CN115877736A - Multi-robot cooperative work simulation monitoring method based on digital twin - Google Patents
Multi-robot cooperative work simulation monitoring method based on digital twin Download PDFInfo
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Abstract
The invention relates to the technical field of industrial robots, in particular to a digital twin-based multi-robot collaborative operation simulation monitoring method, which comprises the following steps: s1, constructing a digital twin model of a multi-robot cooperative working environment based on a digital twin technology, wherein the multi-robot cooperative working environment comprises a robot and a control device; s2, constructing a multi-robot cooperative work simulation monitoring system, and packaging the digital twin model into the multi-robot cooperative work simulation monitoring system; s3, acquiring a multi-robot program file, and operating in the multi-robot collaborative operation simulation monitoring system to obtain an offline simulation result; and S4, connecting the multi-robot cooperative work environment with the multi-robot cooperative work simulation monitoring system through a communication protocol, and monitoring in the multi-robot cooperative work simulation monitoring system. The invention analyzes the interference collision in advance through the movement, thereby improving the real-time degree and the accuracy of the operation monitoring of the robot.
Description
Technical Field
The invention relates to the technical field of industrial robots, in particular to a digital twin-based multi-robot collaborative operation simulation monitoring method.
Background
With the continuous development of intelligent manufacturing, the robot replaces manual production to become the development trend of future manufacturing industry, and is also the guarantee for realizing industrial automation, digitization and intelligence in the future. Industrial robots are widely used in multi-joint manipulators in the industrial field or multi-degree-of-freedom machine devices, have certain automaticity, and can realize various industrial processing and manufacturing functions by means of self power energy and control capability.
In a highly automated production line, a certain process may be cooperatively completed by a plurality of industrial robots, or a plurality of industrial robots may be arranged on the same machine table. Due to the limitations of the production environment, the working spaces of multiple industrial robots may overlap. Under the circumstance, the serious economic loss caused by the interference collision among a plurality of industrial robots and the interference collision between a single industrial robot and the working environment is avoided, and the problem of multi-robot collaborative operation programming is solved.
On the one hand, industrial robots in the prior art mainly use external torque feedback or electronic skin for collision detection. The external torque feedback type usually estimates the external torque according to the feedback of a power loop and a kinetic equation of a robot system, and can also estimate the external torque by adding a torque sensor at a joint, but because the power loop feedback mode is adopted, the accurate modeling and identification of the friction force of the robot joint are difficult, and the precision of the detected collision torque is limited; the use of torque sensors or the addition of electronic skin sensing to the robot, while highly sensitive, also increases costs significantly. In recent years, there have been cases where robot collision detection is performed by combining a virtual robot with a bounding box, but since many bounding boxes are used, such as an AABB bounding box or an OBB bounding box, collision detection accuracy is not high, and a machine is likely to be stopped by mistake due to an excessively large bounding box.
On the other hand, most of robot off-line programming software in the prior art only supports simulation verification of a robot workstation after off-line programming, and does not support state monitoring and collision early warning in the actual operation process of the robot.
In summary, in the prior art, an offline verification and online monitoring method for a robot, which is low in cost, high in precision, fast, efficient and integrated, is lacking.
Disclosure of Invention
The invention provides a digital twin-based multi-robot collaborative operation simulation monitoring method, and aims to solve the technical problem that the prior art cannot efficiently realize off-line verification and on-line monitoring of a robot and control equipment.
Specifically, an embodiment of the present invention provides a digital twin-based multi-robot collaborative work simulation monitoring method, including the following steps:
s1, constructing a digital twin model of a multi-robot cooperative working environment based on a digital twin technology, wherein the multi-robot cooperative working environment comprises a robot and a control device;
s2, constructing a multi-robot cooperative work simulation monitoring system, and packaging the digital twin model into the multi-robot cooperative work simulation monitoring system;
s3, acquiring a multi-robot program file, and operating in the multi-robot collaborative operation simulation monitoring system to obtain an offline simulation result;
and S4, connecting the multi-robot cooperative work environment with the multi-robot cooperative work simulation monitoring system through a communication protocol, and monitoring in the multi-robot cooperative work simulation monitoring system.
Still further, step S1 comprises the sub-steps of:
s11, modeling the robot and the control equipment to obtain a robot model and a control equipment model;
s12, respectively constructing the robot model and the control equipment model into a robot physical model and a control equipment mechanism model based on the motion mechanisms of the robot and the control equipment;
s13, constructing data interaction interfaces for different motion states in the robot model and the control equipment model;
s14, constructing an enclosure comprising the robot physical model and the control equipment mechanism model, and constructing a collision group related to collision detection of any combination of the robot physical model and the control equipment mechanism model based on the enclosure so as to complete construction of the digital twin model, wherein the enclosure comprises a rough enclosure and a corresponding fine enclosure.
Furthermore, the multi-robot cooperative work simulation monitoring system comprises:
the display layer comprises a display interface facing to a user and is used for interaction between the user and the multi-robot collaborative operation simulation monitoring system;
the simulation layer is used for packaging the digital twin model;
the business layer is used for linking the data interaction interface and judging whether the robot mechanism model and the control equipment mechanism model collide or not based on the collision group;
and the data layer is used for realizing data communication with the multi-robot cooperative work environment.
Still further, step S3 comprises the following sub-steps:
s31, acquiring the multi-robot program file, and analyzing the multi-robot program file into a simulation execution file, wherein the multi-robot program file is used for simulating the motion states of the robot mechanism model and the control equipment mechanism model;
s32, executing the simulation execution file and starting off-line simulation;
s33, judging whether the rough enclosing bodies collide in the collision group, and if not, executing a step S35; if yes, go to step S34;
s34, judging whether the fine enclosing bodies corresponding to the rough enclosing bodies collide, and if not, executing a step S35; if yes, recording collision information, and executing step S35;
s35, judging whether a control instruction is received or not to end the simulation, and if not, returning to the step S33; if yes, outputting all the collision information as the off-line simulation result.
Further, step S4 comprises the following sub-steps:
s41, connecting the multi-robot cooperative work environment with the multi-robot cooperative work simulation monitoring system through a communication protocol;
s42, acquiring the real-time states of the robot and the control equipment in the multi-robot cooperative working environment;
s43, writing data into the robot mechanism model and the control equipment mechanism model according to the real-time state, and simulating in the multi-robot cooperative work simulation monitoring system by taking the real-time state as the simulation execution file;
s44, judging whether the simulation result in the real-time state contains the collision information or not, and if so, stopping the operation of the robot and the control equipment; if not, the normal operation is kept.
Further, before step S43, the method further includes the steps of:
and carrying out equal-scale amplification on the surrounding body according to a preset proportion to serve as a collision detection redundant belt.
Further, if the simulation result includes the collision information, the robot and the control device are adjusted in position based on the simulation result.
The method has the advantages that the digital twin-based multi-robot collaborative operation simulation monitoring method is provided, the digital twin body of the multi-robot collaborative operation environment is constructed based on the digital twin technology, and the consistency of the simulation environment and the real environment is ensured; secondly, by constructing a monitoring platform and performing off-line simulation verification on a plurality of industrial robots, whether the robots interfere with the working environment or not can be analyzed before operation, and interference collision during debugging and operation of the physical robots is avoided; and finally, the robot is monitored in an online operation mode by combining a digital twin technology, interference collision is analyzed in advance through movement, and the real-time degree and accuracy of operation monitoring of the robot are improved.
Drawings
FIG. 1 is a schematic flowchart illustrating steps of a digital twin-based multi-robot collaborative work simulation monitoring method according to an embodiment of the present invention;
FIG. 2 is a schematic diagram of a coarse enclosure provided by an embodiment of the present invention;
FIG. 3 is a schematic diagram of a fine enclosure provided by an embodiment of the present invention;
FIG. 4 is a schematic structural diagram of a multi-robot cooperative work simulation monitoring system according to an embodiment of the present invention;
fig. 5 is a sub-flowchart of step S3 in the digital twin-based multi-robot collaborative work simulation monitoring method according to the embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
Referring to fig. 1, fig. 1 is a schematic flow chart illustrating steps of a digital twin-based multi-robot cooperative work simulation monitoring method according to an embodiment of the present invention, where the method includes the following steps:
s1, constructing a digital twin model of a multi-robot cooperative working environment based on a digital twin technology, wherein the multi-robot cooperative working environment comprises a robot and control equipment.
The digital twin technology is a simulation process integrating multiple disciplines, multiple physical quantities, multiple scales and multiple probabilities by utilizing data such as a physical model, sensor updating and operation history, and can complete mapping in a virtual space so as to reflect the full life cycle process of corresponding entity equipment.
Still further, step S1 comprises the following sub-steps:
and S11, modeling the robot and the control equipment to obtain a robot model and a control equipment model.
Illustratively, according to a multi-robot collaborative operation object scene, three-dimensional modeling software such as SolidWorks, unigraphics NX, 3D Studio Max and the like is used for establishing a high-precision model of an operation environment, the model should keep a kinematic relationship corresponding to an object, wherein for modeling of a robot, each moving joint needs to be independently modeled, and finally, the moving joints are combined in an assembly form and the degree of freedom of the model is ensured according to correct kinematic constraint; for modeling of control equipment in a working environment, if the equipment needs to move in an off-line verification simulation, moving parts also need to be modeled separately and combined in an assembly form. The rest of the objects in the working environment which do not need to move can be directly expressed into an integral model.
And S12, respectively constructing the robot model and the control equipment model into a robot physical model and a control equipment mechanism model based on the motion mechanisms of the robot and the control equipment.
Specifically, for the encapsulation of the robot mechanism model, firstly, a robot model kinematic chain is constructed, that is, the child-parent relationship among the joints of the robot is obtained according to the mechanical structure and kinematic constraint of the physical robot. After the kinematic chain is constructed, correcting the kinematic chain according to the standard size parameter or DH parameter of the robot, so that the relative position between each joint completely meets the requirement, and the size error between the virtual robot and the real robot is reduced; and secondly, constructing a robot kinematics algorithm, namely constructing a positive kinematics and an inverse kinematics algorithm of the robot according to the DH parameters of the robot, wherein the positive kinematics is used for solving the terminal pose of the robot, and the inverse kinematics is used for solving the joint pose of the robot. The robot inverse kinematics algorithm includes, but is not limited to, algebraic, geometric, and numerical methods, but preferably, analytic methods are used to achieve faster solution speed. And finally, encapsulating the common robot motion methods such as linear motion, circular motion, point-to-point motion and the like so as to directly control the virtual robot by using the instruction.
For packaging a control equipment mechanism model in an operating environment, firstly, constructing an equipment model kinematic chain, namely obtaining the child-parent relation among all mechanisms of equipment according to the mechanical structure, the power form and the kinematic constraint of physical equipment, so as to construct the kinematic chain of the equipment model; and secondly, packaging the motion method according to the control mode of the physical equipment.
And S13, constructing data interaction interfaces for different motion states in the robot model and the control equipment model.
The data interaction interface in the embodiment of the invention is used for updating the joint angle of the virtual robot or sending a corresponding simulation event after receiving new joint angle data and signal data for the robot; for the control device and the rest of the working devices in the working environment, corresponding simulation events are triggered.
S14, constructing an enclosure comprising the robot physical model and the control equipment mechanism model, and constructing a collision group related to collision detection of any combination of the robot physical model and the control equipment mechanism model based on the enclosure so as to complete construction of the digital twin model, wherein the enclosure comprises a rough enclosure and a corresponding fine enclosure.
For example, referring to fig. 2 and fig. 3, fig. 2 is a schematic diagram of a coarse bounding volume provided by the embodiment of the present invention, fig. 3 is a schematic diagram of a fine bounding volume provided by the embodiment of the present invention, in step S14, a coarse bounding box of each element is first constructed, that is, an OBB bounding box is generated for each model, so as to be used for coarse collision detection, and reduce the amount of computation of collision detection; secondly, constructing a fine bounding volume of each element, namely generating a triangular patch bounding volume for each model for fine collision detection; and finally, performing collision group classification on all models, wherein in a working environment, all the surrounding bodies in a single robot model are classified into one collision group, all the surrounding bodies of all models of other equipment in the working environment are classified into another collision group, and during collision detection, only collision detection between the collision groups is performed, and collision detection of the models in the collision groups is not performed, so that the calculated amount of collision detection is reduced, and the calculation efficiency is improved.
S2, constructing a multi-robot cooperative work simulation monitoring system, and packaging the digital twin model into the multi-robot cooperative work simulation monitoring system.
Further, the multi-robot collaborative work simulation monitoring system comprises:
the display layer comprises a display interface facing to a user and is used for interaction between the user and the multi-robot collaborative operation simulation monitoring system;
the simulation layer is used for packaging the digital twin model;
the business layer is used for linking the data interaction interface and judging whether the robot mechanism model and the control equipment mechanism model collide based on the collision group;
and the data layer is used for realizing data communication with the multi-robot cooperative work environment.
For example, referring to fig. 4, fig. 4 is a schematic structural diagram of a multi-robot cooperative work simulation monitoring system according to an embodiment of the present invention, in actual implementation:
the display layer is mainly used for directly watching and operating interactive pictures and comprises a front-end UI interface and a three-dimensional rendering engine. The front-end UI interface is responsible for configuration and display of test items and test data and can be written by languages such as Java, html5 and JavaScript. The three-dimensional rendering Engine is responsible for rendering three-dimensional scene pictures of the operation environment and performing interactive operation with the scenes, and mature three-dimensional rendering engines such as a non Engine, a Jmonkey Engine, a Unity 3D Engine and a threes Engine can be used, so that platform development work is reduced.
The simulation layer is a virtual mechanism model of each element in the digital twin body of the working environment, and when the simulation layer is specifically implemented, the simulation layer comprises but is not limited to robots, equipment and the like.
The business layer is mainly a core business module of the test platform and comprises a model basic motion module, a physical engine module, a communication module, a front-end UI interface server module, a front-end event processing module, a test report module, a program semantic analysis module, a collision detection module and the like. The model motion module is responsible for interpolation of basic motions such as straight lines, curves and rotations of the model in the three-dimensional scene and is used for accurately controlling the motion of the model; the physical engine module is responsible for calculating the physical attributes of the model in the three-dimensional scene; the communication module is responsible for establishing communication with the physical operation environment, and comprises a communication protocol definition, a communication server, a data receiving and transmitting interface definition and the like, so that the test platform can receive real-time data of the physical operation environment; the front-end UI server module is responsible for starting a lightweight server and is used for loading a front-end UI; the front-end event processing module is responsible for responding to a front-end button triggering event and pushing and displaying on-line monitoring data; the test report module is responsible for recording and exporting offline simulation verification results and related data into pdf format documents; the program semantic analysis module is responsible for analyzing the robot code file and executing off-line simulation on the virtual robot according to the code file; and the collision detection module is responsible for detecting whether the collision groups in the scene interfere with each other.
The data layer is mainly responsible for data interaction among the modules and comprises a data transceiving module, a data processing module and a variable reading and writing module. The data transceiver module is responsible for receiving or sending related data to the physical working environment through the communication module; the data processing module is responsible for analyzing the received data or coding the related data and sending the coded data to the control system; and the variable reading and writing module is responsible for writing data into the relevant variables of the model or reading the relevant variables of the model.
And S3, acquiring a multi-robot program file, and operating in the multi-robot cooperative work simulation monitoring system to obtain an off-line simulation result.
Further, referring to fig. 5, fig. 5 is a sub-flowchart of step S3 in the digital twin-based multi-robot cooperative work simulation monitoring method according to the embodiment of the present invention, where step S3 includes the following sub-steps:
s31, acquiring the multi-robot program file, and analyzing the multi-robot program file into a simulation execution file, wherein the multi-robot program file is used for simulating the motion states of the robot mechanism model and the control equipment mechanism model;
s32, executing the simulation execution file and starting off-line simulation;
s33, judging whether the rough enclosing bodies collide in the collision group, and if not, executing a step S35; if yes, go to step S34;
s34, judging whether the fine enclosing bodies corresponding to the rough enclosing bodies collide, and if not, executing a step S35; if yes, recording collision information, and executing step S35;
s35, judging whether a control instruction is received or not to end the simulation, and if not, returning to the step S33; if yes, outputting all the collision information as the off-line simulation result.
And S4, connecting the multi-robot cooperative work environment with the multi-robot cooperative work simulation monitoring system through a communication protocol, and monitoring in the multi-robot cooperative work simulation monitoring system.
The final purpose of the step S4 is to monitor the robot on-line operation through a digital twin technology when the entity robot is debugged and operated, and to analyze whether interference collision occurs or not in advance through the motion of a robot physical model and stop the operation of the entity robot in time.
Further, step S4 comprises the following sub-steps:
s41, connecting the multi-robot cooperative work environment with the multi-robot cooperative work simulation monitoring system through a communication protocol;
s42, acquiring the real-time states of the robot and the control equipment in the multi-robot cooperative working environment;
s43, writing data into the robot mechanism model and the control equipment mechanism model according to the real-time state, and simulating in the multi-robot cooperative operation simulation monitoring system by taking the real-time state as the simulation execution file;
s44, judging whether the simulation result in the real-time state contains the collision information or not, and if so, stopping the operation of the robot and the control equipment; if not, the normal operation is kept.
Specifically, among different collision groups, a rough surrounding body of the model is used for collision detection; if interference occurs in the rough collision detection, performing fine collision detection on the model corresponding to the rough surrounding body with the interference, namely performing collision detection by using the fine surrounding body of the model, and if interference still occurs, indicating that collision occurs between the two models, namely the physical equipment has collision risk, sending a shutdown instruction to the physical operation environment, waiting for manual processing, and ending the collision detection until the online monitoring is ended.
Further, before step S43, the method further includes the steps of:
and carrying out equal-scale amplification on the surrounding body according to a preset proportion to serve as a collision detection redundant belt. Specifically, during simulation, a rough enclosure and a fine enclosure of the model are adjusted, the rough enclosure and the fine enclosure are amplified in equal proportion by taking a centroid as a center, and a space formed by the enclosure and the surface of the model is a collision detection redundant zone, so that in an actual environment, the amplification factor needs to be comprehensively determined according to the highest operation speed of the robot, the data acquisition communication delay, the safety factor and the like, and the amplification factor is larger when the operation speed is higher, the data acquisition communication delay is longer, and the safety factor is larger. The method has the advantages that the digital twin-based multi-robot collaborative operation simulation monitoring method is provided, the digital twin body of the multi-robot collaborative operation environment is constructed based on the digital twin technology, and the consistency of the simulation environment and the real environment is ensured; secondly, by constructing a monitoring platform and performing off-line simulation verification on a plurality of industrial robots, whether the robots interfere with the working environment or not can be analyzed before operation, and interference collision during debugging and operation of the physical robots is avoided; and finally, on-line operation monitoring is carried out on the robot by combining a digital twin technology, and interference collision is analyzed in advance through movement, so that the real-time degree and the accuracy of operation monitoring of the robot are improved.
Further, if the simulation result includes the collision information, the robot and the control device are adjusted in position based on the simulation result.
It will be understood by those skilled in the art that all or part of the processes of the methods of the embodiments described above can be implemented by a computer program, which can be stored in a computer-readable storage medium, and when executed, can include the processes of the embodiments of the methods described above. The storage medium may be a magnetic disk, an optical disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), or the like.
It should be noted that, in this document, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one of 8230, and" comprising 8230does not exclude the presence of additional like elements in a process, method, article, or apparatus comprising the element.
Through the above description of the embodiments, those skilled in the art will clearly understand that the method of the above embodiments can be implemented by software plus a necessary general hardware platform, and certainly can also be implemented by hardware, but in many cases, the former is a better implementation manner. Based on such understanding, the technical solutions of the present invention may be embodied in the form of a software product, which is stored in a storage medium (such as ROM/RAM, magnetic disk, optical disk) and includes instructions for enabling a terminal (such as a mobile phone, a computer, a server, an air conditioner, or a network device) to execute the method according to the embodiments of the present invention.
While the present invention has been described with reference to the preferred embodiments, it is to be understood that the invention is not limited to the disclosed embodiments, which are illustrative, but not restrictive, and that various changes may be made therein by those skilled in the art without departing from the spirit and scope of the invention as defined by the appended claims.
Claims (7)
1. A digital twin-based multi-robot collaborative operation simulation monitoring method is characterized by comprising the following steps:
s1, constructing a digital twin model of a multi-robot cooperative work environment based on a digital twin technology, wherein the multi-robot cooperative work environment comprises a robot and control equipment;
s2, constructing a multi-robot cooperative work simulation monitoring system, and packaging the digital twin model into the multi-robot cooperative work simulation monitoring system;
s3, acquiring a multi-robot program file, and operating in the multi-robot collaborative operation simulation monitoring system to obtain an offline simulation result;
and S4, connecting the multi-robot cooperative work environment with the multi-robot cooperative work simulation monitoring system through a communication protocol, and monitoring in the multi-robot cooperative work simulation monitoring system.
2. The digital twin-based multi-robot collaborative work simulation monitoring method according to claim 1, wherein the step S1 includes the substeps of:
s11, modeling the robot and the control equipment to obtain a robot model and a control equipment model;
s12, respectively constructing the robot model and the control equipment model into a robot physical model and a control equipment mechanism model based on the motion mechanisms of the robot and the control equipment;
s13, constructing data interaction interfaces for different motion states in the robot model and the control equipment model;
s14, constructing an enclosure comprising the robot physical model and the control equipment mechanism model, and constructing a collision group related to collision detection of any combination of the robot physical model and the control equipment mechanism model based on the enclosure so as to complete construction of the digital twin model, wherein the enclosure comprises a rough enclosure and a corresponding fine enclosure.
3. The digital twin-based multi-robot cooperative work simulation monitoring method as set forth in claim 2, wherein the multi-robot cooperative work simulation monitoring system comprises:
the display layer comprises a display interface facing to a user and is used for interaction between the user and the multi-robot collaborative operation simulation monitoring system;
the simulation layer is used for packaging the digital twin model;
the business layer is used for linking the data interaction interface and judging whether the robot mechanism model and the control equipment mechanism model collide based on the collision group;
and the data layer is used for realizing data communication with the multi-robot cooperative work environment.
4. The digital twin-based multi-robot cooperative work simulation monitoring method as claimed in claim 2, wherein the step S3 comprises the substeps of:
s31, acquiring the multi-robot program file, and analyzing the multi-robot program file into a simulation execution file, wherein the multi-robot program file is used for simulating the motion states of the robot mechanism model and the control equipment mechanism model;
s32, executing the simulation execution file and starting off-line simulation;
s33, judging whether the rough enclosing bodies collide in the collision group, and if not, executing a step S35; if yes, go to step S34;
s34, judging whether the fine surrounding bodies corresponding to the rough surrounding bodies collide with each other, and if not, executing a step S35; if yes, recording collision information, and executing step S35;
s35, judging whether a control instruction is received or not to end the simulation, and if not, returning to the step S33; and if so, outputting all the collision information as the off-line simulation result.
5. The digital twin-based multi-robot cooperative work simulation monitoring method as claimed in claim 4, wherein the step S4 comprises the following sub-steps:
s41, connecting the multi-robot cooperative work environment with the multi-robot cooperative work simulation monitoring system through a communication protocol;
s42, acquiring the real-time states of the robot and the control equipment in the multi-robot cooperative working environment;
s43, writing data into the robot mechanism model and the control equipment mechanism model according to the real-time state, and simulating in the multi-robot cooperative operation simulation monitoring system by taking the real-time state as the simulation execution file;
s44, judging whether the simulation result in the real-time state contains the collision information or not, and if so, stopping the operation of the robot and the control equipment; if not, the normal operation is kept.
6. The simulation monitoring method for multi-robot collaborative work based on digital twin as claimed in claim 5, wherein before step S43, the method further comprises the steps of:
and amplifying the surrounding body in equal proportion according to a preset proportion to serve as a collision detection redundant belt.
7. The simulation monitoring method for the multi-robot collaborative work based on the digital twin as set forth in claim 5, further comprising the following substeps after the step S4:
and if the simulation result contains the collision information, adjusting the positions of the robot and the control equipment based on the simulation result.
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| CN117518880A (en) * | 2024-01-05 | 2024-02-06 | 北京圜晖科技有限公司 | Collision detection method and device in digital twin mode |
Citations (12)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108724190A (en) * | 2018-06-27 | 2018-11-02 | 西安交通大学 | A kind of industrial robot number twinned system emulation mode and device |
| CN109571476A (en) * | 2018-12-14 | 2019-04-05 | 南京理工大学 | The twin real time job control of industrial robot number, monitoring and precision compensation method |
| CN110008605A (en) * | 2019-04-10 | 2019-07-12 | 广东工业大学 | Monitoring method and application based on the twin model of number its hit a machine equipment |
| CN112306464A (en) * | 2020-10-14 | 2021-02-02 | 中国科学院沈阳自动化研究所 | Method and system for realizing information physical fusion in industrial scene by using digital twin |
| CN112828886A (en) * | 2020-12-31 | 2021-05-25 | 天津职业技术师范大学(中国职业培训指导教师进修中心) | Industrial robot collision prediction control method based on digital twinning |
| CN113246122A (en) * | 2021-04-26 | 2021-08-13 | 广东工贸职业技术学院 | Digital twin practical training method and system of industrial robot |
| CN113759753A (en) * | 2021-08-31 | 2021-12-07 | 广东利元亨智能装备股份有限公司 | Simulation debugging system based on digital twin platform |
| WO2022017827A1 (en) * | 2020-07-20 | 2022-01-27 | Siemens Aktiengesellschaft | Method for simulating a robot arm |
| CN114131597A (en) * | 2021-11-24 | 2022-03-04 | 山东哈博特机器人有限公司 | Industrial robot simulation linkage method and system based on digital twinning technology |
| CN115179326A (en) * | 2022-08-24 | 2022-10-14 | 广东工业大学 | Continuous collision detection method for articulated robot |
| CN115556112A (en) * | 2022-10-28 | 2023-01-03 | 北京理工大学 | Robot teleoperation method and system based on digital twins |
| CN115567129A (en) * | 2022-09-21 | 2023-01-03 | 北京交通大学 | Digital twin channel modeling method |
-
2023
- 2023-02-03 CN CN202310076655.6A patent/CN115877736B/en active Active
Patent Citations (12)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108724190A (en) * | 2018-06-27 | 2018-11-02 | 西安交通大学 | A kind of industrial robot number twinned system emulation mode and device |
| CN109571476A (en) * | 2018-12-14 | 2019-04-05 | 南京理工大学 | The twin real time job control of industrial robot number, monitoring and precision compensation method |
| CN110008605A (en) * | 2019-04-10 | 2019-07-12 | 广东工业大学 | Monitoring method and application based on the twin model of number its hit a machine equipment |
| WO2022017827A1 (en) * | 2020-07-20 | 2022-01-27 | Siemens Aktiengesellschaft | Method for simulating a robot arm |
| CN112306464A (en) * | 2020-10-14 | 2021-02-02 | 中国科学院沈阳自动化研究所 | Method and system for realizing information physical fusion in industrial scene by using digital twin |
| CN112828886A (en) * | 2020-12-31 | 2021-05-25 | 天津职业技术师范大学(中国职业培训指导教师进修中心) | Industrial robot collision prediction control method based on digital twinning |
| CN113246122A (en) * | 2021-04-26 | 2021-08-13 | 广东工贸职业技术学院 | Digital twin practical training method and system of industrial robot |
| CN113759753A (en) * | 2021-08-31 | 2021-12-07 | 广东利元亨智能装备股份有限公司 | Simulation debugging system based on digital twin platform |
| CN114131597A (en) * | 2021-11-24 | 2022-03-04 | 山东哈博特机器人有限公司 | Industrial robot simulation linkage method and system based on digital twinning technology |
| CN115179326A (en) * | 2022-08-24 | 2022-10-14 | 广东工业大学 | Continuous collision detection method for articulated robot |
| CN115567129A (en) * | 2022-09-21 | 2023-01-03 | 北京交通大学 | Digital twin channel modeling method |
| CN115556112A (en) * | 2022-10-28 | 2023-01-03 | 北京理工大学 | Robot teleoperation method and system based on digital twins |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116652968A (en) * | 2023-07-24 | 2023-08-29 | 贵州翰凯斯智能技术有限公司 | Multi-mechanical arm collaborative online simulation method and device, electronic equipment and storage medium |
| CN117518880A (en) * | 2024-01-05 | 2024-02-06 | 北京圜晖科技有限公司 | Collision detection method and device in digital twin mode |
| CN117518880B (en) * | 2024-01-05 | 2024-03-26 | 北京圜晖科技有限公司 | Collision detection method and device in digital twin mode |
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