Autonomous Management and Scheduling System for High-Throughput Chemical Laboratory Robots Based on Digital Twins

Abstract

This invention provides an autonomous management and scheduling system for high-throughput chemical experimental robots based on digital twins, relating to the field of robot control technology. It includes a digital twin unit and a production execution unit. The production execution unit inputs production instructions and outputs a first production instruction signal. Based on the first and second production instruction signals, the production execution unit controls the robot to perform chemical experimental operations. The production execution unit feeds back the production result signal to the digital twin unit. This invention continuously collects overall operational and simulation data of the high-throughput chemical experiment through the digital twin unit, continuously improves the equipment twin model related to the entire experiment, and then interacts with the production execution unit. This provides data support for improving the efficiency of high-throughput chemical experiments and the output of experimental samples, and also provides a foundation for decision optimization of the entire system.

Description

Technical Field

[0001] This invention relates to the field of robot control technology, and more particularly to an autonomous management and scheduling system for a high-throughput chemical laboratory robot based on digital twins. Background Technology

[0002] With the development of artificial intelligence and robotics, robots are being applied in various fields. In chemistry-related fields, applying intelligent composite robots to chemical experiments that are highly repetitive, dangerous, and conducted in harsh environments is both effective and necessary. In 2018, researchers from the University of Glasgow trained an AI-driven chemical synthesis robot, thereby automating the process of exploring numerous chemical reactions.

[0003] Patent CN114995467A discloses a chemical robot management and planning scheduling system, method, and device. The system includes: a dynamic optimization module for experimental procedures, capable of receiving chemical experimental procedure files and obtaining multiple sequential workstation procedures for the corresponding chemical experimental tasks of the chemical experimental robot; dynamically iteratively optimizing all sequential workstation procedures to determine the optimal operation to be performed at each step; and sending the optimal operation to the task experimental module as chemical experimental workstation instructions. The task experimental module receives the chemical experimental workstation instructions and, according to the given optimal operation, controls the chemical robot to move to the target chemical experimental workstation to complete the corresponding chemical experimental operation; and feeds back the execution result to the dynamic optimization module for experimental procedures. The module also controls the operation of corresponding chemical instruments based on the corresponding chemical experimental operations performed by the chemical robot. This method and system enable chemical robots to complete chemical experimental operations efficiently and accurately.

[0004] However, this patent has certain shortcomings. 1. Existing chemical laboratory management systems lack specific and comprehensive feedback on the entire experimental process. They cannot monitor the real-time operation of each piece of equipment, and when a malfunction occurs, they cannot reconstruct the entire process at the time of the malfunction, providing only literal data. This leaves room for optimization in fault analysis and resolution. 2. Existing chemical laboratory management systems lack auxiliary positioning algorithms, relying solely on a single algorithm for positioning. Assembly errors, coupled with sensor errors due to increased operating time, accumulate, increasing the likelihood of positioning errors exceeding permissible limits. 3. Existing chemical laboratory management systems, after repeated observations of the experimental process, may develop new process improvements different from those derived from iterative optimization algorithms. Without manual intervention, these improvements cannot be quickly implemented. Digital twins, however, provide direct human intervention, simulating the new process in a simulation world and comparing it with previous processes to derive a superior experimental procedure. Summary of the Invention

[0005] To address the technical problem of feedback regulation in chemical laboratory management systems, which are not addressed by digital twin systems, this invention provides an autonomous management and scheduling system for high-throughput chemical laboratory robots based on digital twins. This invention primarily integrates digital twins with production execution units, improving the efficiency of high-throughput chemical experiments and the output of experimental samples through interconnected data interaction.

[0006] The technical means employed in this invention are as follows:

[0007] An autonomous management and scheduling system for high-throughput chemical laboratory robots based on digital twins, comprising digital twin units and production execution units;

[0008] The digital twin unit is used to establish a digital twin model of the chemical laboratory and the chemical robot as a whole. The digital twin model collects the overall operation data and simulation data of the high-throughput chemical experiment to form a real-time signal, and sends the real-time signal to the production execution unit. The digital twin unit receives the production result signal sent by the production execution unit and performs simulation optimization based on the production result signal. The digital twin model sends the second production instruction signal generated after simulation optimization to the production execution unit.

[0009] The simulation optimization method is as follows: The digital twin model receives the production result signal and converts it into a first experimental process to obtain the time required for the first experimental process; the digital twin model obtains a second experimental process based on the external input experiment to obtain the time required for the second experimental process; the digital twin model compares the time required for the first experimental process with the time required for the second experimental process, and when the time required for the first experimental process is greater than the time required for the second experimental process, the second experimental process is used as the second production instruction signal; when the time required for the first experimental process is less than the time required for the second experimental process, the first experimental process is used as the second production instruction signal.

[0010] The production execution unit is used to input production instructions and output a first production instruction signal. The production execution unit controls the robot to perform chemical experiment operations according to the first production instruction signal and the second production instruction signal. The production execution unit feeds back the production result signal to the digital twin unit.

[0011] Furthermore, the digital twin model includes a macroscopic scene of a chemical laboratory, host equipment and its auxiliary equipment, texture materials and rendering materials;

[0012] The macroscopic scene of the chemical laboratory includes the laboratory model, the laboratory layout, the lighting system, and the skybox.

[0013] Furthermore, the communication process of various devices in high-throughput chemistry experiments is as follows:

[0014] In high-throughput chemistry experiments, communication between various devices uses the TCP / IP communication protocol, and IP addresses are set for each device.

[0015] Use a network switch to connect all the equipment in a high-throughput chemistry experiment to the same local area network.

[0016] Furthermore, the production execution unit includes an order module, an editing module, a log module, and an experiment module;

[0017] The editing module is used to edit new experiments based on the operations that existing equipment and robots can perform, and send the first production instruction signal and the second production instruction signal to the order module.

[0018] The order module is used to add experiments to be completed in the laboratory and send the first production instruction signal and the second production instruction signal to the experiment module;

[0019] The log module is used to record the daily system operations, which include order experiments generated by the first production instruction signal and the second production instruction signal.

[0020] The experimental module is used to receive the first production instruction signal and the second production instruction signal, and to execute the order experiment according to the first production instruction signal and the second production instruction signal.

[0021] Furthermore, the experimental module includes a monitoring module and a task module;

[0022] The monitoring module is used to monitor the status of various devices in the chemical laboratory in real time. The status of each device includes whether the device is online, whether it is working properly, experimental information, and experimental progress.

[0023] The task module is used to receive the first production instruction signal and the second production instruction signal. The task module is communicatively connected to the digital twin unit. The task module receives feedback from the composite robot and corresponding equipment. The task module controls the composite robot and other equipment to perform relevant high-throughput chemical experimental operations to realize the order experiment.

[0024] Furthermore, the experimental information includes the number of experiments being run, the name of the currently running experiment, and the operator of the current experiment. The experimental progress displays the name of the currently running experiment, the experimental equipment, and the current task.

[0025] Furthermore, the task module includes a task receiving submodule, a navigation and positioning control submodule, a multi-site control submodule, a task feedback submodule, and a fault handling submodule;

[0026] The task receiving submodule is used to receive the first production instruction signal and the second production instruction signal sent by the order module and send them to the navigation and positioning control submodule;

[0027] The navigation and positioning control submodule is communicatively connected to the task receiving submodule. The navigation and positioning control submodule receives the first production instruction signal and the second production instruction signal and gives the corresponding navigation and positioning signal according to the first production instruction signal and the second production instruction signal. The composite robot moves and positions itself to the target chemical experiment workstation according to the navigation and positioning signal.

[0028] The multi-site control submodule is used to control the composite robot to complete the corresponding chemical experiment operation according to the corresponding operation procedure of the target chemical experiment work station;

[0029] The task feedback submodule is communicatively connected to the digital twin unit. The digital twin unit displays the working status of the composite robot and the corresponding equipment in real time. The task feedback submodule obtains the execution results of the composite robot for the order experiment and the task completion status of each workstation from the digital twin unit and sends feedback signals to the digital twin unit.

[0030] The fault handling submodule is used to stop the ongoing chemical experiment operation of the composite robot when a fault occurs in the composite robot and the corresponding equipment.

[0031] Furthermore, the navigation and positioning algorithm of the composite robot includes the AMCL algorithm and an auxiliary positioning algorithm based on binary square reference marks. The auxiliary positioning algorithm based on binary square reference marks is used for spatial positioning of the composite robot's mobile chassis and spatial pose compensation of the object during the robotic arm's grasping process.

[0032] Square reference markers are affixed to the ground at each chemical experiment workstation;

[0033] During the process of the composite robot reaching the target chemical experiment workstation based on navigation and positioning signals, if the robotic arm cannot accurately grasp the target due to chassis movement errors, the end-effector camera of the composite robot's robotic arm takes a picture of the target chemical experiment workstation reference, obtaining a three-dimensional QR code of the square reference. The vertices of the three-dimensional QR code are used to form a temporary spatial coordinate system. The temporary spatial coordinate system is compared with the spatial coordinate system during workstation calibration to calculate the offset error of the mobile chassis in the X and Y axes and the angular rotation error around the Z axis. Based on the offset error and rotation error, the error value that needs to be compensated is obtained. The composite robot moves according to the compensated error value to achieve precise positioning.

[0034] Furthermore, the multi-site control submodule includes a map origin control submodule, an initial sample placement control submodule, a weighing robot control submodule, a liquid chromatograph control submodule, a gas chromatography-mass spectrometry (GC-MS) control submodule, a pipetting robot control submodule, a reaction zone control submodule, and a capping machine control submodule.

[0035] The map origin control submodule is used to control the operation of resetting the composite robot to the map origin.

[0036] The initial sample placement control submodule is used to control the composite robot to grasp the sample at the initial position and to process waste samples;

[0037] The weighing robot control submodule is used to control the operation of placing the sample with the required amount of reagent into the weighing robot workstation and the operation of taking out the weighed sample, as well as the operation of controlling the weighing robot.

[0038] The liquid chromatograph control submodule is used to control the operation of placing the sample to be analyzed by liquid chromatography into the liquid chromatograph workstation and the operation of taking out the sample after chromatographic analysis, as well as the operation of the liquid chromatograph.

[0039] The gas chromatography-mass spectrometry (GC-MS) control submodule is used to control the operation of placing samples to be analyzed by gas chromatography and mass spectrometry into the GC-MS workstation and the operation of removing samples after gas chromatography and mass spectrometry analysis, as well as the operation of the GC-MS.

[0040] The pipetting robot control submodule is used to control the operation of placing the sample module that needs to be added with chemical reagents and solutions into the pipetting robot workstation and the operation of taking out the sample module after pipetting, as well as the operation of controlling the pipetting robot.

[0041] The reaction zone control submodule is used to control the operation of placing the sample module that needs to be heated and oscillated into the reaction zone workstation and the operation of taking out the sample module after the reaction, as well as the operation of controlling the oscillation and heating equipment.

[0042] The capping machine control submodule is used to control the operation of placing the sample module that needs to be capped or unscrewed into the capping machine workstation and the operation of taking out the sample module after capping, as well as the operation of controlling the movement of the capping machine.

[0043] Furthermore, the map origin control submodule controls the operation of resetting to the map origin in the following manner: entering the map origin task, controlling the six-axis robotic arm of the composite robot to reset, controlling the chassis of the composite robot to move to the map origin, and completing the task of reaching the map origin.

[0044] The initial sample placement control submodule controls the operation of the sample placement task and the operation of the waste sample handling task in the following manner: entering the initial sample grasping task, controlling the composite robot to grasp the sample, and completing the initial sample grasping task; entering the waste sample handling task, controlling the composite robot to grasp the waste sample, move it to the dedicated waste recycling area, place the waste sample, and complete the waste sample handling task.

[0045] The weighing robot control submodule controls the operation of placing samples requiring quantitative reagents and retrieving weighed samples in the following manner: Entering the sample placement task, the composite robot is controlled to place the sample requiring quantitative reagents into the weighing robot workstation; the weighing robot operates, placing the sample into the reagent-adding device; the reagent-adding device is activated, completing the sample placement task; entering the sample retrieval task, the composite robot is controlled to retrieve the sample from the weighing robot workstation, completing the sample retrieval operation.

[0046] The liquid chromatograph control submodule controls the operation of placing samples for liquid chromatographic analysis and retrieving samples after chromatographic analysis in the following manner: entering the liquid chromatographic sample placement task, controlling the composite robot to place the sample into the liquid chromatograph, starting the liquid chromatograph, and completing the liquid chromatographic sample placement task; entering the post-chromatographic analysis sample retrieval task, controlling the composite robot to retrieve the post-chromatographic analysis sample from the liquid chromatograph, and completing the post-chromatographic analysis sample retrieval task.

[0047] The gas chromatography-mass spectrometry (GC-MS) control submodule controls the operation of placing samples requiring GC-MS analysis and retrieving samples after GC-MS analysis in the following manner: Entering the sample placement task, controlling the composite robot to place the sample into the GC-MS, starting the GC-MS, and completing the sample placement task; entering the sample retrieval task, controlling the composite robot to retrieve the sample after GC-MS analysis from the GC-MS, and completing the sample retrieval task.

[0048] The pipetting robot control submodule controls the operation of placing the sample module requiring chemical reagents and liquids and retrieving the sample module after pipetting in the following manner: Entering the sample placement task, the composite robot is controlled to place the sample module at the pipetting robot workstation, and the pipetting robot operates to add the corresponding chemical reagents or solutions into the sample, completing the sample placement task; entering the sample retrieval task, the composite robot is controlled to retrieve the sample module after pipetting from the pipetting robot workstation, completing the sample retrieval task.

[0049] The reaction zone control submodule controls the tasks of placing the sample module requiring heating and oscillation and retrieving the sample module after reaction in the following manner: Entering the task of placing the sample module requiring heating and oscillation, controlling the composite robot to place the sample module into the reaction zone workstation, activating the heating and oscillation equipment, and completing the task of placing the sample module requiring heating and oscillation; entering the task of retrieving the sample module after reaction, controlling the composite robot to retrieve the sample module after reaction from the reaction zone workstation, and completing the task of retrieving the sample module after reaction.

[0050] The capping machine control submodule controls the operation of placing the sample module that needs to be capped or unscrewed, and the operation of removing the capped sample module in the following manner: entering the task of placing the sample module that needs to be capped or unscrewed, controlling the composite robot to place the sample module that needs to be capped or unscrewed at the capping machine workstation, starting the capping machine, completing the capping or unscrewing operation, and completing the task of placing the sample module that needs to be capped or unscrewed; entering the task of removing the capped sample module, controlling the composite robot to remove the capped sample module from the capping machine workstation, and completing the task of removing the capped sample module.

[0051] Compared with the prior art, the present invention has the following advantages:

[0052] This invention, by setting up mutually feedback digital twin units and production execution units, can observe the specific operating status of each device in real time, and can monitor the operation of composite robots and corresponding equipment. Furthermore, the digital twin units are communicatively connected with the production execution units, which can feed back the status of composite robots and corresponding equipment to the production execution units, thus realizing a closed loop for the entire autonomous management and scheduling system.

[0053] This invention enables precise positioning of a robot at multiple workstations in high-throughput chemical experiments by setting up a navigation and positioning algorithm for the composite robot.

[0054] This invention provides the function of direct human intervention by adopting a digital twin system. It simulates a new process in the simulation world and compares it with the previous process to obtain a better experimental process.

[0055] The production execution unit of this invention analyzes equipment and order information recorded in the database to allocate the working sequence between various devices and robots. It controls the composite robot to simultaneously prepare and react multiple sets of samples, eliminating the need to wait for previous experiments to complete. This allows for the completion of multiple batches of chemical experiments in a relatively short time, yielding a large amount of sample data and enabling rapid and efficient high-throughput chemical experiments. Furthermore, when the waiting time for experiments is long, the system controls the composite robot to use a wireless charging device, extending the robot's working time without delaying the experimental progress.

[0056] The production execution unit of this invention can schedule required experiments through the order module, facilitating the planning and scheduling of equipment and composite robots. The production execution unit can also generate new experimental methods based on existing equipment through the editing module, completing the new experimental process by calling corresponding instruction combinations from different devices. Attached Figure Description

[0057] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0058] Figure 1 This is a schematic diagram of the scheduling system of the present invention.

[0059] Figure 2 This is a schematic diagram of the production execution unit of the present invention.

[0060] Figure 3 This is a communication diagram of the scheduling system of the present invention.

[0061] Figure 4 This is a schematic diagram of the task module of the present invention.

[0062] Figure 5 This is a fault classification diagram for the present invention.

[0063] Figure 6 The flowchart for building the digital twin unit of this invention is shown. Detailed Implementation

[0064] It should be noted that, unless otherwise specified, the embodiments and features described in the present invention can be combined with each other. The present invention will now be described in detail with reference to the accompanying drawings and embodiments.

[0065] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. The following description of at least one exemplary embodiment is merely illustrative and is in no way intended to limit the present invention or its application or use. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0066] It should be noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit the scope of exemplary embodiments according to the invention. As used herein, the singular form is intended to include the plural form as well, unless the context clearly indicates otherwise. Furthermore, it should be understood that when the terms "comprising" and / or "including" are used in this specification, they indicate the presence of features, steps, operations, devices, components, and / or combinations thereof.

[0067] Unless otherwise specifically stated, the relative arrangement, numerical expressions, and values ​​of the components and steps described in these embodiments do not limit the scope of the invention. It should also be understood that, for ease of description, the dimensions of the various parts shown in the drawings are not drawn to actual scale. Techniques, methods, and devices known to those skilled in the art may not be discussed in detail, but where appropriate, such techniques, methods, and devices should be considered part of the specification. In all examples shown and discussed herein, any specific values ​​should be interpreted as merely exemplary and not as limitations. Therefore, other examples of exemplary embodiments may have different values. It should be noted that similar reference numerals and letters in the following figures denote similar items; therefore, once an item is defined in one figure, it need not be further discussed in subsequent figures.

[0068] Furthermore, it should be noted that the use of terms such as "first" and "second" to define components is merely for the purpose of distinguishing the corresponding components. Unless otherwise stated, the above terms have no special meaning and therefore should not be construed as limiting the scope of protection of this invention.

[0069] (a) Scheduling system;

[0070] like Figure 1 As shown, this invention provides an autonomous management and scheduling system for high-throughput chemical experimental robots based on digital twins, including a digital twin unit and a manufacturing execution unit (MES).

[0071] The system involves the following equipment: a composite robot, a pipetting robot, a capping machine, a gas chromatography-mass spectrometry (GC-MS) system, a liquid chromatograph (LC-MS) system, a weighing robot, and a PLC control cabinet. The capping machine is controlled by the PLC control cabinet. The composite robot in this invention refers to a mobile operating robot with a movable chassis and a 6-axis robotic arm. The movable chassis is composed of Mecanum wheels, enabling omnidirectional movement. It can autonomously move sample modules to the target chemical experimental workstation and clamp the sample modules or sample vials within the sample modules to the chemical instruments at the target chemical experimental workstation for corresponding chemical operations.

[0072] The digital twin unit is used to establish a digital twin model of the chemical laboratory and chemical robot as a whole. The digital twin model collects the overall operation data and simulation data of the high-throughput chemical experiment to form a real-time signal, and sends the real-time signal to the production execution unit. The digital twin unit receives the feedback signal sent by the production execution unit and performs simulation optimization based on the feedback signal. The digital twin model sends the second production instruction signal generated after simulation optimization to the production execution unit.

[0073] The production execution unit (MEP) is used to input production instructions and output a first production instruction signal. Based on the first and second production instruction signals, the MEP controls the robot to perform chemical experimental operations. The MEP feeds back the production result signal to the digital twin unit. The MEP, as shown in the example,... Figure 2 As shown.

[0074] The production execution unit is built based on the MVVM (Model-View-ViewMode) architecture of WPF (Windows Presentation Foundation), including the order module, editing module, log module, and experiment module;

[0075] The editing module is used to edit new experiments based on the operations that existing equipment and robots can perform, and send the first production instruction signal and the second production instruction signal to the order module;

[0076] The order module is used to add experiments to be completed in the laboratory and send the first production instruction signal and the second production instruction signal to the experiment module;

[0077] The log module is used to record the daily system operations, including order experiments generated by the first and second production command signals.

[0078] The experimental module is used to receive the first production instruction signal and the second production instruction signal, and to execute the order experiment according to the first production instruction signal and the second production instruction signal.

[0079] The experimental module includes a monitoring module and a task module;

[0080] The monitoring module is used to monitor the status of various devices in the chemistry laboratory in real time. The status of each device includes whether the device is online, whether it is working properly, whether the composite robot is using the wireless charging device, experimental information, and experimental progress. Experimental information includes the number of experiments being run, the name of the currently running experiment (empty if there is no experiment), and the operator of the current experiment. The experimental progress displays the name of the currently running experiment (empty if there is no experiment), the experimental equipment (the experimental equipment currently in motion), and the current task (the operation performed by the currently running experimental equipment).

[0081] The task module is used to receive the first production instruction signal and the second production instruction signal. The task module is connected to the digital twin unit for communication. The task module receives feedback from the composite robot and corresponding equipment. The task module controls the composite robot and other equipment to perform relevant high-throughput chemical experimental operations to realize the order experiment.

[0082] like Figure 4 As shown, the task module includes a task receiving submodule, a navigation and positioning control submodule, a multi-site control submodule, a task feedback submodule, and a fault handling submodule;

[0083] The task receiving submodule is used to receive the first production instruction signal and the second production instruction signal sent by the order module and send them to the navigation and positioning control submodule;

[0084] The navigation and positioning control submodule is communicatively connected to the task receiving submodule. The navigation and positioning control submodule receives the first production instruction signal and the second production instruction signal and gives the corresponding navigation and positioning signal according to the first production instruction signal and the second production instruction signal. The composite robot reaches the target chemical experiment work station according to the navigation and positioning signal.

[0085] The multi-site control submodule is used to control the composite robot to complete the corresponding chemical experiment operation according to the corresponding operation procedure of the target chemical experiment workstation;

[0086] The task feedback submodule communicates with the digital twin unit, which displays the working status of the composite robot and corresponding equipment in real time. The task feedback submodule obtains the execution results of the composite robot for the order experiment and the task completion status of each workstation from the digital twin unit and sends feedback signals to the digital twin unit.

[0087] The fault handling submodule is used to stop the ongoing chemical experiment operation of the composite robot when a fault occurs in the composite robot and the corresponding equipment, and wait for the staff to handle and troubleshoot the cause of the fault.

[0088] The multi-site control submodule includes a map origin control submodule, an initial sample placement control submodule, a weighing robot control submodule, a liquid chromatograph control submodule, a gas chromatography-mass spectrometry system control submodule, a pipetting robot control submodule, a reaction zone control submodule, and a capping machine control submodule;

[0089] The map origin control submodule is used to control the operation of resetting the composite robot to the map origin.

[0090] The initial sample placement control submodule is used to control the composite robot to grasp the sample at the initial position and handle waste samples;

[0091] The weighing robot control submodule is used to control the operation of placing the sample with the required amount of reagent into the weighing robot workstation and the operation of taking out the weighed sample, as well as the operation of the weighing robot.

[0092] The liquid chromatograph control submodule is used to control the operation of placing the sample to be analyzed by liquid chromatography into the liquid chromatograph workstation and the operation of removing the sample after chromatographic analysis, as well as to control the operation of the liquid chromatograph.

[0093] The gas chromatography-mass spectrometry (GC-MS) control submodule is used to control the operation of placing samples to be analyzed by gas chromatography and mass spectrometry into the GC-MS workstation and removing samples after gas chromatography and mass spectrometry analysis, as well as to control the operation of the GC-MS.

[0094] The pipetting robot control submodule is used to control the operation of placing the sample module that needs to be added with chemical reagents and solutions into the pipetting robot workstation and the operation of taking out the sample module after pipetting, as well as the operation of controlling the pipetting robot.

[0095] The reaction zone control submodule is used to control the operation of placing the sample module that needs to be heated and oscillated into the reaction zone workstation and the operation of taking out the sample module after the reaction, as well as the operation of controlling the oscillation and heating equipment.

[0096] The capping machine control submodule is used to control the operation of placing the sample module that needs to be capped or unscrewed into the capping machine workstation and the operation of taking out the sample module after capping, as well as the operation of controlling the movement of the capping machine.

[0097] The map origin control submodule controls the operation of resetting to the map origin in the following ways: entering the map origin task, controlling the six-axis robotic arm of the composite robot to reset, controlling the chassis of the composite robot to move to the map origin, and completing the task of reaching the map origin.

[0098] The initial sample placement control submodule controls the operation of the sample placement task and the waste sample handling task in the following ways: entering the initial sample grasping task, controlling the composite robot to grasp the sample and complete the initial sample grasping task; entering the waste sample handling task, controlling the composite robot to grasp the waste sample, move it to the dedicated waste recycling area, place the waste sample, and complete the waste sample handling task.

[0099] The weighing robot control submodule controls the operation of placing samples requiring quantitative reagents and retrieving weighed samples in the following manner: Entering the sample placement task, the module controls the composite robot to place the sample requiring quantitative reagents into the weighing robot workstation; the weighing robot then places the sample into the reagent-adding device, starts the reagent-adding device, and completes the sample placement task; entering the sample retrieval task, the module controls the composite robot to retrieve the sample from the weighing robot workstation, and completes the sample retrieval operation.

[0100] The liquid chromatograph control submodule controls the operations of placing samples for liquid chromatographic analysis and retrieving samples after chromatographic analysis in the following manner: entering the liquid chromatographic sample placement task, controlling the composite robot to place the sample into the liquid chromatograph, starting the liquid chromatograph, and completing the liquid chromatographic sample placement task; entering the post-chromatographic sample retrieval task, controlling the composite robot to retrieve the post-chromatographic sample from the liquid chromatograph, and completing the post-chromatographic sample retrieval task.

[0101] The gas chromatography-mass spectrometry (GC-MS) control submodule controls the operation of placing samples for GC-MS analysis and retrieving samples after GC-MS analysis in the following manner: Entering the sample placement task, controlling the composite robot to place the sample into the GC-MS, starting the GC-MS, and completing the sample placement task; entering the sample retrieval task, controlling the composite robot to retrieve the sample after GC-MS analysis from the GC-MS, and completing the sample retrieval task.

[0102] The pipetting robot control submodule controls the operations of placing the sample module requiring chemical reagents and liquids and retrieving the sample module after pipetting in the following manner: Entering the sample placement task, the composite robot is controlled to place the sample module at the pipetting robot workstation; the pipetting robot then adds the corresponding chemical reagents or solutions to the sample, completing the sample placement task. Entering the sample retrieval task, the composite robot is controlled to retrieve the sample module from the pipetting robot workstation, completing the sample retrieval task.

[0103] The reaction zone control submodule controls the tasks of placing the sample module requiring heating and agitation and retrieving the sample module after reaction in the following ways: Entering the task of placing the sample module requiring heating and agitation, controlling the composite robot to place the sample module into the reaction zone workstation, activating the heating and agitation equipment, and completing the task of placing the sample module requiring heating and agitation; entering the task of retrieving the sample module after reaction, controlling the composite robot to retrieve the sample module after reaction from the reaction zone workstation, and completing the task of retrieving the sample module after reaction.

[0104] The capping machine control submodule controls the operation of placing the sample module that needs to be capped or unscrewed, and the operation of removing the capped sample module in the following manner: entering the task of placing the sample module that needs to be capped or unscrewed, controlling the composite robot to place the sample module that needs to be capped or unscrewed at the capping machine workstation, starting the capping machine, completing the capping or unscrewing operation, and completing the task of placing the sample module that needs to be capped or unscrewed; entering the task of removing the capped sample module, controlling the composite robot to remove the capped sample module from the capping machine workstation, and completing the task of removing the capped sample module.

[0105] (II) Model building of digital twin units;

[0106] In this invention, a multi-software collaborative approach is employed to construct the digital twin model. SolidWorks and 3ds Max are used for the creation, texturing, and rendering optimization of the twin model, enabling it to describe the basic parameters of the physical device and achieving good spatiotemporal consistency between the physical and virtual components. The development of 3D visualization software is completed on the Unity 3D platform, primarily including 3D visualization of the device model, human-computer interaction, and dynamic control of the digital twin model, such as... Figure 6 As shown.

[0107] Specifically, the construction of the entire intelligent laboratory digital twin model mainly consists of three parts: the macro scene of the laboratory, the host equipment and its auxiliary equipment, and the texture materials and rendering materials.

[0108] The macro-level laboratory scenario refers to the overall framework of the smart laboratory, including the laboratory model, layout, lighting system, skybox, etc. The modeling scale of the macro-level laboratory scenario relies on the existing equipment models in the project. The laboratory model is constructed based on the size of the equipment to perfectly replicate the actual laboratory.

[0109] The models of the main equipment and its auxiliary machines were saved during the design process before the company's production trials. These models were also built using 3D modeling software and only needed to be converted to an intermediate format supported by 3ds Max. Lightweight operations were then performed in 3ds Max to ensure the most efficient use of the hardware.

[0110] Textures and materials are primarily obtained in two ways: simulation generation in 3ds Max and extraction from physical objects. For example, ground textures can be generated through simulation in 3ds Max, randomly generating multiple tiny bumps and imperfections on a complete plane as texture materials. Another method involves photographing physical objects and then using professional image processing tools like Photoshop to create 3D textures. Finally, these are imported directly into Unity3D as .MAT files.

[0111] Real-time data collected from the real laboratory and virtual feedback signals output from the virtual twin laboratory simulation enable interconnection and mapping between the real and virtual laboratories. This allows for the controller program to control the virtual twin model, the virtual twin laboratory to provide virtual feedback to the controller, and the real-time acquisition of information such as the start / stop status of experimental equipment, control commands, operating parameter data, operating status data, and abnormal data during operation. Various physical controllers are connected to the virtual twin laboratory data acquisition client. The virtual twin device performs corresponding actions based on the data acquired by the client and outputs corresponding virtual feedback signals.

[0112] (III) Establishing communication between the digital twin unit and the production execution unit;

[0113] To realize the aforementioned high-throughput chemical experiment robot autonomous management and scheduling system and equipment, communication between the various devices needs to be established first. This includes the following steps: 1. Communication between devices uses the TCP / IP communication protocol, setting IP addresses for each device to achieve connectivity. 2. Using a network switch, each device is connected to the same local area network, facilitating device management, data transmission and reception, and information exchange between devices.

[0114] like Figure 3 The diagram shows the communication between all devices, which is achieved through the TCP / IP protocol. The IP addresses of each device are as follows (note that this is for demonstration purposes only and does not represent actual IP addresses):

[0115] Composite robot IP address: 192.168.2.50

[0116] The IP address of the pipetting robot is 192.168.2.51.

[0117] Capping machine (PLC control cabinet) IP address: 192.168.2.52

[0118] Weighing robot IP address: 192.168.2.53

[0119] IP address of the gas chromatography-mass spectrometry (GC-MS) instrument: 192.168.2.54

[0120] Liquid chromatograph IP address: 192.168.2.55

[0121] After configuring the IP addresses of all devices, connect all devices to the same local area network through a dedicated network switch to prevent interference from other devices. Once connected, the devices can send corresponding data to each other.

[0122] (iv) Navigation and positioning algorithms for composite robots;

[0123] In this invention, the navigation and localization algorithm for the composite robot is the AMCL (Adaptive Monte Carlo Localization) algorithm, an adaptive Monte Carlo localization method. It can fuse multimodal data collected by sensors such as LiDAR and RGBD depth cameras, effectively improving the robot's localization accuracy in intelligent laboratories. In addition, an auxiliary localization algorithm based on binary square reference markers is used for the spatial localization of the composite robot's mobile chassis and for compensating for the spatial pose of objects during the robotic arm's grasping process.

[0124] When the composite robot moves to a specific workstation, the robotic arm cannot accurately grasp the object due to chassis movement errors. At this time, the handheld camera at the end of the robotic arm takes a picture of the square reference of the workstation. Combined with the pose information of the square reference in the robotic arm's base coordinate system when the workstation is calibrated and the relative pose algorithm, the spatial pose of the object to be grasped in the robotic arm's base coordinate system is calculated after the mobile chassis is repositioned. This guides the robotic arm to complete the precise grasping, which also ensures the repeatability and positioning accuracy of grasping and handling multiple samples in high-throughput chemical experiments.

[0125] Furthermore, since the cumulative errors of sensors such as LiDAR and assembly errors can cause positioning errors in the repeated positioning of the mobile chassis, square references are affixed to the ground at each workstation. The chassis positioning camera is used to photograph these references and detect their spatial pose in the chassis positioning camera coordinate system. By comparing the pose information of the square references when calibrating the workstations, the offset errors of the mobile chassis in the X and Y axes and the angular rotation errors around the Z axis are obtained. These errors are then compensated to control the mobile chassis to move precisely to the actual workstation, enabling the robot to achieve precise positioning in multiple workstations in high-throughput chemical experiments.

[0126] (v) Digital twins combined with production execution units;

[0127] The digital twin unit continuously collects overall operational and simulation data from high-throughput chemistry experiments and continuously improves the equipment twin model related to the entire experiment. This data is then interacted with the production execution unit, providing data support for improving the efficiency of high-throughput chemistry experiments and the output of experimental samples, and also providing a basis for decision optimization of the entire system.

[0128] (1) Achieve full-process visualization of the experimental phase.

[0129] By integrating digital twin technology to construct a twin device model that maps to the actual physical equipment, the operation process of the smart laboratory can be displayed more completely and intuitively. Data visualization technology is then comprehensively applied to provide visual monitoring of the entire operation process. Simultaneously, adjustments made to the twin model by management personnel can be synchronously mapped onto the physical equipment.

[0130] (2) It can better collect and store data.

[0131] All data related to the smart laboratory flows into the twin data module, such as laboratory operation status, experimental progress, equipment failure information, equipment operation time, virtual simulation results and auxiliary decision-making information, etc. After the system comprehensively summarizes the experimental data, it saves it as laboratory big data.

[0132] (3) Provide virtual simulation for the system to realize optimization analysis and autonomous decision-making mechanism.

[0133] A twin lab is a virtual counterpart to a physical lab on a computer, mapping its functions and behaviors. For example, upon receiving a personalized experimental plan, the twin lab can virtually simulate equipment operation, material consumption, and completion time, feeding the results back to the management system. Furthermore, it can receive operational data from the real lab, continuously optimizing the virtual simulation analysis algorithm.

[0134] (4) Optimization of processes through human intervention via digital twins

[0135] Real-time feedback from digital twin units not only helps observe the experimental process, but also allows observers to make changes and perform simulation optimizations when they believe the experimental process needs improvement. Human intervention in process planning provides another way to find better processes. In addition to optimizing machine systems, digital twin units reduce the cost and time of process optimization.

[0136] Example 1

[0137] Taking the high-throughput chemistry experiment section as an example, the sequential workstation workflow for this section is as follows: pipetting robot workstation, capping machine workstation, wireless charging station, capping machine workstation, reaction zone workstation, capping machine workstation, wireless charging station workstation, capping machine workstation, and pipetting robot workstation.

[0138] The composite robot arrives at the pipetting robot workstation; it picks up the 48-well plate module at position 2-2 of the pipetting robot and places it on the cart platform; the composite robot moves to the capping machine workstation; the capping machine moves to the right standby position; a blue module is placed on the capping machine; the capping machine resets; the capping machine moves to the left standby position; the capping machine screws on the #1 48 bottle cap; if the composite robot waits for more than 15 minutes, it moves to the wireless charging station for wireless charging; the capping machine finishes its work and moves to the right standby position; the composite robot arrives at the capping machine workstation and picks up the blue module from it; the composite robot arrives at the reaction zone workstation and picks up the module from the cart and places it on the vibration device; etc. After oscillation is complete, the composite robot picks up the module from the oscillation device and places it on the trolley; the composite robot moves to the capping machine workstation; the capping machine reaches the right standby position; the blue module is placed on the capping machine; the capping machine resets; the capping machine reaches the left standby position; the capping machine loosens the cap of bottle #148; if the waiting time exceeds 15 minutes, the composite robot moves to the wireless charging station for wireless charging; the capping machine finishes its work and reaches the right standby position; the composite robot reaches the capping machine workstation and picks up the blue module from the capping machine workstation; the composite robot reaches the pipetting robot workstation; the composite robot picks up the blue module and places it at position 2-2 of the pipetting robot workstation.

[0139] For the movement and operation scenarios of the composite robot at various chemical experimental workstations, a main state machine Main-FSM={A,S,Y,s0,F} was designed for the task module. A represents the input alphabet, i.e., the input for each state; s0 represents the initial state of the Main-FSM, i.e., "receiving order information transmitted by the order module"; the state set S = {S0, S1, S2, S3, S4, S5}, where S0 = s0, S1 represents the state "ensuring the robotic arm is in the Home position before moving, i.e., robotic arm reset", S2 represents the state "moving to the target workstation", S3 represents the state "workstation repositioning", and S4 represents the state "being in a certain sub-state machine". Based on the different experimental operations of all 7 workstations involved in the scenario, 7 sub-state machines sub-FSM = {S4-1, S4-2, ..., S4-7} are designed here, S5 represents the termination state, i.e., "ending the current experimental station task and feeding back to workflow management"; S6 represents the state "fault"; Y represents the termination state set Y = {S5} of the Main-FSM; F is the state transition function: A × S → S, and the jump relationship between the states of the state machine is the formal representation of the state transition function.

[0140] Accordingly, state S0 in the Main-FSM corresponds to the task receiving submodule in the task module of the present invention, S1, S2, and S3 correspond to the navigation control and positioning submodule of the task module of the present invention, S4 corresponds to the multi-site control submodule of the task module of the present invention, S5 corresponds to the task feedback submodule of the task module of the present invention, and S6 corresponds to the fault handling module of the task module of the present invention.

[0141] To address the different robotic experimental operations and chemical instrument communications involved in different chemical experimental workstations, sub-state machines (sub-FSMs) were designed for seven workstations.

[0142] Considering the abnormal situations that may occur in high-throughput chemical experiments, the state machine is designed with a "fault" state S6. This state is designed to handle potential fault events that may occur between states S1 and S4. When a fault occurs, the operation of the composite robot and the corresponding equipment is immediately stopped to ensure the system stability of the composite robot. Specifically, S6 includes several different sub-state anomalies, such as... Figure 5 As shown, the faults are categorized into composite robot faults, capping machine faults, and other faults. Specifically, composite robot faults include: camera failing to recognize the positioning QR code, composite robot arm faults, and composite robot chassis faults. Capping machine faults include: servo faults, object falling from the upper gripper, insufficient loosening torque, loose screws, and incorrect orifice plate position. Other faults include: chemical equipment not responding. When the state machine jumps to state S6 "Fault," the composite robot immediately stops the current experimental operation and then jumps to state S5 to feed back to the task receiving submodule.

[0143] In summary, the composite robot and equipment of this invention analyze orders through the production execution unit, and the digital twin unit collects information such as the start-up and shutdown status, control commands, operating parameter data, operating status data, and abnormal data of the experimental equipment in real time, and feeds the information back to the production execution unit. The experimental process is planned for the highest priority experiment to be executed, and the composite robot is managed to cooperate with other equipment to complete high-throughput chemical experiments.

[0144] Example 2

[0145] The process of building a digital twin unit for the composite robot is as follows: The physical model of the composite robot is mainly divided into an upper robotic arm and a lower mobile chassis. For the robotic arm, a model is created in the modeling software, then lightweighted, and its materials and appearance are processed to match the real world. For the mobile chassis, Mecanum wheels and chassis models are created in the modeling software, lightweighted, and their materials and textures are processed to match the real world. The robotic arm model and the mobile chassis model are then assembled. The entire composite robot model file is converted to a different format and imported into the corresponding development software. The collected real data and the virtual feedback signals output by the twin simulation are compared to achieve controller program control of the composite robot model and mapping of the twin model to the real robot.

[0146] Example 3

[0147] High-throughput chemistry experiments involve multiple samples, necessitating sample vial modules during preparation. Each module contains 48 vials, and operations such as reagent addition and shaking are required, all involving opening and closing the vials. Since a single module contains many samples and multiple modules are involved in a single experiment, significant time is consumed in opening and closing the vials. Consequently, the composite robot needs to transport the sample modules to different workstations and waits for extended periods at the capping machine, reducing experimental efficiency. To address this, digital twin simulations are used to improve the process. The simulated data is then used by the production execution unit to optimize the experimental workflow, thereby reducing the time spent on opening and closing the vials.

[0148] Specifically, the composite robot arrives at the capping machine station, picks up 48 sample modules, and places them there. The capping machine resets and begins tightening caps, while the composite robot waits at the capping machine station for the capping to complete. At this time, the operator can modify the composite robot's task via a digital twin unit. The robot can either go to the wireless charging station to recharge, or go to the pipetting station to assist the pipetting robot, accelerating the pipetting process. Alternatively, the composite robot can assist when other stations are capping or tightening caps. However, this doesn't always speed up the overall experimental process, as some steps require waiting for the capping machine to finish. Therefore, data from the digital twin simulation can be used to test whether the improved steps optimize the experimental process. Finally, this method determines that when capping or tightening takes more than 15 minutes, the composite robot can use wireless charging while waiting for the capping or tightening process to finish, or for other instruments and equipment to complete their processes. This improves the composite robot's battery life and speeds up the experimental process.

[0149] Example 3

[0150] Sometimes experimental procedures need to be modified. This can be done through simulation using digital twin units to obtain feasible data, which can then be implemented in the real world.

[0151] Specifically, for different chemicals, a heating process needs to be added to the original experimental procedure, which takes 6 hours. This heating is simulated by adding a heating device and a metal sample module to the digital twin unit. The metal sample module has a metal cap that requires a capping machine. After multiple simulations, the correctness of the experimental procedure was confirmed. The heating device was then added in the real laboratory, and the simulation data from the digital twin was imported into the production execution unit to implement the heating process, reducing the costs associated with process changes.

[0152] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features therein. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A high-throughput chemical laboratory robot autonomous management and scheduling system based on digital twins, characterized in that, Includes digital twin units and production execution units; The digital twin unit is used to establish a digital twin model of the chemical laboratory and chemical robot as a whole. The digital twin model collects the overall operation data and simulation data of the high-throughput chemical experiment to form a real-time signal, and the digital twin model sends the real-time signal to the production execution unit. The digital twin unit receives the production result signal sent by the production execution unit and performs simulation optimization based on the production result signal. The digital twin model sends the second production instruction signal generated after simulation optimization to the production execution unit. The simulation optimization method is as follows: the digital twin model receives the production result signal and converts the production result signal into a first experimental process to obtain the time required for the first experimental process; The digital twin model obtains the second experimental procedure based on the external input experiment, and calculates the time required for the second experimental procedure. The digital twin model compares the time required for the first experimental process with the time required for the second experimental process. When the time required for the first experimental process is greater than the time required for the second experimental process, the second experimental process is used as the second production instruction signal; when the time required for the first experimental process is less than the time required for the second experimental process, the first experimental process is used as the second production instruction signal. The production execution unit is used to input production instructions and output a first production instruction signal. The production execution unit controls the robot to perform chemical experiment operations according to the first production instruction signal and the second production instruction signal. The production execution unit feeds back the production result signal to the digital twin unit. The production execution unit includes an order module, an editing module, a log module, and an experiment module; The editing module is used to edit new experiments based on the operations that existing equipment and robots can perform, and send the first production instruction signal and the second production instruction signal to the order module. The order module is used to add experiments to be completed in the laboratory and send the first production instruction signal and the second production instruction signal to the experiment module; The log module is used to record the daily system operations, which include order experiments generated by the first production instruction signal and the second production instruction signal. The experimental module is used to receive the first production instruction signal and the second production instruction signal and execute the order experiment according to the first production instruction signal and the second production instruction signal; The experimental module includes a monitoring module and a task module; The monitoring module is used to monitor the status of various devices in the chemical laboratory in real time. The status of each device includes whether the device is online, whether it is working properly, experimental information, and experimental progress. The task module is used to receive the first production instruction signal and the second production instruction signal. The task module is communicatively connected to the digital twin unit. The task module receives feedback from the composite robot and corresponding equipment. The task module controls the composite robot and other equipment to perform relevant high-throughput chemical experimental operations to realize the order experiment. The task module includes a task receiving submodule, a navigation and positioning control submodule, a multi-site control submodule, a task feedback submodule, and a fault handling submodule. The task receiving submodule is used to receive the first production instruction signal and the second production instruction signal sent by the order module and send them to the navigation and positioning control submodule; The navigation and positioning control submodule is communicatively connected to the task receiving submodule. The navigation and positioning control submodule receives the first production instruction signal and the second production instruction signal and gives the corresponding navigation and positioning signal according to the first production instruction signal and the second production instruction signal. The composite robot moves and positions itself to the target chemical experiment workstation according to the navigation and positioning signal. The multi-site control submodule is used to control the composite robot to complete the corresponding chemical experiment operation according to the corresponding operation procedure of the target chemical experiment work station; The task feedback submodule is communicatively connected to the digital twin unit. The digital twin unit displays the working status of the composite robot and the corresponding equipment in real time. The task feedback submodule obtains the execution results of the composite robot for the order experiment and the task completion status of each workstation from the digital twin unit and sends feedback signals to the digital twin unit. The fault handling submodule is used to stop the ongoing chemical experiment operation of the composite robot when a fault occurs in the composite robot and the corresponding equipment.

2. The autonomous management and scheduling system for high-throughput chemical experimental robots based on digital twins according to claim 1, characterized in that, The digital twin model includes a macroscopic scene of a chemical laboratory, main equipment and its auxiliary equipment, texture materials and rendering materials; The macroscopic scene of the chemical laboratory includes the laboratory model, the laboratory layout, the lighting system, and the skybox.

3. The autonomous management and scheduling system for high-throughput chemical experimental robots based on digital twins according to claim 1, characterized in that, The communication process of various devices in high-throughput chemistry experiments is as follows: In high-throughput chemistry experiments, communication between various devices uses the TCP / IP communication protocol, and IP addresses are set for each device. Use a network switch to connect all the equipment in a high-throughput chemistry experiment to the same local area network.

4. The autonomous management and scheduling system for high-throughput chemical experimental robots based on digital twins according to claim 1, characterized in that, The experimental information includes the number of experiments being run, the name of the currently running experiment, and the operator of the current experiment. The experimental progress displays the name of the currently running experiment, the experimental equipment, and the current task.

5. The autonomous management and scheduling system for high-throughput chemical experimental robots based on digital twins according to claim 4, characterized in that, The composite robot uses a navigation and positioning algorithm for positioning and navigation. The navigation and positioning algorithm includes the AMCL algorithm and an auxiliary positioning algorithm based on binary square reference marks. The auxiliary positioning algorithm based on binary square reference marks is used for spatial positioning of the composite robot's mobile chassis and spatial pose compensation of the object during the robotic arm's grasping process. Square reference markers are affixed to the ground at each chemical experiment workstation; During the process of the composite robot reaching the target chemical experiment workstation based on navigation and positioning signals, if the robotic arm cannot accurately grasp the target due to chassis movement errors, the end-effector camera of the composite robot's robotic arm takes a picture of the target chemical experiment workstation reference, obtaining a three-dimensional QR code of the square reference. The vertices of the three-dimensional QR code are used to form a temporary spatial coordinate system. The temporary spatial coordinate system is compared with the spatial coordinate system during workstation calibration to calculate the offset error of the mobile chassis in the X and Y axes and the angular rotation error around the Z axis. Based on the offset error and rotation error, the error value that needs to be compensated is obtained. The composite robot moves according to the compensated error value to achieve precise positioning.

6. The autonomous management and scheduling system for high-throughput chemical experimental robots based on digital twins according to claim 4, characterized in that, The multi-site control submodule includes a map origin control submodule, an initial sample placement control submodule, a weighing robot control submodule, a liquid chromatograph control submodule, a gas chromatography-mass spectrometry (GC-MS) control submodule, a pipetting robot control submodule, a reaction zone control submodule, and a capping machine control submodule. The map origin control submodule is used to control the operation of resetting the composite robot to the map origin. The initial sample placement control submodule is used to control the composite robot to grasp the sample at the initial position and to process waste samples; The weighing robot control submodule is used to control the operation of placing the sample with the required amount of reagent into the weighing robot workstation and the operation of taking out the weighed sample, as well as the operation of controlling the weighing robot. The liquid chromatograph control submodule is used to control the operation of placing the sample to be analyzed by liquid chromatography into the liquid chromatograph workstation and the operation of taking out the sample after chromatographic analysis, as well as the operation of the liquid chromatograph. The gas chromatography-mass spectrometry (GC-MS) control submodule is used to control the operation of placing samples to be analyzed by gas chromatography and mass spectrometry into the GC-MS workstation and the operation of removing samples after gas chromatography and mass spectrometry analysis, as well as the operation of the GC-MS. The pipetting robot control submodule is used to control the operation of placing the sample module that needs to be added with chemical reagents and solutions into the pipetting robot workstation and the operation of taking out the sample module after pipetting, as well as the operation of controlling the pipetting robot. The reaction zone control submodule is used to control the operation of placing the sample module that needs to be heated and oscillated into the reaction zone workstation and the operation of taking out the sample module after the reaction, as well as the operation of controlling the oscillation and heating equipment. The capping machine control submodule is used to control the operation of placing the sample module that needs to be capped or unscrewed into the capping machine workstation and the operation of taking out the sample module after capping, as well as the operation of controlling the movement of the capping machine.

7. The autonomous management and scheduling system for high-throughput chemical laboratory robots based on digital twins according to claim 6, characterized in that, The map origin control submodule controls the operation of resetting to the map origin in the following ways: entering the map origin task, controlling the six-axis robotic arm of the composite robot to reset, controlling the chassis of the composite robot to move to the map origin, and completing the task of reaching the map origin. The initial sample placement control submodule controls the operation of the sample placement task and the operation of the waste sample handling task in the following manner: entering the initial sample grasping task, controlling the composite robot to grasp the sample, and completing the initial sample grasping task; entering the waste sample handling task, controlling the composite robot to grasp the waste sample, move it to the dedicated waste recycling area, place the waste sample, and complete the waste sample handling task. The weighing robot control submodule controls the operation of placing samples requiring quantitative reagents and retrieving weighed samples in the following manner: Entering the sample placement task, the composite robot is controlled to place the sample requiring quantitative reagents into the weighing robot workstation; the weighing robot operates, placing the sample into the reagent-adding device; the reagent-adding device is activated, completing the sample placement task; entering the sample retrieval task, the composite robot is controlled to retrieve the sample from the weighing robot workstation, completing the sample retrieval operation. The liquid chromatograph control submodule controls the operation of placing samples for liquid chromatographic analysis and retrieving samples after chromatographic analysis in the following manner: entering the liquid chromatographic sample placement task, controlling the composite robot to place the sample into the liquid chromatograph, starting the liquid chromatograph, and completing the liquid chromatographic sample placement task; entering the post-chromatographic analysis sample retrieval task, controlling the composite robot to retrieve the post-chromatographic analysis sample from the liquid chromatograph, and completing the post-chromatographic analysis sample retrieval task. The gas chromatography-mass spectrometry (GC-MS) control submodule controls the operation of placing samples requiring GC-MS analysis and retrieving samples after GC-MS analysis in the following manner: Entering the sample placement task, controlling the composite robot to place the sample into the GC-MS, starting the GC-MS, and completing the sample placement task; entering the sample retrieval task, controlling the composite robot to retrieve the sample after GC-MS analysis from the GC-MS, and completing the sample retrieval task. The pipetting robot control submodule controls the operation of placing the sample module requiring chemical reagents and liquids and retrieving the sample module after pipetting in the following manner: Entering the sample placement task, the composite robot is controlled to place the sample module at the pipetting robot workstation, and the pipetting robot operates to add the corresponding chemical reagents or solutions into the sample, completing the sample placement task; entering the sample retrieval task, the composite robot is controlled to retrieve the sample module after pipetting from the pipetting robot workstation, completing the sample retrieval task. The reaction zone control submodule controls the tasks of placing the sample module requiring heating and oscillation and retrieving the sample module after reaction in the following manner: Entering the task of placing the sample module requiring heating and oscillation, controlling the composite robot to place the sample module into the reaction zone workstation, activating the heating and oscillation equipment, and completing the task of placing the sample module requiring heating and oscillation; entering the task of retrieving the sample module after reaction, controlling the composite robot to retrieve the sample module after reaction from the reaction zone workstation, and completing the task of retrieving the sample module after reaction. The capping machine control submodule controls the operation of placing the sample module that needs to be capped or unscrewed, and the operation of removing the capped sample module in the following manner: entering the task of placing the sample module that needs to be capped or unscrewed, controlling the composite robot to place the sample module that needs to be capped or unscrewed at the capping machine workstation, starting the capping machine, completing the capping or unscrewing operation, and completing the task of placing the sample module that needs to be capped or unscrewed; entering the task of removing the capped sample module, controlling the composite robot to remove the capped sample module from the capping machine workstation, and completing the task of removing the capped sample module.

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