Path planning method and system of tower crane and storage medium

Abstract

The invention discloses a path planning method and system of a tower crane and a storage medium, and belongs to the technical field of building construction.The method includes the steps that a modeling device is arranged on a luffing mechanism of the tower crane and used for collecting image data at a plurality of rotating positions and moving positions; according to the method, the camera internal parameters and the camera external parameters of the modeling device can be simply and efficiently determined, so that extraction matching, point cloud fusion and three-dimensional surface model conversion can be efficiently carried out on site features. The site features are identified, so that the construction path can be optimized, and the construction efficiency and the resource utilization efficiency are improved.

Description

Technical Field

[0001] The present invention belongs to the technical field of building construction, and in particular relates to a path planning method, system and storage medium for a tower crane. Background Art

[0002] In the field of tower crane path planning, currently the path planning is mainly based on experience: operators plan the movement path of tower cranes based on experience and intuition. Based on their familiarity with the construction site and their understanding of the task, they manually control the slewing, luffing and other mechanisms of the tower crane to complete the material handling task. For example, after determining the starting and end points of the handling task, the operator will observe the surrounding environment and choose a path that looks more reasonable for the operation.

[0003] However, the experience-based path planning method relies heavily on the personal ability and experience of the operator. The planning results of different operators may vary greatly, lacking unified standards and accuracy. It also cannot give full play to the efficiency of tower cranes, and cannot achieve efficient execution of tasks and optimal allocation of resources. Finding a method for refined management and planning of tower crane movements in different areas has become an urgent problem to be solved. Summary of the invention

[0004] In order to solve the technical problems that the current pole locking and unlocking mechanisms and control methods lack effective mechanisms and control means and have a low level of automation, the present invention provides a technical solution for a pole locking and unlocking mechanism, a control method, a device and a storage medium.

[0005] First aspect

[0006] The present invention provides a path planning method for a tower crane, which specifically includes: the tower crane includes a slewing mechanism, a boom, a luffing mechanism and a modeling device, the slewing mechanism is used to drive the tower crane to rotate between different rotation positions, the luffing mechanism at least includes a hook, and the luffing mechanism can move between multiple active positions along the boom.

[0007] S1: Collecting environmental data, the modeling device is arranged on the luffing mechanism, and is used to collect image data at multiple rotation positions and active positions, the image data including tower crane position information, the rotation position information and the active position information, and the focal length of the camera corresponding to the image shooting;

[0008] The modeling device includes multiple ones, at least two of which are arranged on different tower cranes, the working ranges of the different tower cranes have an intersection area, and the image data at least includes the intersection area. By extracting feature points from the intersection area, the intersection area can correspond to image data from different modeling devices, so that multiple sets of image data can be cross-verified with each other, thereby achieving the establishment and matching of feature points. Based on the coordinates of the world coordinate system, the rotation angle of the tower crane and the coverage area of ​​the luffing mechanism are superimposed to obtain the intersection area within the working range of different tower cranes.

[0009] S2: site modeling, marking the image data into an image sequence, the image sequence having different viewing angles, modeling the site based on the image sequence to obtain a three-dimensional model of the site, the modeling including site feature extraction and matching, point cloud fusion and three-dimensional surface model conversion, wherein the site features at least include construction site features and loading and unloading site features;

[0010] The tower crane position information includes the world coordinate system coordinates of the tower crane, and the camera intrinsic parameters and camera extrinsic parameters are determined according to the world coordinate system coordinates of the tower crane, the rotation position information and the activity position information.

[0011] The camera internal parameters include focal length f, principal point coordinates (u 0 ,v 0 ), etc., can usually be obtained through camera calibration. The principal point coordinates of the camera are determined based on the world coordinate system coordinates of the tower crane, the rotation position information and the activity position information, and the focal length f is obtained through camera calibration.

[0012] The camera external parameters include a rotation matrix R and a translation vector t, and the rotation matrix R and the translation matrix t of the camera are determined based on the world coordinate system coordinates of the tower crane, the rotation position information and the activity position information.

[0013] According to the intrinsic parameters of the camera and the matched feature points, a basic matrix is ​​calculated, and the basic matrix describes the symmetrical geometric relationship between the two image data.

[0014] Furthermore, the world coordinate system coordinates of the tower crane are obtained. The position of the tower crane in the world coordinate system can be determined by installing a positioning device, such as a global positioning system (GPS) or an inertial navigation system (INS), on the tower crane. The rotation position information and activity position information of the tower crane are obtained. The rotation angle of the tower crane and the displacement of the luffing mechanism can be monitored in real time by installing angle sensors, displacement sensors and other equipment. In addition, the rotation angle of the tower crane and the displacement of the luffing mechanism can also be calculated by recording the rotation angle of the driving mechanism of the tower crane. Based on the world coordinate system coordinates, the rotation angle of the tower crane and the displacement of the luffing mechanism are superimposed, and the position and posture of the camera in the world coordinate system are determined by geometric calculation. Thereafter, the position and posture of the camera in the world coordinate system determined by calculation can be used as the principal point coordinates of the camera.

[0015] Furthermore, the tower crane path planning method further includes extracting feature points from the intersection area and matching feature points between image data from different modeling devices.

[0016] Furthermore, the camera projection matrix is ​​calculated using the camera intrinsic parameters and the camera extrinsic parameters, and the coordinates of the feature points in the world coordinate system are calculated using the triangulation principle, specifically including:

[0017] The camera projection matrix P i =K i [R i |t i ], where K i is the intrinsic parameter matrix of the i-th camera, R i and t i are the rotation matrix and translation vector of the i-th camera respectively;

[0018] Assume that the pixel coordinates of the feature points in the two image data are (u 1 ,v 1 ) and (u 2 ,v 2 ), the corresponding projection matrices are P 1 and P 2 , then the three-dimensional coordinates of the feature point X = [x, y, z, 1] T The following equations are satisfied:

[0019]

[0020] The system of equations is solved by the linear least squares method to obtain the three-dimensional coordinates of the feature points, that is, the coordinates of the feature points in the world coordinate system.

[0021] The point clouds are fused based on the coordinates of the feature points in the world coordinate system, and the surface reconstruction algorithm is used to convert the point clouds into a continuous three-dimensional surface model.

[0022] S3: Area division, dividing the three-dimensional model of the site into a construction area, a loading and unloading area, and an environment area, wherein the construction area has a height change as the construction progresses, and the loading and unloading area is used for loading and unloading and storage of construction materials;

[0023] Furthermore, site feature extraction and matching include identifying key elements such as buildings, structures, and construction equipment in the construction site. Image recognition algorithms, such as convolutional neural networks (CNNs), can be used to classify and identify objects in images. Among them, the construction site features are identified by manual demarcation or by the change in the height of objects in the image over a period of time, and the corresponding areas are marked as construction areas. Key elements such as material stacking areas, transportation equipment, and loading and unloading equipment are identified, and the sites corresponding to these elements are marked as loading and unloading sites.

[0024] S4: Construction path optimization, limiting the movement type of the luffing mechanism according to the area where the hook is located, wherein when the hook is in the loading and unloading area and when the slewing mechanism moves, the horizontal movement and vertical movement of the luffing mechanism are locked.

[0025] By superimposing the rotation angle of the tower crane and the displacement of the luffing mechanism based on the coordinates of the world coordinate system, the position and posture of the luffing mechanism in the world coordinate system are determined through geometric calculation. When the luffing mechanism and the hook are in the loading and unloading area, the horizontal and vertical movements of the luffing mechanism are immediately locked.

[0026] By optimizing the construction path of the luffing mechanism in the loading and unloading area, the safety of construction can be improved, and accidents caused by unnecessary movement of the luffing mechanism when the hook is in the loading and unloading area can be avoided. The operation of the tower crane can also be made more standardized and efficient, and unnecessary movements and time waste can be reduced. In addition, the stability of the tower crane system can be enhanced, and the shaking and instability factors that may be caused by complex movement combinations can be reduced.

[0027] In addition, the path planning method of the tower crane also includes establishing a transport task, wherein the transport task includes a starting point, an end point and a transport task priority level, and the tower crane plans the transport task according to the task priority level.

[0028] For tasks of the same priority level, the task starting point closest to the current position of the hook in the remaining handling tasks of the same priority level is queried, and the handling task corresponding to the starting point is used as the subsequent handling task.

[0029] Specifically, the starting point or end point of the handling task is generally located at the loading and unloading site or construction area. When the tower crane is idle, it automatically obtains the highest priority task from the task management system and plans the handling route. If there are multiple tasks in the same area, you can consider executing them in sequence according to the priority of the tasks to reduce unnecessary movement.

[0030] When encountering a task of the same priority level, the system automatically queries the task starting point closest to the current position of the hook among the remaining tasks of the same priority level. By establishing a scientific and reasonable tower crane handling task management mechanism, it is ensured that the tower crane can perform handling tasks efficiently and orderly, thereby improving construction efficiency and resource utilization efficiency.

[0031] The starting point or the end point in the intersection area is identified, and the handling tasks corresponding to the starting point or the end point are evenly distributed to the tower cranes in the intersection area.

[0032] By efficiently and accurately identifying the starting or ending points of handling tasks in the intersection area, and evenly distributing these tasks to the tower cranes in the intersection area, construction efficiency can be improved, resource allocation can be optimized, and timely completion of tasks can be ensured.

[0033] Second aspect

[0034] The present invention provides a path planning system for a tower crane, wherein the tower crane comprises a slewing mechanism, a boom, a luffing mechanism and a modeling device, wherein the slewing mechanism is used to drive the tower crane to rotate between different rotation positions, the luffing mechanism comprises at least a hook, and the luffing mechanism can move between a plurality of active positions along the boom;

[0035] A collection module, used for collecting image data, wherein the modeling device is arranged on the luffing mechanism, and is used for collecting image data at a plurality of rotation positions and active positions, wherein the image data includes the position information of the tower crane, the rotation position information and the active position information, and the focal length of the camera corresponding to the image shooting;

[0036] A modeling module, used for marking the image data into an image sequence, wherein the image sequence has different viewing angles, and modeling the site based on the image sequence to obtain a three-dimensional model of the site, wherein the modeling includes site feature extraction and matching, point cloud fusion and three-dimensional surface model conversion, wherein the site features at least include construction site features and loading and unloading site features;

[0037] A division module, used to divide the three-dimensional model of the site into a construction area, a loading and unloading area and an environment area, wherein the construction area has a height change as the construction progresses, and the loading and unloading area is used for loading and unloading and storing construction materials;

[0038] The optimization module is used to limit the movement type of the luffing mechanism according to the area where the hook is located, wherein when the hook is in the loading and unloading area and when the slewing mechanism moves, the horizontal movement and vertical movement of the luffing mechanism are locked.

[0039] The third aspect

[0040] The present invention provides a computer-readable storage medium having a computer program stored thereon, characterized in that when the program is executed by a microprocessor, the path planning method for a tower crane as described in the first aspect is implemented.

[0041] Compared with the prior art, the present invention has at least the following beneficial technical effects:

[0042] In the present invention, by arranging a modeling device on the luffing mechanism of the tower crane to collect image data at multiple rotation positions and active positions, not only can the camera intrinsic parameters and camera extrinsic parameters of the modeling device be determined simply and efficiently, but also the site features can be efficiently extracted and matched, point cloud fused and converted into a three-dimensional surface model. By identifying the site features, the construction path can be optimized, thereby improving the construction efficiency and resource utilization efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] The preferred implementation modes will be described below in a clear and understandable manner with reference to the accompanying drawings to further illustrate the above-mentioned characteristics, technical features, advantages and implementation methods of the present invention.

[0044] Figure 1 It is a schematic diagram of the main structures of the tower crane provided by the present invention.

[0045] Figure 2 It is a flow chart of the path planning method for a tower crane provided by the present invention.

[0046] Figure 3 It is a flow chart of another path planning method for a tower crane provided by the present invention.

[0047] Figure 4 It is a schematic diagram of the path planning system of the tower crane provided by the present invention. DETAILED DESCRIPTION

[0048] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the specific implementation methods of the present invention will be described below with reference to the accompanying drawings. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings and other implementation methods can be obtained based on these drawings without creative work.

[0049] In order to simplify the drawings, only the parts related to the invention are schematically shown in each figure, and they do not represent the actual structure of the product. In addition, in order to simplify the drawings and facilitate understanding, in some figures, only one of the parts with the same structure or function is schematically drawn or marked. In this article, "one" not only means "only one", but also means "more than one".

[0050] It should be further understood that the term “and / or” used in the present specification and the appended claims refers to any combination and all possible combinations of one or more of the associated listed items, and includes these combinations.

[0051] In this document, it should be noted that, unless otherwise clearly specified and limited, the terms "installed", "connected" and "connected" should be understood in a broad sense. For example, it can be a fixed connection, a detachable connection, or an integral connection. It can be a mechanical connection or an electrical connection. It can be directly connected or indirectly connected through an intermediate medium, or it can be the internal communication of two components. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0052] In addition, in the description of the present invention, the terms “first”, “second”, etc. are only used to distinguish the descriptions and cannot be understood as indicating or implying relative importance.

[0053] Example 1

[0054] In one embodiment, the reference specification Figure 1 , showing a schematic diagram of the path planning method for a tower crane provided by the present invention.

[0055] The present invention provides a path planning method for a tower crane, which specifically includes: the tower crane includes a slewing mechanism 3, a boom, a luffing mechanism 1 and a modeling device 4, the slewing mechanism 3 is used to drive the tower crane to rotate between different rotation positions, the luffing mechanism 1 includes at least a hook, and the luffing mechanism 1 can move between multiple active positions along the boom.

[0056] Specifically, the tower body 2 is the main supporting structure of the tower crane, which is connected by multiple standard sections and is generally a square lattice structure, bearing the weight of the upper structure of the tower crane and various loads. The boom is the main working part of the tower crane for lifting heavy objects. It is usually set horizontally or tilted. Its length and form depend on the model and working requirements of the tower crane. It can be a fixed length, or a telescopic or foldable boom to adapt to different working radius and lifting height requirements. The slewing mechanism 3 is used to drive the boom and balance arm of the tower crane to rotate around the tower body 2, and is composed of a motor and gear bearings. The motor drives the gear transmission device to rotate the slewing bearing, thereby realizing the overall rotation of the part above the tower body 2, expanding the working range of the tower crane and improving the flexibility and efficiency of the construction operation. The variable amplitude mechanism 1 can adjust the position of the hook in the horizontal direction according to the location requirements of cargo loading and unloading, thereby expanding the operating range of the tower crane. Common luffing mechanisms 1 include a trolley luffing mechanism 1, which is composed of a winch, a guide pulley, and a luffing trolley. The winch pulls the luffing trolley to move on the boom to achieve a change in the horizontal position of the hook.

[0057] S1: Collecting environmental data, the modeling device 4 is arranged on the luffing mechanism 1, and is used to collect image data at multiple rotation positions and active positions, the image data including tower crane position information, the rotation position information and the active position information, and the camera focal length corresponding to the image shooting;

[0058] The modeling device 4 includes multiple ones, wherein at least two modeling devices 4 are arranged on different tower cranes, and the working ranges of the different tower cranes have an intersection area, and the image data at least includes the intersection area. By extracting feature points from the intersection area, the intersection area can correspond to image data from different modeling devices 4, so that multiple groups of image data can be cross-verified with each other, thereby achieving the establishment and matching of feature points. Based on the coordinates of the world coordinate system, the rotation angle of the tower crane and the coverage area of ​​the variable-length mechanism 1 are superimposed to obtain the intersection area within the working range of different tower cranes.

[0059] S2: site modeling, marking the image data into an image sequence, the image sequence having different viewing angles, modeling the site based on the image sequence to obtain a three-dimensional model of the site, the modeling including site feature extraction and matching, point cloud fusion and three-dimensional surface model conversion, wherein the site features at least include construction site features and loading and unloading site features;

[0060] Specifically, marking the image data as an image sequence includes marking the acquired image data and organizing it into an image sequence according to factors such as shooting time, location, and viewing angle. Ensure that the image sequence covers all angles and key areas of the site, including the construction site and the loading and unloading site. By adopting a multi-angle and multi-height shooting method, more comprehensive site information can be obtained. Record the parameters of image acquisition, such as camera model, focal length, exposure time, etc., for subsequent processing and analysis.

[0061] The tower crane position information includes the world coordinate system coordinates of the tower crane, and the camera intrinsic parameters and camera extrinsic parameters are determined according to the world coordinate system coordinates of the tower crane, the rotation position information and the activity position information.

[0062] The camera internal parameters include focal length f, principal point coordinates (u 0 ,v 0 ), etc., can usually be obtained through camera calibration. The principal point coordinates of the camera are determined based on the world coordinate system coordinates of the tower crane, the rotation position information and the activity position information, and the focal length f is obtained through camera calibration.

[0063] The camera external parameters include a rotation matrix R and a translation vector t, and the rotation matrix R and the translation matrix t of the camera are determined based on the world coordinate system coordinates of the tower crane, the rotation position information and the activity position information.

[0064] According to the intrinsic parameters of the camera and the matched feature points, a basic matrix is ​​calculated, and the basic matrix describes the symmetrical geometric relationship between the two image data.

[0065] Furthermore, the world coordinate system coordinates of the tower crane are obtained. The position of the tower crane in the world coordinate system can be determined by installing a positioning device on the tower crane, such as a global positioning system (GPS) or an inertial navigation system (I NS). The rotation position information and activity position information of the tower crane are obtained. The rotation angle of the tower crane and the displacement of the luffing mechanism 1 can be monitored in real time by installing angle sensors, displacement sensors and other equipment. In addition, the rotation angle of the tower crane and the displacement of the luffing mechanism 1 can also be calculated by recording the rotation angle of the driving mechanism of the tower crane. Based on the world coordinate system coordinates, the rotation angle of the tower crane and the displacement of the luffing mechanism 1 are superimposed, and the position and posture of the camera in the world coordinate system are determined by geometric calculation. Thereafter, the position and posture of the camera in the world coordinate system determined by calculation can be used as the principal point coordinates of the camera.

[0066] Furthermore, the tower crane path planning method further includes extracting feature points from the intersection area and matching feature points between image data from different modeling devices 4 .

[0067] Specifically, by extracting feature points from the intersection area, the intersection area can correspond to image data from different modeling devices 4, so that multiple sets of image data can be cross-validated with each other. Specifically, algorithms such as SIFT (Scale-Invariant Feature Transform) and SURF (Speeded Up Robust Features) can be used to extract image features, thereby extracting feature points with invariance and uniqueness from the image data of the intersection area.

[0068] Furthermore, the matching of feature points includes using feature point descriptors, such as SIFT descriptors, SURF descriptors, etc., to describe the extracted feature points, and then using efficient feature point matching algorithms, such as FLANN (Fast Library for Approximate Nearest Neighbors), etc., to match the feature points in the two images and find corresponding feature point pairs.

[0069] Furthermore, the camera projection matrix is ​​calculated using the camera intrinsic parameters and the camera extrinsic parameters, and the coordinates of the feature points in the world coordinate system are calculated using the triangulation principle, specifically including:

[0070] The camera projection matrix P i =K i [R i |t i ], where K i is the intrinsic parameter matrix of the i-th camera, R i and t i are the rotation matrix and translation vector of the i-th camera respectively;

[0071] Assume that the pixel coordinates of the feature points in the two image data are (u 1 ,v 1 ) and (u 2 ,v 2 ), the corresponding projection matrices are P 1 and P 2 , then the three-dimensional coordinates of the feature point X = [x, y, z, 1] T The following equations are satisfied:

[0072]

[0073] The system of equations is solved by the linear least squares method to obtain the three-dimensional coordinates of the feature points, that is, the coordinates of the feature points in the world coordinate system.

[0074] The point clouds are fused based on the coordinates of the feature points in the world coordinate system, and the surface reconstruction algorithm is used to convert the point clouds into a continuous three-dimensional surface model.

[0075] First, the measured feature point coordinates are preprocessed, including removing outliers, filtering, and performing coordinate system unification and transformation to ensure that all feature points are in the same world coordinate system.

[0076] Since the point cloud data of the construction site is large in scale, a block fusion strategy can be adopted to divide the point cloud into smaller blocks for processing, and then gradually merge the fusion results. By setting reasonable parameters, such as matching threshold, number of iterations, etc., the best fusion effect can be found through experiments and parameter adjustments. In addition, the quality of the fused point cloud can be checked, including checking the data integrity, whether there are holes or overlapping areas, etc.

[0077] S3: Area division, dividing the three-dimensional model of the site into a construction area, a loading and unloading area, and an environment area, wherein the construction area has a height change as the construction progresses, and the loading and unloading area is used for loading and unloading and storage of construction materials;

[0078] Furthermore, site feature extraction and matching include identifying key elements such as buildings, structures, and construction equipment in the construction site. Image recognition algorithms, such as convolutional neural networks (CNNs), can be used to classify and identify objects in images. Among them, the construction site features are identified by manual demarcation or by the change in the height of objects in the image over a period of time, and the corresponding areas are marked as construction areas. Key elements such as material stacking areas, transportation equipment, and loading and unloading equipment are identified, and the sites corresponding to these elements are marked as loading and unloading sites.

[0079] S4: Construction path optimization, limiting the movement type of the luffing mechanism 1 according to the area where the hook is located, wherein when the hook is in the loading and unloading area and when the slewing mechanism 3 moves, the horizontal movement and vertical movement of the luffing mechanism 1 are locked.

[0080] By superimposing the rotation angle of the tower crane and the displacement of the luffing mechanism 1 based on the coordinates of the world coordinate system, the position and posture of the luffing mechanism 1 in the world coordinate system are determined through geometric calculation. When the luffing mechanism 1 and the hook are in the loading and unloading area, the horizontal and vertical movements of the luffing mechanism 1 are immediately locked.

[0081] By optimizing the construction path of the luffing mechanism 1 in the loading and unloading area, the safety of construction can be improved, and accidents caused by unnecessary movement of the luffing mechanism 1 when the hook is in the loading and unloading area can be avoided. The operation of the tower crane can also be made more standardized and efficient, and unnecessary movements and time waste can be reduced. In addition, the stability of the tower crane system can be enhanced, and the shaking and instability factors caused by complex movement combinations can be reduced.

[0082] In addition, the path planning method of the tower crane also includes establishing a transport task, wherein the transport task includes a starting point, an end point and a transport task priority level, and the tower crane plans the transport task according to the task priority level.

[0083] For tasks of the same priority level, the task starting point closest to the current position of the hook in the remaining handling tasks of the same priority level is queried, and the handling task corresponding to the starting point is used as the subsequent handling task.

[0084] Specifically, the starting point or end point of the handling task is generally located at the loading and unloading site or construction area. When the tower crane is idle, it automatically obtains the highest priority task from the task management system and plans the handling route. If there are multiple tasks in the same area, you can consider executing them in sequence according to the priority of the tasks to reduce unnecessary movement.

[0085] When encountering a task with the same priority level, the system automatically queries the task starting point closest to the current position of the hook among the remaining handling tasks with the same priority level. In order to accurately determine the closest task starting point, distance calculation methods such as Euclidean distance and Manhattan distance can be used. At the same time, considering the actual construction environment and obstacles, the distance is appropriately corrected. Once the closest task starting point is determined, the handling task corresponding to the starting point is used as the subsequent handling task. By establishing a scientific and reasonable tower crane handling task management mechanism, it is ensured that the tower crane can perform handling tasks efficiently and orderly, and improve construction efficiency and resource utilization efficiency.

[0086] The starting point or the end point in the intersection area is identified, and the handling tasks corresponding to the starting point or the end point are evenly distributed to the tower cranes in the intersection area.

[0087] Specifically, by superimposing the rotation angle of the tower crane and the coverage area of ​​the luffing mechanism 1 based on the world coordinate system coordinates, the intersection areas within the working ranges of different tower cranes are obtained. When the world coordinate system coordinates of the transport task including the starting point or the end point are in the intersection area, the task allocation mechanism is triggered. Specifically, it includes determining the number and status of the tower cranes in the intersection area, and evenly allocating them according to the number of tower cranes.

[0088] By efficiently and accurately identifying the starting or ending points of handling tasks in the intersection area, and evenly distributing these tasks to the tower cranes in the intersection area, construction efficiency can be improved, resource allocation can be optimized, and timely completion of tasks can be ensured.

[0089] Example 2

[0090] In one embodiment, a locking and unlocking control method of the pole 101 provided by the present invention is shown, comprising:

[0091] As described in the first embodiment, a locking and unlocking mechanism of the upright pole 101 is characterized in that a calculation model of the weight W of the upright pole 101 is established based on the tension P.

[0092] Based on the tension P, a calculation model for the weight W of the pole 101 is established:

[0093]

[0094] Among them, the tension of the pressure sensor is P, the inclination angle of the pole 101 relative to the vertical direction is γ, the Hall sensor can reflect the angle θ between the suspension rope and the pole 101, and the friction coefficient between the pole 101 and the platform is μ, which is between 0.2-1.

[0095] According to the weight W of the pole 101, the measured data can be used to realize automatic control of the winch. For example, according to the change of the pulling force and the angle, the lifting speed and pulling force of the winch can be automatically adjusted to ensure the smooth operation of the system; according to the pulling force and the tilt angle of the pole 101, the torque of the winch can be automatically adjusted to realize the resistance or hovering of the pole 101, so as to reduce the difficulty of manual operation of the pole 101 and improve work efficiency.

[0096] Example 3

[0097] In one embodiment, the reference specification Figure 2 , shows a path planning system for a tower crane provided by the present invention. The tower crane comprises a slewing mechanism 3, a boom, a luffing mechanism 1 and a modeling device 4, the slewing mechanism 3 is used to drive the tower crane to rotate between different rotation positions, the luffing mechanism 1 comprises at least a hook, and the luffing mechanism 1 can move between multiple active positions along the boom;

[0098] An acquisition module, for acquiring image data, wherein the modeling device 4 is arranged on the luffing mechanism 1, for acquiring image data at a plurality of rotation positions and active positions, the image data including tower crane position information, the rotation position information and the active position information, and the focal length of the camera corresponding to the image shooting;

[0099] A modeling module, used for marking the image data into an image sequence, wherein the image sequence has different viewing angles, and modeling the site based on the image sequence to obtain a three-dimensional model of the site, wherein the modeling includes site feature extraction and matching, point cloud fusion and three-dimensional surface model conversion, wherein the site features at least include construction site features and loading and unloading site features;

[0100] A division module, used to divide the three-dimensional model of the site into a construction area, a loading and unloading area and an environment area, wherein the construction area has a height change as the construction progresses, and the loading and unloading area is used for loading and unloading and storing construction materials;

[0101] The optimization module is used to limit the movement type of the luffing mechanism 1 according to the area where the hook is located, wherein when the hook is in the loading and unloading area and when the slewing mechanism 3 moves, the horizontal movement and vertical movement of the luffing mechanism 1 are locked.

[0102] The modeling module specifically includes: marking the image data into an image sequence, including marking the acquired image data, and organizing it into an image sequence according to factors such as shooting time, location, and viewing angle. Ensure that the image sequence covers all angles and key areas of the site, including the construction site and the loading and unloading site. By adopting multi-angle and multi-height shooting methods, more comprehensive site information can be obtained. Record the parameters of image acquisition, such as camera model, focal length, exposure time, etc., for subsequent processing and analysis.

[0103] The tower crane position information includes the world coordinate system coordinates of the tower crane, and the camera intrinsic parameters and camera extrinsic parameters are determined according to the world coordinate system coordinates of the tower crane, the rotation position information and the activity position information.

[0104] The camera internal parameters include focal length f, principal point coordinates (u 0 ,v 0 ), etc., can usually be obtained through camera calibration. The principal point coordinates of the camera are determined based on the world coordinate system coordinates of the tower crane, the rotation position information and the activity position information, and the focal length f is obtained through camera calibration.

[0105] The camera external parameters include a rotation matrix R and a translation vector t, and the rotation matrix R and the translation matrix t of the camera are determined based on the world coordinate system coordinates of the tower crane, the rotation position information and the activity position information.

[0106] According to the intrinsic parameters of the camera and the matched feature points, a basic matrix is ​​calculated, and the basic matrix describes the symmetrical geometric relationship between the two image data.

[0107] Furthermore, the world coordinate system coordinates of the tower crane are obtained. The position of the tower crane in the world coordinate system can be determined by installing a positioning device on the tower crane, such as a global positioning system (GPS) or an inertial navigation system (I NS). The rotation position information and activity position information of the tower crane are obtained. The rotation angle of the tower crane and the displacement of the luffing mechanism 1 can be monitored in real time by installing angle sensors, displacement sensors and other equipment. In addition, the rotation angle of the tower crane and the displacement of the luffing mechanism 1 can also be calculated by recording the rotation angle of the driving mechanism of the tower crane. Based on the world coordinate system coordinates, the rotation angle of the tower crane and the displacement of the luffing mechanism 1 are superimposed, and the position and posture of the camera in the world coordinate system are determined by geometric calculation. Thereafter, the position and posture of the camera in the world coordinate system determined by calculation can be used as the principal point coordinates of the camera.

[0108] Furthermore, the tower crane path planning method further includes extracting feature points from the intersection area and matching feature points between image data from different modeling devices 4 .

[0109] Specifically, by extracting feature points from the intersection area, the intersection area can correspond to image data from different modeling devices 4, so that multiple sets of image data can be cross-validated with each other. Specifically, algorithms such as SI FT (Scale-Invariant Feature Transform) and SURF (Speeded Up Robust Features) can be used to extract image features, thereby extracting feature points with invariance and uniqueness from the image data of the intersection area.

[0110] Furthermore, the matching of feature points includes using feature point descriptors, such as SIFT descriptor, SURF descriptor, etc., to describe the extracted feature points, and then using efficient feature point matching algorithms, such as FLANN (Fast Library for Approximate Nearest Neighbors), etc., to match the feature points in the two images and find corresponding feature point pairs.

[0111] Furthermore, the camera projection matrix is ​​calculated using the camera intrinsic parameters and the camera extrinsic parameters, and the coordinates of the feature points in the world coordinate system are calculated using the triangulation principle, specifically including:

[0112] The camera projection matrix P i =K i [R i |t i ], where K iis the intrinsic parameter matrix of the i-th camera, R i and t i are the rotation matrix and translation vector of the i-th camera respectively;

[0113] Assume that the pixel coordinates of the feature points in the two image data are (u 1 ,v 1 ) and (u 2 ,v 2 ), the corresponding projection matrices are P 1 and P 2 , then the three-dimensional coordinates of the feature point X = [x, y, z, 1] T The following equations are satisfied:

[0114]

[0115] The system of equations is solved by the linear least squares method to obtain the three-dimensional coordinates of the feature points, that is, the coordinates of the feature points in the world coordinate system.

[0116] The point clouds are fused based on the coordinates of the feature points in the world coordinate system, and the surface reconstruction algorithm is used to convert the point clouds into a continuous three-dimensional surface model.

[0117] The optimization module specifically includes: by superimposing the rotation angle of the tower crane and the displacement of the luffing mechanism 1 based on the coordinates of the world coordinate system, the position and posture of the luffing mechanism 1 in the world coordinate system are determined through geometric calculation; when the luffing mechanism 1 and the hook are in the loading and unloading area, the horizontal movement and vertical movement of the luffing mechanism 1 are immediately locked.

[0118] By optimizing the construction path of the luffing mechanism 1 in the loading and unloading area, the safety of construction is improved, and accidents caused by unnecessary movement of the luffing mechanism 1 when the hook is in the loading and unloading area are avoided. The operation of the tower crane can also be made more standardized and efficient, and unnecessary movements and time waste can be reduced. In addition, the stability of the tower crane system can be enhanced, and the shaking and instability factors that may be caused by complex movement combinations can be reduced.

[0119] In addition, the path planning method of the tower crane also includes establishing a transport task, wherein the transport task includes a starting point, an end point and a transport task priority level, and the tower crane plans the transport task according to the task priority level.

[0120] For tasks of the same priority level, the task starting point closest to the current position of the hook in the remaining handling tasks of the same priority level is queried, and the handling task corresponding to the starting point is used as the subsequent handling task.

[0121] Specifically, the starting point or end point of the handling task is generally located at the loading and unloading site or construction area. When the tower crane is idle, it automatically obtains the highest priority task from the task management system and plans the handling route. If there are multiple tasks in the same area, you can consider executing them in sequence according to the priority of the tasks to reduce unnecessary movement.

[0122] When encountering a task with the same priority level, the system automatically queries the task starting point closest to the current position of the hook among the remaining handling tasks with the same priority level. In order to accurately determine the closest task starting point, distance calculation methods such as Euclidean distance and Manhattan distance can be used. At the same time, considering the actual construction environment and obstacles, the distance is appropriately corrected. Once the closest task starting point is determined, the handling task corresponding to the starting point is used as the subsequent handling task. By establishing a scientific and reasonable tower crane handling task management mechanism, it is ensured that the tower crane can perform handling tasks efficiently and orderly, and improve construction efficiency and resource utilization efficiency.

[0123] The starting point or the end point in the intersection area is identified, and the handling tasks corresponding to the starting point or the end point are evenly distributed to the tower cranes in the intersection area.

[0124] Example 3

[0125] The present invention provides a computer-readable storage medium on which a computer program is stored, characterized in that when the program is executed by a microprocessor, the path planning method for a tower crane described in any one of Embodiment 1 is implemented.

[0126] Compared with the prior art, the present invention has at least the following beneficial technical effects: In the present invention, by arranging a modeling device 4 on the luffing mechanism 1 of a tower crane to collect image data at multiple rotation positions and active positions, not only can the camera intrinsic parameters and camera extrinsic parameters of the modeling device 4 be determined simply and efficiently, but also the site features can be efficiently extracted and matched, point cloud fused and converted into a three-dimensional surface model. By identifying the site features, the construction path can be optimized, thereby improving the construction efficiency and resource utilization efficiency.

[0127] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0128] The above embodiments only express several implementation methods of the present invention, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the invention patent. It should be pointed out that, for those of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present invention, and these all belong to the protection scope of the present invention. Therefore, the protection scope of the patent of the present invention shall be subject to the attached claims.

Claims

1. A path planning method for a tower crane, wherein the tower crane comprises a slewing mechanism, a boom, a luffing mechanism and a modeling device, wherein the slewing mechanism is used to drive the tower crane to rotate between different rotation positions, the luffing mechanism comprises at least a hook, and the luffing mechanism can move between multiple active positions along the boom; S1: Collecting environmental data, the modeling device is arranged on the luffing mechanism, and is used to collect image data at multiple rotation positions and active positions, the image data including tower crane position information, the rotation position information and the active position information, and the focal length of the camera corresponding to the image shooting; S2: Site modeling, marking the image data into an image sequence, the image sequence having different viewing angles, modeling the site based on the image sequence to obtain a three-dimensional model of the site, the modeling including site feature extraction and matching, point cloud fusion and three-dimensional surface model conversion, wherein: The site characteristics at least include construction site characteristics and loading and unloading site characteristics; S3: Area division, dividing the three-dimensional model of the site into a construction area, a loading and unloading area, and an environment area, wherein the construction area has a height change as the construction progresses, and the loading and unloading area is used for loading and unloading and storage of construction materials; S4: Construction path optimization, limiting the movement type of the luffing mechanism according to the area where the hook is located, wherein when the hook is in the loading and unloading area and when the slewing mechanism moves, the horizontal movement and vertical movement of the luffing mechanism are locked.

2. A tower crane path planning method according to claim 1, characterized in that: The collected environmental data also includes: The modeling devices include a plurality of modeling devices, at least two of which are arranged on different tower cranes, the working ranges of the different tower cranes have an intersection area, and the image data at least includes the intersection area.

3. A tower crane path planning method according to claim 2, characterized in that: The site modeling also includes: The tower crane position information includes the world coordinate system coordinates of the tower crane, and the camera intrinsic parameters and camera extrinsic parameters are determined according to the world coordinate system coordinates of the tower crane, the rotation position information and the activity position information; Extracting feature points from the intersection area and matching feature points between image data from different modeling devices; Calculate a basic matrix based on the camera's intrinsic parameters and the matched feature points, wherein the basic matrix describes the symmetrical geometric relationship between the two image data; The camera projection matrix is ​​calculated using the camera intrinsic parameters and the camera extrinsic parameters, and the coordinates of the feature points in the world coordinate system are calculated using the triangulation principle; The point clouds are fused based on the coordinates of the feature points in the world coordinate system, and the surface reconstruction algorithm is used to convert the point clouds into a continuous three-dimensional surface model.

4. A tower crane path planning method according to claim 1, characterized in that: It also includes establishing a transport task, wherein the transport task includes a starting point, an end point, and a transport task priority level, and the tower crane plans the transport task according to the task priority level.

5. A tower crane path planning method according to claim 4, characterized in that: For tasks of the same priority level, the task starting point closest to the current position of the hook in the remaining handling tasks of the same priority level is queried, and the handling task corresponding to the starting point is used as the subsequent handling task.

6. A tower crane path planning method according to claim 2, characterized in that: The site modeling further includes: establishing a transport task, the transport task including a starting point, an end point, and a transport task priority level; The starting point or the end point in the intersection area is identified, and the handling tasks corresponding to the starting point or the end point are evenly distributed to the tower cranes in the intersection area.

7. A tower crane path planning method according to claim 2, characterized in that: The camera internal parameters include a focal length f and a principal point coordinate (u0, v0), and the principal point coordinate of the camera is determined based on the world coordinate system coordinates of the tower crane, the rotation position information, and the activity position information, and the focal length f is obtained by camera calibration; The camera external parameters include a rotation matrix R and a translation vector t, and the rotation matrix R and the translation matrix t of the camera are determined based on the world coordinate system coordinates of the tower crane, the rotation position information and the activity position information.

8. A tower crane path planning method according to claim 7, characterized in that: Use the triangulation principle to calculate the coordinates of feature points in the world coordinate system include: Among them, the camera projection matrix P i =K i [R i |t i ], where K i is the intrinsic parameter matrix of the i-th camera, R i and t i are the rotation matrix and translation vector of the i-th camera respectively; Assume that the pixel coordinates of the feature point in the two images are (u1, v1) and (u2, v2), and the corresponding projection matrices are P1 and P2, then the three-dimensional coordinates of the feature point are X = [x, y, z, 1] T The following equations are satisfied: The system of equations is solved by the linear least squares method to obtain the three-dimensional coordinates of the feature points.

9. A path planning system for a tower crane, characterized in that: The tower crane comprises a slewing mechanism, a boom, a luffing mechanism and a modeling device, wherein the slewing mechanism is used to drive the tower crane to rotate between different rotation positions, the luffing mechanism comprises at least a hook, and the luffing mechanism can move between multiple active positions along the boom; A collection module, used for collecting image data, wherein the modeling device is arranged on the luffing mechanism, and is used for collecting image data at a plurality of rotation positions and active positions, wherein the image data includes the position information of the tower crane, the rotation position information and the active position information, and the focal length of the camera corresponding to the image shooting; A modeling module, used for marking the image data into an image sequence, wherein the image sequence has different viewing angles, and modeling the site based on the image sequence to obtain a three-dimensional model of the site, wherein the modeling includes site feature extraction and matching, point cloud fusion and three-dimensional surface model conversion, wherein the site features at least include construction site features and loading and unloading site features; A division module, used to divide the three-dimensional model of the site into a construction area, a loading and unloading area and an environment area, wherein the construction area has a height change as the construction progresses, and the loading and unloading area is used for loading and unloading and storing construction materials; The optimization module is used to limit the movement type of the luffing mechanism according to the area where the hook is located, wherein when the hook is in the loading and unloading area and when the slewing mechanism moves, the horizontal movement and vertical movement of the luffing mechanism are locked.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the path planning method for a tower crane according to any one of claims 1 to 8 is implemented.

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