Unmanned material transport system and method

Abstract

The application discloses a kind of unmanned material transport systems and methods, including intelligent equipment cluster and remote centralized dispatch system, and intelligent equipment cluster is connected with remote centralized dispatch system;Intelligent equipment cluster includes horizontal transport intelligent equipment for the same layer transport of material, intelligent construction elevator for the cross layer transport of material, and stacking robot for the sorting of material;Remote centralized control system includes front-end interface for issuing tasks, supervising material process and equipment state and back-end server for task scheduling, task path planning, task conflict monitoring and management, and the information collected is transmitted to front-end interface for display, and front-end interface is connected with back-end server;Intelligent equipment cluster and back-end server are communicated bidirectionally through real-time communication module.The application can automatically complete material sorting and transportation, can reduce construction site manual operation, improve equipment efficiency, and reduce transportation cost.

Description

Technical Field

[0001] This invention relates to the field of logistics and transportation technology, specifically to an unmanned material transportation system and method. Background Technology

[0002] Currently, the logistics and transportation operations at construction sites are as follows: materials are first unloaded from trucks manually or by forklifts, then transported to warehouses or storage areas manually or by handcarts. When materials are needed, they are then manually transported horizontally and moved into elevators, which then transport the materials from the ground to designated floors and back to the ground. This traditional construction site logistics and transportation operation requires intensive manual labor throughout, resulting in high labor intensity, cumbersome transportation processes, low work efficiency, poor working conditions, high safety risks, and high material damage rates.

[0003] While the introduction of some intelligent products, such as electric trolleys, can improve transportation efficiency and reduce manual labor to some extent, it still does not solve the problem of relying on manual labor for intensive material handling, transportation, and unloading. In addition, the scheduling of materials, equipment, and manpower on site is in a state of low organization. For example, frequent queuing for elevators during transportation makes it impossible to maximize the allocation and utilization of resources. Summary of the Invention

[0004] The purpose of this invention is to provide an unmanned material transportation system and method that automatically completes material sorting and transportation, can work in a 24 / 7 cycle, can reduce manual labor on construction sites and reduce construction safety risks; it can also connect and organize multiple intelligent devices to work collaboratively in a cyclical manner, avoid equipment task conflicts, improve equipment efficiency and reduce transportation costs.

[0005] The technical solution adopted in this invention is:

[0006] An unmanned material transport system includes an intelligent equipment cluster and a remote centralized dispatch system, wherein the intelligent equipment cluster is connected to the remote centralized dispatch system;

[0007] The intelligent equipment cluster includes:

[0008] Intelligent horizontal transport equipment for transporting materials on the same level;

[0009] Intelligent construction elevators are used for transporting materials across floors.

[0010] Palletizing robots are used for sorting and placing materials.

[0011] The remote centralized control system includes:

[0012] The front-end interface is used to publish tasks, monitor material flow, and track equipment status.

[0013] The backend server is used for task scheduling, path planning, task conflict monitoring and management, and transmits the collected information to the frontend interface for display.

[0014] The real-time communication module is used to enable bidirectional communication between the intelligent equipment cluster and the backend server.

[0015] The front-end interface connects to the back-end server.

[0016] Preferably, the intelligent horizontal transport equipment includes a horizontal transport platform vehicle, an automated guided forklift, and a full-material transport robot;

[0017] The horizontal transport platform vehicle includes a body, an omnidirectional steering chassis located at the bottom of the body, a cargo platform located on the body, and a passive protection module located on the body.

[0018] An automated guided forklift includes a body, an omnidirectional steering chassis located at the bottom of the body, and automated forks and telescopic pallet jacks mounted on the body.

[0019] The material handling robot includes a body, an omnidirectional steering chassis located at the bottom of the body, and an automatic clamping module located on the body.

[0020] Preferably, the palletizing robot includes a fixed palletizing robot and a mobile palletizing robot. The fixed palletizing robot is directly fixed to the installation, and the mobile palletizing robot has a mobile chassis at the bottom of its body. Both the fixed palletizing robot and the mobile palletizing robot have an end-effector 3D vision module on their robotic arms.

[0021] Preferably, the front-end interface includes a real-time status interface and a task management interface, and users can assign tasks, adjust task priorities, and monitor task execution through the front-end interface.

[0022] The real-time status interface is an interactive digital twin, including information on the intelligent equipment cluster and environmental information;

[0023] Among them, intelligent equipment cluster information includes sensor data and location information of each device in the intelligent equipment cluster;

[0024] Environmental information includes sensor data from the environment and video streams returned by the construction site monitoring system;

[0025] The task management interface includes a materials management interface, a task publishing interface, and a task progress interface.

[0026] Preferably, the material management interface is used to provide an intuitive representation of the material flow of the entire site, showing the storage, transportation and usage locations of different materials. On the one hand, it relies on the intelligent equipment vision system and the transportation volume comprehensive statistics system to transport the total amount, and on the other hand, it allows operators to manually enter and correct the material management information.

[0027] The task publishing interface is used to publish material picking and transportation tasks and issue tasks based on material inventory. This includes selecting material type through drop-down menus, manually entering quantity, using topology map to select destination, and selecting priority through drop-down menus. When the database indicates insufficient materials, new materials must be manually added or the task must be modified before it can be executed.

[0028] The task progress interface includes global task progress, displayed as a percentage progress bar showing the number of items transported versus the target number, and task sequences, showing the currently executing task sequences and task sequences arranged by priority; operators can modify individual task sequences.

[0029] Preferably, the backend server includes a layered planning architecture and a hybrid control structure system; specifically, the layered planning architecture and hybrid control structure system includes a top-level planning layer, a middle-level behavior layer, and a bottom-level execution layer;

[0030] The top-level planning layer includes formulating task allocation strategies, planning the paths of each device in the intelligent equipment cluster, and synchronously updating the task allocation module and task conflict resolution module of the material transportation system.

[0031] The middle-level behavior layer includes an action planning module that autonomously plans single-task paths based on global information obtained from the top-level planning layer and exchanges information with other intelligent equipment;

[0032] The underlying execution layer includes a navigation control module, a map generation and update module, and a local path planning module for making real-time decisions on short-term actions and for avoiding obstacles or adjusting routes in real time based on dynamic changes in the scene.

[0033] Preferably, the backend server has a built-in database for storing and managing map data, status information of each device in the intelligent equipment cluster, and task logs;

[0034] The database includes:

[0035] The intelligent equipment status and location database is used to store the real-time status of intelligent equipment, its location and operation status under tasks, and can issue a timely warning on the front-end display interface when an abnormal status of intelligent equipment is detected.

[0036] The materials database is used to store the location and quantity of available materials;

[0037] Digital maps and digital twin databases store and continuously update the digital twin model of the project, reflecting construction progress and updating road conditions to update the planned route in real time;

[0038] Historical data storage records material delivery and material flow statistics, task completion status, and route history for analysis and optimization.

[0039] User and device management database; manages user roles and permissions.

[0040] A material transport method employing the unmanned material transport system described above includes the following steps:

[0041] Publish tasks and adjust task priorities through the front-end interface;

[0042] The backend server obtains the status and environmental information of each device in real time through the sensors of each device in the intelligent equipment cluster, and displays the feedback through the front-end interface.

[0043] The task allocation module in the backend server performs task allocation, task path planning, and task scheduling for each device in the intelligent equipment cluster based on the published tasks.

[0044] The backend server monitors the execution status of each task and the status of each device in the intelligent equipment cluster, and displays the feedback through the front-end interface;

[0045] When the backend server detects conflicts between tasks, the task conflict resolution module in the backend server adjusts the conflicting tasks in a timely manner until the tasks no longer conflict with each other.

[0046] The action planning module in the end server forms global information based on all assigned task paths and environmental information, and divides each individual task into several actions. Each action is executed by the corresponding device in the intelligent equipment cluster. By defining the state, action sequence and constraints of a single action, the device in the intelligent equipment cluster executes the corresponding action according to the changes in environmental information and control task instructions.

[0047] After receiving the global single task paths, the navigation control module in the backend server determines a global path that conforms to the task instructions from the map based on the prior generated map and task allocation, and issues a control to the devices in the intelligent equipment cluster to travel along the global path.

[0048] Preferably, after the backend server detects obstacle information on the path through the sensors of each device in the intelligent equipment cluster, it triggers the local planning adjustment condition. The local path planning module of the backend server uses the previously calculated path as the basis for adjustment, adjusts the cost of the affected nodes, updates a cost map in real time, and calculates the original actual value from the target point to the adjacent node and the heuristic value from the current node to the adjacent node to minimize the actual path length from the current node to the target node. The nodes that need to be readjusted are managed by using a task priority queue to minimize redundant calculations.

[0049] Preferably, the specific process of the task allocation module for planning the task path of each device in the intelligent equipment cluster is as follows: process the environmental road node map to determine the nodes that each device in the intelligent equipment cluster can pass through and occupy; construct a cost matrix, and allocate task paths to each device in the intelligent equipment cluster based on the cost matrix and in combination with the principle of "low-priority tasks slow down and avoid, high-priority tasks accelerate through", and ensure that only a single device in the intelligent equipment cluster occupies a map node within a time step.

[0050] Preferably, the cost matrix includes the task travel time, completion time, path length of the equipment in the intelligent equipment cluster, as well as the capacity utilization rate of each equipment in the intelligent equipment cluster, the types of equipment involved, and the task priority.

[0051] Preferably, during the return process after a single task is completed, the device searches for the nearest location of the start and end points of associated idle tasks; during the task connection process, the device shares a path and assigns idle real-time tasks in the vicinity to devices in the intelligent equipment cluster that are about to finish their task service.

[0052] Preferably, the status of all devices in the intelligent equipment cluster is obtained before each task is assigned. If a single device has insufficient power, the nearest charging station is searched, the coordinates are sent directly, and the device is prioritized to go to the charging station.

[0053] Preferably, the task conflict resolution module iterates through and checks whether there are conflicts between each task path. If there is a conflict, the current path is modified to avoid the conflict by rerouting to an alternative path or delaying the movement of the previous node, or by updating constraints, until all paths are free of conflicts.

[0054] Preferably, the map generation and update module in the backend server generates a high-precision road map by pre-recording road trajectories and processing them. Based on this, a structural topology map is generated to facilitate front-end interface operation and path planning. During execution, the map is updated in real time through sensor data collection from various devices in the intelligent equipment cluster.

[0055] Preferably, the actions in a single task include a material picking process, a transportation process, and a material unloading process;

[0056] In the material handling process, the entire stack of materials is either loaded onto a horizontal conveyor by a palletizing robot or directly by a palletizing robot.

[0057] The transportation process includes intra-floor transportation and inter-floor transportation. Intra-floor transportation involves using intelligent horizontal transportation equipment to transport goods from the origin point A to the target point B on the same floor. Inter-floor transportation involves using intelligent horizontal transportation equipment to enter the assigned intelligent construction elevator from the origin point C on the original floor. The intelligent construction elevator then lifts the intelligent horizontal transportation equipment vertically to the target floor, and the equipment exits from the elevator to the target point D on the target floor.

[0058] The unloading process involves either using a palletizing robot or directly unloading the entire stack of materials to the target location.

[0059] The beneficial effects of this invention are:

[0060] 1. In this invention, the operator only needs to issue tasks and supervise the equipment operation process through a remote centralized control system to complete the material sorting and transportation tasks; it can be widely used in different types of construction sites, without being restricted by the site, environment, or weather, and can work in a 24 / 7 cycle; it can reduce manual labor on the construction site and reduce construction safety risks; it can connect and organize multiple intelligent devices to work in a coordinated cycle, avoid equipment task conflicts, improve equipment efficiency, and reduce transportation costs.

[0061] 2. It can transport most of the materials involved in the secondary structure and decoration stages of the construction site, and can adopt different transportation modes and organize relevant equipment according to the material type and transportation needs, which is more in line with the material handling habits of the construction site; it has a certain degree of adaptability and can adapt to the constantly changing construction site environment. Based on the prior map, it can dynamically update the environmental information to make the equipment operation more stable and less prone to failure; it can record and manage material flow, which is convenient for on-site material management and handling planning. Attached Figure Description

[0062] Figure 1 This is a flowchart of the unmanned material transport system of the present invention.

[0063] Figure 2 This is a schematic diagram illustrating the framework principle of the unmanned material transport system of the present invention. Detailed Implementation

[0064] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention.

[0065] In the description of this invention, it should be understood that if terms such as "center," "longitudinal," "lateral," "length," "width," "thickness," "upper," "lower," "front," "rear," "left," "right," "vertical," "horizontal," "top," "bottom," "inner," "outer," "clockwise," and "counterclockwise" are used to indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings, they are only for the convenience of describing the invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation, and therefore should not be construed as a limitation of the invention. Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of indicated technical features. Thus, features defined with "first" and "second" may explicitly or implicitly include one or more of the stated features. In the description of this invention, "a plurality of" means two or more, unless otherwise explicitly specified.

[0066] In the description of this invention, it should be noted that, unless otherwise explicitly specified and limited, the terms "installation," "connection," and "joining" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection. They can refer to a mechanical connection or an electrical connection. They can refer to a direct connection or an indirect connection through an intermediate medium, and they can refer to the internal communication of two components or the interaction between two components. For those skilled in the art, the specific meaning of the above terms in this invention can be understood according to the specific circumstances.

[0067] Example 1

[0068] An unmanned material transport system, such as Figures 1-2 As shown, it includes an intelligent equipment cluster and a remote centralized dispatch system, with the intelligent equipment cluster connected to the remote centralized dispatch system;

[0069] The intelligent equipment cluster includes:

[0070] Intelligent horizontal transport equipment for transporting materials on the same level;

[0071] Intelligent construction elevators are used for transporting materials across floors.

[0072] Palletizing robots are used for sorting and placing materials.

[0073] The remote centralized control system includes:

[0074] The front-end interface is used to publish tasks, monitor material flow, and track equipment status.

[0075] The backend server is used for task scheduling, task path planning, task conflict monitoring and management, and transmits the collected information to the frontend interface for display.

[0076] Databases are used to store and manage map data, status information of each device in the intelligent equipment cluster, and task logs;

[0077] The real-time communication module is used to enable bidirectional communication between the intelligent equipment cluster and the backend server.

[0078] The database is built into the backend server, and the frontend interface connects to the backend server.

[0079] Furthermore, the intelligent horizontal transport equipment can enter the corresponding intelligent construction elevator to carry out cross-floor transport. The intelligent horizontal transport equipment includes horizontal transport platform vehicles, automated guided forklifts, and bulk material transport robots, which are used for transporting different types of materials. The intelligent horizontal transport equipment cluster is the core equipment for material transport, which is used for horizontal material transport and can automatically navigate to the designated area along the planned path. These equipment all have certain obstacle-crossing capabilities, can move in all directions, have high load capacity, and can work indoors and outdoors.

[0080] The horizontal transport platform vehicle can be equipped with a hopper and requires the assistance of a palletizing robot to complete loading and unloading. It is designed for transporting materials such as boxed concrete, loose blocks, bagged putty, tiles, and fasteners. Its function is to complete the horizontal automatic transport of materials and small machinery throughout the construction area. Its working principle is as follows: the four-wheel independent omnidirectional drive AGV can adapt to all terrains, the 3D vision system is used to identify material information and the surrounding environment, SLAM path planning and autonomous navigation are used, and sensor collaboration enables it to have automatic obstacle avoidance function. Its application scenarios: covering the entire construction area, automatically completing the tasks of picking up materials and horizontal transport with the assistance of palletizing robots, and carrying lightweight intelligent equipment to perform work tasks within the construction site. Its target objects are: blocks, boards, bagged putty, tubular materials, boxed concrete, and steel parts placed on the platform. It can turn in place, has a maximum carrying gradient of 12°, and a maximum obstacle clearance height of 100 mm.

[0081] Automated Guided Vehicles (AGVs) can perform tasks such as pallet picking, material retrieval, and multi-layer stacking, while ensuring that the total weight after loading does not exceed the load limit of the intelligent elevator. They are designed for unloading incoming materials in storage yards, handling stacks of blocks, putty, boards, bundled structural components, curtain wall materials, etc. Their function is to assist in loading and unloading and horizontal material transport throughout the construction area. Their working principle involves a four-wheel independent omnidirectional drive AGV that adapts to all terrains. A 3D vision system identifies material information and the surrounding environment, SLAM path planning and autonomous navigation are used, and sensor collaboration enables automatic obstacle avoidance. The forks insert into the bottom of the pallet or material, lifting it upwards and retracting with the material to place it on a platform. Their application scenarios include: automatically picking up and horizontally transporting materials in the storage yard by sorting and binding them, and assisting in unloading at the target floor. They are suitable for stacks of blocks, bagged putty, boards, and boxed concrete. They can turn in place, have a maximum carrying gradient of 12°, and a maximum obstacle clearance height of 100 mm.

[0082] The bulk material transport robot can autonomously complete material picking and transport tasks. The total weight after loading must not exceed the load limit of the intelligent elevator. During picking, it moves laterally to encompass the material and loads it using its own clamping and lifting device. It can be used to pick up and transport stacks of blocks, stacks of putty, and boxed concrete, etc., within the construction site. Its function is to complete the tasks of picking up, transporting, and placing stacks of materials throughout the entire construction area. Its working principle is as follows: the four-wheel independent omnidirectional drive AGV can adapt to all terrains; a 3D vision system is used to identify material information and the surrounding environment; and SLAM path planning is implemented. Autonomous navigation and sensor collaboration enable it to automatically avoid obstacles. It moves laterally to the top of a stack of materials, lifts the entire stack using a lifting mechanism, and uses limit pins and inner wall clamping surfaces to restrict the relative sliding of the material pallet during transportation. Its application scenarios cover the entire construction area, automatically completing the tasks of material picking and horizontal transportation with the assistance of a palletizing robot. Its target objects are: whole blocks of materials, bagged putty, tiles, and boxed cement. Its performance features include: single load capacity of 1.2t, turning on the spot, maximum carrying gradient of 12°, and maximum obstacle clearance height of 100 mm.

[0083] Furthermore, intelligent construction elevators include, but are not limited to, various customized or added construction elevators capable of remote control with functions such as automatic door opening and closing, automatic leveling, intelligent recognition, and automatic connection. Intelligent construction elevators are divided into remote intelligent elevators and intelligent circulating elevators. Their function is to assist other intelligent equipment in completing vertical transportation. Their working principle is to add a remote control module to the basis of ordinary construction elevators or single-tower multi-cage construction elevators. Through PCL, the elevator door is remotely controlled to open and close, and commands are remotely issued to control the elevator to reach the target floor. Sensors fuse information to monitor the elevator status in real time. A 3D vision system is used for recognition and interaction with other intelligent equipment. For intelligent circulating elevators, intelligent optimization algorithms are used to quickly arrange and schedule the cages, prioritizing the fastest time to complete the cage rotation and reach the designated floor. Their application scenarios are: serving the vertical transportation of construction main bodies with a building height of more than 150 m; their target users are: on-site workers (manual mode) and intelligent equipment (automatic mode).

[0084] Furthermore, the palletizing robot includes a fixed palletizing robot and a mobile palletizing robot. The fixed palletizing robot is directly fixed to the installation, while the mobile palletizing robot has a mobile chassis at the bottom of the robot body, which can drive the robot body to move. Both the fixed palletizing robot and the mobile palletizing robot have an end-effector 3D vision module on their robotic arms.

[0085] Fixed palletizing robots consist of a linkage robotic arm, an end effector gripper, and an end effector 3D vision system. They are capable of identifying and grasping materials for dense sorting and stacking operations. The robotic arm has a load capacity exceeding 50kg for a single material. The gripper can be pneumatic, hydraulic, or electric driven. Designed for use in stockyards, they perform intensive unpacking and fixed-point material pickup to horizontal transport platforms, pallets, or racks. Their functions include: rapidly unpacking incoming materials at fixed points in the stockyard, stacking them according to transport requirements, and placing them on the platform. Their working principle involves a ground rail at the bottom of the robot, extending the movement range of the industrial six-axis robot within a certain range. The 3D vision system identifies material information and technology, while the end effector grippers grasp and place individual materials. Application scenarios include: rapid and intensive material sorting at fixed locations in the stockyard, typically requiring automated guided forklifts for assisted loading. Suitable materials include: blocks, sheets, tubular materials, and bagged putty.

[0086] The mobile palletizing robot consists of a mobile chassis, a collaborative robotic arm, an end effector gripper, and an end effector 3D vision module. It can move freely within the stockyard, identify materials, and then depalletize and stack them onto racks or horizontal transport robots. This allows for depalletizing and stacking at any location within the stockyard. It can also pick up and transport loose materials and tools. The collaborative robotic arm has a rated load of at least 50kg and a reach of at least 2000mm. The mobile palletizing robot itself has a load capacity of at least 500kg and can adapt to all indoor and outdoor terrains at construction sites. Its functions include: within the entire construction area, a single machine can complete fixed-point material pickup, horizontal and vertical transport to the destination. The AGV is used for marking and unloading tasks. Its working principle is as follows: a medium-sized four-wheel independent drive AGV allows the robotic arm to cover the entire construction site. A 3D vision system is used to identify material information and the surrounding environment. SLAM path planning and autonomous navigation, along with sensor collaboration, enable automatic obstacle avoidance. The end-effector gripper picks up and places individual materials. Its application scenarios include: covering the entire construction area, completing the transportation of small quantities of materials from the storage yard to the target location, and assisting the material transport robot in unloading at the target floor. Its target materials include: blocks, boards, and bagged putty. It can turn in place, has a maximum carrying gradient of 12°, and a maximum obstacle clearance height of 100 mm.

[0087] All of the aforementioned intelligent equipment should have manual and automatic control switching functions and be equipped with a control display panel. Operators can easily interact with the equipment via the touch panel, switching between automatic, manual, and remote control modes. In automatic mode, the equipment is controlled by the dispatch system. In manual mode, operators can modify the selected equipment mode, such as standby, follow, stop, return to charging, etc., or select remote control control.

[0088] Furthermore, the front-end interface is used to provide operators with an intuitive interface, including a real-time status interface and a task management interface. At the same time, users can use the front-end interface to assign tasks, adjust priorities, and monitor task execution.

[0089] The real-time status interface is an interactive digital twin, including information on intelligent equipment clusters and environmental information for centralized visualization.

[0090] The intelligent equipment cluster information consists of sensor data and location information from each device in the cluster. The sensor data includes the mileage, battery level, load capacity, and communication status of the intelligent equipment. The location information is displayed by a topology map. Key points are marked on the topology map, including storage yards, intelligent elevators, and unloading points. Corresponding sensors are also installed at each key point. The map generates a path for the intelligent equipment to move. Combined with the information returned by the positioning module on the intelligent equipment, the real-time coordinates and path of the intelligent equipment are displayed.

[0091] Environmental information includes data from sensors installed in the environment and video streams returned by the construction site monitoring system;

[0092] The task management interface includes: material management interface, task publishing interface, and task progress interface;

[0093] The material management interface provides an intuitive representation of the material flow throughout the site, displaying the storage, transportation, and usage locations of different materials. It relies on the intelligent equipment vision system and the comprehensive transportation volume statistics system to transport the total amount of materials, while also allowing operators to manually enter and correct material information.

[0094] The task publishing interface is used to publish material picking and transportation tasks and issue tasks based on material inventory. This includes selecting material type through drop-down menus, manually entering quantity, using topology map to select destination, and selecting priority through drop-down menus. When the database indicates insufficient materials, new materials must be manually added or the task must be modified before it can be executed.

[0095] The task progress interface includes global task progress, displayed as a percentage progress bar showing the number of transported items versus the target quantity, and task sequences, showing the currently executing task sequences and task sequences arranged by priority, including node action numbers and executing equipment numbers. Operators can manage task progress by modifying individual task sequences, such as adding or removing nodes or modifying sequence priorities, and can also view and modify the operating status of executing equipment.

[0096] Example 2

[0097] Based on Example 1, the backend server is further restricted, resulting in Example 2 having even better performance.

[0098] Furthermore, the backend server is responsible for handling transportation logic, data, and communication with intelligent equipment. It adopts a layered planning architecture and a hybrid control structure system to solve the task planning problem in dynamic and uncertain environments. The layered planning architecture and hybrid control structure system specifically includes a top-level planning layer, a middle-level behavior layer, and a bottom-level execution layer.

[0099] The top-level planning layer includes a task allocation module and a task conflict resolution module. As the main control unit, it controls each device in the intelligent equipment cluster. It acquires the status and environmental information of the intelligent equipment through sensors, processes feedback data from the underlying devices, and formulates task allocation strategies according to the principle of "low-priority devices slowing down and avoiding obstacles, high-priority devices accelerating through." Based on this strategy, it logically schedules the priorities of each task, plans the paths of each intelligent device, and synchronously updates the latest global information (global information refers to the intelligent equipment cluster information, environmental information, and the status and progress of each task).

[0100] The middle behavioral layer includes an action planning module, which adopts a distributed control structure. The object is each device in the intelligent equipment cluster as an independent individual. Based on the global information obtained from the top planning layer, it autonomously plans a single task path and realizes information exchange and communication with other intelligent equipment.

[0101] The underlying execution layer includes a navigation control module, a map generation and update module, and a local path planning module, which are used to make real-time decisions on short-term actions. For example, when dynamic changes occur on site, such as encountering new obstacles, the system can avoid the obstacles or adjust the route and update the map in real time (i.e., when obstacles appear, the system can promptly correct the path to bypass the obstacles and continue to execute the mid-level planned path).

[0102] Furthermore, the task allocation module is used for path planning (MAPF) of each intelligent equipment. The specific process of intelligent equipment path planning is as follows: First, the environmental road node map is processed to clarify the nodes that each intelligent equipment can pass through and occupy; then, a cost matrix is ​​constructed, which includes the task travel time, completion time, path length, capacity utilization rate, equipment types involved (multiple equipment collaborations increase task complexity), task priority, etc. of each equipment in the intelligent equipment cluster; and the conflict constraint is determined to be that within a time step, only a single equipment or intelligent equipment occupies a map node; the user issues a task, and the Hungarian algorithm (Kuhn-Munkres) is used to solve the optimal allocation of intelligent equipment AGVs to tasks based on the constructed cost matrix to minimize the total cost; after a single task is completed, during the process of the empty vehicle returning to the picking location, the map is weighted through a shared ride algorithm to search for the closest location of the start and end points of associated idle tasks. During the task connection process, the path is shared as much as possible, that is, the idle real-time tasks in the nearby area are assigned to the equipment in the intelligent equipment cluster that is about to finish its service, provided that the service end point of the equipment is close to the start point of the next task, so as to reduce the empty return rate and improve the efficiency of circular transportation;

[0103] The task allocation module uses a path-least-occupancy strategy for intelligent elevator scheduling. It uses the A* algorithm to find the elevator car that is closest to the 1st floor and can directly reach the destination floor. If such a car is found, it is scheduled to go to the 1st floor to wait. If no elevator car that is closest to the 1st floor and can directly reach the destination floor is found, the system will search for the elevator car with the least occupancy on the path to the destination floor that is closest to the 1st floor. Other elevator cars on the same side will be scheduled to go to the nearest rotating section to avoid the elevator car. If the number of occupancy is equal, the elevator car will be allocated according to distance priority.

[0104] Before each task assignment, obtain the status of all equipment. If a single piece of equipment is low on power, search for the nearest charging station, send its coordinates directly, and prioritize dispatching the smart equipment to the charging station.

[0105] The task conflict resolution module adopts a conflict-based search (CBS) method to perform constrained single-machine planning. This involves using the traditional A* algorithm to construct a cost matrix for path planning within a given path interval, along with constraints on each path. This ensures that each level of the intelligent transport AGV will not share a node with another AGV or an obstacle during any given time period (from arrival time to departure time at a specific location). Constraints include waiting conditions (e.g., waiting for the AGV ahead to pass through elevator entrances, corridors, etc., following a first-in-first-out rule) and operational conditions (speed limits, restricting the maximum speed of the AGV in different scenarios). The top-level module traverses all planned paths at the bottom level, checking for conflicts. If a conflict exists, the current path is modified to avoid conflict by rerouting to an alternative path or delaying the movement of the previous node, or by updating constraints, such as applying new constraints (obstacle avoidance execution time, etc.), until all bottom-level paths are conflict-free.

[0106] The motion planning module adopts behavior-based control, dividing the complete task flow into several basic actions, each of which is executed by the corresponding equipment in the intelligent equipment cluster. According to the equipment type involved in the task stage, the action primitives are divided into four categories: material picking, horizontal transportation, vertical transportation, and unloading. By defining the possible state-action sequences and constraints of a single action, the equipment in the intelligent equipment cluster can execute corresponding actions according to changes in environmental information and control commands. When external conditions and overall task requirements change, it can respond quickly and organize a series of action primitives.

[0107] The material handling process involves a palletizing robot and a horizontal transport device. The constraints are the material handling location, material type, and quantity specified by the task planning module. The corresponding actions can be abstracted into four categories:

[0108] A fixed palletizing robot rapidly stacks and unloads incoming materials within the stockyard onto a horizontal transport platform. After obtaining material position and shape information via a vision camera, the control system plans a multi-node path to control the robotic arm and grippers to complete the grasping and placement. The material handling sequence is as follows: the horizontal transport platform moves to the vicinity of the fixed palletizing robot – precise positioning and posture adjustment – ​​the fixed palletizing robot controls the robotic arm to identify and grasp the material – the identification and control robotic arm stacks the material into the hopper of the horizontal transport platform. The constraints are: material type, transportation method, and picking location. Material types include block materials, bagged putty, and boards; transportation methods include bulk transport or partial transport; picking location: within the stockyard.

[0109] The mobile palletizing robot picks up loose materials at the construction site. Based on available material information from the backend, it moves to the target point, identifies the target material through a vision system, plans the robotic arm path, and controls the gripper's movements. Its material-picking sequence is: the mobile palletizing robot moves to the vicinity of the material location -- the mobile palletizing robot scans and identifies -- the robotic arm is controlled to pick up the material and place it into the hopper. Constraints include: material type, transportation method, and picking location. Material types include block materials, bagged putty, and loose steel parts; transportation methods include bulk material transportation (<500kg); and picking locations include within the construction area.

[0110] The integrated pick-and-carry robot (bulk material transport robot) picks up stacks of materials on the construction site. Based on available material information from the backend, it moves to the target point, identifies the target material through a vision system, and uses vision and laser fusion to assist in precise positioning and alignment, controlling the internal lifting device to complete the pick-up. Its picking sequence is as follows: the integrated pick-and-carry robot moves to the vicinity of the picking point -- scans the environment for precise positioning -- sensor fusion assists in adjusting its posture for precise lateral movement or forward extension of the forks -- controls its own lifting mechanism to pick up the material. Its constraints are: material type, transportation method, and picking location. Material types include block materials, bagged putty, boards, and tubular materials; transportation methods include bulk material transport up to 1 ton; and picking locations are within the construction area.

[0111] The horizontal transport platform vehicle is used to pick up concrete, mortar, etc. at designated locations. After the horizontal transport platform vehicle with a hopper moves to the target point, it automatically unloads the material based on feedback from humans or a vision system, and then drives away after stopping unloading. The material picking sequence is as follows: the horizontal transport platform vehicle carrying the box container moves to the vicinity of the material -- sensor fusion assists in adjusting the posture for precise positioning -- the tanker truck identifies and unloads the material. The constraints are: the material type includes box-filled mortar and box-filled concrete; the transportation method includes box-filled transportation <800kg; and the picking location includes the location of the mixer truck.

[0112] In the horizontal transport phase, the constraints are the completion status of the previous stage, including the executed intelligent equipment and its completion location, material information, and the next planned target point. The transport task from point A to point B is completed by calling the local path planning module. The horizontal transport phase is divided into intra-level transport and inter-level transport. The intra-level transport action sequence is: the horizontal transport robot or mobile palletizing robot moves from the completion point of the previous action and navigates to the task completion point; the constraints for intra-level transport are: Execution equipment: material handling completion equipment, material handling location: material handling completion location, target location: work point. The inter-level transport action sequence is: the horizontal transport robot or mobile palletizing robot moves from the material handling completion point and navigates to the assigned intelligent elevator position—sensor fusion assists in precise positioning of the elevator cage; the constraints for inter-level transport are: Execution equipment: material handling completion equipment, material handling location: material handling completion location, target location: assigned intelligent elevator.

[0113] The vertical transportation process is relatively simple. Based on instructions from the task allocation module, the elevator cage reaches the designated connecting floor and opens its door. The transport equipment, through multi-sensor fusion feedback information, completes precise positioning and adjusts its posture before entering the elevator. Once the elevator's vision system recognizes the transport equipment in place, the elevator cage door closes and the equipment is transported to the target floor. The lifting cage door then opens, and the transport equipment exits. The vertical transportation sequence for transporting the equipment to the target floor is as follows: the intelligent construction elevator automatically opens its door after recognizing the intelligent equipment AGV—the intelligent equipment AGV precisely adjusts its posture and enters the elevator—the elevator door closes, automatically opens after reaching the target floor—the intelligent equipment AGV exits. The constraints are: Execution elevator cage: system allocation and scheduling; Connecting floor: horizontal transportation completion level; Target floor: task target floor.

[0114] The unloading process involves transport equipment and mobile palletizing robots. Based on the constraints such as the unloading target point, the type of transported material, and the quantity of material issued by the task allocation module, it can be divided into three categories:

[0115] The horizontal transport platform vehicle is manually unloaded. After reaching the target point, the vehicle is switched to standby mode by the operator for manual assistance in unloading. Once the unloading task at that point is completed, it can switch to follow mode and, with the assistance of a vision system, follow the worker at low speed to the next location to repeat the unloading task. After all unloading is completed, the vehicle is manually switched back to automatic mode, and the equipment is re-scheduled by the task allocation module. Its constraints are: unloading location: work point; transportation method: scattered transportation; usage: manual assistance in unloading to multiple work points.

[0116] A horizontal transport platform vehicle and a mobile palletizing robot assist in unloading. After the horizontal transport platform vehicle reaches the target point, the mobile palletizing robot deployed on that floor assists in unloading. After obtaining material information through a vision camera, the mobile palletizing robot uses a multi-node path planned by the control system to control the robotic arm and gripper to pick up and place the material at the target location. Once the material is completely unloaded, the equipment ends its current task state and waits for secondary scheduling by the task allocation module. The specific unloading sequence is as follows: the mobile palletizing robot deployed on the floor moves to the vicinity of the horizontal transport platform vehicle -- multi-sensor collaborative assistance for synchronous positioning -- the mobile palletizing robot controls the robotic arm and gripper to pick up the material from the horizontal transport platform. The constraints are: unloading location: work point; transportation method: scattered transportation; usage method: automatic unloading at fixed or multiple work points.

[0117] The integrated pick-and-carry robot unloads materials. After reaching the target point, the robot achieves precise positioning through multi-sensor fusion, adjusts its posture, controls its lifting mechanism to lower the material, and then ends the current task state, waiting for secondary allocation. Its unloading sequence is as follows: after arriving at the floor storage yard, the integrated pick-and-carry robot scans the surrounding environment -- precisely positions itself to the unloading location -- adjusts its posture -- controls the lifting device to lower the material. Its constraints are: unloading location: floor storage yard; transportation method: whole material; usage method: transported as a whole to the target floor and then picked up by humans or mobile palletizing robots as needed.

[0118] Furthermore, the local path planning module is used for the real-time obstacle-avoidance movement or decision-making of the intelligent equipment AGV, responding to changes in the current environment and position of the intelligent equipment AGV, adjusting the path in a small area around the obstacle in real time, and using the incremental search D*Lite algorithm for local planning and adjustment.

[0119] The specific process is as follows: Initially, based on known environmental information and prior maps, a reverse search from the target point to the starting point is performed, and a globally optimal path is planned, establishing a "path field" information. When sensors (sensors on various intelligent equipment, such as millimeter-wave radar and lidar, and obstacles that occasionally and dynamically appear in the real environment) provide obstacle information, the D* Lite algorithm's local planning adjustment condition is triggered (specifically, if there is an obstacle within a set distance of the intelligent equipment vehicle, then local planning adjustment is performed). The previously calculated path is used as the basis for adjustment, adjusting the cost of affected nodes. A cost map is updated in real time based on the A* algorithm, correspondingly calculating the original actual value from the target point to adjacent nodes and the heuristic value from the current node to adjacent nodes, minimizing the actual path length from the current node to the target node. Furthermore, a priority queue is used to manage nodes that need to be readjusted, minimizing redundant calculations. Since a "path field" has been established, in environments where the graphics change due to moving obstacles or terrain cost changes, compared to the A* algorithm's re-path planning, the D* Lite algorithm only needs to locally update the path to complete obstacle avoidance, making it more suitable for scenarios with large and dynamically changing maps.

[0120] Furthermore, after receiving the global single-task paths from the mid-level planning, the navigation control module, based on the prior map and task allocation, uses the A* algorithm to search for a global path that matches the task instructions from the structure map (the structure map is a rasterized version of the prior map, which facilitates feedback on the status of path system nodes and whether nodes are occupied, in order to resolve conflicts), and sends the navigation control module to control the vehicle to drive safely and stably along the global path.

[0121] The navigation control module includes a safety monitoring module, a motion control module, and a positioning perception module. The safety monitoring module uses camera vision to collect information, monitors and analyzes in real time whether obstacles affect the safety of the AGV's planned path execution, and feeds this information back to the motion control module. When executing the upper-level planned path, the motion control module uses a PID tracking algorithm to simplify the vehicle's four-wheel model into a kinematic bicycle model. Based on the GPS and SLAM positioning information from the intelligent equipment cluster, and using the rear axle as the tangent point and the vehicle's longitudinal axis as the tangent line, it controls the front wheel steering angle to guide the vehicle along an arc passing through the target path point. Given the angle α between the vehicle body and the target path point at time t, and the forward sight distance from the target path point, with a fixed wheelbase, the required front wheel steering angle is estimated. The pure tracking controller is actually a P-controller for lateral steering (the pure tracking controller has a built-in tracking algorithm). The main influencing factor of the controller is the forward sight distance. One common method is to express the forward sight distance as a linear function of the vehicle's longitudinal velocity. Then, adjusting the forward sight distance of the pure tracking controller becomes adjusting the coefficient k, using the maximum and minimum forward sight distances to constrain the forward sight distance. A larger forward sight distance means smoother trajectory tracking, while a smaller one results in more accurate tracking. After receiving feedback from the safety monitoring module, a decision to avoid obstacles, follow, or stop is generated based on the current state, road, and obstacle information. When the obstacle avoidance conditions are met, the motion control module calls the obstacle avoidance algorithm's local path planning module to generate control commands and send them to the servo motors. After successful obstacle avoidance, the system returns to the tracking module.

[0122] The map generation and update module first uses a combination of GPS and SLAM to pre-record road trajectories, processes them to generate a high-precision road map, and then generates a structural topology map based on this map to facilitate front-end interface operation and path planning. During execution, the probabilistic raster map is updated in real time through sensor data acquisition.

[0123] Furthermore, the database includes

[0124] The database of intelligent equipment AGV status and location is used to store the real-time status, location and operation of intelligent equipment AGV under task. When an abnormal status of intelligent equipment AGV is detected, a timely warning can be issued on the front-end display interface.

[0125] The materials database is used to store the location and quantity of available materials;

[0126] Digital maps and digital twin databases store and continuously update the digital twin model of the project, reflecting construction progress and updating road conditions to update the planned route in real time;

[0127] Historical data storage records material delivery and material flow statistics, task completion status, and route history for analysis and optimization.

[0128] User and device management database; manages user roles and permissions.

[0129] Furthermore, the real-time communication module, through the installation of wireless communication modules at key locations (AP points) on the construction site, enables indoor and outdoor networking design. This meets the needs of various types of transport robots in the construction environment for high communication flexibility, strong scalability, simple maintenance, and stable transmission. It achieves seamless communication between the cluster control system and transport robots and monitoring equipment at any location on site, ensuring smooth and safe on-site transport operations. The control flow and state flow use the MODBUS communication protocol, while the video stream uses the RTSP protocol (Real-Time Streaming Protocol). The horizontal transport robot and the circulating elevator are networked using the NRF24L01 wireless module. Outdoor long-distance wireless networking is achieved through three bridges, while indoor networking on each floor consists of a mesh network. The construction site uses a 1.4G WiFi mesh network, enabling the backend cluster control system to remotely control AGVs, palletizing robots, and intelligent construction elevators.

[0130] The transportation methods for various typical materials are shown in Table 1 below.

[0131]

[0132] Table 1

[0133] A material transport method employing the unmanned material transport system described above, characterized by comprising the following steps:

[0134] Step 1: Operators publish tasks and adjust task priorities through the front-end interface;

[0135] Step 2: The backend server obtains the status and environmental information of each device in real time through the sensors of each device in the intelligent equipment cluster, displays the feedback through the front-end interface, and updates the environmental map in real time through the map generation and update module.

[0136] Step 3: The task allocation module in the backend server performs task allocation, task path planning, and task scheduling for each device in the intelligent equipment cluster based on the published tasks.

[0137] Step 4: The backend server monitors the execution status of each task and the status of each device in the intelligent equipment cluster, and displays the feedback through the front-end interface.

[0138] Step 5: When the backend server detects conflicts between tasks, the task conflict resolution module in the backend server adjusts the conflicting tasks in a timely manner until the tasks no longer conflict with each other.

[0139] Step 6: The action planning module in the backend server forms global information based on all assigned task paths and environmental information, and divides each individual task into several actions. Each action is executed by the corresponding device in the intelligent equipment cluster. By defining the state, action sequence and constraints of a single action, the device in the intelligent equipment cluster executes the corresponding action according to the changes in environmental information and control task instructions.

[0140] Step 7: After receiving the global single task paths planned by the middle layer, the navigation control module in the backend server searches and determines a global path that conforms to the task instructions from the structure map based on the prior generated map and task allocation, and issues a control to the intelligent equipment cluster to drive safely and stably along the global path.

[0141] Furthermore, after step 7, the backend server detects obstacle information on the path through the sensors of each device in the intelligent equipment cluster, triggering local planning adjustment conditions. The local path planning module of the backend server uses the previously calculated path as the basis for adjustment, adjusts the cost of the affected nodes, updates a cost map in real time, and calculates the original actual value from the target point to the adjacent node and the heuristic value from the current node to the adjacent node to minimize the actual path length from the current node to the target node. The nodes that need to be readjusted are managed by using a task priority queue to minimize redundant calculations.

[0142] Furthermore, in step 3, the specific process of the task allocation module for planning the task paths of each device in the intelligent equipment cluster is as follows: processing the environmental road node map to determine the nodes that each device in the intelligent equipment cluster can pass through and occupy; constructing a cost matrix, and allocating task paths to each device in the intelligent equipment cluster based on the cost matrix and in combination with the principle of "low-priority tasks slowing down and avoiding, and high-priority tasks accelerating through"; and ensuring that only a single device in the intelligent equipment cluster occupies a map node within a time step.

[0143] Furthermore, the cost matrix includes the task travel time, completion time, path length of the equipment in the intelligent equipment cluster, as well as the capacity utilization rate of each equipment in the intelligent equipment cluster, the types of equipment involved, and the task priority.

[0144] Furthermore, in step 3, during the device's return process after a single task ends, the system searches for the closest location to the start and end points of associated idle tasks; during the task connection process, the system shares paths and assigns idle real-time tasks in the vicinity to devices in the intelligent equipment cluster that are about to finish their task service.

[0145] Furthermore, in step 3, the status of all devices in the intelligent equipment cluster is obtained before each task is assigned. If a single device has insufficient power, the nearest charging station is searched, the coordinates are sent directly, and the device is prioritized for charging.

[0146] Furthermore, in step 5, the task conflict resolution module iterates through and checks whether there are conflicts between each task path. If there is a conflict, the current path is modified to avoid the conflict by rerouting to an alternative path or delaying the movement of the previous node, or by updating constraints, until all paths are free of conflicts.

[0147] Furthermore, the map generation and update module in the backend server generates a high-precision road map by pre-recording road trajectories and processing them. Based on this, a structural topology map is generated to facilitate front-end interface operation and path planning. During execution, the probabilistic raster map is updated in real time through sensor data collection from various devices in the intelligent equipment cluster.

[0148] In step 6, the actions in a single task include material handling, transportation, and unloading.

[0149] In the material handling process, the entire stack of materials is either loaded onto a horizontal conveyor by a palletizing robot or directly by a palletizing robot.

[0150] The transportation process includes intra-floor transportation and inter-floor transportation. Intra-floor transportation involves using intelligent horizontal transportation equipment to transport goods from the origin point A to the target point B on the same floor. Inter-floor transportation involves using intelligent horizontal transportation equipment to enter the assigned intelligent construction elevator from the origin point C on the original floor. The intelligent construction elevator then lifts the intelligent horizontal transportation equipment vertically to the target floor, and the equipment exits from the elevator to the target point D on the target floor.

[0151] The unloading process involves either using a palletizing robot or directly unloading the entire stack of materials to the target location.

[0152] The working principle of this invention is as follows: 1) An unmanned material transportation system adapted to the secondary structure construction and decoration construction stages of a construction site, for materials of different types and specifications, including an intelligent equipment cluster and a remote centralized control system. The intelligent equipment cluster includes: intelligent horizontal transportation equipment for same-floor transportation; intelligent construction elevators for cross-floor transportation; and palletizing robots for sorting and placing. The remote centralized scheduling system includes: a front-end interface for issuing tasks, monitoring processes and equipment status; a back-end server for task scheduling, path planning, conflict monitoring and management; a database for storing and managing map data, intelligent equipment status information, and task logs; and a real-time communication module for enabling bidirectional communication between intelligent equipment and the server. The material management system relies on a vision system to classify and statistically analyze the material flow within the construction area. 2) The transportation modes include loose material transportation, stacked material transportation, and boxed material transportation, which can cover most of the materials involved in the secondary structure and decoration construction stages of a construction site, including block materials such as blocks, board materials such as tiles, bagged materials such as putty, tubular materials such as bundled formwork components, loose materials such as fasteners, and roll materials such as waterproof rolls. It can realize the entire process of material picking, transportation, and unloading on the same or cross-floor of the construction site, which is more in line with material usage habits. 3) Users publish material picking and transportation tasks through the remote centralized scheduling system and remotely monitor the execution of tasks by the intelligent equipment cluster. Users first obtain the existing stock information and publish material scheduling information through the front-end graphical operation interface, including material name, required quantity, transportation start point, transportation destination, task priority, etc. After receiving the task, the back-end server of the remote centralized scheduling system parses and assigns the task to a single intelligent equipment, and issues instructions to the intelligent equipment to execute the task through the network communication system. Correspondingly, during the execution phase, the equipment returns the equipment sensor data, updated map information, material statistics information, etc. to the database module through the communication network system, and provides real-time feedback to the user through the graphical front end. 4) In order to solve the problem of efficient allocation of tasks for multiple intelligent equipment working together simultaneously on the construction site, a hierarchical planning architecture and a hybrid control structure system are adopted to solve the task planning problem in dynamic and uncertain environments. The top-level planning layer includes a task allocation and conflict resolution module, which acts as the main control unit to control all intelligent equipment, acquire equipment status and environmental information, process data, and formulate strategies, while synchronizing the latest global information. The middle-level behavior layer mainly consists of an action planning module and a local path planning module, which adopts a distributed control structure. The object is each intelligent equipment as an independent individual, which autonomously plans local paths based on the global information acquired from the upper layer and communicates and exchanges information with other equipment. The bottom-level execution layer includes a navigation control module and a map generation and update module. As the execution layer, it is used to make real-time decisions on short-term actions, such as avoiding obstacles or adjusting routes and updating maps in real time when dynamic changes occur on site, such as encountering new obstacles.5) To address the diverse materials and changing transportation needs at the construction site, a behavior-based control method is adopted. The complete task flow is broken down into several basic actions, executed by corresponding intelligent equipment. These actions can be categorized into four types: material picking, horizontal transportation, vertical transportation, and unloading. By defining state-action sequences and constraints, the intelligent equipment executes corresponding actions based on changes in environmental information and control commands. When external conditions or overall task requirements change, the module can quickly respond and organize action primitives. Based on the input material information, the system determines the material picking method: a mobile palletizing robot can pick up scattered materials at multiple target points; an integrated picking and transport robot can pick up entire pallets of materials; or a horizontal transport platform vehicle can pick up materials with the assistance of a fixed palletizing robot. Based on the completion status of material retrieval and task allocation, the transportation method is determined: the integrated retrieval and transportation robot, the horizontal transport platform vehicle, and the mobile palletizing robot can all complete the same-floor transportation, or autonomously take the elevator to the target floor and then carry out cross-floor transportation; the unloading method is determined according to the target point and transportation status, the integrated retrieval and transportation robot unloads the material in the floor storage yard, or the manual unloading is carried out from the horizontal transport platform vehicle, or the mobile palletizing robot completes the unloading at multiple work points, ensuring that the construction site can efficiently and flexibly meet the transportation needs.

[0153] In summary, by using a remote centralized control platform to issue tasks and monitor processes, manual labor can be reduced and construction safety risks can be lowered; the macro-scheduling system can also avoid collisions between intelligent devices through multi-level planning, thereby improving the safety of equipment use; and precise control and coordination can also prevent damage to the main building structure due to collisions during transportation.

[0154] The unmanned material transport system proposed in this invention can adapt to both indoor and outdoor environments at construction sites, possessing autonomous positioning and navigation capabilities both indoors and outdoors. It is unaffected by site limitations, environmental constraints, or weather conditions, and can operate 24 / 7. It can connect multiple intelligent devices and increase or decrease equipment quantity as needed. In the initial planning stage, equipment and systems can be rationally selected based on the different needs and investment expectations of various owners, maximizing the efficiency of individual intelligent devices and transport efficiency, and reducing initial investment. During operation, some equipment can be gradually reduced according to site conditions, improving equipment turnover rate. It can automatically analyze and decompose macro-level tasks, decompose and establish synchronous multi-line tasks, and rationally arrange multi-machine collaboration. Through an intelligent scheduling system, multiple intelligent devices can efficiently cycle within task threads to maximize the effectiveness of the intelligent equipment cluster, reducing material transport time costs and labor input. Compared to manual handling, human input is only required for remote monitoring, significantly reducing workload. It can switch between automatic and manual modes as needed to meet different requirements in various scenarios and achieve different operational objectives. This highly integrated system can be integrated into the current labor-intensive construction mode without occupying other work flows or interfering with other construction steps, achieving human-machine symbiosis and efficient cooperation.

[0155] It should be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article, or apparatus.

[0156] It should be understood that those skilled in the art can make improvements or modifications based on the above description, and all such improvements and modifications should fall within the protection scope of the appended claims.

Claims

1. An unmanned material transport system, characterized in that: This includes intelligent equipment clusters and a remote centralized dispatch system, with the intelligent equipment clusters connected to the remote centralized dispatch system; The intelligent equipment cluster includes: Intelligent horizontal transport equipment for transporting materials on the same level; Intelligent construction elevators are used for transporting materials across floors. Palletizing robots are used for sorting and placing materials. The remote centralized control system includes: The front-end interface is used to publish tasks, monitor material flow, and track equipment status. The backend server is used for task scheduling, task path planning, task conflict monitoring and management, and transmits the collected information to the frontend interface for display. The real-time communication module is used to enable bidirectional communication between the intelligent equipment cluster and the backend server. The front-end interface connects to the back-end server; The front-end interface includes a real-time status interface and a task management interface. Users can also use the front-end interface to assign tasks, adjust task priorities, and monitor task execution. The real-time status interface is an interactive digital twin, including information on the intelligent equipment cluster and environmental information; Among them, intelligent equipment cluster information includes sensor data and location information of each device in the intelligent equipment cluster; Environmental information includes sensor data from the environment and video streams returned by the construction site monitoring system; The task management interface includes the material management interface, the task publishing interface, and the task progress interface; The backend server includes a layered planning architecture and a hybrid control structure system; specifically, the layered planning architecture and hybrid control structure system includes a top-level planning layer, a middle-level behavior layer, and a bottom-level execution layer; The top-level planning layer includes formulating task allocation strategies, planning the paths of each device in the intelligent equipment cluster, and synchronously updating the task allocation module and task conflict resolution module of the material transportation system. The middle-level behavior layer includes an action planning module that autonomously plans single-task paths based on global information obtained from the top-level planning layer and exchanges information with other intelligent equipment; The underlying execution layer includes a navigation control module, a map generation and update module, and a local path planning module for making real-time decisions on short-term actions and for avoiding obstacles or adjusting routes in real time based on dynamic changes in the scene.

2. The unmanned material transport system as described in claim 1, characterized in that: Intelligent equipment for horizontal transport includes horizontal transport platform vehicles, automated guided forklifts, and bulk material transport robots; The horizontal transport platform vehicle includes a body, an omnidirectional steering chassis located at the bottom of the body, a cargo platform located on the body, and a passive protection module located on the body. An automated guided forklift includes a body, an omnidirectional steering chassis located at the bottom of the body, and automated forks and telescopic pallet jacks mounted on the body. The material handling robot includes a body, an omnidirectional steering chassis located at the bottom of the body, and an automatic clamping module located on the body.

3. The unmanned material transport system as described in claim 1, characterized in that: Palletizing robots include fixed palletizing robots and mobile palletizing robots. Fixed palletizing robots are directly fixed to the installation, while mobile palletizing robots have a mobile chassis at the bottom of the robot body. Both fixed and mobile palletizing robots have an end-effector vision module on their robotic arms.

4. A material transport method using the unmanned material transport system as described in claim 1, characterized in that: Includes the following steps: Publish tasks and adjust task priorities through the front-end interface; The backend server obtains the status and environmental information of each device in real time through the sensors of each device in the intelligent equipment cluster, and displays the feedback through the front-end interface. The task allocation module in the backend server performs task allocation, task path planning, and task scheduling for each device in the intelligent equipment cluster based on the published tasks. The backend server monitors the execution status of each task and the status of each device in the intelligent equipment cluster, and displays the feedback through the front-end interface; When the backend server detects conflicts between tasks, the task conflict resolution module in the backend server adjusts the conflicting tasks in a timely manner until the tasks no longer conflict with each other. The action planning module in the backend server forms global information based on all assigned task paths and environmental information, and divides each individual task into several actions. Each action is executed by the corresponding device in the intelligent equipment cluster. By defining the state, action sequence and constraints of a single action, the device in the intelligent equipment cluster executes the corresponding action according to the changes in environmental information and control task instructions. After receiving the global single task paths, the navigation control module in the backend server determines a global path that conforms to the task instructions from the map based on the prior generated map and task allocation, and sends the control to the devices of the intelligent equipment cluster to drive along the global path. After the backend server detects obstacle information on the path through the sensors of each device in the intelligent equipment cluster, it triggers local planning adjustment conditions. The local path planning module of the backend server uses the previously calculated path as the basis for adjustment, adjusts the cost of the affected nodes, updates a cost map in real time, and calculates the original actual value from the target point to the adjacent node and the heuristic value from the current node to the adjacent node to minimize the actual path length from the current node to the target node. The nodes that need to be readjusted are managed by using a task priority queue to minimize redundant calculations. The specific process of task allocation module for planning task paths for each device in the intelligent equipment cluster is as follows: process the environmental road node map to determine the nodes that each device in the intelligent equipment cluster can pass through and occupy; construct a cost matrix; based on the cost matrix and combined with the principle of "low-priority tasks slow down and avoid, high-priority tasks accelerate through", allocate task paths to each device in the intelligent equipment cluster, and ensure that only a single device in the intelligent equipment cluster occupies a map node within a time step.

5. The material transportation method as described in claim 4, characterized in that: The cost matrix includes the task travel time, completion time, path length of the equipment in the intelligent equipment cluster, as well as the capacity utilization rate of each equipment in the intelligent equipment cluster, the types of equipment involved, and the task priority.

6. The material transportation method as described in claim 4, characterized in that: After a single task is completed, during the device's return process, it searches for the nearest location of the start and end points of associated idle tasks; during the task connection process, it shares paths and assigns idle real-time tasks in the vicinity to devices in the intelligent equipment cluster that are about to finish their tasks.

7. The material transportation method as described in claim 4, characterized in that: Before each task assignment, obtain the status of all devices in the intelligent equipment cluster. If a single device is low on power, search for the nearest charging station, send the coordinates directly, and prioritize scheduling the device to go to the charging station.

8. The material transportation method as described in claim 4, characterized in that: The task conflict resolution module checks for conflicts between task paths. If a conflict is found, it modifies the current path to avoid the conflict by rerouting to an alternative path or delaying the movement of the previous node, or by updating constraints, until all paths are conflict-free.

9. The material transportation method as described in claim 4, characterized in that: The map generation and update module in the backend server generates a high-precision road map by pre-recording road trajectories and processing them. Based on this, a structural topology map is generated to facilitate front-end interface operation and path planning. During execution, the map is updated in real time through sensor data collection from various devices in the intelligent equipment cluster.

10. The material transportation method as described in claim 4, characterized in that: The actions in a single task include material handling, transportation, and unloading. In the material handling process, the entire stack of materials is either loaded onto a horizontal conveyor by a palletizing robot or directly by a palletizing robot. The transportation process includes intra-floor transportation and inter-floor transportation. Intra-floor transportation involves using intelligent horizontal transportation equipment to transport goods from the origin point A to the target point B on the same floor. Inter-floor transportation involves using intelligent horizontal transportation equipment to enter the assigned intelligent construction elevator from the origin point C on the original floor. The intelligent construction elevator then lifts the intelligent horizontal transportation equipment vertically to the target floor, and the equipment exits from the elevator to the target point D on the target floor. The unloading process involves either using a palletizing robot or directly unloading the entire stack of materials to the target location.

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