Disclosure of Invention
In order to solve the technical problems that an effective mechanism and a control means are lacking in the current upright locking and unlocking mechanism and control method and the automation level is low, the invention provides a technical scheme of an upright locking and unlocking mechanism, a control method, a device and a storage medium.
First aspect
The invention provides a path planning method of a tower crane, which specifically comprises a slewing mechanism, a crane boom, an amplitude variation mechanism and a modeling device, wherein the slewing mechanism is used for driving the tower crane to rotate among different rotation positions, the amplitude variation mechanism at least comprises a lifting hook, and the amplitude variation mechanism can move among a plurality of movable positions along the crane boom.
S1, acquiring environment data, wherein the modeling device is arranged on the luffing mechanism and is used for acquiring image data at a plurality of rotating positions and moving positions, and the image data comprises tower crane position information, the rotating position information, the moving position information and camera focal lengths corresponding to the image shooting;
the modeling devices comprise a plurality of modeling devices, wherein at least two modeling devices are arranged on different tower cranes, the working ranges of the different tower cranes are provided with intersection areas, and the image data at least comprise the intersection areas. By extracting feature points from the intersection region, the intersection region can correspond to image data from different modeling apparatuses, so that multiple sets of image data can be mutually cross-validated, thereby realizing establishment and matching of feature points. Based on world coordinate system coordinates, the rotation angle of the tower crane and the coverage area of the luffing mechanism are overlapped to obtain the boundary areas in different working ranges of the tower crane.
S2, site modeling, namely marking the image data into an image sequence, wherein the image sequence has different visual angles, modeling the site based on the image sequence to obtain a site three-dimensional model, wherein the modeling comprises site feature extraction and matching, point cloud fusion and three-dimensional surface model conversion, and the site features at least comprise site feature construction and site feature loading and unloading;
The tower crane position information comprises world coordinate system coordinates of the tower crane, and camera internal parameters and camera external parameters are determined according to the world coordinate system coordinates of the tower crane, the rotation position information and the movable position information.
The camera internal parameters comprise a focal length f, a principal point coordinate (u0,v0) and the like, the focal length f can be usually obtained through camera calibration, and the principal point coordinate of the camera is determined based on the world coordinate system coordinate of the tower crane, the rotation position information and the activity position information.
The camera external parameters comprise 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 world coordinate system coordinates of the tower crane, the rotation position information and the activity position information.
Based on the internal parameters of the camera and the matched feature points, a base matrix is calculated, which describes the symmetrical geometrical relationship between the two pieces of image data.
Further, world coordinate system coordinates of the tower crane are obtained. The location of the tower crane in its world coordinate system may be determined by installing a positioning device, such as a Global Positioning System (GPS) or an Inertial Navigation System (INS), on the tower crane. And acquiring rotation position information and activity position information of the tower crane. The rotation angle of the tower crane and the displacement of the luffing mechanism can be monitored in real time by installing the angle sensor, the displacement sensor and other devices, and in addition, the rotation angle of the driving mechanism of the tower crane and the displacement of the luffing mechanism can 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 superposed, the position and the posture of the camera in the world coordinate system are determined through geometric calculation, and then the position and the posture of the camera in the world coordinate system can be calculated and determined to be used as the main point coordinates of the camera.
Further, the path planning method of the tower crane further comprises the step of extracting characteristic points from the intersection area and matching the characteristic points among image data from different modeling devices.
Further, the camera internal parameter and the camera external parameter are used for calculating a camera projection matrix, and the coordinate of the feature point in a world coordinate system is calculated by using a triangulation principle, and the method specifically comprises the following steps:
The camera projection matrix Pi＝Ki[Ri|ti ], wherein Ki is an i-th camera internal reference matrix, and Ri and ti are rotation matrices and translation vectors of the i-th camera, respectively;
Assuming that the pixel coordinates of the feature points in the two pieces of image data are (u1,v1) and (u2,v2) respectively, and the corresponding projection matrixes are P1 and P2 respectively, the three-dimensional coordinates x= [ X, y, z,1]T of the feature points satisfy the following equation:
And solving the equation set by a linear least square method to obtain the three-dimensional coordinates of the feature points, namely the coordinates of the feature points in a world coordinate system.
And fusing point clouds based on coordinates of the feature points in a world coordinate system, and converting the point clouds into a continuous three-dimensional surface model by using a surface reconstruction algorithm.
S3, dividing the three-dimensional model of the site into a building area, an upper blanking area and an environment area, wherein the building area has a change in the height direction along with the construction progress, and the upper blanking area is used for loading and unloading construction materials and storing the construction materials;
Further, site feature extraction and matching include identifying key elements in the constructed site, such as buildings, structures, construction equipment, and the like. Objects in the image may be classified and identified using an image recognition algorithm, such as Convolutional Neural Network (CNN), or the like. Wherein, the characteristics of the construction site are identified by manual delineation or by the variation of the height of the object in the image over a period of time, and the corresponding area is marked as the construction area. And identifying key elements such as a material stacking area, a conveying device, a loading and unloading device and the like, and marking the places corresponding to the elements as loading and unloading places.
And S4, optimizing a construction path, and limiting the movement type of the luffing mechanism according to the region where the lifting hook is located, wherein when the lifting hook is located in the feeding and discharging region, the horizontal movement and the vertical movement of the luffing mechanism are locked when the slewing mechanism moves.
The method is characterized in that the rotation angle of the tower crane and the displacement of the luffing mechanism are superposed based on the world coordinate system, the position and the posture of the luffing mechanism in the world coordinate system are determined through geometric calculation, and when the luffing mechanism and the lifting hook are positioned in the feeding and discharging areas, the horizontal movement and the vertical movement of the luffing mechanism are immediately locked.
By optimizing the construction path of the luffing mechanism in the loading and unloading area, the construction safety can be improved, accidents caused by unnecessary movement of the luffing mechanism when the lifting hook is positioned in the loading and unloading area are avoided, the operation of the tower crane is more standard and efficient, unnecessary actions and time waste are reduced, the stability of a tower crane system can be enhanced, and shaking and unstable factors possibly caused by complex movement combination are reduced.
In addition, the path planning method of the tower crane further comprises the step of establishing a transport task, wherein the transport task comprises a starting point, a finishing point and a transport task priority level, and the tower crane plans the transport task according to the high and low ordered task priority levels.
And inquiring a task starting point closest to the current position of the lifting hook in the rest of the tasks with the same-level priority, and taking the transport task corresponding to the starting point as a continuous transport task.
Specifically, the starting point or the ending point of the carrying task is generally located in the loading and unloading site or the construction area, when the tower crane is idle, the task with the highest priority is automatically obtained from the task management system, and the carrying path is planned, if a plurality of tasks are located in the same area, the tasks can be considered to be sequentially executed according to the priority of the tasks, so that unnecessary movement is reduced.
When meeting the tasks with the same-level priority, the system automatically inquires the task starting point closest to the current position of the lifting hook in the rest tasks with the same-level priority. By establishing a scientific and reasonable tower crane carrying task management mechanism, the tower crane can be ensured to efficiently and orderly execute carrying tasks, and the construction efficiency and the resource utilization efficiency are improved.
And identifying the starting point or the ending point in the intersection area, and evenly distributing the conveying task corresponding to the starting point or the ending point to the tower crane in the intersection area.
The starting point or the finishing point of the transport task in the intersection area is identified efficiently and accurately, and the tasks are distributed to the tower cranes in the intersection area evenly, so that the construction efficiency is improved, the resource allocation is optimized, and the timely completion of the tasks is ensured.
Second aspect
The invention provides a path planning system of a tower crane, which comprises a slewing mechanism, a crane boom, an amplitude variation mechanism and a modeling device, wherein the slewing mechanism is used for driving the tower crane to rotate among different rotation positions, the amplitude variation mechanism at least comprises a lifting hook, and the amplitude variation mechanism can move among a plurality of movable positions along the crane boom;
the modeling device is arranged on the amplitude variation mechanism and used for acquiring image data at a plurality of rotating positions and moving positions, and the image data comprises tower crane position information, the rotating position information, the moving position information and camera focal lengths corresponding to image shooting;
the modeling module is used for marking the image data into an image sequence, the image sequence has different visual angles, the field is modeled based on the image sequence to obtain a field three-dimensional model, the modeling comprises field feature extraction and matching, point cloud fusion and three-dimensional surface model conversion, and the field features at least comprise building field features and loading and unloading field features;
The division module is used for dividing the site three-dimensional model into a building area, an upper blanking area and a lower blanking area and an environment area, wherein the building area has the change of the height direction along with the construction progress, and the upper blanking area is used for loading and unloading construction materials and storing construction materials;
And the optimizing module is used for limiting the movement type of the amplitude changing mechanism according to the area where the lifting hook is positioned, wherein when the lifting hook is positioned in the feeding and discharging area, the horizontal movement and the vertical movement of the amplitude changing mechanism are locked when the slewing mechanism moves.
Third aspect of the invention
The invention provides a computer readable storage medium on which a computer program is stored, characterized in that the program microprocessor, when executed, implements a path planning method for a tower crane according to the first aspect.
Compared with the prior art, the invention has at least the following beneficial technical effects:
According to the invention, the modeling device is arranged on the luffing mechanism of the tower crane and used for collecting image data at a plurality of rotation positions and activity positions, so that the camera internal parameters and the camera external parameters of the modeling device can be simply and efficiently determined, and the site characteristics can be efficiently extracted and matched, and the point cloud fusion and the three-dimensional surface model conversion can be realized. By identifying the site characteristics, the construction path can be optimized, and the construction efficiency and the resource utilization efficiency are improved.
Detailed Description
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following description will explain the specific embodiments of the present invention with reference to the accompanying drawings. It is evident that the drawings in the following description are only examples of the invention, from which other drawings and other embodiments can be obtained by a person skilled in the art without inventive effort.
For simplicity of the drawing, only the parts relevant to the invention are schematically shown in each drawing, and they do not represent the actual structure thereof as a product. Additionally, in order to simplify the drawing for ease of understanding, components having the same structure or function in some of the drawings are shown schematically with only one of them, or only one of them is labeled. Herein, "a" means not only "only this one" but also "more than one" case.
It should also be understood that the term "and/or" as used in the present specification and the appended claims refers to any and all possible combinations of one or more of the associated listed items, and includes such combinations.
In this context, it should be noted that the terms "mounted," "connected," and "connected" are to be construed broadly, and may be, for example, fixedly connected, detachably connected, or integrally connected, unless otherwise specifically defined and limited. It may be a mechanical connection that is made, or may be an electrical connection. Can be directly connected or indirectly connected through an intermediate medium, and can be communication between two elements. The specific meaning of the above terms in the present invention will be understood in specific cases by those of ordinary skill in the art.
In addition, in the description of the present invention, the terms "first," "second," and the like are used merely to distinguish between descriptions and are not to be construed as indicating or implying relative importance.
Example 1
In one embodiment, referring to fig. 1 of the specification, a schematic diagram of a path planning method of a tower crane provided by the invention is shown.
The invention provides a path planning method of a tower crane, which specifically comprises a slewing mechanism 3, a crane boom, an amplitude variation mechanism 1 and a modeling device 4, wherein the slewing mechanism 3 is used for driving the tower crane to rotate between different rotation positions, the amplitude variation mechanism 1 at least comprises a lifting hook, and the amplitude variation mechanism 1 can move among a plurality of movable positions along the crane boom.
Specifically, the tower body 2 is a main body supporting structure of the tower crane, and is formed by connecting a plurality of standard joints, and is generally of a square lattice type structure, so that the weight and various loads of an upper structure of the tower crane are borne. The crane arm is a main working part of the tower crane for hoisting heavy objects, is usually arranged horizontally or obliquely, and can be fixed in length or telescopic or foldable according to the model and working requirements of the tower crane so as to adapt to different working radius and hoisting height requirements. The slewing mechanism 3 is used for driving a crane arm and a balance arm of the tower crane to perform slewing motion around the tower body 2, and consists of a motor, a gear bearing and the like. The motor drives the gear transmission device to enable the slewing bearing to rotate, so that the whole slewing of the part above the tower body 2 is realized, the working range of the tower crane is enlarged, and the flexibility and the efficiency of construction operation are improved. The luffing mechanism 1 can adjust the position of the lifting hook in the horizontal direction according to the position requirement of cargo loading and unloading, thereby expanding the operation range of the tower crane. The common luffing mechanism 1 is provided with a trolley luffing mechanism 1, the trolley luffing mechanism 1 consists of a winch, a guide pulley, a luffing trolley and the like, and the luffing trolley is pulled to move on a crane boom through the winch, so that the horizontal position change of a lifting hook is realized.
S1, acquiring environmental data, wherein the modeling device 4 is arranged on the luffing mechanism 1 and is used for acquiring image data at a plurality of rotation positions and moving positions, and the image data comprises tower crane position information, rotation position information, moving position information and camera focal lengths corresponding to image shooting;
The modeling means 4 comprise a plurality of modeling means 4, wherein at least two modeling means 4 are arranged on different tower cranes, the operating ranges of which have intersection areas, and the image data comprise at least the intersection areas. By extracting feature points from the intersection region, the intersection region can correspond to image data from different modeling apparatuses 4, so that there are plural sets of image data that can be mutually cross-validated, thereby achieving establishment and matching of feature points. Based on world coordinate system coordinates, the rotation angle of the tower crane and the coverage area of the luffing mechanism 1 are overlapped to obtain the boundary areas in different working ranges of the tower crane.
S2, site modeling, namely marking the image data into an image sequence, wherein the image sequence has different visual angles, modeling the site based on the image sequence to obtain a site three-dimensional model, wherein the modeling comprises site feature extraction and matching, point cloud fusion and three-dimensional surface model conversion, and the site features at least comprise site feature construction and site feature loading and unloading;
Specifically, marking the image data as an image sequence includes marking the acquired image data, and organizing the acquired image data into the image sequence according to factors such as shooting time, position, visual angle and the like. Ensuring that the image sequence encompasses various angles and critical areas of the site, including the build site and the loading and unloading site. By adopting a shooting mode with multiple angles and multiple heights, more comprehensive site information can be obtained. Parameters of image acquisition, such as camera model, focal length, exposure time, etc., are recorded for subsequent processing and analysis.
The tower crane position information comprises world coordinate system coordinates of the tower crane, and camera internal parameters and camera external parameters are determined according to the world coordinate system coordinates of the tower crane, the rotation position information and the movable position information.
The camera internal parameters comprise a focal length f, a principal point coordinate (u0,v0) and the like, the focal length f can be usually obtained through camera calibration, and the principal point coordinate of the camera is determined based on the world coordinate system coordinate of the tower crane, the rotation position information and the activity position information.
The camera external parameters comprise 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 world coordinate system coordinates of the tower crane, the rotation position information and the activity position information.
Based on the internal parameters of the camera and the matched feature points, a base matrix is calculated, which describes the symmetrical geometrical relationship between the two pieces of image data.
Further, world coordinate system coordinates of the tower crane are obtained. The location of the tower crane in its world coordinate system may be determined by mounting a positioning device, such as a Global Positioning System (GPS) or an inertial navigation system (ins), on the tower crane. And acquiring rotation position information and activity position information of the tower crane. The rotation angle of the tower crane and the displacement of the luffing mechanism 1 can be monitored in real time by installing the angle sensor, the displacement sensor and other devices, and in addition, the rotation angle of the tower crane and the displacement of the luffing mechanism 1 can 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 superposed, the position and the posture of the camera in the world coordinate system are determined through geometric calculation, and then the position and the posture of the camera in the world coordinate system can be calculated and determined as the main point coordinates of the camera.
Further, the path planning method of the tower crane further comprises feature point extraction from the intersection region, and feature point matching is performed between image data from different modeling devices 4.
Specifically, by extracting feature points from the intersection region, the intersection region can correspond to image data from different modeling apparatuses 4, so that there are plural sets of image data that can be mutually cross-validated. Specifically, extraction of image features may be achieved using SIFT (scale-INVAR IANT Feature Transform, scale invariant feature transform), SURF (Speeded Up Robust Features, accelerated robust features), or the like, to extract feature points with invariance and uniqueness from image data of intersection regions.
Further, the matching of the feature points includes describing the extracted feature points by using feature point descriptors, such as SIFT descriptors, SURF descriptors, etc., and then matching the feature points in the two images by using an efficient feature point matching algorithm, such as FLANN (Fast Library for Approximate Nearest Neighbors, fast approximate nearest neighbor search library), etc., to find corresponding feature point pairs.
Further, the camera internal parameter and the camera external parameter are used for calculating a camera projection matrix, and the coordinate of the feature point in a world coordinate system is calculated by using a triangulation principle, and the method specifically comprises the following steps:
The camera projection matrix Pi＝Ki[Ri|ti ], wherein Ki is an i-th camera internal reference matrix, and Ri and ti are rotation matrices and translation vectors of the i-th camera, respectively;
Assuming that the pixel coordinates of the feature points in the two pieces of image data are (u1,v1) and (u2,v2) respectively, and the corresponding projection matrixes are P1 and P2 respectively, the three-dimensional coordinates x= [ X, y, z,1]T of the feature points satisfy the following equation:
And solving the equation set by a linear least square method to obtain the three-dimensional coordinates of the feature points, namely the coordinates of the feature points in a world coordinate system.
And fusing point clouds based on coordinates of the feature points in a world coordinate system, and converting the point clouds into a continuous three-dimensional surface model by using a surface reconstruction algorithm.
Firstly, preprocessing the measured characteristic point coordinates, including outlier removal, filtering and coordinate system unification and conversion, so as to ensure that all the characteristic points are in the same world coordinate system.
Because the point cloud data of the construction site has a large scale, a block fusion strategy can be adopted to divide the point cloud into smaller blocks for processing, and then the fusion results are gradually combined. By setting reasonable parameters such as matching threshold values, iteration times and the like. And finding out the optimal fusion effect through experiments and adjustment parameters. In addition, quality inspection can be performed on the fused point cloud, including checking data integrity, whether a cavity or an overlapping area exists, and the like.
S3, dividing the three-dimensional model of the site into a building area, an upper blanking area and an environment area, wherein the building area has a change in the height direction along with the construction progress, and the upper blanking area is used for loading and unloading construction materials and storing the construction materials;
Further, site feature extraction and matching include identifying key elements in the constructed site, such as buildings, structures, construction equipment, and the like. Objects in the image may be classified and identified using an image recognition algorithm, such as Convolutional Neural Network (CNN), or the like. Wherein, the characteristics of the construction site are identified by manual delineation or by the variation of the height of the object in the image over a period of time, and the corresponding area is marked as the construction area. And identifying key elements such as a material stacking area, a conveying device, a loading and unloading device and the like, and marking the places corresponding to the elements as loading and unloading places.
And S4, optimizing a construction path, and limiting the movement type of the luffing mechanism 1 according to the region where the lifting hook is positioned, wherein when the lifting hook is positioned in the feeding and discharging region, the horizontal movement and the vertical movement of the luffing mechanism 1 are locked when the slewing mechanism 3 moves.
The method is characterized in that the rotation angle of the tower crane and the displacement of the luffing mechanism 1 are superposed based on world coordinate system coordinates, the position and the gesture of the luffing mechanism 1 in the world coordinate system are determined through geometric calculation, and when the luffing mechanism 1 and the lifting hook are positioned in an upper and lower material area, the horizontal movement and the vertical movement of the luffing mechanism 1 are immediately locked.
By optimizing the construction path of the luffing mechanism 1 in the loading and unloading area, the construction safety can be improved, accidents caused by unnecessary movement of the luffing mechanism 1 when the lifting hook is positioned in the loading and unloading area are avoided, the operation of the tower crane is more standard and efficient, unnecessary actions and time waste are reduced, the stability of a tower crane system can be enhanced, and shaking and unstable factors caused by complex movement combination are reduced.
In addition, the path planning method of the tower crane further comprises the step of establishing a transport task, wherein the transport task comprises a starting point, a finishing point and a transport task priority level, and the tower crane plans the transport task according to the high and low ordered task priority levels.
And inquiring a task starting point closest to the current position of the lifting hook in the rest of the tasks with the same-level priority, and taking the transport task corresponding to the starting point as a continuous transport task.
Specifically, the starting point or the ending point of the carrying task is generally located in the loading and unloading site or the construction area, when the tower crane is idle, the task with the highest priority is automatically obtained from the task management system, and the carrying path is planned, if a plurality of tasks are located in the same area, the tasks can be considered to be sequentially executed according to the priority of the tasks, so that unnecessary movement is reduced.
When meeting the tasks with the same-level priority, the system automatically inquires the task starting point closest to the current position of the lifting hook in the rest tasks with the same-level priority. To accurately determine the closest task start point, distance calculation methods such as euclidean distance, manhattan distance, etc. may be employed. Meanwhile, the distance is properly corrected in consideration of the actual construction environment and the obstacle situation. Once the closest task start point is determined, the transport task corresponding to the start point is used as the continuous transport task. By establishing a scientific and reasonable tower crane carrying task management mechanism, the tower crane can be ensured to efficiently and orderly execute carrying tasks, and the construction efficiency and the resource utilization efficiency are improved.
And identifying the starting point or the ending point in the intersection area, and evenly distributing the conveying task corresponding to the starting point or the ending point to the tower crane in the intersection area.
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 boundary areas in different tower crane working ranges are obtained. And triggering a task allocation mechanism when world coordinate system coordinates of the transport task including a starting point or an ending point are in the intersection region. The method specifically comprises the steps of determining the number and the state of the tower cranes in the intersection area, and carrying out average distribution according to the number of the tower cranes.
The starting point or the finishing point of the transport task in the intersection area is identified efficiently and accurately, and the tasks are distributed to the tower cranes in the intersection area evenly, so that the construction efficiency is improved, the resource allocation is optimized, and the timely completion of the tasks is ensured.
Example 2
In one embodiment, the method for controlling locking and unlocking of the upright 101 provided by the invention is shown, which comprises the following steps:
the locking and unlocking mechanism for a vertical rod 101 according to the first embodiment 1 is characterized in that a model for calculating the weight W of the vertical rod 101 is built based on the tensile force P
Based on the tensile force P, establishing a weight W calculation model of the vertical rod 101:
The tension of the pressure sensor is P, the inclination angle of the vertical rod 101 relative to the vertical direction is gamma, the Hall sensor can reflect the included angle theta between the lifting rope and the vertical rod 101, the friction coefficient between the vertical rod 101 and the platform is mu, and the mu is between 0.2 and 1.
According to the weight W of the upright 101, the automatic control of the winch can be realized by using the measured data. For example, the hoisting speed and the pulling force of the winch can be automatically adjusted according to the pulling force and the change of the included angle, the stable operation of the system is ensured, and the torque of the winch can be automatically adjusted according to the pulling force and the inclination angle of the vertical rod 101, so that the actions such as resistance or hovering of the vertical rod 101 are realized, the difficulty of manually operating the vertical rod 101 is reduced, and the working efficiency is improved.
Example 3
In one embodiment, referring to fig. 2 of the specification, a path planning system of a tower crane provided by the invention is shown. The tower crane comprises a slewing mechanism 3, a crane arm, an amplitude variation mechanism 1 and a modeling device 4, wherein the slewing mechanism 3 is used for driving the tower crane to rotate between different rotation positions, the amplitude variation mechanism 1 at least comprises a lifting hook, and the amplitude variation mechanism 1 can move along the crane arm between a plurality of movable positions;
The acquisition module is used for acquiring image data, wherein the modeling device 4 is arranged on the luffing mechanism 1 and used for acquiring the image data at a plurality of rotation positions and moving positions, and the image data comprises tower crane position information, the rotation position information, the moving position information and corresponding camera focal lengths during image shooting;
the modeling module is used for marking the image data into an image sequence, the image sequence has different visual angles, the field is modeled based on the image sequence to obtain a field three-dimensional model, the modeling comprises field feature extraction and matching, point cloud fusion and three-dimensional surface model conversion, and the field features at least comprise building field features and loading and unloading field features;
The division module is used for dividing the site three-dimensional model into a building area, an upper blanking area and a lower blanking area and an environment area, wherein the building area has the change of the height direction along with the construction progress, and the upper blanking area is used for loading and unloading construction materials and storing construction materials;
And the optimizing module is used for limiting the movement type of the luffing mechanism 1 according to the area where the lifting hook is positioned, wherein when the lifting hook is positioned in the feeding and discharging area and the slewing mechanism 3 moves, the horizontal movement and the vertical movement of the luffing mechanism 1 are locked.
The modeling module specifically comprises the steps of marking the image data into an image sequence, marking the acquired image data, and organizing the image data into the image sequence according to factors such as shooting time, position, visual angle and the like. Ensuring that the image sequence encompasses various angles and critical areas of the site, including the build site and the loading and unloading site. By adopting a shooting mode with multiple angles and multiple heights, more comprehensive site information can be obtained. Parameters of image acquisition, such as camera model, focal length, exposure time, etc., are recorded for subsequent processing and analysis.
The tower crane position information comprises world coordinate system coordinates of the tower crane, and camera internal parameters and camera external parameters are determined according to the world coordinate system coordinates of the tower crane, the rotation position information and the movable position information.
The camera internal parameters comprise a focal length f, a principal point coordinate (u0,v0) and the like, the focal length f can be usually obtained through camera calibration, and the principal point coordinate of the camera is determined based on the world coordinate system coordinate of the tower crane, the rotation position information and the activity position information.
The camera external parameters comprise 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 world coordinate system coordinates of the tower crane, the rotation position information and the activity position information.
Based on the internal parameters of the camera and the matched feature points, a base matrix is calculated, which describes the symmetrical geometrical relationship between the two pieces of image data.
Further, world coordinate system coordinates of the tower crane are obtained. The location of the tower crane in its world coordinate system may be determined by mounting a positioning device, such as a Global Positioning System (GPS) or an inertial navigation system (ins), on the tower crane. And acquiring rotation position information and activity position information of the tower crane. The rotation angle of the tower crane and the displacement of the luffing mechanism 1 can be monitored in real time by installing the angle sensor, the displacement sensor and other devices, and in addition, the rotation angle of the tower crane and the displacement of the luffing mechanism 1 can 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 superposed, the position and the posture of the camera in the world coordinate system are determined through geometric calculation, and then the position and the posture of the camera in the world coordinate system can be calculated and determined as the main point coordinates of the camera.
Further, the path planning method of the tower crane further comprises feature point extraction from the intersection region, and feature point matching is performed between image data from different modeling devices 4.
Specifically, by extracting feature points from the intersection region, the intersection region can correspond to image data from different modeling apparatuses 4, so that there are plural sets of image data that can be mutually cross-validated. Specifically, the extraction of image features may be implemented using algorithms such as SI FT (Sca l e-I NVAR IANT Feature Transform, scale invariant feature transform), SURF (Speeded Up Robust Features, accelerated robust features), etc., so as to extract feature points having invariance and uniqueness from the image data of the intersection region.
Further, the matching of the feature points includes describing the extracted feature points by using feature point descriptors, such as S IFT descriptors and SURF descriptors, and then matching the feature points in the two images by using an efficient feature point matching algorithm, such as FLANN (Fast L ibrary for Approximate Nearest Neighbors, fast approximate nearest neighbor search library), to find corresponding feature point pairs.
Further, the camera internal parameter and the camera external parameter are used for calculating a camera projection matrix, and the coordinate of the feature point in a world coordinate system is calculated by using a triangulation principle, and the method specifically comprises the following steps:
The camera projection matrix Pi＝Ki[Ri|ti ], wherein Ki is an i-th camera internal reference matrix, and Ri and ti are rotation matrices and translation vectors of the i-th camera, respectively;
Assuming that the pixel coordinates of the feature points in the two pieces of image data are (u1,v1) and (u2,v2) respectively, and the corresponding projection matrixes are P1 and P2 respectively, the three-dimensional coordinates x= [ X, y, z,1]T of the feature points satisfy the following equation:
And solving the equation set by a linear least square method to obtain the three-dimensional coordinates of the feature points, namely the coordinates of the feature points in a world coordinate system.
And fusing point clouds based on coordinates of the feature points in a world coordinate system, and converting the point clouds into a continuous three-dimensional surface model by using a surface reconstruction algorithm.
The optimization module specifically comprises the steps of determining the position and the posture of the luffing mechanism 1 in a world coordinate system through geometric calculation by superposing the rotation angle of the tower crane and the displacement of the luffing mechanism 1 based on world coordinate system coordinates, and immediately locking the horizontal movement and the vertical movement of the luffing mechanism 1 when the luffing mechanism 1 and the lifting hook are in an upper and lower material area.
By optimizing the construction path of the luffing mechanism 1 in the loading and unloading area, the construction safety is improved, accidents caused by unnecessary movement of the luffing mechanism 1 when the lifting hook is positioned in the loading and unloading area are avoided, the operation of the tower crane is more standard and efficient, unnecessary actions and time waste are reduced, the stability of a tower crane system is enhanced, and shaking and unstable factors possibly caused by complex movement combination are reduced.
In addition, the path planning method of the tower crane further comprises the step of establishing a transport task, wherein the transport task comprises a starting point, a finishing point and a transport task priority level, and the tower crane plans the transport task according to the high and low ordered task priority levels.
And inquiring a task starting point closest to the current position of the lifting hook in the rest of the tasks with the same-level priority, and taking the transport task corresponding to the starting point as a continuous transport task.
Specifically, the starting point or the ending point of the carrying task is generally located in the loading and unloading site or the construction area, when the tower crane is idle, the task with the highest priority is automatically obtained from the task management system, and the carrying path is planned, if a plurality of tasks are located in the same area, the tasks can be considered to be sequentially executed according to the priority of the tasks, so that unnecessary movement is reduced.
When meeting the tasks with the same-level priority, the system automatically inquires the task starting point closest to the current position of the lifting hook in the rest tasks with the same-level priority. To accurately determine the closest task start point, distance calculation methods such as euclidean distance, manhattan distance, etc. may be employed. Meanwhile, the distance is properly corrected in consideration of the actual construction environment and the obstacle situation. Once the closest task start point is determined, the transport task corresponding to the start point is used as the continuous transport task. By establishing a scientific and reasonable tower crane carrying task management mechanism, the tower crane can be ensured to efficiently and orderly execute carrying tasks, and the construction efficiency and the resource utilization efficiency are improved.
And identifying the starting point or the ending point in the intersection area, and evenly distributing the conveying task corresponding to the starting point or the ending point to the tower crane in the intersection area.
Example 3
The present invention provides a computer readable storage medium having a computer program stored thereon, wherein the program is executed by a microprocessor to implement the path planning method of the tower crane according to any one of embodiment 1.
Compared with the prior art, the invention has the beneficial technical effects that the modeling device 4 is arranged on the luffing mechanism 1 of the tower crane and is used for collecting image data at a plurality of rotating positions and moving positions, so that the camera internal parameters and the camera external parameters of the modeling device 4 can be simply and efficiently determined, and the site characteristics can be efficiently extracted and matched, and the point cloud fusion and the three-dimensional surface model conversion can be realized. By identifying the site characteristics, the construction path can be optimized, and the construction efficiency and the resource utilization efficiency are improved.
The technical features of the above embodiments may be arbitrarily combined, and all possible combinations of the technical features in the above embodiments are not described for brevity of description, however, as long as there is no contradiction between the combinations of the technical features, they should be considered as the scope of the description.
The foregoing examples illustrate only a few embodiments of the invention, which are described in detail and are not to be construed as limiting the scope of the invention. It should be noted that it will be apparent to those skilled in the art that several variations and modifications can be made without departing from the spirit of the invention, which are all within the scope of the invention. Accordingly, the scope of protection of the present invention is to be determined by the appended claims.