Tower crane motion planning method and system

Abstract

The invention discloses a tower crane motion planning method and system, and relates to the technical field of cranes. Comprising the following steps: collecting geometric parameters and material parameters of the tower crane, constructing a finite element model of the tower crane based on the geometric parameters and the material parameters, and determining motion constraint conditions of the tower crane; based on the established model, setting target positions of the rotating arm and the trolley, generating a plurality of paths for the rotating arm and the trolley to reach the target positions, determining a shortest path, inputting control variable combinations to carry out a simulation test, obtaining cost factors under different control variable combinations, and based on a set fitness function, selecting motion planning input to obtain a simulation result. Meanwhile, a working range environment image and real-time environment load data of the tower crane are collected; and correcting the motion planning input based on the working range environment image of the tower crane and the real-time environment load data, and adjusting the motion paths of the rotating arm and the trolley to obtain the accurate motion planning input and the motion path.

Description

Technical Field

[0001] The present invention relates to the technical field of cranes, and in particular to a tower crane motion planning method and system. Background Art

[0002] In the field of modern construction and engineering, tower cranes are an important type of lifting equipment, widely used in the construction of high-rise buildings and the installation of large structures. These cranes are able to efficiently complete tasks in complex construction environments due to their height and load capacity. However, with the continuous expansion of building scale and the increasing complexity of construction environments, the challenges faced by traditional tower cranes in motion planning and path optimization are becoming more and more significant.

[0003] First, the motion planning of tower cranes involves multiple complex factors, including but not limited to its geometric parameters and material parameters. These parameters directly affect the stability, load capacity and motion performance of the crane. Under high wind speeds or adverse weather conditions, the operational safety of tower cranes is severely tested, and traditional motion planning methods are difficult to quickly adapt to these changes. In addition, existing methods mostly rely on experience and manual judgment, lack of systematicity and scientificity, resulting in uncertainty in the path selection and motion control process, which in turn increases construction risks and energy consumption.

[0004] Secondly, the current motion path planning of tower cranes usually does not take into account the impact of real-time environmental factors, such as wind speed, wind direction, obstacle location, etc. These environmental factors may cause load imbalance, motion path deviation, and even safety accidents in actual operation. In the case of high wind speed, the swing and vibration amplitude of the jib will increase significantly, posing a threat to construction accuracy and construction safety. However, traditional control algorithms have poor adaptability to dynamic environmental factors and often find it difficult to achieve real-time and effective motion adjustments. Therefore, a new motion planning method is urgently needed to better cope with the challenges in complex construction environments and improve the work efficiency and safety of tower cranes.

[0005] In the prior art, the publication number CN118239388A discloses a tower crane motion planning method, system, medium, equipment and product, and the specific steps include: obtaining the target position of the jib, trolley and suspension rope in the tower crane; based on the target position of the jib, trolley and suspension rope in the tower crane, the optimal motion trajectory of the jib, trolley and suspension rope is obtained by solving the optimization target; wherein the optimization target is to minimize the sum of the transportation time, energy consumption and absolute change rate of the control input, and based on the coupling relationship between the state variables and the control input of the tower crane and the path parameter, the optimization target is converted into a function of the path parameter. The tower crane realizes efficient and safe load transportation. However, this method mainly relies on the preset target position and optimization target, and fails to fully consider the dynamic changes of real-time environmental factors (such as wind speed, wind direction, obstacles, etc.). This may cause the motion trajectory of the tower crane to be unable to adapt to emergencies in actual operation, thereby affecting safety and efficiency. Therefore, relying only on a set of acquisition devices and a set of judgment logic algorithms to perform general motion planning not only wastes resources, but also reduces the safety and effectiveness of the planning system.

[0006] The above information disclosed in this Background section is only for enhancement of understanding of the background of the present disclosure and therefore it may contain information that does not constitute the prior art that is already known to one of ordinary skill in the art. Summary of the invention

[0007] The object of the present invention is to provide a tower crane motion planning method and system to solve the problems raised in the above background technology.

[0008] To achieve the above object, the present invention provides the following technical solutions: A tower crane motion planning method, the specific steps include: Collecting geometric parameters and material parameters of the tower crane, building a finite element model of the tower crane based on the geometric parameters and material parameters, and determining the motion constraints of the tower crane based on the geometric parameters and material parameters, wherein the geometric parameters include tower height, jib length, trolley shape, base size, and rope length for lifting loads, and the material parameters include stiffness, Poisson's ratio, and density of the tower crane tower material; Based on the established tower crane finite element model, the target positions of the jib and trolley are set, and the A * The algorithm generates several paths for the slewing arm and the trolley to reach the target position, determines the shortest path, inputs the control variables for simulation test, and obtains the cost factors under different control variable combinations. The control variables include the slewing arm rotation control torque, the slewing arm motor power and the displacement force of the trolley. The cost factors include the shortest path movement time, vibration amplitude and energy consumption of movement. Based on the cost factors under different control variable combinations, a fitness function is set, the fitness values ​​of different control variable combinations are calculated, and the control variable combination with the largest fitness value is selected as the motion planning input, and at the same time, an environmental image of the working range of the tower crane and real-time environmental load data are collected, wherein the real-time environmental load data includes wind direction data and wind speed data; Based on the comparison between the environmental image of the tower crane's working range and the real-time working image, the difference area between the two images is calculated. The motion planning input is corrected based on the difference area and the real-time environmental load data. At the same time, the motion path of the jib and the trolley is adjusted to finally obtain accurate motion planning input and motion path.

[0009] Furthermore, geometric parameters and material parameters of the tower crane are collected, and the motion constraint conditions of the tower crane are determined based on the collected geometric parameters and material parameters, wherein the formula based on the motion constraint conditions is: ; In the formula, is the rotation control torque, To resist the overturning moment, is the jib movement angle of the tower crane, is the maximum range of motion of the jib of the tower crane. is the maximum tensile stress of the tower body, is the yield strength of the tower body material, is the trolley motion acceleration, is the maximum acceleration of the trolley movement; The moment of resistance to overturning The calculation is based on the formula: ; In the formula, is the base size width, Indicates the tower height, is the density of the tower material, is the acceleration due to gravity; Maximum range of jib motion angle of tower crane The calculation is based on the formula: ; In the formula, is the length of the spiral arm; Maximum tensile stress of tower body The calculation is based on the formula: ; In the formula, Indicates the maximum load. is the length of the rope used to lift the load, It represents the distance from the tower section to the neutral axis. represents the moment of inertia of the cross section.

[0010] Furthermore, through A * The algorithm generates several paths for the jib and trolley to reach the target location and determines the shortest path. The logic is as follows: establish a plane coordinate system for the tower crane, with the horizontal direction of the jib as the x-axis, the direction perpendicular to the tower body as the y-axis, and the direction away from the tower body as the positive direction of the x-axis. To indicate the position of the trolley and the angle of the swing arm; Set A based on the established plane coordinate system * The heuristic function of the algorithm is used to estimate the distance from the current node to the target node, where the specific expression of the heuristic function is: ; In the formula, represents the heuristic function, Indicates the current node coordinates, Represents the nodes adjacent to the current node; Among them A * The specific steps of the algorithm to determine the shortest path include: creating an open list to store the nodes to be evaluated and a closed list to store the evaluated nodes, adding the starting node to the open list, performing a loop operation, and when the open list is not empty, finding the starting node from the open list as the current node, if the current node is the target node, building the path and ending the algorithm, moving the current node from the open list to the closed list, for each adjacent node of the current node, if the adjacent node is in the closed list, skip it, if the adjacent node is not in the open list, calculate its heuristic function The value of and add it to the open list. If the adjacent node is already in the open list, check the heuristic function to update it. Value, select the heuristic function The adjacent node with the smallest value is used as the next current node until the target node is found, and the shortest path is constructed by tracing back from the target node to the starting node.

[0011] Furthermore, based on the cost factors under different combinations of control variables, the logic for setting the fitness function is: The motion time under different input control variable combinations is obtained through simulation experiments. Based on the input control variable data, the vibration amplitude and the energy consumption of the motion are calculated. The formulas for calculating the vibration amplitude and the energy consumption of the motion are: ; ; In the formula, is the vibration amplitude generated during the movement, is the energy consumption of the movement at time t, is the shortest path movement time, represents the acceleration of the rotary motion of the spiral arm at time t, represents the acceleration of the trolley at time t, Indicates the power of the swing arm motor, is the displacement of the trolley, is the displacement force of the trolley at time t, is the friction coefficient of the trolley motion, is the mass of the trolley, represents the acceleration due to gravity; Among them, the acceleration of the trolley at time t is It is calculated from the displacement force of the trolley, and the specific formula is: ; The acceleration of the arm rotation at time t The torque is obtained by rotating the swing arm. The specific calculation formula is: ; In the formula, is the arm rotation control torque at time t, is the moment of inertia of the swing arm.

[0012] Furthermore, based on the cost factors under different combinations of control variables, a fitness function is set, wherein the fitness function is established in combination with the motion constraint conditions, and the specific formula of the set fitness function is: ; In the formula, represents the fitness function, represents the combination of control variables, including the swing arm rotation control torque, swing arm motor power and trolley displacement force, , and are vibration amplitude, energy consumption of movement and movement time, respectively. ; Based on the set fitness function, the control variable combination with the highest fitness is determined through the genetic algorithm as the motion planning input.

[0013] Furthermore, a high-definition camera is set at the center of the jib to collect ground images of the entire movement process of the crane. At the same time, based on the collected environmental images of the working range of the tower crane, a background model is established through the background modeling algorithm, and the difference between the current frame image collected by the high-definition camera and the background model is calculated. The changed area in the image is marked and extracted, and the area of ​​the changed area in the image is extracted through the edge detection algorithm; at the same time, the wind direction and wind speed data at the horizontal plane of the jib are detected by sensors.

[0014] Furthermore, the logic for modifying the motion planning input based on the real-time environmental load data is as follows: ; ; ; In the formula, is the correction value of the swing arm rotation control torque at time t, is the power correction value of the swing arm motor at time t, is the displacement force correction value of the trolley at time t, and Respectively represent the wind speed and wind direction angle at time t, is the angular velocity of the swing arm at time t, , and They represent the torque adjustment coefficient, power adjustment coefficient and displacement force adjustment coefficient respectively.

[0015] Furthermore, the logic for adjusting the motion path of the jib and the trolley is as follows: the area and wind speed data of the changed area in the image are extracted through the edge detection algorithm to adjust the motion path of the jib and the trolley, and the changed area threshold and the maximum wind speed threshold are set. When it is detected that the area of ​​the changed area in the image is greater than or equal to the changed area threshold, or the current wind speed is greater than or equal to the maximum wind speed threshold, the current node where the crane is located is marked as an abnormal node. After removing the abnormal node, the A node is used again. * The algorithm generates several paths for the arms and trolleys to reach the target location and determines the shortest path without abnormal nodes.

[0016] The present invention also provides a tower crane motion planning system, which is used to execute the above-mentioned tower crane motion planning method, and includes: A simulation model building module is used to collect geometric parameters and material parameters of the tower crane, build a finite element model of the tower crane based on the geometric parameters and material parameters, and determine the motion constraints of the tower crane based on the geometric parameters and material parameters. The geometric parameters include tower height, jib length, trolley shape, base size, and rope length for lifting loads. The material parameters include stiffness, Poisson's ratio, and density of the tower crane tower material. The motion path planning module is used to set the target position of the jib and the trolley based on the established tower crane finite element model. * The algorithm generates several paths for the slewing arm and the trolley to reach the target position, determines the shortest path, inputs the control variables for simulation test, and obtains the cost factors under different control variable combinations. The control variables include the slewing arm rotation control torque, the slewing arm motor power and the displacement force of the trolley. The cost factors include the shortest path movement time, vibration amplitude and energy consumption of movement. The optimal solution characterization module is used to set the fitness function based on the cost factors under different control variable combinations, calculate the fitness values ​​of different control variable combinations, select the control variable combination with the largest fitness value as the motion planning input, and collect the working range environment image and real-time environmental load data of the tower crane at the same time, wherein the real-time environmental load data includes wind direction data and wind speed data; The motion planning correction module is used to compare the working range environment image of the tower crane with the real-time working image, calculate the difference area between the two images, correct the motion planning input based on the difference area and real-time environmental load data, and adjust the motion path of the jib and the trolley at the same time, and finally obtain accurate motion planning input and motion path.

[0017] Compared with the prior art, the present invention has the following beneficial effects: First, the finite element model established based on the geometric and material parameters of the tower crane makes motion planning more scientific and accurate. Through the precise simulation of the dynamic characteristics of the tower crane, the operational risk is reduced and the construction safety is improved. Secondly, the optimal path generated by the A* algorithm combined with the real-time environmental load data can effectively reduce the movement time, vibration amplitude and energy consumption, making the tower crane more efficient in complex environments. In addition, the introduction of the fitness function makes the selection of different control variables (such as the jib rotation control torque, the jib motor power and the displacement force of the trolley) more scientific, ensuring maximum adaptability and operational efficiency, thereby promoting construction progress and reducing operating costs. Finally, the combination of obstacle area recognition and real-time environmental data not only improves the intelligence and adaptability of the crane's motion path, but also enhances its ability to cope with dynamic environments, allowing the tower crane to flexibly adjust the motion path and effectively avoid potential obstacles and safety hazards. It can still maintain efficient and safe operation performance under more complex and changeable construction conditions. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1 It is a schematic diagram of the overall method flow of the present invention; Figure 2 It is a schematic diagram of the overall system structure of the present invention. DETAILED DESCRIPTION

[0019] In order to make the objectives, technical solutions and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with specific embodiments.

[0020] It should be noted that, unless otherwise defined, the technical terms or scientific terms used in the present invention should be understood by people with ordinary skills in the field to which the present invention belongs. The words "first", "second" and similar words used in the present invention do not indicate any order, quantity or importance, but are only used to distinguish different components. "Include" or "comprise" and similar words mean that the elements or objects appearing before the word include the elements or objects listed after the word and their equivalents, without excluding other elements or objects. "Connect" or "connected" and similar words are not limited to physical or mechanical connections, but may include electrical connections, whether direct or indirect. "Up", "down", "left", "right" and the like are only used to indicate relative positional relationships. When the absolute position of the described object changes, the relative positional relationship may also change accordingly.

[0021] Example: See also Figure 1 , the present invention provides a technical solution: A tower crane motion planning method, the specific steps include: Step 1: Collect the geometric parameters and material parameters of the tower crane, build a finite element model of the tower crane based on the geometric parameters and material parameters, and determine the motion constraints of the tower crane based on the geometric parameters and material parameters. The geometric parameters include tower height, jib length, trolley shape, base size, and rope length for lifting loads. The material parameters include stiffness, Poisson's ratio, and density of the tower crane tower material. The geometric parameters and material parameters of the tower crane are collected, and the motion constraint conditions of the tower crane are determined based on the collected geometric parameters and material parameters, wherein the formula based on the motion constraint conditions is: ; In the formula, is the rotation control torque, To resist the overturning moment, is the jib movement angle of the tower crane, is the maximum range of motion of the jib of the tower crane. is the maximum tensile stress of the tower body, is the yield strength of the tower body material, is the trolley motion acceleration, is the maximum acceleration of the trolley movement; The moment of resistance to overturning The calculation is based on the formula: ; In the formula, is the base size width, Indicates the tower height, is the density of the tower material, is the acceleration due to gravity; Maximum range of jib motion angle of tower crane The calculation is based on the formula: ; In the formula, is the length of the spiral arm; Maximum tensile stress of tower body The calculation is based on the formula: ; In the formula, Indicates the maximum load. is the length of the rope used to lift the load, It represents the distance from the tower section to the neutral axis. represents the moment of inertia of the cross section. In stress analysis, the length of the rope and the location of the load also affect the forces applied to the tower. Longer ropes may result in greater leverage, thereby increasing the bending moment; where the moment of inertia of the cross section The method of obtaining is: according to the actual shape of the cross section, select the corresponding moment of inertia formula. Since the cross section of the crane tower is generally rectangular, the moment of inertia of the cross section can be obtained by calculating the formula for the moment of inertia of a rectangular cross section. .

[0022] Step 2: Based on the established tower crane finite element model, set the target positions of the jib and trolley through A * The algorithm generates several paths for the slewing arm and the trolley to reach the target position, determines the shortest path, inputs the control variables for simulation test, and obtains the cost factors under different control variable combinations. The control variables include the slewing arm rotation control torque, the slewing arm motor power and the displacement force of the trolley. The cost factors include the shortest path movement time, vibration amplitude and energy consumption of movement. By A * The algorithm generates several paths for the jib and trolley to reach the target location and determines the shortest path. The logic is as follows: establish a plane coordinate system for the tower crane, with the horizontal direction of the jib as the x-axis, the direction perpendicular to the tower body as the y-axis, and the direction away from the tower body as the positive direction of the x-axis. To indicate the position of the trolley and the angle of the swing arm; Set A based on the established plane coordinate system * The heuristic function of the algorithm is used to estimate the distance from the current node to the target node, where the specific expression of the heuristic function is: ; In the formula, represents the heuristic function, Indicates the current node coordinates, Represents the nodes adjacent to the current node; Among them A * The specific steps of the algorithm to determine the shortest path include: creating an open list to store the nodes to be evaluated and a closed list to store the evaluated nodes, adding the starting node to the open list, performing a loop operation, and when the open list is not empty, finding the starting node from the open list as the current node, if the current node is the target node, building the path and ending the algorithm, moving the current node from the open list to the closed list, for each adjacent node of the current node, if the adjacent node is in the closed list, skip it, if the adjacent node is not in the open list, calculate its heuristic function The value of and add it to the open list. If the adjacent node is already in the open list, check the heuristic function to update it. Value, select the heuristic function The adjacent node with the smallest value is used as the next current node until the target node is found, and the shortest path is constructed by tracing back from the target node to the starting node.

[0023] Step 3: Based on the cost factors under different control variable combinations, set the fitness function, calculate the fitness values ​​of different control variable combinations, select the control variable combination with the largest fitness value as the motion planning input, and collect the working range environment image and real-time environmental load data of the tower crane at the same time, wherein the real-time environmental load data includes wind direction data and wind speed data; Based on the cost factors under different control variable combinations, the logic for setting the fitness function is: The motion time under different input control variable combinations is obtained through simulation experiments. Based on the input control variable data, the vibration amplitude and the energy consumption of the motion are calculated. The formulas for calculating the vibration amplitude and the energy consumption of the motion are: ; ; In the formula, is the vibration amplitude generated during the movement, is the energy consumption of the movement at time t, is the shortest path movement time, represents the acceleration of the rotary motion of the spiral arm at time t, represents the acceleration of the trolley at time t, Indicates the power of the swing arm motor, is the displacement of the trolley, is the displacement force of the trolley at time t, is the friction coefficient of the trolley motion, is the mass of the trolley, represents the acceleration due to gravity; Among them, the acceleration of the trolley at time t is It is calculated from the displacement force of the trolley, and the specific formula is: ; The acceleration of the arm rotation at time t The torque is obtained by rotating the swing arm. The specific calculation formula is: ; In the formula, is the arm rotation control torque at time t, is the moment of inertia of the swing arm; Among them, the moment of inertia of the swing arm is The calculation is based on the formula: ; In the formula, is the mass of the spiral arm, represents the width of the spiral arm section, is the height of the cross section of the spiral arm; it is assumed that the cross section of the spiral arm is a rectangle. If the cross section of the actual spiral arm is of other shapes, different moment of inertia calculation formulas can be selected according to actual conditions.

[0024] Based on the cost factors under different combinations of control variables, a fitness function is set, which is established in combination with motion constraints. The specific formula of the fitness function is as follows: ; In the formula, represents the fitness function, represents the combination of control variables, including the swing arm rotation control torque, swing arm motor power and trolley displacement force, , and They are vibration amplitude, energy consumption of movement and movement time respectively. Since the larger the vibration amplitude generated during the movement, the lower the safety factor, the weight of vibration amplitude is greater than the energy consumption and movement time in the fitness function. Therefore, ; Based on the set fitness function, the control variable combination with the maximum fitness is determined by genetic algorithm as the motion planning input; At the same time, the fitness function It is inversely proportional to the vibration amplitude, energy consumption of exercise and exercise time. That is, the smaller the vibration amplitude, the lower the energy consumption of exercise and the shorter the exercise time, the higher the fitness value.

[0025] The step of determining the control variable combination with the maximum fitness through genetic algorithm includes: defining individual chromosomes, wherein the individual chromosomes have three gene positions, which correspond to different groups of data storing the swing arm rotation control torque, swing arm motor power and displacement force of the trolley, selecting several individual chromosomes to form an initial population, calculating the fitness values ​​of individual chromosomes in the initial population, and performing iterative operations of selection, crossover and mutation until the iteration termination condition is reached, wherein the iteration termination condition can be set to terminate after a fixed number of iterations, and the individual chromosome with the maximum fitness in the current population is selected as the optimal solution. Alternatively, a fitness threshold can be set. When an individual chromosome with a fitness greater than the fitness threshold appears during the iteration process, the iteration is stopped and the individual chromosome is used as the optimal solution. The genetic algorithm for obtaining the optimal solution is a mature existing technology, so it will not be described in detail here.

[0026] Step 4: Compare the working range environment image of the tower crane with the real-time working image, calculate the difference area between the two images, correct the motion planning input based on the difference area and real-time environmental load data, and adjust the motion path of the jib and trolley to finally obtain accurate motion planning input and motion path.

[0027] Set up a high-definition camera at the center of the jib, and use a tripod or other supporting equipment to fix the high-definition camera at the selected position to ensure that the camera can cover the entire working range of the crane. Used to collect ground images of the entire movement process of the crane, set the resolution, frame rate and exposure time of the camera to ensure image quality, start real-time collection of images during the movement of the crane, and record the timestamp. At the same time, based on the collection of environmental images of the working range of the tower crane, a background model is established through the background modeling algorithm, and methods such as Gaussian mixture model (GMM) or mean background modeling can be used. Calculate the difference between the current frame image collected by the high-definition camera and the background model, mark and extract the changed area in the image, and extract the area of ​​the changed area in the image through the edge detection algorithm, where the contour detection algorithm (such as Canny edge detection) can be used to extract the edge of the changed area; At the same time, the wind direction and wind speed data at the horizontal plane of the jib are detected by the sensor to ensure that the image acquisition and sensor data are recorded at the same timestamp and align the data.

[0028] The logic behind the correction of motion planning input based on real-time environmental load data is: ; ; ; In the formula, is the correction value of the swing arm rotation control torque at time t, is the power correction value of the swing arm motor at time t, is the displacement force correction value of the trolley at time t, and Respectively represent the wind speed and wind direction angle at time t, is the angular velocity of the swing arm at time t, , and They represent the torque adjustment coefficient, power adjustment coefficient and displacement force adjustment coefficient respectively.

[0029] The logic for adjusting the motion path of the jib and the trolley is as follows: the area and wind speed data of the changed area in the image are extracted through the edge detection algorithm to adjust the motion path of the jib and the trolley, and the area threshold of the changed area and the maximum wind speed threshold are set. When it is detected that the area of ​​the changed area in the image is greater than or equal to the area threshold of the changed area, or the current wind speed is greater than or equal to the maximum wind speed threshold, the current node where the crane is located is marked as an abnormal node. After removing the abnormal node, the A node is used again. * The algorithm generates several paths for the arms and trolleys to reach the target location and determines the shortest path without abnormal nodes.

[0030] See also Figure 2The present invention also provides a tower crane motion planning system, which is used to execute the above-mentioned tower crane motion planning method, including: A simulation model building module is used to collect geometric parameters and material parameters of the tower crane, build a finite element model of the tower crane based on the geometric parameters and material parameters, and determine the motion constraints of the tower crane based on the geometric parameters and material parameters. The geometric parameters include tower height, jib length, trolley shape, base size, and rope length for lifting loads. The material parameters include stiffness, Poisson's ratio, and density of the tower crane tower material. The motion path planning module is used to set the target position of the jib and the trolley based on the established tower crane finite element model. * The algorithm generates several paths for the slewing arm and the trolley to reach the target position, determines the shortest path, inputs the control variables for simulation test, and obtains the cost factors under different control variable combinations. The control variables include the slewing arm rotation control torque, the slewing arm motor power and the displacement force of the trolley. The cost factors include the shortest path movement time, vibration amplitude and energy consumption of movement. The optimal solution characterization module is used to set the fitness function based on the cost factors under different control variable combinations, calculate the fitness values ​​of different control variable combinations, select the control variable combination with the largest fitness value as the motion planning input, and collect the working range environment image and real-time environmental load data of the tower crane at the same time, wherein the real-time environmental load data includes wind direction data and wind speed data; The motion planning correction module is used to compare the working range environment image of the tower crane with the real-time working image, calculate the difference area between the two images, correct the motion planning input based on the difference area and real-time environmental load data, and adjust the motion path of the jib and the trolley at the same time, and finally obtain accurate motion planning input and motion path.

[0031] The above formulas are all dimensionless and numerical calculations. The formula is a formula for the most recent real situation obtained by collecting a large amount of data and performing software simulation. The preset parameters in the formula are set by technicians in this field according to actual conditions.

[0032] The above embodiments may be implemented in whole or in part by software, hardware, firmware or any other combination thereof. When implemented by software, the above embodiments may be implemented in whole or in part in the form of a computer program product. Those skilled in the art may appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein may be implemented by electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed by hardware or software methods depends on the specific application and design constraints of the technical solution.

[0033] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, and may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0034] The above description is only a specific implementation manner of the present application, but the protection scope of the present application is not limited thereto. Any technician familiar with the technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application.

Claims

1. A tower crane motion planning method, characterized in that: The specific steps include: Collecting geometric parameters and material parameters of the tower crane, building a finite element model of the tower crane based on the geometric parameters and material parameters, and determining the motion constraints of the tower crane based on the geometric parameters and material parameters, wherein the geometric parameters include tower height, jib length, trolley shape, base size, and rope length for lifting loads, and the material parameters include stiffness, Poisson's ratio, and density of the tower crane tower material; Based on the established tower crane finite element model, the target positions of the jib and trolley are set, and the A * The algorithm generates several paths for the slewing arm and the trolley to reach the target position, determines the shortest path, inputs the control variables for simulation test, and obtains the cost factors under different control variable combinations. The control variables include the slewing arm rotation control torque, the slewing arm motor power and the displacement force of the trolley. The cost factors include the shortest path movement time, vibration amplitude and energy consumption of movement. Based on the cost factors under different control variable combinations, a fitness function is set, the fitness values ​​of different control variable combinations are calculated, and the control variable combination with the largest fitness value is selected as the motion planning input, and at the same time, an environmental image of the working range of the tower crane and real-time environmental load data are collected, wherein the real-time environmental load data includes wind direction data and wind speed data; Based on the comparison between the environmental image of the tower crane's working range and the real-time working image, the difference area between the two images is calculated. The motion planning input is corrected based on the difference area and the real-time environmental load data. At the same time, the motion path of the jib and the trolley is adjusted to finally obtain accurate motion planning input and motion path.

2. A tower crane motion planning method according to claim 1, characterized in that: The geometric parameters and material parameters of the tower crane are collected, and the motion constraint conditions of the tower crane are determined based on the collected geometric parameters and material parameters, wherein the formula based on the motion constraint conditions is: ； In the formula, is the rotation control torque, To resist the overturning moment, is the jib movement angle of the tower crane, is the maximum range of motion of the jib of the tower crane. is the maximum tensile stress of the tower body, is the yield strength of the tower body material, is the trolley motion acceleration, is the maximum acceleration of the trolley movement; The moment of resistance to overturning The calculation is based on the formula: ； In the formula, is the base size width, Indicates the tower height, is the density of the tower material, is the acceleration due to gravity; Maximum range of jib motion angle of tower crane The calculation is based on the formula: ； In the formula, is the length of the spiral arm; Maximum tensile stress of tower body The calculation is based on the formula: ； In the formula, Indicates the maximum load. is the length of the rope used to lift the load, It represents the distance from the tower section to the neutral axis. represents the moment of inertia of the cross section.

3. A tower crane motion planning method according to claim 1, characterized in that: By A * The algorithm generates several paths for the jib and trolley to reach the target location and determines the shortest path. The logic is as follows: establish a plane coordinate system for the tower crane, with the horizontal direction of the jib as the x-axis, the direction perpendicular to the tower body as the y-axis, and the direction away from the tower body as the positive direction of the x-axis. To indicate the position of the trolley and the angle of the swing arm; Set A based on the established plane coordinate system * The heuristic function of the algorithm is used to estimate the distance from the current node to the target node, where the specific expression of the heuristic function is: ； In the formula, represents the heuristic function, Indicates the current node coordinates, Represents the nodes adjacent to the current node; Among them A * The specific steps of the algorithm to determine the shortest path include: creating an open list to store the nodes to be evaluated and a closed list to store the evaluated nodes, adding the starting node to the open list, performing a loop operation, and when the open list is not empty, finding the starting node from the open list as the current node, if the current node is the target node, building the path and ending the algorithm, moving the current node from the open list to the closed list, for each adjacent node of the current node, if the adjacent node is in the closed list, skip it, if the adjacent node is not in the open list, calculate its heuristic function The value of and add it to the open list. If the adjacent node is already in the open list, check the heuristic function to update it. Value, select the heuristic function The adjacent node with the smallest value is used as the next current node until the target node is found, and the shortest path is constructed by tracing back from the target node to the starting node.

4. A tower crane motion planning method according to claim 2, characterized in that: Based on the cost factors under different control variable combinations, the logic for setting the fitness function is: The motion time under different input control variable combinations is obtained through simulation experiments. Based on the input control variable combination data, the vibration amplitude and the energy consumption of the motion are calculated. The formulas for calculating the vibration amplitude and the energy consumption of the motion are: ； ； In the formula, is the vibration amplitude generated during the movement, is the energy consumption of the movement at time t, is the shortest path movement time, represents the acceleration of the rotary motion of the spiral arm at time t, represents the acceleration of the trolley at time t, Indicates the power of the swing arm motor, is the displacement of the trolley, is the displacement force of the trolley at time t, is the friction coefficient of the trolley motion, is the mass of the trolley, represents the acceleration due to gravity; Among them, the acceleration of the trolley at time t is It is calculated from the displacement force of the trolley, and the specific formula is: ； The acceleration of the arm rotation at time t The torque is obtained by rotating the swing arm. The specific calculation formula is: ； In the formula, is the arm rotation control torque at time t, is the moment of inertia of the swing arm.

5. A tower crane motion planning method according to claim 4, characterized in that: Based on the cost factors under different combinations of control variables, a fitness function is set, which is established in combination with motion constraints. The specific formula of the fitness function is as follows: ； In the formula, represents the fitness function, represents the combination of control variables, including the swing arm rotation control torque, swing arm motor power and trolley displacement force, , and are vibration amplitude, energy consumption of movement and movement time, respectively. ; Based on the set fitness function, the control variable combination with the maximum fitness is determined by genetic algorithm as the motion planning input.

6. A tower crane motion planning method according to claim 1, characterized in that: A high-definition camera is set at the center of the jib to collect ground images of the entire movement process of the crane. At the same time, based on the collection of environmental images of the working range of the tower crane, a background model is established through the background modeling algorithm, and the difference between the current frame image collected by the high-definition camera and the background model is calculated. The changed area in the image is marked and extracted, and the area of ​​the changed area in the image is extracted through the edge detection algorithm. At the same time, the wind direction and wind speed data at the horizontal plane of the jib are detected by sensors.

7. A tower crane motion planning method according to claim 4, characterized in that: The logic behind the correction of motion planning input based on real-time environmental load data is: ； ； ； In the formula, is the correction value of the swing arm rotation control torque at time t, is the power correction value of the swing arm motor at time t, is the displacement force correction value of the trolley at time t, and Respectively represent the wind speed and wind direction angle at time t, is the angular velocity of the swing arm at time t, , and They represent the torque adjustment coefficient, power adjustment coefficient and displacement force adjustment coefficient respectively.

8. A tower crane motion planning method according to claim 6, characterized in that: The logic for adjusting the motion path of the jib and the trolley is as follows: the area and wind speed data of the changed area in the image are extracted through the edge detection algorithm to adjust the motion path of the jib and the trolley, and the area threshold of the changed area and the maximum wind speed threshold are set. When it is detected that the area of ​​the changed area in the image is greater than or equal to the area threshold of the changed area, or the current wind speed is greater than or equal to the maximum wind speed threshold, the current node where the crane is located is marked as an abnormal node. After removing the abnormal node, the A node is used again. * The algorithm generates several paths for the arms and trolleys to reach the target location and determines the shortest path without abnormal nodes.

9. A tower crane motion planning system, characterized in that: The tower crane motion planning system is used to execute the tower crane motion planning method according to any one of claims 1 to 8, specifically comprising: A simulation model building module is used to collect geometric parameters and material parameters of the tower crane, build a finite element model of the tower crane based on the geometric parameters and material parameters, and determine the motion constraints of the tower crane based on the geometric parameters and material parameters. The geometric parameters include tower height, jib length, trolley shape, base size, and rope length for lifting loads. The material parameters include stiffness, Poisson's ratio, and density of the tower crane tower material. The motion path planning module is used to set the target position of the jib and the trolley based on the established tower crane finite element model. * The algorithm generates several paths for the slewing arm and the trolley to reach the target position, determines the shortest path, inputs the control variables for simulation test, and obtains the cost factors under different control variable combinations. The control variables include the slewing arm rotation control torque, the slewing arm motor power and the displacement force of the trolley. The cost factors include the shortest path movement time, vibration amplitude and energy consumption of movement. The optimal solution characterization module is used to set the fitness function based on the cost factors under different control variable combinations, calculate the fitness values ​​of different control variable combinations, select the control variable combination with the largest fitness value as the motion planning input, and collect the working range environment image and real-time environmental load data of the tower crane at the same time, wherein the real-time environmental load data includes wind direction data and wind speed data; The motion planning correction module is used to compare the working range environment image of the tower crane with the real-time working image, calculate the difference area between the two images, correct the motion planning input based on the difference area and real-time environmental load data, and adjust the motion path of the jib and the trolley at the same time, and finally obtain accurate motion planning input and motion path.

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