Industrial robot remote teaching data transmission method and system

Abstract

The application relates to the technical field of robot control, and discloses an industrial robot remote teaching data transmission method and system. The method comprises the following steps: acquiring remote teaching data, network state parameters and motion states; dividing the data into safety control layer, state feedback layer and media display layer data according to business semantics and mapping independent channels; determining network quality levels and obtaining joint operation states in combination with the motion states; determining channel transmission scheduling strategies and resource allocation according to the joint operation states, and the priorities of the safety control layer, the state feedback layer and the media display layer are sequentially reduced; updating the strategies and adjusting the resources when the joint operation states change, keeping the safety control layer resources when the joint operation states change, and reducing the media display layer and the state feedback layer resources. The application guarantees the reliability of safety control data transmission in a weak network environment, reduces the influence of head congestion, and improves the utilization rate of transmission resources through data layering and dynamic scheduling.

Description

Technical Field

[0001] This invention relates to the field of robot control technology, and in particular to a method and system for remote teaching data transmission for industrial robots. Background Technology

[0002] During remote teaching of industrial robots, it is necessary to transmit safety control commands, robot status data, and media data such as video and point clouds between the remote teaching terminal and the robot. To avoid head-of-line congestion when using a single TCP connection to transmit various types of data, related technologies have developed a solution based on multiple independent UDP channels to transmit control data, status data, and media data separately, with each channel pre-configured with a fixed transmission rate, refresh rate, and quality of service level.

[0003] However, the aforementioned multi-channel transmission schemes typically employ static resource configuration, failing to dynamically adjust transmission resources for different service data based on real-time network conditions and robot motion status. When available bandwidth decreases or network jitter and packet loss intensify, large volumes of media data may continue to consume network bandwidth and terminal processing resources, while security control data cannot receive timely transmission resource guarantees. Furthermore, these schemes often rely on general-purpose operating systems for software scheduling of different channels, making critical security control data susceptible to application processing load and kernel scheduling latency.

[0004] Therefore, how to layer remote teaching data according to business criticality and dynamically adjust the transmission strategy of each layer of data in combination with network status and robot motion status has become an urgent technical problem to be solved. Summary of the Invention

[0005] The purpose of this invention is to provide a method and system for remote teaching data transmission for industrial robots, aiming to solve the problem of how to layer remote teaching data according to business criticality and dynamically adjust the transmission strategy of each layer of data in combination with network status and robot motion status.

[0006] In a first aspect, embodiments of the present invention provide a method for remote teaching data transmission for industrial robots, comprising: Acquire the remote teaching data to be transmitted, the current network status parameters, and the motion status of the industrial robot; Based on the business semantics of the remote teaching data, it is divided into security control layer data, status feedback layer data and media display layer data, and the data of different layers are mapped to multiple independent transmission channels respectively. The network quality level is determined based on the current network status parameters, and the joint operation status is determined based on the network quality level and the motion status. Based on the joint operation status, the transmission scheduling strategy and transmission resource allocation corresponding to each transmission channel are determined; wherein, the priority of transmission resource allocation for the transmission channels corresponding to the security control layer, status feedback layer and media presentation layer decreases in that order. In response to a change in the joint operation status, the transmission scheduling strategy corresponding to each transmission channel is updated, and the transmission resources of each transmission channel are adjusted; wherein, when the transmission resources decrease, the transmission resources of the transmission channel corresponding to the security control layer are maintained, while the transmission resources of the media display layer and the status feedback layer are reduced.

[0007] Secondly, embodiments of the present invention provide a remote teaching data transmission system for industrial robots, comprising: A semantically aware data classifier is used to acquire remote teaching data to be transmitted, and divide the remote teaching data into security control layer data, status feedback layer data and media display layer data according to the business semantics of the remote teaching data, and map the data of different layers to multiple independent transmission channels respectively. An adaptive bandwidth detection and negotiation engine is used to obtain current network status parameters and the motion state of the industrial robot, determine the network quality level based on the current network status parameters, and determine the joint operation state based on the network quality level and the motion state. A hierarchical transmission scheduler is used to determine the transmission scheduling strategy and transmission resource allocation corresponding to each transmission channel based on the joint operating state; wherein, the priority of transmission resource allocation for the transmission channels corresponding to the security control layer, the status feedback layer, and the media presentation layer decreases sequentially; the hierarchical transmission scheduler is also used to update the transmission scheduling strategy corresponding to each transmission channel and adjust the transmission resources of each transmission channel in response to changes in the joint operating state; wherein, when transmission resources decrease, the transmission resources of the transmission channel corresponding to the security control layer are maintained, while the transmission resources of the media presentation layer and the status feedback layer are reduced; The intelligent compensation and fault tolerance module is used to receive the state feedback layer data and sort and store the state feedback layer data according to timestamps; detect whether there are lost data frames in the state feedback layer data; when a lost data frame is detected, use Kalman filtering to predict the lost data frame to obtain an interpolated data frame; fuse the interpolated data frame with the received state feedback layer data to obtain smooth rendering data; if the state feedback layer data is continuously lost for more than a preset duration threshold, a safety flag is triggered, the robot model animation is frozen, and a connection disconnection warning is issued.

[0008] The beneficial effects of this invention are as follows: Remote teaching data is divided into security control layer data, status feedback layer data, and media display layer data according to business semantics, and mapped to multiple independent transmission channels respectively. This isolates data of different security importance along the transmission path, reducing interference from large data volumes on security-related data. Furthermore, a joint operating state is determined based on current network status parameters and the industrial robot's motion state. The transmission scheduling strategy and resource allocation for each transmission channel are then determined according to this joint operating state, enabling transmission resource configuration to adapt to changes in both link quality and motion safety requirements. Since the priority of transmission resource allocation for the corresponding transmission channels of the security control layer, status feedback layer, and media display layer decreases sequentially, the transmission channel corresponding to the security control layer receives priority when transmission resources are limited, while the status feedback layer and media display layer are degraded in that order. This ensures basic resource guarantees for data transmission in the security control layer even when the link deteriorates. Meanwhile, when the joint operation status changes, the transmission scheduling strategy of each transmission channel is updated and the transmission resources are adjusted. When the transmission resources are reduced, the transmission resources of the corresponding transmission channel of the security control layer are maintained, while the transmission resources of the media presentation layer and the status feedback layer are reduced. This enables the entire transmission process to dynamically adjust with changes in network and motion status, reducing the risk of data transmission delay or loss in the security control layer caused by static resource configuration in weak network or motion status. Attached Figure Description

[0009] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0010] Figure 1 This is a flowchart illustrating a remote teaching data transmission method for industrial robots provided in an embodiment of the present invention. Figure 2 This is a schematic diagram of a sub-process of step S102 provided in an embodiment of the present invention; Figure 3 This is a schematic diagram of a sub-process of step S103 provided in an embodiment of the present invention; Figure 4 This is a schematic diagram of another sub-process of step S103 provided in an embodiment of the present invention; Figure 5 This is a schematic diagram of a sub-process of step S104 provided in an embodiment of the present invention; Figure 6 This is a schematic diagram of a sub-process of step S105 provided in an embodiment of the present invention; Figure 7This is another flowchart illustrating the remote teaching data transmission method for industrial robots provided in this embodiment of the invention. Figure 8 This is a schematic block diagram of an industrial robot remote teaching data transmission system provided in an embodiment of the present invention. Figure 9 A schematic block diagram of a computer device provided in an embodiment of the present invention; Figure 10 This is a schematic diagram of the overall architecture of the industrial robot remote teaching data transmission system provided in an embodiment of the present invention. Detailed Implementation

[0011] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0012] It should be understood that, when used in this specification and the appended claims, the terms "comprising" and "including" indicate the presence of the described features, integrals, steps, operations, elements and / or components, but do not exclude the presence or addition of one or more other features, integrals, steps, operations, elements, components and / or collections thereof.

[0013] It should also be understood that the terminology used in this specification is for the purpose of describing particular embodiments only and is not intended to limit the invention. As used in this specification and the appended claims, the singular forms “a,” “an,” and “the” are intended to include the plural forms unless the context clearly indicates otherwise.

[0014] It should also be further understood that the term "and / or" as used in this specification and the appended claims refers to any combination of one or more of the associated listed items and all possible combinations, and includes such combinations.

[0015] The industrial robot remote teaching data transmission method provided in this embodiment of the invention is applied to a remote teaching system; such as... Figure 10As shown, the remote teaching system comprises three parts: a remote teaching terminal 100, a cloud collaboration server 200, and an industrial robot body 300. The remote teaching terminal 100 is deployed on the operator's side, responsible for human-computer interaction, command acquisition, local preprocessing, network sensing, and image rendering. The cloud collaboration server 200 is deployed at an edge node or data center, responsible for data aggregation, mirror synchronization, security verification, and traffic distribution. The industrial robot body 300 is located at the factory site, responsible for action execution, high-frequency status reporting, and underlying safety protection. The three components communicate bidirectionally via wired or wireless networks (such as 5G / Wi-Fi / TSN Ethernet).

[0016] Based on the aforementioned industrial robot remote teaching data transmission system, such as Figure 1 As shown, Figure 1 This is a flowchart illustrating the remote teaching data transmission method for industrial robots provided in an embodiment of the present invention; the remote teaching data transmission method for industrial robots includes steps S101 to S105.

[0017] S101. Obtain the remote teaching data to be transmitted, the current network status parameters, and the motion status of the industrial robot; In step S101, the remote teaching data originates from three sources: the human-machine interface of the remote teaching terminal, the cloud collaboration server, and the industrial robot itself. Specifically, the remote teaching data from the remote teaching terminal includes operation events input by the operator via touchscreen, buttons, voice, etc., as well as visual data generated by media acquisition devices or graphics processing devices; the remote teaching data from the cloud collaboration server includes control data and relay data sent after security verification; and the remote teaching data from the industrial robot itself includes operational status data such as joint angles, end effector pose, torque, and error codes.

[0018] In step S101, the current network status parameters are obtained by reading network interface statistics and measuring end-to-end transmission quality, etc., and are used to reflect the link status between the remote teaching terminal and the peer device, including indicators such as available bandwidth, network jitter and packet loss rate.

[0019] In step S101, the motion state of the industrial robot can be obtained from the speed information and / or joint motion data reported by the industrial robot controller, which is used to distinguish whether the industrial robot is currently in an actual motion process.

[0020] S102. Based on the business semantics of the remote teaching data, divide it into security control layer data, status feedback layer data and media display layer data, and map the data of different layers to multiple independent transmission channels respectively. In step S102, the business semantics of remote teaching data refers to the function and safety criticality of the data in the remote teaching service. Safety control layer data carries instructions to change the motion state of the industrial robot; its data volume is relatively small, but its timeliness and reliability requirements are the highest. State feedback layer data carries telemetry information during the operation of the industrial robot; its data volume is moderate and exists in the form of a continuous high-frequency stream. Media display layer data carries visual reference content such as video streams and point clouds; its data volume is the largest, but its real-time requirements are relatively low. After the partitioning is completed, the data from different layers are mapped to multiple independent transmission channels. Each transmission channel has an independent protocol stack and buffer queue, and they do not share sending windows and retransmission queues, thus achieving business isolation at the transmission layer.

[0021] like Figure 2 As shown, step S102, which divides the remote teaching data into security control layer data, status feedback layer data, and media presentation layer data based on the business semantics, includes: S201. Perform semantic parsing on the remote teaching data to determine the data purpose, business event type, and data generation method of the remote teaching data; and proceed to steps S202, S203, or S204. S202. When remote teaching data is used to change the motion state of an industrial robot, and the business event type belongs to the preset safety control event type, the remote teaching data is classified as safety control layer data. S203. When remote teaching data is generated by robot-side equipment and used to characterize the operating state of industrial robots, the remote teaching data is divided into state feedback layer data. S204. When remote teaching data is generated by media acquisition equipment or graphics processing equipment and is used to provide a visual reference for remote teaching, the remote teaching data shall be divided into media presentation layer data.

[0022] In steps S201-S204, the semantic parsing process extracts information from the remote teaching data in three dimensions: data purpose, business event type, and data generation method. Data purpose identifies the data's functional positioning at the business level, such as changing the motion state of the industrial robot, characterizing the robot's operating state, or providing a visual reference for remote teaching. Business event type is obtained by identifying operational events. Preset safety control event types include operational events directly related to motion safety, such as emergency stop, enable switching, and single-step movement. Loss or delay of these events may cause safety accidents; therefore, their corresponding data is prioritized as safety control layer data and given the highest transmission priority at the source. Data generation method distinguishes the data's source device. Data generated by robot-side devices and used to characterize the industrial robot's operating state is classified as state feedback layer data; data generated by media acquisition devices or graphics processing devices and used to provide a visual reference for remote teaching is classified as media display layer data.

[0023] In practical implementation, a QoS tag (Quality of Service tag) can be attached to each data packet after segmentation. For example, Tag=0x01 identifies security control layer data, Tag=0x02 identifies status feedback layer data, and Tag=0x03 identifies media presentation layer data. This tag maps data from different layers to multiple independent transmission channels. This classification process is completed before data transmission, ensuring that each data item is assigned a priority attribute matching its business semantics before entering the network protocol stack. This avoids the additional processing delay introduced by judging data type during transmission scheduling, guaranteeing that security control layer data is identified and prioritized at the source.

[0024] S103. Determine the network quality level based on the current network status parameters, and determine the joint operation status based on the network quality level and the motion status; In step S103, the current network state parameters reflect link quality, while the industrial robot's motion state reflects the urgency of data transmission requirements for motion safety. When resource allocation is based solely on the network dimension, excessive transmission resources might be allocated to state feedback layer data and media display layer data when the industrial robot is stationary, even though the need for detailed observation of slow state changes is actually higher at this time. Conversely, considering only the motion dimension fails to address actual link conditions such as network congestion. Combining network quality level and motion state into a joint operating state simultaneously covers information from both dimensions, allowing for unified adjustments to the transmission scheduling strategies and resource allocation of subsequent transmission channels based on the joint operating state.

[0025] like Figure 3 As shown, step S103, which involves determining the network quality level based on the current network status parameters, includes: S301. Periodically send network probe data packets to the cloud collaboration server where the industrial robot is located, and calculate the current network status based on the response data packets corresponding to the network probe data packets; wherein, the current network status includes available bandwidth, network jitter and packet loss rate; and proceed to steps S302, S303 or S304. S302. When the available bandwidth is greater than the preset second bandwidth threshold, the network jitter is less than the preset jitter threshold, and the packet loss rate is less than or equal to the preset packet loss rate threshold, the network quality is determined to be Level 1. S303. When the available bandwidth is greater than the preset first bandwidth threshold and less than or equal to the second bandwidth threshold, or when the network jitter is greater than or equal to the preset jitter threshold, the network quality is determined to be level two. S304. When the available bandwidth is less than or equal to the first bandwidth threshold, or the packet loss rate is greater than the packet loss rate threshold, the network quality is determined to be level three. Among them, the first bandwidth threshold is less than the second bandwidth threshold, and the network quality corresponding to level 1, level 2 and level 3 decreases in that order.

[0026] In steps S301-S304, network probe data packets are sent by the remote teaching terminal to the cloud collaboration server at preset intervals (e.g., 500ms). These probe data packets can be designed as packets of varying sizes to segment and probe link throughput. Response data packets are returned by the peer device. Round-trip delay, network jitter, and packet loss rate are calculated by statistically analyzing the arrival of these response data packets. Available bandwidth is estimated from the temporal distribution of the response data packets using throughput estimation algorithms (such as those based on the BBR principle). When determining the network quality level, packet loss rate is used as a reliability criterion, network jitter as a stability criterion, and available bandwidth as a capacity criterion. When available bandwidth is greater than the second bandwidth threshold, network jitter is less than the jitter threshold, and packet loss rate is less than or equal to the packet loss rate threshold, it indicates sufficient link capacity, stable and reliable transmission, and is classified as Level 1. When available bandwidth is between the first and second bandwidth thresholds, or network jitter is greater than or equal to the jitter threshold, it indicates a decrease in link capacity or increased latency fluctuations, but no severe packet loss degradation has occurred, and is classified as Level 2. When available bandwidth is less than or equal to the first bandwidth threshold, or packet loss rate is greater than the packet loss rate threshold, it indicates severely insufficient link capacity or significantly deteriorated reliability, and is classified as Level 3. The three network quality levels decrease sequentially, covering the complete range from good link to severely deteriorated link.

[0027] Based on this, by periodically probing and combining the judgment of three indicators, the classification of network quality levels can reflect the degree of degradation of links in three different aspects: capacity, stability and reliability, so that subsequent transmission scheduling strategies can be adjusted for specific degradation types.

[0028] like Figure 4 As shown, step S103, which involves determining the joint operating state based on the network quality level and motion state, includes: S401. Based on the comparison between the industrial robot's movement speed and the preset speed threshold, determine whether the industrial robot is in motion mode or stationary mode. S402. Combine the network quality level with the motion mode or stationary mode to obtain the joint operating state.

[0029] In steps S401-S402, the industrial robot's movement speed can be obtained from the joint speed or end effector linear speed reported by the industrial robot controller. A preset speed threshold is used to distinguish whether the industrial robot is in actual motion. When the movement speed is greater than the preset speed threshold, it is determined to be in motion mode; when the movement speed is less than or equal to the preset speed threshold, it is determined to be in stationary mode. Motion mode and stationary mode have different data transmission requirements. In motion mode, the timeliness requirements for safety control layer data are higher, and the state feedback layer data needs to maintain a sufficient refresh rate to reflect pose changes during continuous motion. In stationary mode, the state variables of the industrial robot change slowly, and the refresh rate of the state feedback layer data can be appropriately reduced to save transmission resources. Meanwhile, the resolution and frame rate of the media display layer data can be maintained at a high level to meet the operator's requirements for image clarity during fine-tuning and static observation.

[0030] Based on this, by combining network quality levels with motion or stationary modes, joint operating states such as "Level 1 network quality and motion mode," "Level 2 network quality and stationary mode," and "Level 3 network quality and motion mode" are obtained. Through the above combinations, the joint operating state can simultaneously express information from two dimensions: link quality conditions and motion safety requirements, providing complete query conditions for subsequently querying the corresponding transmission scheduling strategy from the preset transmission strategy matrix.

[0031] S104. Determine the transmission scheduling strategy and transmission resource allocation for each transmission channel based on the joint operation status; among them, the priority of transmission resource allocation for the transmission channels corresponding to the security control layer, status feedback layer and media display layer decreases in that order. In step S104, the transmission scheduling strategy includes the transmission protocol, refresh frequency, encoding parameters, and scheduling method used by each transmission channel; transmission resource allocation refers to dividing the available transmission resources among the transmission channels. The decreasing priority of transmission resource allocation means that when transmission resources are insufficient to simultaneously meet the needs of all transmission channels, priority is given to the transmission resources of the channel corresponding to the safety control layer, followed by the transmission resources of the channel corresponding to the status feedback layer, and finally, the transmission resources of the channel corresponding to the media display layer are allocated. This priority order matches the safety criticality of the data at each layer. Safety control layer data relates to the motion safety of the industrial robot, status feedback layer data relates to the operator's perception and judgment of the industrial robot's operating status, and media display layer data mainly provides visual reference; even if downgraded, it will not directly affect motion safety.

[0032] like Figure 5 As shown, step S104 includes steps S501 to S506.

[0033] S501. Query the transmission policy corresponding to the joint operation state from the preset transmission policy matrix; and proceed to one of steps S502-S506; In step S501, the preset transmission strategy matrix is ​​a two-dimensional lookup table. The row dimension represents the network quality level, and the column dimension represents the motion mode or stationary mode. Each cell in the matrix corresponds to a transmission scheduling strategy configuration under a joint operating state. During execution, the joint operating state obtained in step S103 is used as the query condition to query the preset transmission strategy matrix for a transmission strategy that matches the joint operating state. Then, control is implemented on each transmission channel according to the query results.

[0034] S502. When the joint operation status is Level 1 network quality and in motion mode, the control security control layer data is transmitted using the User Datagram Protocol with retransmission mechanism, the control status feedback layer data is transmitted according to the first refresh frequency, and the control media display layer data is transmitted according to the first resolution, the first frame rate, and the first encoding bit rate. In step S502, under Level 1 network quality and motion mode, the link is in good condition, and each layer operates according to preset high specifications. The safety control layer data is transmitted using a User Datagram Protocol (UDP) with a retransmission mechanism. This leverages the connectionless nature of UDP to achieve low transmission latency, while the retransmission mechanism compensates for the inherent unreliability of UDP, resulting in minimal retransmission overhead when the link is in good condition. The status feedback layer data is transmitted at a first refresh rate (e.g., 100Hz) to meet the operator's need for continuous perception of the industrial robot's pose during motion. The media display layer data is transmitted at a first resolution, first frame rate, and first encoding bitrate (e.g., 4K resolution, 60 frames per second) to provide high-quality visual reference.

[0035] S503. When the joint operation status is Level 1 network quality and in static mode, the control security control layer data is transmitted using the User Datagram Protocol with retransmission mechanism, the control status feedback layer data is transmitted at a second refresh frequency lower than the first refresh frequency, and the control media display layer data is transmitted at a second resolution not lower than the first resolution, a second frame rate not lower than the first frame rate, and a second coding rate not lower than the first coding rate. In step S502, under Level 1 network quality and in static mode, the transmission control method for security control layer data remains consistent with that in motion mode. This is because even in static mode, commands such as emergency stop and enable must still be delivered reliably with low latency. Status feedback layer data is transmitted at a second refresh rate (e.g., 10-20Hz) lower than the first refresh rate, because status changes are slow in static mode, and reducing the refresh rate frees up transmission resources. Media display layer data is transmitted at a second resolution no lower than the first resolution, a second frame rate no lower than the first frame rate, and a second encoding bitrate no lower than the first encoding bitrate, maintaining a level above the first resolution, first frame rate, and first encoding bitrate. This is because operators require a clearer image for detailed observation in static debugging scenarios, and when link conditions are good, the saved transmission resources can be allocated to media display layer data.

[0036] S504. When the joint operation status is Level 2 network quality and in motion mode, the corresponding transmission channel of the control security control layer enters the exclusive scheduling mode, the control status feedback layer data is transmitted at a third refresh frequency lower than the first refresh frequency and forward error correction and / or interpolation compensation is enabled, and the control media display layer data is transmitted at a third resolution lower than the first resolution, a third frame rate lower than the first frame rate and a third coding rate lower than the first coding rate. In step S504, under Level 2 network quality and motion mode, the link quality degrades, and the corresponding transmission channel of the security control layer enters exclusive scheduling mode. Exclusive scheduling mode means that the transmission channel corresponding to the security control layer obtains exclusive access to the processor during the scheduling cycle, and data from other transmission channels does not compete for it, thus avoiding latency jitter introduced by software scheduling. In specific implementations, the transmission channel corresponding to the security control layer can be bound to the real-time core in a heterogeneous processor, and interrupt affinity can be configured so that when security control layer data arrives, the interrupt service routine of the real-time core is directly triggered, bypassing the network protocol stack and scheduling queue of the general operating system kernel. Status feedback layer data is transmitted at a third refresh frequency (e.g., 10-20Hz) lower than the first refresh frequency, and forward error correction and / or interpolation compensation are enabled to address data loss caused by degraded link quality. Forward error correction adds redundant coded data at the sending end, enabling the receiving end to recover the original data when some packets are lost; interpolation compensation predicts and estimates lost data frames at the receiving end. Media presentation layer data is transmitted at a third resolution (e.g., 1080p) lower than the first resolution, a third frame rate (e.g., 15-20 FPS) lower than the first frame rate, and a third coding bitrate lower than the first coding bitrate, in order to match the reduced link capacity by reducing the amount of data.

[0037] S505. When the joint operation status is Level 2 network quality and static mode, the corresponding transmission channel of the control security control layer enters the exclusive scheduling mode, the control status feedback layer data is transmitted at a fourth refresh frequency lower than the third refresh frequency, and the control media display layer data is transmitted at a fourth resolution lower than the third resolution, a fourth frame rate lower than the third frame rate, and a fourth encoding rate lower than the third encoding bit rate. In step S505, under Level 2 network quality and static mode, the corresponding transmission channel of the safety control layer also enters exclusive scheduling mode to ensure that the transmission of safety control layer data is not affected by data from other layers. State feedback layer data is transmitted at a fourth refresh rate (e.g., 5-10Hz) lower than the third refresh rate, further reducing the refresh rate compared to Level 2 network quality and motion mode. This is because the industrial robot's state changes slowly in static mode, and a lower refresh rate can still maintain basic pose visibility. Media display layer data is transmitted at a fourth resolution (e.g., 720p), a fourth frame rate (e.g., 10FPS), and a fourth encoding bitrate (lower than the third encoding bitrate), further compressing the bandwidth usage of media display layer data.

[0038] S506. When the joint operation status is Level 3 network quality and in motion or static mode, the corresponding transmission channel of the control safety control layer enters hard real-time direct mode, and the control status feedback layer data can only transmit key pose data and / or heartbeat data, while the transmission of control media display layer data is suspended. In step S506, under Level 3 network quality conditions, regardless of whether it's in motion or stationary mode, the corresponding transmission channel of the safety control layer enters hard real-time direct access mode. Hard real-time direct access mode goes a step further than exclusive scheduling mode, completely bypassing the general protocol stack on top of exclusive scheduling. Safety control layer data is sent directly to the network interface via hardware interrupt pass-through in the form of simplified user datagram protocol packets. Status feedback layer data can only transmit key pose data and / or heartbeat data. Key pose data provides basic position information for the industrial robot's end effector, and heartbeat data is used to confirm connection survival. All other non-critical telemetry data is discarded. Transmission of media display layer data is paused, and the released transmission resources are used entirely to ensure the transmission of critical parts of the safety control layer data and status feedback layer data. During the transmission pause, the remote teaching terminal's display interface can retain the last static frame and display a network restricted message to inform the operator of the current link status.

[0039] Based on this, steps S501-S506 above configure different transmission scheduling strategies for different joint operation states, enabling the protocol selection, refresh frequency, and encoding parameters of each transmission channel to dynamically adjust according to changes in link quality and motion status. When the link is good, bandwidth capacity is fully utilized; when the link deteriorates, priority is given to ensuring the transmission of security control layer data. Simultaneously, by gradually reducing the transmission specifications of status feedback layer data and media presentation layer data to match available transmission resources, the problem of security control layer data being squeezed out by media presentation layer data when the link deteriorates, as seen in traditional static configuration schemes, is avoided.

[0040] S105. In response to changes in the joint operation status, update the transmission scheduling strategy corresponding to each transmission channel and adjust the transmission resources of each transmission channel; wherein, when the transmission resources are reduced, maintain the transmission resources of the transmission channel corresponding to the security control layer, and reduce the transmission resources of the media display layer and the status feedback layer. In step S105, the reasons for changes in the joint operating state include changes in network quality level and the industrial robot switching from motion mode to stationary mode or vice versa. When a change in the joint operating state from one combination to another is detected, the preset transmission strategy matrix needs to be queried again to obtain the changed target transmission strategy, and the transmission scheduling strategy and transmission resources of each transmission channel are adjusted according to the target transmission strategy. When transmission resources decrease, the transmission resources of the transmission channel corresponding to the security control layer are kept constant, the transmission resources of the transmission channel corresponding to the media display layer are reduced first, and then the transmission resources of the transmission channel corresponding to the status feedback layer are reduced. In this way, through the responsive update mechanism, the transmission scheduling strategy can switch in a timely manner according to changes in link status and motion state, avoiding the disconnect between transmission resource configuration and actual operating conditions. When transmission resources decrease, priority is given to protecting the transmission channel corresponding to the security control layer, ensuring that the transmission of security control layer data is not affected during link deterioration.

[0041] like Figure 6 As shown, step S105 includes: S601. When the joint operation state changes from one combination to another, query the target transmission strategy corresponding to the changed joint operation state from the preset transmission strategy matrix; and proceed to step S602 or S603. S602. If the network quality level in the target transmission strategy is lower than the network quality level before the change, the transmission resources of the corresponding transmission channels shall be reduced in the order of media presentation layer and status feedback layer, and the transmission resources of the corresponding transmission channels of security control layer shall be kept at no less than the preset minimum guaranteed bandwidth. S603. If the network quality level in the target transmission strategy is higher than the network quality level before the change, the transmission resources of the corresponding transmission channel shall be increased in the order of state feedback layer and media presentation layer. Specifically, when the industrial robot is in motion mode, the degradation lower limit of the corresponding transmission channel in the state feedback layer during the reduction process is higher than the degradation lower limit when the industrial robot is in stationary mode.

[0042] In the scheme of steps S601-S603, the detection of changes in the joint operating state can be a change in network quality level or a switch between motion mode and stationary mode. When a change in the joint operating state from one combination to another is detected, the target transmission policy is queried from the preset transmission policy matrix using the changed joint operating state as the query condition. If the network quality level in the target transmission policy is lower than the network quality level before the change, it indicates that the link conditions have deteriorated and transmission resources need to be reduced. The reduction order is media presentation layer first, then state feedback layer. The reason for reducing the transmission resources of the transmission channel corresponding to the media presentation layer first is that the data volume of the media presentation layer is the largest, the transmission resources released after reduction are the largest, and the media presentation layer data does not involve motion security, so the reduction has the least impact. When the transmission resources of the transmission channel corresponding to the media presentation layer have been reduced to the minimum specification and still cannot meet the requirements, the transmission resources of the transmission channel corresponding to the state feedback layer are then reduced. The transmission resources of the transmission channel corresponding to the security control layer are kept at no less than the preset minimum guaranteed bandwidth throughout the entire reduction process to ensure that the security control layer data always has basic transmission capabilities. If the network quality level in the target transmission strategy is higher than the network quality level before the change, it indicates that the link conditions have improved, and transmission resources can be increased. The increase order is: first the status feedback layer, then the media display layer. Prioritize restoring the resolution and refresh rate of the status feedback layer data, enabling the operator to more accurately perceive the operating status of the industrial robot. Then restore the transmission specifications of the media display layer data to avoid the media display layer data prematurely occupying the newly released transmission resources. When the industrial robot is in motion mode, the degradation lower limit of the corresponding transmission channel of the status feedback layer during the reduction process is higher than the degradation lower limit when the industrial robot is in stationary mode. The degradation lower limit refers to the lowest refresh rate or minimum encoding specification that the corresponding transmission channel of the status feedback layer is allowed to be reduced to during the reduction process. In motion mode, the status feedback layer data maintains a higher degradation lower limit because during motion, the operator needs a higher frequency of status feedback layer data to perceive the movement trend and pose changes of the industrial robot. If the refresh rate of the status feedback layer data is too low, the operator will not be able to accurately judge the current state of the industrial robot.

[0043] Based on this, when the joint operation status changes, the reduction and increase mechanism is provided to make the adjustment process of transmission resources directional and sequential, avoiding the problem of disorderly competition among transmission channels when adjusting transmission resources, while ensuring that the data of the security control layer always obtains basic transmission resource guarantees during the adjustment process.

[0044] In summary, in the scheme of steps S101-S105 of the present invention, remote teaching data is divided into security control layer data, status feedback layer data, and media display layer data according to business semantics, and mapped to multiple independent transmission channels respectively. This isolates data of different security importance from each other on the transmission path, reducing the interference of large data volumes on security-related data. Based on this, a joint operating state is determined jointly according to the current network status parameters and the motion state of the industrial robot. The transmission scheduling strategy and transmission resource allocation for each transmission channel are then determined based on the joint operating state, enabling the transmission resource configuration to adapt to changes in link quality and motion safety requirements simultaneously. Since the priority of transmission resource allocation for the corresponding transmission channels of the security control layer, status feedback layer, and media display layer decreases sequentially, when transmission resources are limited, the transmission channel corresponding to the security control layer receives priority in obtaining transmission resources, while the status feedback layer and media display layer are degraded in turn. This ensures basic resource guarantees for data transmission of the security control layer even when the link deteriorates. Meanwhile, when the joint operation status changes, the transmission scheduling strategy of each transmission channel is updated and the transmission resources are adjusted. When the transmission resources are reduced, the transmission resources of the corresponding transmission channel of the security control layer are maintained, while the transmission resources of the media presentation layer and the status feedback layer are reduced. This enables the entire transmission process to dynamically adjust with changes in network and motion status, reducing the risk of data transmission delay or loss in the security control layer caused by static resource configuration in weak network or motion status.

[0045] like Figure 7 As shown, the industrial robot remote teaching data transmission method of the present invention further includes: S701. Receive status feedback layer data and sort and store the status feedback layer data according to timestamp; S702. Detect whether there are missing data frames in the status feedback layer data; S703. When a lost data frame is detected, Kalman filtering is used to predict the lost data frame and obtain the interpolated data frame. S704. The interpolated data frame is fused with the received state feedback layer data to obtain smooth rendering data. S705. If the continuous loss of status feedback layer data exceeds the preset time threshold, the safety flag will be triggered, the robot model animation will be frozen, and a connection disconnection warning will be issued.

[0046] In steps S701-S705, after the state feedback layer data arrives at the remote teaching terminal, it is first sorted and stored according to timestamps to eliminate possible out-of-order data during network transmission. Since the state feedback layer data is transmitted through an independent transmission channel, and forward error correction and / or interpolation compensation may be enabled when network quality deteriorates, data frame loss may still occur at the receiving end. After sorting and storage, the presence of lost data frames is determined by checking whether the interval between timestamps of adjacent data frames exceeds the normal reporting cycle, or by checking for discontinuities in sequence numbers. When a lost data frame is detected, a Kalman filter is used to predict it. The prediction process uses joint angles and angular velocities from the state feedback layer data as state vectors, and uses valid data frames before and after the lost data frame as observations. The interpolated data frame corresponding to the lost data frame is obtained through the prediction and update equations of the Kalman filter. After data compensation, the interpolated data frame is merged with the original received data in timestamp order, providing a continuous and complete data source for the robot model rendering on the remote teaching terminal, avoiding animation stuttering and jump issues.

[0047] In addition, when the network connection quality deteriorates significantly and the duration of continuous data frame loss exceeds a preset threshold, it indicates that the current network environment can no longer support the basic interactive needs of remote teaching. At this time, triggering the safety flag can freeze the robot model animation in time to avoid incorrect poses due to invalid data rendering. At the same time, a connection disconnection warning is issued to remind the teaching operator to check the network connection status in time to avoid production safety risks caused by teaching command deviations due to incorrect model poses.

[0048] This invention also provides an industrial robot remote teaching data transmission system, which is used to execute any embodiment of the aforementioned industrial robot remote teaching data transmission method. Specifically, please refer to... Figure 8 , Figure 8 This is a schematic block diagram of the industrial robot remote teaching data transmission system provided in an embodiment of the present invention.

[0049] like Figure 8 As shown, the industrial robot remote teaching data transmission system 800 includes: a semantic data classifier 801, an adaptive bandwidth detection and negotiation engine 802, a hierarchical scheduler 803, and an intelligent compensation and fault tolerance module 804.

[0050] The semantically aware data classifier 801 is used to acquire the remote teaching data to be transmitted, divide it into security control layer data, status feedback layer data and media display layer data according to the business semantics of the remote teaching data, and map the data of different layers to multiple independent transmission channels respectively. The adaptive bandwidth detection and negotiation engine 802 is used to obtain the current network status parameters and the motion state of the industrial robot, determine the network quality level based on the current network status parameters, and determine the joint operation state based on the network quality level and motion state. The hierarchical transmission scheduler 803 is used to determine the transmission scheduling strategy corresponding to each transmission channel based on the joint operation status, and to allocate transmission resources to each transmission channel according to the transmission scheduling strategy; wherein, the priority of transmission resource allocation for the transmission channels corresponding to the security control layer, the status feedback layer, and the media presentation layer decreases in that order; the hierarchical transmission scheduler 803 is also used to update the transmission scheduling strategy corresponding to each transmission channel and adjust the transmission resources of each transmission channel in response to changes in the joint operation status; wherein, when the transmission resources decrease, the transmission resources of the transmission channel corresponding to the security control layer are maintained, while the transmission resources of the media presentation layer and the status feedback layer are reduced; The intelligent compensation and fault tolerance module 804 is used to receive state feedback layer data and sort and store the state feedback layer data according to timestamps; detect whether there are lost data frames in the state feedback layer data; when a lost data frame is detected, Kalman filtering is used to predict the lost data frame to obtain an interpolated data frame; the interpolated data frame is fused with the received state feedback layer data to obtain smooth rendering data; if the continuous loss of state feedback layer data exceeds a preset duration threshold, a safety flag is triggered, the robot model animation is frozen, and a connection disconnection warning is issued.

[0051] This system categorizes remote teaching data into three layers based on business semantics: safety control layer data, status feedback layer data, and media display layer data. These layers are then mapped to multiple independent transmission channels, isolating data of varying safety importance along the transmission path and reducing interference from large data volumes on safety-related data. Furthermore, the system determines the joint operating state based on current network status parameters and the industrial robot's motion state. Based on this joint operating state, it determines the transmission scheduling strategy and resource allocation for each transmission channel, enabling the transmission resource configuration to adapt to changes in both link quality and motion safety requirements. Since the priority of transmission resource allocation decreases sequentially for the safety control layer, status feedback layer, and media display layer, the safety control layer transmission channel receives priority when transmission resources are limited, while the status feedback layer and media display layer receive priority in that order. This ensures that basic resource guarantees for safety control layer data transmission are maintained even when the link deteriorates. Meanwhile, when the joint operation status changes, the transmission scheduling strategy of each transmission channel is updated and the transmission resources are adjusted. When the transmission resources are reduced, the transmission resources of the corresponding transmission channel of the security control layer are maintained, while the transmission resources of the media presentation layer and the status feedback layer are reduced. This enables the entire transmission process to dynamically adjust with changes in network and motion status, reducing the risk of data transmission delay or loss in the security control layer caused by static resource configuration in weak network or motion status.

[0052] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working process of the above-described apparatus and unit can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here.

[0053] The aforementioned industrial robot remote teaching data transmission system 800 can be implemented as a computer program, which can be used in, for example... Figure 9 It runs on the computer device shown.

[0054] Please see Figure 9 , Figure 9 This is a schematic block diagram of a computer device provided in an embodiment of the present invention. The computer device 900 is a server, which can be a standalone server or a server cluster composed of multiple servers.

[0055] See Figure 9 The computer device 900 includes a processor 902, a memory, and a network interface 905 connected via a system bus 901. The memory may include a non-volatile storage medium 903 and internal memory 904.

[0056] The non-volatile storage medium 903 can store an operating system 9031 and a computer program 9032. When the computer program 9032 is executed, it enables the processor 902 to execute a remote teaching data transmission method for industrial robots.

[0057] The processor 902 provides computing and control capabilities to support the operation of the entire computer device 900.

[0058] The internal memory 904 provides an environment for the operation of the computer program 9032 in the non-volatile storage medium 903. When the computer program 9032 is executed by the processor 902, the processor 902 can execute the industrial robot remote teaching data transmission method.

[0059] The network interface 905 is used for network communication, such as providing data transmission. Those skilled in the art will understand that... Figure 9 The structure shown is merely a block diagram of a portion of the structure related to the present invention and does not constitute a limitation on the computer device 900 to which the present invention is applied. The specific computer device 900 may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0060] Those skilled in the art will understand that Figure 9 The embodiments of the computer device shown do not constitute a limitation on the specific configuration of the computer device. In other embodiments, the computer device may include more or fewer components than illustrated, or combine certain components, or have different component arrangements. For example, in some embodiments, the computer device may include only memory and a processor. In such embodiments, the structure and function of the memory and processor are different from those shown. Figure 9 The embodiments shown are consistent and will not be described again here.

[0061] It should be understood that, in this embodiment of the invention, the processor 902 may be a Central Processing Unit (CPU), or it may be other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or any conventional processor.

[0062] In another embodiment of the invention, a computer-readable storage medium is provided. This computer-readable storage medium may be a non-volatile computer-readable storage medium. The computer-readable storage medium stores a computer program, wherein the computer program, when executed by a processor, implements the industrial robot remote teaching data transmission method of the embodiments of the present invention.

[0063] The storage medium is a physical, non-transient storage medium, such as a USB flash drive, external hard drive, read-only memory (ROM), magnetic disk, or optical disk, etc., which are all physical storage media capable of storing program code.

[0064] Those skilled in the art will understand that, for the sake of convenience and brevity, the specific working process of the system and modules described above can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here.

[0065] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any person skilled in the art can easily conceive of various equivalent modifications or substitutions within the technical scope disclosed in the present invention, and these modifications or substitutions should all be covered within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A method for remote teaching data transmission for industrial robots, characterized in that, include: Acquire the remote teaching data to be transmitted, the current network status parameters, and the motion status of the industrial robot; Based on the business semantics of the remote teaching data, it is divided into security control layer data, status feedback layer data and media display layer data, and the data of different layers are mapped to multiple independent transmission channels respectively. The network quality level is determined based on the current network status parameters, and the joint operation status is determined based on the network quality level and the motion status. Based on the joint operation status, the transmission scheduling strategy and transmission resource allocation corresponding to each transmission channel are determined; wherein, the priority of transmission resource allocation for the transmission channels corresponding to the security control layer, status feedback layer and media presentation layer decreases in that order. In response to a change in the joint operation status, the transmission scheduling strategy corresponding to each transmission channel is updated, and the transmission resources of each transmission channel are adjusted; wherein, when the transmission resources decrease, the transmission resources of the transmission channel corresponding to the security control layer are maintained, while the transmission resources of the media display layer and the status feedback layer are reduced.

2. The industrial robot remote teaching data transmission method according to claim 1, characterized in that, Based on the business semantics of the remote teaching data, it is divided into security control layer data, status feedback layer data, and media presentation layer data, including: Perform semantic parsing on the remote teaching data to determine the data purpose, business event type, and data generation method of the remote teaching data; When the remote teaching data is used to change the motion state of the industrial robot, and the business event type belongs to the preset safety control event type, the remote teaching data is divided into the safety control layer data. When the remote teaching data is generated by the robot-side device and used to characterize the operating state of the industrial robot, the remote teaching data is divided into the state feedback layer data. When the remote teaching data is generated by a media acquisition device or a graphics processing device and is used to provide a visual reference for remote teaching, the remote teaching data is divided into the media presentation layer data.

3. The industrial robot remote teaching data transmission method according to claim 1, characterized in that, Determining the network quality level based on the current network status parameters includes: Network probe data packets are periodically sent to the cloud collaboration server where the industrial robot is located, and the current network status is calculated based on the response data packets corresponding to the network probe data packets; wherein, the current network status includes available bandwidth, network jitter and packet loss rate; When the available bandwidth is greater than a preset second bandwidth threshold, the network jitter is less than a preset jitter threshold, and the packet loss rate is less than or equal to a preset packet loss rate threshold, the network quality is determined to be Level 1. When the available bandwidth is greater than a preset first bandwidth threshold and less than or equal to a second bandwidth threshold, or when the network jitter is greater than or equal to the preset jitter threshold, the network quality is determined to be level two. When the available bandwidth is less than or equal to the first bandwidth threshold, or the packet loss rate is greater than the packet loss rate threshold, the network quality is determined to be level three. Wherein, the first bandwidth threshold is less than the second bandwidth threshold, and the network quality corresponding to the first, second and third levels decreases sequentially.

4. The industrial robot remote teaching data transmission method according to claim 3, characterized in that, Determining the joint operation status based on the network quality level and the motion status includes: Based on the comparison between the industrial robot's movement speed and a preset speed threshold, it is determined whether the industrial robot is in motion mode or stationary mode. The network quality level is combined with the motion mode or the stationary mode to obtain the joint operating state.

5. The industrial robot remote teaching data transmission method according to claim 4, characterized in that, Based on the joint operation status, the transmission scheduling strategy and transmission resource allocation corresponding to each transmission channel are determined, including: Query the transmission strategy corresponding to the joint operation state from the preset transmission strategy matrix; When the joint operation state is at level 1 network quality and in motion mode, the security control layer data is controlled to be transmitted using the User Datagram Protocol with retransmission mechanism, the status feedback layer data is controlled to be transmitted according to the first refresh frequency, and the media display layer data is controlled to be transmitted according to the first resolution, the first frame rate and the first encoding bit rate. When the joint operation state is at level 1 network quality and in static mode, the security control layer data is controlled to be transmitted using the User Datagram Protocol with retransmission mechanism, the status feedback layer data is controlled to be transmitted at a second refresh frequency lower than the first refresh frequency, and the media presentation layer data is controlled to be transmitted at a second resolution not lower than the first resolution, a second frame rate not lower than the first frame rate, and a second encoding bitrate not lower than the first encoding bitrate.

6. The industrial robot remote teaching data transmission method according to claim 5, characterized in that, Based on the joint operation status, the transmission scheduling strategy and transmission resource allocation corresponding to each transmission channel are determined, including: When the joint operation state is at level 2 network quality and in motion mode, the corresponding transmission channel of the security control layer is controlled to enter exclusive scheduling mode, the data of the status feedback layer is controlled to be transmitted at a third refresh frequency lower than the first refresh frequency and forward error correction and / or interpolation compensation is enabled, and the data of the media presentation layer is controlled to be transmitted at a third resolution lower than the first resolution, a third frame rate lower than the first frame rate and a third coding rate lower than the first coding rate. When the joint operation state is at level 2 network quality and in static mode, the corresponding transmission channel of the security control layer is controlled to enter exclusive scheduling mode, the data of the status feedback layer is controlled to be transmitted at a fourth refresh frequency lower than the third refresh frequency, and the data of the media display layer is controlled to be transmitted at a fourth resolution lower than the third resolution, a fourth frame rate lower than the third frame rate, and a fourth encoding bitrate lower than the third encoding bitrate.

7. The industrial robot remote teaching data transmission method according to claim 6, characterized in that, Based on the joint operation status, the transmission scheduling strategy and transmission resource allocation corresponding to each transmission channel are determined, including: When the joint operation status is a level 3 network quality and in motion or static mode, the corresponding transmission channel of the security control layer is controlled to enter hard real-time direct mode, the status feedback layer data can only transmit key pose data and / or heartbeat data, and the transmission of the media display layer data is paused.

8. The industrial robot remote teaching data transmission method according to claim 1, characterized in that, In response to a change in the joint operation status, the transmission scheduling strategy corresponding to each transmission channel is updated, and the transmission resources of each transmission channel are adjusted, including: When the joint operation state changes from one combination to another, the target transmission strategy corresponding to the changed joint operation state is queried from the preset transmission strategy matrix. If the network quality level in the target transmission strategy is lower than the network quality level before the change, the transmission resources of the corresponding transmission channels are reduced in the order of the media presentation layer and the status feedback layer, while the transmission resources of the corresponding transmission channel of the security control layer are kept at no less than the preset minimum guaranteed bandwidth. If the network quality level in the target transmission strategy is higher than the network quality level before the change, then the transmission resources of the corresponding transmission channel are increased sequentially in the order of the status feedback layer and the media presentation layer. Specifically, when the industrial robot is in motion mode, the degradation lower limit of the corresponding transmission channel of the state feedback layer during the reduction process is higher than the degradation lower limit when the industrial robot is in stationary mode.

9. The industrial robot remote teaching data transmission method according to claim 1, characterized in that, Also includes: Receive the status feedback layer data and sort and store the status feedback layer data according to timestamp; Detect whether there are any missing data frames in the state feedback layer data; When a lost data frame is detected, the lost data frame is predicted using Kalman filtering to obtain an interpolated data frame. The interpolated data frame is fused with the received state feedback layer data to obtain smooth rendering data; If the state feedback layer data is continuously lost for more than a preset time threshold, a safety flag is triggered, the robot model animation is frozen, and a connection disconnection warning is issued.

10. A remote teaching data transmission system for industrial robots, characterized in that, include: A semantically aware data classifier is used to acquire remote teaching data to be transmitted, and divide the remote teaching data into security control layer data, status feedback layer data and media display layer data according to the business semantics of the remote teaching data, and map the data of different layers to multiple independent transmission channels respectively. An adaptive bandwidth detection and negotiation engine is used to obtain current network status parameters and the motion state of the industrial robot, determine the network quality level based on the current network status parameters, and determine the joint operation state based on the network quality level and the motion state. A hierarchical transmission scheduler is used to determine the transmission scheduling strategy and transmission resource allocation corresponding to each transmission channel based on the joint operating state; wherein, the priority of transmission resource allocation for the transmission channels corresponding to the security control layer, the status feedback layer, and the media presentation layer decreases sequentially; the hierarchical transmission scheduler is also used to update the transmission scheduling strategy corresponding to each transmission channel and adjust the transmission resources of each transmission channel in response to changes in the joint operating state; wherein, when transmission resources decrease, the transmission resources of the transmission channel corresponding to the security control layer are maintained, while the transmission resources of the media presentation layer and the status feedback layer are reduced; The intelligent compensation and fault tolerance module is used to receive the state feedback layer data and sort and store the state feedback layer data according to timestamps; detect whether there are lost data frames in the state feedback layer data; when a lost data frame is detected, use Kalman filtering to predict the lost data frame to obtain an interpolated data frame; fuse the interpolated data frame with the received state feedback layer data to obtain smooth rendering data; if the state feedback layer data is continuously lost for more than a preset duration threshold, a safety flag is triggered, the robot model animation is frozen, and a connection disconnection warning is issued.

Images