Robotic fast deployment base system and tool chain

Abstract

The invention provides a base system and a tool chain for quickly deploying a robot, abstract adaptation is performed on a base interface through an interface protocol to obtain a multi-available interface, adaptation to different brands of robots is realized, access of various robots is met, and a display interface is generated according to data information of the robot accessed based on the multi-available interface, so that the robot can be quickly deployed. Rapid operation and maintenance are achieved, the operation and maintenance period is shortened, rapid change of service logic is achieved by generating task deployment of the robot on the basis of production requirements in combination with display interface information, flexible manufacturing is better adapted, and finally the robot deployment efficiency is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of robot deployment, and particularly relates to a base system and a tool chain for rapid robot deployment. Background Art

[0002] Robots are the core force in the manufacturing industry and are widely used in fields such as automobile manufacturing, electronic manufacturing, and machining. They can complete tasks such as welding, painting, assembly, and handling, significantly improving production efficiency and product quality, while reducing labor costs and safety risks.

[0003] For existing robot deployments, the hardware interfaces of different brands are closed, the integration cycle is long, the operation and maintenance cost cycle is long and the cost is high. The functions of traditional base systems are fixed, making it difficult to quickly adapt to different business scenarios. The business logic is fixed and difficult to meet the needs of flexible production. There is a lack of full-process support from action design to business verification, resulting in low robot deployment efficiency. Summary of the Invention

[0004] The present invention provides a base system and a tool chain for rapid robot deployment to solve the problems raised in the background art.

[0005] A base system for rapid robot deployment includes: An interface abstraction module for abstractly adapting the base interface through an interface protocol to obtain multiple available interfaces; An interface generation module for generating a display interface for the data information of the robot connected based on the multiple available interfaces; A task deployment module for generating a task deployment for the robot based on production requirements and combining the information on the display interface.

[0006] In this embodiment, different types of robots correspond to different interface protocols. The base interface during abstract adaptation through the interface protocol satisfies different types of robots. When a robot is recognized, the corresponding interface adaptation is retrieved to implement connecting the robot to the base system.

[0007] Preferably, the interface abstraction module includes: A protocol determination unit for determining the connection interface protocols of each brand of robot based on the collected information and obtaining the access interface protocol of the base interface; A template establishment unit for establishing an abstract adaptation template for the connection interface protocol and the access interface protocol based on the protocol content of the connection interface protocol and the access interface protocol; An interface determination unit for connecting the abstract adaptation template to the base interface to obtain multiple available interfaces.

[0008] Preferably, the application of the interface abstraction module is as follows: After detecting that the robot is connected to the base system, obtain the connection interface protocol of the robot, and in combination with the access interface protocol of the base interface, retrieve the target abstract adaptation template that meets the requirements from the abstract adaptation template; After performing abstract adaptation on the interface protocol based on the target abstract adaptation template, obtain the currently available interface; Connect the data information of the robot to the base system based on the currently available interface.

[0009] Preferably, the interface generation module includes: A plug-in selection unit for selecting a plug-in that meets the requirements of the robot based on the data information of the robot accessed through multiple available interfaces; A plug-in configuration unit for configuring information for the plug-in based on the interface display requirements to obtain the configuration information of the plug-in; An interface generation unit for loading the plug-in based on the configuration information of the plug-in to generate a display interface.

[0010] Preferably, the task deployment module includes: An information acquisition unit for acquiring all the robots connected to the base system and the communication information with industrial equipment from the display interface information; A task deployment unit for generating a task deployment for the robot based on the production requirements, in combination with the behavior trees and communication information of all the robots.

[0011] Preferably, the template establishment unit includes: A model establishment unit for learning the data of the abstract adaptation process of the historical interface protocol to obtain the necessary description features in the abstract adaptation process, and establishing an abstract adaptation description model based on the necessary description features; An element determination unit for standardizing the connection interface protocol and the access interface protocol to obtain the target protocol content, and extracting the target content elements from the target protocol content through the abstract adaptation description model; A configuration unit for matching the target content elements based on an intelligent matching method, and performing conversion configuration on the element matching result based on a visual configuration tool to obtain an initial adaptation template; A priority definition unit for obtaining the basic template information, node template information, and application template information from the initial adaptation template, setting the basic template information as the third priority, the node template information as the second priority, and the application template information as the first priority, and optimizing the initial adaptation template to obtain a target adaptation template; A testing unit for performing a stability test on the target adaptation template based on an automated testing framework, and using it as the adaptation parent template after passing the test; A template derivation unit, which is used to obtain the business requirements that adapt to the parent template, obtain the extended business requirements with a similarity within a preset similarity range to the business requirements from a large database, and based on the extended business requirements, use an abstract adaptation description model to determine the modification content of the custom fields that adapt to the parent template and the added extended fields, so as to obtain an adapted derived template; A template storage unit, which is used to store the adapted parent template and the adapted derived template as abstract adaptation templates to obtain a template library.

[0012] Preferably, the testing unit includes: A stability testing unit, which is used to simulate a variety of application environments and perform stability testing on the target adaptation template using an automated testing framework to obtain performance data in each application environment; A stability judgment unit, which is used to determine the stability based on the performance data and judge whether the stability meets the stability requirements; If so, use the target adaptation template as the adapted parent template; Otherwise, determine that the target adaptation template is abnormal and return it to the configuration unit for reconfiguration.

[0013] Preferably, the task deployment unit includes: An analysis unit, which is used to analyze the production requirements based on an AI model to obtain real-time dynamic business rules, and based on the AI model, match the business rules with the nodes of the behavior trees of all robots, and obtain the structural characteristics of the behavior trees according to the matching results; A priority setting unit, which is used to determine the collaborative task characteristics of all robots based on the structural characteristics of the behavior trees, analyze the importance of the collaborative task characteristics based on the production requirements and the requirements of task execution, and establish the priority of each robot node based on the importance; A resource allocation unit, which is used to uniformly allocate resources for all robots based on the priority of each robot node and the collaborative task characteristics, combined with the communication information of all robots, to obtain a resource allocation result; A model establishment unit, which is used to establish a task execution model for all robots based on the structural characteristics of all robots, the priority of each robot node, and the resource allocation result, combined with the digital twin technology; A model connection unit, which is used to obtain the rule engine and the behavior tree nodes in the task execution model, and establish a first connection between the production requirements and the rule engine, and a second connection between the rule engine and the behavior tree nodes based on the AI model; A dynamic establishment unit, which is used to extract the priority collaboration mechanism in the task execution model, and when the production requirements change dynamically, based on the first connection and the second connection, combined with the priority collaboration mechanism, determine the latest structural characteristics and the latest resource allocation of the behavior tree of the robot output by the task execution model; A deployment determination unit, which is used to obtain the latest structural features and the latest resource allocation of the robot behavior tree from the task execution model in real time to obtain the task deployment of all robots.

[0014] Preferably, the deployment determination unit includes: A real-time monitoring unit, which is used to monitor the output result of the task execution model in real time, and give a warning reminder when it is detected that the output result changes dynamically; A data acquisition unit, which is used to obtain the latest structural features and the latest resource allocation of the robot behavior tree from the task execution model when receiving the warning reminder; A deployment adjustment unit, which is used to make adjustments based on the latest structural features and the latest resource allocation on the basis of the current task deployment to obtain the latest task deployment.

[0015] A tool chain for rapid deployment of robots includes a compiler, an assembler, a linker, a debugger, and a simulation and verification tool.

[0016] Compared with the prior art, the present invention has achieved the following beneficial effects: By abstractly adapting the base interface through an interface protocol, multiple available interfaces are obtained, realizing the adaptation to robots of different brands, meeting the access of various robots. By generating a display interface for the data information of the robots accessed based on the multiple available interfaces, rapid operation and maintenance are realized, the operation and maintenance cycle is reduced. By generating the task deployment of the robots based on production requirements and combining the display interface information, rapid change of business logic is realized, which is more adaptable to flexible manufacturing. Finally, the efficiency of robot deployment is improved.

[0017] Other features and advantages of the present invention will be described in the following specification, and, in part, will be obvious from the specification, or will be understood by implementing the present invention. The objectives and other advantages of the present invention can be realized and obtained through the structures specifically pointed out in this application document.

[0018] The technical solution of the present invention will be further described in detail below through the drawings and embodiments. Description of the Drawings

[0019] The drawings are used to provide a further understanding of the present invention, and constitute a part of the specification. They are used to explain the present invention together with the embodiments of the present invention, and do not constitute a limitation to the present invention. In the drawings: Figure 1 It is a structural diagram of a base system for rapid deployment of a robot in an embodiment of the present invention; Figure 2 It is a structural diagram of the interface abstraction module in an embodiment of the present invention; Figure 3This is the structural diagram of the interface generation module in the embodiments of the present invention. Detailed implementation manners

[0020] The preferred embodiments of the present invention will be described below with reference to the accompanying drawings. It should be understood that the preferred embodiments described herein are only for illustrating and explaining the present invention, and are not used to limit the present invention.

[0021] Embodiment 1 The embodiment of the present invention provides a base system for rapid deployment of robots, as Figure 1 shown, including: An interface abstraction module, which is used to abstractly adapt the base interface through an interface protocol to obtain multiple available interfaces; An interface generation module, which is used to generate a display interface for the data information of the robot accessed based on multiple available interfaces; A task deployment module, which is used to generate the task deployment of the robot based on production requirements and in combination with the display interface information.

[0022] In this embodiment, different types of robots correspond to different interface protocols. The base interface during abstract adaptation through the interface protocol satisfies different types of robots. When a robot is recognized, the corresponding interface adaptation is retrieved to implement the connection of the robot to the base system.

[0023] In this embodiment, the data information includes messages such as the identity, attributes, and historical operations of the robot.

[0024] In this embodiment, the display interfaces of robots of different brands are the same.

[0025] In this embodiment, generating the task deployment of the robot is, for example, to quickly realize the automated operation of workshop-level production tasks by obtaining device communication, system communication, and robot communication.

[0026] In this embodiment, generating the task deployment of the robot applies technologies such as the behavior tree, scheduling, task choreography, and digital twin of the robot.

[0027] The beneficial effects of the above design scheme are as follows: By abstractly adapting the base interface through the interface protocol to obtain multiple available interfaces, the adaptation of different brands of robots is realized, meeting the access of various robots. By generating a display interface for the data information of the robot accessed based on multiple available interfaces, rapid operation and maintenance are realized, the operation and maintenance cycle is reduced. By generating the task deployment of the robot based on production requirements and in combination with the display interface information, the rapid change of business logic is realized, making it more adaptable to flexible manufacturing. Finally, the efficiency of robot deployment is improved.

[0028] Embodiment 2 Based on Embodiment 1, an embodiment of the present invention provides a base system for rapid deployment of robots, as Figure 2 shown. The interface abstraction module includes: A protocol determination unit, configured to obtain the access interface protocol of the base interface based on the connection interface protocols of robots of various brands collected. A template establishment unit, configured to establish an abstract adaptation template for the connection interface protocol and the access interface protocol based on the protocol contents of the connection interface protocol and the access interface protocol. An interface determination unit, configured to access the abstract adaptation template into the base interface to obtain multiple available interfaces.

[0029] In this embodiment, a script for abbreviating the interface based on the abstract adaptation template is saved in the base system to achieve binding with the base system.

[0030] The beneficial effects of the above design solution are as follows: By obtaining the access interface protocol of the base interface based on the connection interface protocols of robots of various brands collected, it provides a basis for the pre-establishment of the abstract adaptation template. Based on the protocol contents of the connection interface protocol and the access interface protocol, an abstract adaptation template for the connection interface protocol and the access interface protocol is established, so as to directly retrieve the relevant abstract adaptation template when connecting robots of various brands, improving the efficiency of robot access to the base system. The abstract adaptation template is accessed into the base interface to obtain multiple available interfaces, realizing the adaptation to robots of different brands and meeting the access of various robots.

[0031] Embodiment 3 Based on Embodiment 2, an embodiment of the present invention provides a base system for rapid deployment of robots. The application of the interface abstraction module is as follows: After detecting that a robot is connected to the base system, obtain the connection interface protocol of the robot, and combine it with the access interface protocol of the base interface to retrieve a target abstract adaptation template that meets the requirements from the abstract adaptation templates. After performing abstract adaptation on the interface protocol based on the target abstract adaptation template, obtain the currently available interface. Based on the currently available interface, access the data information of the robot into the base system.

[0032] The beneficial effects of the above design solution are as follows: After detecting that a robot is connected to the base system, obtain the connection interface protocol of the robot, combine it with the access interface protocol of the base interface, retrieve a target abstract adaptation template that meets the requirements from the abstract adaptation templates, perform abstract adaptation on the interface protocol based on the target abstract adaptation template to obtain the currently available interface, and access the data information of the robot into the base system based on the currently available interface, specifically implementing the process of the base system accessing the robot, providing a basis for subsequent rapid deployment of the robot.

[0033] Example 4 Based on Example 1, an embodiment of the present invention provides a base system for rapid deployment of a robot, as Figure 3 shown, the interface generation module includes: A plugin selection unit for selecting a plugin that meets the robot's needs based on the data information of the robot accessed through multiple available interfaces; A plugin configuration unit for configuring information for the plugin based on the interface display requirements to obtain the configuration information of the plugin; An interface generation unit for loading the plugin based on the configuration information of the plugin to generate a display interface.

[0034] In this embodiment, a plugin-based interface switch is adopted, which can quickly provide a matching operation and maintenance interaction interface according to on-site needs, reducing the maintenance threshold for workers.

[0035] The beneficial effects of the above design solution are: by selecting a plugin that meets the robot's needs based on the data information of the robot accessed through multiple available interfaces, configuring information for the plugin based on the interface display requirements to obtain the configuration information of the plugin, and loading the plugin based on the configuration information of the plugin to generate a display interface, the display interfaces of different robots are made consistent, greatly reducing the cost of switching the use of robots, achieving rapid operation and maintenance, and reducing the operation and maintenance cycle.

[0036] Example 5 Based on Example 1, an embodiment of the present invention provides a base system for rapid deployment of a robot, and the task deployment module includes: An information acquisition unit for acquiring all the robots accessing the base system and the communication information with industrial equipment from the display interface information; A task deployment unit for generating a task deployment for the robot based on production requirements, in combination with the behavior trees and communication information of all the robots.

[0037] The beneficial effects of the above design solution are: by acquiring all the robots accessing the base system and the communication information with industrial equipment from the display interface information, and generating a task deployment for the robot based on production requirements, in combination with the behavior trees and communication information of all the robots, rapid change of business logic is realized, which is more adaptable to flexible manufacturing, and ultimately, the efficiency of robot deployment is improved.

[0038] Example 6 Based on Example 2, an embodiment of the present invention provides a base system for rapid deployment of a robot, and the template establishment unit includes: A model building unit is used to learn the abstract adaptation process data of the historical interface protocol, obtain necessary description features in the abstract adaptation process, and build an abstract adaptation description model based on the necessary description features; An element determination unit is used to standardize the connection interface protocol and the access interface protocol to obtain the target protocol content, and extract the target content elements in the target protocol content through the abstract adaptation description model; A configuration unit, configured to match the target content elements based on an intelligent matching method, and convert and configure the element matching results based on a visual configuration tool to obtain an initial adaptation template; a priority definition unit, configured to obtain basic template information, node template information, and application template information from the initial adaptation template, set the basic template information to a third priority, the node template information to a second priority, and the application template information to a first priority, optimize the initial adaptation template, and obtain a target adaptation template; The test unit is used to perform stability tests on the target adaptation template based on the automated test architecture. After passing the test, it will be used as the adaptation parent template; The template derivation unit is used to obtain business requirements for adapting the parent template, obtain extended business requirements with similarity to the business requirements within a preset similarity range from a large database, and determine the modified content of custom field modifications and added extended fields of the adapted parent template using an abstract adaptation description model based on the extended business requirements to obtain an adapted derived template; The template storage unit is used to store the adaptation parent template and the adaptation derivative template as abstract adaptation templates to obtain a template library.

[0039] In this embodiment, by setting the basic template information as the third priority, the node template information as the second priority, and the application template information as the first priority, there can be a basis for judgment when conflicts occur during the use of the template, and the interface adaptation can be carried out smoothly. The initial adaptation template is optimized to obtain the target adaptation template to further reduce the occurrence of conflicts and ensure the smooth execution of the template-based interface connection.

[0040] In this embodiment, the element matching results are converted and configured based on a visual configuration tool so that the interface adaptability meets the requirements.

[0041] In this embodiment, the adaptation derived template is derived from the adaptation parent template, which enriches the types of templates and meets the needs of multiple types of robots and multiple application scenarios as much as possible.

[0042] The beneficial effects of the above design scheme are: by learning the abstract adaptation process data of the historical interface protocol, the necessary descriptive features in the abstract adaptation process are obtained, and an abstract adaptation description model is established based on the necessary descriptive features to provide a basis for determining the template elements, standardize the connection interface protocol and the access interface protocol, obtain the target protocol content, and extract the target content elements in the target protocol content through the abstract adaptation description model, match the target content elements based on the intelligent matching method, and convert and configure the element matching results based on the visual configuration tool to obtain the initial adaptation template, obtain the basic template information, node template information and application template information from the initial adaptation template, set the basic template information as the third priority and the node template information as the second priority Level, application template information is the first priority, the initial adaptation template is optimized, and the target adaptation template is obtained. The target adaptation template further reduces the occurrence of conflicts and ensures the smooth execution of the interface connection based on the template. The target adaptation template is tested for stability based on the automated testing architecture. After the test passes, it is used as the adaptation parent template to ensure the stability of the template in the actual application process, and the business requirements of the adaptation parent template are obtained. The extended business requirements with similarity to the business requirements within the preset similarity range are obtained from the big database. Based on the extended business requirements, the abstract adaptation description model is used to determine the modification content of the custom fields of the adaptation parent template and the addition of the extended fields, and the adaptation derivative template is obtained, which enriches the template types and meets the needs of multiple types of robots and multiple application scenarios as much as possible.

[0043] Example 7 Based on Example 6, an embodiment of the present invention provides a base system for rapid deployment of a robot, wherein the testing unit includes: The stability test unit is used to simulate multiple application environments and use the automated test architecture to perform stability tests on the target adaptation template to obtain performance data in each application environment; a stability determination unit, configured to determine stability based on the performance data and determine whether the stability meets stability requirements; If so, use the target adaptation template as the adaptation parent template; Otherwise, it is determined that the target adaptation template is abnormal, and the process returns to the configuration unit for reconfiguration.

[0044] The beneficial effect of the above design scheme is: by performing stability testing on the target adaptation template based on the automated testing architecture, it is used as the adaptation parent template after passing the test, ensuring the stability of the template during actual application.

[0045] Example 8 Based on Example 5, an embodiment of the present invention provides a base system for rapid deployment of a robot, wherein the task deployment unit includes: An analysis unit for analyzing production requirements based on an AI model to obtain real-time dynamic business rules, and based on the AI model, matching the business rules with the nodes of the behavior trees of all robots, and obtaining the structural features of the behavior trees according to the matching results; A priority setting unit for determining the collaborative task characteristics of all robots based on the structural features of the behavior trees, analyzing the importance of the collaborative task characteristics based on production requirements and task execution requirements, and establishing the priority of each robot node based on the importance; A resource allocation unit for uniformly allocating resources to all robots based on the priority of each robot node and the collaborative task characteristics, combined with the communication information of all robots, to obtain a resource allocation result; A model establishment unit for establishing a task execution model of all robots based on the structural features of all robots, the priority of each robot node, and the resource allocation result, combined with digital twin technology; A model connection unit for obtaining the rule engine and behavior tree nodes in the task execution model, and establishing a first connection between the production requirements and the rule engine, and a second connection between the rule engine and the behavior tree nodes based on the AI model; A dynamic establishment unit for extracting the priority coordination mechanism in the task execution model, and when the production requirements change dynamically, based on the first connection and the second connection, combined with the priority coordination mechanism, determining the latest structural features and the latest resource allocation of the robot behavior tree output by the task execution model; A deployment determination unit for obtaining the latest structural features and the latest resource allocation of the robot behavior tree from the task execution model in real time to obtain the task deployment of all robots.

[0046] In this embodiment, the structural features of the behavior tree are used to represent the execution operation situation of the robot.

[0047] In this embodiment, the communication information of all robots is the communication information between the actual task and the task device.

[0048] In this embodiment, the task execution model is used to implement the digital simulation of the robot operation.

[0049] In this embodiment, the dynamic adjustment of the task execution model can be realized through the first connection and the second connection.

[0050] The beneficial effects of the above design solution are as follows: By parsing the production requirements based on the AI model, obtaining real-time dynamic business rules, and matching the business rules with the nodes of the behavior trees of all robots based on the AI model, the structural characteristics of the behavior trees are obtained according to the matching results. Based on the structural characteristics of the behavior trees, the collaborative task characteristics of all robots are determined. Based on the production requirements and the requirements of task execution, the importance of the collaborative task characteristics is analyzed, and the priorities of each robot node are established based on the importance to achieve the task allocation of the robots. Based on the priorities of each robot node and the collaborative task characteristics, combined with the communication information of all robots, resources are uniformly allocated to all robots to obtain the resource allocation result, realizing the reasonable allocation of the resources of the robots. Based on the structural characteristics of all robots, the priorities of each robot node, and the resource allocation result, combined with the digital twin technology, a task execution model of all robots is established, and the rule engine and behavior tree nodes in the task execution model are obtained. A first connection is established between the production requirements and the rule engine based on the AI model, and a second connection is established between the rule engine and the behavior tree nodes. The priority coordination mechanism in the task execution model is extracted, which is used to determine the latest structural characteristics and the latest resource allocation of the robot behavior tree output by the task execution model based on the first connection, the second connection, and the priority coordination mechanism when the production requirements change dynamically, and the latest structural characteristics and the latest resource allocation of the robot behavior tree are obtained from the task execution model in real time to obtain the task deployment of all robots, realizing dynamic resource allocation and task deployment, and realizing the flexibility of task deployment, which is more suitable for flexible manufacturing.

[0051] Embodiment 9 Based on Embodiment 8, the embodiment of the present invention provides a base system for rapid deployment of robots. The deployment determination unit includes: A real-time monitoring unit for real-time monitoring of the output result of the task execution model, and giving a warning reminder when it is detected that the output result changes dynamically; A data acquisition unit for obtaining the latest structural characteristics and the latest resource allocation of the robot behavior tree from the task execution model when receiving the warning reminder; A deployment adjustment unit for making adjustments based on the latest structural characteristics and the latest resource allocation on the basis of the current task deployment to obtain the latest task deployment.

[0052] The beneficial effects of the above design solution are as follows: The task deployment of all robots is obtained by obtaining the latest structural characteristics and the latest resource allocation of the robot behavior tree from the task execution model in real time, realizing the flexibility of task deployment, which is more suitable for flexible manufacturing.

[0053] Embodiment 10: An embodiment of the present invention provides a tool chain for rapid deployment of a robot, including a compiler, an assembler, a linker, a debugger, and a simulation and verification tool.

[0054] In this embodiment, the compiler: converts a high-level programming language into machine code; the assembler: converts the code output by the compiler into machine-readable instructions; the linker: combines multiple compiled code modules into an executable file; the debugger: is used to find and fix errors in the code; the simulation and verification tool: is used to test and verify the correctness of software or hardware designs.

[0055] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of this application document and its equivalent technologies, the present invention is also intended to include these changes and modifications.

Claims

1. A base system for rapid deployment of a robot, characterized in that, Including: An interface abstraction module, which is used to abstractly adapt the base interface through an interface protocol to obtain multiple available interfaces; An interface generation module, which is used to generate a display interface for the data information of the robot accessed based on the multiple available interfaces; A task deployment module, which is used to generate the task deployment of the robot based on production requirements and in combination with the interface information of the display interface.

2. The base system for rapid deployment of a robot according to claim 1, characterized in that, The interface abstraction module includes: A protocol determination unit, which is used to determine the connection interface protocols of each brand of robot based on the collected information and obtain the access interface protocol of the base interface; A template establishment unit, which is used to establish an abstract adaptation template for the connection interface protocol and the access interface protocol based on the protocol content of the connection interface protocol and the access interface protocol; An interface determination unit, which is used to access the abstract adaptation template into the base interface to obtain multiple available interfaces.

3. The base system for rapid deployment of a robot according to claim 2, characterized in that, The application of the interface abstraction module is as follows: After detecting that the robot is connected to the base system, obtain the connection interface protocol of the robot, and in combination with the access interface protocol of the base interface, retrieve the target abstract adaptation template that meets the requirements from the abstract adaptation template; After abstractly adapting the interface protocol based on the target abstract adaptation template, obtain the currently available interface; Based on the currently available interface, access the data information of the robot into the base system.

4. The base system for rapid deployment of a robot according to claim 1, characterized in that, The interface generation module includes: A plug-in selection unit, which is used to select a plug-in that meets the requirements of the robot based on the data information of the robot accessed through the multiple available interfaces; A plug-in configuration unit, which is used to configure the information of the plug-in based on the interface display requirements to obtain the configuration information of the plug-in; An interface generation unit, which is used to load the plug-in based on the configuration information of the plug-in and generate a display interface.

5. A base system for rapid deployment of a robot according to claim 1, characterized in that, The task deployment module includes: An information acquisition unit, which is used to acquire all the robots connected to the base system and the communication information with industrial equipment from the interface information of the display interface; A task deployment unit, which is used to generate the task deployment of the robot based on production requirements and in combination with the behavior tree and communication information of all the robots.

6. The base system for rapid deployment of a robot according to claim 2, characterized in that, The template establishment unit includes: A model establishment unit, which is used to learn the data of the abstract adaptation process of the historical interface protocol to obtain the necessary description features in the abstract adaptation process, and establish an abstract adaptation description model based on the necessary description features; An element determination unit, which is used to standardize the connection interface protocol and the access interface protocol to obtain the target protocol content, and extract the target content elements from the target protocol content through the abstract adaptation description model; A configuration unit, which is used to match the target content elements based on an intelligent matching method and perform conversion configuration on the element matching result based on a visual configuration tool to obtain an initial adaptation template; A priority definition unit, which is used to obtain the basic template information, node template information, and application template information from the initial adaptation template, set the basic template information as the third priority, the node template information as the second priority, and the application template information as the first priority, and optimize the initial adaptation template to obtain a target adaptation template; A testing unit, which is used to perform a stability test on the target adaptation template based on an automated testing framework, and use it as an adaptation parent template after passing the test. A template derivation unit, which is used to obtain the business requirements that adapt to the parent template, obtain the extended business requirements with a similarity within a preset similarity range to the business requirements from a large database, and based on the extended business requirements, use an abstract adaptation description model to determine the modification content of the custom fields that adapt to the parent template and the modification content of adding extended fields, so as to obtain an adapted derived template; A template storage unit, which is used to store the adapted parent template and the adapted derived template as an abstract adaptation template to obtain a template library.

7. The base system for rapid deployment of a robot according to claim 6, characterized in that, The test unit includes: A stability test unit, which is used to simulate a variety of application environments and use an automated test framework to perform stability tests on the target adaptation template to obtain performance data in each application environment; A stability judgment unit, which is used to determine the stability based on the performance data and judge whether the stability meets the stability requirements; If so, use the target adaptation template as the adapted parent template; Otherwise, determine that the target adaptation template is abnormal and return it to the configuration unit for reconfiguration.

8. The base system for rapid deployment of a robot according to claim 5, characterized in that, The task deployment unit includes: An analysis unit, which is used to analyze the production requirements based on an AI model to obtain real-time dynamic business rules, and based on the AI model, match the business rules with the nodes of the behavior trees of all robots, and obtain the structural characteristics of the behavior trees according to the matching results; A priority setting unit, which is used to determine the collaborative task characteristics of all robots based on the structural characteristics of the behavior trees, analyze the importance of the collaborative task characteristics based on the production requirements and the requirements of task execution, and establish the priority of each robot node based on the importance; A resource allocation unit, which is used to uniformly allocate resources to all robots based on the priority of each robot node and the collaborative task characteristics, in combination with the communication information of all robots, to obtain a resource allocation result; A model establishment unit, which is used to establish a task execution model for all robots based on the structural characteristics of all robots, the priority of each robot node, and the resource allocation result, in combination with digital twin technology; A model connection unit, which is used to obtain the rule engine and the behavior tree nodes in the task execution model, and establish a first connection between the production requirements and the rule engine based on the AI model, and a second connection between the rule engine and the behavior tree nodes; A dynamic establishment unit, which is used to extract the priority coordination mechanism in the task execution model, and when the production requirements change dynamically, based on the first connection and the second connection, in combination with the priority coordination mechanism, determine the latest structural characteristics and the latest resource allocation of the robot behavior tree output by the task execution model; A deployment determination unit, which is used to obtain the latest structural characteristics and the latest resource allocation of the robot behavior tree from the task execution model in real time to obtain the task deployment of all robots.

9. The base system for rapid deployment of a robot according to claim 8, characterized in that, The deployment determination unit includes: A real-time monitoring unit, which is used to perform real-time monitoring on the output results of the task execution model, and give a warning reminder when it is detected that the output results change dynamically; A data acquisition unit, which is used to obtain the latest structural characteristics and the latest resource allocation of the robot behavior tree from the task execution model when receiving the warning reminder; A deployment adjustment unit, configured to make adjustments based on the latest structural features and the latest resource allocation on the basis of the current task deployment, so as to obtain the latest task deployment.

10. A tool chain for rapid robot deployment, which is used in the base system as described in claim 1, and includes a compiler, an assembler, a linker, a debugger, and a simulation and verification tool.

Images