Intelligent unmanned factory control method and system

Abstract

The invention provides an intelligent unmanned factory control method and system, the intelligent unmanned factory control method is suitable for a multi-terminal interaction system, the multi-terminal interaction system comprises an intelligent mcc device server and a plurality of different types of robots, and the intelligent unmanned factory control method is used for the intelligent mcc device server. The method comprises the following steps: acquiring a two-dimensional code of a gas cylinder and a serial number of a corresponding sensor; analyzing the two-dimensional code and the serial number of the sensor, and obtaining regional nodes and gas cylinder information; robot numbers and path information are determined according to the area nodes and the gas cylinder information; and sending a task instruction to the target robot according to the robot number and the path information, and executing a robot task. The technical problem that in the prior art, cooperative planning and cooperative control of multiple robots of an intelligent unmanned factory are difficult is solved.

Description

Technical Field

[0001] The present application belongs to the technical field of gas and liquid supply, and relates to an intelligent unmanned factory control method and system. Background Art

[0002] With the transformation and upgrading of the manufacturing industry, more and more companies are beginning to seek intelligent and automated production solutions. As a representative of advanced manufacturing, intelligent unmanned factories have broad market prospects and huge development potential.

[0003] The application of multi-robots is not limited to the field of marine defense. In fact, the application demand of multi-robots in many fields such as industrial manufacturing is also gradually increasing. At present, multi-robots can be found in industrial manufacturing, warehousing and logistics, reconnaissance and monitoring, environmental monitoring, emergency rescue and other fields.

[0004] At present, the collaborative system for multiple robots involves three aspects: path planning, collaborative control and task allocation. At present, most smart factory control systems are based on real-time path management for different robots. When there are multiple robots with different functions in the entire smart factory control system performing different tasks, there are still many compatibility and unification issues in its overall management and control, especially collaborative perception, collaborative planning and collaborative control. There are still huge challenges. Summary of the invention

[0005] The present application provides a control method and system for an intelligent unmanned factory, which solves the technical problems of the collaborative planning and collaborative control difficulties of multiple robots in an intelligent unmanned factory in the prior art.

[0006] This application adopts the following technical solutions:

[0007] The present application provides a method for controlling an intelligent unmanned factory. The method for controlling an intelligent unmanned factory is applicable to a multi-terminal interactive system. The multi-terminal interactive system includes an intelligent MCC device server and multiple robots of different types. The method for controlling an intelligent unmanned factory is used for the intelligent MCC device server. The method includes:

[0008] Get the QR code of the gas cylinder and the number of the corresponding sensor;

[0009] Parse the QR code and sensor number to obtain regional node and gas cylinder information;

[0010] Determine the robot number and path information based on the regional node and gas cylinder information;

[0011] According to the robot number and path information, the task instructions are sent to the target robot to execute the robot task.

[0012] Optionally, before obtaining the QR code of the gas cylinder, the following steps are also included:

[0013] Receive truck information from the unloading area, including license plate, truck position and number of gas cylinders;

[0014] According to the truck information, confirm the forklift and distribute the forklift task. The forklift task is to transport the gas cylinder to the designated area by the designated forklift.

[0015] Optionally, parsing the QR code and the sensor number to obtain regional node and gas cylinder information includes:

[0016] According to the QR code, obtain the gas cylinder information such as gas type, pressure and weight;

[0017] And, according to the number of the sensor, the regional node is determined.

[0018] Optionally, determining the robot number and path information according to the regional node and the gas cylinder information includes:

[0019] Determine the corresponding robot number based on the current area node and gas cylinder information;

[0020] The pre-stored path information is read according to the robot number and sent to the target robot, or according to the robot number, the target robot is triggered to perform path planning in real time to obtain path information.

[0021] Optionally, according to the robot number and path information, a task instruction is sent to the target robot, and the execution of the robot task includes:

[0022] When the area node is a conveyor belt area, the target robot in the waiting area is called according to the gas type, pressure and weight attributes of the gas cylinder information and the robot number, where the target robot in the waiting area is the AGV docking robot;

[0023] And according to the corresponding path information, the task instructions are sent to the target robot and the robot tasks are executed, wherein the agv docking robot is used to transfer the gas cylinder from the conveyor belt outlet to the corresponding gas supply room door.

[0024] The present application also provides a method for controlling an intelligent unmanned factory. The method for controlling an intelligent unmanned factory is applicable to a multi-terminal interactive system. The multi-terminal interactive system includes an intelligent MCC device server and multiple robots of different types. The method for controlling an intelligent unmanned factory is used for an AGV docking robot. The method includes:

[0025] Receive task instructions sent by the intelligent MCC device server;

[0026] Obtain path information and execute robot tasks according to task instructions.

[0027] Optionally, when the AGV docking robot is waiting in the waiting area, it sends a start signal to the AMR robot and the AI ​​robot to complete the transportation of the gas cylinders to the corresponding gas supply room and the replacement of empty cylinders in the gas cylinder cabinet.

[0028] Optionally, after the empty bottle replacement is completed, the method further comprises: sending an empty bottle replacement completion signal to the smart MCC device server;

[0029] Receive the empty bottle return task instruction returned by the intelligent MCC device server;

[0030] Execute the empty bottle return task instruction to return the empty bottles to the conveyor belt.

[0031] The present application also provides an unmanned factory control system, including: an intelligent MCC device server and a plurality of different types of robots, the plurality of different robots at least including: a forklift, an AGV docking robot, an AMR robot and an AI robot;

[0032] The intelligent MCC device is used to first receive the truck information of the unloading area, which includes the license plate, truck position and the number of gas cylinders. According to the truck information, the forklift is confirmed and the forklift task is assigned. The forklift task is to transport the gas cylinders to the designated area by the designated forklift.

[0033] Secondly, obtain the QR code of the gas cylinder and the number of the corresponding sensor, parse the QR code and the number of the sensor, and obtain the regional node and gas cylinder information; determine the robot number and path information based on the regional node and gas cylinder information; send task instructions to the target robot based on the robot number and path information to execute the robot task;

[0034] Forklift, used to receive forklift tasks sent by the intelligent MCC device server and execute forklift tasks;

[0035] The docking robot is used to receive task instructions sent by the intelligent MCC device server, obtain path information according to the task instructions and execute robot tasks.

[0036] The beneficial effects of this application are:

[0037] First of all, this application provides a specific and feasible intelligent unmanned factory control system, which replaces the existing technology in which most factory operations are performed by workers, realizes the intelligent integration of the factory, improves the factory's operating efficiency and saves investment costs.

[0038] Secondly, the application adopts intelligent MCC equipment and intelligent MCC equipment server to solve the problems of collaborative perception, collaborative planning and collaborative control of multiple robots in the entire intelligent factory. Intelligent MCC equipment and its server can also provide motor position and speed servo control functions for multiple robots, as well as detailed equipment operation data and status information, which is convenient for electrical personnel to perform equipment maintenance and repair work.

[0039] Finally, based on the current intelligent factory multi-robot execution tasks, each robot is generally required to perform path planning in real time, which poses challenges to the efficiency of real-time interaction between devices and large amounts of data processing. This application adopts the method of setting a QR code on each cargo, which contains cargo information (for example, gas cylinder information), so that the server can accurately distinguish the categories of cargo. The most important thing is that the QR code can not only directly store the robot's path information, but also call the robot's path information pre-stored in the server in real time according to the parsing results of the QR code, reducing the robot's operating burden. In addition, through the QR code, path planning instructions can be issued to the robot to control the robot to perform path planning in real time. Through these three methods, the problem of robot path planning timeliness is solved, and the robot's work efficiency is greatly improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] Figure 1 A step diagram of an intelligent unmanned factory control method provided in this application.

[0041] Figure 2 A schematic diagram of an intelligent unmanned factory model provided for this application.

[0042] Figure 3 A communication system for an intelligent unmanned factory control system is provided in this application.

[0043] Figure 4 A distribution diagram of a host computer and a slave computer provided for this application. DETAILED DESCRIPTION

[0044] In order to enable those skilled in the art to better understand the solution of the present application, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present application.

[0045] It should be noted that the terms "first", "second", etc. in the specification and claims of the present application and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments of the present application described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any of their variations are intended to cover non-exclusive inclusions, for example, a process, method, method, product or device comprising a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0046] The present application is further described in detail below with reference to the accompanying drawings:

[0047] The present application provides a smart unmanned factory control method, which is applicable to a multi-terminal interactive system. The multi-terminal interactive system includes a smart MCC device server and multiple robots of different types. As shown in 1, the smart unmanned factory control method is used for the smart MCC device server. It should be noted that the method steps include S101-S104, but are not limited to steps S101-S104, and the order of the implemented method steps is not limited to the current step order.

[0048] Combination Figure 2 , Figure 2 A schematic diagram of an intelligent unmanned factory model is given. In a specific factory model, it mainly includes a variety of basic equipment and functional areas such as the MCC equipment room, server room, gas supply room No. 1, gas supply room No. 2, gas supply room No. 3, inert gas storage room, corrosive gas storage room, cold storage room, forklift, conveyor belt, code scanning equipment, AGV docking robot, AMR robot and AI robot, central control room, robot automatic charging room, etc. It should be noted that the factory model mainly uses the intelligent MCC equipment to realize the collection of operating data of other equipment and the monitoring of operating status. A series of data interaction and data processing are performed by the intelligent MCC equipment server. In addition, the entire control system still requires a host computer (such as PLC) to automatically control it as a whole or the application software on the computer to assist in realizing visual interface operations, such as the display of some basic data and the prompt of fault signals. Specifically, the intelligent MCC and the host computer transmit data and issue instructions through a communication interface (such as field bus, Ethernet, etc.). As the control center of the system, the host computer can send control instructions to the intelligent MCC, such as starting and stopping the motor. At the same time, the intelligent MCC also feeds back the motor's operating status, fault information and other data to the host computer in real time so that the host computer can monitor and manage it.

[0049] like Figure 2As shown, the factory model includes: Gas Supply Room No. 1: Corrosive gas cylinder cabinets are placed in the red area; Gas Supply Room No. 2: Inert gas cylinder cabinets are placed in the green area; Gas Supply Room No. 3: Explosion-proof gas cylinder cabinets are placed in the yellow area. Refrigerator: Store gases that require a temperature below 0 degrees Celsius. Multifunctional maintenance room: Basic maintenance and accessories storage for forklifts, robots, gas cylinder cabinets, etc. Central control room: Responsible for fire and explosion safety in the factory area, pay close attention to the operating status of the equipment under monitoring, regularly inspect and repair the equipment in the machine room according to regulations, ensure the normal operation of the equipment system under monitoring, and report any abnormalities and failures of the equipment in a timely manner. Robot charging area: AMR0.0 robot automatic charging equipment, the robot automatically goes to the charging area to charge when the battery is less than 20%. Inert gas storage room: for storing inert, inactive gases; corrosive gas storage room: for storing corrosive and active gases. Server room: for storing all interactive data and data processing. It should be noted that only a specific intelligent unmanned factory model is given in this embodiment, which does not mean that the factory model only includes these basic facilities. The specific design can change, add or delete some facilities according to actual conditions to ensure that the factory further improves its infrastructure while meeting normal working requirements.

[0050] Based on this factory model, a feasible intelligent unmanned factory control method is described.

[0051] Based on the intelligent MCC device server, the following steps can be performed:

[0052] Optionally, before obtaining the QR code of the gas cylinder, the following steps are also included:

[0053] Receive truck information from the unloading area, including license plate, truck position and number of gas cylinders;

[0054] According to the truck information, confirm the forklift and distribute the forklift task. The forklift task is to transport the gas cylinder to the designated area by the designated forklift.

[0055] In one embodiment, an automated forklift is used for unloading. After the truck carrying the gas cylinders arrives, the monitoring and lidar scanner at the door are used to accurately read the truck's license plate, truck posture, and gas cylinder quantity information using the matching target recognition system, and then the information is fed back to the intelligent MCC device server. The intelligent MCC device server sends a forklift task to the forklift system, and after an idle forklift is designated to receive the forklift task, it obtains the set path and transports the gas cylinders to the designated area. It should be noted that in the unloading area, the forklift task includes moving the unloaded gas cylinders to the conveyor belt entrance or the gas storage room; it also includes moving the replaced air cylinders from the conveyor belt entrance back to the gas storage room.

[0056] After unloading is completed, the intelligent MCC device server then performs the following steps:

[0057] S101: Obtain the QR code of the gas cylinder and the number of the corresponding sensor;

[0058] S102: Parse the QR code and the sensor number to obtain regional node and gas cylinder information;

[0059] S103: Determine the robot number and path information according to the regional node and gas cylinder information;

[0060] S104: Sending a task instruction to the target robot according to the robot number and path information to execute the robot task.

[0061] In one embodiment, since the intelligent unmanned factory contains multiple functional areas, the areas mainly involving robot execution tasks include unloading areas, conveyor belts, waiting areas, gas supply rooms and other functional areas. And some gas types involved in the gas cylinders include inert gas (green): N2 (nitrogen) CF4 (carbon tetrafluoride), etc.; toxic and corrosive gases (yellow): GeF4 (germanium tetrafluoride) WF6 (tungsten hexafluoride), etc.; toxic, flammable, corrosive (red): NH3 (ammonia) CH3OH (methanol), etc. The storage and transportation routes of different types of gases are inconsistent. Therefore, when they are sent to different gas supply rooms, they need to be strictly classified in advance and the accurate line worker robots need to be determined to complete them.

[0062] Step S101, specifically, after the forklift places the gas cylinder on the conveyor belt for transportation, different sensors are installed at the conveyor belt, each sensor is set with a unique number, and specifically identifies the gas cylinder of a fixed type of gas, so as to realize the classification of the gas cylinder. This embodiment takes the gas cylinders of three types of gas as an example, and accurately identifies the gas cylinder information by scanning the gas cylinder on the conveyor belt and the QR code on the gas cylinder through the barcode identifier and monitoring radar hanging on the first door of the conveyor belt. And the number of the sensor monitoring radar corresponds to the regional node in advance. For this reason, by sending data to the intelligent MCC device server, the intelligent MCC device server can accurately obtain the regional node and gas cylinder information where the gas cylinder is currently detected, and then the intelligent MCC device server controls the corresponding AGV docking robot to perform the handling task.

[0063] It should be noted that in the above embodiment, the sensor on each door identifies gas cylinders of fixed gas types to achieve gas cylinder classification, and the corresponding numbered sensors are associated with the current area node, as well as the number of the robot corresponding to each type of gas and the path information to the next area node.

[0064] Specifically, S102: parsing the QR code and the sensor number, obtaining regional node and gas cylinder information includes:

[0065] According to the QR code, obtain the gas cylinder information such as gas type, pressure and weight;

[0066] And, according to the number of the sensor, the regional node is determined.

[0067] Optionally, determining the robot number and path information according to the regional node and the gas cylinder information includes:

[0068] Determine the corresponding robot number based on the current area node and gas cylinder information;

[0069] The pre-stored path information is read according to the robot number and sent to the target robot, or according to the robot number, the target robot is triggered to perform path planning in real time to obtain path information.

[0070] In one embodiment, for a large intelligent unmanned factory, the electrical equipment and robots involved are extremely complex. In particular, for robots in many factories, it is necessary to pre-store the global information of the entire factory environment and plan the path according to the actual task instructions. This undoubtedly poses a severe challenge to the real-time operation and management of the entire factory. In order to improve the operating efficiency of the robot, for simple robot path information, a format can be designed to directly store the robot's path information through a QR code. The path information can include a series of coordinate points, direction instructions or other navigation data. For example, the JSON format can be used to represent the path. When the intelligent MCC device server obtains the QR code, it is parsed and the parsed regional node, gas cylinder information, corresponding robot number and path information are sent to the target robot, thereby controlling the target robot to immediately perform its robot task.

[0071] In one embodiment, in order to achieve flexible adjustment, when the QR code does not contain the path information of a certain type of robot, the intelligent MCC device server needs to determine the number of the corresponding robot based on the parsed regional node and gas cylinder information, and retrieve the path information of the robot pre-stored in the server, and send the path information together with the robot task to the target robot, so as to control the target robots in different areas to perform their robot tasks, such as forklifts in the unloading area and AGV docking robots in the waiting area.

[0072] In one embodiment, AMR robots and AI robots need to determine the positions of gas cylinder cabinets and air cylinders to be replaced in real time in different gas supply rooms. There are many situations in their operation trajectories, and it is impossible to obtain their accurate path information through a QR code. For such robots, the intelligent MCC device server needs to determine the corresponding robot based on the parsed regional nodes and gas cylinder information. When issuing robot tasks, it is also necessary to give path planning instructions. The robot needs to perform path planning on its own and complete the robot task.

[0073] It should be noted that storing robot paths through QR codes is a simple and effective method that can quickly transmit path information. This method is particularly suitable for scenarios that require rapid deployment or where path information changes frequently. In order to achieve more complex situations, multi-robot path planning and deployment, the flexible control strategy of the intelligent MCC device server in this embodiment is also required to achieve the effect of efficient management and scheduling of multiple robots and improve the overall operation efficiency of the factory.

[0074] Optionally, when the area node is a conveyor belt area, the target robot in the waiting area is called according to the gas type, pressure and weight attributes of the gas cylinder information and the robot number, wherein the target robot in the waiting area is an AGV docking robot; and according to the corresponding path information, task instructions are sent to the target robot, and the robot task is executed, wherein the AGV docking robot is used to transfer the gas cylinder from the conveyor belt outlet to the corresponding gas supply room door.

[0075] The present application also provides a method for controlling an intelligent unmanned factory. The method for controlling an intelligent unmanned factory is applicable to a multi-terminal interactive system. The multi-terminal interactive system includes an intelligent MCC device server and multiple robots of different types. The method for controlling an intelligent unmanned factory is used for an AGV docking robot. The method includes:

[0076] Receive task instructions sent by the intelligent MCC device server;

[0077] Obtain path information and execute robot tasks according to task instructions.

[0078] Optionally, when the AGV docking robot is waiting in the waiting area, it sends a start signal to the AMR robot and the AI ​​robot to complete the transportation of the gas cylinders to the corresponding gas supply room and the replacement of empty cylinders in the gas cylinder cabinet.

[0079] Optionally, after the empty bottle replacement is completed, the method further comprises: sending an empty bottle replacement completion signal to the smart MCC device server;

[0080] Receive the empty bottle return task instruction returned by the intelligent MCC device server;

[0081] Execute the empty bottle return task instruction to return the empty bottles to the conveyor belt.

[0082] This application also provides an embodiment of a complete intelligent MCC device server interacting with multiple different types of robots. The specific process is as follows:

[0083] When the truck arrives at the unloading area, the system's lidar automatically scans the license plate, cargo quantity, gas cylinder information and other information, and then sends a signal to the intelligent MCC device server. After receiving the signal, the intelligent MCC device server distributes the task to the forklift system. After receiving the signal, the forklift arrives at the designated route and transports the gas cylinders to the conveyor belt or gas storage room.

[0084] After the forklift places the gas cylinder on the conveyor belt, it passes through the scanner and monitoring equipment on the first door of the conveyor belt and sends the data to the intelligent MCC device server. If the first door detects a matching gas cylinder, it will confirm the scanning result again through the second door. After passing through the third door, the data will be sent to the MCC device again, and the gas cylinder will reach the waiting area from the conveyor belt exit.

[0085] After receiving the signal, the intelligent MCC equipment server sends the signal to the AGV docking robot in the waiting area. After receiving the signal, the AGV docking robot automatically reaches the conveyor belt exit and moves the gas cylinder to the waiting area at the door of the gas supply room to wait.

[0086] After arriving at the waiting area, the AGV robot sends a signal to start the AMR robot and the AI ​​robot. The AMR robot and the AI ​​robot arrive at the door of the waiting area, carry the gas cylinder to the gas supply room, and then transport it to the location of the gas cylinder cabinet that needs to be replaced. After the gas cylinder is replaced by the AI ​​robot and the AMR's mechanical arm, the AMR robot puts the air cylinder in the gas cylinder cabinet back to the docking rack at the door waiting area.

[0087] After all the gas is replaced, the AGV docking robot in the waiting area moves the air bottle to the conveyor belt and returns. After the conveyor belt door scanner recognizes the air bottle, it sends a signal to the intelligent MCC device server again.

[0088] After receiving the signal, the intelligent MCC device server distributes it to the forklift system again. The forklift system assigns the forklift task to the designated forklift. After receiving the signal, the forklift arrives at the entrance of the conveyor belt and then transports the air bottle back to the gas storage room for storage, completing the robot task.

[0089] The present application also provides an unmanned factory control system, including: an intelligent MCC device server and multiple robots of different types, the multiple different robots include at least: a forklift, an AGV docking robot, an AMR robot and an AI robot.

[0090] The intelligent MCC device is used to first receive the truck information of the unloading area. The truck information includes the license plate, truck posture and the number of gas cylinders. According to the truck information, the forklift is confirmed and the forklift task is distributed. The forklift task is to transport the gas cylinders to the designated area by the designated forklift.

[0091] Secondly, obtain the QR code of the gas cylinder and the corresponding sensor number, parse the QR code and the sensor number, and obtain the regional node and gas cylinder information; determine the robot number and path information based on the regional node and gas cylinder information; according to the robot number and path information, send task instructions to the target robot to execute the robot task.

[0092] Optionally, the intelligent MCC device server is also used to obtain the QR code of the gas cylinder and also includes:

[0093] Receive truck information from the unloading area, including license plate, truck position and number of gas cylinders;

[0094] According to the truck information, confirm the forklift and distribute the forklift task. The forklift task is to transport the gas cylinder to the designated area by the designated forklift.

[0095] Optionally, parsing the QR code and the sensor number to obtain regional node and gas cylinder information includes:

[0096] According to the QR code, obtain the gas cylinder information such as gas type, pressure and weight;

[0097] And, according to the number of the sensor, the regional node is determined.

[0098] Optionally, determining the robot number and path information according to the regional node and the gas cylinder information includes:

[0099] Determine the corresponding robot number based on the current area node and gas cylinder information;

[0100] The pre-stored path information is read according to the robot number and sent to the target robot, or according to the robot number, the target robot is triggered to perform path planning in real time to obtain path information.

[0101] Optionally, task instructions are sent to the target robot based on the robot number and path information, and the execution of the robot task includes: when the area node is a conveyor belt area, calling the target robot in the waiting area based on the gas type, pressure and weight attributes of the gas cylinder information and the robot number, wherein the target robot in the waiting area is an AGV docking robot; and sending task instructions to the target robot based on the corresponding path information, and executing the robot task, wherein the AGV docking robot is used to transfer the gas cylinder from the conveyor belt outlet to the corresponding gas supply room door.

[0102] The forklift is used to receive forklift tasks sent by the intelligent MCC device server and perform forklift tasks; in addition to transporting goods from the door to the conveyor belt entrance during unloading, the forklift is also used to arrive at the conveyor belt entrance after receiving the empty bottle replacement completion signal sent by the intelligent MCC device server, and then transport the air bottle back to the gas storage room for storage to complete the forklift task.

[0103] The AGV docking robot is used to receive task instructions sent by the intelligent MCC device server, obtain path information according to the task instructions and execute robot tasks.

[0104] The AGV docking robot is also used to send a start signal to the AMR robot and the AI ​​robot when the AGV docking robot is waiting in the waiting area, to complete the transportation of the gas cylinders to the corresponding gas supply room and the replacement of empty cylinders in the gas cylinder cabinet.

[0105] Optionally, after completing the empty bottle replacement, the method also includes: sending an empty bottle replacement completion signal to the smart MCC device server; receiving an empty bottle return task instruction returned by the smart MCC device server; executing the empty bottle return task instruction to return the empty bottle to the conveyor belt.

[0106] It should be noted that the unmanned factory control system provided in this embodiment can implement an unmanned factory control method that is completely consistent with the above method embodiment, and therefore will not be described in detail.

[0107] It should be noted that the entire unmanned factory control system provided by this application mainly controls and manages the equipment containing motors in the factory through intelligent Mcc equipment and its server. It is not just forklifts, agv docking robots, AMR robots and AI robots. It also includes other equipment with motors in the entire factory. For this reason, it can be understood by those skilled in the art that in addition to the robots involved in this application, other equipment can be reasonably expanded on the server side of the intelligent mcc device according to the needs of factory functions. For example: using the motor control technology and network communication technology of the intelligent MCC device to control the distribution box of the overall equipment operation, to ensure the high-speed operation of the network control platform. Using open networks such as Profibus and ProfiNet PN that meet industrial standards, connecting the starting equipment of gas cylinder cabinets, forklifts, conveyor belts, robots, etc., including soft starters, inverters, intelligent motor protectors, etc., to obtain motor and load information from these devices, including current, voltage, overload, speed, etc. Through the network and the DCS and PLC of the system, the motor control information is transmitted to the corresponding equipment.

[0108] Specifically, in this embodiment, the full name of the GDS system is the combustible gas and toxic gas detection alarm system, abbreviated as Gas Detection System, which is built through the field bus and various communication protocols. In the production, storage and transportation process of enterprises, various types of combustible and toxic gases are often involved. The function of the GDS system is to monitor the status of each leakage source in real time and actively remind when there is a danger of leakage, so as to eliminate hidden dangers and ensure safe production.

[0109] like Figure 3 As shown, the central control room is connected to the switch via a network cable, and then connected to the server room, WIFI equipment and PLC equipment via a network cable.

[0110] The lower end connection equipment of the PLC equipment room includes the MCC equipment room, the gas cylinder cabinet, and the AGV robot. There are multiple intelligent MCC devices placed in the MCC equipment room, and each intelligent MCC device can control the motors of other equipment such as fans and compressors. PLC to MCC uses Ethernet connection; PLC to gas cylinder cabinet also uses Ethernet and adopts TCP communication protocol (the specific communication protocol is determined by the equipment in the cabinet). The connection method between PLC and AGV robot can be: the manufacturer's own communication protocol, WIFI connection or TCP protocol through PLC and AGV robot.

[0111] Specifically, Figure 4 As shown in the system flow chart, PLC is the central part of the system, and the upper part is called the upper computer, and the lower part is called the lower computer. The upper computer mainly includes the central control room, server room, printer and HIM; while the lower computer mainly includes intelligent MCC, sensor, gas cylinder cabinet and AGV robot. The whole system operates with PLC as the core to realize the real-time monitoring and alarm function of flammable gas and toxic gas. Among them, the upper computer is responsible for the monitoring, command issuance, data collection, processing and analysis, and user interaction of the entire control system. It processes complex algorithms, performs long-term data storage, and provides a graphical interface for user operation. The upper computer can also issue commands to monitor and coordinate the lower computer. The lower computer receives the instructions of the upper computer, performs corresponding actions according to the instructions, and returns the action results to the upper computer.

[0112] It should be noted that when the central control room mentioned in this application uses humanoid robots to fully automate the operation of gas cylinder cabinets in the semiconductor industry, the main matters that the central control room needs to monitor and manage are as follows:

[0113] 1. Gas status and balance monitoring

[0114] Real-time monitoring of the remaining gas volume and pressure status of the gas cylinders in each gas cylinder cabinet; when the gas cylinder status reaches a certain critical value, a notification is automatically sent for refilling or replacement.

[0115] 2. Leak detection and safety alarm

[0116] The gas leak sensor monitors the leak in real time and issues an alarm immediately when a leak is detected.

[0117] In dangerous situations, the robot can be set up to automatically cut off the gas supply.

[0118] 3. Temperature and humidity monitoring

[0119] Continuously check the temperature and humidity inside the gas cabinet to maintain optimal conditions.

[0120] Alerts are issued when temperature and humidity fall outside certain ranges so that action can be taken.

[0121] 4. Robot status and operation monitoring

[0122] Monitor the status of each robot in real time (power supply, battery level, network connection status, etc.).

[0123] When a job stops, a notification is sent to the control room for quick processing.

[0124] 5.Job log and data recording

[0125] Real-time recording of the operation status of the gas cylinder cabinet, the robot's operation records and all warning events.

[0126] Analyze operational efficiency and gas usage patterns through data logs.

[0127] 6. Automatic emergency response system

[0128] The robot is set up to take quick action in the event of an emergency such as a leak or fire.

[0129] Send real-time situation notifications to the control room and have the robot perform emergency evacuation measures.

[0130] 7. Real-time video monitoring and control

[0131] Confirm the operation status through CCTV and real-time video monitoring around the gas cylinder cabinet.

[0132] If necessary, the control room can control the robot's position and work path.

[0133] Through these systems, the central control room can comprehensively monitor the operating status and achieve efficient and safe gas management and operation.

[0134] Finally, it should be noted that the above embodiments are only used to illustrate the technical solution of the present application rather than to limit it. Although the present application has been described in detail with reference to the above embodiments, ordinary technicians in the relevant field should understand that the specific implementation methods of the present application can still be modified or replaced by equivalents, and any modifications or equivalent replacements that do not depart from the spirit and scope of the present application should be included in the scope of protection of the claims of the present application.

Claims

1. A method for controlling an intelligent unmanned factory, characterized in that: The intelligent unmanned factory control method is applicable to a multi-terminal interactive system, wherein the multi-terminal interactive system includes an intelligent MCC device server and a plurality of robots of different types. The intelligent unmanned factory control method is used for the intelligent MCC device server, and the method includes: Get the QR code of the gas cylinder and the number of the corresponding sensor; Parse the QR code and the sensor number to obtain regional node and gas cylinder information; Determine the robot number and path information according to the regional node and gas cylinder information; According to the robot number and path information, a task instruction is sent to the target robot to execute the robot task.

2. The intelligent unmanned factory control method according to claim 1, characterized in that: Get the QR code of the gas cylinder, which previously included: Receive truck information of the unloading area, the truck information including license plate, truck position and gas cylinder quantity information; According to the truck information, a forklift is confirmed and a forklift task is distributed, wherein the forklift task is to transport the gas cylinder to a designated area by a designated forklift.

3. The intelligent unmanned factory control method according to claim 1, characterized in that: Parse the QR code and the sensor number to obtain regional node and gas cylinder information, including: According to the QR code, obtain the gas cylinder information such as gas type, pressure and weight; And, according to the number of the sensor, the regional node is determined.

4. The intelligent unmanned factory control method according to claim 1, characterized in that: The robot number and path information are determined according to the regional node and the gas cylinder information, including: Determine the corresponding robot number according to the current regional node and gas cylinder information; The pre-stored path information is read according to the robot number and sent to the target robot, or the target robot is triggered to perform path planning in real time according to the robot number to obtain the path information.

5. The intelligent unmanned factory control method according to claim 1, characterized in that: According to the robot number and path information, a task instruction is sent to the target robot, and the robot task execution includes: When the area node is a conveyor belt area, the target robot in the waiting area is called according to the gas type, pressure size and weight attributes of the gas cylinder information and the robot number, wherein the target robot in the waiting area is an AGV docking robot; And according to the corresponding path information, a task instruction is sent to the target robot, and the robot task is executed, wherein the agv docking robot is used to transfer the gas cylinder from the conveyor belt outlet to the corresponding gas supply room door.

6. A method for controlling an intelligent unmanned factory, characterized in that: The intelligent unmanned factory control method is applicable to a multi-terminal interactive system, wherein the multi-terminal interactive system includes an intelligent MCC device server and multiple robots of different types. The intelligent unmanned factory control method is used for an AGV docking robot, and the method includes: Receive task instructions sent by the intelligent MCC device server; Acquire path information and execute robot tasks according to the task instructions.

7. The unmanned factory control method according to claim 6, characterized in that: When the AGV docking robot is waiting in the waiting area, it sends a start signal to the AMR robot and the AI ​​robot to complete the transportation of the gas cylinders to the corresponding gas supply room and the replacement of empty bottles in the gas cylinder cabinet.

8. The unmanned factory control method according to claim 7, characterized in that: After completing the empty bottle replacement, the method further comprises: Sending an empty bottle replacement completion signal to the smart MCC device server; Receiving the empty bottle return task instruction returned by the intelligent MCC device server; Execute the empty bottle return task instruction to return the empty bottle to the conveyor belt.

9. An unmanned factory control system, characterized in that: include: An intelligent MCC device server and multiple different types of robots, wherein the multiple different robots include at least: a forklift, an AGV docking robot, an AMR robot and an AI robot; The intelligent MCC device is used to first receive the truck information of the unloading area, the truck information includes the license plate, the truck position and the number of gas cylinders, and according to the truck information, confirm the forklift and distribute the forklift task, the forklift task is to transport the gas cylinders to the designated area by the designated forklift; Secondly, obtain the QR code of the gas cylinder and the number of the corresponding sensor, parse the QR code and the number of the sensor, and obtain the regional node and gas cylinder information; determine the robot number and path information according to the regional node and gas cylinder information; send a task instruction to the target robot according to the robot number and path information to execute the robot task; The forklift is used to receive the forklift task sent by the intelligent MCC device server and execute the forklift task; The docking robot is used to receive the task instructions sent by the intelligent MCC device server, obtain path information according to the task instructions and execute the robot task.

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