Distributed message control method and system for industrial robot control

Abstract

The invention provides a distributed message control method and system for industrial robot control, and relates to the technical field of industrial robot control, the method comprises the following steps: receiving data issued by an industrial robot and storing the data to a network sending queue, the data comprising state data, sensor information and a task instruction; and grading the data in the network sending queue through a multi-level priority queue scheduling algorithm to obtain a plurality of queues with different priorities, and sequentially sending the queues to the network receiving queue based on the different priorities, so that a subscriber receives the data in the network receiving queue. According to the embodiment of the invention, based on a time-sensitive network technology and in combination with a real-time operating system priority scheduling mechanism, efficient message receiving and transmitting queue design is carried out, high-reliability distributed real-time message transmission is realized, and the requirement of industrial robot control is met.

Description

Technical Field

[0001] The present invention relates to the technical field of industrial robot control, and in particular to a distributed message control method and system for industrial robot control. Background Art

[0002] In distributed hard real-time and safety-critical applications such as industrial control and automotive applications, the demand for network communications continues to grow, while current proprietary bus-based network technologies have reached their limits in supporting the growing demand for communication bandwidth. To address this challenge, the industry has proposed a variety of proprietary network protocols based on standard Ethernet, such as industrial Ethernet control automation technology, automation bus standards based on industrial Ethernet technology, and serial real-time communication systems. Although the industrial control and automation fields can improve transmission real-time, reliability, and security through customized solutions, incompatible and relatively closed network technologies also bring problems such as poor interoperability, low portability, low application compatibility, and high development and deployment and operation and maintenance costs.

[0003] At present, distributed communication technology has become the main message transmission method in the field of industrial robot control. Most of the existing distributed middleware implementation methods are based on middleware frameworks such as ROS (Robot Operating System) and DDS (Data Distribution Service), which provide basic support for distributed communication. Among them, DDS is widely used in the industrial field due to its high reliability and real-time performance.

[0004] At present, the network control system in the intelligent operating system of industrial robots encapsulates the functions of industrial robots in a componentized form, which puts forward higher requirements on the real-time, reliability and security of communication between multiple components. The existing distributed communication methods cannot meet the above requirements well. Summary of the invention

[0005] To solve the above problems, an embodiment of the present invention provides a distributed message control method for industrial robot control, which is applied to a control system. The control system is connected to the industrial robot based on Ethernet and time-sensitive network communication. The industrial robot includes a publisher and a subscriber. The method includes: receiving data published by the industrial robot and storing the data in a network sending queue, wherein the data includes status data, sensor information and task instructions; through a multi-level priority queue scheduling algorithm, grading the data in the network sending queue to obtain multiple queues with different priority levels and sending them to the network receiving queue in sequence based on different priorities, so that the subscriber receives the data in the network receiving queue.

[0006] The distributed message control method for industrial robot control provided by the embodiment of the present invention is based on time-sensitive network technology and combined with the priority scheduling mechanism of the real-time operating system to perform efficient message sending and receiving queue design, realize high-reliability distributed real-time message transmission, and meet the needs of industrial robot control.

[0007] Optionally, the method further includes: selecting an optimal master clock according to an A-star-based clock selection algorithm, and synchronizing the clocks of each of the industrial robots based on the optimal master clock; the optimal clock is a master clock with the shortest transmission path and the smallest jitter.

[0008] In the embodiment of the present invention, an A-star-based clock selection algorithm is used to quickly select a clock, thereby reducing the master clock selection time and reducing the clock synchronization time consumption in the scheduling process, thereby improving the real-time performance of data transmission.

[0009] Optionally, the method further comprises: adopting a multi-path propagation mechanism so that a plurality of the industrial robots receive master clock synchronization information in parallel.

[0010] In the embodiment of the present invention, parallel multi-path synchronization is adopted. On the basis of traditional single-path synchronization, a multi-path propagation mechanism is introduced, and multiple nodes receive master clock synchronization information in parallel, thereby accelerating the synchronization coverage.

[0011] Optionally, the method further comprises: predicting a future clock drift error trend between the local clock and the master clock according to a pre-trained radial basis function network, and performing clock error compensation according to the drift error trend.

[0012] In the embodiment of the present invention, a clock drift correction algorithm based on a radial basis function neural network is established, which can predict the clock drift error.

[0013] Optionally, the method further includes: using a sliding window to record the clock deviation historical values ​​of the local clock over a period of time, and training the radial basis function network based on the clock deviation historical values; the input of the radial basis function network is the clock deviation historical values, and the output is the clock error compensation value.

[0014] In the embodiment of the present invention, a radial basis function network is trained based on the historical value of the clock deviation, and the trained radial basis function network can output clock error compensation.

[0015] Optionally, the data in the network sending queue is graded to obtain multiple queues with different priority levels through a multi-level priority queue scheduling algorithm, and the data are sent to the network receiving queue in sequence based on different priorities, including: classifying the data in the network sending queue according to the characteristics of the data, and adding a priority tag to each data packet according to the classification result; constructing multiple queues with different priorities, and mapping the data packets to queues with different priorities according to the priority tags of the data packets; sending the queues with different priorities to the network receiving queue in sequence based on different priorities; wherein the queues with higher priorities are sent first, and more bandwidth is allocated to the queues with higher priorities.

[0016] The embodiment of the present invention provides a specific method of a multi-level priority queue scheduling algorithm to ensure that high-priority robot message traffic is processed first and improve data transmission reliability.

[0017] Optionally, the method further includes: allocating bandwidth to queues of different priorities according to the priority levels and traffic requirements of the queues of different priorities; if the bandwidth requirements of multiple queues of different priorities are similar, allocating time slices to the multiple queues of different priorities in sequence in a round-robin scheduling manner.

[0018] The embodiments of the present invention provide scheduling strategies and bandwidth allocation strategies for queues of different priorities, thereby ensuring that high-priority robot message traffic is processed first and improving data transmission reliability.

[0019] Optionally, multiple low-priority queues adopt a bandwidth sharing mode, and occupy the remaining bandwidth when the bandwidth of the high-priority queue is not used up.

[0020] In the embodiment of the present invention, the low-priority queue can adopt a bandwidth sharing method, and only when the bandwidth of the high-priority queue is not used up will it occupy the remaining bandwidth.

[0021] Optionally, the method further includes: when network congestion occurs, using weighted random early detection as a queue discard strategy to randomly discard part of the data packets; when network congestion occurs, reducing bandwidth allocation of low priority queues.

[0022] The embodiment of the present invention provides a congestion control strategy to reduce the possibility that the distributed message mechanism of the industrial robot will reduce the timing of data packets due to network congestion.

[0023] An embodiment of the present invention provides a distributed message control system for industrial robot control, which is used to execute any of the above-mentioned distributed message control methods for industrial robot control.

[0024] The distributed message control system for industrial robot control provided by the embodiment of the present invention can achieve the same technical effect as the above-mentioned distributed message control method for industrial robot control. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on the provided drawings without paying creative work.

[0026] Figure 1 A block diagram of a high-reliability real-time distributed message mechanism for industrial robot control provided by an embodiment of the present invention;

[0027] Figure 2 A schematic diagram of a control system for connecting multiple industrial robot nodes provided by an embodiment of the present invention;

[0028] Figure 3 A schematic flow chart of a distributed message control method for industrial robot control provided by an embodiment of the present invention;

[0029] Figure 4 A schematic diagram of a clock architecture provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0030] In order to make the above-mentioned objects, features and advantages of the present invention more clearly understood, the specific embodiments of the present invention are described in detail below in conjunction with the accompanying drawings. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0031] The embodiment of the present invention designs and implements a distributed message mechanism for industrial robot control based on key mechanisms such as real-time information transmission of Time-Sensitive Networking (TSN) and transmission control based on quality of service strategy, thereby achieving high-reliability real-time distributed message distribution and information security transmission.

[0032] In response to the industrial robot network control system's demand for strong real-time and high-reliability message transmission between components, based on the time-sensitive network stack and the Ethernet network stack, we implement the publish / subscribe model, message queue cache, node discovery, service quality control and other technologies to form a high-reliability real-time distributed message mechanism.

[0033] TSN is an enhanced technology of standard Ethernet, which aims to provide real-time, reliable and efficient transmission for data streams of different priorities. Specifically, the existing standards such as IEEE 802.1AS (precision clock synchronization protocol), IEEE802.1Qbu (frame preprocessing standard), IEEE 802.1Qbv (traffic scheduling and time slot pre-scheduling standard) of TSN are adopted in this embodiment to ensure that different devices can transmit data in a coordinated manner, and schedule the traffic in a time-aware manner to ensure that high-priority data streams are transmitted within the specified time slot, and allow the switch to pre-process the traffic when processing the data stream to reduce delay. At the same time, it can be combined with carrier sense multiple access with collision detection (Carrier Sense Multiple Access withCollision Detection, CSMA / CD) through collision detection algorithm and conflict back-off algorithm, which can effectively reduce the conflicts caused by multiple devices sending data at the same time, and further ensure the reliability of the distributed message mechanism of industrial robots.

[0034] This embodiment can realize network transmission of the distributed message mechanism of the industrial robot, achieve high-precision time synchronization, low latency, high reliability and bandwidth guarantee, and meet the application requirements of high reliability, real-time and timing of the distributed communication mechanism.

[0035] Figure 1 The block diagram shows a high-reliability real-time distributed message mechanism for industrial robot control provided by an embodiment of the present invention.

[0036] exist Figure 1 The network transmission part and the message mechanism part are shown in . The network transmission part is composed of TSN and CSMA / CD, including the time-sensitive network fast clock selection algorithm based on A-star to quickly select the master clock, and the network fast clock correction algorithm based on the radial basis function (RBF) to compensate for the clock error; the message mechanism part includes hierarchical sending of different message queues based on the multi-level priority queue (PQ) scheduling algorithm, and the construction of network sending queues and network receiving queues. Figure 1 The figure also shows the distributed message mechanism of industrial robots, including node discovery, message serialization and QoS (Quality of Service) control.

[0037] like Figure 1 As shown in the figure, the main communication process of the distributed message mechanism of industrial robots is as follows:

[0038] First, all industrial robots and control systems are interconnected through standard Ethernet to form a network topology, integrate TSN technology, and achieve clock synchronization across the entire network through IEEE 802.1AS. Ensure that all robot systems and devices have consistent clocks so that the real-time control system can perform precise scheduling. This ensures that time-sensitive messages (such as control instructions and status updates) are given priority transmission in the network.

[0039] In this embodiment, the distributed communication adopts the publish-subscribe mode, and the robot can exchange information through the publish-subscribe node. Through the DDS (Data Distribution Service) protocol, the robot sends state data, sensor information and task instructions to the network.

[0040] The publisher publishes the information, and the published message enters the network sending queue. Then, through the multi-level priority queue PQ scheduling algorithm, different message queues are graded, and then the priority queue is sent to the network stack. The time slot scheduling uses IEEE802.1Qbv. The robot system defines a time window within which real-time critical data is transmitted. The scheduler will transmit messages of different priorities according to the time window setting to ensure the delivery of real-time messages. The queue information is sent to the network receiving queue cache, and the subscriber receives the message data.

[0041] Figure 2 A schematic diagram of connecting multiple industrial robot nodes to a control system is shown. Each industrial robot node is connected to the control system for communication, and multicast or unicast transmission can be used.

[0042] Figure 3 The following is a schematic flow chart of a distributed message control method for industrial robot control in an embodiment of the present invention. The method is applied to a control system, and the control system is connected to the industrial robot based on Ethernet and time-sensitive network communication. The industrial robot may include publishers and subscribers. Figure 3 As shown, the method includes:

[0043] S302, receiving data released by the industrial robot and storing the data in a network transmission queue. The data may include status data, sensor information and task instructions.

[0044] The control system receives the data published by each industrial robot and stores the data in a network sending queue.

[0045] S304, through a multi-level priority queue scheduling algorithm, the data in the network sending queue is classified to obtain multiple queues with different priorities and sent to the network receiving queue in sequence based on the different priorities, so that the subscriber receives the data in the network receiving queue.

[0046] Specifically, the data in the network sending queue can be classified according to its characteristics, and a priority tag can be added to each data packet according to the classification result. Then, multiple queues with different priorities are constructed, and the data packets are mapped to queues with different priorities according to the priority tags of the data packets. Finally, the queues with different priorities are sent to the network receiving queue in turn based on different priorities.

[0047] During scheduling, queues with higher priorities are sent first, and more bandwidth is allocated to queues with higher priorities. In this embodiment, queues with higher priorities are always scheduled first, and data packets of the highest priority queue are processed at any time.

[0048] Furthermore, the method further includes: allocating bandwidth to queues of different priorities according to their priority levels and traffic requirements; if the bandwidth requirements of multiple queues of different priorities are similar, allocating time slices to the queues of different priorities in turn in sequence using a round-robin scheduling method.

[0049] In this embodiment, each queue is allocated bandwidth according to its priority level and traffic demand, so as to avoid a queue from occupying too much bandwidth when traffic is high. For low priority queues, traffic can be queued and wait for free bandwidth, ensuring that each queue has a certain bandwidth allocation.

[0050] Specifically, multiple low-priority queues may adopt a bandwidth sharing method to occupy the remaining bandwidth when the bandwidth of the high-priority queue is not used up.

[0051] Furthermore, the method further includes: when network congestion occurs, using weighted random early detection as a queue discard strategy to randomly discard some data packets; when network congestion occurs, reducing bandwidth allocation for low priority queues. In this embodiment, a transmission control mechanism based on quality of service strategy is adopted to achieve high reliability real-time distributed message distribution and information security transmission.

[0052] The distributed message control method for industrial robot control provided by the embodiment of the present invention is based on time-sensitive network technology and combined with the priority scheduling mechanism of the real-time operating system to perform efficient message sending and receiving queue design, realize high-reliability distributed real-time message transmission, and meet the needs of industrial robot control.

[0053] Exemplarily, the design goal of the multi-level priority queue scheduling algorithm in this embodiment is as follows: according to the timeliness and importance of different traffic types, the traffic is allocated to multiple queues, each with a different priority. The network traffic is classified according to application requirements (such as control traffic, data traffic, real-time traffic, background traffic, etc.). The high-priority queue ensures the transmission delay of real-time traffic, and the low-priority traffic can be moderately delayed.

[0054] Specifically, the multi-level priority queue scheduling algorithm in this embodiment is as follows:

[0055] For example, there are 10 priority queues, and the priority of the queues ranges from 1 to 10. The smaller the number, the higher the priority. For example, priority queue 1 (highest priority) is used for real-time control data, and priority queue 10 (lowest priority) is used for background data flow.

[0056] The specific implementation steps of the multi-level priority queue scheduling algorithm are:

[0057] a. Traffic classification and marking

[0058] Traffic can be classified according to its characteristics (e.g., real-time, importance, etc.). Each data packet can be labeled according to the flow attributes (e.g., protocol type, packet size, source / destination address, etc.). At the same time, each data flow is assigned a priority and the priority of the data packet is marked.

[0059] High priority traffic: such as control commands, real-time status updates, etc., ensure that they are transmitted within the predetermined time window. Medium priority traffic: non-real-time status data, etc. Low priority traffic: data backup, log records, etc., can be transmitted during non-emergency periods.

[0060] b. Construction of multi-level queues

[0061] Map traffic to multiple queues based on different priorities:

[0062] Queue 1: Highest priority queue (control commands, real-time status).

[0063] Queue 2: The second highest priority queue (non-real-time status data).

[0064] Queue 3, 4, ..., 10: other low-priority queues (data backup, logging, etc.).

[0065] c. Scheduling strategy

[0066] The queue with a higher priority will always be scheduled first, such as the traffic in queue 1 will be prioritized over queue 2, and so on. At this time, the packets of the highest priority queue will be processed at all times.

[0067] Each queue is allocated bandwidth based on its priority and traffic demand, to prevent a queue from taking up too much bandwidth when traffic is high. For low-priority queues, traffic can be queued and wait for free bandwidth. Ensure that each queue has a certain amount of bandwidth allocated.

[0068] When the bandwidth requirements of queues are similar, round-robin scheduling is used to allocate time slices to each queue in turn. This method ensures that all queues can get a certain amount of bandwidth.

[0069] d. Bandwidth guarantee

[0070] For each queue, a fixed or dynamic bandwidth is allocated based on its priority. For high-priority queues, more bandwidth is usually allocated and low latency is guaranteed. Low-priority queues can share bandwidth and only occupy the remaining bandwidth when the bandwidth of the high-priority queue is not used up. When the resources are fully occupied, the TSN network reaches the upper limit of its carrying capacity. Define the bandwidth reservation ratio ρ as:

[0071]

[0072] Among them, C res To reserve bandwidth, C net is the total bandwidth.

[0073] e. Congestion control

[0074] When the network is congested, for example, a weighted random early detection (WRED) queue drop strategy is used: according to the priority of the data packet and the length of the queue, some data packets are randomly dropped, and low-priority traffic data packets are dropped first, reducing the possibility that the industrial robot distributed message mechanism will reduce the timing of data packets due to network congestion. The probability of data packet drop P is:

[0075]

[0076] Among them, avg_len is the current average length of the queue, min_th is the minimum threshold, max_th is the maximum threshold, and k_level is the current queue level.

[0077] f. Dynamic adjustment

[0078] Dynamically adjust the weight and bandwidth allocation of queues according to network load. When the network is congested, automatically reduce the bandwidth allocation of low-priority queues to reduce network congestion in advance and ensure the normal transmission of high-priority traffic.

[0079] In this embodiment, QoS network management technology is used to design a multi-level priority queue scheduling algorithm to ensure that high-priority robot message traffic is processed first and improve data transmission reliability.

[0080] Taking into account the clock drift phenomenon between multiple industrial robots, this embodiment also establishes a time-sensitive network fast clock selection algorithm based on A-star to reduce the master clock selection time, while reducing the clock synchronization time consumption in the scheduling process and improving the real-time performance of data transmission.

[0081] Based on this, the method further includes: selecting the best master clock according to the A-star-based clock selection algorithm, and synchronizing the clocks of the industrial robots based on the best master clock. Exemplarily, the best clock is the master clock with the shortest transmission path and the smallest jitter.

[0082] Figure 4 FIG. 2 shows a schematic diagram of the clock architecture in this embodiment. Figure 4 The master-slave architecture shown in the figure includes a synchronization message Sync, a follow message Follow_Up, a delay request message Delay_Req, and a delay response message Delay_Resp. The master clock initiates a synchronization request message Sync, and uses the local clock as a reference. It stamps the time when the message Sync is sent with a hardware timestamp t1, and records the timestamp on the master clock side. The time when the slave clock receives the Sync message is recorded as the hardware timestamp t2. After sending the Sync message, the master clock immediately sends a Follow_Up message carrying the timestamp information t1. After receiving the Follow_Up message, the slave clock saves the hardware timestamp t1. The slave clock sends a Delay_Req message, and at the same time stamps t3 and saves it. When the master clock receives the Delay_Req message, it stamps t4 and saves it. The master clock sends a Delay_Resp message to the slave clock, which carries the timestamp t4 information. The slave clock receives the timestamp t4 information and records it.

[0083] To ensure the clock synchronization performance of the master clock-slave clock architecture in TSN, during the network initialization phase, the sending frequency of synchronization messages (Sync) and follow-up messages (Follow_Up) is increased to quickly adjust the clock. When the synchronization is stable, the message frequency is gradually reduced to reduce the network load.

[0084] Then, the master clock is selected quickly, and the improved shortest path heuristic search A-Star algorithm is used to quickly select the best master clock in the entire network. This algorithm uses a path quality evaluation formula to quickly select the master clock with the shortest transmission path and the smallest jitter in the network topology.

[0085] f(n)=g(n)+ω·h(n)

[0086] Among them, f(n) is the cost estimate from the initial state via state n to the target state, g(n) is the actual cost from the initial state to state n, h(n) is the estimated cost of the best path from state n to the target state, and ω is the heuristic weight.

[0087] Optionally, the state of the master clock is quickly detected through a heartbeat mechanism. If the master clock fails, a quick switch is performed to shorten the recovery time.

[0088] Furthermore, a multi-path propagation mechanism is adopted, and multiple industrial robots receive master clock synchronization information in parallel. This embodiment adopts parallel multi-path synchronization, and introduces a multi-path propagation mechanism on the basis of traditional single-path synchronization, so that multiple nodes receive master clock synchronization information in parallel, thereby accelerating the synchronization coverage.

[0089] Considering that a clock may drift during long-term operation, an embodiment of the present invention further provides a correction algorithm for clock drift, which can predict the clock drift error and thus compensate for the error in a timely manner.

[0090] Based on this, this embodiment predicts the future clock drift error trend of the local clock and the master clock according to the pre-trained radial basis function network, and performs clock error compensation according to the drift error trend. Specifically, the training process of the above network can be carried out in the following manner: using a sliding window to record the clock deviation history value of the local clock within a period of time, and training the radial basis function network based on the clock deviation history value; the input of the radial basis function network is the clock deviation history value, and the output is the clock error compensation value.

[0091] In view of the clock drift phenomenon caused by the accumulated errors between the local clock and the master clock over time, this embodiment establishes a clock drift correction algorithm based on the RBF neural network to predict the clock drift error. Optionally, this embodiment designs a clock correction algorithm to perform fast clock drift detection and correction, uses a sliding window to record the clock deviation value over a period of time, predicts the future clock drift trend based on historical data, compensates for the error in advance, and designs a fast clock correction algorithm based on the RBF neural network.

[0092] The algorithm consists of an input layer, a hidden layer, and an output layer. The clock deviation recorded by the sliding window is used as the algorithm input, and the clock error compensation is used as the output. The neuron output of the hidden layer is constructed as follows:

[0093]

[0094] Among them, h j is the output, T offset is the clock deviation, c is the center value of the Gaussian function, and b is the width of the Gaussian function.

[0095] Its clock error compensation output is:

[0096]

[0097] Among them, T offset_com is the clock error compensation, and τ is the weight.

[0098] The learning algorithm for the weights of neural network training is:

[0099]

[0100] Among them, E p is the error function and η is the learning rate.

[0101] The result of weight iteration calculation is:

[0102] τ j (k+1)=τ j (k)+Δτ j +α·[τ j (k)-τ j (k-1)]

[0103] Among them, η is the learning rate and α is the momentum factor.

[0104] This embodiment uses the clock deviation data collected in the sliding window as the training set of the RBF neural network, and integrates the trained neural network with the correction algorithm, so as to predict the clock drift trend and compensate for the clock drift error in advance.

[0105] In view of the real-time and reliability problems that are prone to occur in traditional industrial robot network control systems, the embodiments of the present invention are based on time-sensitive network technology and combined with the priority scheduling mechanism of the real-time operating system to design an efficient message sending and receiving queue, realize high-reliability distributed real-time message transmission, and reach leading levels in real-time, reliability, transmission bandwidth and other indicators.

[0106] Specifically, the embodiments of the present invention have the following advantages:

[0107] (1) Establish a fast clock selection algorithm based on time-sensitive network to reduce the master clock selection time, while reducing the clock synchronization time consumption in the scheduling process and improving the real-time performance of data transmission; (2) Establish a clock drift correction algorithm based on RBF neural network to predict the clock drift error; (3) Design a multi-level priority queue scheduling algorithm to ensure that high-priority robot message traffic is given priority processing and improve data transmission reliability.

[0108] An embodiment of the present invention provides a distributed message control system for industrial robot control, which is used to execute the above-mentioned distributed message control method for industrial robot control.

[0109] The embodiment of the present invention also provides a computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, each process of the above-mentioned distributed message control method embodiment for industrial robot control is implemented, and the same technical effect can be achieved. To avoid repetition, it is not repeated here. The computer-readable storage medium is, for example, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk.

[0110] Of course, those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be implemented by instructing the control device through a computer, and the program can be stored in a computer-readable storage medium. When the program is executed, it may include the processes of the above-mentioned method embodiments, wherein the storage medium may be a memory, a disk, an optical disk, etc.

[0111] In this article, relational terms such as first and second, etc. are used only to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "comprise", "include" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the statement "comprise a ..." do not exclude the presence of other identical elements in the process, method, article or device including the elements.

[0112] The various embodiments in this specification are described in a progressive manner, and each embodiment focuses on the differences from other embodiments. The same or similar parts between the various embodiments can be referenced to each other.

[0113] The above description of the disclosed embodiments enables those skilled in the art to implement or use the present invention. Various modifications to these embodiments will be apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention will not be limited to the embodiments shown herein, but will conform to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A distributed message control method for industrial robot control, characterized in that: Applied to a control system, the control system is connected to an industrial robot based on Ethernet and a time-sensitive network communication, the industrial robot includes a publisher and a subscriber, and the method includes: Receiving data published by the industrial robot and storing the data in a network sending queue, the data including status data, sensor information and task instructions; Through a multi-level priority queue scheduling algorithm, the data in the network sending queue is graded to obtain multiple queues with different priorities and sent to the network receiving queue in sequence based on different priorities, so that the subscriber receives the data in the network receiving queue.

2. The method according to claim 1, characterized in that The method further comprises: The best master clock is selected according to the A-star-based clock selection algorithm, and the clocks of the industrial robots are synchronized based on the best master clock; the best clock is the master clock with the shortest transmission path and the smallest jitter.

3. The method according to claim 2, characterized in that The method further comprises: By adopting a multi-path propagation mechanism, a plurality of the industrial robots receive the master clock synchronization information in parallel.

4. The method according to claim 1, characterized in that: The method further comprises: The future clock drift error trend between the local clock and the master clock is predicted according to the pre-trained radial basis function network, and the clock error compensation is performed according to the drift error trend.

5. The method according to claim 4, characterized in that The method further comprises: A sliding window is used to record the clock deviation history value of the local clock within a period of time, and the radial basis function network is trained based on the clock deviation history value; the input of the radial basis function network is the clock deviation history value, and the output is the clock error compensation value.

6. The method according to claim 1, characterized in that The multi-level priority queue scheduling algorithm is used to classify the data in the network sending queue to obtain multiple queues with different priorities and send them to the network receiving queue in sequence based on different priorities, including: Classifying the data in the network sending queue according to characteristics, and adding a priority tag to each data packet according to the classification result; Constructing a plurality of queues of different priorities, and mapping the data packets to the queues of different priorities according to the priority labels of the data packets; Based on different priorities, queues of different priorities are sent to the network receiving queue in turn; wherein the queue with a higher priority is sent first, and more bandwidth is allocated to the queue with a higher priority.

7. The method according to claim 6, characterized in that The method further comprises: Allocate bandwidth to queues of different priorities based on their priority levels and traffic requirements; If the bandwidth requirements of multiple queues of different priorities are similar, a round-robin scheduling method is used to allocate time slices to the multiple queues of different priorities in turn in sequence.

8. The method according to claim 7, characterized in that Multiple low-priority queues share bandwidth and occupy the remaining bandwidth when the bandwidth of the high-priority queue is not used up.

9. The method according to claim 6, characterized in that The method further comprises: When network congestion occurs, weighted random early detection is used as a queue drop strategy to randomly drop some of the data packets; When network congestion occurs, reduce bandwidth allocation to low-priority queues.

10. A distributed message control system for industrial robot control, characterized in that: Used to execute the distributed message control method for industrial robot control as described in any one of claims 1-9.

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