Flexible assembly line man-machine cooperation dynamic security domain construction method and device, medium and product
Through digital twin technology and optimization algorithms, virtual models are built in real time and security domains are dynamically adjusted, which solves the problem that traditional static security domains cannot adapt to changes in flexible assembly line tasks, and achieves the security and efficiency improvement of human-machine collaboration.
Patent Information
- Application Number
- CN202510359201.9
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-03-25
- Publication Date
- 2025-07-11
AI Technical Summary
Traditional static security domains cannot adapt to rapidly changing task requirements and dynamic interactions on flexible assembly lines, resulting in insecurity and inefficiency.
The virtual model is built in real time using digital twin technology, combined with optimization algorithms to dynamically adjust the security domain, and based on real-time human-computer collaboration status data, adaptive adjustment of the security domain is realized.
Improve the safety and efficiency of human-machine collaboration, ensuring the safety and productivity of operators and robots.
Smart Images
Figure CN120297895A_ABST
Abstract
Description
Technical Field
[0001] The present application relates to the field of human - machine collaboration safety control, and particularly to a method, device, medium and product for constructing a dynamic safety domain for human - machine collaboration in a flexible assembly line. Background Art
[0002] In the flexible assembly lines of modern manufacturing, the application of human - machine collaboration technology is becoming more and more extensive. With the close cooperation between robots and operators, traditional static safety domains cannot adapt to rapidly changing task requirements and dynamic interactions. Currently, the construction methods of safety domains usually set fixed safety distances or regions based on experience or industry standards. The following problems exist in practical applications:
[0003] 1) Task diversity: The complexity and diversity of assembly tasks lead to different safety requirements, and a fixed safety domain cannot adapt to all tasks.
[0004] 2) Interaction dynamics: During the human - machine collaboration process, the interaction between the operator and the robot is dynamic, and traditional safety domains cannot respond in real - time to the time - varying behaviors between the robot and the operator.
[0005] 3) Real - time performance: Assembly tasks require real - time adjustment of working states, and traditional safety domains cannot react quickly, which may affect production efficiency and safety.
[0006] Therefore, a new safety domain construction method is needed to be able to flexibly construct a safety domain with strong adaptability and self - adaptive adjustment based on real - time data and task dynamics, so as to ensure the safety and efficiency of the collaboration between the operator and the robot. Summary of the Invention
[0007] The purpose of the present application is to provide a method, device, medium and product for constructing a dynamic safety domain for human - machine collaboration in a flexible assembly line, which can construct a safety domain with strong adaptability and self - adaptive adjustment, ensure the safety and efficiency of the collaboration between the operator and the robot, and thus provide a strong guarantee for the production efficiency and safety of the flexible assembly line.
[0008] To achieve the above purpose, the present application provides the following solutions:
[0009] In the first aspect, the present application provides a method for constructing a dynamic safety domain for human - machine collaboration in a flexible assembly line, including:
[0010] Obtaining human - machine collaboration status data in real - time;
[0011] Using digital twin technology to perform real - time construction of a virtual model based on the human - machine collaboration status data, and obtaining the dynamic information of human - machine collaboration in the virtual model in real - time;
[0012] Based on the types of tasks on the flexible assembly line and the safety requirements in each task stage, the safety domain is initially set;
[0013] Using an optimization algorithm, the initially set safety domain is dynamically adjusted in real time based on the dynamic information of human-robot collaboration.
[0014] Optionally, the human-robot collaboration state data includes the state data of the robot, the state data of the operator, and the state data of the working environment where the robot and the operator are located; the state data of the robot includes the working state of the robot, the actions of the robot, and the working trajectory of the robot; the state data of the operator includes the working state of the operator and the actions of the operator; the state data of the working environment where the robot and the operator are located includes the operating state of the equipment in the working environment and the spatial changes of the working environment.
[0015] Optionally, the dynamic information of human-robot collaboration includes the relative positions between the operator and the robot, the pose information of the operator and the robot, and the action information of the operator and the robot.
[0016] Optionally, based on the types of tasks on the flexible assembly line and the safety requirements in each task stage, initially setting the safety domain includes:
[0017] Analyzing the types of tasks on the flexible assembly line to obtain the risk factors existing in the task process;
[0018] Determining the safety requirements for different task stages based on the risk factors;
[0019] Based on the safety requirements for different task stages, combining with empirical rules to initially set the scope and shape of the safety domain.
[0020] Optionally, based on the safety requirements for different task stages, combining with empirical rules to initially set the scope and shape of the safety domain, including:
[0021] Based on the safety requirements for different task stages, combining with empirical rules to determine the minimum safety distance between the operator and the robot in each task stage;
[0022] Taking the minimum safety distance between the operator and the robot as the boundary of the initially set safety domain to obtain the scope and shape of the initially set safety domain.
[0023] Optionally, using an optimization algorithm to dynamically adjust the initially set safety domain in real time based on the dynamic information of human-robot collaboration, including:
[0024] Obtaining a risk assessment result based on the dynamic information of human-robot collaboration;
[0025] Using an optimization algorithm to determine and update the boundary of the initially set safety domain based on the risk assessment result to achieve real-time dynamic adjustment of the initially set safety domain.
[0026] Optionally, the optimization algorithm is a constrained optimization method or a gradient descent method.
[0027] In a second aspect, the present application provides a computer device, including: a memory, a processor, and a computer program stored on the memory and executable on the processor, where the processor executes the computer program to implement the steps of the above-provided method for constructing a flexible assembly line human-machine collaboration dynamic safety domain.
[0028] In a third aspect, the present application provides a computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, it implements the steps of the above-provided method for constructing a flexible assembly line human-machine collaboration dynamic safety domain.
[0029] In a fourth aspect, the present application provides a computer program product, including a computer program, and when the computer program is executed by a processor, it implements the steps of the above-provided method for constructing a flexible assembly line human-machine collaboration dynamic safety domain.
[0030] According to the specific embodiments provided by the present application, the present application has the following technical effects:
[0031] The present application provides a method, device, medium, and product for constructing a flexible assembly line human-machine collaboration dynamic safety domain. By using digital twin technology, a real-time virtual model is constructed based on human-machine collaboration state data, and the dynamic information of human-machine collaboration in the virtual model is obtained in real time, providing a basis for the construction of the dynamic safety domain. After initially setting the safety domain based on the type of tasks on the flexible assembly line and the safety requirements in each task stage, an optimization algorithm is used to dynamically adjust the initially set safety domain in real time based on the dynamic information of human-machine collaboration, and a safety domain that can be dynamically adjusted according to the task type, environmental changes, and operator behavior is constructed, improving the adaptability of the safety domain and realizing the adaptive adjustment of the safety domain to ensure the safety and efficiency of the collaboration between the operator and the robot, and thus providing a strong guarantee for the production efficiency and safety of the flexible assembly line. Description of the Drawings
[0032] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the following will briefly introduce the drawings required to be used in the embodiments. Obviously, the drawings in the following description are only some embodiments of the present application, and those of ordinary skill in the art can obtain other drawings based on these drawings without creative efforts.
[0033] Figure 1 It is a schematic flowchart of a method for constructing a flexible assembly line human-machine collaboration dynamic safety domain provided by an embodiment of the present application;
[0034] Figure 2A schematic structural diagram of a computer device provided by an embodiment of the present application. Detailed implementation manners
[0035] Next, the technical solutions in the embodiments of the present application will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present application.
[0036] To make the above objects, features, and advantages of the present application more obvious and understandable, the present application will be further described in detail below in conjunction with the accompanying drawings and specific implementation manners.
[0037] In an exemplary embodiment, the present application provides a method for constructing a dynamic safety domain for human-robot collaboration on a flexible assembly line. This method is executed by a computer device, which can be specifically executed by a computer device such as a terminal or a server alone, or jointly executed by a terminal and a server. In the embodiments of the present application, this method is described by taking its application to a server as an example. As Figure 1 shown, this method includes:
[0038] Step 100: Real-time obtain human-robot collaboration status data. Among them, the human-robot collaboration status data includes the status data of the robot, the status data of the operator, and the status data of the working environment where the robot and the operator are located. The status data of the robot includes the working status of the robot, the actions of the robot, and the working trajectory of the robot. The status data of the operator includes the working status of the operator and the actions of the operator. The status data of the working environment where the robot and the operator are located includes the running status of the equipment in the working environment and the spatial changes of the working environment.
[0039] Step 101: Use digital twin technology to construct a virtual model in real time based on the human-robot collaboration status data, and real-time obtain the dynamic information of human-robot collaboration in the virtual model. Among them, the dynamic information of human-robot collaboration includes the relative positions between the operator and the robot, the pose information of the operator and the robot, and the action information of the operator and the robot.
[0040] Step 102: Based on the types of tasks on the flexible assembly line and the safety requirements in each task stage, initially set the safety domain.
[0041] Step 103: Use an optimization algorithm to perform real-time dynamic adjustment on the initially set safety domain based on the dynamic information of human-robot collaboration.
[0042] In another exemplary embodiment of the present application, state data of the robot, the operator, and the surrounding environment (i.e., the working environment) involved in step 100 can be collected in real time through integrated sensors (such as position sensors, vision sensors, etc.), and in step 101, these data are mapped into the virtual model in real time through digital twin technology to reflect the relative positions, postures, and motion information between the operator and the robot.
[0043] By performing real-time modeling on the operator's actions, the robot's trajectory, changes in the working environment, etc., dynamic information of human-robot collaboration is obtained, providing a basis for the construction of the dynamic safety zone. Based on this information, a virtual safety bubble (i.e., the safety zone) can be constructed in real time, and this safety bubble can change dynamically as the task progresses, the operator's behavior, and the environment change.
[0044] In the actual application process, in order to further improve the efficiency of data application, integrated sensors can be used to perform real-time modeling on the operator's actions, the robot's trajectory, changes in the working environment, etc. Among them, during the modeling process of the robot's position and posture, the position and posture matrix of the robot is collected and updated in real time. The position of the robot is represented as p r =[x r ,y r ,z r T ,[x r ,y r ,z r is the position coordinate matrix of the robot, and T represents the transpose of the matrix. The posture matrix of the robot is represented as R r , and the obtained mathematical model of the robot's position and posture is represented as The mathematical model of the operator's position and actions is represented as p o is the position of the operator, and θ o is the joint angle of the operator. The state model of the objects and obstacles in the environment is represented as p i is the position of object i, R i is the rotation of object i, and S i is the shape information of object i.
[0045] Taking the models constructed above as sensing data and integrating them into the digital twin system to obtain a state vector, which can be used for subsequent safety zone optimization and risk assessment.
[0046] In another exemplary embodiment of the present application, the requirements for the initially set safety domain vary greatly for different assembly tasks. The known traditional methods usually define the safety domain using a fixed safety distance and cannot make flexible adjustments according to the task type and task stage. To solve this problem, a task-driven dynamic construction of the safety domain can be achieved based on the construction method of the safety domain according to the task type and status. Based on this, in this embodiment, the implementation manner of the above step 102 can be replaced by the following steps (1) to (3).
[0047] Step (1): Analyze the risk factors existing in the task process based on the type analysis of the tasks on the flexible assembly line.
[0048] Step (2): Determine the safety requirements for different task stages based on the risk factors.
[0049] Step (3): Based on the safety requirements for different task stages, combine the empirical rules to initially set the scope and form of the safety domain.
[0050] Furthermore, in the actual application process, the above steps (1) and (2) are mainly for task requirement analysis and safety requirement definition. Among them, according to the types of different assembly tasks (such as assembly, handling, inspection, etc.), analyze the possible risk factors in the task process, and define different safety requirements according to different stages of the task (preparation, execution, completion, etc.). For example, in the complex assembly stage, a larger safety distance is required between the operator and the robot, while in the simple handling task, the safety domain can be relatively small.
[0051] Based on the above description, in this embodiment, the construction process of the task stage-driven safety domain can be described as: dynamically adjusting the form and size (i.e., scope) of the safety domain according to different stages of the task. In the initial stage of the task (such as the preparation stage), a very strict safety distance may not be required, while in the high-risk stages of the task (such as assembly, welding, etc.), the safety domain will automatically expand to ensure the safety of the operator.
[0052] Still further, the traditional safety domain construction methods usually only rely on empirical rules to set the safety distance, but these rules cannot cope with complex dynamic interactions. Based on this, the present application combines the empirical rules of experts in the field in the above step (3) and adopts a mathematical optimization algorithm to construct the safety domain in an adaptive adjustment manner. Among them:
[0053] Step 1): Application of empirical rules: Based on the empirical rules of domain experts and industry standards, initially set the boundary of the safety domain (such as the minimum safety distance between the operator and the robot). The empirical rules and industry standards can provide a preliminary framework for the dynamic construction of the safety domain.
[0054] Step 2), Dynamic adjustment driven by optimization algorithms: Based on Step 1), use optimization algorithms (such as constrained optimization method, gradient descent method, optimal control, etc.) to dynamically adjust the initially set safety domain. During the actual application process, the optimization algorithm will determine the potentially risky areas in the current state according to the data collected by the integrated sensors in real time, and adjust the boundaries of the safety domain. For example, when the operator's actions approach the robot, or the robot's actions are relatively sharp, the boundaries of the safety domain are automatically expanded. Conversely, when the robot maintains a safe distance from the operator, the safety domain is reduced, thereby improving work efficiency.
[0055] Based on the descriptions of the above Step 1) and Step 2), the implementation manner of Step (3) provided in this application can be replaced by the following Step 1 and Step 2. Among them:
[0056] Step 1, Based on the safety requirements in different task phases, combine empirical rules to determine the minimum safe distance between the operator and the robot in each task phase.
[0057] Step 2, Use the minimum safe distance between the operator and the robot as the boundary of the initially set safety domain to obtain the range and shape of the initially set safety domain.
[0058] In another exemplary embodiment of this application, in order to realize the dynamic construction of the safety domain, a real-time risk assessment and dynamic safety domain update mechanism can also be set up. By monitoring the states of the operator and the robot in real time, potential safety risks are evaluated, and the size and shape of the safety domain are adjusted according to the risk assessment results. Based on this, the implementation manner of Step 103 provided in this application can be replaced by the following Step 1 and Step 2.
[0059] Step 1, Obtain a risk assessment result based on the dynamic information of human-robot collaboration.
[0060] Step 2, Use an optimization algorithm to determine and update the boundary of the initially set safety domain based on the risk assessment result to realize the real-time dynamic adjustment of the initially set safety domain.
[0061] Based on the description of the above Step 1, during the actual application process, the methods for real-time risk assessment can include: using digital twin technology to track the interaction between the operator and the robot in real time, and evaluating possible collision risks or approaching dangers. By analyzing factors such as the robot's trajectory, the operator's actions, and the relative positions of objects, potential safety risks are predicted and evaluated to obtain a risk assessment result.
[0062] Based on the description in the above step 2, the dynamic update mechanism adopted when dynamically adjusting the safety domain can be described as follows: automatically adjust the safety domain according to the real-time obtained risk assessment results. Automatically calculate and update the boundary of the safety domain through an optimization algorithm to ensure that the operator is always in a safe working space during the task execution process.
[0063] In another exemplary embodiment of the present application, the actual implementation process of the method for constructing a dynamic safety domain for human-robot collaboration in a flexible assembly line provided by the present application may include:
[0064] 1. Use integrated sensors to perform real-time modeling of the operator's actions, robot trajectories, changes in the working environment, etc.
[0065] 2. Task type analysis and safety requirement definition.
[0066] 2.1. Mathematical modeling of task types.
[0067] The task type T is represented as a set of task parameters such as the accuracy, speed, risk, etc. of the task, and there is:
[0068]
[0069] The calculation formula of the safety domain requirement function depends on the task type parameters. Based on this, the safety domain requirement function is expressed as D safe (T):
[0070]
[0071] In the formula, α i is the weight coefficient of the task parameter, indicating the influence of the task type on the safety domain. is the i-th task parameter, i = 1, 2,..., n.
[0072] 2.2 Safety domain adjustment driven by task phases.
[0073] In different phases of the task type T (such as the preparation phase, execution phase, completion phase), adjust the size of the safety domain through the task phase parameter μ. The phase function f stage (μ) will affect the expansion or contraction of the safety domain. At this time, the safety domain requirement function is expressed as D safe (T, μ):
[0074] D safe (T, μ) = f stage (μ) × D safe (T).
[0075] For example, in the execution phase (μ = 1), the adjusted safety domain may increase. In the task preparation phase (μ = 0), the adjusted safety domain may decrease.
[0076] 3. Preliminary safety domain construction and application of empirical rules.
[0077] 3.1. Preliminary setting of the safety domain. Among them, the preliminary calculation formula of the safety domain is:
[0078]
[0079] In the formula, d min is the minimum safety distance set by empirical rules, and f(T) is the safety domain required for the task. is the preliminarily set safety domain, and α safe is the safety weight coefficient.
[0080] 3.2. Adjust the preliminarily set safety domain by applying empirical rules. Among them, the safety domain adjustment formula for applying empirical rules is expressed as:
[0081]
[0082] In the formula, is the adjusted safety domain. λ T is the risk coefficient of the task, which can adjust the size of the safety domain according to the task type.
[0083] 4. Dynamic safety domain adjustment based on optimization algorithm.
[0084] 4.1. Real-time risk assessment. The risk assessment model uses the state vector X to calculate the relative distance d ro between the robot and the operator, and based on this, predicts and evaluates potential safety risks to obtain the risk assessment result. Among them, the risk assessment result is expressed as R(d ro ):
[0085]
[0086] In the formula, the relative distance d ro between the robot and the operator is calculated through the position p r of the robot and the position p o of the operator, and is expressed as d ro =||p r -p o ||.
[0087] 4.2. Adjust the safety domain by the optimization algorithm.
[0088] Based on the risk assessment result, use the constrained optimization algorithm to dynamically adjust the safety domain boundary. The goal is to minimize the risk assessment result R(d ro ), while ensuring that the safety domain meets the minimum requirements. This process can be expressed as:
[0089]
[0090] In the formula, D safe is the current security domain, and s.t. represents the condition.
[0091] The process of dynamically adjusting the security domain boundary using numerical optimization methods such as the gradient descent method is expressed as:
[0092]
[0093] Where: is the security domain obtained in the nth iteration, η represents the step size, is the gradient of the risk assessment result R(d ro ) with respect to the security domain. is the security domain obtained in the (n + 1)th iteration.
[0094] In summary, the present application can perform real-time perception and analysis of multi-source data by combining digital twin technology, task-driven security requirement analysis, and optimization algorithms, and can dynamically adjust the security domain according to the task type, environmental changes, and operator behavior, thereby ensuring the collaboration between the operator and the robot is both safe and efficient.
[0095] In an exemplary embodiment, a computer device is provided. The computer device can be a server or a terminal, and its internal structure diagram can be as Figure 2 shown. The computer device includes a processor, a memory, an input / output interface (Input / Output, abbreviated as I / O), and a communication interface. Among them, the processor, the memory, and the input / output interface are connected through a system bus, and the communication interface is connected to the system bus through the input / output interface. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program, and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store data for constructing a dynamic security domain for human-robot collaboration in a flexible assembly line. The input / output interface of the computer device is used to exchange information between the processor and external devices. The communication interface of the computer device is used to communicate with external terminals through a network connection. When the computer program is executed by the processor, it implements a method for constructing a dynamic security domain for human-robot collaboration in a flexible assembly line.
[0096] Those skilled in the art can understand, Figure 2The structure shown is only a block diagram of some structures related to the solution of this application, and does not constitute a limitation on the computer device to which the solution of this application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine some components, or have different component arrangements. In an exemplary embodiment, a computer device is provided, including a memory and a processor. A computer program is stored in the memory, and when the processor executes the computer program, the steps in the above method embodiments are implemented.
[0097] In an exemplary embodiment, a computer-readable storage medium is provided, storing a computer program, and when the computer program is executed by a processor, the steps in the above method embodiments are implemented.
[0098] In an exemplary embodiment, a computer program product is provided, including a computer program, and when the computer program is executed by a processor, the steps in the above method embodiments are implemented.
[0099] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use, and processing of relevant data need to comply with relevant regulations.
[0100] Those of ordinary skill in the art can understand that all or part of the processes in the methods of the above embodiments can be completed by instructing relevant hardware through a computer program. The computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above methods. Among them, any reference to a memory, database, or other medium used in the embodiments provided in the present application can include at least one of non-volatile and volatile memories. Non-volatile memories can include read-only memory (ROM), magnetic tapes, floppy disks, flash memories, optical memories, high-density embedded non-volatile memories, resistive random access memories (ReRAM), magnetoresistive random access memories (MRAM), ferroelectric random access memories (FRAM), phase change memories (PCM), graphene memories, etc. Volatile memories can include random access memory (RAM) or external cache memories, etc. By way of illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM), etc.
[0101] The databases involved in the embodiments provided in the present application can include at least one of relational databases and non-relational databases. Non-relational databases can include distributed databases based on blockchain, etc., without limitation. The processors involved in the embodiments provided in the present application can be general-purpose processors, central processors, graphics processors, digital signal processors, programmable logics, data processing logics based on quantum computing, etc., without limitation.
[0102] The technical features of the above embodiments can be combined arbitrarily. For the sake of brevity of description, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, it should be considered as the scope described in this specification.
[0103] Specific examples are used in this article to elaborate on the principles and implementation manners of the present application. The descriptions of the above embodiments are only used to help understand the method and its core idea of the present application; at the same time, for those of ordinary skill in the art, according to the idea of the present application, there will be changes in the specific implementation manners and application scopes. In summary, the content of this specification should not be construed as a limitation to the present application.
Claims
1. A method for constructing a dynamic safety domain for human-machine collaboration in a flexible assembly line, characterized in that Including: Obtain human-robot collaboration status data in real time; Use digital twin technology to perform real-time construction of a virtual model based on the human-robot collaboration status data, and obtain the dynamic information of human-robot collaboration in the virtual model in real time; Based on the types of tasks on the flexible assembly line and the safety requirements in each task stage, preliminarily set the safety domain; Use an optimization algorithm to perform real-time dynamic adjustment of the preliminarily set safety domain based on the dynamic information of human-robot collaboration.
2. The method for constructing a dynamic safety zone for human-machine collaboration in a flexible assembly line according to claim 1, wherein The human-robot collaboration status data includes the status data of the robot, the status data of the operator, and the status data of the working environment where the robot and the operator are located; the status data of the robot includes the working status of the robot, the actions of the robot, and the working trajectory of the robot; the status data of the operator includes the working status of the operator and the actions of the operator; the status data of the working environment where the robot and the operator are located includes the running status of the equipment in the working environment and the spatial changes in the working environment.
3. The method for constructing a dynamic safety domain for human-machine collaboration in a flexible assembly line according to claim 1, wherein The dynamic information of human-robot collaboration includes the relative position between the operator and the robot, the pose information of the operator and the robot, and the action information of the operator and the robot.
4. The method for constructing a dynamic safety domain for human-machine collaboration in a flexible assembly line according to claim 1, wherein Based on the types of tasks on the flexible assembly line and the safety requirements in each task stage, preliminarily set the safety domain, including: Analyze the types of tasks on the flexible assembly line to obtain the potential risk factors during the task process; Determine the safety requirements for different task stages based on the risk factors; Based on the safety requirements for different task stages, combine with empirical rules to preliminarily set the scope and shape of the safety domain.
5. The method for constructing a dynamic safety domain for human-machine collaboration in a flexible assembly line according to claim 4, wherein Based on the safety requirements for different task stages, combine with empirical rules to preliminarily set the scope and shape of the safety domain, including: Based on the safety requirements for different task stages, combine with empirical rules to determine the minimum safety distance between the operator and the robot in each task stage; Use the minimum safety distance between the operator and the robot as the boundary of the preliminarily set safety domain to obtain the scope and shape of the preliminarily set safety domain.
6. The method for constructing a dynamic safety domain for human-machine collaboration in a flexible assembly line according to claim 1, characterized in that, Use an optimization algorithm to perform real-time dynamic adjustment of the preliminarily set safety domain based on the dynamic information of human-robot collaboration, including: Obtain a risk assessment result based on the dynamic information of human-robot collaboration; Use an optimization algorithm to determine and update the boundary of the preliminarily set safety domain based on the risk assessment result to achieve real-time dynamic adjustment of the preliminarily set safety domain.
7. The method for constructing a dynamic safety zone for human-machine collaboration in a flexible assembly line according to claim 1, wherein The optimization algorithm is a constraint optimization method or a gradient descent method.
8. A computer device, comprising: A memory, a processor, and a computer program stored on the memory and executable on the processor, wherein the processor executes the computer program to implement the method for constructing a dynamic safety domain for human-robot collaboration on a flexible assembly line according to any one of claims 1-7.
9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the method for constructing a dynamic safety domain for human-robot collaboration on a flexible assembly line according to any one of claims 1-7.
10. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by the processor, it implements the method for constructing a dynamic safety domain for human-robot collaboration on a flexible assembly line according to any one of claims 1-7.