A surgical robot master-slave hand control system based on 5G network and edge computing

Abstract

The present invention relates to the field of surgical robot technology, and more specifically, to a surgical robot master-slave hand control system based on 5G network and edge computing. It includes an infrastructure unit, an edge computing unit, an intelligent control unit, and an extended application unit; the infrastructure unit is used to provide basic equipment and technology to support the operation of the system; the edge computing unit is used to provide intelligent services nearby on the edge side of the robot operation system; the intelligent control unit is used to perform unified centralized control and autonomous management of the robot master and slave hands; the extended application unit is used to add a variety of extended services to improve the functionality of the system. The design of the present invention can realize the rapid deployment of master-slave hand robots, uniformly control the operation process of the master and slave hands, and improve the quality and stability of the working network, thereby improving computing efficiency and reducing costs, and can upload video images to the cloud in a timely manner, ensuring the convenience, timeliness and security of data storage, and improving surgical efficiency.

Description

Technical Field

[0001] The present invention relates to the technical field of surgical robots, and in particular to a master-slave hand control system of a surgical robot based on 5G network and edge computing. Background Art

[0002] The surgical robot system is a complex that integrates many modern high-tech means. It has a wide range of uses and has a large number of applications in clinical surgery. Surgeons can operate the machine away from the operating table to perform surgery, which is completely different from the traditional concept of surgery. It is a well-deserved revolutionary surgical tool in the field of minimally invasive surgery. With the continuous development of medical technology and network technology, the application scenarios of various minimally invasive surgical robots are becoming more and more extensive, especially remote surgery. Various robotic surgical systems are composed of a console and an operating arm. The console consists of a computer system, a surgical operation monitor, a robot control monitor, an operating handle, and input and output devices. The doctor controls the operating lever with both hands, and the hand movements are transmitted to the tip of the robotic arm to complete the surgical operation. However, the current conventional surgical robot console and operating arm are connected by wire, that is, a one-to-one master-servant operation mode, which cannot realize remote control of the operating arm; it is impossible to realize one console controlling multiple robotic arms. In addition, the computer system of the console has limited data processing capabilities, resulting in significant delays in major indicators such as mechanical response, endoscopic imaging and image processing, and video encoding and decoding. Based on the above background, technologies that break through traditional wired network connections and improve computer processing capabilities will greatly improve the performance of surgical robots and expand their application scenarios. Summary of the invention

[0003] The purpose of the present invention is to provide a surgical robot master-slave hand control system based on 5G network and edge computing to solve the problems raised in the above background technology.

[0004] In order to solve the above technical problems, one of the objectives of the present invention is to provide a surgical robot master-slave hand control system based on 5G network and edge computing, including:

[0005] An infrastructure unit, an edge computing unit, an intelligent control unit and an extended application unit; the signal output end of the infrastructure unit is connected to the signal input end of the edge computing unit, the signal output end of the edge computing unit is connected to the signal input end of the intelligent control unit, and the signal output end of the intelligent control unit is connected to the signal input end of the extended application unit; the infrastructure unit is used to provide basic equipment and technology to support the operation of the system; the edge computing unit is used to provide intelligent services nearby on the edge side of the robot operation system through edge node control technology; the intelligent control unit is used to perform unified centralized control and distributed autonomous management of the robot's operating master and slave hands; the extended application unit is used to add a variety of extended services on the basis of the normal operation of the system to improve the functionality of the system;

[0006] The infrastructure unit includes an application terminal module, a cloud database module, a network communication module and a functional service module;

[0007] The edge computing unit includes an edge deployment module, a data processing module, an edge node module and a security protection module;

[0008] The intelligent control unit includes a centralized control module, a quick control module, a master-hand independent control module and a slave-hand cloud control module;

[0009] The extended application unit includes an intermittent connection module, a predictive maintenance module, an energy efficiency management module, an intelligent manufacturing module and a flexible replacement module.

[0010] As a further improvement of the present technical solution, the application terminal module, the cloud database module and the functional service module are connected in sequence via Ethernet communication and run in parallel; the application terminal module is used to provide basic application equipment and terminal platforms for building the system and to manage and allocate each device; the cloud database module is used to establish a database in the cloud to store image data and other work data uploaded by the robot's main hand and slave hands; the network communication module is used to provide signal connections and data transmission channels between various levels of the system through a variety of network communication technologies; the functional service module is used to support the operation of the system by setting up a variety of service items.

[0011] Among them, application terminals include but are not limited to robots, robot master-hand interfaces, robot slave-hand interfaces, processors, displays, edge computing server mec devices, routing gateways, network devices, network switches, cameras, etc.

[0012] Among them, network communication technologies include dedicated line networks, local area networks, wired networks, wireless WiFi, Bluetooth, 5G networks, etc., among which 5G is the main one and dedicated line networks are the auxiliary ones.

[0013] As a further improvement of the present technical solution, the functional service module includes a network monitoring module, a private network switching module, an image recording module and a data cloud module; the signal output end of the network monitoring module is connected to the signal input end of the private network switching module, the network monitoring module and the image recording module run in parallel, and the signal output end of the image recording module is connected to the signal input end of the data cloud module; the network monitoring module is used to monitor the network link status in real time during the system operation to determine whether each link is connected and unobstructed; the private network switching module is used to switch to the dedicated network to work and provide a ping-pong protection mechanism when a problem occurs in the current working network such as the 5G network; the image recording module is used to record the working environment such as surgical procedures, surgical field conditions, etc. through a camera device set on the master / slave end of the robot; the data cloud module is used to timely transmit the recorded image video to the cloud database for storage through wireless transmission technology.

[0014] As a further improvement of the technical solution, in the private network switching module, an algorithm for job priority is used in different network switching processes, and its calculation formula is:

[0015]

[0016] in, Indicates the job Priority during the switching process, The priority assigned to the job when it was submitted. is the time the job waits in the queue, is a constant factor. As the waiting time increases, the job priority increases dynamically until it reaches the threshold, which is the highest priority.

[0017] As a further improvement of the present technical solution, the edge deployment module, the data processing module, the edge node module and the security protection module are connected in sequence through Ethernet communication and operate independently; the edge deployment module is used to deploy edge computing workloads at different network levels to achieve targeted support for various 5G services; the data processing module is used to process and self-manage data information within the system through edge computing; the edge node module is used to utilize edge nodes closer to users as a beneficial supplement to cloud computing to reduce network waiting time; the security protection module is used to establish end-to-end security protection measures across cloud computing and edge computing between each edge node.

[0018] Among them, the deployment requirements of edge computing workloads are: for low-latency scenarios, edge computing needs to be deployed in an access cloud close to the base station; for high-traffic hotspot scenarios, edge computing can be deployed in an edge cloud to improve the reuse rate; for wide-area large-connection scenarios, edge computing can be deployed in a higher aggregation cloud to meet business needs in a large coverage area.

[0019] As a further improvement of the present technical solution, the data processing module includes a data filtering module, a data computing module, a data storage module and a data transmission module; the signal output end of the data filtering module is connected to the signal input end of the data computing module, the signal output end of the data computing module is connected to the signal input end of the data storage module, and the signal output end of the data storage module is connected to the signal input end of the data transmission module; the data filtering module is used to filter or analyze data at the edge node to reduce the pressure of cloud computing; the data computing module is used to realize data computing and analysis at the edge of the network close to the source of objects or data to reduce data transmission; the data storage module is used to store the data after edge side computing and analysis on-site; the data transmission module is used to transmit the data stored on the edge side for use.

[0020] As a further improvement of the technical solution, in the data filtering module, the calculation energy consumption expression of the local calculation process is:

[0021]

[0022] In the formula, Indicates the local calculation process The computational energy consumption of each task or workload; For the The energy consumption ratio coefficient of each CPU cycle is used to calculate the linear correlation between energy consumption and workload; Indicates Tasks in time The weight value of the workload intensity at time ; Represents the workload at time The energy consumption at that time.

[0023] As a further improvement of the present technical solution, the signal output end of the centralized control module is connected to the signal input end of the quick control module, and the signal output end of the quick control module is simultaneously connected to the signal input ends of the master-hand independent control module and the slave-hand cloud control module; the centralized control module is used to centrally manage and uniformly allocate various levels and functions of the system through a main processor arranged in the computer room; the quick control module is used to quickly deploy and allocate work content for the robot master hand and several slave hands through the centralized control room; the master-hand independent control module is used to independently control the operation process of the robot master hand through the processor via the controller; the slave-hand cloud control module is used to independently control the operation process of each robot slave hand through the processor via the controller deployed at the edge node based on the cloud bearer network.

[0024] Among them, one master hand can control multiple slave hands, which is convenient for quickly switching to another slave hand to perform the operation at the end of the operation, thereby improving the efficiency of the operation.

[0025] As a further improvement of the present technical solution, the intermittent connection module, the predictive maintenance module, the energy efficiency management module, the intelligent manufacturing module and the flexible replacement module operate in parallel; the intermittent connection module is used to reduce the data transmission cost through low intermittent connection between remote locations under the premise of complying with network security regulations, and obtain time data for real-time analysis through instant analysis to reduce transmission delay; the predictive maintenance module is used to predict the operating status of edge devices by monitoring the operating status of each edge node for timely maintenance, thereby achieving the effect of reducing costs, ensuring safety and expanding products to services; the energy efficiency management module is used to manage energy efficiency through system operation to reduce energy consumption, reduce maintenance costs and improve reliability; the intelligent manufacturing module is used to increase and customize the functionality of the system and robot according to user needs; the flexible replacement module is used to flexibly adjust the robot's operation plan according to the characteristics of the edge node and quickly deploy new processes and models.

[0026] The second object of the present invention is to provide an operation method of a surgical robot master-slave hand control system based on 5G network and edge computing, comprising the following steps:

[0027] S1. Connect the robot master / slave to the system through a suitable network interface, and deploy the centralized operation to the edge computing server mec device through edge computing;

[0028] S2. Access 5G network, dedicated network and other network technologies simultaneously through industrial gateway devices. Set 5G network as the main network and dedicated network as the auxiliary network through parameter settings, and set appropriate switching protection mechanism;

[0029] S3. The operator in the machine room uses centralized processing equipment to quickly deploy the robot master / slave, and controls the independent operation of the master / slave respectively;

[0030] S4. During the operation of the robot, the working environment, surgical video, and surgical field image information are recorded in real time;

[0031] S5. The robot uses wireless transmission technology to transmit the recorded video to the cloud database via the existing network in a timely manner and automatically classifies and stores it;

[0032] S6. During the operation of the working network, the 5G network is mainly used. When a problem occurs in the 5G network or the network delay exceeds the preset threshold, the network switch set on the gateway device will automatically switch the working network to the dedicated network. During the network switching process, the switching protection mechanism will be used to avoid frequent switching, improve the quality of the working network, and ensure smooth system operation;

[0033] S7. A master hand is connected to multiple slave hands at the same time. When the operation on one of the slave hands is finished, the master hand can quickly switch to connect with another slave hand to control the operation.

[0034] The third object of the present invention is to provide an operating device of a surgical robot master-slave hand control system based on 5G network and edge computing, including a processor, a memory, and a computer program stored in the memory and running on the processor, and the processor is used to implement any of the above-mentioned surgical robot master-slave hand control systems based on 5G network and edge computing when executing the computer program.

[0035] The fourth object of the present invention is that the computer-readable storage medium stores a computer program, and when the computer program is executed by the processor, it implements any of the above-mentioned surgical robot master-slave hand control systems based on 5G network and edge computing.

[0036] Compared with the prior art, the beneficial effects of the present invention are as follows: in the surgical robot master-slave hand control system based on 5G network and edge computing, by setting the robot master hand and slave hand, the robot master-slave hand control system is concentrated in the computer room equipment, and the operation is deployed to a convenient computing server through edge computing, which can realize the rapid deployment of master-slave hand robots, uniformly control the operation process of the master and slave hands, improve the mobility of the slave hand, and set a switchable working network with 5G network as the main and dedicated line network as the auxiliary to improve the quality and stability of the working network, thereby improving computing efficiency and reducing costs, and can upload video images to the cloud in time to ensure the convenience, timeliness and security of storage of surgical video image data, improve surgical efficiency, and reduce the work pressure of doctors. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] Figure 1 It is a structural block diagram of the system architecture of the present invention;

[0038] Figure 2 It is the overall system device structure diagram of the present invention;

[0039] Figure 3 This is one of the local system device structure diagrams of the present invention;

[0040] Figure 4 This is the second structural diagram of the local system device of the present invention;

[0041] Figure 5 This is the third structural diagram of the local system device of the present invention;

[0042] Figure 6 This is the fourth structural diagram of the local system device of the present invention;

[0043] Figure 7 This is the fifth structural diagram of the local system device of the present invention;

[0044] Figure 8 This is the sixth structural diagram of the local system device of the present invention;

[0045] Fig. 9 FIG. 5 is a block diagram of an exemplary computer program product of the present invention.

[0046] The meaning of each number in the figure is:

[0047] 100, infrastructure unit; 101, application terminal module; 102, cloud database module; 103, network communication module; 104, functional service module; 1041, network monitoring module; 1042, private network switching module; 1043, video recording module; 1044, data cloud module;

[0048] 200, edge computing unit; 201, edge deployment module; 202, data processing module; 2021, data filtering module; 2022, data computing module; 2023, data storage module; 2024, data transmission module; 203, edge node module; 204, security protection module;

[0049] 300, intelligent control unit; 301, centralized control module; 302, quick control module; 303, master control module; 304, slave cloud control module;

[0050] 400. Extended application unit; 401. Intermittent connection module; 402. Predictive maintenance module; 403. Energy efficiency management module; 404. Intelligent manufacturing module; 405. Flexible replacement module. DETAILED DESCRIPTION

[0051] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0052] Example 1

[0053] like Figure 1-Figure 9 As shown, this embodiment provides a surgical robot master-slave hand control system based on 5G network and edge computing, including:

[0054] Infrastructure unit 100, edge computing unit 200, intelligent control unit 300 and extended application unit 400; the signal output end of the infrastructure unit 100 is connected to the signal input end of the edge computing unit 200, the signal output end of the edge computing unit 200 is connected to the signal input end of the intelligent control unit 300, and the signal output end of the intelligent control unit 300 is connected to the signal input end of the extended application unit 400; the infrastructure unit 100 is used to provide basic equipment and technology to support the operation of the system; the edge computing unit 200 is used to provide intelligent services nearby on the edge side of the robot operation system through edge node control technology; the intelligent control unit 300 is used to perform unified centralized control and distributed autonomous management of the robot's operating master and slave hands; the extended application unit 400 is used to add a variety of extended services on the basis of the normal operation of the system to improve the functionality of the system;

[0055] The infrastructure unit 100 includes an application terminal module 101, a cloud database module 102, a network communication module 103 and a functional service module 104;

[0056] The edge computing unit 200 includes an edge deployment module 201, a data processing module 202, an edge node module 203 and a security protection module 204;

[0057] The intelligent control unit 300 includes a centralized control module 301, a quick control module 302, a master-hand independent control module 303 and a slave-hand cloud control module 304;

[0058] The extended application unit 400 includes an intermittent connection module 401 , a predictive maintenance module 402 , an energy efficiency management module 403 , an intelligent manufacturing module 404 and a flexible replacement module 405 .

[0059] In this embodiment, the application terminal module 101, the cloud database module 102 and the functional service module 104 are connected in sequence via Ethernet communication and run in parallel; the application terminal module 101 is used to provide basic application equipment and terminal platforms for building the system and to manage and allocate each device; the cloud database module 102 is used to establish a database in the cloud to store image data and other work data uploaded by the robot master hand and slave hands; the network communication module 103 is used to provide signal connections and data transmission channels between various levels of the system through a variety of network communication technologies; the functional service module 104 is used to support the operation of the system by setting up a variety of service items.

[0060] Among them, application terminals include but are not limited to robots, robot master-hand interfaces, robot slave-hand interfaces, processors, displays, edge computing server mec devices, routing gateways, network devices, network switches, cameras, etc.

[0061] Among them, network communication technologies include dedicated line networks, local area networks, wired networks, wireless WiFi, Bluetooth, 5G networks, etc., among which 5G is the main one and dedicated line networks are the auxiliary ones.

[0062] Furthermore, the functional service module 104 includes a network monitoring module 1041, a private network switching module 1042, an image recording module 1043 and a data cloud module 1044; the signal output end of the network monitoring module 1041 is connected to the signal input end of the private network switching module 1042, the network monitoring module 1041 and the image recording module 1043 operate in parallel, and the signal output end of the image recording module 1043 is connected to the signal input end of the data cloud module 1044; the network monitoring module 1041 is used to monitor the network link status in real time during the operation of the system to determine whether each link is connected and unobstructed; the private network switching module 1042 is used to switch to the dedicated network to work and provide a ping-pong protection mechanism when a problem occurs in the current working network such as the 5G network; the image recording module 1043 is used to record the working environment such as the surgical process, the surgical field condition, etc. through a camera device set at the master / slave end of the robot; the data cloud module 1044 is used to timely transmit the recorded image video to the cloud database for storage through wireless transmission technology.

[0063] Specifically, in the private network switching module 1042, the algorithm of job priority is adopted in the process of switching different networks, and its calculation formula is:

[0064]

[0065] in, Indicates the job Priority during the switching process, The priority assigned to the job when it was submitted. is the time the job waits in the queue, is a constant factor. As the waiting time increases, the job priority increases dynamically until it reaches the threshold, which is the highest priority.

[0066] In this embodiment, the edge deployment module 201, the data processing module 202, the edge node module 203 and the security protection module 204 are connected in sequence via Ethernet communication and operate independently; the edge deployment module 201 is used to deploy edge computing workloads at different network levels to achieve targeted support for various 5G services; the data processing module 202 is used to process and self-manage data information within the system through edge computing; the edge node module 203 is used to utilize edge nodes closer to users as a beneficial supplement to cloud computing to reduce network waiting time; the security protection module 204 is used to establish end-to-end security protection measures across cloud computing and edge computing between each edge node.

[0067] Among them, the deployment requirements of edge computing workloads are: for low-latency scenarios, edge computing needs to be deployed in an access cloud close to the base station; for high-traffic hotspot scenarios, edge computing can be deployed in an edge cloud to improve the reuse rate; for wide-area large-connection scenarios, edge computing can be deployed in a higher aggregation cloud to meet business needs in a large coverage area.

[0068] Furthermore, the data processing module 202 includes a data filtering module 2021, a data computing module 2022, a data storage module 2023 and a data transmission module 2024; the signal output end of the data filtering module 2021 is connected to the signal input end of the data computing module 2022, the signal output end of the data computing module 2022 is connected to the signal input end of the data storage module 2023, and the signal output end of the data storage module 2023 is connected to the signal input end of the data transmission module 2024; the data filtering module 2021 is used to filter or analyze data at the edge node to reduce the pressure of cloud computing; the data computing module 2022 is used to realize data computing and analysis at the edge of the network close to the object or data source to reduce data transmission; the data storage module 2023 is used to store the data after edge side computing and analysis on the spot; the data transmission module 2024 is used to transmit the data stored on the edge side for use.

[0069] Specifically, in the data filtering module 2021, the calculation energy consumption expression of the local calculation process is:

[0070]

[0071] In the formula, Indicates the local calculation process The computational energy consumption of each task or workload; For the The energy consumption ratio coefficient of each CPU cycle is used to calculate the linear correlation between energy consumption and workload; Indicates Tasks in time The weight value of the workload intensity at time ; Represents the workload at time The energy consumption at that time.

[0072] In this embodiment, the signal output end of the centralized control module 301 is connected to the signal input end of the quick control module 302, and the signal output end of the quick control module 302 is simultaneously connected to the signal input ends of the master-hand independent control module 303 and the slave-hand cloud control module 304; the centralized control module 301 is used to centrally manage and uniformly allocate all levels and functions of the system through a main processor arranged in the computer room; the quick control module 302 is used to quickly deploy and allocate work content to the working areas of the robot master hand and several slave hands through the centralized control room; the master-hand independent control module 303 is used to independently control the operation process of the robot master hand through the processor via the controller; the slave-hand cloud control module 304 is used to independently control the operation process of each robot slave hand through the processor via the controller deployed at the edge node based on the cloud bearer network.

[0073] Among them, one master hand can control multiple slave hands, which is convenient for quickly switching to another slave hand to perform the operation at the end of the operation, thereby improving the efficiency of the operation.

[0074] In this embodiment, the intermittent connection module 401, the predictive maintenance module 402, the energy efficiency management module 403, the intelligent manufacturing module 404 and the flexible replacement module 405 operate in parallel; the intermittent connection module 401 is used to reduce the data transmission cost through low intermittent connection between remote locations under the premise of complying with network security regulations, and obtain time data for real-time analysis through instant analysis to reduce transmission delay; the predictive maintenance module 402 is used to predict the operating status of edge devices by monitoring the operating status of each edge node for timely maintenance, thereby achieving the effect of reducing costs, ensuring safety and expanding products to services; the energy efficiency management module 403 is used to manage energy efficiency through system operation to reduce energy consumption, reduce maintenance costs and improve reliability; the intelligent manufacturing module 404 is used to increase and customize the functionality of the system and the robot according to user needs; the flexible replacement module 405 is used to flexibly adjust the robot's operation plan according to the characteristics of the edge node and quickly deploy new processes and models.

[0075] This embodiment also provides an operation method of a surgical robot master-slave hand control system based on 5G network and edge computing, comprising the following steps:

[0076] S1. Connect the robot master / slave to the system through a suitable network interface, and deploy the centralized operation to the edge computing server mec device through edge computing;

[0077] S2. Access 5G network, dedicated network and other network technologies simultaneously through industrial gateway devices. Set 5G network as the main network and dedicated network as the auxiliary network through parameter settings, and set appropriate switching protection mechanism;

[0078] S3. The operator in the machine room uses centralized processing equipment to quickly deploy the robot master / slave, and controls the independent operation of the master / slave respectively;

[0079] S4. During the operation of the robot, the working environment, surgical video, and surgical field image information are recorded in real time;

[0080] S5. The robot uses wireless transmission technology to transmit the recorded video to the cloud database via the existing network in a timely manner and automatically classifies and stores it;

[0081] S6. During the operation of the working network, the 5G network is mainly used. When a problem occurs in the 5G network or the network delay exceeds the preset threshold, the network switch set on the gateway device will automatically switch the working network to the dedicated network. During the network switching process, the switching protection mechanism will be used to avoid frequent switching, improve the quality of the working network, and ensure smooth system operation;

[0082] S7. A master hand is connected to multiple slave hands at the same time. When the operation on one of the slave hands is finished, the master hand can quickly switch to connect with another slave hand to control the operation.

[0083] like Fig. 9 As shown, this embodiment also provides an operating device of a surgical robot master-slave hand control system based on 5G network and edge computing, which includes a processor, a memory, and a computer program stored in the memory and running on the processor.

[0084] The processor includes one or more processing cores, the processors are connected to each other through a bus, the memory is used to store program instructions, and when the processor executes the program instructions in the memory, the above-mentioned surgical robot master-slave hand control system based on 5G network and edge computing is realized.

[0085] Optionally, the memory can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic storage, flash memory, magnetic disk or optical disk.

[0086] In addition, the present invention also provides a computer-readable storage medium, which stores a computer program. When the computer program is executed by a processor, it implements the above-mentioned surgical robot master-slave hand control system based on 5G network and edge computing.

[0087] Optionally, the present invention also provides a computer program product comprising instructions, which, when executed on a computer, enables the computer to execute the above-mentioned aspects of the surgical robot master-slave hand control system based on 5G network and edge computing.

[0088] A person skilled in the art will appreciate that all or part of the steps to implement the above embodiments may be accomplished by hardware or by instructing related hardware through a program, and the program may be stored in a computer-readable storage medium, and the above-mentioned storage medium may be a read-only memory, a disk, or an optical disk, etc.

[0089] The above shows and describes the basic principles, main features and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited by the above embodiments. The above embodiments and descriptions are only preferred examples of the present invention and are not intended to limit the present invention. Without departing from the spirit and scope of the present invention, the present invention may have various changes and improvements, which fall within the scope of the present invention. The scope of protection of the present invention is defined by the attached claims and their equivalents.

Claims

1. A surgical robot master-slave hand control system based on 5G network and edge computing, characterized by: include An infrastructure unit (100), an edge computing unit (200), an intelligent control unit (300) and an extended application unit (400); the signal output end of the infrastructure unit (100) is connected to the signal input end of the edge computing unit (200), the signal output end of the edge computing unit (200) is connected to the signal input end of the intelligent control unit (300), and the signal output end of the intelligent control unit (300) is connected to the signal input end of the extended application unit (400); the infrastructure unit (100) is used to provide basic equipment and technology for supporting system operation; the edge computing unit (200) is used to provide intelligent services nearby at the edge side of the robot operation system through edge node control technology; the intelligent control unit (300) is used to perform unified centralized control and distributed autonomous management of the robot's operating master hand and slave hand; the extended application unit (400) is used to add a variety of extended services on the basis of normal system operation to improve the functionality of the system; The infrastructure unit (100) comprises an application terminal module (101), a cloud database module (102), a network communication module (103) and a functional service module (104); The application terminal module (101), the cloud database module (102) and the functional service module (104) are connected in sequence via Ethernet communication and run in parallel; the application terminal module (101) is used to provide basic application equipment and terminal platforms for building the system and manage and allocate various devices; the cloud database module (102) is used to establish a database in the cloud to store image data and work data uploaded by the robot master hand and slave hands; the network communication module (103) is used to provide signal connection and data transmission channels between various levels of the system through a variety of network communication technologies; the functional service module (104) is used to support the operation of the system by setting up a variety of service items; The functional service module (104) comprises a network monitoring module (1041), a private network switching module (1042), an image recording module (1043) and a data cloud module (1044); the signal output end of the network monitoring module (1041) is connected to the signal input end of the private network switching module (1042), the network monitoring module (1041) and the image recording module (1043) operate in parallel, and the signal output end of the image recording module (1043) is connected to the signal input end of the data cloud module (1044); The network monitoring module (1041) is used to monitor the network link status in real time during the operation of the system to determine whether each link is connected smoothly; the private network switching module (1042) is used to switch to the private network to work and provide a ping-pong protection mechanism when a problem occurs in the current working network; the image recording module (1043) is used to record the working environment through a camera device set on the master / slave end of the robot; the data cloud module (1044) is used to timely transmit the recorded image video to the cloud database for storage through wireless transmission technology; The edge computing unit (200) comprises an edge deployment module (201), a data processing module (202), an edge node module (203) and a security protection module (204); The edge deployment module (201), the data processing module (202), the edge node module (203) and the security protection module (204) are connected in sequence via Ethernet communication and operate independently; the edge deployment module (201) is used to deploy edge computing workloads at different network levels to achieve targeted support for various 5G services; the data processing module (202) is used to process and self-manage data information within the system through edge computing; the edge node module (203) is used to use edge nodes closer to users as a beneficial supplement to cloud computing to reduce network waiting time; the security protection module (204) is used to establish end-to-end security protection measures across cloud computing and edge computing between each edge node; The data processing module (202) comprises a data filtering module (2021), a data computing module (2022), a data storage module (2023) and a data transmission module (2024); the signal output end of the data filtering module (2021) is connected to the signal input end of the data computing module (2022), the signal output end of the data computing module (2022) is connected to the signal input end of the data storage module (2023), and the signal output end of the data storage module (2023) is connected to the signal input end of the data transmission module (2024); the data filtering module (2021) is used to filter or analyze data at an edge node to reduce the pressure of cloud computing; the data computing module (2022) is used to implement data computing and analysis at the edge of the network close to the object or data source to reduce data transmission; the data storage module (2023) is used to store the data after computing and analyzing at the edge locally; the data transmission module (2024) is used to transmit the data stored at the edge for use; The intelligent control unit (300) comprises a centralized control module (301), a quick control module (302), a master-hand independent control module (303) and a slave-hand cloud control module (304); The signal output end of the centralized control module (301) is connected to the signal input end of the quick control module (302), and the signal output end of the quick control module (302) is simultaneously connected to the signal input ends of the master hand individual control module (303) and the slave hand cloud control module (304); the centralized control module (301) is used to centrally manage and uniformly allocate various levels and functions of the system through a main processor arranged in a computer room; the quick control module (302) is used to quickly deploy and allocate work content to the working areas of the robot master hand and a plurality of slave hands through the centralized control computer room; the master hand individual control module (303) is used to individually control the operation process of the robot master hand through a processor via a controller; the slave hand cloud control module (304) is used to individually control the operation process of each robot slave hand through a processor via a controller deployed at an edge node based on a cloud bearer network; The extended application unit (400) comprises an intermittent connection module (401), a predictive maintenance module (402), an energy efficiency management module (403), an intelligent manufacturing module (404) and a flexible replacement module (405); The intermittent connection module (401), the predictive maintenance module (402), the energy efficiency management module (403), the intelligent manufacturing module (404) and the flexible replacement module (405) are operated in parallel; the intermittent connection module (401) is used to reduce the data transmission cost through low intermittent connection between remote locations under the premise of complying with network security regulations, and obtain time data for real-time analysis through instant analysis to reduce transmission delay; the predictive maintenance module (402) is used to predict the operating status of edge devices by monitoring the operating status of each edge node for timely maintenance, thereby achieving the effect of reducing costs, ensuring safety and expanding products to services; the energy efficiency management module (403) is used to manage energy efficiency through system operation to reduce energy consumption, reduce maintenance costs and improve reliability; the intelligent manufacturing module (404) is used to increase and customize the functionality of the system and the robot according to user needs; the flexible replacement module (405) is used to flexibly adjust the robot's operation plan according to the characteristics of the edge node and quickly deploy new processes and models.

2. The surgical robot master-slave hand control system based on 5G network and edge computing according to claim 1 is characterized in that: In the private network switching module (1042), an algorithm for job priority is used in the switching process of different networks, and its calculation formula is: in, Indicates the job Priority during the switching process, The priority assigned to the job when it was submitted. is the time the job waits in the queue, is a constant factor. As the waiting time increases, the job priority increases dynamically until it reaches the threshold, which is the highest priority.

3. The surgical robot master-slave hand control system based on 5G network and edge computing according to claim 1 is characterized in that: In the data filtering module (2021), the calculation energy consumption expression of the local calculation process is: In the formula, Indicates the local calculation process The computational energy consumption of each task or workload; For the The energy consumption ratio coefficient of each CPU cycle is used to calculate the linear correlation between energy consumption and workload; Indicates Tasks in time The weight value of the workload intensity at time ; Represents the workload at time The energy consumption at that time.

4. The surgical robot master-slave hand control system based on 5G network and edge computing according to claim 1 is characterized in that: The operation method of the system includes the following steps: S1. Connect the robot master / slave to the system through a suitable network interface, and deploy the centralized operation to the edge computing server mec device through edge computing; S2. Use industrial gateway devices to simultaneously access the 5G network and dedicated line network. Set the 5G network as the primary and the dedicated line network as the secondary through parameter settings, and set a suitable switching protection mechanism; S3. The operator in the machine room uses centralized processing equipment to quickly deploy the robot master / slave, and controls the independent operation of the master / slave respectively; S4. During the operation of the robot, the working environment, surgical video, and surgical field image information are recorded in real time; S5. The robot uses wireless transmission technology to transmit the recorded video to the cloud database via the existing network in a timely manner and automatically classifies and stores it; S6. During the operation of the working network, the 5G network is mainly used. When a problem occurs in the 5G network or the network delay exceeds the preset threshold, the network switch set on the gateway device will automatically switch the working network to the dedicated network. During the network switching process, the switching protection mechanism will be used to avoid frequent switching, improve the quality of the working network, and ensure smooth system operation; S7. A master hand is connected to multiple slave hands at the same time. When the operation on one of the slave hands is finished, the master hand can quickly switch to connect with another slave hand to control the operation.

Images