running direction is consistent with a second running direction indicated by the lifting control instruction; if yes, controlling the fork to run at the first speed in response to the lifting control instruction; if no, not responding to the lifting control instruction.

3. The lift control method of claim 1, wherein During the running of the fork, the method further comprises: when there is a cargo on the fork and the fork is in a descending state, or when there is no cargo on the fork, identifying an obstacle on a running path of the fork; when the identification result indicates that there is an obstacle on the running path of the fork, controlling the fork to stop moving and alarming.

4. The lift control method of claim 3, wherein The identification of the obstacle on the running path of the fork comprises: performing image recognition on the real-time image, and when it is recognized that the shelf in front of the fork stores a cargo protruding towards the fork and overlapping with the running path, or when a pedestrian is recognized, outputting the identification result indicating that there is an obstacle on the running path of the fork.

5. The lift control method according to claim 4, wherein When it is recognized that the shelf in front of the fork stores a cargo, the method further comprises: recognizing, based on the real-time image, a first horizontal distance by which the cargo protrudes from the shelf, and a second horizontal distance from an edge of the shelf on a side facing the shelf to the fork; when the first horizontal distance is greater than the second horizontal distance, determining that the shelf in front of the fork stores a cargo protruding towards the fork and overlapping with the running path.

6. The lift control method of claim 1, wherein The determination of the actual target height based on the real-time image in front of the fork comprises: recognizing a current task type; when the current task type is a cargo taking task, recognizing and calculating a vertical height difference between a center of a tray hole on a target shelf included in the real-time image and the fork; when the current task type is a cargo placing task, recognizing and calculating a vertical height difference between an upper edge of the target shelf included in the real-time image and the fork; processing the actual target height based on the current running height and the vertical height difference.

7. The lift control method according to claim 6, wherein The recognition of the current task type comprises: performing image recognition on the real-time image, and when the image recognition result indicates that there is no cargo on the fork, determining that the current task type is the cargo taking task, and when the image recognition result indicates that there is a cargo on the fork, determining that the current task type is the cargo placing task.

8. The lift control method of claim 1, wherein After the fork is controlled to run at the second speed, the method further comprises: controlling the forks to run at a third speed until stopping at the actual target height when the actual target height is determined; the third speed is less than the second speed.

9. A lift control system for a fork, characterized by A lift control system comprising a processor and a memory including a computer storage medium, the processor executing the computer storage medium to perform the lift control method of any one of claims 1 to 8.

10. A fork lift truck characterised in that, A lift control system comprising the lift control system of claim 9.

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