Alignment method, system, device and storage medium based on characteristics of hoisting equipment

Abstract

The application provides a positioning method and system based on characteristics of hoisting equipment, a device and a storage medium, and the method comprises the following steps: collecting point cloud information of a container and hoisting equipment during hoisting of the container by the hoisting equipment to a container transport device; obtaining a spatial position of the container based on the point cloud information of the container; obtaining a positioning calibration parameter corresponding to a surface feature with the highest priority and a feature relative position based on surface feature recognition of the point cloud information of the hoisting equipment; and guiding the container transport device to position based on the hoisting equipment according to the positioning calibration parameter, the feature relative position and the current spatial position of the container. The application can extract structural features of a crane and a lifting tool, perform more accurate parameter calibration through priority sorting of various structural features, improve positioning accuracy, reduce workload and simplify the hoisting process.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of hoisting alignment, and in particular to a hoisting alignment method and system based on characteristics of hoisting equipment, a hoisting alignment device and a storage medium. BACKGROUND

[0002] An unmanned vehicle is an important part of the intelligentization and automation of a container terminal, and a more autonomous, efficient and accurate vehicle autonomous alignment method can greatly improve the operation efficiency. A common unmanned vehicle autonomous alignment method needs to externally modify the hoisting equipment, such as adding a high-reflective marker to the equipment for single-vehicle recognition, and needs to individually calibrate parameters for each hoisting equipment. This method increases the deployment process of the unmanned vehicle and cannot install markers on the crane equipment in some container terminals with narrow operation lanes, limiting the universality. For a manual truck driver, the alignment process is to first ensure that the truck is stopped within a preset range, and then manually observe the relative position of the spreader and the container when the spreader approaches the container to adjust the position of the truck to realize the grab-and-drop operation. This mode is low in efficiency, poor in accuracy and has a large safety risk.

[0003] Therefore, the present application provides a hoisting alignment method and system based on characteristics of hoisting equipment, a hoisting alignment device and a storage medium.

[0004] It should be noted that the information disclosed in the above background section is only used to strengthen the understanding of the background of the present application, and therefore can include information that does not constitute prior art known to those of ordinary skill in the art. SUMMARY

[0005] In view of the problems in the prior art, the present application aims to provide a hoisting alignment method and system based on characteristics of hoisting equipment, a hoisting alignment device and a storage medium, which overcome the difficulties of the prior art, can extract the structural characteristics of the crane and the spreader, prioritize multiple structural characteristics for more accurate parameter calibration, improve the alignment accuracy, reduce the workload and simplify the hoisting process.

[0006] An embodiment of the present application provides a hoisting alignment method based on characteristics of hoisting equipment, comprising the following steps:

[0007] In the process of hoisting a container by a hoisting equipment to a container transport equipment, point cloud information of the container and the hoisting equipment is collected;

[0008] Based on the point cloud information of the container, a spatial position of the container is obtained;

[0009] Based on surface feature recognition of the point cloud information of the hoisting equipment, an alignment calibration parameter and a feature relative position corresponding to a surface feature with the highest priority are obtained; and

[0010] The container transport device is guided to align with the hoisting device based on the alignment calibration parameter, the feature relative position and the current spatial position of the container.

[0011] Preferably, the point cloud information of the container and the hoisting device is collected during the process that the container is lifted by the hoisting device to the container transport device, including:

[0012] The container transport device is a truck, and the first point cloud collecting device for collecting the point cloud above is arranged on the top of the truck head in the vertical direction, and the second point cloud collecting device for collecting the point cloud above is arranged on the tail of the truck in the vertical direction, so as to collect the point cloud information of the two ends of the container and the hoisting device and / or the spreader, respectively.

[0013] The container transport device is a flat unmanned transport vehicle, and the first point cloud collecting device for collecting the point cloud above is arranged on the top of the flat unmanned transport vehicle in the vertical direction, and the second point cloud collecting device for collecting the point cloud above is arranged on the tail of the flat unmanned transport vehicle in the vertical direction, so as to collect the point cloud information of the two ends of the container and the hoisting device and / or the spreader, respectively.

[0014] Preferably, the spatial position of the container is obtained based on the point cloud information of the container, including:

[0015] The spatial position of at least one vertical plane of the container is obtained from the point cloud data through plane fitting; and

[0016] The center position of the container is obtained based on the spatial position of the vertical plane and the known length of the container.

[0017] Preferably, the alignment calibration parameter and the feature relative position corresponding to the highest priority surface feature are obtained based on the surface feature recognition of the point cloud information of the hoisting device, including:

[0018] The spatial position of the spreader is obtained based on the recognition of the point cloud information of the hoisting device; it is judged whether the height of the spreader is less than a preset threshold value, if yes, the corresponding alignment calibration parameter and feature relative position are obtained based on the surface feature of the spreader, if no, the corresponding alignment calibration parameter and feature relative position are obtained based on the surface feature of the hoisting device.

[0019] Preferably, the corresponding alignment calibration parameter and feature relative position are obtained based on the surface feature of the spreader, including:

[0020] At least one preset surface feature of the spreader is matched based on the recognition of the point cloud information of the spreader;

[0021] The matched surface feature of the spreader is sorted based on a preset priority; and

[0022] obtaining the alignment calibration parameters and the relative position of the features corresponding to the surface feature of the spreader with the highest priority.

[0023] Preferably, the identification based on the point cloud information of the spreader matches at least one preset surface feature of the spreader, including:

[0024] Based on the spatial position of the horizontal plane of the container floor and the preset height of the container, the relative height area of the spreader is obtained; the point cloud data of the outer vertical plane and / or the lower horizontal plane of the spreader is obtained by plane fitting on the point cloud located in the relative height area; when the vertical plane and the lower horizontal plane exist in the point cloud at the same time, the point cloud data of the edge at the intersection of the outer vertical plane and the lower horizontal plane is obtained.

[0025] Preferably, the matched surface features of the spreader are sorted based on a preset priority, including:

[0026] The surface features of the spreader are sorted based on a preset priority, and the preset priority sequence is the point cloud data of the edge, the point cloud data of the outer vertical plane, and the point cloud data of the lower horizontal plane.

[0027] Preferably, the corresponding alignment calibration parameters and the relative position of the features are obtained based on the surface features of the hoisting equipment, including:

[0028] The identification based on the point cloud information of the hoisting equipment matches at least one preset surface feature of the hoisting equipment, and the surface feature of the hoisting equipment includes the leg feature and the line feature on the side of the work lane, the surface feature and the line feature of the upper cross beam;

[0029] The matched surface features of the hoisting equipment are sorted based on a preset priority; and

[0030] The alignment calibration parameters and the relative position of the features corresponding to the surface feature with the highest priority are obtained.

[0031] Preferably, the guiding of the container transport equipment based on the hoisting equipment alignment according to the alignment calibration parameters, the relative position of the features, and the current spatial position of the container includes:

[0032] The preset position of the container when the preset accurate alignment is obtained according to the spatial position of the surface feature, the alignment calibration parameters corresponding to the surface feature, and the relative position of the features;

[0033] The container transport equipment is guided based on the hoisting equipment alignment according to the preset position of the container and the current spatial position of the container.

[0034] The embodiment of the present application also provides a positioning system based on the characteristics of the hoisting equipment, which is used for realizing the positioning method based on the characteristics of the hoisting equipment, and comprises the following modules:

[0035] A point cloud collection module collects point cloud information of the container and the hoisting equipment during hoisting of the container by the hoisting equipment to the container transport equipment.

[0036] A space detection module obtains a spatial position of the container based on the point cloud information of the container.

[0037] A calibration parameter module obtains a positioning calibration parameter and a feature relative position corresponding to a surface feature with the highest priority based on surface feature recognition of the point cloud information of the hoisting equipment.

[0038] A positioning guidance module guides the container transport equipment to be positioned based on the hoisting equipment according to the positioning calibration parameter, the feature relative position and the current spatial position of the container.

[0039] The embodiment of the present application also provides a positioning device based on the characteristics of the hoisting equipment, which comprises the following modules:

[0040] A processor;

[0041] A memory in which executable instructions of the processor are stored;

[0042] The processor is configured to execute the steps of the positioning method based on the characteristics of the hoisting equipment by executing the executable instructions.

[0043] The embodiment of the present application also provides a computer readable storage medium for storing a program, which is executed to realize the steps of the positioning method based on the characteristics of the hoisting equipment.

[0044] The positioning method, system, device and storage medium based on the characteristics of the hoisting equipment can extract the structural characteristics of the hoisting machine and the structural characteristics of the lifting tool, perform more accurate parameter calibration through priority sorting of multiple structural characteristics, improve positioning accuracy, reduce workload and simplify hoisting process. BRIEF DESCRIPTION OF DRAWINGS

[0045] Other features, objects and advantages of the present application will become more apparent from the following detailed description of non-limiting embodiments with reference to the attached drawings.

[0046] Figure 1 is a flowchart of the positioning method based on the characteristics of the hoisting equipment.

[0047] Figure 2 is a flowchart of the positioning method based on the characteristics of the hoisting equipment.

[0048] Figure 3 、 4 is a schematic diagram of an implementation scenario of the alignment method based on the characteristics of the hoisting equipment of the present application.

[0049] Figure 5 is a structural schematic diagram of the alignment system based on the characteristics of the hoisting equipment of the present application.

[0050] Figure 6 is a structural schematic diagram of the alignment device based on the characteristics of the hoisting equipment of the present application. And

[0051] Figure 7 is a structural schematic diagram of the computer readable storage medium of an embodiment of the present application. DETAILED DESCRIPTION

[0052] The present application can be implemented or applied in other different specific embodiments, and the details in the present application can be modified or changed according to different views and application systems without departing from the spirit of the present application. It should be noted that the embodiments in the present application and the features in the embodiments can be combined with each other without conflict.

[0053] The embodiments of the present application will be described in detail below with reference to the accompanying drawings. The present application can be embodied in various different forms, and is not limited to the embodiments described herein.

[0054] In the description of the present application, the expressions of "one embodiment", "some embodiments", "an example", "a specific example", or "some examples" mean that the specific features, structures, materials or characteristics expressed in connection with the embodiment or example are included in at least one embodiment or example of the present application. Moreover, the specific features, structures, materials or characteristics expressed can be combined in any suitable manner in any one or more embodiments or examples. In addition, the skilled in the art can combine and combine the different embodiments or examples expressed in the present application and the features of the different embodiments or examples without conflict.

[0055] In addition, the terms "first", "second" are only used for the purpose of expression, and cannot be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Therefore, the features limited by "first", "second" can explicitly or implicitly include at least one of the features. In the description of the present application, the meaning of "multiple" is two or more, unless otherwise specifically limited.

[0056] For the sake of clearness of the present application, devices irrelevant to the description are omitted, and the same reference numerals are given to the same or similar constituent elements throughout the description.

[0057] Throughout the specification, when it is said that a certain device is "connected" to another device, this includes not only the case of "direct connection" but also the case of "indirect connection" in which other elements are interposed therebetween. In addition, when it is said that a certain device "includes" a certain constituent element, other constituent elements are not excluded unless specifically stated to the contrary, and it means that other constituent elements can be further included.

[0058] When it is said that a certain device is "on" another device, this can be directly on the other device, but can also be accompanied by other devices therebetween. When it is said in contrast that a certain device is "directly on" another device, there are no other devices therebetween.

[0059] Although the terms first, second, etc. are used in the present application to indicate various elements, these elements should not be limited by these terms. These terms are only used to distinguish one element from another. For example, first interface and second interface, etc. are indicated. Also, as used in the present application, the singular forms "a," "an," and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise. It will be further understood that the terms "comprises," "comprising," "includes," and / or "including," when used herein, specify the presence of stated features, steps, operations, elements, components, items, and / or groups thereof, but do not preclude the presence or addition of one or more other features, steps, operations, elements, components, items, and / or groups thereof. As used herein, the terms "or" and "and / or" are construed to be inclusive, or mean either one or any combination thereof. Thus, "A, B, or C" or "A, B, and / or C" means "any of the following: A; B; C; A and B; A and C; B and C; A, B, and C." Exceptions to this definition are only present when the combination of elements, functions, steps, or actions are inherently mutually exclusive.

[0060] The professional terms used herein are used only to refer to specific embodiments, and are not intended to limit the present application. The singular form used herein, unless the context clearly indicates otherwise, also includes the plural form. The meaning of "include" used in the specification is to specify a certain characteristic, region, integer, step, operation, element, and / or component, and is not to exclude the presence or addition of other characteristics, regions, integers, steps, operations, elements, and / or components.

[0061] Although not defined differently, the technical terms and scientific terms used herein include the technical terms and scientific terms commonly used in the art to which the present application belongs, and all the terms have the same meaning as generally understood by those skilled in the art to which the present application belongs. The terms defined in the commonly used dictionary are additionally explained to have the meaning consistent with the relevant technical documents and the content currently prompted, and if not defined, should not be interpreted as ideal or very formal meaning.

[0062] Figure 1 is a flowchart of the alignment method based on the characteristics of the hoisting equipment of the present application. As shown in Figure 1 , the embodiment of the present application provides an alignment method based on the characteristics of the hoisting equipment, comprising the following steps:

[0063] S110, collecting point cloud information of the container and the hoisting equipment during hoisting of the container by the hoisting equipment to the container transport equipment;

[0064] S120, obtaining the spatial position of the container based on the point cloud information of the container;

[0065] S130, based on the surface feature recognition of the point cloud information of the hoisting equipment, obtaining the alignment calibration parameter and the feature relative position corresponding to the highest priority surface feature; and

[0066] S140, guiding the container transport equipment to align based on the hoisting equipment according to the alignment calibration parameter, the feature relative position and the current spatial position of the container.

[0067] The present application proposes an autonomous alignment method, which accurately detects the spatial position between the container carried by the vehicle and the multiple structural features originally possessed by the hoisting equipment through sensors such as laser radar, performs coarse alignment, extracts the relationship between the sling features and the vehicle-mounted container when the sling is detected, guides the vehicle to perform accurate alignment, realizes interaction with the hoisting equipment, and improves the efficiency of loading and unloading.

[0068] In a preferred embodiment, step S110 comprises:

[0069] The container carrying equipment is a truck, and a first point cloud collecting device for collecting point cloud above is arranged in the vertical direction on the top of the truck head, and a second point cloud collecting device for collecting point cloud above is arranged in the vertical direction on the tail of the truck, and the point cloud information of the two ends of the container and the hoisting equipment and / or the sling is collected respectively, but it is not limited thereto.

[0070] In a preferred embodiment, the step S110 comprises: the container carrying device is a flat unmanned transport vehicle, a first point cloud collecting device for collecting the point cloud above is arranged at the front of the flat unmanned transport vehicle in the vertical direction, and a second point cloud collecting device for collecting the point cloud above is arranged at the tail of the flat unmanned transport vehicle in the vertical direction, and the point cloud information of the container at both ends and the hoisting device and / or the spreader is collected respectively, but not limited thereto.

[0071] In a preferred embodiment, the step S120 comprises:

[0072] S121, obtaining the spatial position of at least one vertical surface of the container from the point cloud data through plane fitting; and

[0073] S122, obtaining the center position of the container based on the spatial position of the vertical surface and the known length of the container, but not limited thereto.

[0074] In a preferred embodiment, the step S130 comprises:

[0075] S131, obtaining the spatial position of the spreader based on the recognition of the point cloud information of the hoisting device;

[0076] S132, judging whether the height of the spreader is less than a preset threshold value, if yes, executing the step S133, and if not, executing the step S134;

[0077] S133, obtaining the corresponding alignment calibration parameters and feature relative positions based on the surface features of the spreader; and

[0078] S134, obtaining the corresponding alignment calibration parameters and feature relative positions based on the surface features of the hoisting device, but not limited thereto.

[0079] In a preferred embodiment, the step S133 comprises:

[0080] S1331, matching at least one preset surface feature of the spreader based on the recognition of the point cloud information of the spreader;

[0081] S1332, sorting the matched surface features of the spreader based on a preset priority; and

[0082] S1333, obtaining the alignment calibration parameters and feature relative positions corresponding to the surface feature of the spreader with the highest priority, but not limited thereto.

[0083] In a preferred embodiment, the step S1331 comprises:

[0084] The relative height area of the spreader is obtained based on the spatial position of the horizontal plane of the container floor and the preset height of the container; the point cloud data of the outer vertical plane and / or the point cloud data of the lower horizontal plane of the spreader are obtained by plane fitting on the point cloud located in the relative height area; when the vertical plane and the lower horizontal plane exist in the point cloud at the same time, the point cloud data of the edge at the intersection of the outer vertical plane and the lower horizontal plane is obtained, but not limited thereto.

[0085] In a preferred embodiment, step S1332 comprises:

[0086] The surface features of the spreader are sorted based on preset priorities, and the preset priority sequence is the point cloud data of the edge, the point cloud data of the outer vertical plane, and the point cloud data of the lower horizontal plane, but not limited thereto.

[0087] In a preferred embodiment, step S134 comprises:

[0088] S1341, at least one preset surface feature of the hoisting equipment is matched based on the recognition of the point cloud information of the hoisting equipment, and the surface feature of the hoisting equipment includes the leg feature and the line feature on the side of the work lane, the surface feature and the line feature of the upper beam;

[0089] S1342, the matched surface features of the hoisting equipment are sorted based on preset priorities; and

[0090] S1343, the alignment calibration parameters and the feature relative positions corresponding to the highest priority surface feature of the hoisting equipment are obtained, but not limited thereto.

[0091] In a preferred embodiment, step S140 comprises:

[0092] S141, the preset position of the container when the preset accurate alignment is achieved is obtained according to the spatial position of the surface feature, the alignment calibration parameters corresponding to the surface feature, and the feature relative positions;

[0093] S142, the container handling equipment is guided to align with the hoisting equipment based on the preset position of the container and the current spatial position of the container, but not limited thereto.

[0094] The present application extracts the structural features of the crane itself and the structural features of the spreader, does not need to add third-party markers to the equipment, and is more suitable for different wharf scenes. In the present application, various structural features of the crane equipment are extracted and sorted in priority, which is not limited to a single feature, and is more suitable for different sensor arrangements and different vehicle types. It is suitable for various hoisting equipment. In the present application, the final high-precision alignment is performed through the relative attitude of the spreader and the container, and the alignment accuracy can be controlled within ±5cm. And it does not need to calibrate the parameters of the hoisting equipment, reduces the workload, and simplifies the deployment process.

[0095] The present application can extract the structural characteristics of the crane itself and the structural characteristics of the lifting tool, perform more accurate parameter calibration through priority sorting of various structural characteristics, improve the positioning accuracy, reduce the workload and simplify the lifting process.

[0096] Figure 2 is a flowchart of the positioning method based on the characteristics of the hoisting equipment of the present application. Figure 2 As shown in the figure, the present application has the following requirements for vehicle sensor installation: for unmanned flat cars, at least one multi-line laser radar is installed at the front and rear, the radar is installed vertically to the ground, ensures that the laser field of view is upward, and makes the single vehicle have the ability to detect the crane equipment and the container; for unmanned trucks, a multi-line laser radar perpendicular to the ground is installed on the roof, and a detector (such as a multi-line laser radar / ultrasonic radar / single-line laser radar, etc.) is installed at the rear of the trailer, and the rear radar of the trailer is only used to detect the state of the container in the present application.

[0097] The present application mainly includes the following steps:

[0098] S201, acquiring positioning task information. The upstream module (such as FMS) informs the task container type, equipment type, equipment ID number (not optional), and operation type (grasping or placing the container). Among them, the operation type can be judged by the vehicle according to the preset relative position between the container and the vehicle to extract the ROI area point cloud to fit the container plane vertical plane, such as the target container exists, then it is a grasping (crane grasps the container from the vehicle) operation, and the opposite is a placing (crane places the container on the vehicle) operation.

[0099] S202, point cloud preprocessing. The point cloud is decoded and processed to remove noise, and is converted to the vehicle body coordinate system through the sensor external parameter matrix

[0100] S203, acquiring vehicle-mounted container information. According to the preset relative position between the container and the vehicle, the ROI area point cloud (region of interest point cloud) of the front and rear containers is extracted, and the RANSAC (Random Sample Consensus) is used to fit the container vertical plane (RANSAC is the abbreviation of Random Sample Consensus, which is an algorithm for calculating the mathematical model parameters of data from a sample data set containing abnormal data. RANSAC algorithm is often used in computer vision. For example, in the field of stereo vision, the matching point problem of a pair of cameras and the calculation of the basic matrix are solved), if the container vertical plane exists, the average of the point cloud coordinates of the vertical plane point cloud outside a certain proportion is taken as the container plane position P(front_container) and P(rear_container). Then the container center position is:

[0101] P(conatiner_center)=P(container_plane)+length*dir

[0102] Wherein, P(container_center) is the center position of the container, P(container_plane) is the plane position of the container, length is the length of the container, and dir is 1 for the rear plane and -1 for the front plane.

[0103] S204, detecting the spreader height information. The ROI region point cloud of the spreader is obtained according to the preset relative position relationship between the spreader position and the vehicle, and the point cloud is clustered. The lowest point of the de-clustered point cloud is the spreader height H(spreader).

[0104] S205, judging whether the spreader meets the preset spreader feature extraction height. If yes, step S206 is executed, and if no, step S211 is executed.

[0105] S206, when the spreader meets the preset spreader feature extraction height, the spreader feature extraction module is called to extract the spreader feature to obtain the spreader position P(spreader). The reason for setting the extraction height is that the spreader will shake during the lowering process. In theory, the closer the spreader position is to the container, the more accurate the alignment guide value calculated according to the spreader is. The guide value calculation formula according to the spreader feature is as follows:

[0106] Deviation = P(spreader) - P(container_plane) + Offset(Spreader)

[0107] Wherein, Deviation is the alignment guide value of the vehicle; P(spreader) is the spreader feature alignment position; P(container_plane) is the container plane position on the same side of the spreader feature; Offset(Spreader) is the calibration difference value of the spreader position and the container plane position when grabbing the container, which is generally 0.

[0108] S207, calculating the alignment guide value and smoothing the alignment guide value, and executing step S208.

[0109] S208, if the spreader cannot be detected or the spreader height does not meet the requirements, the lifting equipment feature is extracted for alignment.

[0110] S209, extract multiple fixed structure features of the crane equipment. Because the yard bridge spans the working lane and the container yard, the extracted features include the leg surface features and line features on the side of the working lane and the surface features and line features of the upper cross beam; for the shore crane, because the shore crane only spans the working lane, the extracted features are the surface features and line features of the shore crane cross beam, and the extraction steps are as follows: obtain the ROI region point cloud of the crane features. According to the correct positioning position of the task box type, give the ROI region of each feature, and extract the target region point cloud. Fit the point cloud result feature. The RANSAC method is used to fit the surface feature planes and the 2D line feature lines. For the edges (the intersection of the vertical surface and the horizontal surface) of the cross beam, the edge point of the horizontal surface is first extracted by the point cloud normal vector, and then the line feature that meets the condition in the edge point is extracted as the edge.

[0111] S210, pair and prioritize the extracted multiple features. The extracted features are labeled according to the positional relationship. The label is inside planes, inside lines, inside edges and outside planes, outside lines and outside edges. According to the preset feature priority, the extracted features are sorted, so that the highest priority feature P(feature) and the corresponding preset parameter Offset(feature) are called to calculate the positioning guide value, and the guide value formula of the feature is as follows:

[0112] Deviation = P(feature) + Offset(feature) - P(conatiner_center)

[0113] Where P(conatiner_center) is the center position of the container; Offset(feature) is the calibration parameter of the feature, and P(feature) + Offset(feature) is the center position of the equipment in theory assuming correct positioning.

[0114] S211, output the positioning guide value to the downstream module.

[0115] S212, automatically calibrating the alignment parameters. To avoid the extreme situation that the features of the spreader cannot be observed due to the field of view being blocked, and to ensure that the coarse positioning is more accurate, the application adds an automatic calibration function for the alignment parameters of the features. The vehicle determines whether automatic calibration is needed according to the initial alignment state information of the vehicle-mounted container and the real-time detected state information of the vehicle-mounted container, in combination with the vehicle speed. When the recorded feature deviation value is less than the threshold value, it is considered that the coarse alignment is successful, and the deviation value of the feature is continuously saved in the buffer. When it is detected that the coarse alignment is successful and the vehicle-mounted container state shows that the vehicle has not been kept stationary, it is considered that automatic calibration is needed. After the buffer is processed for outliers, then:

[0116] calibrated_param = param + offset

[0117] wherein calibrated_param is the calibrated parameter; param is the parameter actually used in the alignment process; offset is the average of the guide values found before and after the completion of the operation according to the time sequence, and then the process ends.

[0118] Figure 3 、 4 is a schematic diagram of an implementation scenario of the alignment method based on the features of the hoisting equipment of the application. As shown in Figure 3 、 4 , the alignment method based on the features of the hoisting equipment of the application mainly includes the following steps:

[0119] First, a first point cloud collecting device 11 for collecting point clouds above is arranged in the vertical direction at the front of the flat unmanned transport vehicle 10, and a second point cloud collecting device 12 for collecting point clouds above is arranged in the vertical direction at the tail of the flat unmanned transport vehicle 10, so as to collect point cloud information of the two ends of the container 13 and the point cloud information of the shore crane 2 and / or the spreader 21.

[0120] Then, the spatial position of at least one vertical plane 131 of the container 13 is obtained from the point cloud data through plane fitting. Based on the spatial position of the vertical plane and the known length of the container 13, the center position of the container 13 is obtained. Based on the point cloud information of the shore crane 2, the spatial position of the spreader 21 is obtained.

[0121] When the height of the spreader 21 is less than the preset threshold, the relative height region of the spreader 21 is obtained based on the spatial position of the horizontal plane of the bottom surface of the container 13 and the preset height of the container 13. The point cloud data of the outer vertical surface 15 of the spreader 21 and / or the point cloud data of the lower horizontal surface 16 are obtained by plane fitting on the point cloud located in the relative height region. When the vertical surface and the lower horizontal surface 16 exist in the point cloud at the same time, the point cloud data of the edge 14 at the intersection of the outer vertical surface 15 and the lower horizontal surface 16 is obtained. The surface features 23 of the spreader 21 are sorted based on the preset priority, and the preset priority sequence is the point cloud data of the edge 14, the point cloud data of the outer vertical surface 15, and the point cloud data of the lower horizontal surface 16. The corresponding alignment calibration parameters and feature relative positions of the surface feature 23 of the spreader 21 with the highest priority are obtained. In this embodiment, the point cloud data of the edge 14, the point cloud data of the outer vertical surface 15, and the point cloud data of the lower horizontal surface 16 are obtained by fitting algorithm, and the alignment calibration parameters and feature relative positions corresponding to the point cloud data of the edge 14 with the highest priority are selected. In other variants, only the point cloud data of the outer vertical surface 15 is obtained, and the point cloud data of the lower horizontal surface 16 and the point cloud data of the edge 14 are not successfully obtained, and the alignment calibration parameters and feature relative positions corresponding to the outer vertical surface 15 are selected.

[0122] When the height of the spreader 21 is greater than or equal to the preset threshold, at least one preset surface feature 23 of the shore crane 2 is matched based on the recognition of the point cloud information of the shore crane 2, and the surface feature 23 of the shore crane 2 includes the leg feature 22 and the line feature on the side of the working lane, the surface feature 23 and the line feature of the upper cross beam. The matched surface features 23 of the shore crane 2 are sorted based on the preset priority. The alignment calibration parameters and feature relative positions corresponding to the surface feature 23 with the highest priority are obtained.

[0123] Finally, the preset position of the container 13 at the preset accurate alignment is obtained according to the spatial position of the surface feature 23, the alignment calibration parameters and feature relative positions corresponding to the surface feature 23. The shore crane 2 is guided to align according to the preset position of the container 13 and the current spatial position of the container 13.

[0124] Figure 5 is a structural schematic diagram of the alignment system based on the features of the hoisting equipment of the present application. As shown in Figure 5 the alignment system based on the features of the hoisting equipment of the present application 5, comprising:

[0125] The point cloud acquisition module 51 acquires the point cloud information of the container and the hoisting equipment during the process of hoisting the container by the hoisting equipment to the container transport equipment.

[0126] The spatial detection module 52 obtains the spatial position of the container based on the point cloud information of the container.

[0127] The calibration parameter module 53 obtains the alignment calibration parameter and the feature relative position corresponding to the surface feature with the highest priority based on the surface feature recognition of the point cloud information of the hoisting equipment.

[0128] The alignment guiding module 54 guides the container transport equipment to align with the hoisting equipment based on the alignment calibration parameter, the feature relative position and the current spatial position of the container.

[0129] In a preferred embodiment, the container transport equipment is a truck, and the point cloud collection module 51 is configured to arrange a first point cloud collection device to collect the point cloud information above the hoisting equipment and / or the spreader at the front of the truck, and arrange a second point cloud collection device to collect the point cloud information above the hoisting equipment and / or the spreader at the rear of the truck, so as to respectively collect the point cloud information of the two ends of the container and the hoisting equipment and / or the spreader.

[0130] In a preferred embodiment, the container transport equipment is a flat unmanned transport vehicle, and the point cloud collection module 51 is configured to arrange a first point cloud collection device to collect the point cloud information above the hoisting equipment and / or the spreader at the front of the flat unmanned transport vehicle, and arrange a second point cloud collection device to collect the point cloud information above the hoisting equipment and / or the spreader at the rear of the flat unmanned transport vehicle, so as to respectively collect the point cloud information of the two ends of the container and the hoisting equipment and / or the spreader.

[0131] In a preferred embodiment, the spatial detection module 52 is configured to obtain the spatial position of at least one vertical face of the container from the point cloud data through plane fitting. The center position of the container is obtained based on the spatial position of the vertical face and the known length of the container.

[0132] In a preferred embodiment, the calibration parameter module 53 is configured to obtain the spatial position of the spreader based on the recognition of the point cloud information of the hoisting equipment. It is determined whether the height of the spreader is less than a preset threshold value. If yes, the alignment calibration parameter and the feature relative position corresponding to the surface feature of the spreader are obtained based on the surface feature of the spreader. If no, the alignment calibration parameter and the feature relative position corresponding to the surface feature of the hoisting equipment are obtained based on the surface feature of the hoisting equipment.

[0133] In a preferred embodiment, the calibration parameter module 53 is further configured to match at least one preset surface feature of the spreader based on the recognition of the point cloud information of the spreader. The matched surface features of the spreader are sorted based on a preset priority. And the alignment calibration parameter and the feature relative position corresponding to the surface feature with the highest priority are obtained.

[0134] In a preferred embodiment, the calibration parameter module 53 is further configured to obtain a relative height region of the spreader based on the spatial position of the horizontal plane of the container floor and the preset height of the container. Plane fitting is performed on the point cloud located in the relative height region to obtain the point cloud data of the outer vertical plane of the spreader and / or the point cloud data of the lower horizontal plane. When both the vertical plane and the lower horizontal plane exist in the point cloud, the point cloud data of the edge at the intersection of the outer vertical plane and the lower horizontal plane is obtained.

[0135] In a preferred embodiment, the calibration parameter module 53 is further configured to sort the surface features of the spreader based on a preset priority sequence, which is the point cloud data of the edge, the point cloud data of the outer vertical plane, and the point cloud data of the lower horizontal plane.

[0136] In a preferred embodiment, the calibration parameter module 53 is further configured to match at least one preset hoisting equipment surface feature based on the recognition of the point cloud information of the hoisting equipment, the hoisting equipment surface feature including the leg feature and line feature on the side of the work lane, the plane feature and line feature of the upper cross beam. The hoisting equipment surface features that are matched are sorted based on a preset priority. The alignment calibration parameters and feature relative positions corresponding to the hoisting equipment surface feature with the highest priority are obtained.

[0137] In a preferred embodiment, the alignment guiding module 54 is configured to obtain a preset position of the container at a preset accurate alignment according to the spatial position of the surface feature, the alignment calibration parameters and feature relative positions corresponding to the surface feature. The container handling equipment is guided to align with the hoisting equipment according to the preset position of the container and the current spatial position of the container.

[0138] The alignment system based on hoisting equipment features of the present application can extract the structural features of the crane itself and the structural features of the spreader, perform more accurate parameter calibration through priority sorting of multiple structural features, improve alignment accuracy, reduce workload, and simplify the lifting process.

[0139] The embodiment of the present application also provides an alignment device based on hoisting equipment features, which includes a processor and a memory having executable instructions of the processor stored therein. The processor is configured to perform the steps of the alignment method based on hoisting equipment features via execution of the executable instructions.

[0140] As described above, the alignment device based on hoisting equipment features of the present application can extract the structural features of the crane itself and the structural features of the spreader, perform more accurate parameter calibration through priority sorting of multiple structural features, improve alignment accuracy, reduce workload, and simplify the lifting process.

[0141] Those skilled in the art can understand that each aspect of the present application can be implemented as a system, a method or a program product. Therefore, each aspect of the present application can be embodied in a form of entirely hardware, entirely software (including firmware, microcode, etc.), or a combination of hardware and software, which can be generically referred to as "circuitry", "module" or "platform".

[0142] Figure 6 is a structural diagram of a positioning device based on a feature of hoisting equipment according to the present application. The electronic device 600 according to this embodiment of the present application will be described below with reference to Figure 6 Figure 6 The electronic device 600 shown is merely an example and should not bring any limitation to the function and use range of the embodiments of the present application.

[0143] As shown in Figure 6 , the electronic device 600 is in the form of a general computing device. The components of the electronic device 600 can include, but are not limited to, at least one processing unit 610, at least one storage unit 620, a bus 630 connecting different platform components (including the storage unit 620 and the processing unit 610), a display unit 640, etc.

[0144] The storage unit stores program codes, which can be executed by the processing unit 610, so that the processing unit 610 performs the steps according to various exemplary embodiments of the present application described in the electronic prescription flow processing method part of the present specification. For example, the processing unit 610 can perform the steps as shown in Figure 1

[0145] The storage unit 620 can include a readable medium in the form of a volatile storage unit, such as a random access memory (RAM) 6201 and / or a cache memory unit 6202, and can further include a read-only memory (ROM) 6203.

[0146] The storage unit 620 can further include a program / utility 6204 having a set of (at least one) program modules 6205, which include, but are not limited to, an operating system, one or more application programs, other program modules, and program data, each of which or a combination thereof can include implementation of a network environment.

[0147] The bus 630 can represent one or more of several types of bus structures, including a storage unit bus or storage unit controller, a peripheral bus, a graphics acceleration port, a processing unit bus, or a local bus using any of a variety of bus architectures.

[0148] ​​The electronic device 600 can also communicate with one or more external devices 700 such as a keyboard or pointing devices, a Bluetooth device, or a disk drive. These and other peripherals can be connected to the electronic device 600 by one or more peripheral interfaces 650, such as a USB hub, a Bluetooth transceiver, an antenna, or a network adapter. The communication can occur via Input / Output (I / O) interface 650. Still yet, the electronic device 600 can communicate with one or more networks, such as a local area network (LAN), a general wide area network (WAN), or a public network such as the Internet, via network adapter 660. As depicted, the network adapter 660 can be communicatively coupled to the other components of the electronic device 600 via bus 630. It should be appreciated that various other peripherals can be connected to the electronic device 600, including but not limited to a microphone, a speaker, a camera, a printer, a scanner, a facsimile machine, a digital imager, or a television set, to name a few.

[0149] The embodiment of the present application also provides a computer readable storage medium for storing a program, the program being executed to implement the steps of the lifting equipment feature-based positioning method. In some possible implementation manners, various aspects of the present application can also be implemented in the form of a program product, which includes program codes for causing a terminal device to perform the steps of the various exemplary embodiments of the present application described in the above electronic prescription flow processing method part of the specification when the program product is run on the terminal device.

[0150] As shown above, the program of the computer readable storage medium of the embodiment, when executed, can calibrate more accurate parameters by extracting the structure features of the crane itself and the lifting tool structure features, and performing priority sorting through various structure features, thereby improving the positioning accuracy, reducing the workload, and simplifying the lifting process.

[0151] Figure 7 is a structural schematic diagram of the computer readable storage medium of the present application. Referring to Figure 7 As shown, the program product 800 for implementing the above method according to the embodiment of the present application can be in the form of a portable compact disc read-only memory (CD-ROM) and includes program codes, and can be run on a terminal device such as a personal computer. However, the program product of the present application is not limited to this, and in the present document, the readable storage medium can be any tangible medium containing or storing a program, which can be used by or in combination with an instruction execution system, device or apparatus.

[0152] The program product can employ any combination of one or more computer readable media. The computer readable media can be a computer readable signal medium or a computer readable storage medium. A computer readable storage medium can be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. More specific examples (a non-exhaustive list) of the computer readable storage medium include an electrical connection having one or more wires, a portable disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or Flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0153] The computer readable storage medium can include a computer-readable medium in the form of a data signal embodied in a carrier wave, wherein the data signal modulates an electromagnetic wave, a magnetic field, or other transport mechanism. The computer readable storage medium can also include any computer-readable medium excluding a transitory, propagating signal per se.

[0154] The program code can be executed by one or more programmable processors, which can be individually, or within a group, integral to one or more machines or apparatus-based implementations of the application. Program code can be stored in one or more machine-readable medium, which can be embodied in one or more computer- readable media, in a database, in a computer memory, in a read-only memory, or on a computer has a hard disk drive. The computer-readable medium can be a computer storage medium. The computer-readable medium can be a computer-readable storage medium. The computer-readable medium can be a computer-readable storage medium.

[0155] In summary, the alignment method, system, device and storage medium based on the characteristics of the hoisting equipment can extract the structural characteristics of the crane itself and the spreader, and perform more accurate parameter calibration through priority sorting of various structural characteristics, thereby improving the alignment accuracy, reducing the workload, and simplifying the hoisting process.

[0156] The above is further detailed description of the present application in combination with specific preferred embodiments, and cannot be deemed as limitation of the specific implementation of the present application to these descriptions. For those skilled in the art to which the present application belongs, without departing from the concept of the present application, a number of simple deductions or substitutions can be made, and all of them shall be deemed as falling within the protection scope of the present application.

Claims

1. A positioning method based on characteristics of a hoisting device, characterized in that, The method comprises the following steps: In the process of hoisting the container by the hoisting equipment to the container transport equipment, point cloud information of the container and the hoisting equipment is collected, including: the container transport equipment is a truck, a first point cloud collecting device for collecting point cloud above is arranged on the top of the truck head in the vertical direction, a second point cloud collecting device for collecting point cloud above is arranged on the tail of the truck in the vertical direction, and point cloud information of the two ends of the container and the hoisting equipment and / or the spreader is collected respectively; or the container transport equipment is a flat unmanned transport vehicle, a first point cloud collecting device for collecting point cloud above is arranged on the head of the flat unmanned transport vehicle in the vertical direction, a second point cloud collecting device for collecting point cloud above is arranged on the tail of the flat unmanned transport vehicle in the vertical direction, and point cloud information of the two ends of the container and the hoisting equipment and / or the spreader is collected respectively; The spatial position of the container is obtained based on the point cloud information of the container; The spatial position of the spreader is obtained based on the identification of the point cloud information of the hoisting equipment; it is judged whether the height of the spreader is less than a preset threshold value, if yes, the relative height area of the spreader is obtained based on the spatial position of the horizontal plane of the bottom surface of the container and the preset height of the container; the point cloud information of the outer vertical plane and / or the point cloud information of the lower horizontal plane of the spreader are obtained by plane fitting on the point cloud in the relative height area; when the vertical plane and the lower horizontal plane exist in the point cloud at the same time, the point cloud information of the edge at the intersection of the outer vertical plane and the lower horizontal plane is obtained; the surface features of the spreader are sorted based on a preset priority, the sequence of the preset priority is the point cloud information of the edge, the point cloud information of the outer vertical plane, and the point cloud information of the lower horizontal plane; the alignment calibration parameter and the feature relative position corresponding to the surface feature of the spreader with the highest priority are obtained; if not, the alignment calibration parameter and the feature relative position corresponding to the surface feature of the hoisting equipment are obtained based on the surface feature of the hoisting equipment; and The container transport equipment is guided to align based on the hoisting equipment according to the alignment calibration parameter, the feature relative position, and the current spatial position of the container.

2. The alignment method based on the characteristics of hoisting equipment according to claim 1, characterized in that, The spatial position of the container is obtained based on the point cloud information of the container, including: The spatial position of at least one vertical plane of the container is obtained by plane fitting from the point cloud information; and The center position of the container is obtained based on the spatial position of the vertical plane and the known length of the container.

3. The alignment method based on the characteristics of the hoisting equipment according to claim 1, characterized in that, The alignment calibration parameter and the feature relative position corresponding to the surface feature of the hoisting equipment are obtained based on the surface feature of the hoisting equipment, including: At least one preset surface feature of the hoisting equipment is matched based on the identification of the point cloud information of the hoisting equipment, the surface feature of the hoisting equipment includes the leg feature and the line feature on the side of the working lane, the plane feature and the line feature of the upper cross beam; The surface feature of the hoisting equipment with the highest priority is sorted based on a preset priority; and The alignment calibration parameter and the feature relative position corresponding to the surface feature of the hoisting equipment with the highest priority are obtained.

4. The alignment method based on the characteristics of hoisting equipment according to claim 1, characterized in that, The container transport equipment is guided to align based on the hoisting equipment according to the alignment calibration parameter, the feature relative position, and the current spatial position of the container. obtaining a preset position of the container according to the spatial position of the surface feature, the alignment calibration parameter corresponding to the surface feature, and the feature relative position of the container at a preset accurate alignment; guiding the container transport equipment to align with the lifting equipment based on the preset position of the container and the current spatial position of the container.

5. A positioning system based on characteristics of a hoisting device, characterized in that The system comprises: a point cloud acquisition module, which acquires point cloud information of the container and the lifting equipment during hoisting of the container by the lifting equipment to the container transport equipment, including that the container transport equipment is a truck, a first point cloud acquisition device for acquiring upper point cloud is arranged on the top of the truck head in the vertical direction, a second point cloud acquisition device for acquiring upper point cloud is arranged on the tail of the truck in the vertical direction, and point cloud information of both ends of the container and the lifting equipment and / or the spreader is acquired respectively; or the container transport equipment is a flat unmanned transport vehicle, a first point cloud acquisition device for acquiring upper point cloud is arranged on the top of the vehicle head in the vertical direction, a second point cloud acquisition device for acquiring upper point cloud is arranged on the tail of the vehicle in the vertical direction, and point cloud information of both ends of the container and the lifting equipment and / or the spreader is acquired respectively; a spatial detection module, which obtains a spatial position of the container based on the point cloud information of the container; a calibration parameter module, which identifies based on the point cloud information of the lifting equipment to obtain a spatial position of the spreader; judges whether the height of the spreader is less than a preset threshold, if yes, obtains a relative height region of the spreader based on the spatial position of the horizontal plane of the bottom surface of the container and a preset height of the container; performs plane fitting on point cloud located in the relative height region to obtain point cloud information of an outer vertical plane and / or point cloud information of a lower horizontal plane of the spreader; when the vertical plane and the lower horizontal plane exist in the point cloud at the same time, obtains point cloud information of an edge at the intersection of the outer vertical plane and the lower horizontal plane; sorts surface features of the spreader based on a preset priority, the sequence of the preset priority being point cloud information of the edge, point cloud information of the outer vertical plane, and point cloud information of the lower horizontal plane; obtains an alignment calibration parameter corresponding to a surface feature with the highest priority and a feature relative position; if not, obtains an alignment calibration parameter corresponding to a surface feature and a feature relative position based on surface features of the lifting equipment; and an alignment guiding module, which guides the container transport equipment to align with the lifting equipment according to the alignment calibration parameter, the feature relative position, and the current spatial position of the container.

6. A positioning device based on characteristics of a hoisting device, characterized in that comprise: a processor; a memory having executable instructions of the processor stored therein; wherein the processor is configured to execute the steps of the alignment method based on features of a lifting equipment of any one of claims 1-4 via execution of the executable instructions.

7. A computer readable storage medium for storing a program, characterized in that, The program, when executed, implements the steps of the alignment method based on features of a lifting equipment of any one of claims 1-4. The program, when executed, implements the steps of the alignment method based on features of a lifting equipment of any one of claims 1-4.

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