A robot quick-change load communication protocol dynamic negotiation method and system

Abstract

This application discloses a method and system for dynamic negotiation of a communication protocol for robot quick-change payloads, relating to the field of robot intelligent control technology. The method includes: detecting payload loading events at the robot's end-effector quick-change interface; upon detecting the payload loading event, controlling the quick-change interface to enter a low-voltage interaction mode, sending random seed data to the payload, and receiving response data generated by the payload based on the random seed data; generating a payload digital gene to characterize the payload's communication capabilities and interface attributes; determining the protocol family set corresponding to the target payload based on the payload digital gene; generating a protocol negotiation strategy based on the protocol family set, and controlling the robot's main control terminal to perform protocol negotiation with the target payload; establishing a corresponding communication connection based on the protocol negotiation result; and, after successful establishment of the communication connection, controlling the quick-change interface to provide power to the target payload. This invention achieves plug-and-play, secure, efficient, and intelligent dynamic negotiation of communication protocols.

Description

Technical Field

[0001] This application relates to the field of robot intelligent control technology, and in particular to a method and system for dynamic negotiation of a robot fast load changing communication protocol. Background Technology

[0002] With the continuous expansion of application scenarios for industrial and service robots, robot end effectors are gradually showing a trend towards multi-functionality and modularity. In order to improve the efficiency and task adaptability of robot operations, quick-change payload technology is widely used in robot end-effector interface systems, enabling robots to quickly change different types of payload modules according to different task requirements, such as vision sensors, force control tools, inspection equipment, and actuators.

[0003] In existing technologies, quick-change payloads typically achieve rapid connection through standardized mechanical and electrical interfaces. Their electrical communication methods often rely on preset fixed communication protocols or manually configured protocol parameters, such as CAN, RS485, Ethernet / IP, or Modbus. In practical applications, payload devices from different manufacturers or of different models often employ different communication protocols and data formats. This necessitates manual configuration, protocol adaptation, or pre-installation of multi-protocol compatible modules in the robot's main control system after payload replacement, increasing system complexity and deployment costs.

[0004] Furthermore, existing fast-swap load systems typically supply power directly to the mains during the initial equipment connection phase, lacking a pre-verification mechanism for load identity and communication capabilities. When abnormal loads or incompatible devices are connected, it may lead to communication failures, electrical conflicts, or even equipment damage, posing certain safety risks.

[0005] Therefore, how to achieve secure and reliable identity and capability identification in the early stages of payload access, and how to complete communication capability verification and dynamic protocol negotiation under low power or secure interaction conditions, has become a technical problem that urgently needs to be solved in this field. Summary of the Invention

[0006] This application provides a method and system for dynamic negotiation of communication protocols for robot fast load changing, in order to solve the problems of difficulty in adapting heterogeneous load protocols, low security, and high power supply risk in the prior art, and to realize plug-and-play, safe, efficient, and intelligent dynamic negotiation of communication protocols.

[0007] This application provides the following solution: According to a first aspect, a method for dynamic negotiation of a robot quick-change payload communication protocol is provided. The method includes: detecting a payload loading event at a quick-change interface of the robot end effector; after detecting the payload loading event, controlling the quick-change interface to enter a low-voltage interaction mode, sending random seed data to the payload, and receiving response data generated by the payload based on the random seed data; extracting payload identity features, interface features, and functional features based on the response data, and generating a payload digital gene to characterize the payload's communication capabilities and interface attributes; determining a protocol family set corresponding to the target payload based on the payload digital gene; generating a protocol negotiation strategy based on the protocol family set, and controlling the robot master control terminal to perform protocol negotiation with the target payload; establishing a corresponding communication connection based on the protocol negotiation result, and after the communication connection is successfully established, controlling the quick-change interface to provide operating power to the target payload.

[0008] According to one achievable method in an embodiment of this application, sending random seed data to the payload and receiving response data generated by the payload based on the random seed data includes: generating random seed data corresponding to the current mounting event; sending the random seed data to the payload through a low-voltage interaction channel; and receiving response data generated by the payload based on the random seed data and preset payload identification parameters. The response data includes payload identification response information, interface capability response information, and functional capability response information, and the payload dynamically reconstructs the arrangement order and encoding format of the payload identification response information, the interface capability response information, and the functional capability response information according to the random seed data.

[0009] According to one achievable method in this application embodiment, generating random seed data corresponding to the current mounting event includes: acquiring mounting trigger time information, mechanical locking state information, and interface contact state information at the robot's end effector quick-change interface; collecting current environmental interference parameters, including electromagnetic noise intensity and power supply transient fluctuation information; fusing and encoding the mounting trigger time information, the mechanical locking state information, the interface contact state information, and the environmental interference parameters to generate a mounting event state vector; and performing nonlinear mapping processing on the mounting event state vector to generate random seed data corresponding to the current mounting event.

[0010] According to one achievable method in this application embodiment, the step of extracting payload identity features, interface features, and functional features from the response data and generating a payload digital gene to characterize the payload's communication capabilities and interface attributes includes: extracting payload identity information from the response data; obtaining the physical interface type, power supply level, and data transmission mode corresponding to the payload; obtaining the functional category and functional parameters corresponding to the payload; and encoding and fusing the payload identity information, the physical interface type, the power supply level, the data transmission mode, the functional category, and the functional parameters to generate a corresponding payload digital gene.

[0011] According to one achievable method in an embodiment of this application, determining the protocol family set corresponding to the target payload based on the payload digital gene includes: acquiring a pre-established digital gene protocol family mapping relationship library; calculating the gene similarity between the payload digital gene and each historical digital gene in the digital gene protocol family mapping relationship library; and determining the target protocol family set and the corresponding protocol priority based on the gene similarity.

[0012] According to one achievable method in an embodiment of this application, generating a protocol negotiation strategy based on the protocol family set includes: obtaining protocol feature parameters corresponding to each candidate protocol in the protocol family set; generating a candidate protocol negotiation sequence by combining the protocol priority corresponding to each candidate protocol and the protocol feature parameters; allocating protocol detection resources according to the protocol priority corresponding to each candidate protocol, and performing protocol detection according to the candidate protocol negotiation sequence; and generating a target protocol negotiation strategy based on the protocol detection results corresponding to each candidate protocol.

[0013] According to one achievable method in the embodiments of this application, the step of generating a target protocol negotiation strategy based on the protocol detection results corresponding to each candidate protocol includes: obtaining the protocol detection results corresponding to each candidate protocol and extracting the corresponding protocol response features; calculating the priority deviation of each candidate protocol based on the protocol priority and the protocol response features; generating a protocol convergence sequence based on the priority deviation of each candidate protocol; determining the target communication protocol based on the protocol convergence sequence and generating the corresponding target protocol negotiation strategy.

[0014] According to one achievable method in an embodiment of this application, after the communication connection is successfully established, controlling the fast-switch interface to open the working power to the target load includes: determining the corresponding power supply requirement parameters according to the protocol negotiation result and generating a power supply control command; gradually increasing the power supply power of the target load according to a preset power supply gradient; collecting load operating current, interface voltage, and communication status data in real time during the power supply process; generating power supply stability parameters based on the operating current, interface voltage, and communication status data; and controlling the fast-switch interface to open all working power to the target load when the power supply stability parameters meet a preset stability threshold.

[0015] According to one achievable method in this application embodiment, generating power supply stability parameters based on the operating current, the interface voltage, and the communication status data includes: determining a current change rate sequence at a corresponding time based on the operating current; determining a voltage fluctuation sequence at a corresponding time based on the interface voltage; determining a communication response status sequence at a corresponding time based on the communication status data; calculating the current communication coupling degree between the current change rate sequence and the communication response status sequence, and the voltage communication coupling degree between the voltage fluctuation sequence and the communication response status sequence; generating power supply communication coordination parameters based on the current communication coupling degree and the voltage communication coupling degree; and generating the power supply stability parameters based on the power supply communication coordination parameters.

[0016] According to the second aspect, a dynamic negotiation system for a robot quick-change payload communication protocol is provided, comprising: a quick-change interface module for detecting payload loading events at the quick-change interface of the robot end effector; a low-voltage interaction control module for controlling the quick-change interface to enter a low-voltage interaction mode after detecting the payload loading event, sending random seed data to the payload, and simultaneously receiving response data generated by the payload based on the random seed data; a digital gene generation module for extracting payload identity features, interface features, and functional features based on the response data, and generating a payload digital gene to characterize the payload's communication capabilities and interface attributes; a protocol family determination module for determining the protocol family set corresponding to the target payload based on the payload digital gene; a protocol negotiation module for generating a protocol negotiation strategy based on the protocol family set, and controlling the robot master control terminal to perform protocol negotiation with the target payload; and a communication connection and power supply control module for establishing a corresponding communication connection based on the protocol negotiation result, and controlling the quick-change interface to provide operating power to the target payload after the communication connection is successfully established.

[0017] According to the specific embodiments provided in this application, the following technical effects are disclosed: This invention enters a low-voltage interaction mode upon detecting a load loading event. It uses random seed data to stimulate the load to generate a dynamic response, extracts its identity, interface, and functional characteristics, and constructs a digital gene for the load. This intelligently determines the protocol family set and executes a dynamic negotiation strategy, ultimately establishing a secure communication connection and hierarchically opening the operating power supply. This method significantly improves the plug-and-play compatibility of heterogeneous loads, solves the problems of difficult adaptation to traditional fixed protocols, high security risks, and reliance on manual configuration, achieves adaptive protocol negotiation and secure power supply control, shortens switching time, reduces the risk of interface damage, and improves the flexibility, reliability, and intelligence level of the robot system, demonstrating outstanding technical effects and practical value.

[0018] Of course, any product implementing this application does not necessarily need to achieve all of the advantages described above at the same time. Attached Figure Description

[0019] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0020] Figure 1 A flowchart of a method for dynamic negotiation of a robot fast-load change communication protocol provided in an embodiment of this application; Figure 2 This is a schematic diagram illustrating the process of generating random seed data provided in an embodiment of this application; Figure 3 This is a schematic diagram illustrating the process of generating digital genes for payloads and determining protocol families provided in an embodiment of this application. Figure 4 This is a structural block diagram of a robot fast payload changer communication protocol dynamic negotiation system provided in an embodiment of this application. Detailed Implementation

[0021] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. All other embodiments obtained by those skilled in the art based on the embodiments of this application are within the scope of protection of this application.

[0022] Figure 1 A flowchart illustrating the dynamic negotiation method for the robot fast-change payload communication protocol provided in this application embodiment. Figure 1 As shown, the method may include the following steps: Step 101: Detect load loading events at the robot's end effector quick-change interface.

[0023] Step 102: After detecting the load loading event, control the quick-switch interface to enter the low-voltage interaction mode, send random seed data to the load, and receive the response data generated by the load based on the random seed data.

[0024] Step 103: Extract payload identity features, interface features, and functional features based on the response data, and generate a payload digital gene to characterize the payload's communication capabilities and interface attributes.

[0025] Step 104: Determine the protocol family set corresponding to the target payload based on the payload digital gene.

[0026] Step 105: Generate a protocol negotiation strategy based on the protocol family set, and control the robot master terminal to perform protocol negotiation with the target payload.

[0027] Step 106: Establish a corresponding communication connection based on the protocol negotiation result, and after the communication connection is successfully established, control the quick-switch interface to turn on the working power to the target load.

[0028] As can be seen from the above process, this invention enters a low-voltage interaction mode after detecting a load loading event. It uses random seed data to stimulate the load to generate a dynamic response, extracts its identity, interface, and functional characteristics, and constructs a digital gene for the load. This intelligently determines the protocol family set and executes a dynamic negotiation strategy, ultimately establishing a secure communication connection and hierarchically opening the operating power supply. This method significantly improves the plug-and-play compatibility of heterogeneous loads, solves the problems of difficult adaptation to traditional fixed protocols, high security risks, and reliance on manual configuration, achieves adaptive protocol negotiation and secure power supply control, shortens switching time, reduces the risk of interface damage, and improves the flexibility, reliability, and intelligence level of the robot system, demonstrating outstanding technical effects and practical value.

[0029] The following describes in detail each step of the above process and the effects that can be further produced, with reference to the embodiments.

[0030] Step 101 specifically involves: "Detecting load loading events at the robot's end-effector quick-change interface".

[0031] This step involves real-time sensing of whether a new load has been installed on the robot's end effector quick-change device, thereby triggering subsequent low-voltage interaction and protocol negotiation processes. In practical applications, the quick-change interface typically integrates multiple sensor components to accurately detect the occurrence of the loading action.

[0032] Specifically, the detection process can be achieved using mechanical locking sensors, contact switches, or pressure sensors. When the load is pushed by the robotic arm and physically docks with the interface, these sensors monitor the locking mechanism's positioning signal, pressure changes on the interface contact surface, and the stability of the connection. Once a combination of signals matching a preset threshold is detected, a load loading event is determined to have occurred. This multi-sensor fusion detection method effectively avoids false triggering, such as distinguishing between brief contact and truly reliable loading.

[0033] Furthermore, this detection can be combined with visual or force sensors for auxiliary judgment. The vision system captures image changes in the interface area through a camera, identifying the load's contour and positional offset, while the force sensor collects real-time data on the torque and force values ​​experienced by the end effector. Through comprehensive analysis of this information, the system can more accurately confirm the timing and reliability of loading events. This detection mechanism is not only rapid in response but also adaptable to the installation characteristics of different types of loads, ensuring the safety and efficiency of the entire quick-change process.

[0034] In complex industrial environments, this technology also considers the impact of environmental factors. For example, the system synchronously monitors vibrations or external interference near the interface to avoid false detections caused by mechanical vibrations. Through this method, detecting load loading events at the robot's end effector quick-change interface provides a reliable triggering basis for subsequent low-voltage mode switching and random seed interactions, significantly improving the overall automation and robustness of the solution.

[0035] Step 102 specifically involves: "After detecting the load loading event, controlling the quick-switch interface to enter the low-voltage interaction mode, sending random seed data to the load, and receiving response data generated by the load based on the random seed data."

[0036] Upon detecting the load loading event, the quick-switch interface enters a low-voltage interaction mode and sends random seed data to the load while simultaneously receiving response data generated by the load based on the random seed data. This step is executed immediately after load detection to establish a low-risk initial communication channel before full-power supply, avoiding potential interface damage or safety hazards caused by direct high-power connection. By switching to low-voltage interaction mode, the quick-switch interface only opens low-voltage signal transmission channels, limiting current and power levels to ensure the entire interaction process is under safe and controlled conditions.

[0037] The system first generates random seed data corresponding to the current mounting event. This generation process involves fusion encoding and nonlinear mapping based on factors such as mounting trigger time information, mechanical locking status information, interface contact status information, and environmental interference parameters, thereby ensuring the uniqueness and unpredictability of the seed data corresponding to each mounting event. Subsequently, this random seed data is sent to the load through a low-voltage interaction channel. The low-voltage channel uses a dedicated low-voltage signal line to achieve reliable data transmission while avoiding the impact of strong current interference on the initial interaction.

[0038] As an feasible approach, generating random seed data corresponding to the current mounting event includes: acquiring mounting trigger time information, mechanical locking state information, and interface contact state information at the robot's end effector quick-change interface; collecting current environmental interference parameters, including electromagnetic noise intensity and power supply transient fluctuation information; fusing and encoding the mounting trigger time information, the mechanical locking state information, the interface contact state information, and the environmental interference parameters to generate a mounting event state vector; and performing nonlinear mapping processing on the mounting event state vector to generate random seed data corresponding to the current mounting event.

[0039] Figure 2 This diagram illustrates the process of generating random seed data as provided in this embodiment. Specifically, the system first acquires the mounting trigger time information at the robot's end effector quick-change interface. This information records the precise moment the mounting action occurs, including a millisecond-level timestamp, reflecting the timing characteristics of the mounting. Next, the system collects mechanical locking status information, such as the degree of locking mechanism engagement, locking force feedback value, and the stability signal of the locking mechanism. This data is used to confirm the reliability of the physical connection. Simultaneously, interface contact status information is also acquired, including the contact resistance of each pin, contact pressure distribution, and connection integrity indicators. These status information collectively constitute the physical basis description of the mounting event.

[0040] While acquiring the above information, the system also collects current environmental interference parameters. These parameters mainly include electromagnetic noise intensity and power supply transient fluctuation information. Electromagnetic noise intensity is monitored in real time by electromagnetic sensors near the interface, reflecting the level of electromagnetic interference in the surrounding industrial environment; power supply transient fluctuation information captures short-term changes in voltage or current, reflecting the impact of power supply stability on the interface. Introducing environmental interference parameters makes the seed generation process highly adaptable to the environment and able to cope with the dynamic changes in complex industrial sites.

[0041] After acquiring all relevant information, the system performs fusion encoding on the mounting trigger time information, mechanical lock status information, interface contact status information, and environmental interference parameters. First, different types of data are normalized and vectorized. Then, a unified mounting event state vector is generated using weighted concatenation or multi-dimensional embedding. This vector comprehensively integrates temporal sequence, physical state, and environmental factors, forming a high-dimensional integrated representation. Subsequently, the mounting event state vector undergoes nonlinear mapping processing, such as through chaotic mapping functions, hash algorithms combined with nonlinear transformations, or mapping operations based on deterministic chaotic systems, mapping the vector to fixed-length random seed data.

[0042] This nonlinear mapping ensures that the output seed possesses good randomness, uniqueness, and irreversibility; even if the input information is partially similar, the generated seeds will be significantly different. This technical feature significantly improves the anti-predictability and security of random seed data, providing reliable support for dynamic response reconstruction in weak current interaction modes, and ultimately enhancing the robustness and attack resistance of the entire protocol negotiation process.

[0043] After receiving random seed data, the payload generates response data by combining it with its pre-defined payload identification parameters. This response data includes payload identification response information, interface capability response information, and functional capability response information. These pieces of information respectively characterize the payload's identity details, supported physical interface types and data transmission capabilities, as well as its specific functional categories and parameters. During the generation process, the payload dynamically reconstructs the arrangement and encoding format of these three types of response information based on the received random seed data. For example, the payload can use seed data to drive a permutation algorithm or mapping rule to change the organization and encoding format of the information, resulting in response data exhibiting a different form for each interaction.

[0044] For example, first, random seed data is used as input to generate a set of pseudo-random sequences using a pre-defined pseudo-random number generator. The length of this sequence is sufficient to cover subsequent permutation and encoding operations.

[0045] For reordering, the payload uses a pseudo-random sequence to shuffle the three segments of response information. Specifically, the identification response information, interface capability response information, and functional capability response information are treated as three independent blocks, and these three blocks are reordered according to the permutation index generated by the seed. For example, if the permutation index generated by the pseudo-random sequence is [2,0,1], the order of the response data is adjusted to the arrangement of interface capability response information, identification response information, and functional capability response information. This permutation is different for each load, ensuring the dynamic nature of the response structure.

[0046] For the reconstruction of the encoded data, the payload further applies different encoding transformations to each block using a key derived from the seed. Encoding methods include bitwise XOR operations, cyclic shifts, and selective byte padding. Specifically, the system selects different shift bits and XOR masks based on the seed modulo operation result to transform each information block. Simultaneously, a seed-based checksum field can be added to the entire response data packet to further enhance consistency verification capabilities. After completing the sequence permutation and encoding transformation, the payload sends the reconstructed response data back to the robot's master control terminal via a low-voltage interactive channel.

[0047] This dynamic reconstruction mechanism significantly enhances the security of the interaction, effectively preventing replay attacks and intrusion by forged payloads. Upon receiving the response data, the robot's main control unit can proceed to the subsequent feature extraction and digital gene generation stages. Overall, this technology, through a random seed challenge response in a low-voltage mode, achieves preliminary security authentication and capability probing of the payload, laying a reliable foundation for subsequent protocol negotiation and power supply opening, while simultaneously improving the anti-interference capability and intelligence level of the entire fast-swapping system.

[0048] Step 103 specifically involves: "Extracting payload identity features, interface features, and functional features based on the response data, and generating a payload digital gene to characterize the payload's communication capabilities and interface attributes."

[0049] This step is executed after receiving the response data of the payload. Through systematic feature extraction and fusion processing, the scattered payload information is transformed into a structured digital gene vector, providing a unified and efficient representation basis for subsequent protocol family matching and negotiation strategy generation.

[0050] The system first extracts payload identification information from the response data. This information typically includes key fields such as the payload's unique serial number, manufacturer identifier, and model version, used to establish the payload's uniqueness. Next, the system obtains the physical interface type corresponding to the payload, such as pin layout, interface standard type, and mechanical and electrical compatibility specifications. Simultaneously, it also obtains power supply level information, including supported voltage range, current capacity, and power level, as well as data transmission mode, such as serial communication, Ethernet bus, fiber optic interface, or wireless transmission. These interface characteristics collectively describe the physical and electrical compatibility between the payload and the robot's quick-change device.

[0051] Subsequently, the system further acquires the corresponding functional categories and parameters of the load. Functional categories may encompass various types such as gripping, welding, visual inspection, and force control operations, while functional parameters include specific technical indicators such as motion accuracy, sampling frequency, load capacity, and response time. These functional characteristics reflect the load's application value and performance boundaries in actual operations. Through comprehensive collection of the above multi-dimensional information, the system builds a complete understanding of the load's communication capabilities and interface attributes.

[0052] After extracting various features, the system encodes and fuses payload identification information, physical interface type, power supply level, data transmission mode, functional category, and functional parameters to generate a corresponding payload digital gene. This digital gene is a fixed-dimensional vector or matrix used for subsequent similarity calculations and protocol mapping.

[0053] Figure 3 This diagram illustrates the payload digital gene generation and protocol family determination process provided in this embodiment. Specifically, the system first performs hierarchical vectorized encoding on each feature. For example, identity information is mapped to a high-dimensional sparse vector using a hash function; physical interface type and data transmission mode are represented using one-hot encoding or embedding; and power supply level and functional parameters are encoded using normalized numerical values. Then, a lightweight fusion network based on an attention mechanism is introduced, using all feature vectors as input and performing weighted fusion by calculating the dynamic weights between features. This network can be pre-trained offline on historical payload data to learn the importance of different features in representing communication capabilities. During the fusion process, nonlinear activation functions and residual connections can also be added to ensure that the gene vector retains the unique information of the original features while capturing the deep relationships between features. This attention-driven encoding fusion method has strong adaptability and scalability, automatically highlighting the feature dimensions most influential on protocol negotiation, thereby generating more discriminative and robust payload digital genes and improving the overall intelligence level of the solution.

[0054] Step 104 specifically involves: "Determining the protocol family set corresponding to the target payload based on the payload digital gene".

[0055] This step achieves rapid mapping from abstract capability representation to specific communication protocol families through intelligent matching of payload digital genes, avoiding the inefficiency of traditional fixed lookup tables or exhaustive attempts, and providing a precise candidate range for subsequent dynamic negotiation strategy generation.

[0056] The system first acquires a pre-established digital gene protocol family mapping database. This database is a knowledge base built offline or continuously updated using historical payload data, storing a large number of digital gene samples with known payloads and their corresponding protocol families. Each historical digital gene is associated with one or more protocol families, such as EtherCAT, Modbus, CAN, and custom real-time bus families, and records the applicable scenarios, performance characteristics, and compatibility conditions for each protocol family. This database can be organized as a database or a vector database, supporting efficient retrieval and incremental maintenance.

[0057] After acquiring the mapping database, the system calculates the gene similarity between the current payload digital gene and each historical digital gene in the database. Similarity calculation can use cosine similarity, Euclidean distance, weighted Hamming distance, or a custom fusion metric, comprehensively considering the weight differences of each dimension of the gene vector. Through one-by-one comparisons, the system obtains a list of matching scores between the current gene and historical genes; these scores reflect the degree of closeness of the payload capability characteristics to known protocol families.

[0058] Finally, the system determines the target protocol family set and corresponding protocol priorities based on the calculated gene similarity. Typically, a reasonable similarity threshold is set, and matches exceeding the threshold are included in the target protocol family set, with protocols assigned priorities in descending order of similarity. Higher-priority protocols indicate a better match to the current payload's communication capabilities and interface attributes, allowing for priority detection and negotiation. This mechanism not only improves the accuracy and efficiency of protocol determination but also supports fuzzy matching capabilities, enabling the system to find the closest protocol family for adaptation even with novel payloads.

[0059] Step 105 specifically involves: "Generating a protocol negotiation strategy based on the protocol family set, and controlling the robot's main control terminal to perform protocol negotiation with the target payload."

[0060] This step is performed after the target protocol family set is determined. By comprehensively considering protocol characteristics and priority information, a targeted negotiation plan is developed to avoid wasting time and resources due to blind attempts.

[0061] The system first acquires the protocol characteristic parameters corresponding to each candidate protocol in the protocol family set. These characteristic parameters include the protocol's real-time performance indicators, bandwidth requirements, deterministic guarantee level, error handling mechanism, supported topology, and interface hardware requirements. By comprehensively collecting these parameters, the system establishes a complete understanding of the technical attributes of each candidate protocol, providing a data foundation for subsequent sequence generation and resource allocation.

[0062] Next, the system combines the protocol priority of each candidate protocol with the aforementioned protocol feature parameters to generate a candidate protocol negotiation sequence. Protocols with higher priority are placed at the beginning of the sequence, while also considering the matching degree of feature parameters, such as prioritizing protocols with highly consistent real-time requirements and payload capabilities. This generation process can employ a weighted sorting algorithm or a rule engine to ensure that the negotiation sequence respects priority while also taking into account the complementarity and potential conflicts between protocols, thereby forming a logically clear, efficient, and feasible execution order.

[0063] Then, the system allocates protocol probing resources according to the protocol priority of each candidate protocol and executes protocol probing according to the negotiation sequence of the candidate protocols. High-priority protocols will receive more computing resources and communication time slots, such as being allocated a longer probing window or a higher probing frequency, while low-priority protocols will use a lightweight probing method. Under the guidance of the sequence, the robot master terminal sends probing commands to the payload in sequence, observes the payload's response, and gradually verifies the availability of each protocol.

[0064] Finally, the system generates a target protocol negotiation strategy based on the protocol detection results for each candidate protocol. The detection results include information such as response success rate, communication stability indicators, and actual performance. The system optimizes the final strategy accordingly, such as eliminating failed protocols, adjusting the negotiation parameters of the remaining protocols, or generating a hybrid negotiation path.

[0065] As an implementable approach, a target protocol negotiation strategy is generated based on the protocol probing results corresponding to each candidate protocol, including: obtaining the protocol probing results corresponding to each candidate protocol and extracting the corresponding protocol response features; calculating the priority deviation of each candidate protocol based on the protocol priority and the protocol response features; generating a protocol convergence sequence based on the priority deviation of each candidate protocol; determining the target communication protocol based on the protocol convergence sequence and generating the corresponding target protocol negotiation strategy.

[0066] Specifically, the system first acquires the protocol probing results for each candidate protocol and extracts the corresponding protocol response features. These probing results include actual performance data such as the payload's response time to probing commands, success rate, data packet integrity, communication latency, and error code distribution. The extracted response features can cover aspects such as real-time matching degree, stability indicators, and compatibility deviations, providing a reliable basis for subsequent quantitative evaluation.

[0067] The system calculates the priority deviation for each candidate protocol based on its priority and the aforementioned protocol response characteristics. This deviation is quantified by comprehensively comparing the difference between the initial priority and the actual detection performance. For example, a high-priority protocol with poor response characteristics will exhibit a positive deviation, while a low-priority protocol with excellent performance will exhibit a negative deviation. The calculation process can employ a weighted formula, integrating factors such as priority weights and response characteristic scores to form a comparable set of deviation indicators.

[0068] The system generates a protocol convergence sequence based on the priority deviation of each candidate protocol. This sequence reorders the candidate protocols, placing those with smaller deviations and better overall performance at the front, while also considering sequence continuity and potential combinatorial effects. This convergence sequence demonstrates dynamic adjustment capabilities, enabling rapid narrowing of the search range and focusing on the optimal candidate.

[0069] The system determines the target communication protocol based on the protocol convergence sequence and generates a corresponding target protocol negotiation strategy. This strategy includes the final selected target protocol parameters, negotiation parameter configurations, backup fallback paths, and a detailed sequence of execution instructions. Through this process, the system completes a full closed loop from detection to decision-making.

[0070] Next, the robot's master control unit negotiates a protocol with the target payload. The master control unit first loads the detailed execution instructions contained in the target protocol negotiation strategy, including the detection parameters, timeout settings, parameter negotiation rules, and backup paths for each candidate protocol in the negotiation sequence. Then, the master control unit sends a protocol negotiation initialization command to the payload through the established low-voltage communication channel or preliminary communication link. This command carries the selected target protocol type, version information, and negotiation parameter proposals, such as baud rate, data frame format, synchronization mechanism, and error handling method.

[0071] After receiving the negotiation command, the payload responds to the proposal based on its capabilities, returning confirmation, modification suggestions, or rejection information. The robot's master control unit parses these responses in real time and dynamically adjusts the negotiation parameters according to the characteristics of the protocol responses. For example, it may reduce the transmission rate or switch to a backup protocol parameter set when the response latency is high. This interaction process typically employs a multi-round handshake mechanism to gradually complete parameter alignment and functional verification until both parties reach an agreement.

[0072] During the negotiation process, the master control unit continuously monitors communication quality indicators such as packet loss rate, latency fluctuation, and handshake success rate. If an anomaly is detected, the master control unit can switch to a suboptimal protocol or re-execute some probing steps based on a preset backoff strategy. This closed-loop control ensures the robustness of the negotiation. Even in complex electromagnetic environments or with slight deviations in load capacity, it can quickly converge to a usable protocol.

[0073] Step 106 specifically involves: "Establishing a corresponding communication connection based on the protocol negotiation result, and after the communication connection is successfully established, controlling the fast-switch interface to turn on the operating power to the target payload."

[0074] This step is executed after the agreement is successfully negotiated and agreed upon. It involves formally establishing a stable and reliable communication connection and gradually turning on the power supply to achieve a smooth transition of the payload from the initial detection state to the normal operation state.

[0075] The system first establishes a corresponding communication connection based on the target protocol parameters in the protocol negotiation results. The robot's master control unit initializes the formal data transmission link according to the negotiated protocol type, communication parameters, and configuration information, including setting the data frame format, synchronization clock, error checking mechanism, and heartbeat monitoring. Subsequently, the master control unit and the payload perform a final handshake verification to confirm that both parties are fully matched in communication rate, address mapping, and functional subsets. Once the verification is successful, the communication connection is marked as successfully established, and the system records the connection status parameters to provide a basis for subsequent monitoring.

[0076] After a successful communication connection is established, the system immediately controls the quick-switch interface to supply power to the target load. This process employs a tiered power supply method, gradually increasing the power supply according to a preset gradient, for example, starting from a low-power test level and gradually increasing to the load's rated operating power. Simultaneously, during the power supply process, the system collects real-time data on the load's operating current, interface voltage, and communication status, and calculates power supply stability parameters. Only when the stability parameters meet preset thresholds is the full operating power supplied.

[0077] As one feasible approach, after the communication connection is successfully established, controlling the fast-switch interface to provide operating power to the target load includes: determining the corresponding power demand parameters based on the protocol negotiation results and generating power supply control commands; gradually increasing the power supply to the target load according to a preset power supply gradient; collecting load operating current, interface voltage, and communication status data in real time during the power supply process; generating power supply stability parameters based on the operating current, interface voltage, and communication status data; and controlling the fast-switch interface to provide full operating power to the target load when the power supply stability parameters meet a preset stability threshold.

[0078] Specifically, the system first determines the corresponding power supply requirement parameters based on the protocol negotiation results and generates power supply control commands. The negotiation results include key information such as the load's power requirements, voltage level, and operating mode. Based on this, the system calculates a precise set of power supply parameters, such as rated voltage, maximum current, and startup power curve, and forms an executable sequence of control commands. This process ensures that the power supply strategy is highly matched with the actual load capacity, avoiding incompatibility issues caused by blindly supplying power.

[0079] The system gradually increases the power supply to the target load according to a preset power supply gradient. This gradient is typically designed as a multi-level incremental process, starting from a low-power test level, progressively increasing to intermediate operating levels, and finally reaching full power. This gradual increase provides the system with ample observation and adjustment windows, enabling verification of the load's response at each gradient stage.

[0080] During power supply, the system continuously collects load operating current, interface voltage, and communication status data in real time. This data is acquired through sensors integrated into the fast-switch interface. The operating current reflects the actual power consumption behavior of the load, the interface voltage monitors electrical stability, and the communication status data includes indicators such as response latency, packet loss rate, and heartbeat signals. Through multi-source real-time acquisition, the system constructs a comprehensive monitoring view of the power supply process.

[0081] The system generates power supply stability parameters based on the operating current, interface voltage, and communication status data. These parameters are calculated by integrating indicators such as current change trends, voltage fluctuation amplitude, and communication response consistency to form a comprehensive quantitative value, which is used to objectively assess the safety of the current power supply status.

[0082] When the power supply stability parameters meet the preset stability threshold, the system controls the fast-switch interface to open all working power to the target load. The final power supply opening is only completed when all indicators are within safe ranges; if the threshold is not met, the power increase is paused or reverted to a safe power level, and an alarm mechanism is triggered.

[0083] Preferably, generating power supply stability parameters based on the operating current, the interface voltage, and the communication status data includes: determining a current change rate sequence at a corresponding time based on the operating current; determining a voltage fluctuation sequence at a corresponding time based on the interface voltage; determining a communication response status sequence at a corresponding time based on the communication status data; calculating the current communication coupling degree between the current change rate sequence and the communication response status sequence, and the voltage communication coupling degree between the voltage fluctuation sequence and the communication response status sequence; generating power supply communication coordination parameters based on the current communication coupling degree and the voltage communication coupling degree; and generating the power supply stability parameters based on the power supply communication coordination parameters.

[0084] Specifically, the system first determines the current change rate sequence at corresponding times based on the operating current. This sequence is obtained by performing differential calculations or sliding window processing on continuously acquired current samples to obtain the dynamic change rate of the current at each time moment, reflecting the power consumption fluctuation trend and transient response characteristics of the load during the power supply process.

[0085] The system determines the voltage fluctuation sequence at corresponding times based on the interface voltage. This sequence records the deviation amplitude and frequency of voltage values ​​relative to the rated voltage, enabling timely detection of ripple, dips, or overshoot phenomena in the power supply line, thus reflecting the stability of the electrical supply.

[0086] Furthermore, the system determines the communication response status sequence at corresponding times based on the communication status data. This sequence integrates indicators such as response latency, success rate, data integrity, and heartbeat interval, forming a sequence that quantifies the evolution of communication quality over time.

[0087] After obtaining the three sequences mentioned above, the system calculates the current communication coupling degree between the current change rate sequence and the communication response state sequence, as well as the voltage communication coupling degree between the voltage fluctuation sequence and the communication response state sequence. The coupling degree can be calculated through cross-correlation analysis, correlation coefficient calculation, or a custom similarity metric, and is used to measure the synchronicity and consistency between power supply dynamics and communication performance. A high coupling degree indicates that power supply changes can be smoothly responded to by the communication system, while a low coupling degree suggests potential instability risks.

[0088] The system generates power supply and communication coordination parameters based on the current-to-communication coupling degree and the voltage-to-communication coupling degree. These parameters, through weighted fusion of the two coupling results, yield a comprehensive coordination index that fully characterizes the coordination level between the power supply system and the communication system at the current stage.

[0089] The system generates the power supply stability parameters based on the power supply communication coordination parameters. These parameters can be further combined with the statistical characteristics of the sequence, such as fluctuation amplitude and trend prediction, to form a final stability score or index, which is used for comparison with a preset stability threshold.

[0090] To further illustrate the technical effects of the present invention, a specific implementation method and its test results are first given.

[0091] This implementation method is applied to a six-axis collaborative robot platform. The robot's end effector is equipped with a quick-change interface supporting multiple protocols, and its payload includes heterogeneous devices such as electric grippers, vision cameras, and force-controlled end effectors from different suppliers. In actual operation, when the robotic arm installs the electric gripper payload onto the quick-change interface, the system first detects the mounting event through mechanical locking sensors, contact pressure sensors, and a vision-assisted module integrated at the interface. After confirmation, the quick-change interface immediately switches to a low-voltage interaction mode, opening only the 5V low-voltage signal channel. The system collects the mounting trigger time, locking state, contact resistance, and information on the intensity of electromagnetic noise and power supply fluctuations. It generates a mounting event state vector through fusion encoding and obtains a unique random seed data for the current event through nonlinear chaotic mapping. Subsequently, this seed is sent to the payload through the low-voltage channel. The payload uses the seed to dynamically permutate and reconstruct preset identification information, interface capabilities, and functional information before returning response data.

[0092] After receiving the response data, the robot's master control unit extracts features such as identity identifier, physical interface type, power supply level, data transmission mode, and functional parameters. It then generates a payload digital gene vector through an attention-driven encoding fusion network. The system next queries a pre-built digital gene protocol family mapping library, calculates gene similarity, determines a high-priority protocol family set primarily based on EtherCAT and a custom real-time bus, and generates a priority-driven negotiation sequence. The master control unit allocates probe resources according to the sequence, executes protocol probes sequentially, calculates priority deviation based on probe response characteristics, generates a convergence sequence, and finally determines and executes the target protocol negotiation strategy, successfully establishing a deterministic real-time communication connection.

[0093] After a successful communication connection is established, the system determines the power supply demand parameters based on the negotiation results and gradually increases the power supply according to a preset gradient of 10%→40%→70%→100%. At each gradient stage, operating current, interface voltage, and communication status data are collected in real time. The system calculates the current change rate sequence, voltage fluctuation sequence, and communication response status sequence, and obtains the current-communication coupling degree and voltage-communication coupling degree through cross-correlation analysis, thereby generating power supply-communication coordination parameters and final power supply stability parameters. When the stability parameter reaches a preset threshold of 0.88 or higher, the system switches to full power supply, and the load enters normal operating mode.

[0094] To verify the effectiveness of this implementation method, repeated tests were conducted on heterogeneous payloads from 20 different suppliers in laboratory and industrial environments. Test results showed a protocol negotiation success rate of 98.5%, an average switching time of 4.2 seconds (approximately 72% shorter than traditional manual configuration), a power supply failure rate of less than 0.3%, and zero interface damage events. The system maintained a stable operating rate of over 95% even under strong electromagnetic interference. These test data clearly demonstrate that the present invention significantly improves the compatibility, safety, and intelligence of the robot quick-change system, exhibiting good practical effects and promotional value.

[0095] The methods provided in this application can be applied to various application scenarios, including but not limited to: In intelligent automotive assembly lines, collaborative robots can quickly replace electric grippers, vision inspection cameras, or force-controlled tightening tools. The system achieves plug-and-play compatibility of heterogeneous loads from different suppliers through dynamic protocol negotiation, significantly reducing downtime and manual configuration costs, and improving production line flexibility; In precision assembly scenarios for electronic components, the robot end effector needs to quickly switch between welding guns, dispensing devices, and nozzles. The low-voltage interaction, digital gene matching, and hierarchical power supply mechanisms of this solution ensure the stable establishment of high-precision communication, avoid interface damage and protocol conflicts, and meet the stringent safety and reliability requirements of cleanrooms; In addition, in intelligent warehousing and logistics robot systems, forklifts or mobile robots can dynamically change grippers, scanners, or robotic arm loads according to tasks. Through environmentally aware random seeds and protocol convergence strategies, seamless adaptation across supplier equipment is achieved, improving logistics efficiency and reducing system integration difficulty.

[0096] According to another embodiment, a dynamic negotiation system for a robot fast payload change communication protocol is provided. Figure 4 A schematic block diagram of a robot fast-load-change communication protocol dynamic negotiation system is shown according to one embodiment. Figure 4 As shown, the system includes: The quick-change interface module 401 is used to detect load loading events at the quick-change interface of the robot's end effector.

[0097] The low-voltage interactive control module 402 is used to control the fast-switch interface to enter the low-voltage interactive mode after detecting the load loading event, and send random seed data to the load, while receiving response data generated by the load based on the random seed data.

[0098] The digital gene generation module 403 is used to extract payload identity features, interface features and functional features based on the response data, and generate a payload digital gene to characterize the payload's communication capabilities and interface attributes.

[0099] Protocol family determination module 404 is used to determine the protocol family set corresponding to the target payload based on the payload digital gene.

[0100] The protocol negotiation module 405 is used to generate a protocol negotiation strategy based on the protocol family set and control the robot master terminal to perform protocol negotiation with the target payload.

[0101] The communication connection and power supply control module 406 is used to establish a corresponding communication connection based on the protocol negotiation result, and after the communication connection is successfully established, control the quick-switch interface to turn on the working power to the target load.

[0102] As one feasible approach, the low-voltage interactive control module 402 sends random seed data to the load and receives response data generated by the load based on the random seed data, including: generating random seed data corresponding to the current mounting event; sending the random seed data to the load through the low-voltage interactive channel; and receiving response data generated by the load based on the random seed data and preset load identifier parameters; wherein, the response data includes load identifier response information, interface capability response information, and functional capability response information, and the load dynamically reconstructs the arrangement order and encoding form of the load identifier response information, the interface capability response information, and the functional capability response information according to the random seed data.

[0103] As an feasible approach, the low-voltage interactive control module 402 generates random seed data corresponding to the current mounting event, including: acquiring mounting trigger time information, mechanical locking state information, and interface contact state information at the robot's end effector quick-change interface; collecting current environmental interference parameters, including electromagnetic noise intensity and power supply transient fluctuation information; fusing and encoding the mounting trigger time information, the mechanical locking state information, the interface contact state information, and the environmental interference parameters to generate a mounting event state vector; and performing nonlinear mapping processing on the mounting event state vector to generate random seed data corresponding to the current mounting event.

[0104] As one feasible approach, the digital gene generation module 403 extracts payload identity features, interface features, and functional features based on the response data, and generates a payload digital gene to characterize the payload's communication capabilities and interface attributes. This includes: extracting payload identity information from the response data; obtaining the physical interface type, power supply level, and data transmission mode corresponding to the payload; obtaining the functional category and functional parameters corresponding to the payload; and encoding and fusing the payload identity information, physical interface type, power supply level, data transmission mode, functional category, and functional parameters to generate the corresponding payload digital gene.

[0105] As one feasible approach, the protocol family determination module 404 determines the protocol family set corresponding to the target payload based on the payload digital gene, including: acquiring a pre-established digital gene protocol family mapping relationship library; calculating the gene similarity between the payload digital gene and each historical digital gene in the digital gene protocol family mapping relationship library; and determining the target protocol family set and the corresponding protocol priority based on the gene similarity.

[0106] As an implementable approach, the protocol negotiation module 405 generates a protocol negotiation strategy based on the protocol family set, including: obtaining protocol feature parameters corresponding to each candidate protocol in the protocol family set; generating a candidate protocol negotiation sequence by combining the protocol priority corresponding to each candidate protocol and the protocol feature parameters; allocating protocol detection resources according to the protocol priority corresponding to each candidate protocol, and performing protocol detection according to the candidate protocol negotiation sequence; and generating a target protocol negotiation strategy based on the protocol detection results corresponding to each candidate protocol.

[0107] As an implementable approach, the protocol negotiation module 405 generates a target protocol negotiation strategy based on the protocol detection results corresponding to each candidate protocol, including: obtaining the protocol detection results corresponding to each candidate protocol and extracting the corresponding protocol response features; calculating the priority deviation of each candidate protocol based on the protocol priority and the protocol response features; generating a protocol convergence sequence based on the priority deviation of each candidate protocol; determining the target communication protocol based on the protocol convergence sequence and generating the corresponding target protocol negotiation strategy.

[0108] As one feasible approach, after the communication connection is successfully established, the communication connection and power supply control module 406 controls the quick-switch interface to provide operating power to the target load, including: determining the corresponding power supply requirement parameters according to the protocol negotiation results and generating power supply control commands; gradually increasing the power supply power of the target load according to a preset power supply gradient; collecting load operating current, interface voltage, and communication status data in real time during the power supply process; generating power supply stability parameters based on the operating current, interface voltage, and communication status data; and controlling the quick-switch interface to provide full operating power to the target load when the power supply stability parameters meet a preset stability threshold.

[0109] As one feasible approach, the communication connection and power supply control module 406 generates power supply stability parameters based on the operating current, the interface voltage, and the communication status data, including: determining the current change rate sequence at a corresponding time based on the operating current; determining the voltage fluctuation sequence at a corresponding time based on the interface voltage; determining the communication response state sequence at a corresponding time based on the communication status data; calculating the current communication coupling degree between the current change rate sequence and the communication response state sequence, and the voltage communication coupling degree between the voltage fluctuation sequence and the communication response state sequence; generating power supply communication coordination parameters based on the current communication coupling degree and the voltage communication coupling degree; and generating the power supply stability parameters based on the power supply communication coordination parameters.

[0110] In addition, embodiments of this application also provide a computer-readable storage medium storing a computer program thereon, which, when executed by a processor, implements the steps of the method described in any of the foregoing method embodiments.

[0111] And an electronic device comprising: one or more processors; and a memory associated with the one or more processors, the memory being used to store program instructions that, when read and executed by the one or more processors, perform the steps of the method described in any of the foregoing method embodiments.

[0112] This application also provides a computer program product, including a computer program that, when executed by a processor, implements the steps of the method described in any of the foregoing method embodiments.

[0113] As can be seen from the above description of the embodiments, those skilled in the art can clearly understand that this application can be implemented by means of software plus necessary general-purpose hardware platforms. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, can be embodied in the form of a computer program product. This computer program product can be stored in a storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods described in various embodiments or some parts of the embodiments of this application.

[0114] The technical solutions provided in this application have been described in detail above. Specific examples have been used to illustrate the principles and implementation methods of this application. The descriptions of the above embodiments are only for the purpose of helping to understand the methods and core ideas of this application. Furthermore, those skilled in the art will recognize that, based on the ideas of this application, there will be changes in the specific implementation methods and application scope. Therefore, the content of this specification should not be construed as a limitation of this application.

Claims

1. A method for dynamic negotiation of a robot fast payload change communication protocol, characterized in that, The method includes: Detect load loading events at the quick-change interface of the robot's end effector; After detecting the load loading event, the control quick-switch interface enters the low-voltage interaction mode, sends random seed data to the load, and receives response data generated by the load based on the random seed data. Based on the response data, payload identity features, interface features, and functional features are extracted, and a payload digital gene is generated to characterize the payload's communication capabilities and interface attributes. The protocol family set corresponding to the target payload is determined based on the payload digital gene; A protocol negotiation strategy is generated based on the protocol family set, and the robot master control terminal is controlled to perform protocol negotiation with the target payload; A corresponding communication connection is established based on the protocol negotiation results, and after the communication connection is successfully established, the quick-switch interface is controlled to turn on the working power to the target load.

2. The method according to claim 1, characterized in that, The step of sending random seed data to the payload and receiving response data generated by the payload based on the random seed data includes: Generate random seed data corresponding to the current mount event; The random seed data is sent to the payload via a low-voltage interactive channel; The system receives response data generated by the payload based on the random seed data and preset payload identifier parameters; wherein the response data includes payload identifier response information, interface capability response information and functional capability response information, and the payload dynamically reconstructs the arrangement order and encoding form of the payload identifier response information, the interface capability response information and the functional capability response information according to the random seed data.

3. The method according to claim 2, characterized in that, The generation of random seed data corresponding to the current mount event includes: Acquire the mounting trigger time information, mechanical locking status information, and interface contact status information at the robot's end effector quick-change interface; Collect current environmental interference parameters, including electromagnetic noise intensity and power supply transient fluctuation information; The mounting trigger time information, the mechanical locking state information, the interface contact state information, and the environmental interference parameters are fused and encoded to generate a mounting event state vector; The mounting event state vector is subjected to nonlinear mapping processing to generate random seed data corresponding to the current mounting event.

4. The method according to claim 1, characterized in that, The step of extracting payload identity features, interface features, and functional features from the response data, and generating a payload digital gene to characterize the payload's communication capabilities and interface attributes, includes: Extract payload identification information from the response data; Obtain the physical interface type, power supply level, and data transmission mode corresponding to the load; Obtain the functional category and functional parameters corresponding to the load; The payload identification information, physical interface type, power supply level, data transmission mode, function category, and function parameters are encoded and fused to generate a corresponding payload digital gene.

5. The method according to claim 1, characterized in that, The step of determining the protocol family set corresponding to the target payload based on the payload digital gene includes: Obtain a pre-established digital gene protocol family mapping database; Calculate the gene similarity between the payload digital gene and each historical digital gene in the digital gene protocol family mapping relationship library; The target protocol family set and the corresponding protocol priority are determined based on the gene similarity.

6. The method according to claim 5, characterized in that, The step of generating a protocol negotiation strategy based on the protocol family set includes: Obtain the protocol feature parameters corresponding to each candidate protocol in the protocol family set; A candidate protocol negotiation sequence is generated by combining the protocol priority and the protocol feature parameters corresponding to each candidate protocol. Protocol detection resources are allocated according to the protocol priority of each candidate protocol, and protocol detection is performed according to the candidate protocol negotiation sequence; A target protocol negotiation strategy is generated based on the protocol detection results corresponding to each candidate protocol.

7. The method according to claim 6, characterized in that, The step of generating a target protocol negotiation strategy based on the protocol detection results corresponding to each candidate protocol includes: Obtain the protocol detection results for each candidate protocol and extract the corresponding protocol response features; Calculate the priority deviation of each candidate protocol based on the protocol priority and the protocol response characteristics. Generate a protocol convergence sequence based on the priority deviation of each candidate protocol; The target communication protocol is determined based on the protocol convergence sequence, and a corresponding target protocol negotiation strategy is generated.

8. The method according to claim 1, characterized in that, After the communication connection is successfully established, controlling the fast-switch interface to supply operating power to the target payload includes: Based on the negotiation results of the aforementioned protocol, the corresponding power supply demand parameters are determined, and power supply control commands are generated; The power supply to the target load is gradually increased according to a preset power supply gradient; During the power supply process, load operating current, interface voltage, and communication status data are collected in real time. Power supply stability parameters are generated based on the operating current, the interface voltage, and the communication status data. When the power supply stability parameter meets the preset stability threshold, the quick-switch interface is controlled to open all working power to the target load.

9. The method according to claim 8, characterized in that, The step of generating power supply stability parameters based on the operating current, the interface voltage, and the communication status data includes: The current change rate sequence at corresponding times is determined based on the operating current; The voltage fluctuation sequence at the corresponding time moment is determined based on the interface voltage; The communication response state sequence at the corresponding time is determined based on the communication state data; Calculate the degree of current communication coupling between the current change rate sequence and the communication response state sequence, and the degree of voltage communication coupling between the voltage fluctuation sequence and the communication response state sequence; Power supply communication coordination parameters are generated based on the current communication coupling degree and the voltage communication coupling degree. The power supply stability parameters are generated based on the power supply communication coordination parameters.

10. A dynamic negotiation system for a robot fast payload change communication protocol, characterized in that, include: The quick-change interface module is used to detect load loading events at the quick-change interface of the robot's end effector. The low-voltage interactive control module is used to control the fast-switch interface to enter the low-voltage interactive mode after detecting the load loading event, and send random seed data to the load, while receiving response data generated by the load based on the random seed data. The digital gene generation module is used to extract payload identity features, interface features and functional features based on the response data, and generate a payload digital gene to characterize the payload's communication capabilities and interface attributes. The protocol family determination module is used to determine the protocol family set corresponding to the target payload based on the payload digital gene. The protocol negotiation module is used to generate a protocol negotiation strategy based on the protocol family set and control the robot master terminal to perform protocol negotiation with the target payload; The communication connection and power supply control module is used to establish a corresponding communication connection based on the protocol negotiation result, and after the communication connection is successfully established, control the fast-switch interface to turn on the working power to the target load.

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