Low-latency control data transmission method for multi-axis motion controller

Abstract

The present application relates to the technical field of data transmission, and particularly relates to a low-delay control data transmission method for a multi-axis motion controller. The present application obtains a fast response urgency coefficient of a current moment according to the similarity distribution of historical time sequence transmission amounts among different types of data to be transmitted at the current moment, and the bandwidth value and bus load rate distribution at different moments; obtains a transmission speed-up tendency degree of the current moment according to the end-to-end delay length distribution at different moments and the fast response urgency coefficient of the current moment; obtains the necessity of asynchronous transmission of the current moment according to the packet loss rate distribution, the effective payload ratio distribution and the weight of the heavy object at different moments; and obtains the low-delay transmission demand degree of the current moment according to the necessity of asynchronous transmission of the current moment and the transmission speed-up tendency degree, and regulates the data transmission bandwidth. The present application improves the effectiveness of the bandwidth quota regulation of the controller data transmission by accurately analyzing the low-delay transmission demand degree of the current moment.

Description

Technical Field

[0001] This invention relates to the field of data transmission technology, and more specifically to a low-latency control data transmission method for multi-axis motion controllers. Background Technology

[0002] A multi-axis motion controller is a high-tech control device that can simultaneously control the coordinated movement of multiple motors or joints. It is often used in intelligent assembly and collaborative scenarios of industrial robots and robotic arms. During the operation of a multi-axis motion controller, a large amount of data needs to be transmitted, such as command control or status feedback.

[0003] In existing technologies, network communication of controllers mainly includes two types of data transmission mechanisms: synchronous data transmission with low latency but consuming a large amount of data transmission resources, and asynchronous data transmission with relatively high latency but less consumption of transmission resources. Bandwidth quotas are selected based on the amount of tasks to be transmitted in real time. However, considering that the data transmission tasks and control operating environment of multi-axis motion controllers are different at different times in actual scenarios, the demand for the two types of data transmission mechanisms varies at different times. Traditional methods lack comprehensive consideration of multi-dimensional operating conditions, resulting in low adaptability of bandwidth regulation results and reduced data transmission efficiency for multi-axis motion controllers. Summary of the Invention

[0004] To address the varying demands on two types of data transmission mechanisms at different times, traditional methods lack comprehensive consideration of multi-dimensional operating conditions, resulting in low adaptability of bandwidth regulation results and reduced data transmission efficiency for multi-axis motion controllers. The present invention aims to provide a low-latency control data transmission method for multi-axis motion controllers, and the specific technical solution adopted is as follows: This invention proposes a low-latency control data transmission method for multi-axis motion controllers, the method comprising: Real-time acquisition of historical time-series transmission volume, bandwidth value, and bus load rate of various types of data to be transmitted during multi-axis motion controller operation; real-time acquisition of end-to-end delay, packet loss rate, and payload ratio of controller data transmission; real-time acquisition of the weight of the heavy object grasped by the robotic arm to which the controller belongs; Based on the similarity distribution of historical time-series transmission volumes among different types of data to be transmitted at the current moment, the strong correlation information aggregation factor at the current moment is obtained; based on the bandwidth values ​​and bus load rate distributions at different moments, the bandwidth constraint presentation degree at the current moment is obtained; based on the strong correlation information aggregation factor and bandwidth constraint presentation degree at the current moment, the fast response urgency coefficient at the current moment is obtained. Based on the end-to-end delay duration distribution at different times and the urgency coefficient of fast response at the current time, the transmission speed-up tendency at the current time is obtained; based on the packet loss rate distribution and payload ratio distribution at different times, the low latency adaptation coefficient at the current time is obtained; based on the weight of the object at different times and the low latency adaptation coefficient, the necessity of asynchronous transmission at the current time is obtained. Based on the necessity of asynchronous transmission and the trend towards faster transmission at the current moment, the demand for low-latency transmission at the current moment is obtained, and the data transmission bandwidth is adjusted accordingly.

[0005] Furthermore, the method for obtaining the strongly correlated information aggregation factor includes: Obtain the correlation coefficient of historical time-series transmission volume between different types of data to be transmitted at the current time. If the correlation coefficient is greater than the preset correlation threshold, the corresponding type is regarded as a strongly correlated type, forming a set of strongly correlated types at the current time. The number of strongly correlated types in the strongly correlated type set of different types of data to be transmitted at each historical moment is counted, and the average number of strongly correlated types at all historical moments is obtained as the average number of strongly correlated types. The difference between the number of all types in the strongly correlated type set and the average number of strongly correlated types is obtained and normalized, and used as the strongly correlated information aggregation factor.

[0006] Furthermore, the method for obtaining the bandwidth constraint rendering degree includes: Obtain the average bandwidth value at all historical time points as the historical average bandwidth value; obtain the average bus load rate at all historical time points as the historical average bus load rate. Based on the ratio of historical average bandwidth value to current bandwidth value, and the ratio of current bus load rate to historical average bus load rate, the bandwidth constraint presentation degree at the current moment is obtained. The bandwidth constraint presentation degree is negatively correlated with the current bandwidth value and positively correlated with the current bus load rate.

[0007] Furthermore, the method for obtaining the rapid response urgency coefficient includes: A negative correlation mapping is performed on the bandwidth constraint presentation degree at the current moment. The product between the negative correlation mapping result and the strong correlation information aggregation factor is used as the rapid response urgency coefficient at the current moment.

[0008] Furthermore, the method for obtaining the transmission speed-up tendency includes: Obtain the average of all end-to-end delays within the neighborhood at the current moment as the local delay; obtain the average of all end-to-end delays across all historical time ranges as the historical average delay. The difference between the local delay duration at the current moment and the historical average delay duration is obtained and normalized. Based on the normalization result, the gain of the fast response urgency coefficient at the current moment is adjusted to obtain the transmission speed-up tendency at the current moment.

[0009] Furthermore, the method for obtaining the low-latency adaptation coefficient includes: Based on the packet loss rate distribution at different times, the importance of missed transmissions at the current time is obtained; The average of the payload ratios at all historical moments is obtained as the historical average payload ratio; the average of the payload ratios at all moments within the neighborhood of the current moment is obtained as the local average payload ratio. Based on the ratio between historical average load ratio and local average load ratio, the load relative fluctuation factor is obtained. The local average load ratio and the load relative fluctuation factor are negatively correlated. The product between the load relative fluctuation factor and the importance of missed transmission is calculated as the low-latency adaptation coefficient at the current moment.

[0010] Furthermore, the method for obtaining the importance of missed transmissions includes: Within the neighborhood of the current time, obtain a fitted straight line that fits the packet loss rate of all time sequences; obtain the product of the slope of the fitted straight line and the preset trend weight coefficient as the first missed transmission importance coefficient. Based on the ratio between the current packet loss rate and the average packet loss rate at all historical times, a second missed transmission importance coefficient is obtained, and the packet loss rate is positively correlated with the second missed transmission importance coefficient. The sum of the first missed transmission importance coefficient and the second missed transmission importance coefficient is obtained, and the maximum value between the sum and the preset importance lower threshold is selected as the missed transmission importance at the current time.

[0011] Furthermore, the method for obtaining the necessity of asynchronous transmission includes: The delay tolerance is obtained based on the ratio of the average weight of the object at all historical moments to the weight of the object at the current moment. The weight of the object at the current moment is negatively correlated with the delay tolerance. A negative correlation mapping is performed on the low-latency adaptation coefficient, and the product between the negative correlation mapping result and the latency tolerance is obtained as the necessity of asynchronous transmission.

[0012] Furthermore, the method for obtaining the low-latency transmission demand includes: A negative correlation mapping is performed on the necessity of asynchronous transmission to obtain the product between the negative correlation mapping result and the transmission speed-up tendency, and then normalized to serve as the low-latency transmission demand degree.

[0013] Furthermore, the regulation of data transmission bandwidth includes: The minimum synchronous guarantee bandwidth and the minimum asynchronous guarantee bandwidth are preset. The rated bus bandwidth is subtracted from the sum of the minimum synchronous guarantee bandwidth and the minimum asynchronous guarantee bandwidth to obtain the dynamically allocable bandwidth. Multiply the low-latency transmission demand by the dynamically allocable bandwidth to obtain the synchronization bandwidth increment; add the minimum synchronization guarantee bandwidth to the synchronization bandwidth increment to obtain the total synchronization bandwidth quota allocated to synchronization data transmission at the current moment. The difference between the rated bus bandwidth and the total synchronous bandwidth quota is obtained and used as the total asynchronous bandwidth quota allocated to asynchronous data transmission.

[0014] The present invention has the following beneficial effects: This invention obtains the urgency coefficient for rapid response at the current moment based on the similarity distribution of historical time-series transmission volumes among different types of data to be transmitted at the current moment, as well as the distribution of bandwidth values ​​and bus load rates at different times. This reflects the comprehensive urgency of the system needing to allocate more bandwidth to ensure low-latency, rapid response transmission of data during synchronization processes when facing high-intensity multi-axis coupled collaborative actions, considering the sufficiency of available communication resources at the underlying level. Furthermore, based on the end-to-end delay duration distribution at different times and the urgency coefficient for rapid response at the current moment, this invention obtains the transmission speed-up trend at the current moment. This reflects the effectiveness of shortening end-to-end response time and ensuring high-latency transmission when facing strongly correlated control tasks and latency deterioration trends. This invention addresses the urgent need for strictly synchronous communication. Based on the packet loss rate distribution and payload ratio distribution at different times, it obtains the low-latency adaptation coefficient for the current moment, reflecting the comprehensive adaptability to stringent low-latency synchronous transmission requirements. Based on the weight of the load and the low-latency adaptation coefficient at different times, it obtains the necessity of asynchronous transmission at the current moment, reflecting the tolerance for communication latency and the safety feasibility of allocating bandwidth to asynchronous data under the current load and network conditions. Based on the necessity of asynchronous transmission and the trend towards faster transmission, it obtains the demand for low-latency transmission at the current moment, reflecting the tendency of the real-time controller's data transmission process towards synchronous data transmission, and thus regulating the data transmission bandwidth. This invention improves the effectiveness of controller data transmission bandwidth quota regulation by accurately analyzing the current demand for low-latency transmission. Attached Figure Description

[0015] Figure 1 A flowchart illustrating a low-latency control data transmission method for a multi-axis motion controller, as provided in one embodiment of the present invention; Figure 2 This is a flowchart illustrating a method for obtaining low-latency adaptation coefficients according to an embodiment of the present invention. Detailed Implementation

[0016] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains.

[0017] The following description, in conjunction with the accompanying drawings, details a specific scheme for a low-latency control data transmission method for multi-axis motion controllers provided by the present invention.

[0018] Please see Figure 1 The diagram illustrates a flowchart of a low-latency control data transmission method for multi-axis motion controllers according to an embodiment of the present invention. The specific method includes: Step S1: Real-time acquisition of historical time-series transmission volume, bandwidth value and bus load rate of various types of data to be transmitted during the operation of the multi-axis motion controller; real-time acquisition of end-to-end delay, packet loss rate and effective load ratio of controller data transmission; real-time acquisition of the weight of the heavy object grasped by the robotic arm to which the controller belongs.

[0019] In embodiments of the present invention, the real-time timing data information of various types of data to be transmitted is read by the transmission dispatch module, including the historical timing transmission volume information of each type of data to be transmitted, that is, the transmission volume sequence formed in the historical 24 hours at the real time; the bandwidth value and bus load rate of the controller's operating environment are read in real time by the bandwidth monitoring module; the end-to-end delay time of the controller is read in real time by the delay timing sensing module, that is, the total time from the issuance of a control command to the start of action of the corresponding actuator, including the master station software processing time, the frame transmission time on the physical line, and the hardware forwarding delay of each slave node, wherein end-to-end refers to the controller to the corresponding execution end, or the execution end to the controller; the data transmission monitoring module reads the packet loss rate and payload ratio of data transmission in real time; and the weight of the heavy object grasped by the robotic arm to which the controller belongs is read in real time by the grasping task recording module.

[0020] It should be noted that, considering the electromagnetic interference and bus jitter present in industrial environments, the acquired data is prone to sudden distortions, extreme values, or data gaps. Directly using these data in subsequent calculations can lead to results that deviate significantly from the actual working conditions and cause incorrect bandwidth allocation. Therefore, in order to remove missing values ​​from the read data, the read data is preprocessed by data cleaning. The median filtering algorithm is used to filter out sudden outliers in each time series data sequence. The specific methods are well known to those skilled in the art and will not be elaborated here.

[0021] Step S2: Based on the similarity distribution of historical time-series transmission volume among different types of data to be transmitted at the current moment, obtain the strong correlation information aggregation factor at the current moment; based on the bandwidth value and bus load rate distribution at different moments, obtain the bandwidth constraint presentation degree at the current moment; based on the strong correlation information aggregation factor and bandwidth constraint presentation degree at the current moment, obtain the fast response urgency coefficient at the current moment.

[0022] Considering that there are many strongly correlated data in the data to be transmitted by the multi-axis motion controller, the strongly correlated data should be packaged synchronously as much as possible during transmission to avoid local transmission interruptions caused by slow response. Therefore, analyzing the similarity of the historical transmission volume between the data to be transmitted reflects the strong correlation of the data to be transmitted, which helps to characterize the degree of demand for high-precision and low-latency transmission. Based on the similarity distribution of the historical time-series transmission volume between different types of data to be transmitted at the current moment, the strong correlation information aggregation factor at the current moment can be obtained.

[0023] Preferably, in one embodiment of the present invention, the method for obtaining the strongly correlated information aggregation factor includes: Obtain the correlation coefficient of historical time-series transmission volume between different types of data to be transmitted at the current time. If the correlation coefficient is greater than the preset correlation threshold, the corresponding type is regarded as a strongly correlated type, forming a set of strongly correlated types at the current time. It should be noted that, in the embodiments of the present invention, the correlation coefficient is the Pearson correlation coefficient, and the specific means are well known to those skilled in the art, and will not be described in detail here.

[0024] The number of strongly correlated types in the strongly correlated type set of different types of data to be transmitted at each historical moment is counted, and the average number of strongly correlated types at all historical moments is obtained as the average number of strongly correlated types. The difference between the number of all types in the strongly correlated type set and the average number of strongly correlated types is obtained and normalized, and used as the strongly correlated information aggregation factor.

[0025] Based on this, the number of all types in the strongly correlated type set reflects the scale of real-time data concurrency that needs to be strictly synchronized in time; the average number of strongly correlated types reflects the baseline synchronization communication load of the multi-axis controller under normal operating conditions. Therefore, the larger the difference, the larger the strongly correlated information aggregation factor at the current moment.

[0026] It should be noted that, in one embodiment of the present invention, the larger the correlation coefficient, the stronger the correlation of the data to be transmitted. The boundary value of strong coupling correlation of dual-axis linkage is determined based on historical debugging experience, and the preset correlation threshold is set to 0.76 according to relevant historical experience. In other embodiments of the present invention, the size of the preset correlation threshold can be set according to specific circumstances, and will not be limited or elaborated here.

[0027] It should be noted that in the embodiments of the present invention, maximum and minimum value normalization is adopted, that is, the maximum and minimum values ​​are obtained based on a large amount of historical data and normalized. If the difference is greater than the maximum value, the normalization result is set to 1, and if the difference is less than the minimum value, the normalization result is set to 0. The specific means are well known to those skilled in the art and will not be described in detail here.

[0028] During multi-axis linkage, position commands and feedback need to be refreshed within a very short period of time. Therefore, the rapid transmission of data requires the support of sufficient bandwidth resources. The bus load rate refers to the percentage of the effective data actually transmitted on the bus per unit time to the theoretical maximum transmission capacity. The smaller the bus load rate, the more transmission resources are available in real time, and the smaller the limitation on transmission resources. Based on the bandwidth value and bus load rate distribution at different times, the bandwidth constraint presentation degree at the current time can be obtained.

[0029] Preferably, in one embodiment of the present invention, the method for obtaining the bandwidth constraint rendering degree includes: Obtain the average bandwidth value at all historical time points as the historical average bandwidth value; obtain the average bus load rate at all historical time points as the historical average bus load rate. Based on the ratio of historical average bandwidth value to current bandwidth value, and the ratio of current bus load rate to historical average bus load rate, the bandwidth constraint presentation degree at the current moment is obtained. The bandwidth constraint presentation degree is negatively correlated with the current bandwidth value and positively correlated with the current bus load rate.

[0030] It should be noted that the more abundant the bandwidth resources, the lower the bus load rate, reflecting better real-time transmission resources and a smaller bandwidth constraint presentation. Therefore, the bandwidth constraint presentation is negatively correlated with the current bandwidth value and positively correlated with the current bus load rate. In the embodiments of the present invention, the historical average bandwidth value is calculated as the sum of the current bandwidth value and the smallest positive number, which is used as the first ratio; the current bus load rate is calculated as the sum of the historical average bus load rate and the smallest positive number, which is used as the second ratio; and the product between the first ratio and the second ratio is calculated as the bandwidth constraint presentation.

[0031] The bandwidth constraint presentation degree reflects the degree of limitation of communication network transmission resources. The smaller the bandwidth constraint presentation degree, the more abundant the idle transmission resources in the current network environment, which objectively provides better underlying resource support conditions for high-precision and fast-response synchronous transmission. Moreover, when the strong correlation information aggregation factor is larger and the synchronization demand is higher, the feasibility and necessity of implementing high-precision and fast transmission are greater. Based on the strong correlation information aggregation factor and bandwidth constraint presentation degree at the current moment, the urgency coefficient of fast response at the current moment is obtained.

[0032] Preferably, in one embodiment of the present invention, the method for obtaining the urgency coefficient of rapid response includes: A negative correlation mapping is performed on the bandwidth constraint presentation degree at the current moment. The product between the negative correlation mapping result and the strong correlation information aggregation factor is used as the rapid response urgency coefficient at the current moment.

[0033] It should be noted that, in one embodiment of the present invention, negative correlation mapping is performed by taking the reciprocal. To avoid the formula being meaningless when the bandwidth constraint is zero, a very small positive number with consistent dimensions is added to the denominator, the value of which is specifically set according to the range of the denominator. In other embodiments of the present invention, an exponential function with the natural constant as its base can also be used. Negative correlation mapping is performed; the specific methods are well known to those skilled in the art and will not be elaborated here.

[0034] Step S3: Based on the end-to-end delay duration distribution at different times and the urgency coefficient of fast response at the current time, obtain the transmission speed-up trend at the current time; based on the packet loss rate distribution and payload ratio distribution at different times, obtain the low latency adaptation coefficient at the current time; based on the weight of the object at different times and the low latency adaptation coefficient, obtain the necessity of asynchronous transmission at the current time.

[0035] Considering that end-to-end delay duration characterizes the actual response performance of data transmission in the short term, the controller transmission mode can be evaluated more accurately. The urgency coefficient of fast response reflects the overall urgency of the system in the face of high-intensity multi-axis coupled collaborative action, combined with the sufficiency of available communication resources at the underlying level, that it urgently needs to allocate more bandwidth to ensure low-latency and fast-response transmission of synchronous process data. Therefore, based on the distribution of end-to-end delay duration within the historical time range and the urgency coefficient of fast response at the current moment, the transmission speed-up trend at the current moment can be obtained.

[0036] Preferably, in one embodiment of the present invention, the method for obtaining the transmission speed-up tendency includes: Obtain the average of all end-to-end delays within the neighborhood at the current moment as the local delay; obtain the average of all end-to-end delays across all historical time ranges as the historical average delay. It should be noted that, in one embodiment of the present invention, the neighborhood range is a range consisting of historical moments of a preset duration, with the current time as the reference, and the preset duration is set to 10 seconds; the historical time range is a range consisting of the current time and all previous historical moments; in other embodiments of the present invention, the size of the neighborhood range can be set according to specific circumstances, and will not be limited or elaborated here.

[0037] The difference between the local delay duration at the current moment and the historical average delay duration is obtained and normalized. Based on the normalization result, the gain of the fast response urgency coefficient at the current moment is adjusted to obtain the transmission speed-up tendency at the current moment.

[0038] It should be noted that, in the embodiments of the present invention, the difference between the local delay duration at the current moment and the historical average delay duration is obtained, and divided by the historical average delay duration, so that the absolute time difference is converted into a relative rate of change, reflecting the degree of network degradation; the division result is normalized using a hyperbolic tangent function so that the result is in the range of -1 to 1; the gain adjustment is obtained by: obtaining the sum of the positive integer 1 and the normalization result as the adjustment weight; obtaining the product between the adjustment weight and the fast response urgency coefficient as the transmission speed-up tendency at the current moment.

[0039] The formula for the transmission speed-up trend is expressed as: ;in, Indicates the degree of transmission speed increase trend; It represents the average of all end-to-end delays within the neighborhood at the current moment, i.e., the local delay. This represents the average end-to-end latency across all historical timeframes, i.e., the historical average latency. Represents the hyperbolic tangent function; This indicates the urgency level for rapid response.

[0040] In demanding real-time controller operating systems, a high packet loss rate indicates that the proportion of tasks that fail to complete data transmission or processing within the specified time is insufficient to handle short-term data transmission tasks. In such cases, the supply of transmission resources should be appropriately increased, favoring higher-precision, low-latency synchronous data transmission. The payload ratio reflects the ratio of bus transmission efficiency to protocol overhead. A low payload ratio indicates that the bus is filled with short frames carrying very little useful data, and it does not favor asynchronous transmission that supports large data blocks. Based on the packet loss rate distribution and payload ratio distribution at different times, the low-latency adaptation coefficient for the current time can be obtained.

[0041] Preferably, in one embodiment of the present invention, the method for obtaining the low-latency adaptation coefficient is described in [reference needed]. Figure 2 It illustrates a flowchart of a method for obtaining low-latency adaptation coefficients, including: Step S201: Based on the packet loss rate distribution at different times, obtain the importance of missed transmissions at the current time.

[0042] Preferably, in one embodiment of the present invention, the method for obtaining the importance of missed transmissions includes: Within the neighborhood of the current time, obtain a fitted straight line that fits the packet loss rate of all time sequences; obtain the product of the slope of the fitted straight line and the preset trend weight coefficient as the first missed transmission importance coefficient. It should be noted that, in the embodiments of the present invention, the slope of the fitted line is obtained by taking the derivative of the fitted line. In order to enable the system to have a moderate ability to intervene in advance, so as to raise the attention in time when the packet loss rate rises rapidly to prevent communication interruption, and to avoid over-adjustment due to occasional network jitter, the trend weight coefficient is preset to 0.5 based on relevant historical experience. The specific means are technical means well known to those skilled in the art, and will not be described in detail here.

[0043] Based on the ratio between the current packet loss rate and the average packet loss rate at all historical times, a second missed transmission importance coefficient is obtained, and the packet loss rate is positively correlated with the second missed transmission importance coefficient. The sum of the first missed transmission importance coefficient and the second missed transmission importance coefficient is obtained, and the maximum value between the sum and the preset importance lower threshold is selected as the missed transmission importance at the current time.

[0044] It should be noted that, in the embodiments of the present invention, when the packet loss rate shows a decreasing trend, the slope is negative, which makes the sum of the first missed transmission importance coefficient and the second missed transmission importance coefficient potentially negative. The lower the tendency for synchronous data transmission with high precision and low latency, the smaller the missed transmission importance. In order to ensure that the missed transmission importance is not negative, the preset importance lower limit threshold is set to 0.

[0045] It should be noted that, in the embodiments of the present invention, the packet loss rate at the current moment is calculated as the sum of the average packet loss rate at all historical moments and a very small positive number, which is used as the second error transmission importance coefficient; in order to avoid the average packet loss rate being 0, a very small positive number with the same dimensions as the denominator is added, and its value is specifically set according to the range of values ​​of the denominator, which will not be elaborated here.

[0046] Step S202: Obtain the average of the effective load ratio at all historical times as the historical average load ratio; obtain the average of the effective load ratio at all times within the neighborhood of the current time as the local average load ratio.

[0047] By quantizing the mean value, sudden changes in the length of a single communication frame and occasional noise interference are filtered out, which smoothly reflects the true data transmission load trend and avoids making incorrect bandwidth allocation decisions based on a single extreme value. The historical average load ratio reflects the benchmark steady-state norm of the multi-axis control system under macroscopic long-cycle operation, with a mixture of long and short frames of bus communication data. The lower the local average load ratio, the denser the short frames of high-frequency control are in a short period of time.

[0048] Step S203: Based on the ratio of historical average load ratio to local average load ratio, obtain the load relative fluctuation factor. The local average load ratio and the load relative fluctuation factor are negatively correlated. Calculate the product between the load relative fluctuation factor and the importance of missed transmission, and use it as the low latency adaptation coefficient at the current moment.

[0049] It should be noted that, in one embodiment of the present invention, the historical average load ratio is calculated and divided by the sum of the local average load ratio and the minimum positive number to serve as the load relative fluctuation factor; in order to avoid the effective load ratio being 0, a minimum positive number with the same dimensions as the denominator is added, and its value is specifically set according to the range of values ​​of the denominator, which will not be elaborated here.

[0050] Based on this, the smaller the local average load ratio, the more real-time control short frames are present on the bus, indicating that the current communication is more inclined to high-frequency scattered control scheduling. More bandwidth quota must be allocated for synchronous data transmission to avoid control command congestion and delay, and the lower the low latency adaptation coefficient is. The smaller the importance of missed transmission, the healthier the current network communication and the smooth issuance of control commands, and therefore the lower the low latency adaptation coefficient is.

[0051] In scenarios where multi-axis motion controllers drive robotic arms for tasks such as grasping and handling, when the robotic arm grasps a heavy object, the load inertia ratio of the robotic arm is very large. At this time, the entire system is extremely sensitive to the lag of control commands. Even a jitter of only tens of microseconds in communication will cause strong resonance or end-effector jitter in the motor output torque. The more urgent the need for high-precision, low-latency data transmission, the less necessary asynchronous transmission becomes. The necessity of asynchronous transmission at the current moment can be obtained based on the weight of the object at different times and the low-latency adaptation coefficient.

[0052] Preferably, in one embodiment of the present invention, the method for obtaining the necessity of asynchronous transmission includes: The delay tolerance is obtained based on the ratio of the average weight of the object at all historical moments to the weight of the object at the current moment. The weight of the object at the current moment is negatively correlated with the delay tolerance. It should be noted that, in one embodiment of the present invention, the average weight of the object at all historical moments is calculated and divided by the sum of the weight of the object at the current moment and a very small positive number, which is used as the delay tolerance. In order to avoid the weight of the object at the current moment being 0, a very small positive number with the same dimension as the denominator is added. The value of the number is specifically set according to the range of the denominator, which will not be elaborated here.

[0053] A negative correlation mapping is performed on the low-latency adaptation coefficient, and the product between the negative correlation mapping result and the latency tolerance is obtained as the necessity of asynchronous transmission.

[0054] It should be noted that the lighter the weight of the object at the current moment, the smaller the communication error caused by the object, the greater the latency tolerance, and the smaller the low-latency adaptation coefficient, the higher the asynchronous transmission tolerance. In one embodiment of the present invention, negative correlation mapping is performed by taking the reciprocal. In order to avoid the low-latency adaptation coefficient being 0, a very small positive number with the same dimension as the denominator is added, and its value is specifically set according to the range of the denominator. The specific means are well known to those skilled in the art and will not be described in detail here.

[0055] Step S4: Based on the necessity of asynchronous transmission and the trend of transmission speed-up at the current moment, obtain the demand for low-latency transmission at the current moment, and adjust the data transmission bandwidth accordingly.

[0056] The necessity of asynchronous transmission reflects the tolerance for communication latency under the current load and network conditions, as well as the security and feasibility of allocating bandwidth to asynchronous data; the tendency to increase transmission speed reflects the urgent need to shorten end-to-end response time and ensure strict synchronous communication when facing strongly correlated control tasks and latency deterioration trends; the greater the tendency to increase transmission speed and the smaller the necessity of asynchronous transmission, the greater the tendency of the controller to use high-precision, low-latency synchronous transmission for real-time data transmission, and the greater the demand for low-latency transmission.

[0057] Preferably, in one embodiment of the present invention, the method for obtaining the low-latency transmission requirement includes: A negative correlation mapping is performed on the necessity of asynchronous transmission to obtain the product between the negative correlation mapping result and the transmission speed-up tendency, and then normalized to serve as the low-latency transmission demand degree.

[0058] It should be noted that, in one embodiment of the present invention, negative correlation mapping is performed by taking the reciprocal. In order to avoid the necessity of asynchronous transmission being 0, a very small positive number with the same dimension as the denominator is added, and its value is specifically set according to the range of the denominator. Maximum and minimum value normalization is adopted, that is, when the system is enabled, it retrieves the highest control demand estimate and the lower limit demand estimate in the past records and normalizes them to the interval [0,1]. The specific means are well known to those skilled in the art and will not be described in detail here.

[0059] Preferably, the low-latency transmission demand reflects the real-time controller's tendency towards synchronous data transmission; the greater the low-latency transmission demand, the greater the tendency towards synchronous transmission, and the greater the bandwidth usage. In one embodiment of the present invention, the data transmission bandwidth is controlled by: The minimum synchronous guarantee bandwidth and the minimum asynchronous guarantee bandwidth are preset. The rated bus bandwidth is subtracted from the sum of the minimum synchronous guarantee bandwidth and the minimum asynchronous guarantee bandwidth to obtain the dynamically allocable bandwidth. Multiply the low-latency transmission demand by the dynamically allocable bandwidth to obtain the synchronization bandwidth increment; add the minimum synchronization guarantee bandwidth to the synchronization bandwidth increment to obtain the total synchronization bandwidth quota allocated to synchronization data transmission at the current moment. The difference between the rated bus bandwidth and the total synchronous bandwidth quota is obtained and used as the total asynchronous bandwidth quota allocated to asynchronous data transmission.

[0060] Based on this, by allocating appropriate transmission bandwidth, the bus bandwidth can be dynamically and securely allocated while ensuring uninterrupted basic communication.

[0061] It should be noted that, in the embodiments of the present invention, the method for obtaining the minimum synchronous guarantee bandwidth is as follows: multiply the total number of axis nodes currently connected to the bus by the fixed byte length of the process data dictionary of a single node to obtain the total amount of synchronous data, and then divide by the system's basic communication cycle; the minimum asynchronous guarantee bandwidth can be calculated by dividing the number of bytes of basic diagnostic messages required for the underlying communication link to keep it alive by the link keep-alive time threshold, or by manually entering a fixed empirical value during system initialization; the rated bus bandwidth is obtained by reading the physical layer protocol parameters of the multi-axis controller's underlying network card or the system's initial network configuration file.

[0062] In summary, this invention obtains the urgency coefficient for rapid response at the current moment based on the similarity distribution of historical time-series transmission volumes among different types of data to be transmitted, as well as the distribution of bandwidth values ​​and bus load rates at different times; it obtains the transmission speed-up trend at the current moment based on the end-to-end delay duration distribution at different times and the rapid response urgency coefficient at the current moment; it obtains the necessity of asynchronous transmission at the current moment based on the packet loss rate distribution, payload ratio distribution, and weight of the load at different times; and it obtains the demand for low-latency transmission at the current moment based on the necessity of asynchronous transmission and the transmission speed-up trend, thereby regulating the data transmission bandwidth. This invention improves the effectiveness of controller data transmission bandwidth quota regulation by accurately analyzing the demand for low-latency transmission at the current moment.

Claims

1. A low-latency control data transmission method for multi-axis motion controllers, characterized in that, The method includes: Real-time acquisition of historical time-series transmission volume, bandwidth value, and bus load rate of various types of data to be transmitted during multi-axis motion controller operation; real-time acquisition of end-to-end delay, packet loss rate, and payload ratio of controller data transmission; real-time acquisition of the weight of the heavy object grasped by the robotic arm to which the controller belongs; Based on the similarity distribution of historical time-series transmission volumes among different types of data to be transmitted at the current moment, the strong correlation information aggregation factor at the current moment is obtained; based on the bandwidth values ​​and bus load rate distributions at different moments, the bandwidth constraint presentation degree at the current moment is obtained; based on the strong correlation information aggregation factor and bandwidth constraint presentation degree at the current moment, the fast response urgency coefficient at the current moment is obtained. Based on the end-to-end delay duration distribution at different times and the urgency coefficient of fast response at the current time, the transmission speed-up tendency at the current time is obtained; based on the packet loss rate distribution and payload ratio distribution at different times, the low latency adaptation coefficient at the current time is obtained; based on the weight of the object at different times and the low latency adaptation coefficient, the necessity of asynchronous transmission at the current time is obtained. Based on the necessity of asynchronous transmission and the trend towards faster transmission at the current moment, the demand for low-latency transmission at the current moment is obtained, and the data transmission bandwidth is adjusted accordingly.

2. The low-latency control data transmission method for multi-axis motion controllers according to claim 1, characterized in that, The method for obtaining the strongly correlated information aggregation factor includes: Obtain the correlation coefficient of historical time-series transmission volume between different types of data to be transmitted at the current time. If the correlation coefficient is greater than the preset correlation threshold, the corresponding type is regarded as a strongly correlated type, forming a set of strongly correlated types at the current time. The number of strongly correlated types in the strongly correlated type set of different types of data to be transmitted at each historical moment is counted, and the average number of strongly correlated types at all historical moments is obtained as the average number of strongly correlated types. The difference between the number of all types in the strongly correlated type set and the average number of strongly correlated types is obtained and normalized, and used as the strongly correlated information aggregation factor.

3. The low-latency control data transmission method for multi-axis motion controllers according to claim 1, characterized in that, The method for obtaining the bandwidth constraint rendering degree includes: Obtain the average bandwidth value at all historical time points as the historical average bandwidth value; obtain the average bus load rate at all historical time points as the historical average bus load rate. Based on the ratio of historical average bandwidth value to current bandwidth value, and the ratio of current bus load rate to historical average bus load rate, the bandwidth constraint presentation degree at the current moment is obtained. The bandwidth constraint presentation degree is negatively correlated with the current bandwidth value and positively correlated with the current bus load rate.

4. The low-latency control data transmission method for multi-axis motion controllers according to claim 1, characterized in that, The method for obtaining the urgency coefficient of the rapid response includes: A negative correlation mapping is performed on the bandwidth constraint presentation degree at the current moment. The product between the negative correlation mapping result and the strong correlation information aggregation factor is used as the rapid response urgency coefficient at the current moment.

5. The low-latency control data transmission method for multi-axis motion controllers according to claim 1, characterized in that, The method for obtaining the transmission speed-up tendency includes: Obtain the average of all end-to-end delays within the neighborhood at the current moment as the local delay; obtain the average of all end-to-end delays across all historical time ranges as the historical average delay. The difference between the local delay duration at the current moment and the historical average delay duration is obtained and normalized. Based on the normalization result, the gain of the fast response urgency coefficient at the current moment is adjusted to obtain the transmission speed-up tendency at the current moment.

6. The low-latency control data transmission method for multi-axis motion controllers according to claim 1, characterized in that, The method for obtaining the low-latency adaptation coefficient includes: Based on the packet loss rate distribution at different times, the importance of missed transmissions at the current time is obtained; The average of the payload ratios at all historical moments is obtained as the historical average payload ratio; the average of the payload ratios at all moments within the neighborhood of the current moment is obtained as the local average payload ratio. Based on the ratio between historical average load ratio and local average load ratio, the load relative fluctuation factor is obtained. The local average load ratio and the load relative fluctuation factor are negatively correlated. The product between the load relative fluctuation factor and the importance of missed transmission is calculated as the low-latency adaptation coefficient at the current moment.

7. A low-latency control data transmission method for multi-axis motion controllers according to claim 6, characterized in that, The method for obtaining the importance of missed transmissions includes: Within the neighborhood of the current time, obtain a fitted straight line that fits the packet loss rate of all time sequences; obtain the product of the slope of the fitted straight line and the preset trend weight coefficient as the first missed transmission importance coefficient. Based on the ratio between the current packet loss rate and the average packet loss rate at all historical times, a second missed transmission importance coefficient is obtained, and the packet loss rate is positively correlated with the second missed transmission importance coefficient. The sum of the first missed transmission importance coefficient and the second missed transmission importance coefficient is obtained, and the maximum value between the sum and the preset importance lower threshold is selected as the missed transmission importance at the current time.

8. A low-latency control data transmission method for multi-axis motion controllers according to claim 1, characterized in that, The method for obtaining the necessity of asynchronous transmission includes: The delay tolerance is obtained based on the ratio of the average weight of the object at all historical moments to the weight of the object at the current moment. The weight of the object at the current moment is negatively correlated with the delay tolerance. A negative correlation mapping is performed on the low-latency adaptation coefficient, and the product between the negative correlation mapping result and the latency tolerance is obtained as the necessity of asynchronous transmission.

9. A low-latency control data transmission method for multi-axis motion controllers according to claim 1, characterized in that, The method for obtaining the low-latency transmission demand includes: A negative correlation mapping is performed on the necessity of asynchronous transmission to obtain the product between the negative correlation mapping result and the transmission speed-up tendency, and then normalized to serve as the low-latency transmission demand degree.

10. A low-latency control data transmission method for multi-axis motion controllers according to claim 1, characterized in that, The regulation of data transmission bandwidth includes: The minimum synchronous guarantee bandwidth and the minimum asynchronous guarantee bandwidth are preset. The rated bus bandwidth is subtracted from the sum of the minimum synchronous guarantee bandwidth and the minimum asynchronous guarantee bandwidth to obtain the dynamically allocable bandwidth. Multiply the low-latency transmission demand by the dynamically allocable bandwidth to obtain the synchronization bandwidth increment; add the minimum synchronization guarantee bandwidth to the synchronization bandwidth increment to obtain the total synchronization bandwidth quota allocated to synchronization data transmission at the current moment. The difference between the rated bus bandwidth and the total synchronous bandwidth quota is obtained and used as the total asynchronous bandwidth quota allocated to asynchronous data transmission.

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