Multi-terminal cooperative control system and method for industrial spraying equipment

Abstract

The invention discloses a multi-terminal cooperative control system and method for industrial spraying equipment, and belongs to the technical field of robot control. The system is composed of an application layer, a back-end layer and an interaction layer, the application layer is used for achieving state data extraction, operation parameter analysis and motion control instruction issuing of multiple devices, and the back-end layer is responsible for work order scheduling, task execution and device control logic processing, receives an instruction from a human-computer interaction interface of the interaction layer and issues the instruction to the application layer. And the interaction layer is responsible for establishing a human-computer interaction interface and defining a proto file required by gRPC communication so as to realize human-computer interaction and state monitoring. Cross-platform interaction from the browser to the server side is achieved through the gRPC protocol, cooperative control over the mechanical arm and the RGV module is supported, a closed-loop system from work order driving to control execution to state feedback is formed, and the efficiency and accuracy of the operation process of the spraying robot are improved.

Description

Technical Field

[0001] This invention belongs to the field of industrial automation and robot control technology, specifically relating to a multi-terminal collaborative control system and method for industrial spraying equipment. Background Technology

[0002] In recent years, with the rapid development of intelligent manufacturing and industrial automation technologies, industrial robots have been widely used in scenarios such as painting, grinding, welding, and material handling. Among them, painting robots, with their high precision and high consistency, are widely used in automobile manufacturing, parts processing, and other fields. A painting robot system typically consists of a robotic arm, a control cabinet, an industrial computer, and host computer control software. The planning and execution of the painting path are achieved through control commands from the host computer.

[0003] Existing painting robot control systems mostly adopt a centralized architecture, with the control core primarily deployed on a host computer running in a Windows platform software environment. Communication between the host computer and the underlying industrial control computer, PLC, sensors, and actuators is generally achieved through protocols such as serial ports (RS232 / RS485), TCP / IP, or CAN bus. These systems typically require binding to a specific model or brand of industrial control computer, resulting in high coupling between the software interface and the hardware platform. This leads to difficulties in system portability and expansion. When adding new functions or connecting new devices, it is often necessary to recompile the software or modify the underlying communication protocol, causing complex maintenance and high update costs.

[0004] Furthermore, the existing spraying robot control software operates with separate work order management and robot control modules, lacking a unified task scheduling and information management mechanism. Spraying tasks typically rely on manual work order creation, parameter setting, and manual triggering, resulting in a high degree of human involvement and low automation throughout the process. Data sharing between different tasks is difficult, hindering the reuse and optimization of spraying parameters. Summary of the Invention

[0005] To address the problems of existing spray painting robot control systems, such as system closure, rigid control logic, low intelligence level, and insufficient real-time performance, the present invention aims to provide a multi-terminal collaborative control system and method for industrial spray painting equipment.

[0006] The objective of this invention is achieved through the following technical solution: a multi-terminal collaborative control system for industrial spraying equipment, comprising: an application layer, a backend layer, and an interaction layer; The application layer is used to extract status data of multiple devices, parse operating parameters, and issue motion control commands. The devices include a robotic arm, an RGV trolley, a PLC controller, and a battery power supply module. By collecting, analyzing, and synchronizing the status of the devices in real time, the spraying trajectory, speed, posture, and motion path are controlled to achieve collaborative spraying operations of multiple devices. The backend layer includes a gRPC server and a database. The gRPC server is used to receive requests from the interaction layer, perform work order scheduling, task execution and equipment control logic processing, send control commands to the application layer and receive equipment status feedback through bidirectional streaming communication. The database is used to store work order information, spraying parameters, equipment operating status, execution records and historical task information, and provide persistent data access support to the gRPC server. The interaction layer includes a web-based human-computer interaction interface and defines a proto file. The web-based human-computer interaction interface interacts with the backend layer through the gRPC-Web communication mechanism, receiving and displaying work order content, equipment status, painting progress, and feedback information. At the same time, the communication message structure is uniformly described by defining the proto file, realizing unified data format, interface consistency, and cross-platform communication between the interaction layer, the backend layer, and the application layer.

[0007] Furthermore, the application layer includes a gRPC client, within which a multi-device control algorithm is deployed to control the robotic arm, RGV vehicle, PLC controller, and battery power supply module.

[0008] Furthermore, the gRPC client includes: real-time data interaction and bidirectional streaming communication between devices based on the gRPC communication mechanism; the robotic arm operates based on a Linux controller, receives motion commands issued by the server through the gRPC interface and provides real-time status feedback; the PLC controller receives control commands from the server for the RGV vehicle through the gRPC channel and uploads the operating status; and the battery power supply module communicates periodically with the server through the gRPC interface.

[0009] Furthermore, the application layer includes a multi-device state synchronization mathematical model. Based on interpolation and prediction algorithms, it performs real-time state synchronization calculations for the robotic arm and the RGV vehicle, wherein the device synchronization constraints satisfy: , and The states of the robotic arm and the RGV vehicle at time t are respectively. When the threshold ε is exceeded, the system compensates for the state based on the interpolation compensation algorithm and the prediction model to achieve collaborative control of multiple devices.

[0010] Furthermore, the backend layer includes a work order scheduling module and a task execution module, which form a transmission unit with the proxy server based on the gRPC-Web protocol to realize data transmission between the work order scheduling module and the task execution module and the interaction layer.

[0011] Furthermore, the database of the backend layer includes: recording spraying parameters and trajectory information during the execution of the spraying task, and automatically loading matching spraying parameters when the same spraying target is received.

[0012] Furthermore, the interaction layer is implemented based on the Web platform and can run on PCs, tablets, and mobile devices, supporting multiple terminals to be online simultaneously and maintaining real-time synchronized interface status.

[0013] Furthermore, the proto file is used to define the data communication structure between the interaction layer, the backend layer, and the application layer. The proto file includes device status messages, work order messages, control command messages, and response messages.

[0014] Furthermore, the device status message is used to describe the real-time status including the robotic arm pose, spraying speed, spraying flow rate, spraying pressure, RGV cart position, battery voltage, and temperature; the work order message is used to describe the vehicle brand, VIN code, sprayed parts, spraying parameters, and work order execution status; the control command message is used to define the structured format of robotic arm trajectory commands, posture adjustment commands, spraying parameter commands, and RGV cart movement commands; and the response message is used to return task execution results, device feedback, and status update information in gRPC bidirectional streaming communication.

[0015] This invention also provides a multi-terminal collaborative control method for industrial spraying equipment, comprising the following steps: The application layer implements the extraction of status data of multiple devices, parsing of operating parameters, and issuance of motion control commands. The devices include a robotic arm, an RGV trolley, a PLC control unit, and a battery power supply module. By collecting, analyzing, and synchronizing the status of the devices in real time, the control of the spraying trajectory, speed, posture, and motion path is completed, realizing the collaborative spraying operation of multiple devices. A gRPC server and database are built in the backend layer. The gRPC server is responsible for work order scheduling, task execution and equipment control logic processing. It receives requests from the interaction layer, sends control commands to the application layer through bidirectional streaming communication and receives equipment status feedback. The database is used to store work order information, spraying parameters, equipment operating status, execution records and historical task information, and provides persistent data access support to the gRPC server. A web-based human-computer interaction interface and a defined proto file are constructed in the interaction layer. The web-based human-computer interaction interface interacts with the backend layer through the gRPC-Web communication mechanism, receiving and displaying work order content, equipment status, painting progress and feedback information. At the same time, the communication message structure is uniformly described by defining the proto file, so as to realize the data format unification, interface consistency and cross-platform communication between the interaction layer, the backend layer and the application layer.

[0016] The beneficial effects of this invention are as follows: Compared with existing painting robot control software on the market, this invention has significant advantages. Existing software typically deploys its control core on a host computer, requiring the software to be bound to a specific industrial control computer model. This results in high coupling between the interface and hardware, and the need to modify the underlying protocol or compile the program when adding new functions or connecting new devices, leading to complex maintenance and difficult expansion. In contrast, this invention achieves modular design for work order management, parameter configuration, and robot control through a front-end / back-end separation architecture, significantly reducing system coupling and improving system scalability and maintainability. Furthermore, the work order management and painting control modules are independent, lacking a unified management mechanism for task scheduling. Painting parameters rely on manual configuration, resulting in low automation and overall low operating efficiency. This invention unifies the scheduling of the work order management module and the robot control module. The system can collaboratively control the robotic arm and RGV vehicle to move according to different work order information (brand, vehicle model, painting parts, etc.), achieving standardization and automation of painting tasks, reducing manual intervention, and improving work efficiency and painting consistency. Attached Figure Description

[0017] Figure 1 This is an overall framework diagram of the invention; Figure 2 This is a diagram of the application layer structure of the present invention; Figure 3 This is a diagram of the gRPC communication structure of the present invention; Figure 4 This is a database structure diagram of the present invention; Figure 5 This is a schematic diagram of the gRPC communication proto file of this invention. Detailed Implementation

[0018] To enable those skilled in the art to better understand the technical solutions in the embodiments of this application, the technical solutions in the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art should fall within the protection scope of the embodiments of this application.

[0019] like Figure 1As shown, this embodiment of the invention provides a multi-terminal collaborative control system for industrial spraying equipment, including: an application layer, a backend layer, and an interaction layer.

[0020] The application layer is used to extract status data of multiple devices, parse operating parameters, and issue motion control commands. The devices include a robotic arm, an RGV trolley, a PLC controller, and a battery power supply module. By collecting, analyzing, and synchronizing the device status in real time, the spraying trajectory, speed, posture, and motion path are controlled to achieve collaborative spraying operations of multiple devices.

[0021] The backend layer includes a gRPC server and a database. The gRPC server is used to receive requests from the interaction layer, perform work order scheduling, task execution and equipment control logic processing, send control commands to the application layer and receive equipment status feedback through bidirectional streaming communication. The database is used to store work order information, spraying parameters, equipment operating status, execution records and historical task information, and provide persistent data access support to the gRPC server.

[0022] The interaction layer includes a web-based human-computer interaction interface and defines a proto file. The web-based human-computer interaction interface interacts with the backend layer through the gRPC-Web communication mechanism, receiving and displaying work order content, equipment status, painting progress, and feedback information. At the same time, the communication message structure is uniformly described by defining the proto file, realizing unified data format, interface consistency, and cross-platform communication between the interaction layer, the backend layer, and the application layer.

[0023] This invention also provides a multi-terminal collaborative control method for industrial spraying equipment, comprising the following steps: S1: Implement data extraction and motion control of physical objects of hardware devices at the application layer.

[0024] Specifically, such as Figure 2As shown, the application layer includes a gRPC client, within which a multi-device control algorithm is deployed. This algorithm controls the robotic arm, RGV vehicle, PLC controller, and battery power supply module. This invention employs the gRPC communication mechanism to achieve real-time data interaction and bidirectional streaming communication between control units. The gRPC server acts as the core control node, establishing stable gRPC stream connections with both the robotic arm control unit and the PLC control unit via a network interface, issuing control commands in real time and receiving device status feedback. The robotic arm operates on a Linux controller, receiving spraying trajectory, speed, and attitude control commands from the gRPC server via a gRPC interface, and uploading motion status and execution information in real time to achieve precise control and status monitoring of the spraying process. The PLC controller is responsible for the underlying control logic of the RGV vehicle, receiving travel, stop, and speed adjustment commands from the server via a gRPC channel, and uploading position, speed, and running status in real time to achieve coordinated movement between the vehicle and the robotic arm. The battery power supply module communicates periodically with the gRPC server via a gRPC interface. The gRPC server actively acquires battery status parameters every minute for energy consumption analysis and health management.

[0025] In the collaborative control system of this invention, multiple devices (such as robotic arms, RGV vehicles, battery-powered modules, etc.) need to maintain real-time synchronization. Therefore, a unified state synchronization mathematical model is introduced: ; in, Indicates the first Each device in time The state (velocity, position). Indicates the input of control commands. Indicates the sensor feedback parameters, This indicates the communication delay between the device and the control system.

[0026] Preferably, to ensure that devices can work in coordination at different time steps, the gRPC bidirectional streaming mechanism is used to exchange device states in real time, ensuring that the state differences of all devices are always within an acceptable range. The synchronization constraints between devices can be expressed by the following formula: ; in: and The robotic arm and the RGV vehicle were respectively in time The status is obtained in real time based on the gRPC protocol. This is the synchronization tolerance threshold. The system considers the devices to be synchronized; if If so, the interpolation compensation algorithm will be triggered.

[0027] The interpolation compensation algorithm is specifically as follows: given a set of known robotic arm position data points... and the corresponding speed data points The Lagrange polynomials for position interpolation and velocity interpolation are: ; ; in, Let Lagrange basis functions be defined as follows: ; Assume the position and velocity of the robotic arm are at time t. Given the position and velocity data as follows: ; According to the Lagrange interpolation method, the interpolation polynomials for position and velocity are as follows: ; ; Simultaneously, the system will run a prediction algorithm in parallel to predict the future state of the device based on historical state sequences, defining the state variables as follows: ; The state equations are defined as follows: ; The observation equation is defined as follows: ; in, Here is the state transition matrix. To control the input matrix, For the observation matrix, For process noise, To observe the noise, Let be the covariance matrix.

[0028] The predicted state for the next time step is obtained by combining Kalman filtering: ; Predict Interpolation compensation results The final compensation result is obtained by weighted fusion: ; in, It can adaptively adjust according to the system status.

[0029] The gRPC communication architecture enables the system to achieve high real-time and low-latency data interaction, ensuring multi-device collaborative control and status synchronization during the spraying task execution process.

[0030] S2: Build a gRPC server and database in the backend layer.

[0031] like Figure 3 As shown, the communication process of this invention is implemented through a gRPC server, a web client, and a gRPC client. The web client supports deployment on multiple devices, such as PCs, tablets, and mobile phones. The gRPC server is responsible for scheduling work orders and issuing task instructions. It mainly handles the overall system's operational logic and connects to the application layer and database through various API interfaces. It issues motion control instructions to the application layer, receives status updates uploaded by various hardware devices, and stores status and work order information in the database. The transmission unit, consisting of the gRPC-Web protocol and a proxy server, is responsible for data transmission between the gRPC client and the gRPC server. The gRPC client sends a data stream to the gRPC server, the gRPC server receives it and outputs a reply data stream, and the gRPC client responds and displays the data stream. The specific transmission process is as follows: S2.1: Front-end (interaction layer) request generation and sending; User operation commands are denoted as the input set: ; The front-end uses the gRPC-Web framework to handle input. Perform serialization to generate Protocol Buffers binary data packets. : ; in, This indicates the serialization function executed according to Protocol Buffers encoding rules. The front end will... Send to the proxy layer via HTTP / 1.1 protocol.

[0032] S2.2: Proxy layer protocol conversion; Envoy, acting as an independent middleware node, executes protocol mapping functions on received HTTP / 1.1 messages: ; in, This indicates that the proxy server Envoy is used to map the HTTP / 1.1 message structure to the HTTP / 2 frame structure, while preserving the message body. The binary content remains unchanged.

[0033] The transformed data stream selects its target based on the request path r: ; And forward it to the corresponding cloud gRPC service node. .

[0034] S2.3: Cloud (backend) parsing and task execution; Cloud reception Deserialization is performed using Protocol Buffers deserialization functions: ; Obtain the set of robotic arm parameters from the human-computer interaction interface. .

[0035] The server uses the set Calling robot control functions : ; in, The final task execution result is then serialized again into a response packet using Protocol Buffers encoding rules. .

[0036] S2.4: Response feedback.

[0037] Envoy performs reverse protocol mapping: ; The result is then returned to the client via HTTP / 1.1, and the client parses the response. ; Through the above mapping link, the front-end and back-end of the communication layer, logic layer and deployment layer are completely separated, and the device status and execution feedback are finally displayed on the interface.

[0038] like Figure 4 As shown, the database stores the following information: work order information, battery status, and robotic arm status. The work order information includes vehicle brand, license plate number, vehicle signals, painted parts, and other vehicle-related information. The battery status includes battery charge, voltage, NTC temperature, and other statuses. The robotic arm status includes robotic arm pose and trajectory.

[0039] S3: Build the web-based human-computer interaction interface and define the proto file in the interaction layer; like Figure 5The diagram shows a schematic of the proto definition for a hardware device. Proto uses a binary serialization format, which, compared to text formats such as JSON or XML, results in smaller data size and faster encoding and decoding speeds. This significantly reduces network bandwidth usage and improves communication efficiency, making it particularly suitable for data interaction scenarios requiring high real-time performance in robot control. Furthermore, proto natively supports multi-language code generation and can automatically generate communication interface files in various language environments such as C++, Python, Go, and JavaScript.

[0040] In a preferred embodiment, the motion control commands issued by the application layer are mainly applied to the robotic arm, RGV vehicle, and battery-powered module. First, it is defined whether the device is in an operational state: Message Status { bool arm_status = 1; bool rgv_status = 2; bool battery_status = 3; } The robotic arm upload status is as follows: Message Pose { double x = 1; double y = 2; double z = 3; double rx = 4; double ry = 5; double rz = 6; } Message Trajectory { Pose pose = 1; double speed = 2; double flow_rate = 3; Double pressure = 4; } The RGV upload status is as follows: Message RGV { int32 point = 1; double x = 2; double y = 3; double rgv_speed = 4; } The battery-powered module upload status is as follows: Message battery { double voltage = 1; int32 current = 2; bool current_mode = 3; int32 quantity_electricity = 4; int32 tem = 5; } In a further application of this embodiment, the spraying robot operation and management system can be deployed in a distributed architecture. The industrial control computers of each workshop or spraying station operate independently as edge nodes, while the centralized server is responsible for unified work order scheduling and data aggregation management. The edge nodes can perform trajectory planning and spraying control tasks locally, and regularly upload operation logs and equipment status through the cloud interface to realize multi-station collaborative spraying and remote operation and maintenance management. This architecture can be flexibly expanded according to the number of production lines, supports parallel task scheduling of multiple robots, and significantly improves the production efficiency and robustness of the system.

[0041] Other embodiments of this application will readily occur to those skilled in the art upon consideration of the specification and practice of the disclosure herein. This application is intended to cover any variations, uses, or adaptations of this application that follow the general principles of this application and include common knowledge or customary techniques in the art not disclosed herein. The specification and embodiments are to be considered exemplary only.

[0042] It should be understood that this application is not limited to the precise structure described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from its scope.

Claims

1. A multi-terminal cooperative control system for industrial spraying equipment, characterized in that, The application layer, the backend layer and the interaction layer are included. The application layer is used for realizing state data extraction of multiple devices, running parameter analysis and motion control instruction issuing, the devices including a mechanical arm, an RGV trolley, a PLC controller and a battery power supply module, through real-time collection, analysis and synchronization of device states, control of spraying track, speed, posture and motion path, and realization of collaborative spraying operation execution of multiple devices. The backend layer includes a gRPC server and a database, wherein the gRPC server is used for receiving requests from the interaction layer, performing work order scheduling, task execution and device control logic processing, sending control instructions to the application layer and receiving device state feedback through bidirectional streaming communication, and the database is used for storing work order information, spraying parameters, device running states, execution records and historical task information, and providing persistent data access support for the gRPC server. The interaction layer includes a Web-based human-computer interaction interface and a proto file, the Web-based human-computer interaction interface interacts with the backend layer through a gRPC-Web communication mechanism, receives and displays work order content, device state, spraying progress and feedback information, and simultaneously uniformly describes communication message structures through the proto file to realize data format uniformity, interface consistency and cross-platform communication among the interaction layer, the backend layer and the application layer. The application layer includes a gRPC client, multiple device control algorithms are deployed in the gRPC client, and the mechanical arm, the RGV trolley, the PLC controller and the battery power supply module are controlled through the control algorithms.

2. The system of claim 1, wherein, The gRPC client includes real-time data interaction and bidirectional streaming communication among devices based on a gRPC communication mechanism, the mechanical arm runs based on a Linux controller, receives motion instructions issued by the server through a gRPC interface and feeds back states in real time, the PLC controller receives control instructions of the RGV trolley from the server through a gRPC channel and uploads running states, and the battery power supply module communicates with the server periodically through a gRPC interface.

3. The system of claim 2, wherein, The backend layer includes a work order scheduling module and a task execution module, a transmission unit is formed based on a gRPC-Web protocol and a proxy server to realize data transmission between the work order scheduling module, the task execution module and the interaction layer.

4. The system of claim 2, wherein, The application layer is provided with a multi-device state synchronization mathematical model, and the real-time states of the mechanical arm and the RGV trolley are synchronously calculated based on interpolation and prediction algorithms, wherein the device synchronization constraint satisfies: , and are the states of the mechanical arm and the RGV trolley at time t respectively, and when the threshold value ε is exceeded, the system compensates the state based on an interpolation compensation algorithm and a prediction model, thereby realizing collaborative control of multiple devices.

5. The system of claim 1, wherein, The database of the backend layer includes spraying parameter and track information recorded during spraying task execution, and spraying parameters matched with the same spraying target are automatically loaded when the same spraying target is received.

6. The system of claim 1, wherein, The interaction layer is realized based on a Web terminal and can run on a PC, a tablet and a mobile terminal, supports multiple terminals online at the same time and maintains a real-time synchronous interface state.

7. The system of claim 1, wherein, The proto file is used for defining data communication structures among the interaction layer, the backend layer and the application layer, and includes device state messages, work order messages, control instruction messages and response messages.

8. The system of claim 1, wherein, ​ 9. The system of claim 8, wherein, The device state message is used to describe real-time states including mechanical arm pose, spraying speed, spraying flow, spraying pressure, RGV trolley position, battery voltage and temperature; the work order message is used to describe vehicle brand, VIN code, spraying component, spraying parameter and work order execution state; the control instruction message is used to define the structured format of mechanical arm trajectory instruction, pose adjustment instruction, spraying parameter instruction and RGV trolley movement instruction; the response message is used to return task execution result, device feedback and state update information in gRPC bidirectional streaming communication.

10. A multi-terminal cooperative control method for industrial spraying equipment, characterized in that, The method comprises the following steps: In the application layer, the state data of multiple devices is extracted, the running parameter is analyzed and the motion control instruction is issued, the devices include a mechanical arm, an RGV trolley, a PLC control unit and a battery power supply module, through real-time collection, analysis and synchronization of device states, the control of spraying trajectory, speed, pose and motion path is completed, and the spraying operation execution of multiple devices is realized; In the backend layer, a gRPC server and a database are constructed, wherein the gRPC server undertakes the processing of work order scheduling, task execution and device control logic, receives requests from the interaction layer, sends control instructions to the application layer and receives device state feedback through bidirectional streaming communication; the database is used to store work order information, spraying parameters, device running state, execution record and historical task information, and provides persistent data access support for the gRPC server; In the interaction layer, a Web-based human-computer interaction interface and a proto file are constructed, the Web-based human-computer interaction interface interacts with the backend layer through the gRPC-Web communication mechanism, receives and displays work order content, device state, spraying progress and feedback information; at the same time, the proto file is used to uniformly describe the communication message structure, so as to realize data format unification, interface consistency and cross-platform communication among the interaction layer, the backend layer and the application layer.

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