Building logistics robot carrying path determination method and device

Abstract

This invention relates to the field of smart construction site logistics management technology, specifically to a method and apparatus for determining the handling path of a construction logistics robot. The method and apparatus first acquire basic metadata of the construction material handling task, then standardize and decompose the complete handling task into a continuous sequence of micro-segments without a globally preset route. A decentralized distributed relay node network covering fixed relay anchor points and ubiquitous displacement units on the construction site is constructed, and a real-time node status broadcasting mechanism is established. An optimal execution node is matched for each micro-segment task using a multi-dimensional adaptability calculation model, completing standardized connection and single-segment task verification. Dynamic fault tolerance and path adaptive adjustment are implemented for abnormal working conditions, and convergence verification controls the relay transmission of the task to the target unloading point to achieve task closure. This invention eliminates the need for a pre-set global complete path, adapts to complex working conditions on construction sites, improves on-site transportation capacity and channel resource utilization, and reduces material handling costs.

Description

Technical Field

[0001] This invention relates to the field of smart construction site logistics management technology, and more specifically, to a method and apparatus for determining the handling path of a construction logistics robot. Background Technology

[0002] Smart construction sites are the core development direction for the digital and intelligent transformation of the construction industry. Automated material handling at construction sites is the core link in the construction of smart construction sites, which directly determines the efficiency of construction progress and the level of on-site safety management. Path planning technology is the core supporting technology for realizing automated material handling.

[0003] Existing material handling path planning technologies generally adopt a global path pre-planning model, requiring the pre-planning of a complete handling route from the loading point to the unloading point. However, construction sites have inherent characteristics such as temporary passageway blockages, dynamic changes in working conditions, and random distribution of obstacles. The pre-planned complete path is prone to partial failure, requiring frequent re-execution of the global path search. This not only significantly increases the computational and communication load but also easily leads to handling task interruptions. Furthermore, it cannot adapt to the scattered passageway gaps on site, resulting in low utilization of passageway resources. At the same time, existing solutions mostly rely on dedicated logistics robots to perform the entire handling task, failing to reuse existing equipment with displacement capabilities on the construction site, such as construction hoists, tower crane horizontal trolleys, and fixed-route engineering vehicles. A large amount of idle transportation resources cannot be effectively utilized, and the configuration and maintenance costs of dedicated robots are high, making it difficult to adapt to the material handling needs of the entire construction site scenario.

[0004] To address the numerous shortcomings of the existing technologies, this invention proposes a method and apparatus for determining the handling path of a logistics robot used in construction. Summary of the Invention

[0005] To address the shortcomings of existing technologies, the present invention aims to provide a method and apparatus for determining the handling path of a logistics robot used in construction.

[0006] To achieve the above objectives, the present invention provides the following technical solution: A method for determining the handling path of a construction logistics robot specifically includes the following steps: S1. Obtain the basic metadata of a single building material handling task, perform standardized micro-segment decomposition and task metadata encapsulation on the single complete handling task, and generate a continuous micro-segment task sequence without a global unloading endpoint and a preset complete route. Each micro-segment task retains only the core constraint parameters required for single-segment execution. S2. Construct a decentralized distributed relay node network covering all ubiquitous displacement units and fixed spatial relay anchor points on the construction site, establish a real-time status broadcasting mechanism for all network nodes, and synchronously update the status data of adjacent nodes stored locally by each node. S3. When the micro-segment task reaches the corresponding relay anchor point, based on the multi-dimensional adaptability calculation model, a set of candidate execution nodes that meet the constraints is selected for the micro-segment task, the optimal execution node is matched, and the standardized connection of the material carrier and the closed-loop verification of the single micro-segment task are completed. S4. During the entire execution cycle of the task, in response to abnormal working conditions at the construction site, perform dynamic fault-tolerant processing of micro-segment tasks and adaptive adjustment of relay paths. S5. After each micro-segment task completes the relay matching, perform task convergence verification, control the task to continuously relay to the target unloading point until the task reaches the target area and completes the closed-loop execution of the entire handling task.

[0007] The present invention also provides a device for determining the handling path of a logistics robot for construction, including a task decomposition and encapsulation module, a distributed node network construction module, a micro-segment task relay matching module, a dynamic fault-tolerant adjustment module, and a convergence verification and closed-loop execution module. The task decomposition and encapsulation module acquires the basic metadata of a single building material handling task, and completes the standardized micro-segment decomposition and task metadata encapsulation of a single complete handling task; the distributed node network construction module constructs a decentralized distributed relay node network covering all nodes on the construction site, and establishes a real-time node status broadcasting mechanism; the micro-segment task relay matching module filters and matches the optimal execution node for micro-segment tasks arriving at the relay anchor point, and completes the closed-loop verification of a single micro-segment task; the dynamic fault tolerance adjustment module performs dynamic fault tolerance processing of micro-segment tasks and adaptive adjustment of relay paths for abnormal working conditions on the construction site; the convergence verification and closed-loop execution module verifies the convergence status of micro-segment tasks, controls the continuous relay transmission of tasks to the target unloading point, and completes the closed-loop execution of the entire handling task.

[0008] Furthermore, the standardization of micro-segment decomposition and task metadata encapsulation for a single complete transportation task specifically involves: dynamically calculating the micro-segment decomposition granularity based on the road network topology and inherent forced transfer node distribution at the construction site; arranging a continuous sequence of micro-segment tasks with the inherent forced transfer nodes as the core anchor points; assigning a unique task identifier to each micro-segment task that is bound to a single complete transportation task; and issuing the first micro-segment task to the starting relay node after completing the standardized metadata encapsulation.

[0009] Furthermore, each micro-segment task generated is only bound to the current relay anchor point, the optional set of relay anchor points, and the single-segment passage constraint parameters.

[0010] Furthermore, the construction of a decentralized distributed relay node network specifically involves: assigning a unique node identifier to each node connected to the network and binding it with corresponding basic attribute data; each node broadcasts real-time status data only to its neighboring nodes within its communication range at a fixed frequency; after receiving the broadcast data, the neighboring nodes synchronously update their locally stored neighboring node status tables, without needing to synchronize node status data to the entire network.

[0011] Furthermore, the nodes connected to the distributed relay node network include fixed spatial relay anchor point nodes and ubiquitous displacement unit nodes. For ubiquitous displacement unit nodes, their displacement trajectory and start and end node displacement plans are updated in real time. When the displacement plan changes, the changed status data is immediately sent to adjacent nodes.

[0012] Furthermore, the process of matching the optimal execution node for the micro-segment task specifically involves: selecting a set of candidate execution nodes that meet the single-segment passage constraints of the micro-segment task from the adjacent node status table of the current relay anchor point; calculating the comprehensive fit of each candidate node based on a multi-dimensional fit calculation model; and selecting the node with the highest comprehensive fit as the execution node of the current micro-segment task.

[0013] Furthermore, the method for calculating the comprehensive adaptability of the multi-dimensional adaptability calculation model is as follows: select the idle capacity status of the candidate execution node, the communication distance with the current relay anchor point, and the passage constraint matching degree as the core adaptability dimensions, assign corresponding weights to each adaptability dimension, standardize the actual values ​​of each dimension, and calculate the comprehensive adaptability of each candidate execution node by weighted summation.

[0014] Furthermore, the dynamic fault-tolerant processing and adaptive adjustment of the relay path for executing micro-segment tasks are as follows: when the executing node cannot complete the current micro-segment task, the micro-segment task is returned to the corresponding relay anchor node, and the candidate node screening and matching process is re-executed. At the same time, the micro-segment splitting granularity is dynamically adjusted according to the changes in the road network topology and channel status at the construction site.

[0015] Furthermore, the convergence verification of the execution task is specifically as follows: after each micro-segment task completes the relay matching, the convergence coefficient of the current micro-segment task is calculated, the convergence status of the task towards the target unloading point is verified, the task is controlled to continue relaying towards the target unloading point, and when the task arrives at the target area, unloading and full task closed-loop verification are completed, and the transportation resources of the corresponding node are released.

[0016] Compared with the prior art, the present invention has the following beneficial effects: 1. This invention abandons the traditional approach of pre-planning the entire global path, breaking down a single complete material handling task into a standardized sequence of micro-segments without a pre-defined global unloading endpoint route. Each micro-segment task retains only the core constraint parameters required for single-segment execution. This technical solution eliminates the need to pre-lock the complete handling route, adapting to the dynamic changes in construction site access and complex and varied working conditions. It avoids the problem of global path replanning due to local path failure, significantly reducing the probability of task interruption. Simultaneously, it can flexibly match short-term gaps in scattered passageways on the construction site, achieving dynamic and efficient utilization of passageway resources and significantly improving the adaptability of the material handling solution to on-site working conditions. 2. This invention breaks away from the traditional model of dedicated logistics robots being bound to the entire process for execution. It constructs a decentralized distributed relay node network covering all ubiquitous displacement units on the construction site, expanding the execution subject of micro-segment tasks from dedicated logistics robots to all ubiquitous displacement units on the construction site with controllable displacement capabilities, including construction hoists, tower crane horizontal trolleys, and engineering vehicles traveling on fixed routes. This solution can fully reuse the existing displacement equipment capacity resources on the construction site without the need to configure a large number of dedicated logistics robots, significantly reducing the equipment configuration and maintenance costs for material handling. At the same time, it realizes the efficient revitalization of idle capacity on site and improves the comprehensive utilization rate of capacity resources across the entire scenario. Attached Figure Description

[0017] Figure 1 A flowchart of a method for determining the handling path of a logistics robot used in construction. Figure 2 This is a flowchart illustrating the implementation of step S3 of the present invention; Figure 3 This is a structural block diagram of a device for determining the handling path of a logistics robot used in construction. Detailed Implementation

[0018] Example 1, refer to Figure 1 The method for determining the handling path of a construction logistics robot according to this embodiment specifically includes the following steps: S1. Standardized micro-segment decomposition and task metadata encapsulation for a single transport task.

[0019] A single complete material handling task is broken down into several standardized micro-segment relay task units, and the task metadata is uniformly encapsulated. The decomposed micro-segment tasks are not associated with the complete route preset of the global unloading endpoint, but only retain the core constraint parameters required for single-segment execution, providing unified and standardized data input for subsequent distributed relay matching.

[0020] S11. Obtain basic task metadata: Basic data for a single material handling task is obtained from the smart construction site management platform and the construction progress management system. The data acquisition supports both manual entry and automatic system synchronization, specifically including: 1. Basic material attributes: including material type, total weight, outer contour dimensions, and fixing method; among which, the material type can be preset to several standard categories such as concrete components, steel bars, formwork, and electromechanical equipment; the total weight is obtained through the bill of materials or weighing equipment; and the outer contour dimensions are extracted from the BIM model or measured manually. 2. Semantic identifier for target process: A semantic string or code used to uniquely represent the target process link corresponding to the material. Its value is derived from the construction schedule and is bound to each process node. The specific implementation method is as follows: all procedures at the construction site are preset as a standardized terminology library, such as the first-floor column concrete pouring, the second-floor wall panel installation, and the roof steel structure hoisting. The procedure identifiers contained in the task data must be completely matched with the standard terms in the terminology library. These identifiers are used to guide the ubiquitous displacement unit to accurately connect the materials to the corresponding work surface unloading point. 3. Spatial coordinates of the target unloading point: This is the three-dimensional spatial position vector of the target unloading point in a unified coordinate system at the construction site. The method of obtaining it is as follows: based on the BIM model of the construction site, it is obtained by reverse query through the semantic identifier of the target process or by manually selecting and calibrating it on the map of the management platform; the coordinate system can be the independent coordinate system of the construction site, or preferably the national geodetic coordinate system, which needs to be uniformly set during system initialization; 4. Construction period time window constraints: including the earliest allowed start time and the latest required completion time, to ensure the time matching of material supply and construction progress; 5. Load Safety Constraints: Load safety limits that must be met to perform this handling task; specifically including: total material weight threshold and special safety factor determined by the material type; for example, for precision equipment materials, an additional horizontal swaying acceleration threshold must be set; for fragile building materials, a vertical impact load threshold must be set; the maximum load capacity of the ubiquitous displacement unit must be greater than or equal to the product of the total material weight and the special safety factor; 6. Traffic Risk Level Constraints: This is for the quantitative assessment of potential risk factors in the material handling path. Specific assessment dimensions include: aisle width risk, ground flatness risk, obstacle distribution risk, and personnel activity density risk. The risk values ​​for each dimension are obtained through on-site image recognition, sensor data collection, or manual pre-set scoring, and are combined to form a continuous risk level value from 0 to 1. The maximum allowable risk threshold for this handling is clearly specified in the task parameters, and the ubiquitous displacement unit must not exceed this threshold when selecting the path. S12. Dynamically calculate the micro-segment splitting granularity: Based on the road network topology and inherent transfer node distribution at the construction site, the micro-segment task is dynamically decomposed. The granularity of the micro-segment decomposition is determined by a dynamically adjustable model, and the calculation formula is as follows: ; In the formula: This is the maximum path length of a single micro-segment task, in meters. Its value is determined based on the maximum length of a single continuous passage at the construction site, and the upper limit can be set through the system configuration interface. In some embodiments, it is set to no more than 50 meters. The maximum length of a single continuous passage without mandatory relocation nodes at the construction site, in meters; determined by extracting data from the construction site BIM model and road network topology data, the extraction rule being the maximum straight-line distance between two adjacent mandatory relocation nodes; This is the straight-line distance between the loading point and the unloading point, in meters; it is determined by calculation using the spatial coordinates of the loading point and the unloading point. The total number of inherent forced transfer nodes between the loading point and the unloading point is determined by extracting data from the BIM model and construction site layout, and its value is a positive integer; when When the value is zero, it indicates that there is no forced transfer point between the loading and unloading points. Direct value ;when Less than hour, Direct value No need for multi-segment splitting; S13. Generate a sequence of micro-segments: Based on the above granularity of breakdown, a single handling task is decomposed into a continuous sequence of micro-segments. These micro-segments are arranged continuously according to the spatial flow of material handling, with inherent forced transfer nodes as core anchor points. The endpoint anchor point of an adjacent micro-segment becomes the starting anchor point of the next micro-segment. Each micro-segment only binds three core parameters: the current relay anchor point, a set of optional relay anchor points, and single-segment access constraints. Complete route planning data for the global unloading point is not encapsulated. The current relay anchor point represents the starting spatial coordinates and process semantic identifier of the micro-segment. The set of optional relay anchor points is the set of accessible relay nodes adjacent to the current anchor point. Single-segment access constraints include the allowed passage time window for the micro-segment, maximum load limit, maximum outer contour size limit, and risk level threshold. S14. Encapsulate metadata and distribute it: Each micro-segment task undergoes standardized metadata encapsulation to generate a unique task identifier ID. This task identifier ID is bound to the number of a single complete transport task and also associated with the sequence number of the micro-segment task. A specific example of a unique task identifier ID is: MPT-20260325-001-003. The meanings of the parameters are as follows: MPT is a standardized abbreviation for Material Handling Task, used to specify the task type; 20260325 is the creation date of a single complete handling task, in the format of year-month-day (separators are omitted here to conform to standardized coding requirements); 001 is the number of the single complete handling task, using a three-digit code, which can support task quantities from 001 to 999; 003 is the sequence number of the micro-segment task under this complete task, also using a three-digit code, corresponding to the third micro-segment task after the complete task is broken down. The first micro-segment task after packaging is sent to the starting relay node corresponding to the loading point to complete the initialization process.

[0021] S2, Distributed relay node network construction and status broadcasting.

[0022] Construct a distributed, centerless relay node network covering all ubiquitous displacement units at the construction site, enabling real-time status broadcasting and data communication of all nodes, and providing globally accessible node status data for seamless relay matching of micro-segment tasks; this step is executed synchronously with the initialization process of step S1 and continues to run throughout the entire task execution cycle.

[0023] S21. Define the main body of the network nodes: The nodes connected to the distributed relay node network are identified, comprising two core node types: the first type is spatial relay anchor nodes, including fixed spatial nodes such as material storage yards, construction hoist docking points, floor passage entrances, and unloading points on work surfaces; the second type is ubiquitous displacement unit nodes, including logistics robots with controllable displacement capabilities, construction hoists, tower crane horizontal trolleys, and engineering vehicles operating on fixed routes. All nodes are equipped with wireless self-organizing network communication modules and edge computing units, enabling point-to-point data communication between adjacent nodes without the need for a central server. Among them, the wireless self-organizing network communication module adopts a wireless communication standard that supports multi-hop forwarding. The communication coverage can be adjusted by the transmission power, and the single-hop communication distance can cover the maximum spatial interval between adjacent nodes on the construction site. The minimum computing power of the edge computing unit can meet the needs of node status data processing, adaptability calculation, and adjacent node status table storage. It can complete the local calculation of micro-segment task matching without uploading to the central server.

[0024] For fixed-path ubiquitous displacement units, including construction hoists, tower crane horizontal trolleys, and engineering vehicles traveling on fixed routes, the displacement trajectory parameters are the preset fixed operating path and operating range, the available transport capacity margin is the minimum of the number of currently idle load-bearing spaces and the rated load-bearing capacity, and the passage cost coefficient is the estimated operating time required to complete the displacement of the corresponding range. S22. Assign node identifiers and attributes: Each node connected to the network is assigned a unique node identifier (ID) and bound to its basic attribute data, including node type, fixed spatial coordinates, displacement trajectory parameters, maximum load capacity, maximum compatible vehicle size, available transport capacity margin, and passage cost coefficient. The available transport capacity margin of the ubiquitous displacement unit node is the node's currently idle load capacity and the number of connectable vehicle bays. Fixed spatial coordinates are set only for fixed nodes; the coordinates of mobile nodes are updated through real-time positioning data, with the update frequency of the positioning data consistent with the node status broadcast frequency. The passage cost coefficient... This is used to quantify the combined time and energy cost required for a ubiquitous displacement unit to complete a unit displacement task. The smaller the value, the lower the overall cost of performing the task. Its calculation method varies depending on the node type. (1) For ubiquitous displacement units with fixed paths (such as construction hoists, tower crane horizontal trolleys, and fixed-route engineering vehicles), the passage cost coefficient is calculated according to the following formula: ; in, The estimated running time required to complete the current path segment, This is the baseline operating time for nodes of the same type under standard operating conditions. To complete the estimated energy consumption required for the current path segment, Baseline energy consumption; For the weighting coefficients, satisfying It can be dynamically adjusted through the system configuration interface according to the priority of efficiency and energy saving in the construction project; (2) For ubiquitous displacement units with free paths (such as logistics robots), the passage cost coefficient is dynamically calculated based on the real-time path planning results. It is the weighted sum of the estimated travel time and energy consumption per unit distance of the current planned path, and then normalized to... The interval is used as a real-time passage cost coefficient in broadcasting and matching calculations; S23. Establish a real-time status broadcast mechanism: A real-time status broadcasting mechanism for all network nodes is constructed. Each node broadcasts its real-time status data only to neighboring nodes within its communication range at a fixed frequency. The broadcast frequency can be dynamically adjusted according to the network environment at the construction site, and in some embodiments, it can be set to 1Hz~10Hz. The broadcast real-time status data includes node ID, real-time spatial coordinates, available transport capacity, real-time passage cost coefficient, current occupancy status, and start and end node displacement plans. After receiving the broadcast data, neighboring nodes synchronously update their locally stored neighbor node status tables, without needing to synchronize data to the entire network, significantly reducing network communication load. The start and end node displacement plans are used to describe the displacement task arrangements of the ubiquitous displacement unit in the current and future period. Its data structure includes at least: starting node ID, starting arrival time, ending node ID, expected ending arrival time, displacement task priority, and occupied transport capacity. For ubiquitous displacement units with fixed paths (such as construction hoists and tower crane horizontal trolleys), their displacement plans are generated dynamically by the system's preset operating shifts or by scheduling instructions; for ubiquitous displacement units with free paths (such as logistics robots), their displacement plans are dynamically determined by the target anchor point of the current micro-segment task and the real-time path planning results. The relationship between displacement plan and displacement trajectory is as follows: the displacement trajectory is a sequence of historical position points generated during the execution of the displacement plan, used to monitor the progress of task execution and to determine anomalies; the displacement plan is a prospective description of future displacement behavior, used to calculate the directional convergence and time window fit during relay matching; when the ubiquitous displacement unit is matched and takes on a new micro-segment task, its displacement plan is updated immediately, and the updated plan is broadcast to the network through adjacent nodes. The neighbor node status table stores the neighbor node's identifier ID, the latest broadcast status data, and the data update timestamp. When a node does not receive broadcast data from a neighbor node for a preset time, the node is automatically removed from the neighbor node status table. The preset time can be set through the system configuration interface. S24. Dynamically update the displacement element status: For ubiquitous displacement unit nodes, their displacement trajectories and start and end node plans are updated in real time. When the displacement plan of a node changes, the updated status data is immediately sent to adjacent nodes to ensure the real-time performance and accuracy of the adjacent node status tables, providing reliable data support for subsequent relay matching.

[0025] S3. Micro-segment task relay matching based on multi-dimensional adaptability.

[0026] like Figure 2As shown, this step enables seamless and automatic matching between micro-segment tasks and ubiquitous displacement unit nodes, completely eliminating the binding restrictions of dedicated logistics robots. Through a multi-dimensional adaptation calculation model, the optimal execution node is matched for the current micro-segment task. This step is automatically triggered when each micro-segment task reaches its corresponding relay anchor point.

[0027] S31. Filter the candidate execution node set: When a micro-segment task reaches the current relay anchor point, the anchor point node selects a set of candidate nodes from its local adjacent node status table that meet the single-segment passage constraints of the micro-segment task. The selection criteria include: the maximum carrying capacity of the candidate node is greater than or equal to the total weight of the micro-segment task's materials, the maximum compatible vehicle size is greater than or equal to the outer contour size of the material carrier, the risk level meets the safety constraints of the micro-segment task, and the available transport capacity margin is greater than or equal to 1. S32. Calculate the multi-dimensional comprehensive fit: For the selected candidate node set, a multi-dimensional fit calculation model is used to standardize the actual values ​​of each dimension, ensuring that the values ​​of each dimension are all within the range of 0 to 1. Then, the comprehensive fit between each candidate node and the current micro-segment task is calculated. The calculation formula is as follows: ; In the formula: This represents the overall fit between the candidate node and the current micro-segment task, with a value ranging from 0 to 1. A higher value indicates better fit. This is the directional convergence coefficient, ranging from 0 to 1, used to characterize the convergence degree between the displacement direction of the candidate node and the target unloading point. Its value is determined based on the spatial coordinates of the endpoint coordinates of the candidate node's real-time displacement plan and the spatial coordinates of the target unloading point. The calculation method is as follows: when the spatial distance between the endpoint of the candidate node's displacement and the target unloading point is less than the distance between the current anchor point and the target unloading point, the value is 1; otherwise, it follows the formula... Calculation, where The distance between the current anchor point and the target unloading point is the straight-line distance in space. The distance between the candidate node displacement endpoint and the target unloading point is calculated and the result is rounded to two decimal places, with a value range of 0 to 1. The passage cost adaptation coefficient, ranging from 0 to 1, is used to characterize the passage cost advantage or disadvantage of a candidate node in executing the current micro-segment task. Its value is determined by normalizing the inverse of the candidate node's real-time passage cost coefficient. The normalization method is: using the smallest passage cost coefficient in the candidate node set. The reciprocal of the coefficient is the maximum value of 1. The values ​​of the other candidate nodes are the ratio of the reciprocal of their own passage cost coefficient to the maximum value. The lower the passage cost, the higher the coefficient value. The time window adaptation coefficient ranges from 0 to 1 and is used to characterize the degree of matching between the displacement plan of the candidate node and the travel time window of the micro-segment task. The calculation method is as follows: when the executable time of the candidate node completely covers the travel time window of the micro-segment task, the value is 1; when it partially covers, it is calculated as the ratio of the coverage time to the total travel time window; when the time window constraint is not met at all, the value is 0. This is a weighting coefficient, with a sum of values ​​equal to 1; it can be configured according to the priority requirements of the construction project, and in some embodiments... The value should be no less than 0.5 to ensure that the task converges primarily towards the target unloading point; when the project prioritizes transportation efficiency, the value can be increased. The value of can be increased when the project prioritizes meeting schedule milestones. The values ​​of each weight can be dynamically adjusted through the system configuration interface; S33. Complete optimal node matching and distribution: From the candidate node set, the node with the highest overall suitability is selected as the execution node for the current micro-segment task; the anchor node sends the standardized data of the micro-segment task to the execution node to complete the relay matching process; if the candidate node set is empty, the anchor node automatically broadcasts the task request to the adjacent nodes to expand the candidate node selection range. The broadcast request sets the maximum forwarding hop count, which can be set through the system configuration interface. When the maximum forwarding hop count is reached and no execution node that meets the constraints is still not matched, a matching failure warning is sent to the task initiator until an execution node that meets the constraints is matched. S34. Execution of connection and task verification: After receiving the micro-segment task, the execution node completes the automatic docking of the vehicle through the standardized quick-switch interface. After docking is completed, it sends an acknowledgment signal to the current anchor node. The anchor node synchronously completes the closed-loop verification of the current micro-segment task without reporting the task status to the central server.

[0028] S4. Dynamic fault tolerance and adaptive adjustment of relay path for micro-segment tasks.

[0029] This step addresses unforeseen scenarios at construction sites, such as unexpected passageway blockages, node failures, and changes in operating conditions, by enabling dynamic fault tolerance for micro-segments and adaptive adjustment of relay paths. This step is continuously triggered throughout the entire task execution cycle, eliminating the need for global path replanning and fundamentally resolving the issue of complete paths being prone to failure.

[0030] S41. Exception Triggering and Task Feedback: When an execution node fails, a channel is temporarily blocked, or the node's capacity status changes, making it impossible to complete the current micro-segment task, the execution node immediately sends the micro-segment task back to the current relay anchor node, and at the same time broadcasts its own abnormal status data to adjacent nodes and updates the status table of adjacent nodes. S42, Local or Backtracking Rematch: After receiving the returned micro-segment task, the relay anchor node re-executes the candidate node screening and adaptability calculation process of S3 to match a new execution node and complete the relay transmission of the micro-segment task. If there are no candidate nodes that meet the constraints among the adjacent nodes of the current anchor node, the anchor node will return the micro-segment task to the previous level relay anchor node, which will then re-match the relay node. The maximum backtracking level is set during the backtracking, which can be set through the system configuration interface. When the maximum backtracking level is reached and no execution node that meets the constraints is still not matched, a path adjustment failure warning is sent to the task initiator. S43, Adaptive synchronization of global changes: When the road network topology and the status of inherent transfer nodes at the construction site undergo global changes, all nodes in the network synchronously update their adjacent node status tables through status broadcasts from neighboring nodes. The matching process for subsequent micro-segment tasks is automatically executed based on the updated status data. There is no need to adjust the completed micro-segment tasks or replan the global complete path. Only the subsequent micro-segment tasks are adaptively adapted. S44. Dynamically adjust the granularity of micro-segment splitting: The system continuously monitors the stability of the access status in each road network section at the construction site. When a continuous area meets the following merging trigger conditions, it automatically merges 2-3 adjacent consecutive micro-segment tasks into a new micro-segment task: (1) No abnormal events such as channel blockage, equipment failure, or node status change occurred in this area for 30 consecutive minutes (this duration can be set through the system configuration interface); (2) The merged micro-segment tasks still meet the passage constraints (such as load, size, risk level, etc.). (3) The merged node does not cross any inherent forced transition nodes; The merging operation is as follows: the current relay anchor points of multiple adjacent micro-segment tasks in the original micro-segment task sequence are merged with the set of optional relay anchor points, retaining the first segment's starting anchor point and the last segment's ending anchor point, while intermediate anchor points are converted into waypoints; the merged new micro-segment task inherits the task identifier ID of the original first micro-segment task and is identified by the suffix "-Mx", for example, MPT-20260325-001-003-M1; the single-segment passage constraint parameters are taken from the intersection of the original micro-segment constraints (e.g., the time window is taken from the overlapping interval, the load is taken from the minimum value, and the risk level is taken from the most stringent threshold). When the channel status changes more than 3 times in a certain area within a unit time (e.g., 10 minutes) (the threshold can be set through the system configuration interface), and the current micro-segment task splitting granularity is not less than the minimum granularity threshold (e.g., 20m, configurable), the splitting granularity of the current micro-segment task will be reduced to 1 / 2 of the original granularity (if it is still greater than the minimum granularity threshold) or directly reduced to the minimum granularity threshold; after the splitting granularity is adjusted, the remaining unexecuted paths will be re-split into micro-segment task sequences according to the new granularity, the task identifier ID will be reassigned and the binding relationship with the original complete task will be maintained.

[0031] S5. Convergence verification and closed-loop execution of micro-segment tasks.

[0032] Verify the convergence of the micro-segment tasks to ensure that the tasks automatically reach the target unloading point through relay transmission, completing the closed-loop execution of the entire handling task. This step is triggered synchronously after each micro-segment task completes relay matching.

[0033] S51. Calculate the convergence coefficient: After each micro-segment task completes the relay matching, the execution node synchronously calculates the convergence coefficient of the current micro-segment task to verify whether the task is continuously converging towards the target unloading point. The formula for calculating the convergence coefficient is as follows: ; in, This is the convergence coefficient of the current micro-segment task. A value greater than 0 indicates that the task is converging toward the target unloading point, while a value less than or equal to 0 indicates that the task has not converged. The distance between the previous relay anchor point and the target unloading point is expressed in meters and is determined by calculation using the spatial coordinates of the previous relay anchor point and the target unloading point. The distance between the current relay anchor point and the target unloading point is expressed in meters and is calculated using the spatial coordinates of the current relay anchor point and the target unloading point. when When the value is less than the preset approach threshold, the task is directly determined to be in a convergence state without the need to calculate the convergence coefficient. The approach threshold can be configured according to the positioning accuracy requirements of the unloading point. S52. Perform the task based on convergence: When the convergence coefficient is greater than 0, the task is confirmed to be continuously converging. After the execution node completes the execution of the current micro-segment task, it sends the micro-segment task to the corresponding next-level relay anchor point and repeats the process from S3 to S5. When the convergence coefficient is less than or equal to 0, after the current execution node completes the micro-segment task, the next-level relay anchor point re-matches the execution node converging towards the target direction to ensure that the task always converges towards the target unloading point. S53. Determine arrival and complete loop closure: When the spatial distance between the current relay anchor point of the micro-segment task and the target unloading point is less than a preset threshold, it is determined that the task has reached the target area. This preset threshold can be configured according to the positioning accuracy requirements of the unloading point, and in some implementations it can be set to 0.5m~2m. At this time, the final execution node completes the automatic docking and unloading of the vehicle, broadcasts the task completion signal to all adjacent nodes in the network, and completes the closed-loop verification of the entire transportation task. S54. Release node resources: Once the task is completed, all participating nodes synchronously clear the corresponding task data in their local storage, release transportation resources, and wait to receive new micro-segment tasks.

[0034] The implementation basis of this embodiment is that the materials to be transported are fixed in a standardized universal vehicle with a quick-change interface that is compatible with all scenarios. The quick-change interface is fully compatible with the connection mechanism of all ubiquitous displacement units in this embodiment. The micro-segment relay process is only the automatic connection and swapping of the vehicle between different displacement units, without the need for secondary loading, unloading, stacking or displacement operations on the materials themselves. At the same time, the micro-segment relay anchor points prioritize the reuse of the inherent forced transfer nodes of building material transportation, without adding any additional transfer connection nodes, thus eliminating additional loading and unloading costs and expenses from the source. The standardized universal carrier is a closed / open material carrying unit with a rigid frame. The outer contour dimensions, load-bearing weight range, and quick-change interface installation position of the carrier are all designed in a unified and standardized manner. The all-scenario compatible quick-change interface adopts a standardized mechanical locking structure and signal docking terminal. The docking tolerance, locking force, and unlocking triggering method of the locking structure are all set in a unified manner. It can be accurately docked and locked with the docking mechanism of all ubiquitous displacement units. The signal docking terminal is used to complete the synchronous transmission of task data between the carrier and the ubiquitous displacement unit. The inherent rules for determining mandatory transfer nodes are: fixed spatial locations where the displacement carrier must be switched during material handling, including material yard entrances and exits, construction elevator docking ports, floor passage entrances, and unloading points on the work surface. The spatial coordinates of such nodes can be directly extracted from the construction site BIM model and construction site layout data without the need for additional on-site surveying and calibration.

[0035] Example 2, refer to Figure 3 This embodiment of a construction logistics robot handling path determination device includes a task decomposition and encapsulation module, a distributed node network construction module, a micro-segment task relay matching module, a dynamic fault tolerance adjustment module, and a convergence verification and closed-loop execution module. The task decomposition and encapsulation module obtains the basic metadata of a single transport task, dynamically calculates the micro-segment splitting granularity, decomposes a single complete transport task into a continuous standardized micro-segment task sequence, encapsulates metadata and assigns a unique identifier to each micro-segment task, and sends the first micro-segment task to the starting relay node. The distributed node network construction module constructs a decentralized distributed relay node network covering all nodes on the construction site, assigns a unique identifier to each node connected to the network and binds it to basic attribute data, establishes a real-time node status broadcasting mechanism, and synchronously updates the status tables of adjacent nodes and the real-time status data of ubiquitous displacement units. When a micro-segment task relay matching module reaches the relay anchor point, it filters a set of candidate execution nodes that meet the single-segment passage constraints, calculates the comprehensive adaptability of the candidate nodes through a multi-dimensional adaptability calculation model, matches the optimal execution node and sends out task data to complete the vehicle docking confirmation and the closed-loop verification of the single-segment micro-segment task. When an anomaly occurs during task execution, the dynamic fault tolerance adjustment module receives the micro-segment task returned by the abnormal node, executes the local or retrospective rematch process, synchronizes the global working condition changes at the construction site and updates the node status data, and dynamically adjusts the splitting granularity of the micro-segment task according to the channel status. The convergence verification and closed-loop execution module calculates the convergence coefficient of each micro-segment task after the relay matching is completed, verifies the convergence status of the task towards the target unloading point, controls the task to continue relaying towards the target direction, completes unloading and full task closed-loop verification when the task arrives at the target area, and releases the transportation resources of the corresponding node.

[0036] Through the detailed description of the above embodiments, the present invention provides a method and apparatus for determining the handling path of a construction logistics robot. By breaking down a complete handling task into a standardized micro-segment task sequence, it abandons the inherent mode of traditional global path pre-planning and solves the industry pain points of frequent path failures and high task interruption rates caused by the changing working conditions at construction sites. By constructing a decentralized distributed relay node network, the handling execution subject is extended to ubiquitous displacement units across all scenarios, breaking the binding restrictions of dedicated logistics robots and realizing the efficient reuse of transportation capacity and channel resources at construction sites. Through the closed-loop management of the entire process of micro-segment relay matching, dynamic fault-tolerant adjustment, and convergence verification, the present invention can adapt to the complex and changing working environment of construction sites. While ensuring the stable execution of material handling tasks, it effectively reduces handling costs, providing a new and reliable technical solution for automated material handling in smart construction site scenarios.

[0037] The above formulas are all dimensionless calculations, and the preset parameters in the formulas should be set by those skilled in the art according to the actual situation.

[0038] The above embodiments can be implemented, in whole or in part, by software, hardware, firmware, or any other combination thereof. When implemented using software, the above embodiments can be implemented, in whole or in part, as a computer program product. The computer program product includes one or more computer instructions or computer programs. When the computer instructions or computer programs are loaded or executed on a computer, all or part of the processes or functions described in the embodiments of this application are generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wired or wireless (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that includes one or more sets of available media. The available medium can be a magnetic medium (e.g., floppy disk, hard disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium. A semiconductor medium can be a solid-state drive.

[0039] It should be understood that in the various embodiments of this application, the order of the above-mentioned processes does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of this application.

[0040] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0041] Those skilled in the art will understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0042] In the several embodiments provided in this application, it should be understood that the disclosed systems, apparatuses, and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between apparatuses or units may be electrical, mechanical, or other forms.

[0043] If the aforementioned functions are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0044] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A method for determining the handling path of a construction logistics robot, characterized in that, The method flow is as follows: S1. Obtain the basic metadata of a single building material handling task, perform standardized micro-segment decomposition and task metadata encapsulation on the single building material handling task, and generate a continuous micro-segment task sequence without a global unloading endpoint and a complete route preset. Each micro-segment task retains only the core constraint parameters required for single-segment execution. S2. Construct a decentralized distributed relay node network covering all ubiquitous displacement units and fixed spatial relay anchor points on the construction site, establish a real-time status broadcasting mechanism for all network nodes, and synchronously update the status data of adjacent nodes stored locally by each node. S3. When the micro-segment task reaches the corresponding relay anchor point, based on the multi-dimensional adaptability calculation model, a set of candidate execution nodes that meet the constraints is selected for the micro-segment task, the optimal execution node is matched, and the standardized connection of the material carrier and the closed-loop verification of the single micro-segment task are completed. S4. During the entire execution cycle of the task, in response to abnormal working conditions at the construction site, perform dynamic fault-tolerant processing of micro-segment tasks and adaptive adjustment of relay paths. S5. After each micro-segment task completes the relay matching, perform task convergence verification, control the task to continuously relay to the target unloading point until the task reaches the target area and completes the closed-loop execution of the entire handling task.

2. The method for determining the handling path of a construction logistics robot according to claim 1, characterized in that, The standardization of micro-segment decomposition and task metadata encapsulation for a single building material handling task is as follows: Based on the road network topology and inherent forced transfer node distribution at the construction site, the micro-segment decomposition granularity is dynamically calculated, and a continuous sequence of micro-segment tasks is arranged with the inherent forced transfer nodes as the core anchor points. Each micro-segment task is assigned a task identifier bound to a single complete handling task. After completing the standardized metadata encapsulation, the first micro-segment task is sent to the starting relay node.

3. The method for determining the handling path of a construction logistics robot according to claim 2, characterized in that, Each micro-segment task generated by decomposition is only bound to the current relay anchor point, the optional set of relay anchor points, and the single-segment passage constraint parameters.

4. The method for determining the handling path of a construction logistics robot according to claim 1, characterized in that, The construction of a decentralized distributed relay node network specifically involves: assigning a unique node identifier to each node connected to the network and binding it with corresponding basic attribute data; each node broadcasts real-time status data only to neighboring nodes within its communication range at a fixed frequency; and neighboring nodes synchronously update their locally stored neighboring node status tables after receiving the broadcast data, without needing to synchronize node status data to the entire network.

5. The method for determining the handling path of a construction logistics robot according to claim 4, characterized in that, The nodes connected to the distributed relay node network include fixed spatial relay anchor nodes and ubiquitous displacement unit nodes. For ubiquitous displacement unit nodes, their displacement trajectory and displacement plan are updated in real time. The displacement plan includes at least the starting point node, ending point node, time arrangement and capacity occupancy information for the current and future period. When the displacement plan changes, the changed status data is immediately sent to adjacent nodes.

6. The method for determining the handling path of a construction logistics robot according to claim 1, characterized in that, The process of matching the optimal execution node for a micro-segment task is as follows: a set of candidate execution nodes that meet the single-segment passage constraints of the micro-segment task are selected from the adjacent node status table of the current relay anchor point; the comprehensive adaptability of each candidate node is calculated based on a multi-dimensional adaptability calculation model; and the node with the highest comprehensive adaptability is selected as the execution node of the current micro-segment task.

7. The method for determining the handling path of a construction logistics robot according to claim 6, characterized in that, The implementation method of the multi-dimensional adaptation calculation model for calculating the comprehensive adaptation degree is as follows: select the directional convergence coefficient, passage cost adaptation coefficient, and time window adaptation coefficient corresponding to the candidate execution node as the core adaptation dimension, assign corresponding weight coefficients to each adaptation dimension, and the sum of the values ​​of each weight coefficient is 1. The directional convergence coefficient is used to characterize the degree of convergence between the displacement direction of the candidate node and the target unloading point. The passage cost adaptation coefficient is used to characterize the merits of the passage cost of the candidate node executing the current micro-segment task. The time window adaptation coefficient is used to characterize the degree of matching between the displacement plan of the candidate node and the passage time window of the micro-segment task.

8. The method for determining the handling path of a construction logistics robot according to claim 1, characterized in that, The dynamic fault-tolerant processing and adaptive adjustment of the relay path for executing micro-segment tasks are as follows: when the execution node cannot complete the current micro-segment task, the micro-segment task is returned to the corresponding relay anchor node, and the candidate node screening and matching process is re-executed. At the same time, based on the changes in the road network topology and channel status at the construction site, and based on the stable duration or change frequency of the channel status, the micro-segment splitting granularity is dynamically adjusted, including merging multiple consecutive micro-segment tasks into one micro-segment task, or splitting one micro-segment task into multiple micro-segment tasks with finer granularity.

9. The method for determining the handling path of a construction logistics robot according to claim 1, characterized in that, The convergence verification of the execution task is specifically as follows: after each micro-segment task completes the relay matching, the convergence coefficient of the current micro-segment task is calculated, the convergence status of the task towards the target unloading point is verified, the task is controlled to continue relaying towards the target unloading point, and when the task arrives at the target area, the unloading and full task closed-loop verification are completed, and the transportation resources of the corresponding node are released.

10. A device for determining the handling path of a construction logistics robot, used to implement the method for determining the handling path of a construction logistics robot as described in any one of claims 1-9, characterized in that, The device includes a task decomposition and encapsulation module, a distributed node network construction module, a micro-segment task relay matching module, a dynamic fault tolerance adjustment module, and a convergence verification and closed-loop execution module. The task decomposition and encapsulation module acquires the basic metadata of a single building material handling task, and completes the standardized micro-segment decomposition and task metadata encapsulation of a single complete handling task; the distributed node network construction module constructs a decentralized distributed relay node network covering all nodes on the construction site, and establishes a real-time node status broadcasting mechanism; the micro-segment task relay matching module filters and matches the optimal execution node for micro-segment tasks arriving at the relay anchor point, and completes the closed-loop verification of a single micro-segment task; the dynamic fault tolerance adjustment module performs dynamic fault tolerance processing of micro-segment tasks and adaptive adjustment of relay paths for abnormal working conditions on the construction site; the convergence verification and closed-loop execution module verifies the convergence status of micro-segment tasks, controls the continuous relay transmission of tasks to the target unloading point, and completes the closed-loop execution of the entire handling task.

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