Task allocation method and system for multiple transfer robots

Abstract

The invention relates to a task allocation method and system for multiple transfer robots. The task allocation method for the multiple transfer robots comprises the following steps: acquiring road network information; obtaining a road condition health map according to the road network information; state information of the multiple transfer robots is obtained, wherein the state information comprises tire models, endurance information and load information of the transfer robots; and carrying tasks of the multiple carrying robots are allocated according to the road condition health map and the state information. According to the task allocation method and system for the multiple transfer robots, the road condition is evaluated through the road network health map, and the transfer tasks are scheduled and allocated in combination with the state information of the transfer robots, so that the refinement degree and the intelligence degree of task allocation are improved, and the utilization efficiency of the transfer robots is improved.

Description

Technical Field

[0001] This invention relates to the field of building construction, and in particular to a method and system for task allocation of multiple handling robots. Background Technology

[0002] In the construction industry, material handling robots have been widely used in material handling, greatly improving handling efficiency, reducing costs, and enhancing construction safety. However, current task allocation methods are rather crude, mostly employing centralized scheduling systems that randomly assign tasks based solely on the robot's idle status, without considering the robot's specific circumstances. For example, different robots have different load capacities and endurance, which can easily lead to robots with insufficient load capacity malfunctioning while handling heavy objects, or robots with poor endurance stopping midway through long-distance tasks. At the same time, the impact of complex road networks on construction sites is ignored. Construction sites have diverse road conditions; wide-tire robots are needed to ensure passage on muddy sections, while narrow-tire robots have better maneuverability on flat sections. However, the existing allocation method does not select suitable robots based on these factors, making robots prone to slipping and getting stuck in poor road conditions, increasing losses and costs, and reducing handling efficiency and safety. Therefore, there is an urgent need for a task allocation method that comprehensively considers the specific circumstances of the robot and the road network to improve robot utilization efficiency. Summary of the Invention

[0003] Therefore, it is necessary to address the current problem in the construction industry where handling robots cannot be assigned tasks based on both the robot's specific situation and the road network conditions. A multi-handling robot task allocation method and system that can allocate tasks based on both the robot's condition and the road network conditions is needed.

[0004] This invention provides a method for task allocation among multiple handling robots, comprising the following steps: Obtain road network information; Obtaining a road health map based on the road network information includes at least one of the following: Obtain the slope and friction coefficient of the transport path in the road network information; The road condition health value of the transport path is calculated based on the slope and the friction coefficient. The road condition health map is obtained based on the road condition health values; Acquire status information of multiple transport robots, including robot type, tire model, range information, and load information. The robot type information includes standard transport robots and off-road transport robots. The transport tasks of multiple transport robots are allocated according to the road condition health map and the status information. For transport paths with road condition health values ​​below a preset threshold, off-road transport robots are given priority to perform the tasks. For transport paths with road condition health values ​​above or equal to the preset threshold, standard transport robots are assigned to perform the tasks.

[0005] In one embodiment, the step of obtaining the road condition health map based on the slope and the friction coefficient includes: The transport path is divided into three levels: Level 1, Level 2, and Level 3, based on the road health value in the road health map. The road health values ​​of Level 1, Level 2, and Level 3 increase sequentially.

[0006] In one embodiment, the step of allocating handling tasks to multiple handling robots based on the road condition health map and the status information includes: The tires of the transport robot are divided into a first tire model and a second tire model according to their width, and the tire width of the second tire model is greater than that of the first tire model. The appropriate tire model is selected according to the level of the transport path, and the transport robot with the second tire model is selected for the third level of transport path.

[0007] In one embodiment, the step of allocating handling tasks to multiple handling robots based on the road condition health map and the status information includes: The priority of the status information of multiple handling robots, from high to low, is as follows: battery life information, tire model, and load information.

[0008] In one embodiment, after the step of allocating handling tasks to the multiple handling robots based on the road condition health map and the status information, the method further includes: Get the priority of the tasks to be moved; Transportation tasks are assigned based on the stated priority.

[0009] In one embodiment, the step of allocating handling tasks to multiple handling robots based on the road condition health map and the status information further includes: Determine whether the transport path of the transport task can be broken down; If so, obtain the road conditions of each of the split transport paths based on the road health map; The handling tasks of multiple handling robots are allocated according to the split handling paths.

[0010] In one embodiment, after the step of allocating handling tasks to the multiple handling robots based on the road condition health map and the status information, the method further includes: Obtain the remaining battery power of the transport robot after it completes the transport task and the initial battery power when it starts the transport task; The power consumption of the handling robot is calculated based on the remaining power and the initial power. Determine whether the power consumption exceeds a preset value; If so, issue a road maintenance notification.

[0011] In one embodiment, after the step of allocating handling tasks to the multiple handling robots based on the road condition health map and the status information, the method further includes: Obtain real-time traffic information for the transport route; Determine whether the real-time traffic information of the transport route is consistent with the traffic information of the road network information; If not, update the traffic health map based on the real-time traffic information.

[0012] The present invention also provides a multi-handling robot task allocation system, comprising: The acquisition module is used to acquire road network information; A road condition health map module, connected to the acquisition module, is used to obtain a road condition health map based on road network information; The handling robot status module is used to acquire the status information of the handling robot; The task allocation module, connected to the road condition health map module and the transport robot status module, is used to allocate transport tasks to multiple transport robots based on the road condition health map and the status information.

[0013] The aforementioned task allocation method and system for multiple transport robots assesses road conditions using a road network health map and, combined with the status information of the transport robots, schedules and allocates transport tasks, thereby improving the precision and intelligence of task allocation and increasing the utilization efficiency of the transport robots. Attached Figure Description

[0014] Figure 1 This is a flowchart of a multi-handling robot task allocation method according to one embodiment; Figure 2 This is a schematic diagram of a multi-handling robot task allocation system according to one embodiment. Detailed Implementation

[0015] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0016] The multi-handling robot task allocation method and system of the present invention are applicable to the scenario of material handling at construction sites. Due to the complex road conditions at construction sites and the different states of each robot, considering both road condition information and the state information of the handling robots during task allocation can improve the utilization efficiency of the handling robots and the overall handling efficiency. The multi-handling robot task allocation method of the present invention will be described below with reference to specific embodiments.

[0017] Generally, due to the large amount of materials that need to be handled, multiple handling robots are deployed simultaneously on a construction site to meet the requirements of the construction schedule. These handling robots may be of different models or have different load capacities. The problem this invention aims to solve is how to allocate tasks among multiple handling robots in this scenario to achieve refined management of task allocation. Figure 1 As shown, an embodiment of a task allocation method for multiple handling robots, the task allocation method being executed by a server, includes the following steps: Step S10: Obtain road network information.

[0018] Road network information refers to road condition information at the construction site, including the number and location of roads within the site, and the start and end points, length, width, slope, and coefficient of friction for each road. The start and end points, length, width, and slope of each road can be obtained from design drawings during the engineering planning phase and from a BIM (Building Information Modeling) system. The coefficient of friction reflects the smoothness of the road surface and the resistance to the wheels of the transport robot, and can be obtained using a vehicle-mounted laser surface leveling instrument or a vision camera.

[0019] Step S20: Obtain a road condition health map based on road network information.

[0020] Once the road condition information of each road within the construction site is obtained, the road condition health map of each road can be obtained by extracting the road condition information.

[0021] In this embodiment, the slope and friction coefficient of the transport path are obtained from the road network information. The road condition health value of the transport path is calculated based on the slope and friction coefficient, and a road condition health map is obtained from the road condition health value. In the road network information, the slope and friction coefficient of the travel path cause significant wear and tear on the transport robot; therefore, these are used as the main factors for assessing the health status of the road. The magnitude of the road condition health value reflects the health status of the road; a higher road condition health value indicates a more severe road condition.

[0022] As mentioned above, the slope can be obtained from design drawings or BIM models. The steeper the slope, the higher the energy consumption of the transport robot climbing the slope, and the greater the risk of slippage. In this embodiment, the percentage slope of the road is 0-10%, where a slope less than 5% is considered a gentle slope, and 5%-10% is considered a medium slope. The coefficient of friction can be obtained using a vehicle-mounted laser leveling instrument or a vision camera. Alternatively, the coefficient of friction can be manually set according to the type of road surface material. For example, the coefficient of friction for dry asphalt or concrete is set to 0.8, for wet asphalt or concrete to 0.3, for dry sand to 0.4, and for wet sand to 0.7. The lower the coefficient of friction, the higher the probability of slippage.

[0023] After calculating the road condition health value for each road based on its slope and friction coefficient, the road condition health values ​​of all roads are summarized to obtain a road condition health map. In this embodiment, the road condition health value = slope * 10 + (1 - friction coefficient). The higher the road condition health value, the more complex the road conditions of that section, and the higher the performance requirements for the handling robot. For example, road 1 is a flat dry sand road, i.e., the slope is 0 and the friction coefficient is 0.4, then the road condition health value of this road is: 0 + (1 - 0.4) = 0.6. Road 2 is a wet and slippery asphalt or concrete road surface with a slope of 6%, and the health value of this road is: 6% * 10 + (1 - 0.3) = 0.9. The road condition health value of road 2 is greater than that of road 1, indicating that the road conditions of road 2 are more complex than those of road 1. According to the above method, the road condition health value of each road can be calculated, and thus a road condition health map can be obtained. Additionally, it should be noted that each road can be divided into multiple segments. When calculating the road health value, you can either calculate the road health value for each segment separately and then use the average value as the road health value for that road, or you can calculate the road health value separately based on the actual conditions of the road, for example, if the road surface condition of a certain segment is significantly different from that of other segments.

[0024] Furthermore, in this embodiment, the step of obtaining the road condition health map based on the slope and friction coefficient further includes: Based on the road condition health values ​​in the road condition health map, the transport paths are divided into three levels: Level 1, Level 2, and Level 3, with the road condition health values ​​increasing sequentially. The wear and tear on the transport robot increases sequentially from Level 1 to Level 3. The road condition health value, calculated using slope and friction coefficient, ranges from 0.2 to 1.7. The transport paths are then divided according to these road condition health values: Level 1 has a health value range of 0.2-0.6, Level 2 0.7-1.3, and Level 3 1.4-1.7. Higher levels correspond to more complex road conditions, greater wear and tear on the transport robot, and higher performance requirements. For example, if the road condition health map indicates a transport path is at Level 3, meaning it has a slope and is prone to slipping, the server can assign a wide-tire robot to complete the transport task.

[0025] Step S30: Obtain status information of multiple handling robots, including tire model, battery life, and load information of the handling robots.

[0026] In construction sites, to complete material handling tasks more efficiently and quickly, multiple handling robots are usually deployed to handle different paths and types of materials. The status information of the handling robots can be obtained from the manufacturer at the time of manufacture, such as tire width, range, and maximum load capacity. Among these, a wider tire provides a larger contact area with the ground and better anti-slip capabilities.

[0027] Step S40: Assign handling tasks to multiple handling robots based on road health map and status information.

[0028] The road condition health map reveals the road conditions of each road, allowing for the assignment of different transport tasks to corresponding robots based on these conditions. Taking transport task A as an example, this task requires transporting blocks from points a and b to the construction site at point c. There are paths 1 and 2 from point a to point c, and paths 3 and 4 from point b to point c. The transport robots are R1, R2, R3, and R4, all of which are fully charged. R1 and R2 have narrow tires, while R3 and R4 have wide tires. The server first obtains the road condition health values ​​for paths 1-4, which are 0.2, 1.0, 0.6, and 1.4 respectively. At this point, transport robots R3 and R4 can be assigned to paths 2 and 4 to perform transport tasks, while transport robots R1 and R2 can be assigned to paths 1 and 3 to perform transport tasks.

[0029] The aforementioned multi-robot task allocation method quantifies the road network conditions within the construction site when allocating tasks, and combines these conditions with the status of the transport robots. This maximizes the utilization of the transport robots' carrying capacity and improves transport efficiency.

[0030] As an example, a road health map is obtained based on the road network information; the status information of multiple transport robots is obtained, including the type of transport robot, tire model, range information and load information. The types are divided into standard robots and off-road robots. Standard robots are suitable for transporting general goods, with high transport efficiency but poor passability. On roads with poor health values, the robots will experience accelerated wear and tear. Off-road robots have a slightly slower travel speed but are suitable for roads with poor health values ​​and extremely poor road conditions. The transport tasks of the multiple transport robots are allocated according to the road condition health map and the status information. For transport paths where the road condition health value is lower than a preset threshold, off-road robots are given priority to perform the tasks. For transport paths where the road condition health value is higher than or equal to the preset threshold, standard robots are assigned to perform the tasks.

[0031] In this embodiment, the step of allocating handling tasks to multiple handling robots based on the road condition health map and the status information includes: The tires of the handling robot are divided into two types according to their width: the first tire type and the second tire type. The tire width of the second tire type is greater than that of the first tire type. Select the appropriate tire model according to the level of the transport path; for the third level of transport path, select the transport robot with the second tire model.

[0032] As mentioned above, transport paths can be categorized into different levels based on road health values. Similarly, transport robots can also be categorized into different levels based on tire width. The first tire model corresponds to transport robots with narrow tires, suitable for transport paths with gentle slopes and low friction coefficients. The second tire model corresponds to transport robots with wide tires, suitable for transport paths with slopes and / or high friction coefficients.

[0033] Furthermore, when allocating transport tasks, the server prioritizes the status information of multiple transport robots. In this embodiment, the priority of the status information of multiple transport robots, from highest to lowest, is: battery life, tire model, and load information. That is, when allocating tasks, the server prioritizes whether the transport robot's battery life is sufficient to complete the transport task. For example, if the current battery life of a transport robot is less than 30% of its full battery life, the server will exclude that transport robot from the current transport task and issue a charging reminder. When the battery life of all robots meets the requirements of the transport task, the server will prioritize the tire model of the transport robot. For example, if the road condition health value of a certain transport path is at the first level, and multiple transport robots can perform the transport task, the server will prioritize the transport robot with narrow tires. When the battery life and tire model are the same, the server will prioritize the transport robot with a larger load, i.e., a larger single transport volume, to shorten the transport time.

[0034] The server connects to the BIM system, which provides access to the construction material list and project progress. The order and schedule of material handling will vary depending on the construction progress. In this embodiment, after allocating handling tasks to multiple handling robots based on road condition health maps and status information, the following steps are also included: Get the priority of the tasks to be moved; Handling tasks are assigned based on priority.

[0035] As the construction progresses, the quantity, type, and location of required materials will change. The server uses the BIM system to obtain the urgency of the required materials and prioritizes the handling tasks accordingly. For example, location A has handling task 1, and location B has handling task 2. The BIM system indicates that location A is currently under construction and requires a large number of blocks, while construction at location B will begin in two days. In this case, the server sets the priority of handling task 1 to the highest and schedules a handling robot to execute handling task 1. By setting the priority of handling tasks, the smooth progress of construction can be ensured.

[0036] Furthermore, due to the complex road conditions at construction sites, some sections are relatively flat, while others become more complex due to construction or weather conditions. When a transport path involves two different types of road conditions, the transport path can be split to ensure the smooth completion of the transport task. In this embodiment, the step of allocating transport tasks to multiple transport robots based on road condition health maps and status information further includes: Determine whether the transport path of the transport task can be broken down; If so, obtain the road conditions of each transport route after splitting based on the road health map; The handling tasks of multiple handling robots are allocated according to the split handling paths.

[0037] Breaking down the transport path and having different transport robots complete the transport tasks for different sections—that is, relay transport—maximizes the efficiency of the transport robots' carrying capacity. Factors to consider when deciding whether to break down the transport path include: whether there are material storage points along the path; and whether the road conditions are generally consistent. For example, if there are multiple storage points along the path, the path can be broken down according to the location of these storage points. Additionally, the road conditions should be relatively uniform; for example, is the entire transport path a flat sandy road, or does it have a steep slope, or a muddy section, etc.?

[0038] For example, when the transport path of a transport task involves different road conditions, the transport path can be divided into path s1 and path s2. According to the road condition health map, the road condition health value of path s1 is at level one, and the road condition health value of path s2 is at level three. Based on the road condition health values ​​of paths s1 and s2, a transport robot with the first tire model can be assigned to complete the transport task of path s1, and a transport robot with the second tire model can be assigned to complete the transport task of path s2.

[0039] By breaking down the transport path, the most suitable transport robot is selected for each segment, enabling refined management of task allocation. Furthermore, segmenting the transport path allows for segmented transport, enabling robots with insufficient endurance to complete the entire transport task to perform the transport of a segment, thus improving robot utilization. Additionally, by dividing the path according to different road conditions, transport tasks in complex sections are assigned to robots with wider tires, reducing robot failure rates and helping to lower maintenance costs.

[0040] After each transport task is completed, the wear and tear on the transport robots along the transport path can be assessed to determine the wear and tear on that section of the path. Specifically, in this embodiment, after the step of allocating transport tasks to multiple transport robots based on the road health map and status information, the method further includes: Obtain the remaining battery power of the transport robot after it completes the transport task and the initial battery power when it starts the transport task; Calculate the power consumption of the handling robot based on the remaining power and the initial power. Determine if the power consumption exceeds the preset value; If so, issue a road maintenance notification.

[0041] When a transport robot begins a transport task, the server obtains the robot's initial battery level and transport load. After the task is completed, the server obtains the robot's remaining battery level. Power consumption is calculated using the initial and remaining battery levels: Power consumption = (Initial battery level - Remaining battery level) / Initial battery level. The server can obtain the average power consumption (preset value) of previous transport robots carrying the same load along the same transport path length from a database or historical records. If the power consumption exceeds the preset value, it indicates that the path conditions are causing significant wear and tear on the transport robot and require maintenance. In this case, the server can issue a road maintenance instruction to promptly repair or level the path, reducing power consumption in that section.

[0042] Because road conditions at construction sites are affected by changes in the construction site or weather, such as stones falling during sand transport or slippery roads due to rain, the road health value can change. Therefore, in this embodiment, after the step of allocating the transport tasks of the multiple transport robots according to the road health map and status information, the method further includes: Obtain real-time traffic information for the transport route; Determine whether the real-time traffic information of the transport route is consistent with the traffic information of the road network; If not, update the traffic health map based on real-time traffic information.

[0043] The transport robot can be equipped with a vision camera to collect and identify road conditions in real time during the transport task, and send the road condition information of the transport path to the server. The server updates the road network health map based on the real-time road conditions. Specifically, during the transport process, the vision camera collects road information at preset intervals and sends the information to the server. After receiving the road information, the server compares it with the road information in the database and determines whether they are consistent. If they are consistent, the road health map remains unchanged. If they are inconsistent, the server recalculates the road health value of that road segment and updates the road network health map. By updating the road network health map in real time, the server can adjust the transport robot's transport task in a timely manner according to the road conditions. In other embodiments, the road network health map can also be updated manually. For example, when staff learn that the road conditions of a certain road segment have changed, such as due to rain causing a change in the friction coefficient of a certain road segment, or due to construction needs requiring the addition of a slope to a certain road segment, the slope and / or friction coefficient of that road segment can be changed in the server to obtain an updated road network health map.

[0044] like Figure 2As shown, the multi-transport robot task allocation system includes an acquisition module, a road condition health map module, a transport robot status module, and a task allocation module. The acquisition module is used to acquire road network information. The road condition health map is connected to the acquisition module and is used to obtain the road condition health map based on the road network information. The transport robot status module is used to acquire the status information of the transport robots. The task allocation module is connected to the road condition health map module and the transport robot status module and is used to allocate transport tasks to multiple transport robots based on the road condition health map and the status information.

[0045] The aforementioned task allocation method and system for multiple transport robots assesses road conditions using a road network health map and combines this with the transport robot's status information to schedule and allocate transport tasks. This improves the precision and intelligence of task allocation, thereby increasing the utilization efficiency of the transport robots. Furthermore, the road network health map can be updated in real time, allowing the server to adjust task allocation promptly based on the updated map and robot status information. This reduces robot wear and tear and costs, while improving transport efficiency and safety.

[0046] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0047] The embodiments described above are merely illustrative of several implementations of the present invention, and while the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the invention patent. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of the present invention, and these all fall within the protection scope of the present invention. Therefore, the protection scope of this invention patent should be determined by the appended claims.

Claims

1. A method for task allocation among multiple handling robots, characterized in that, Includes the following steps: Obtain road network information; Obtaining a road health map based on the road network information includes at least one of the following: Obtain the slope and friction coefficient of the transport path in the road network information; The road condition health value of the transport path is calculated based on the slope and the friction coefficient. The road condition health map is obtained based on the road condition health values; Acquire status information of multiple transport robots, including robot type, tire model, range information, and load information. The robot type information includes standard transport robots and off-road transport robots. Based on the road condition health map and the status information, the transport tasks of the multiple transport robots are allocated. For transport paths where the road condition health value is lower than a preset threshold, off-road transport robots are given priority to perform the tasks. For transport paths where the road condition health value is higher than or equal to the preset threshold, standard transport robots are allocated to perform the tasks.

2. The multi-transport robot task allocation method according to claim 1, characterized in that, The steps for obtaining the road condition health map based on the slope and the friction coefficient include: The transport path is divided into three levels: Level 1, Level 2, and Level 3, based on the road condition health value in the road condition health map. The road condition health values ​​of Level 1, Level 2, and Level 3 increase sequentially.

3. The multi-transport robot task allocation method according to claim 2, characterized in that, The step of allocating handling tasks to multiple handling robots based on the road condition health map and the status information includes: The tires of the transport robot are divided into a first tire model and a second tire model according to their width, and the tire width of the second tire model is greater than that of the first tire model. The appropriate tire model is selected according to the level of the transport path, and the transport robot with the second tire model is selected for the third level of transport path.

4. The task allocation method for multiple handling robots according to claim 1, characterized in that, The step of allocating handling tasks to multiple handling robots based on the road condition health map and the status information includes: The priority of the status information of multiple handling robots, from high to low, is as follows: battery life information, tire model, and load information.

5. The multi-transport robot task allocation method according to claim 1, characterized in that, After the step of allocating handling tasks to multiple handling robots based on the road condition health map and the status information, the method further includes: Get the priority of the tasks to be moved; Transportation tasks are assigned based on the stated priority.

6. The multi-transport robot task allocation method according to claim 1, characterized in that, The step of allocating handling tasks to multiple handling robots based on the road condition health map and the status information further includes: Determine whether the transport path of the transport task can be broken down; If so, obtain the road conditions of each of the split transport paths based on the road health map; The handling tasks of multiple handling robots are allocated according to the split handling paths.

7. The multi-transport robot task allocation method according to claim 1, characterized in that, After the step of allocating handling tasks to multiple handling robots based on the road condition health map and the status information, the method further includes: Obtain the remaining battery power of the transport robot after it completes the transport task and the initial battery power when it starts the transport task; The power consumption of the handling robot is calculated based on the remaining power and the initial power. Determine whether the power consumption exceeds a preset value; If so, issue a road maintenance notification.

8. The multi-transport robot task allocation method according to claim 1, characterized in that, After the step of allocating handling tasks to multiple handling robots based on the road condition health map and the status information, the method further includes: Obtain real-time traffic information for the transport route; Determine whether the real-time traffic information of the transport route is consistent with the traffic information of the road network information; If not, update the traffic health map based on the real-time traffic information.

9. A task allocation system for multiple handling robots, characterized in that, include: The acquisition module is used to acquire road network information; A road condition health map module, connected to the acquisition module, is used to obtain a road condition health map based on road network information; The transport robot status module is used to acquire the status information of the transport robot. The status information includes the type of transport robot, tire model, range information, and load information. The type information of the transport robot includes standard transport robot and off-road transport robot. The task allocation module, connected to the road condition health map module and the transport robot status module, is used to allocate transport tasks to multiple transport robots according to the road condition health map and the status information. Specifically, for transport paths where the road condition health value is lower than a preset threshold, off-road transport robots are given priority to perform the tasks, while for transport paths where the road condition health value is higher than or equal to the preset threshold, standard transport robots are assigned to perform the tasks.

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