Base system and tool chain for rapid robot deployment

Abstract

The present invention provides a base system and tool chain for rapid deployment of robots. By abstractly adapting the base interface through the interface protocol, multiple available interfaces are obtained to achieve adaptation to robots of different brands and meet the access needs of various robots. By generating a display interface for the data information of the robot based on the multiple available interfaces, rapid operation and maintenance are achieved and the operation and maintenance cycle is reduced. By generating the robot's task deployment based on production needs and combining the display interface information, rapid changes in business logic are achieved, which is more adaptable to flexible manufacturing and ultimately improves the efficiency of robot deployment.

Description

Technical Field

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

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

[0003] Existing robots deployed with different brands have closed hardware interfaces, long integration cycles, and long and high operation and maintenance costs. The traditional base system has rigid functions and is difficult to quickly adapt to different business scenarios. The rigid business logic is difficult to adapt to flexible production needs. There is a lack of full-process support from action design to business verification, resulting in inefficient robot deployment. Summary of the Invention

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

[0005] A base system for rapid deployment of a robot, comprising:

[0006] The interface abstraction module is used to abstractly adapt the base interface through the interface protocol to obtain multiple available interfaces;

[0007] An interface generation module is used to generate a display interface for the data information of the robot accessed based on multiple available interfaces;

[0008] The task deployment module is used to generate the robot's task deployment based on production requirements and combined with the display interface information.

[0009] In this embodiment, different robot types correspond to different interface protocols. The base interface during abstract adaptation through the interface protocol satisfies different types of robots. When a robot is identified, the corresponding interface adaptation is called to connect the robot to the base system.

[0010] Preferably, the interface abstraction module includes:

[0011] A protocol determination unit is used to obtain the access interface protocol of the base interface based on the collected connection interface protocols of various brands of robots;

[0012] A template establishing unit, configured to establish an abstract adaptation template of the connection interface protocol and the access interface protocol based on the protocol contents of the connection interface protocol and the access interface protocol;

[0013] The interface determination unit is used to connect the abstract adaptation template to the base interface to obtain multiple available interfaces.

[0014] Preferably, the application of the interface abstraction module is as follows:

[0015] After detecting that the robot is connected to the base system, the connection interface protocol of the robot is obtained, and combined with the access interface protocol of the base interface, the target abstract adaptation template that meets the requirements is retrieved from the abstract adaptation template;

[0016] After abstract adaptation of the interface protocol based on the target abstract adaptation template, the currently available interface is obtained;

[0017] Connect the robot's data information to the base system based on the currently available interface.

[0018] Preferably, the interface generation module includes:

[0019] A plug-in selection unit, configured to select a plug-in that meets the needs of the robot based on data information of the robot accessed through multiple available interfaces;

[0020] The plug-in configuration unit is used to configure the plug-in information based on the interface display requirements and obtain the configuration information of the plug-in;

[0021] The interface generation unit is used to load the plug-in based on the configuration information of the plug-in and generate a display interface.

[0022] Preferably, the task deployment module includes:

[0023] An information acquisition unit, used to obtain all robots connected to the base system and communication information with industrial equipment from the display interface information;

[0024] The task deployment unit is used to generate task deployment for robots based on production requirements and combined with the behavior trees and communication information of all robots.

[0025] Preferably, the template establishing unit includes:

[0026] 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;

[0027] 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;

[0028] 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;

[0029] 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;

[0030] 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;

[0031] 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;

[0032] 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.

[0033] Preferably, the testing unit comprises:

[0034] 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;

[0035] a stability determination unit, configured to determine stability based on the performance data and determine whether the stability meets stability requirements;

[0036] If so, use the target adaptation template as the adaptation parent template;

[0037] Otherwise, it is determined that the target adaptation template is abnormal, and the process returns to the configuration unit for reconfiguration.

[0038] Preferably, the task deployment unit includes:

[0039] The parsing unit is used to parse production requirements based on the AI ​​model to obtain real-time dynamic business rules. The business rules are then matched with the nodes of the behavior tree of all robots based on the AI ​​model, and the structural characteristics of the behavior tree are obtained based on the matching results.

[0040] The priority setting unit is used to determine the collaborative task characteristics of all robots based on the structural characteristics of the behavior tree. Based on production needs and task execution requirements, it analyzes the importance of collaborative task characteristics and establishes the priority of each robot node based on the importance.

[0041] The resource allocation unit is used to allocate resources to all robots based on the priority and collaborative task characteristics of each robot node and the communication information of all robots to obtain the resource allocation result;

[0042] The model building unit is used to build 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 results, combined with digital twin technology;

[0043] A model connection unit, configured to obtain a rule engine and behavior tree nodes in the task execution model, and establish a first connection between the production demand and the rule engine, and a second connection between the rule engine and the behavior tree nodes based on the AI ​​model;

[0044] A dynamic establishment unit is used to extract the priority coordination mechanism in the task execution model, and is used to determine the latest structural features and latest resource allocation of the robot behavior tree output by the task execution model based on the first connection and the second connection in combination with the priority coordination mechanism when production demand changes dynamically;

[0045] The deployment determination unit 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.

[0046] Preferably, the deployment determination unit includes:

[0047] The real-time monitoring unit is used to monitor the output results of the task execution model in real time and issue early warning reminders when dynamic changes are detected in the output results;

[0048] A data acquisition unit is used to obtain the latest structural features and resource allocation of the robot behavior tree from the task execution model after receiving an early warning reminder;

[0049] The deployment adjustment unit is used to adjust the current task deployment based on the latest structural features and the latest resource allocation to obtain the latest task deployment.

[0050] A tool chain for rapid robot deployment, including a compiler, assembler, linker, debugger, and simulation and verification tools.

[0051] Compared with the prior art, the present invention has achieved the following beneficial effects:

[0052] By abstractly adapting the base interface through the interface protocol, multiple available interfaces are obtained to achieve adaptation to robots of different brands and meet the access needs of various robots. By generating a display interface for the data information of robots accessed based on multiple available interfaces, rapid operation and maintenance are achieved and the operation and maintenance cycle is reduced. By generating the robot's task deployment based on production needs and combining the display interface information, rapid changes in business logic are achieved, which is more adaptable to flexible manufacturing and ultimately improves the efficiency of robot deployment.

[0053] Other features and advantages of the present invention will be described in the following description, and in part will become apparent from the description, or will be understood by practicing the present invention. The purpose and other advantages of the present invention can be achieved and obtained through the structures specifically pointed out in this application document.

[0054] The technical solution of the present invention is further described in detail below through the accompanying drawings and embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0055] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings:

[0056] Figure 1 This is a structural diagram of a base system for rapid robot deployment according to an embodiment of the present invention;

[0057] Figure 2 This is a structural diagram of the interface abstraction module described in an embodiment of the present invention;

[0058] Figure 3 This is a structural diagram of the interface generation module described in an embodiment of the present invention. DETAILED DESCRIPTION

[0059] The preferred embodiments of the present invention are described below with reference to the accompanying drawings. It should be understood that the preferred embodiments described herein are only used to illustrate and explain the present invention, and are not used to limit the present invention.

[0060] Example 1

[0061] The embodiment of the present invention provides a base system for rapid deployment of a robot, such as Figure 1 As shown, including:

[0062] The interface abstraction module is used to abstractly adapt the base interface through the interface protocol to obtain multiple available interfaces;

[0063] An interface generation module is used to generate a display interface for the data information of the robot accessed based on multiple available interfaces;

[0064] The task deployment module is used to generate the robot's task deployment based on production requirements and combined with the display interface information.

[0065] In this embodiment, different robot types correspond to different interface protocols. The base interface during abstract adaptation through the interface protocol satisfies different types of robots. When a robot is identified, the corresponding interface adaptation is called to connect the robot to the base system.

[0066] In this embodiment, the data information includes the robot's identity, attributes, historical operation and other information.

[0067] In this embodiment, the display interfaces of robots of different brands are consistent.

[0068] In this embodiment, the task deployment of the generated robot is, for example, to quickly realize the automated operation of the workshop-level production tasks by acquiring device communication, system communication, and robot communication.

[0069] In this embodiment, generating the robot's task deployment utilizes the robot's behavior tree, scheduling, task orchestration, digital twin and other technologies.

[0070] The beneficial effects of the above design scheme are: by abstractly adapting the base interface through the interface protocol, multiple available interfaces are obtained, adaptation to robots of different brands is achieved, and access to various robots is met; by generating a display interface for the data information of the robot based on the multiple available interfaces, rapid operation and maintenance is achieved, and the operation and maintenance cycle is reduced; by generating the robot's task deployment based on production needs and combining the display interface information, rapid changes in business logic are achieved, which is more adaptable to flexible manufacturing and ultimately improves the efficiency of robot deployment.

[0071] Example 2

[0072] Based on Example 1, the present invention provides a base system for rapid deployment of a robot, such as Figure 2 As shown, the interface abstract module includes:

[0073] A protocol determination unit is used to obtain the access interface protocol of the base interface based on the collected connection interface protocols of various brands of robots;

[0074] A template establishing unit, configured to establish an abstract adaptation template of the connection interface protocol and the access interface protocol based on the protocol contents of the connection interface protocol and the access interface protocol;

[0075] The interface determination unit is used to connect the abstract adaptation template to the base interface to obtain multiple available interfaces.

[0076] In this embodiment, a script based on the abstract adaptation template abbreviated interface is saved in the base system to achieve binding with the base system.

[0077] The beneficial effects of the above design scheme are: by collecting the connection interface protocols of robots of various brands and obtaining the access interface protocol of the base interface, a basis is provided for the pre-establishment of an abstract adaptation template; based on the protocol contents of the connection interface protocol and the access interface protocol, an abstract adaptation template of the connection interface protocol and the access interface protocol is established, so that when taking screenshots of robots of various brands, the relevant abstract adaptation template can be directly called up, thereby improving the efficiency of the robot accessing the base system; the abstract adaptation template is connected to the base interface to obtain multiple available interfaces, thereby realizing adaptation to robots of different brands and meeting the access needs of various robots.

[0078] Example 3

[0079] Based on Example 2, this embodiment of the present invention provides a base system for rapid deployment of a robot, and the application of the interface abstraction module is as follows:

[0080] After detecting that the robot is connected to the base system, the connection interface protocol of the robot is obtained, and combined with the access interface protocol of the base interface, the target abstract adaptation template that meets the requirements is retrieved from the abstract adaptation template;

[0081] After abstract adaptation of the interface protocol based on the target abstract adaptation template, the currently available interface is obtained;

[0082] Connect the robot's data information to the base system based on the currently available interface.

[0083] The beneficial effects of the above design scheme are: after detecting that the robot is connected to the base system, the connection interface protocol of the robot is obtained, combined with the access interface protocol of the base interface, the target abstract adaptation template that meets the requirements is called from the abstract adaptation template, and the interface protocol is abstractly adapted based on the target abstract adaptation template to obtain the currently available interface. Based on the currently available interface, the robot's data information is connected to the base system, specifically realizing the process of connecting the base system to the robot, and providing a basis for the subsequent rapid deployment of the robot.

[0084] Example 4

[0085] Based on Example 1, the present invention provides a base system for rapid deployment of a robot, such as Figure 3 As shown, the interface generation module includes:

[0086] A plug-in selection unit, configured to select a plug-in that meets the needs of the robot based on data information of the robot accessed through multiple available interfaces;

[0087] The plug-in configuration unit is used to configure the plug-in information based on the interface display requirements and obtain the configuration information of the plug-in;

[0088] The interface generation unit is used to load the plug-in based on the configuration information of the plug-in and generate a display interface.

[0089] In this embodiment, a plug-in interface switching is adopted, which can quickly provide a matching operation and maintenance interactive interface according to on-site needs, thereby lowering the maintenance threshold for workers.

[0090] The beneficial effects of the above design scheme are: by selecting the plug-in that meets the needs of the robot based on the data information of the robot accessed through multiple available interfaces, configuring the plug-in information based on the interface display requirements, obtaining the configuration information of the plug-in, loading the plug-in based on the configuration information of the plug-in, and generating a display interface, so that the display interfaces of different robots are consistent, which greatly reduces the cost of switching the robot, realizes rapid operation and maintenance, and shortens the operation and maintenance cycle.

[0091] Example 5

[0092] Based on Example 1, this embodiment of the present invention provides a base system for rapid robot deployment, wherein the task deployment module includes:

[0093] An information acquisition unit, used to obtain all robots connected to the base system and communication information with industrial equipment from the display interface information;

[0094] The task deployment unit is used to generate task deployment for robots based on production requirements and combined with the behavior trees and communication information of all robots.

[0095] The beneficial effects of the above design scheme are: by obtaining all robots connected to the base system and communication information with industrial equipment from the display interface information, based on production needs, combined with the behavior trees and communication information of all robots, task deployment for the robots is generated, and business logic can be quickly changed, which is more suitable for flexible manufacturing and ultimately improves the efficiency of robot deployment.

[0096] Example 6

[0097] Based on Example 2, this embodiment of the present invention provides a base system for rapid deployment of a robot, wherein the template establishment unit includes:

[0098] 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;

[0099] 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;

[0100] 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;

[0101] 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;

[0102] 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;

[0103] 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;

[0104] 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.

[0105] 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.

[0106] 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.

[0107] 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.

[0108] 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.

[0109] Example 7

[0110] 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:

[0111] 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;

[0112] a stability determination unit, configured to determine stability based on the performance data and determine whether the stability meets stability requirements;

[0113] If so, use the target adaptation template as the adaptation parent template;

[0114] Otherwise, it is determined that the target adaptation template is abnormal, and the process returns to the configuration unit for reconfiguration.

[0115] 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.

[0116] Example 8

[0117] 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:

[0118] The parsing unit is used to parse production requirements based on the AI ​​model to obtain real-time dynamic business rules. The business rules are then matched with the nodes of the behavior tree of all robots based on the AI ​​model, and the structural characteristics of the behavior tree are obtained based on the matching results.

[0119] The priority setting unit is used to determine the collaborative task characteristics of all robots based on the structural characteristics of the behavior tree. Based on production needs and task execution requirements, it analyzes the importance of collaborative task characteristics and establishes the priority of each robot node based on the importance.

[0120] The resource allocation unit is used to allocate resources to all robots based on the priority and collaborative task characteristics of each robot node and the communication information of all robots to obtain the resource allocation result;

[0121] The model building unit is used to build 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 results, combined with digital twin technology;

[0122] A model connection unit, configured to obtain a rule engine and behavior tree nodes in the task execution model, and establish a first connection between the production demand and the rule engine, and a second connection between the rule engine and the behavior tree nodes based on the AI ​​model;

[0123] A dynamic establishment unit is used to extract the priority coordination mechanism in the task execution model, and is used to determine the latest structural features and latest resource allocation of the robot behavior tree output by the task execution model based on the first connection and the second connection in combination with the priority coordination mechanism when production demand changes dynamically;

[0124] The deployment determination unit 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.

[0125] In this embodiment, the structural features of the behavior tree are used to represent the execution operation of the robot.

[0126] In this embodiment, the communication information of all robots is the communication information between the actual task and the task equipment.

[0127] In this embodiment, the task execution model is used to realize digital simulation of the robot operation.

[0128] In this embodiment, dynamic adjustment of the task execution model can be achieved through the first connection and the second connection.

[0129] The beneficial effects of the above design scheme are: by parsing the production demand based on the AI ​​model, real-time dynamic business rules are obtained, and the business rules are matched with the nodes of the behavior tree of all robots based on the AI ​​model, and the structural characteristics of the behavior tree are obtained according to the matching results. Based on the structural characteristics of the behavior tree, the collaborative task characteristics of all robots are determined, and based on the production demand and task execution requirements, the importance of the collaborative task characteristics is analyzed, and the priority of each robot node is established based on the importance to realize the task allocation of the robots. Based on the priority and collaborative task characteristics of each robot node, combined with the communication information of all robots, unified resource allocation is performed for all robots to obtain resource allocation results, and reasonable allocation of resources for robots is realized. Based on the structural characteristics of all robots, each robot The priority and resource allocation results of the nodes are combined with digital twin technology to establish a task execution model for all robots, obtain the rule engine and behavior tree nodes in the task execution model, and build the first connection between production demand and the rule engine based on the AI ​​model, and the second connection between the rule engine and the behavior tree node. The priority coordination mechanism in the task execution model is extracted. When production demand changes dynamically, based on the first connection and the second connection, combined with the priority coordination mechanism, the latest structural features and the latest resource allocation of the robot behavior tree output by the task execution model are determined. The latest structural features 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, realize dynamic resource allocation and task deployment, realize the flexibility of task deployment, and are more suitable for flexible manufacturing.

[0130] Example 9

[0131] Based on Example 8, an embodiment of the present invention provides a base system for rapid deployment of a robot, wherein the deployment determination unit includes:

[0132] The real-time monitoring unit is used to monitor the output results of the task execution model in real time and issue early warning reminders when dynamic changes are detected in the output results;

[0133] A data acquisition unit is used to obtain the latest structural features and resource allocation of the robot behavior tree from the task execution model after receiving an early warning reminder;

[0134] The deployment adjustment unit is used to adjust the current task deployment based on the latest structural features and the latest resource allocation to obtain the latest task deployment.

[0135] The beneficial effect of the above design scheme is: by obtaining 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, the flexibility of task deployment is achieved, which is more suitable for flexible manufacturing.

[0136] Example 10:

[0137] An embodiment of the present invention provides a tool chain for rapid robot deployment, including a compiler, an assembler, a linker, a debugger, and a simulation and verification tool.

[0138] 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-recognizable instructions; the linker combines multiple compiled code modules into an executable file; the debugger is used to find and fix errors in the code; and the simulation and verification tool is used to test and verify the correctness of the software or hardware design.

[0139] Obviously, those skilled in the art may 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 equivalents, the present invention is intended to include these modifications and variations.

Claims

1. A base system for rapid deployment of a robot, characterized in that: include: The interface abstraction module is used to abstractly adapt the base interface through the interface protocol to obtain multiple available interfaces, including: A protocol determination unit is used to obtain the access interface protocol of the base interface based on the collected connection interface protocols of various brands of robots; The template establishment unit is used to establish an abstract adaptation template of the connection interface protocol and the access interface protocol based on the protocol contents of the connection interface protocol and the access interface protocol, including: 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; A template storage unit, used for storing the adaptation parent template and the adaptation derivative template as an abstract adaptation template to obtain a template library; An interface determination unit, configured to connect the abstract adaptation template to the base interface to obtain multiple available interfaces; An interface generation module is used to generate a display interface for the data information of the robot accessed based on multiple available interfaces; The task deployment module is used to generate the robot's task deployment based on production requirements and combined with the display interface information.

2. A robot rapid deployment base system according to claim 1, characterized in that: The application of the interface abstraction module is as follows: After detecting that the robot is connected to the base system, the connection interface protocol of the robot is obtained, and combined with the access interface protocol of the base interface, the target abstract adaptation template that meets the requirements is retrieved from the abstract adaptation template; After abstract adaptation of the interface protocol based on the target abstract adaptation template, the currently available interface is obtained; Connect the robot's data information to the base system based on the currently available interface.

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

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

5. The base system for rapid robot deployment according to claim 1, characterized in that: The testing unit comprises: 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.

6. The base system for rapid robot deployment according to claim 4, characterized in that: The task deployment unit includes: The parsing unit is used to parse production requirements based on the AI ​​model to obtain real-time dynamic business rules. The business rules are then matched with the nodes of the behavior tree of all robots based on the AI ​​model, and the structural characteristics of the behavior tree are obtained based on the matching results. The priority setting unit is used to determine the collaborative task characteristics of all robots based on the structural characteristics of the behavior tree. Based on production needs and task execution requirements, it analyzes the importance of collaborative task characteristics and establishes the priority of each robot node based on the importance. The resource allocation unit is used to allocate resources to all robots based on the priority and collaborative task characteristics of each robot node and the communication information of all robots to obtain the resource allocation result; The model building unit is used to build 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 results, combined with digital twin technology; A model connection unit, configured to obtain a rule engine and behavior tree nodes in the task execution model, and establish a first connection between the production demand 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 is used to extract the priority coordination mechanism in the task execution model, and is used to determine the latest structural features and latest resource allocation of the robot behavior tree output by the task execution model based on the first connection and the second connection in combination with the priority coordination mechanism when production demand changes dynamically; The deployment determination unit 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.

7. The base system for rapid robot deployment according to claim 6, characterized in that: The deployment determination unit includes: The real-time monitoring unit is used to monitor the output results of the task execution model in real time and issue early warning reminders when dynamic changes are detected in the output results; A data acquisition unit is used to obtain the latest structural features and resource allocation of the robot behavior tree from the task execution model after receiving an early warning reminder; The deployment adjustment unit is used to adjust the current task deployment based on the latest structural features and the latest resource allocation to obtain the latest task deployment.

8. A tool chain for rapid deployment of a robot, used in the base system as claimed in claim 1, comprising a compiler, an assembler, a linker, a debugger, and a simulation and verification tool.

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