An automatic hoisting method, system, electronic device and storage medium for a truck-mounted crane

Abstract

The application discloses a kind of automatic hoisting method, system, electronic equipment and storage medium of truck crane, wherein the automatic hoisting method of truck crane includes: obtaining the point cloud scanned by multiple laser radars to the same to-be-hoisted object, determine parent laser radar and child laser radar;With the point cloud of parent laser radar as target point cloud, ICP registration is carried out with the point cloud of child laser radar as source point cloud to obtain transformation matrix;The transformation matrix is converted into the transformation matrix of each child laser radar relative to parent laser radar;The point cloud obtained by transformation matrix and each laser radar is fused;Point cloud grid is constructed and cut, the first cutting surface is the intersection surface of work station and ground horizontal plane, and the second cutting surface is the horizontal plane where the bottom surface of the to-be-hoisted object is located;The projection coordinates of the bottom center point of work station on the first cutting surface are used as termination point, and the bottom center coordinates of the to-be-hoisted object are used as starting point, and the horizontal moving path of the to-be-hoisted object is obtained by ant colony algorithm.

Description

Technical Field

[0001] This invention relates to the field of hoisting technology, and in particular to an automatic hoisting method, system, electronic equipment, and storage medium for truck-mounted cranes. Background Technology

[0002] Large equipment hoisting is a common process in industrial assembly, frequently seen in power supply and distribution, chemical, and petroleum industries. Currently, the hoisting of large goods mainly relies on manually operated cranes to lift goods to designated locations or containers. However, due to the large size of the goods limiting the field of vision and the high skill requirements of manual operation, manual hoisting often leads to low hoisting accuracy and even safety accidents such as collisions between the goods and other objects. This is especially true in special scenarios, such as hoisting a large transformer into a work position recessed below ground level. Ensuring safe and accurate placement is crucial. Furthermore, if obstacles must be avoided along the hoisting path, multiple workers are needed to direct the operation, causing significant inconvenience and increasing labor costs.

[0003] Solving these technical problems has become an urgent technical challenge for the industry. Summary of the Invention

[0004] To at least solve the above-mentioned technical problems, the present invention aims to provide an automatic lifting method for truck-mounted cranes, which uses the projection coordinates of the center point of the bottom surface of the work station on the first cutting surface as the end point and the center coordinates of the bottom surface of the object to be lifted as the starting point, and obtains the horizontal movement path of the object to be lifted through an ant colony algorithm, thereby realizing automatic lifting of the object to be lifted.

[0005] To achieve the above objectives, the automatic lifting method for truck-mounted cranes provided in this application includes:

[0006] The point cloud of multiple lidar scans of the same object to be lifted is obtained, and the scans of multiple lidars of the same object to be lifted have a common intersection. The parent lidar and child lidar are determined from the multiple lidars.

[0007] ICP registration is performed using the point cloud of the parent lidar as the target point cloud and the point cloud of the child lidar as the source point cloud to obtain the transformation matrix.

[0008] The transformation matrix is ​​transformed into a transformation matrix for each child lidar relative to the parent lidar;

[0009] The transformation matrix is ​​fused with the point cloud acquired by each lidar;

[0010] Construct a point cloud mesh that includes the coordinates of the front end of the crane boom, the coordinates of the end of the crane boom, and the coordinates of the bottom surface of the object to be lifted;

[0011] The cutting point cloud grid has two cutting surfaces: the first cutting surface is the intersection of the work station and the horizontal plane of the ground, and the second cutting surface is the horizontal plane where the bottom of the object to be hoisted is located.

[0012] The projection coordinates of the bottom center point of the workstation onto the first cutting surface are used as the termination point, and the bottom center coordinates of the object to be lifted are used as the starting point. The horizontal movement path of the object to be lifted is obtained through the ant colony algorithm.

[0013] Furthermore, the horizontal movement path also includes:

[0014] The maximum travel speed, acceleration, and steering angle of the truck-mounted crane are dynamically controlled using a PID control algorithm.

[0015] Furthermore, it also includes: obtaining the height difference between the bottom of the workstation and the horizontal plane of the ground, the height of the parent lidar from the horizontal plane of the ground, the height of the end of the boom from the horizontal plane of the ground, and the horizontal coordinate difference between the end of the boom and the parent lidar.

[0016] Furthermore, in the step of obtaining the transformation matrix through ICP registration using the point cloud of the parent lidar as the target point cloud and the point cloud of the child lidar as the source point cloud, the transformation matrix of the child lidar relative to the parent lidar is obtained through ICP registration.

[0017] To achieve the above objectives, the truck-mounted crane automatic lifting system provided in this embodiment of the invention includes:

[0018] Multiple lidar sensors surround the workstation where the object to be lifted is located;

[0019] The data acquisition module acquires point clouds of scans of the same object to be lifted by multiple lidars, and the scans of the same object by multiple lidars have a common intersection;

[0020] The data processing module determines the parent and child lidars from multiple lidars;

[0021] ICP registration is performed using the point cloud of the parent lidar as the target point cloud and the point cloud of the child lidar as the source point cloud to obtain the transformation matrix.

[0022] The transformation matrix is ​​transformed into a transformation matrix for each child lidar relative to the parent lidar;

[0023] The transformation matrix is ​​fused with the point cloud acquired by each lidar;

[0024] The point cloud mesh construction module constructs a point cloud mesh that includes the coordinates of the front end of the crane boom, the coordinates of the end of the crane boom, and the coordinates of the bottom surface of the object to be lifted.

[0025] The data processing module also includes: cutting point cloud mesh, the first cutting surface is the intersection of the work station and the horizontal plane of the ground, and the second cutting surface is the horizontal plane where the bottom of the object to be hoisted is located;

[0026] The projection coordinates of the bottom center point of the workstation onto the first cutting surface are used as the termination point, and the bottom center coordinates of the object to be lifted are used as the starting point. The horizontal movement path of the object to be lifted is obtained through the ant colony algorithm.

[0027] Furthermore, the horizontal movement path also includes:

[0028] The maximum travel speed, acceleration, and steering angle of the truck-mounted crane are dynamically controlled using a PID control algorithm.

[0029] Furthermore, the data acquisition module also includes: acquiring the height difference between the bottom of the workstation and the horizontal plane of the ground, the height of the parent lidar from the horizontal plane of the ground, the height of the end of the boom from the horizontal plane of the ground, and the horizontal coordinate difference between the end of the boom and the parent lidar.

[0030] Furthermore, in the step of obtaining the transformation matrix through ICP registration using the point cloud of the parent lidar as the target point cloud and the point cloud of the child lidar as the source point cloud, the transformation matrix of the child lidar relative to the parent lidar is obtained through ICP registration.

[0031] To achieve the above objectives, embodiments of the present invention also provide an electronic device, including a processor; and

[0032] The memory is configured to store computer-executable instructions, which, when executed, cause the processor to perform the steps of the above-described automatic lifting method for truck-mounted cranes.

[0033] To achieve the above objectives, embodiments of the present invention also provide a computer-readable storage medium storing one or more programs, which, when executed by an electronic device including multiple applications, cause the electronic device to perform the steps of the above-described automatic lifting method for truck-mounted cranes.

[0034] The automatic lifting method for truck-mounted cranes according to this application includes: acquiring point clouds scanned by multiple lidars of the same object to be lifted, wherein the scans of the same object by multiple lidars have a common intersection, and determining the parent lidar and child lidars from the multiple lidars; performing ICP registration with the point cloud of the parent lidar as the target point cloud and the point cloud of the child lidar as the source point cloud to obtain a transformation matrix; converting the transformation matrix into a transformation matrix of each child lidar relative to the parent lidar; fusing the transformation matrix with the point cloud acquired by each lidar; constructing a point cloud mesh including the coordinates of the front end of the crane boom, the coordinates of the end of the crane boom, and the coordinates of the bottom surface of the object to be lifted; cutting the point cloud mesh, wherein the first cutting surface is the intersection of the work station and the horizontal plane of the ground, and the second cutting surface is the horizontal plane where the bottom surface of the object to be lifted is located; using the projection coordinates of the center point of the bottom surface of the work station on the first cutting surface as the termination point and the center coordinates of the bottom surface of the object to be lifted as the starting point, and obtaining the horizontal movement path of the object to be lifted through an ant colony algorithm. Using the projection coordinates of the center point of the bottom surface of the workstation onto the first cutting surface as the end point and the center coordinates of the bottom surface of the object to be lifted as the starting point, the horizontal movement path of the object to be lifted is obtained through the ant colony algorithm, thereby achieving automatic lifting of the object to be lifted while avoiding obstacles; saving labor costs. Attached Figure Description

[0035] The accompanying drawings are provided to further illustrate the present application and form part of the specification. Together with the embodiments of the present application, they serve to explain the present application but do not constitute a limitation thereof. In the drawings:

[0036] Figure 1 This is a flowchart illustrating the automatic lifting method of a truck-mounted crane according to an embodiment of this application;

[0037] Figure 2 This is a schematic diagram of the automatic lifting system for truck-mounted cranes according to an embodiment of this application;

[0038] Figure 3 This is a structural diagram of the object to be lifted in an embodiment of this application when it is located above the workstation;

[0039] Figure 4 This is a schematic diagram of the structure when the object to be lifted is translated towards the workstation according to an embodiment of this application;

[0040] Figure 5 This is a schematic diagram of the structure of an electronic device according to an embodiment of this application.

[0041] Explanation of reference numerals in the attached figures:

[0042] 301 - Truck-mounted crane; 302 - Crane boom; 303 - Workstation; 304 - LiDAR; 305 - Bottom of workstation; 306 - Obstacle; 307 - Object to be lifted. Detailed Implementation

[0043] Embodiments of this application will now be described in more detail with reference to the accompanying drawings. While some embodiments of this application are shown in the drawings, it should be understood that this application can be implemented in various forms and should not be construed as limited to the embodiments set forth herein. Rather, these embodiments are provided to provide a more thorough and complete understanding of this application. It should be understood that the drawings and embodiments of this application are for illustrative purposes only and are not intended to limit the scope of protection of this application.

[0044] It should be understood that the steps described in the method embodiments of this application may be performed in different orders and / or in parallel. Furthermore, the method embodiments may include additional steps and / or omit the steps shown. The scope of this application is not limited in this respect.

[0045] The term "comprising" and its variations as used herein are open-ended inclusions, meaning "including but not limited to". The term "based on" means "at least partially based on". The term "one embodiment" means "at least one embodiment"; the term "another embodiment" means "at least one additional embodiment"; the term "some embodiments" means "at least some embodiments". Definitions of other terms will be given in the description below.

[0046] It should be noted that the terms "one" and "multiple" used in this application are illustrative rather than restrictive, and those skilled in the art should understand that, unless explicitly stated otherwise in the context, they should be understood as "one or more". "Multiple" should be understood as two or more.

[0047] The embodiments of this application will now be described in detail with reference to the accompanying drawings.

[0048] This invention provides an automatic lifting method for truck-mounted cranes, comprising:

[0049] The point cloud of multiple lidar scans of the same object to be lifted is obtained, and the scans of multiple lidars of the same object to be lifted have a common intersection. The parent lidar and child lidar are determined from the multiple lidars.

[0050] ICP registration is performed using the point cloud of the parent lidar as the target point cloud and the point cloud of the child lidar as the source point cloud to obtain the transformation matrix.

[0051] The transformation matrix is ​​transformed into a transformation matrix for each child lidar relative to the parent lidar;

[0052] The transformation matrix is ​​fused with the point cloud acquired by each lidar;

[0053] Construct a point cloud mesh that includes the coordinates of the front end of the crane boom, the coordinates of the end of the crane boom, and the coordinates of the bottom surface of the object to be lifted;

[0054] The cutting point cloud grid has two cutting surfaces: the first cutting surface is the intersection of the work station and the horizontal plane of the ground, and the second cutting surface is the horizontal plane where the bottom of the object to be hoisted is located.

[0055] The projection coordinates of the bottom center point of the workstation onto the first cutting surface are used as the termination point, and the bottom center coordinates of the object to be lifted are used as the starting point. The horizontal movement path of the object to be lifted is obtained through the ant colony algorithm.

[0056] Example 1

[0057] Figure 1 This is a flowchart illustrating the automatic lifting method for truck-mounted cranes according to an embodiment of this application. Figure 3 This is a structural diagram of the object to be lifted when it is located above the workstation, according to an embodiment of this application. Figure 4 This is a structural schematic diagram of the object to be lifted being translated towards the workstation according to an embodiment of this application. The following will be combined with... Figure 1 , 3 -4 provides a detailed description of the automatic lifting method for truck-mounted cranes according to embodiments of this application.

[0058] The automatic lifting method for truck-mounted cranes in this application embodiment is applicable to the automatic lifting of truck-mounted cranes 301, which are truck-mounted cranes, including wheeled truck-mounted cranes and crawler truck-mounted cranes.

[0059] First, in step 101, point clouds of multiple lidars scanning the same object to be lifted are obtained. The scans of the same object by multiple lidars have a common intersection. The parent lidar and child lidar are determined from the multiple lidars.

[0060] In one exemplary embodiment, taking the work station 303 where the object to be lifted 307 needs to be placed below the ground surface as an example, the work station 303 that accommodates the object to be lifted 307 is in the shape of a groove.

[0061] In one exemplary embodiment, when the object to be lifted 307 is placed on the workstation 303 as needed, the upper part of the object to be lifted 307 may be level with the ground surface; or the upper part of the object to be lifted 307 may be slightly protruding above the ground surface.

[0062] In one exemplary embodiment, multiple lidar sensors 304 surround the workstation 303. For example, when the workstation 303 is rectangular, four lidar sensors 304 are arranged above the four corners of the workstation 303, i.e., the lidar sensors 304 are positioned on the ground surface. Figure 3 As shown.

[0063] In one exemplary embodiment, a plurality of lidar sensors 304 are arranged at equal intervals around the workstation 303.

[0064] In one exemplary embodiment, the ground clearance of the lidar 304 is designed to ensure that the workstation 303 and the surrounding obstacles 306 between the workstation 303 and the temporary placement point of the object to be lifted 307 can be detected.

[0065] In one exemplary implementation, lidar (light detection and routing) is an optical remote sensing technology that measures parameters such as the target's azimuth and distance by illuminating the target with a pulsed laser beam.

[0066] In one exemplary embodiment, if a laser beam is scanned along a certain trajectory, the information of reflected laser points will be recorded while scanning. Since the scanning is extremely precise, a large number of laser points can be obtained, thus forming a laser point cloud, i.e., a point cloud.

[0067] In one exemplary embodiment, the scans of the same object to be lifted 307 by multiple lidars 304 have a common intersection, which can be understood as the lidars 304 being able to illuminate the same object to be lifted 307.

[0068] In one exemplary embodiment, after acquiring point clouds scanned by multiple lidars 304 on the same object to be lifted 307, the method further includes filtering and downsampling the point clouds as needed.

[0069] In one exemplary implementation, filtering is used to eliminate high-frequency noise; filtering and downsampling are used to reduce the hardware requirements for subsequent registration, i.e., ICP registration.

[0070] In one exemplary embodiment, one of the multiple lidars 304 is selected as the parent lidar, and the remaining lidars are child lidars.

[0071] In one exemplary embodiment, the parent lidar can be selected as the lidar 304 that has the widest imaging range of the object to be suspended 307.

[0072] In step 102, ICP registration is performed using the point cloud of the parent lidar as the target point cloud and the point cloud of the child lidar as the source point cloud to obtain the transformation matrix.

[0073] In one exemplary implementation, ICP (Iterative Closest Point) registration is a point cloud registration algorithm, mainly used to find rotation and translation parameters so that point clouds in two different coordinate systems can overlap.

[0074] In one exemplary implementation, ICP registration is for 3D reconstruction, that is, reconstruction is performed after scanning by LiDAR 304, to align and fuse point clouds acquired from different viewpoints to generate a complete 3D model.

[0075] In one exemplary implementation, registration is the process of finding a spatial transformation relationship between two sets of three-dimensional data points from different coordinate systems, so that the two sets of points can be unified into the same coordinate system.

[0076] In one exemplary embodiment, ICP registration obtains the transformation matrix of the sub-library radar relative to the parent radar, that is, using the point cloud of the sub-library radar as the source point cloud, it is converted into displacement and Euler angles relative to the target point cloud.

[0077] In one exemplary implementation, the transformation matrix is ​​transformed into a transformation matrix for each child lidar relative to the parent lidar.

[0078] In an exemplary implementation, for example, a point in the sub-LiDAR point cloud has coordinates [x, y, z] in the coordinate system. The transformation matrix from the coordinate system of the parent LiDAR point cloud to the coordinate system of the sub-LiDAR point cloud is RT. Assuming the corresponding point coordinates in the coordinate system of the parent LiDAR point cloud are [a, b, c], then [x, y, z, 1]' = RT × [a, b, c, 1]', and correspondingly [a, b, c, 1] = the inverse of RT × [x, y, z, 1]. That is, the coordinate system of the unified LiDAR 304 is transformed to the coordinate system of the parent LiDAR point cloud by multiplying the corresponding point coordinates in the coordinate system of the sub-LiDAR point cloud by the inverse of the transformation matrix. The 1 is added to the above coordinates because the transformation matrix is ​​of order 4 and needs to be matched before multiplication.

[0079] In one exemplary implementation, ICP registration obtains the transformation matrix of the sub-lidar relative to the parent lidar.

[0080] Step 103: Fuse the transformation matrix with the point cloud acquired by each lidar.

[0081] In one exemplary embodiment, the transformation matrix of the sub-LiDAR relative to the parent LiDAR is obtained through ICP registration. The coordinates of each point in the sub-LiDAR point cloud are multiplied by the inverse of the transformation matrix to obtain the coordinates of that point in the parent LiDAR. The coordinates of each sub-LiDAR are unified into the coordinate point cloud of the parent LiDAR, which is equivalent to all LiDARs 304 using the coordinate system of the parent LiDAR.

[0082] In one exemplary embodiment, after point cloud fusion, the fused point cloud is further downsampled to the point cloud density acquired by a single lidar 304; that is, the point cloud is subjected to density downsampling processing in order to restore the point cloud to a reasonable level, that is, to the point cloud density level acquired by a single lidar 304.

[0083] In one exemplary implementation, the new coordinate system of the fused point cloud is set as the point cloud coordinate system.

[0084] Step 104: Construct a point cloud mesh including the coordinates of the front end of the crane boom, the coordinates of the end of the crane boom, and the coordinates of the bottom surface of the object to be lifted.

[0085] In one exemplary embodiment, the coordinates of the boom end of the truck-mounted crane 301 in the truck-mounted crane 301 coordinate system and the coordinates in the point cloud coordinate system are obtained. By measurement, the coordinate difference between the origin of the truck-mounted crane 301 coordinate system and the origin of the point cloud coordinate system in three-dimensional space can be determined to be [-Δx, -Δy, -Δz]. T The system acquires in real-time the deflection angle α, pitch angle θ, length l, and hook sag length h of the boom 302 in the coordinate system of the truck-mounted crane 301. The coordinates of the hook in the point cloud coordinate system are [lcosθcosα-Δx,lcosθsinα-Δy,lsinθ-h-Δz]. T After the measurement is completed, the point cloud mesh is obtained.

[0086] In one exemplary embodiment, the front end of the boom 302 is the end of the boom 302 connected to the truck crane 301; the rear end of the boom 302 is the end of the boom 302 away from the truck crane 301, that is, the end connected to the hook.

[0087] In one exemplary embodiment, the bottom coordinates of the object to be lifted 307 are the bottom coordinates of the object to be lifted 307 when it is placed in the temporary storage area.

[0088] Step 105: Cut the point cloud mesh. The first cutting surface is the intersection of station 303 and the horizontal surface of the ground. The second cutting surface is the horizontal surface where the bottom of the object to be lifted is located.

[0089] In one exemplary embodiment, the point cloud mesh is cut, and the first cutting surface is the intersection of station 303 and the horizontal surface of the ground, that is, the intersection of the upper part of station 303 and the ground surface, or the cutting surface of the horizontal surface of the ground where station 303 is located.

[0090] In one exemplary embodiment, the point cloud mesh is cut, and the second cutting surface is the horizontal plane where the bottom surface of the object to be lifted 307 is located; that is, the horizontal plane where the bottom surface of the object to be lifted 307 is located when the object to be lifted 307 is in the temporary placement position.

[0091] In an exemplary embodiment, for example, workstation 303 is location A and temporary storage location is location B. It is necessary to hoist the object 307 located at location B into workstation 303 at location A. The first cutting surface is the horizontal surface of the ground at workstation 303 at location A, and the second cutting surface is the horizontal surface of the bottom surface of the object 307 located at location B. The horizontal surface of the bottom surface of the object 307 is selected as the second cutting surface because a cushioning pad is usually laid under the bottom surface of the object 307. In order to reduce the calculation of the thickness of the cushioning pad, the horizontal surface of the bottom surface of the object 307 is used as the second cutting surface.

[0092] In one exemplary embodiment, the first cutting surface obtains the coordinates of the center of the cut surface contour, and obtains the coordinates of the center point of the bottom surface of the workstation 303 based on the height difference between the bottom surface of the workstation 303 and the horizontal plane of the ground; assuming the obtained coordinates of the center of the cut surface contour are [a, b, c] T If the height difference between the point cloud coordinate system and the ground is h0, and the height difference between the ground and the container ground is h1, then the coordinates of the center of the container's bottom surface are [a, b, -h0 - h1]. T .

[0093] In one exemplary embodiment, for the second cutting surface, assuming the height from the hook to the bottom surface of the cargo is h2, the coordinates of the center of the cargo's bottom surface are [lcosθcosα-Δx,lcosθsinα-Δy,lsinθ-h-h2-Δz]. T The projected coordinates from the center of the container's bottom surface to this horizontal plane are [a, b, lsinθ-h-h²-Δz]. T .

[0094] Step 106: Take the projection coordinates of the center point of the bottom surface of the workstation onto the first cutting surface as the end point, and the center coordinates of the bottom surface of the object to be lifted as the starting point, and obtain the horizontal movement path of the object to be lifted using the ant colony algorithm.

[0095] In one exemplary embodiment, the center point of the bottom surface of the workstation 303 is projected onto the first cutting surface as the end point; the center coordinates of the bottom surface of the object to be lifted 307 are taken as the starting point, that is, the center coordinates of the bottom surface of the object to be lifted 307 located at the temporary placement area are taken as the starting point.

[0096] In an exemplary embodiment, the horizontal movement path of the object to be lifted 307 is obtained by ant colony algorithm, that is, the horizontal movement path of the object to be lifted 307 from the starting point to the ending point is obtained by ant colony algorithm. The purpose of using ant colony algorithm is that there will be obstacles 306 in the contours of the first cutting surface and the second cutting surface. That is, whether there are obstacles 306 blocking the straight distance route of the truck crane 301 from the starting point to the ending point needs to be considered.

[0097] In one exemplary embodiment, the maximum travel speed, acceleration, and steering angle of the truck-mounted crane 301 are dynamically controlled using a PID control algorithm. Using the PID control algorithm, the object to be lifted 307 is transported to the endpoint along a horizontal movement path obtained through an ant colony algorithm. Then, the hook is lowered so that the bottom surface of the object to be lifted 307 gradually approaches the center of the workstation bottom 305 [a,b,-h0-h1]. T The hoisting is completed when the bottom surface of the object to be hoisted 307 is attached to the bottom surface of the work station 303.

[0098] In one exemplary embodiment, the method further includes obtaining the height difference between the bottom of the workstation 303 (i.e., the bottom of the workstation 305) and the horizontal plane of the ground, the height of the parent lidar from the horizontal plane of the ground, the height of the end of the boom 302 from the horizontal plane of the ground, and the horizontal coordinate difference between the end of the boom 302 and the parent lidar.

[0099] In one exemplary embodiment, the height difference between the bottom of workstation 303, i.e., the bottom of workstation 305, and the horizontal plane of the ground is the depth of workstation 303.

[0100] In one exemplary embodiment, the height of the parent lidar above the horizontal plane of the ground is the ground clearance of the parent lidar.

[0101] Example 2

[0102] Figure 2 This is a schematic diagram of the automatic lifting system for truck-mounted cranes according to an embodiment of this application. Figure 3 This is a structural diagram of the object to be lifted when it is located above the workstation, according to an embodiment of this application. Figure 4 This is a structural schematic diagram of the object to be lifted being translated towards the workstation according to an embodiment of this application. The following will be combined with... Figure 2-4 The automatic lifting system for truck-mounted cranes according to embodiments of this application will be described in detail.

[0103] In one exemplary embodiment, the truck-mounted crane automatic lifting system of this application includes: a plurality of lidar sensors 304.

[0104] In one exemplary embodiment, multiple lidar sensors 304 surround the workstation 303 that houses the object to be lifted 307. For example, if the workstation 303 is rectangular, four lidar sensors 304 are positioned above the four corners of the workstation 303, meaning the lidar sensors 304 are positioned above the ground. Figure 3 As shown.

[0105] In one exemplary embodiment, the workstation 303 is recessed, meaning that at least part of the workstation 303 is recessed below the ground surface, or that when the object to be lifted 307 is placed on the workstation 303, at least part of the object to be lifted 307 is submerged below the ground surface.

[0106] In one exemplary embodiment, a plurality of lidar sensors 304 are arranged at equal intervals around the workstation 303.

[0107] In one exemplary embodiment, the ground clearance of the lidar 304 is designed to ensure that the workstation 303 and the surrounding obstacles 306 between the workstation 303 and the temporary placement point of the object to be lifted 307 can be detected.

[0108] In one exemplary embodiment, the truck-mounted crane automatic lifting system of this application includes: a data acquisition module 201.

[0109] In one exemplary embodiment, the data acquisition module 201 is used to acquire point clouds of the same object to be lifted 307 scanned by multiple lidars 304 above the hoisting equipment.

[0110] In one exemplary embodiment, the scans of the same object to be lifted 307 by multiple lidars 304 have a common intersection, which can be understood as the lidars 304 being able to illuminate the same object to be lifted 307.

[0111] In one exemplary embodiment, the data acquisition module 201 includes a plurality of lidars 304; it can be understood that the lidars 304 belong to the data acquisition module 201, or that the data acquired by the data acquisition module 201 is at least partially acquired through the lidars 304.

[0112] In one exemplary embodiment, one of the multiple lidars 304 is selected as the parent lidar, and the remaining lidars 304 are child lidars.

[0113] In one exemplary embodiment, the parent lidar can be selected as the lidar 304 that has the widest imaging range of the object to be suspended 307.

[0114] In one exemplary embodiment, the truck-mounted crane automatic lifting system of this application further includes a data processing module 202.

[0115] In one exemplary embodiment, the data processing module 202 determines the parent lidar and child lidar from a plurality of lidars 304.

[0116] In one exemplary embodiment, after acquiring point clouds scanned by multiple lidar sensors 304 on the same object to be lifted 307, the data processing module 202 further includes filtering and downsampling the point clouds.

[0117] In one exemplary implementation, filtering is used to eliminate high-frequency noise; filtering and downsampling are used to reduce the hardware requirements for subsequent registration, i.e., ICP registration.

[0118] In one exemplary implementation, ICP (Iterative Closest Point) registration is a point cloud registration algorithm, mainly used to find rotation and translation parameters so that point clouds in two different coordinate systems can overlap.

[0119] In one exemplary implementation, ICP registration is for 3D reconstruction, that is, reconstruction is performed after scanning by LiDAR 304, to align and fuse point clouds acquired from different viewpoints to generate a complete 3D model.

[0120] In one exemplary implementation, registration is the process of finding a spatial transformation relationship between two sets of three-dimensional data points from different coordinate systems, so that the two sets of points can be unified into the same coordinate system.

[0121] In one exemplary implementation, ICP registration is performed using the point cloud of the parent lidar as the target point cloud and the point cloud of the child lidar as the source point cloud to obtain the transformation matrix.

[0122] In one exemplary embodiment, ICP registration obtains the transformation matrix of the sub-library radar relative to the parent radar, that is, using the point cloud of the sub-library radar as the source point cloud, it is converted into displacement and Euler angles relative to the target point cloud.

[0123] In an exemplary implementation, for example, a point in the sub-LiDAR point cloud has coordinates [x, y, z] in the coordinate system. The transformation matrix from the coordinate system of the parent LiDAR point cloud to the coordinate system of the sub-LiDAR point cloud is RT. Assuming the corresponding point coordinates in the coordinate system of the parent LiDAR point cloud are [a, b, c], then [x, y, z, 1]' = RT × [a, b, c, 1]', and correspondingly [a, b, c, 1] = the inverse of RT × [x, y, z, 1]. That is, the coordinate system of the unified LiDAR 304 is transformed to the coordinate system of the parent LiDAR point cloud by multiplying the corresponding point coordinates in the coordinate system of the sub-LiDAR point cloud by the inverse of the transformation matrix. The 1 is added to the above coordinates because the transformation matrix is ​​of order 4 and needs to be matched before multiplication.

[0124] In one exemplary implementation, the transformation matrix is ​​transformed into a transformation matrix for each child lidar relative to the parent lidar.

[0125] In one exemplary implementation, the transformation matrix is ​​fused with the point cloud acquired by each lidar 304.

[0126] In one exemplary embodiment, the transformation matrix of the sub-LiDAR relative to the parent LiDAR is obtained through ICP registration. The coordinates of each point in the sub-LiDAR point cloud are multiplied by the inverse of the transformation matrix to obtain the coordinates of that point in the parent LiDAR. The coordinates of each sub-LiDAR are unified into the coordinate point cloud of the parent LiDAR, which is equivalent to all LiDARs 304 using the coordinate system of the parent LiDAR.

[0127] In one exemplary embodiment, after point cloud fusion, the fused point cloud is further downsampled to the point cloud density acquired by a single lidar 304; that is, the point cloud is subjected to density downsampling processing in order to restore the point cloud to a reasonable level, that is, to the point cloud density level acquired by a single lidar 304.

[0128] In one exemplary embodiment, the data acquisition module 201 further includes: acquiring the height difference between the bottom of the workstation 303 (i.e., the bottom of the workstation 305) and the horizontal surface of the ground, the height of the parent lidar from the horizontal surface of the ground, the height of the end of the boom 302 from the horizontal surface of the ground, and the horizontal coordinate difference between the end of the boom 302 and the parent lidar.

[0129] In one exemplary embodiment, the data processing module 202 further includes: after acquiring point clouds scanned by multiple lidars 304 on the same object to be lifted 307, filtering and downsampling the point clouds.

[0130] In one exemplary embodiment, the truck-mounted crane automatic lifting system of this application further includes: a point cloud mesh construction module 203.

[0131] In one exemplary embodiment, the point cloud mesh construction module 203 constructs a point cloud mesh including the coordinates of the front end of the boom 302 of the truck-mounted crane 301, the coordinates of the end of the boom 302, and the coordinates of the bottom surface of the object to be lifted 307.

[0132] In one exemplary embodiment, the coordinates of the end of the boom 302 of the truck-mounted crane 301 in the coordinate system of the truck-mounted crane 301 and in the point cloud coordinate system are obtained. By measurement, the coordinate difference between the origin of the coordinate system of the truck-mounted crane 301 and the origin of the point cloud coordinate system in three-dimensional space can be determined to be [-Δx, -Δy, -Δz]. T The system acquires in real-time the deflection angle α, pitch angle θ, length l, and hook sag length h of the boom 302 in the coordinate system of the truck-mounted crane 301. The coordinates of the hook in the point cloud coordinate system are [lcosθcosα-Δx,lcosθsinα-Δy,lsinθ-h-Δz]. T After the measurement is completed, the point cloud mesh is obtained.

[0133] In one exemplary embodiment, the front end of the boom 302 is the end of the boom 302 connected to the truck crane 301; the rear end of the boom 302 is the end of the boom 302 away from the truck crane 301, that is, the end connected to the hook.

[0134] In one exemplary embodiment, the bottom coordinates of the object to be lifted 307 are the bottom coordinates of the object to be lifted 307 when it is placed in the temporary storage area.

[0135] In one exemplary embodiment, the data processing module 202 further includes: cutting point cloud mesh, the first cutting surface being the intersection of the work station 303 and the horizontal surface of the ground, and the second cutting surface being the horizontal surface where the bottom surface of the object to be hoisted is located.

[0136] In one exemplary embodiment, the point cloud mesh is cut, and the first cutting surface is the intersection of station 303 and the horizontal surface of the ground, that is, the intersection of the upper part of station 303 and the ground surface, or the cutting surface of the horizontal surface of the ground where station 303 is located.

[0137] In one exemplary embodiment, the point cloud mesh is cut, and the second cutting surface is the horizontal plane where the bottom surface of the object to be lifted 307 is located; that is, the horizontal plane where the bottom surface of the object to be lifted 307 is located when the object to be lifted 307 is in the temporary placement position.

[0138] In an exemplary embodiment, for example, workstation 303 is location A and temporary storage location is location B. It is necessary to hoist the object 307 located at location B into workstation 303 at location A. The first cutting surface is the horizontal surface of the ground at workstation 303 at location A, and the second cutting surface is the horizontal surface of the bottom surface of the object 307 located at location B. The horizontal surface of the bottom surface of the object 307 is selected as the second cutting surface because a cushioning pad is usually laid under the bottom surface of the object 307. In order to reduce the calculation of the thickness of the cushioning pad, the horizontal surface of the bottom surface of the object 307 is used as the second cutting surface.

[0139] In one exemplary embodiment, the first cutting surface obtains the coordinates of the center of the cut surface contour, and obtains the coordinates of the center point of the bottom surface of the workstation 303 based on the height difference between the bottom surface of the workstation 303 and the horizontal plane of the ground; assuming the obtained coordinates of the center of the cut surface contour are [a, b, c] T If the height difference between the point cloud coordinate system and the ground is h0, and the height difference between the ground and the container ground is h1, then the coordinates of the center of the container's bottom surface are [a, b, -h0 - h1]. T .

[0140] In one exemplary embodiment, for the second cutting surface, assuming the height from the hook to the bottom surface of the cargo is h2, the coordinates of the center of the cargo's bottom surface are [lcosθcosα-Δx,lcosθsinα-Δy,lsinθ-h-h2-Δz]. TThe projected coordinates from the center of the container's bottom surface to this horizontal plane are [a, b, lsinθ - h - h² - Δz]. T .

[0141] In one exemplary embodiment, the projection coordinates of the bottom center point of the workstation 303 onto the first cutting surface are used as the termination point, and the bottom center coordinates of the object to be lifted 307 are used as the starting point. The horizontal movement path of the object to be lifted 307 is obtained through an ant colony algorithm.

[0142] In one exemplary embodiment, the center point of the bottom surface of the workstation 303 is projected onto the first cutting surface as the end point; the center coordinates of the bottom surface of the object to be lifted 307 are taken as the starting point, that is, the center coordinates of the bottom surface of the object to be lifted 307 located at the temporary placement area are taken as the starting point.

[0143] In an exemplary embodiment, the horizontal movement path of the object to be lifted 307 is obtained by ant colony algorithm, that is, the horizontal movement path of the object to be lifted 307 from the starting point to the ending point is obtained by ant colony algorithm. The purpose of using ant colony algorithm is that there will be obstacles 306 in the contours of the first cutting surface and the second cutting surface. That is, whether there are obstacles 306 blocking the straight distance route of the truck crane 301 from the starting point to the ending point needs to be considered.

[0144] In one exemplary embodiment, the maximum travel speed, acceleration, and steering angle of the truck-mounted crane 301 are dynamically controlled using a PID control algorithm. Using the PID control algorithm, the object to be lifted 307 is transported to the endpoint along a horizontal movement path obtained through an ant colony algorithm. Then, the hook is lowered so that the bottom surface of the object to be lifted 307 gradually approaches the center of the bottom surface of the workstation 303 [a,b,-h0-h1]. T The hoisting is completed when the bottom surface of the object to be hoisted 307 is attached to the bottom surface of the work station 303.

[0145] Example 3

[0146] Figure 5 This is a schematic diagram of the structure of an electronic device according to an embodiment of the present invention, such as... Figure 5 As shown, at the hardware level, this electronic device includes a processor, and optionally also includes a bus, a network interface, and memory. The memory may include main memory, such as high-speed random-access memory (RAM), or non-volatile memory, such as at least one disk drive. Of course, this electronic device may also include other hardware required for other business operations.

[0147] Processors, network interfaces, and memory can be interconnected via buses, which can be ISA (Industry Standard Architecture) buses, PCI (Peripheral Component Interconnect) buses, or EISA (Extended Industry Standard Architecture) buses, etc. Buses can be categorized as address buses, data buses, control buses, etc. For ease of representation, Figure 5 The symbol is represented by a single double-headed arrow, but this does not mean that there is only one bus or one type of bus.

[0148] Memory is used to store programs. Specifically, programs can include program code, which includes computer operation instructions.

[0149] The processor reads the corresponding computer program from non-volatile memory into memory and then runs it, forming a shared resource access control device at the logical level. The processor executes the program stored in memory and specifically performs the steps of the above-described automatic lifting method for truck-mounted cranes.

[0150] Example 4

[0151] This invention also proposes a computer-readable storage medium storing one or more programs, each program including instructions that, when executed by a portable electronic device including multiple applications, enable the portable electronic device to perform the methods of the embodiments shown in the accompanying drawings, specifically for performing the steps of the above-described automatic lifting method for truck-mounted cranes. While the embodiments disclosed in this invention are as described above, they are merely illustrative of the invention and are not intended to limit the invention. Any person skilled in the art can make any modifications and variations in the form and details of the implementation without departing from the spirit and scope of this invention; however, the patent protection scope of this invention shall be determined by the scope defined in the appended claims.

Claims

1. An automatic lifting method for truck-mounted cranes, characterized in that, include: The point cloud of multiple lidars scanning the same object to be lifted is obtained, and the scans of the multiple lidars on the same object to be lifted have a common intersection. The parent lidar and child lidar are determined from the multiple lidars. ICP registration is performed using the point cloud of the parent lidar as the target point cloud and the point cloud of the child lidar as the source point cloud to obtain the transformation matrix. The transformation matrix is ​​transformed into a transformation matrix for each of the child lidars relative to the parent lidar; The transformation matrix is ​​fused with the point cloud acquired by each of the lidar sensors; Construct a point cloud mesh including the coordinates of the front end of the boom, the end of the boom, and the bottom surface coordinates of the object to be lifted by the truck-mounted crane; The point cloud mesh is cut, with the first cutting surface being the intersection of the work station and the horizontal plane of the ground, and the second cutting surface being the horizontal plane where the bottom surface of the object to be lifted is located; The projection coordinates of the bottom center point of the workstation onto the first cutting surface are used as the termination point, and the bottom center coordinates of the object to be lifted are used as the starting point. The horizontal movement path of the object to be lifted is obtained through the ant colony algorithm. The height difference between the bottom of the workstation and the horizontal plane of the ground surface, the height of the parent lidar from the horizontal plane of the ground surface, the height of the end of the boom from the horizontal plane of the ground surface, and the horizontal coordinate difference between the end of the boom and the parent lidar are obtained. In the step of obtaining the transformation matrix by performing ICP registration with the point cloud of the parent lidar as the target point cloud and the point cloud of the child lidar as the source point cloud, the ICP registration obtains the transformation matrix of the child lidar relative to the parent lidar.

2. The automatic lifting method for truck-mounted cranes according to claim 1, characterized in that, The horizontal movement path also includes: The maximum travel speed, acceleration, and steering angle of the truck-mounted crane are dynamically controlled using a PID control algorithm.

3. An automatic lifting system for truck-mounted cranes, characterized in that, The automatic lifting method for truck-mounted cranes according to any one of claims 1-2 includes: Multiple lidar sensors surround the workstation where the object to be lifted is located; The data acquisition module acquires point clouds of scans of the same object to be lifted by multiple lidars, and the scans of the same object by the multiple lidars have a common intersection; The data processing module determines the parent lidar and child lidar from the plurality of lidars; ICP registration is performed using the point cloud of the parent lidar as the target point cloud and the point cloud of the child lidar as the source point cloud to obtain the transformation matrix. The transformation matrix is ​​transformed into a transformation matrix for each of the child lidars relative to the parent lidar; The transformation matrix is ​​fused with the point cloud acquired by each of the lidar sensors; The point cloud mesh construction module constructs a point cloud mesh including the coordinates of the front end of the boom, the coordinates of the end of the boom, and the coordinates of the bottom surface of the object to be lifted by the truck-mounted crane. The data processing module further includes: cutting the point cloud mesh, wherein the first cutting surface is the intersection of the work station and the horizontal surface of the ground, and the second cutting surface is the horizontal surface where the bottom surface of the object to be lifted is located; The projection coordinates of the bottom center point of the workstation onto the first cutting surface are used as the termination point, and the bottom center coordinates of the object to be lifted are used as the starting point. The horizontal movement path of the object to be lifted is obtained through the ant colony algorithm.

4. The automatic lifting system for truck-mounted cranes according to claim 3, characterized in that, The horizontal movement path also includes: The maximum travel speed, acceleration, and steering angle of the truck-mounted crane are dynamically controlled using a PID control algorithm.

5. The automatic lifting system for truck-mounted cranes according to claim 3, characterized in that, The data acquisition module further includes: acquiring the height difference between the bottom of the workstation and the horizontal surface of the ground, the height of the parent lidar from the horizontal surface of the ground, the height of the end of the boom from the horizontal surface of the ground, and the horizontal coordinate difference between the end of the boom and the parent lidar.

6. The automatic lifting system for truck-mounted cranes according to claim 3, characterized in that, In the step of obtaining the transformation matrix by performing ICP registration with the point cloud of the parent lidar as the target point cloud and the point cloud of the child lidar as the source point cloud, the ICP registration obtains the transformation matrix of the child lidar relative to the parent lidar.

7. An electronic device, characterized in that, include: processor; as well as A memory configured to store computer-executable instructions, which, when executed, cause the processor to perform the steps of the automatic lifting method for a truck-mounted crane according to any one of claims 1-2.

8. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores one or more programs that, when executed by an electronic device including multiple applications, cause the electronic device to perform the steps of the automatic lifting method for truck-mounted cranes according to any one of claims 1-2.

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