A tower crane group collaborative operation scheduling and optimization system

Abstract

The present invention provides a collaborative operation scheduling and optimization system for a group of tower cranes, including a task dynamic allocation module, a conflict perception path planning module, and a collaborative scheduling module. Based on the task requirements at the construction site, tasks are dynamically allocated to the tower cranes, and the cost of path conflict prediction is calculated; then, according to the task allocation results, the movement paths of the tower cranes are generated in real time, and the position conflicts and time overlaps between the tower cranes are dynamically avoided with the spatio-temporal grid as a constraint; finally, the status of the tower cranes and environmental changes are monitored in real time through sensors, and the priorities of task allocation and the parameters of path planning are dynamically adjusted to form a global collaborative optimization model. The global collaborative optimization model integrates task allocation, path planning, and real-time scheduling and is achieved through joint optimization. This system can effectively solve the problems of task delays, resource waste, and safety hazards caused by insufficient management in the collaborative operation of a group of tower cranes, and improve the collaboration and flexibility of the operation of the group of tower cranes.

Description

Technical Field

[0001] The present invention relates to the technical field of tower crane management, and specifically to a collaborative operation scheduling and optimization system for a group of tower cranes. Background Art

[0002] With the continuous expansion of the building scale and the increase in construction complexity, multiple tower cranes are often required to work together at the construction site to complete tasks such as the hoisting, transportation, and installation of materials.

[0003] Although the existing tower crane scheduling and management systems can, to a certain extent, achieve task allocation and path planning, there are still some technical deficiencies. The existing tower crane systems are difficult to cope with the dynamic changes at the construction site, resulting in task delays and resource waste. They lack dynamic consideration of the movement speed and load of the tower cranes and are difficult to effectively quantify the conflict risk, leading to frequent path conflicts between tower cranes. These technical deficiencies limit the efficiency and safety of the collaborative operation of the tower crane group. Summary of the Invention

[0004] (I) Technical Problems to be Solved

[0005] In view of the deficiencies of the prior art, the present invention provides a collaborative operation scheduling and optimization system for a group of tower cranes, which solves the problems of task delays, resource waste, and safety hazards caused by insufficient management in the collaborative operation of the tower crane group.

[0006] (II) Technical Solutions

[0007] To achieve the above objectives, the present invention is realized through the following technical solutions: A collaborative operation scheduling and optimization system for a group of tower cranes, comprising:

[0008] A task dynamic allocation module: Based on the task requirements at the construction site, including the starting point, ending point, priority, and time window, the task is dynamically allocated to the tower crane, and the path conflict prediction cost is calculated;

[0009] A conflict-aware path planning module: According to the task allocation result, the movement path of the tower crane is generated in real time. The path planning is constrained by a spatio-temporal grid to dynamically avoid position conflicts and time overlaps between tower cranes;

[0010] A collaborative scheduling module: The status of the tower crane and environmental changes are monitored in real time through sensors, and the priority of task allocation and the parameters of path planning are dynamically adjusted to form a global collaborative optimization model;

[0011] Among them, the global collaborative optimization model integrates task allocation, path planning, and real-time scheduling, and is realized through

[0012] through joint optimization, where is the task execution time cost; is the actual task completion time. is the deadline; is the predicted cost of path conflict between tower crane m and tower crane n.

[0013] The system ensures the collaborative optimization of task allocation, path planning, and real-time scheduling by minimizing the task execution time cost, task delay cost, and path conflict prediction cost; in the global collaborative optimization model, the adjustment rules for the dynamic weight coefficients α, β, γ in the global collaborative optimization model are as follows: when the task delay rate exceeds 15%, increase the value of β; among them, the task delay rate = (the number of delayed tasks / the total number of tasks) × 100%, and the number of delayed tasks is the number of tasks whose actual completion time exceeds the deadline; the total number of tasks refers to all the assigned tasks within the statistical time period; when the distance between tower cranes is lower than 80% of the safety threshold, increase the value of γ. For example, if the safety threshold is set to 5 meters, when the distance between tower cranes is lower than 4 meters, that is, 80% of 5 meters, the system will trigger an adjustment to increase the value of γ to enhance the intensity of conflict avoidance; the adjustment of α is optimized online by calculating the priority of tower crane tasks.

[0014] In the system, tower crane tasks are reasonably allocated. The system calculates the priority of each task according to the urgency, deadline, and task type weight of the task. The calculation of the priority takes into account the urgency of the task, the remaining time, and the importance of the task type; the initial priority is calculated from the task tightness, deadline d i and the task type weight, where w1, w2, w3 are the weights preset according to the importance of the initial task, is the current time; the setting of these weights is based on the nature and importance of the task. For example, for the critical path tasks in construction, the weight of task urgency will be higher, while for non-critical path tasks, the weight of the deadline will be higher; when a sudden task or environmental interference is detected, increase the priority, where Δp is the priority increment, and p emr is the emergency task threshold; for example, when a sudden task or environmental interference is detected, Δp is set according to the task urgency and the severity of the environmental interference. If the task urgency is high, such as involving construction safety or critical path tasks, Δp is set to 0.5 - 1.0; if the urgency is medium, Δp is set to 0.3 - 0.5; if the urgency is low, Δp is set to 0.1 - 0.3; at the same time, when the environmental interference is severe, such as bad weather or major equipment failures, Δp is increased by 0.4 - 0.6 on the original basis; if the interference is general, it is increased by 0.2 - 0.4; if the interference is minor, it is increased by 0.1 or less; after the priority is increased, trigger the local re-optimization of the conflict-aware path planning module, freeze the space-time grid occupancy status of low-priority tasks, and release the frozen grid resources, which are preferentially allocated to the emergency task path.

[0015] The conflict-aware path planning module divides the construction site into spatio-temporal grids with a horizontal resolution of no more than 1 meter and a temporal resolution of no more than 10 seconds, enabling it to precisely capture the movement trajectory and temporal changes of the tower crane, providing detailed spatio-temporal constraints for path planning. The spatio-temporal grid discretizes the space and time of the construction site into grid cells, which are used to accurately describe the movement trajectory and temporal changes of the tower crane. The calculation of the grid size is based on the maximum speed and minimum safety distance of the tower crane, ensuring that the movement range of the tower crane within adjacent time windows does not exceed the grid boundary. For example, if the maximum speed of the tower crane is 5 meters per second and the minimum safety distance is 2 meters, then the horizontal size of the grid will be set to no more than 5 meters, and the temporal size will be set to no more than 10 seconds, ensuring that the movement of the tower crane within any time window does not exceed the grid boundary. When planning the path of the tower crane, the path is discretized into a sequence of spatio-temporal grids. Each grid is automatically marked as occupied when it is occupied by the tower crane, and other tower cranes must avoid the occupied grids when planning their paths, thus achieving dynamic avoidance of position conflicts and temporal overlaps between tower cranes. For example, if tower crane A occupies a spatio-temporal grid within a certain time window, tower crane B will automatically avoid this grid and select other available grids for path planning.

[0016] When a sudden obstacle is detected, the system freezes the affected grids and makes local adjustments to the path segments associated with these grids. For example, if a transport vehicle suddenly appears at the construction site, the system will immediately freeze the spatio-temporal grids at the location of the transport vehicle and make local adjustments to the tower crane paths passing through these grids, such as re-planning the path or adjusting the movement speed, to ensure that the tower crane can safely bypass the obstacle. At the same time, the unaffected path segments will remain unchanged and continue to be executed according to the original plan.

[0017] During each task assignment, potential paths are pre-generated and the conflict probability is calculated, taking the path conflict risk as a task assignment cost item. The system quantifies the conflict risk between tower cranes based on factors such as the movement speed, load factor, real-time distance, and path time overlap of the tower cranes. For example, if the real-time speeds of two tower cranes m and n are and , the load factors are and , the real-time distance is , the path time overlap is , and the safety time threshold is , then the path conflict risk Expressed as a function of these factors; the task assignment result will be optimized through a global collaborative optimization model, taking into account factors such as the task execution time cost, the actual task completion time, the deadline, and the cost of predicting path conflicts between tower cranes; the dynamic adjustment rule of the conflict risk threshold is that when the average load of the tower crane exceeds 70% of the rated value, the system will reduce the conflict risk threshold to enhance the conflict avoidance intensity and ensure the safe operation of the tower crane under high load conditions; for example, if the rated load of the tower crane is 10 tons and the current average load is 7 tons, the system will reduce the conflict risk threshold from the original 0.5 to 0.3 to improve the sensitivity of conflict avoidance; when the task delay rate exceeds 20%, the system increases the conflict risk threshold to prioritize the task completion rate; for example, if the task delay rate reaches 25%, the system will increase the conflict risk threshold from the original 0.5 to 0.7 to reduce the interference of conflict avoidance on task completion.

[0018] (III) Beneficial effects

[0019] The present invention provides a collaborative operation scheduling and optimization system for a group of tower cranes, having the following beneficial effects:

[0020] 1. The dynamic allocation method of the present invention can reasonably arrange the tasks of the tower cranes according to the urgency, deadline, and type weight of the tasks, avoiding the problems of tower crane idleness or overload caused by unreasonable task allocation in the traditional scheduling method, and further improving the operation efficiency of the tower cranes.

[0021] 2. The present invention divides the construction site into space-time grids, and by calculating the movement range of the tower crane within adjacent time windows, it ensures that the movement of the tower crane does not exceed the grid boundary, thereby effectively avoiding collisions between tower cranes, further reducing the safety risk of tower crane operation and reducing the loss of maintenance.

[0022] 3. The global collaborative optimization model of the present invention can comprehensively consider the task execution time cost, the actual task completion time, the deadline, and the cost of predicting path conflicts between tower cranes, realizing the global optimization of the operation of the group of tower cranes, and further enhancing the coordination and flexibility of the operation of the group of tower cranes. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] Figure 1 It is a schematic flow chart of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0024] The technical solutions in the embodiments of the present invention will be clearly and completely described below. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments; based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0025] The present invention provides a collaborative operation scheduling and optimization system for tower cranes, aiming to solve the problems of task delay, resource waste and safety hazards caused by insufficient management during the collaborative operation of multiple tower cranes at the construction site.

[0026] At the construction site, the system is first initialized according to the task requirements; assume that there are tower cranes A, B, and C at the construction site, and currently 5 tasks need to be executed, and each task contains information such as the starting point, ending point, priority, time window, etc.; the priority of the task is determined by the task urgency, deadline, and task type weight; first, the task urgency is quantified, and the system divides it into three levels: high 1.0, medium 0.7, low 0.3; for example, the urgency of task 1 is high 1.0, the deadline is 2 hours, and the task type weight is 0.8; the urgency of task 2 is medium 0.7, the deadline is 3 hours, and the task type weight is 0.5; the system calculates the initial priority of each task according to the following formula:

[0027] , where w1, w2, and w3 are the preset weights of the task urgency, deadline, and task type weight respectively, is the deadline of the task, is the current time; assume , , , the priority calculation of task 1 is as follows:

[0028]

[0029] The system dynamically assigns tasks to tower cranes according to the priority; for example, task 1 is assigned to tower crane A, task 2 is assigned to tower crane B, and task 3 is assigned to tower crane C; through the dynamic assignment method, the system reasonably arranges the tasks of tower cranes according to the urgency and deadline of the tasks, avoiding the problems of tower crane idleness or overload caused by unreasonable task assignment in the traditional scheduling method.

[0030] After the task assignment is completed, the system enters the conflict perception path planning stage; first, the system divides the construction site into spatio-temporal grids, with a horizontal resolution of no more than 1 meter and a time resolution of no more than 10 seconds; assume that the maximum speed of tower crane A is 5 meters per second and the minimum safety distance is 2 meters, and the system sets the horizontal size of the grid to 5 meters and the time size to 10 seconds to ensure that the movement range of the tower crane within adjacent time windows does not exceed the grid boundary.

[0031] The task 1 path of tower crane A is discretized into a sequence of spatio-temporal grids; for example, tower crane A occupies grid (1,1) in time window 1, grid (1,2) in time window 2, and grid (1,3) in time window 3; the system automatically marks these grids as occupied, and other tower cranes must avoid these grids when planning their paths; for example, when tower crane B is planning its path, if it detects that grid (1,2) is already occupied, it will select other available grids for path planning.

[0032] Through the division of spatio-temporal grids and path discretization, the system accurately captures the movement trajectories and time changes of tower cranes, effectively avoiding position conflicts and time overlaps between tower cranes; for example, if tower crane A occupies a spatio-temporal grid within a certain time window, tower crane B will automatically avoid this grid and select other available grids for path planning when planning its path, thus ensuring a safe distance between tower cranes.

[0033] During the task execution process, the system monitors the status of tower cranes and environmental changes in real time through sensors; assume that when tower crane A is executing task 1, a transport vehicle suddenly appears at the construction site, the system immediately freezes the spatio-temporal grid where the transport vehicle is located, and makes a local adjustment to the path of tower crane A; for example, tower crane A originally planned to occupy grid (1,4) in time window 4, but due to the appearance of the transport vehicle, the system re-plans the path and adjusts the movement speed of tower crane A so that it occupies grid (2,4) in time window 4, bypassing the obstacle; at the same time, the system detects a sudden task 4, its urgency is high, the deadline is 1 hour, and the task type weight is 0.9; the system raises the priority of task 4 according to the following rules: , assume , , the initial priority of task 4 is 0.75, which is lower than the emergency task threshold of 0.8, and the system raises its priority to 0.95; after the priority is raised, the system triggers a local re-optimization of the conflict-aware path planning module, freezes the spatio-temporal grid occupancy status of low-priority tasks, and releases the frozen grid resources, which are preferentially allocated to the emergency task 4; through the dynamic priority adjustment mechanism, the system responds in a timely manner to sudden tasks and environmental changes, ensuring that emergency tasks are given priority; for example, if a tower crane suddenly encounters strong winds during hoisting, the system will detect this environmental interference and raise the priority of the tower crane task according to the preset rules to ensure safety and the timely completion of the task.

[0034] The system realizes the global optimization of tower crane group operation through a global collaborative optimization model, comprehensively considering the task execution time cost, the actual task completion time, the deadline, and the path conflict prediction cost between tower cranes; the optimization objective can be expressed by the following formula: where is the task execution time cost; is the actual task completion time, is the deadline; represents the path conflict prediction cost between tower crane m and tower crane n; assume , , , the system realizes the collaborative optimization of task allocation, path planning and real-time scheduling through joint optimization; through the global collaborative optimization model, the system comprehensively considers the task execution time, task delay cost and path conflict risk to achieve the global optimization of tower crane group operation; for example, when the path conflict risk between tower crane A and tower crane B is relatively high, the system will automatically adjust the movement speed of the tower crane or reallocate tasks to reduce the conflict risk and ensure the timely completion of tasks.

[0035] In each task allocation iteration, the system pre-generates potential paths and calculates the conflict probability; the path conflict risk is calculated as follows:

[0036]

[0037] where and represent the real-time speeds of tower crane m and tower crane n respectively, and represent the load factors of tower crane m and tower crane n respectively, represents the real-time distance between tower crane m and tower crane n, represents the path time overlap, represents the safety time threshold, is a very small constant; assume the real-time speeds of tower crane A and tower crane B are 5 m / s and 4 m / s respectively, the load factors are 0.7 and 0.6 respectively, the real-time distance is 6 m, the path time overlap is 5 s, and the safety time threshold is 3 s. The path conflict risk is calculated as follows:

[0038] Assume the threshold is 1.0. If the conflict risk exceeds the threshold, the system triggers an optimization operation to adjust the movement speed of tower crane A or tower crane B to reduce the path overlap time, or reallocate tasks to reduce the load of the tower crane; through the path conflict risk calculation and adjustment, the system effectively avoids collisions between tower cranes and reduces safety risks; for example, when the path conflict risk between tower crane A and tower crane B is relatively high, the system will automatically adjust the movement speed of the tower crane or reallocate tasks to ensure the safe distance between tower cranes.

[0039] The system dynamically adjusts the weight coefficients α, β, and γ in the global collaborative optimization model according to the task delay rate and the distance between tower cranes. Assuming that the task delay rate exceeds 15%, the system increases the value of β to enhance the penalty for task delays. Assuming that the safety threshold is 5 meters and 80% of it is 4 meters, when the distance between tower cranes is lower than 80% of the safety threshold, the system increases the value of γ to enhance the conflict avoidance intensity. For example, if the real-time distance between tower crane A and tower crane B is 3.5 meters, the system increases the value of γ from 0.2 to 0.3 to enhance the sensitivity of conflict avoidance. Through the adjustment of dynamic weight coefficients, the system flexibly adjusts the optimization objectives according to the real-time situation to ensure the timely completion of tasks and avoid conflicts between tower cranes. For example, when the load of a tower crane is high, the system automatically reduces the conflict risk threshold to enhance the intensity of conflict avoidance and ensure the safe operation of the tower crane under high-load conditions.

[0040] Through the collaborative operation scheduling and optimization of the tower crane group, Task 1, Task 2, and Task 3 are completed on time, and the sudden Task 4 is also processed in a timely manner after the priority is improved. The path planning of tower crane A, tower crane B, and tower crane C avoids position conflicts and time overlaps. The advantages of this system in improving the operation efficiency of the tower crane group and reducing safety risks. Through dynamic task allocation, conflict-aware path planning, and global collaborative optimization, the system can effectively respond to the dynamic changes at the construction site, ensure the timely completion of tasks and avoid conflicts between tower cranes, and significantly improve the collaboration and flexibility of the tower crane group operation.

[0041] Although the embodiments of the present invention have been shown and described, it will be understood by those of ordinary skill in the art that various changes, modifications, substitutions, and variations can be made to these embodiments without departing from the principles and spirit of the present invention. The scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A tower crane group collaborative operation scheduling and optimization system, characterized in that: include: Task dynamic allocation module: Based on the task requirements of the construction site, including the starting point, end point, priority, and time window, tasks are dynamically allocated to the tower crane, and the path conflict prediction cost is embedded; Conflict-aware path planning module: Generates crane motion paths in real time based on task allocation results. Path planning uses the space-time grid as a constraint to dynamically avoid position conflicts and time overlaps between cranes. Collaborative scheduling module: uses sensors to monitor the crane status and environmental changes in real time, dynamically adjusts the priority of task allocation and path planning parameters, and forms a global collaborative optimization model; Among them, the global collaborative optimization model integrates task allocation, path planning and real-time scheduling. Joint optimization is achieved, where The time cost of task execution; is the actual completion time of the task, is the deadline; is the path conflict prediction cost between crane m and crane n, α, β, γ are dynamic weight coefficients; C conflict (m,n) quantifies the probability of path overlap between crane m and crane n in the space-time grid, and its calculation method is: , where v m ,v n is the real-time speed of crane m and crane n, L m ,L n is the load factor of crane m and crane n. The larger the load, the higher the conflict risk. mn is the real-time distance between crane m and crane n, t overlap is the path time overlap, t safe is the safety time threshold, is a very small constant; when the path conflict risk is detected to exceed the threshold, the optimization operation is triggered, including adjusting the movement speed of crane m or crane n to reduce the path overlap time t overlap , redistribute tasks to reduce the crane load L m or L n , and insert waiting time windows to ensure the distance d between cranes mn Always greater than the safety threshold d safe .

2. A tower crane group collaborative operation scheduling and optimization system according to claim 1, characterized in that: The adjustment rules of the dynamic weight coefficients α, β, and γ in the global collaborative optimization model are as follows: when the task delay rate exceeds 15%, the β value is increased; when the distance between tower cranes is lower than 80% of the safety threshold, the γ value is increased; the adjustment of α is optimized online by calculating the priority of the tower crane task.

3. A tower crane group collaborative operation scheduling and optimization system according to claim 2, characterized in that: The priority calculation method of the tower crane task is as follows: The initial priority is determined by the task urgency, deadline i and task type weight calculation, ,in is the priority, w1, w2, w3 are the weights preset according to the importance of the initial task, is the current time; when an emergency task or environmental interference is detected, the priority is increased according to the following rules , where Δp is the priority increment, p emr is the emergency task threshold; after the priority is increased, the local re-optimization of the conflict-aware path planning module is triggered.

4. A tower crane group collaborative operation scheduling and optimization system according to claim 3, characterized in that: In the conflict-aware path planning module, the construction site area is divided into space-time grids with a horizontal resolution of ≤1 meter and a time resolution of ≤10 seconds. The grid size is calculated based on the maximum speed and minimum safety distance of the tower crane so that the movement range of the tower crane in adjacent time windows does not exceed the grid boundary. When planning the tower crane path, the path is discretized into a sequence of space-time grids, and the grid is automatically marked as occupied when it is occupied. The occupied grids need to be avoided when planning the paths of other tower cranes. When a sudden obstacle is detected, the affected grids are frozen and the path segments associated with the affected grids are locally adjusted to retain the unaffected path segments.

5. The tower crane group collaborative operation scheduling and optimization system according to claim 1 is characterized by: In the collaborative scheduling module, in each task allocation iteration, potential paths are pre-generated and conflict probabilities are calculated, and path conflict risks are used as task allocation cost items; If the conflict risk exceeds the threshold, the current allocation plan will be rejected and solved again. The task allocation result is optimized through the global collaborative optimization model. The dynamic adjustment rule of the conflict risk threshold is as follows: when the average tower crane load exceeds 70% of the rated value, the conflict risk threshold is lowered to enhance the conflict avoidance intensity; when the task delay rate exceeds 20%, the conflict risk threshold is increased to prioritize the task completion rate.

6. A tower crane group collaborative operation scheduling and optimization system according to claim 1, characterized in that: In the collaborative scheduling module, when it is detected that a single tower crane deviates from the planned path, only the associated variables of the tower crane are frozen and the global collaborative optimization model is locally updated; when the priority of the burst task exceeds the threshold, the low-priority task is forcibly interrupted and the path resources are released.

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