Self-adaptive dynamic current protection method and related equipment

Abstract

The invention provides a self-adaptive dynamic current protection method and related equipment, and relates to the technical field of robots. Operation state information and task working condition information of a joint module are obtained, a current protection threshold value is dynamically determined according to the operation state information and the task working condition information, a future current peak value is determined in combination with prediction of a future operation state, then an optimal current protection threshold value is comprehensively determined, and finally graded protection of the joint module is achieved. The method can effectively solve the problem that in the prior art, a single fixed current protection threshold value cannot distinguish'benign overload 'and'fault overload', and the defect that when the robot executes a high-dynamic task, protection is triggered by mistake due to a transient current peak value, and consequently the performance of the robot is limited is overcome.

Description

Technical Field

[0001] This application relates to the field of robotics technology, and more specifically, to an adaptive dynamic current protection method and related equipment. Background Technology

[0002] With the rapid development of artificial intelligence technology, embodied intelligent robots are becoming the core carriers of next-generation intelligent systems. Unlike traditional industrial robots that perform repetitive tasks in fixed environments, embodied intelligent robots emphasize real-time, proactive, and compliant interaction with the physical world. Integrated joint modules are the core components for achieving precise motion control in robots. The performance of the joint modules directly determines the robot's output torque and dynamic response capabilities. The module's protection strategy is a crucial safety feature.

[0003] Currently, the commonly used protection scheme in industry is to set a single, fixed current protection threshold for the controller in the joint module. The controller monitors the motor phase current in real time, and once the instantaneous or effective value of the current in any phase exceeds this preset threshold, the drive immediately enters a fault protection state. Although the above-mentioned single current protection strategy is widely used in traditional industrial automation due to its high reliability and ease of implementation, in the context of embodied intelligence that emphasizes autonomy, safety, and continuity, this single and direct protection strategy has obvious limitations. When the robot has unexpected physical contact with people or the environment, or when it needs to output a large torque instantaneously to cope with disturbances (such as being bumped by a person, lifted with a heavy object, or stuck), the current can easily exceed the fixed threshold briefly. At this time, the servo drive controller immediately enters a protection state, which may cause the entire joint module to lose torque instantaneously, causing the robot to become immobilized. Existing protection strategies lack intelligent judgment of overcurrent scenarios and cannot distinguish between "benign overload" and "fault overload". Moreover, existing protection strategies are also disconnected from the operating state of the embodied intelligent robot itself, and do not fully consider the robot's tolerance to overcurrent under different task scenarios.

[0004] There is currently no effective technical solution to the above problems. Summary of the Invention

[0005] The purpose of this application is to provide an adaptive dynamic current protection method and related equipment, which aims to solve the technical problems in the existing robot joint module protection strategies, such as the limitation of robot performance by a single fixed current threshold, the inability to distinguish between "benign overload" and "fault overload", and the disconnection from the robot's operating status.

[0006] In a first aspect, this application provides an adaptive dynamic current protection method for robots, comprising the following steps: S1. Obtain the running status information and task condition information of the joint module; S2. Determine the dynamic current protection threshold of the joint module based on the operating status information and task condition information; S3. Based on the operating status information, predict the future operating status of the joint module, and determine the future peak current of the joint module based on the future operating status; S4. Determine the optimal current protection threshold for the joint module based on the dynamic current protection threshold and the future peak current. S5. Monitor the actual output current of the joint module in real time, and perform graded protection for the joint module based on the actual output current and the optimal current protection threshold.

[0007] Through this technical solution, this application can dynamically adjust the current protection threshold according to the real-time operating status and task conditions of the robot joint module, and combine it with future current prediction to achieve adaptive hierarchical protection of the joint module. This effectively solves the "one-size-fits-all" problem of traditional fixed threshold protection strategies in embodied intelligent robot applications, avoids false protection and performance limitations caused by short-term current peaks, and improves the reliability and task continuity of the robot.

[0008] Optionally, step S2 includes: Obtain the static current protection value of the joint module; Based on the task operating condition information, consult the preset operating condition adaptive control factor form to obtain the operating condition adaptive control factor; determine the time decay constant based on the thermodynamic model of the joint module and the experimental data of actual operation. The peak boundary current of the operating condition is calculated based on the adaptive control factor of the operating condition, the time decay constant, and the first current preset based on the maximum demagnetizing current of the joint module. Based on the operating status information, the position of the joint module on the robot body, and the task requirements, determine the first weighting factor of the thermal protection boundary and the second weighting factor of the working condition peak boundary. The dynamic current protection threshold is calculated based on the static current protection value, the peak boundary current under operating conditions, the first weighting factor, and the second weighting factor.

[0009] Through this technical solution, this application can comprehensively consider the static thermal protection of the joint module, the current tolerance under different task conditions, and the instantaneous overload capability. Combined with the specific application scenario of the joint module on the robot body, dynamic balancing is performed through weighting factors to calculate a dynamic current protection threshold that is more in line with actual operating requirements. This enables the protection strategy to distinguish between "benign overload" and "fault overload", avoiding false triggering of protection due to brief current peaks when the robot is performing highly dynamic tasks, and solving the problem of the "one-size-fits-all" approach of traditional protection strategies.

[0010] Optionally, the peak boundary current under operating conditions is calculated according to the following formula: I_mode = k_mode * f(t) * I_set; In the formula, k_mode is the adaptive control factor for operating conditions, f(t) is the time decay constant, I_set is the preset first current, and I_mode is the peak boundary current of the operating conditions.

[0011] This technical solution allows the joint module to briefly break through static limitations and fully unleash its performance when dealing with instantaneous impacts or explosive force demands.

[0012] Optionally, the dynamic current protection threshold is calculated according to the following formula: I_safe=a*I_thermal+b*I_mode; I_safe is the dynamic current protection threshold, I_thermal is the static current protection value, a is the first weighting factor, and b is the second weighting factor.

[0013] Optionally, the operating status information includes the current position, current speed, and current output torque of the joint module; Step S3 includes: Based on the current position, current speed, and current output torque, and combined with the preset state prediction model, the future operating state of the joint module within the preset time window is predicted. The future motion state includes the future position, future speed, and future acceleration. Based on the future motion state, combined with the joint dynamics model and the transmission characteristics of the joint module, the future torque information required by the joint module at each time point within the preset time window is obtained. Based on future torque information, the future current value generated by the joint module at each time point within a preset time window is determined according to the number of pole pairs and flux linkage parameters of the motor in the joint module and the preset electrode control strategy; and the future current peak value of the joint module is determined from the future current value.

[0014] Through this technical solution, by combining a preset state prediction model, a joint dynamics model, and the transmission characteristics of the joint module, this application can accurately predict the operating state and required current of the joint module in the future time window, thereby identifying potential current peak risks in advance and providing forward-looking data support for the subsequent determination of the optimal current protection threshold, effectively avoiding performance loss or safety hazards that may be caused by hysteresis protection.

[0015] Optionally, step S4 includes: The dynamic current protection threshold and the predicted future current peak value within the future prediction time window are obtained, resulting in a dynamic current protection threshold sequence and a future current peak value sequence. Calculate the difference between the dynamic current protection threshold sequence and the future current peak sequence at each time point to obtain the difference sequence; Based on the difference sequence, risk points where future current peak values ​​exceed the dynamic current protection threshold are identified, and a risk point time set is obtained. Based on the risk point time set, the risk time sequence is obtained, and it is determined whether the risk time sequence exceeds the preset maximum allowable overload time. If the risk timing time does not exceed the maximum allowable overload time, the dynamic current protection threshold is adjusted according to the maximum difference of the difference sequence and the preset adjustment coefficient to obtain the optimal current protection threshold. If the risk timing exceeds the maximum allowable overload time, the dynamic current protection threshold is adjusted according to the preset rules to obtain the optimal current protection threshold, and the risk information is fed back to the controller, which then readjusts the robot's state.

[0016] Optionally, step S5 includes: Obtain the actual output current of the joint module; Based on the optimal current protection threshold, a first current threshold and a second current threshold are determined. The first current threshold is less than the optimal current protection threshold, and the second current threshold is equal to the optimal current protection threshold. If the actual output current is greater than or equal to the first current threshold and less than the second current threshold, a first warning message is sent to the controller. If the actual output current is greater than or equal to the second current threshold, the joint module is current-limited and the current operating status information of the robot body is obtained. Based on the current operating status information, determine whether the robot body is in an abnormal state; If the robot body is in an abnormal state, the joint module will be shut down for protection. Record protection operation information and feed the recorded information back to the controller. The protection operation information includes at least one of the following: first warning information, current limiting output operation, and shutdown protection operation.

[0017] Secondly, this application provides an adaptive dynamic current protection device for use in robots, including: The acquisition module is used to acquire the running status information and task condition information of the joint module. The first determining module is used to determine the dynamic current protection threshold of the joint module based on the operating status information and task condition information. The prediction module is used to predict the future operating status of the joint module based on the operating status information, and to determine the future peak current of the joint module based on the future operating status. The second determining module is used to determine the optimal current protection threshold of the joint module based on the dynamic current protection threshold and the future current peak value. The protection module is used to monitor the actual output current of the joint module in real time and to perform graded protection of the joint module based on the actual output current and the optimal current protection threshold.

[0018] Thirdly, this application provides an electronic device including a processor and a memory, the memory storing computer-readable instructions, which, when executed by the processor, perform the steps of the adaptive dynamic current protection method provided in the first aspect above.

[0019] Fourthly, this application provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, performs the steps of the adaptive dynamic current protection method provided in the first aspect above.

[0020] As described above, the adaptive dynamic current protection and related equipment provided in this application acquires the operating status information and task condition information of the joint module, dynamically determines the current protection threshold based on this information, and determines the future current peak value by combining it with the prediction of future operating status. This, in turn, comprehensively determines the optimal current protection threshold, ultimately achieving hierarchical protection of the joint module. This method effectively solves the problem in existing technologies where a single fixed current protection threshold cannot distinguish between "benign overload" and "fault overload," avoiding the drawback of falsely triggering protection due to brief current peaks when the robot is performing highly dynamic tasks, thus limiting the robot's performance. Through real-time monitoring and hierarchical protection, this application can adaptively adjust the protection strategy according to the actual operating status and task requirements of the robot, enabling the joint module to fully release its performance while ensuring safety, thereby improving the reliability, task continuity, and safety of the embodied intelligent robot in complex dynamic environments.

[0021] Other features and advantages of this application will be set forth in the following description and will be apparent in part from the description or may be learned by practicing embodiments of this application. The objectives and other advantages of this application may be realized and obtained by means of the structures particularly pointed out in the written description and the accompanying drawings. Attached Figure Description

[0022] Figure 1 This is a flowchart of an adaptive dynamic current protection method provided in an embodiment of this application.

[0023] Figure 2 This is a schematic diagram of the adaptive dynamic current protection device provided in the embodiments of this application.

[0024] Figure 3 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. Detailed Implementation

[0025] 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 a part of the embodiments of this application, and not all of the embodiments. The components of the embodiments of this application described and shown in the accompanying drawings can generally be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of this application provided in the accompanying drawings is not intended to limit the scope of the claimed application, but merely represents selected embodiments of this application. All other embodiments obtained by those skilled in the art based on the embodiments of this application without inventive effort are within the scope of protection of this application.

[0026] It should be noted that similar reference numerals and letters in the following figures indicate similar items; therefore, once an item is defined in one figure, it does not need to be further defined and explained in subsequent figures. Furthermore, in the description of this application, terms such as "first," "second," etc., are used only to distinguish descriptions and should not be construed as indicating or implying relative importance.

[0027] In a first aspect, this application provides an adaptive dynamic current protection method for robots, comprising the following steps: S1. Obtain the running status information and task condition information of the joint module; S2. Determine the dynamic current protection threshold of the joint module based on the operating status information and task condition information; S3. Based on the operating status information, predict the future operating status of the joint module, and determine the future peak current of the joint module based on the future operating status; S4. Determine the optimal current protection threshold for the joint module based on the dynamic current protection threshold and the future peak current. S5. Monitor the actual output current of the joint module in real time, and perform graded protection for the joint module based on the actual output current and the optimal current protection threshold.

[0028] Specifically, the adaptive dynamic current protection method proposed in this application is applied to robots. Its core lies in its ability to intelligently adjust the current protection strategy of the joint module based on the robot's actual operating environment and task requirements. The joint module is the core component for achieving precise motion control in a robot, typically composed of motors, reducers, sensors, and controllers. Operating status information refers to the physical quantities of the joint module at a given moment, such as joint position, velocity, and output torque. This information can be acquired in real-time by sensors within the joint module. Task condition information refers to the type of task the robot is currently performing and its load data, such as running, walking, and jumping. This information is usually provided by the robot's upper-level controller. The dynamic current protection threshold is a variable upper limit value for the current, which is adjusted according to the robot's operating status and task condition to adapt to different working scenarios. The future operating status refers to the motion trend of the joint module over a future period, obtained through a prediction algorithm. The future current peak value refers to the maximum current value that the joint module may reach under the predicted future operating status. The optimal current protection threshold is the final threshold determined after comprehensively considering the dynamic current protection threshold and the future current peak value, used to guide actual current protection. Graded protection refers to taking different levels of protection measures based on the relationship between the actual output current and the optimal current protection threshold, such as early warning, current limiting, or shutdown.

[0029] In step S1, the operating status information and task condition information of the joint module are acquired. The operating status information may include the joint's position, velocity, and output torque. This information can be acquired through various sensors installed on the joint module. For example, position information can be acquired through an encoder, velocity information can be acquired by differentiating the position information or through a velocity sensor, and output torque can be obtained through a torque sensor or estimated from the motor current. Task condition information refers to the load data of the robot performing tasks, such as running, walking, and jumping. This information can be provided by the robot's upper-level task planning system or determined by the robot's internal state recognition module. For example, when the robot performs a "running" task, the upper-level controller sends the corresponding condition information to the protection system.

[0030] In step S2, the dynamic current protection threshold of the joint module is determined based on the operating status information and task condition information. The purpose of this step is to calculate a dynamic threshold that reflects the robot's current current tolerance based on its actual working conditions. For example, when the robot is performing a high-explosive task, the dynamic current protection threshold can be appropriately increased to allow the joint module to output a larger current in a short period of time; while when performing delicate operations, the dynamic current protection threshold can be decreased to ensure the accuracy and safety of the operation.

[0031] In step S3, the future operating state of the joint module is predicted based on the operating status information, and the future peak current of the joint module is determined based on the future operating state. This step aims to identify potential overcurrent risks in advance by predicting the future movement trend of the joint module. For example, based on the current position information, speed, and output torque of the joint module, combined with a preset kinematic and dynamic model, the position and speed changes of the joint module within a future time window can be predicted. Based on these predicted future movement states, the torque that the joint module may need in the future can be further estimated, and finally, the possible future current value can be calculated, thereby determining the future peak current.

[0032] In step S4, the optimal current protection threshold for the joint module is determined based on the dynamic current protection threshold and the future current peak value. This step is one of the core innovations of this application, as it combines the dynamically adjusted protection threshold with the prediction of future risks to form a more intelligent and robust protection strategy. For example, if it is predicted that the current peak value may exceed the current dynamic current protection threshold at some future moment, the system can fine-tune the dynamic current protection threshold in advance to avoid unnecessary protection triggering, or take measures in advance when necessary.

[0033] In step S5, the actual output current of the joint module is monitored in real time. Based on the actual output current and the optimal current protection threshold, the joint module is subjected to graded protection. This step is the final execution stage, which takes corresponding protection measures based on the actual current situation and the determined optimal protection threshold. For example, when the actual output current approaches the optimal current protection threshold, an early warning message can be issued; when the actual output current reaches or exceeds the optimal current protection threshold, current limiting can be implemented, and even shutdown protection can be implemented in extreme cases.

[0034] The adaptive dynamic current protection method of this application, through the synergistic effect of the above steps, can effectively solve the limitations of the "one-size-fits-all" protection strategy in the prior art. Traditional methods rely solely on fixed current thresholds and cannot distinguish between "benign overload" generated when robots perform highly dynamic tasks and "fault overload" caused by genuine faults. This leads to frequent false triggering of protection when the robot needs high burst force or to cope with external disturbances, thereby affecting the continuity of tasks and the performance of the robot.

[0035] Compared with existing technologies, the advantages of this application are as follows: First, it can adaptively adjust the protection threshold according to the task conditions and operating status, making the protection strategy more flexible and intelligent, and avoiding the false protection problem caused by traditional fixed thresholds. Second, it introduces the prediction of future current peaks, making the protection strategy forward-looking and able to deal with potential overcurrent risks in advance, further improving the robustness and reliability of the system. Third, through a hierarchical protection mechanism, this application can take different levels of protection measures according to the degree of current over-limit, thereby minimizing the impact on robot task execution while ensuring safety. These improvements enable the robot to operate stably and efficiently in more complex and dynamic environments, significantly improving the reliability and task continuity of embodied intelligent robots.

[0036] In some implementations, step S2 includes: Obtain the static current protection value of the joint module; Based on the task operating condition information, consult the preset operating condition adaptive control factor form to obtain the operating condition adaptive control factor; determine the time decay constant based on the thermodynamic model of the joint module and the experimental data of actual operation. The peak boundary current of the operating condition is calculated based on the adaptive control factor of the operating condition, the time decay constant, and the first current preset based on the maximum demagnetizing current of the joint module. Based on the operating status information, the position of the joint module on the robot body, and the task requirements, determine the first weighting factor of the thermal protection boundary and the second weighting factor of the working condition peak boundary. The dynamic current protection threshold is calculated based on the static current protection value, the peak boundary current under operating conditions, the first weighting factor, and the second weighting factor.

[0037] Specifically, the static current protection value of the joint module is obtained. This static current protection value is usually based on the motor thermal protection setting, which aims to ensure that the motor will not be damaged due to overheating during long-term operation.

[0038] Specifically, based on task condition information, such as running, walking, and jumping, the system utilizes task condition information provided by the upper-level controller to consult pre-defined forms based on the physical characteristics and system pressure tolerance of different conditions, thereby obtaining the corresponding adaptive control factor. This adaptive control factor quantifies the tolerance of the joint module to current surges under different task scenarios, enabling the protection strategy to distinguish between benign overloads and fault overloads, thus preventing false triggering of protection due to brief current peaks when the robot performs highly dynamic tasks.

[0039] In practical applications, a time decay constant is determined based on the physical thermodynamic model of the joint module and experimental data from actual operation. This time decay constant characterizes the dynamic characteristics of the joint module's temperature rise and heat dissipation after a short-term overload, allowing the joint module to withstand currents exceeding the static threshold for a certain period of time, and safely limiting the current back to the normal range over time. This enables the joint module to briefly break through static limitations and fully release its performance when dealing with instantaneous impacts or explosive force demands, while avoiding damage caused by prolonged overload, thus solving the "one-size-fits-all" problem of traditional protection strategies.

[0040] Based on this, and combining the obtained adaptive control factor for operating conditions, time decay constant, and the first current preset based on the maximum demagnetizing current of the joint module, the peak boundary current of the operating conditions is calculated. This peak boundary current reflects the upper limit of the instantaneous current that the joint module can withstand under specific operating conditions and short-term overload capacity.

[0041] Furthermore, based on the operational status information, the position of the joint module on the robot body, and the task requirements—for example, determining whether the joint module is a finger joint used for fine manipulation or a leg joint used for support and movement—the priority of fine control or the degree of high burst power required by the joint module in the current task is determined, thereby establishing a first weighting factor for the thermal protection boundary and a second weighting factor for the peak operating condition boundary. These weighting factors are used to balance the contributions of static thermal protection and dynamic peak operating condition protection in the final threshold calculation.

[0042] Finally, the dynamic current protection threshold of the joint module is calculated based on the static current protection value, the peak boundary current under operating conditions, the first weighting factor, and the second weighting factor. This dynamic current protection threshold comprehensively considers the long-term thermal stability, short-term overload capacity, and the specific requirements of the current task conditions of the joint module.

[0043] In some preferred embodiments, a specific example is given below. Suppose a robot joint module is performing a "walking" task, and its task condition information is identified as low dynamic load. In this case, the system consults a preset adaptive control factor table and obtains a relatively small adaptive control factor. Simultaneously, because the "walking" task has high requirements for long-term stability and thermal protection, the first weighting factor (thermal protection boundary) is assigned a higher value, while the second weighting factor (peak load boundary) is relatively lower. The dynamically current protection threshold calculated thus will be more inclined towards the static current protection value to ensure long-term operational stability. When the robot joint module switches to performing a "jumping" task, the task condition information is identified as high dynamic, high burst force load. In this case, the system consults a table and obtains a larger adaptive control factor to allow for larger instantaneous current surges. Simultaneously, considering the instantaneous burst force requirements of the "jumping" task, the second weighting factor is assigned a higher value, while the first weighting factor is relatively lower. By combining the time decay constant determined by the thermodynamic model of the joint module, the calculated peak boundary current under operating conditions is significantly increased. This allows the final dynamic current protection threshold to enable the joint module to output higher current for a short period of time to complete the jumping action without immediately triggering the protection. This adaptive adjustment allows the robot to ensure both safety and full performance utilization in different task scenarios.

[0044] In some implementations, the peak boundary current of the operating condition is calculated according to the following formula: I_mode = k_mode * f(t) * I_set; In the formula, k_mode is the adaptive control factor for operating conditions, f(t) is the time decay constant, I_set is the preset first current, and I_mode is the peak boundary current of the operating conditions.

[0045] The proposed solution dynamically calculates the peak boundary current I_mode under different operating conditions by multiplying the adaptive control factor k_mode, the time decay constant f(t), and the preset first current I_set. The adaptive control factor k_mode is adjusted based on the current task operating conditions, reflecting the actual tolerance of the joint module to current surges under different task scenarios. The time decay constant f(t) is determined based on the thermodynamic model of the joint module and actual operating data, ensuring that the current limit of the joint module can safely return to the normal range over time after a short-term overload. The preset first current I_set provides a basic upper limit for the current. Through this multiplicative relationship, the peak boundary current I_mode can comprehensively consider the characteristics of the current task, the thermal dynamic response of the joint module, and its inherent current limit, thereby achieving a refined quantification of the current withstand capability of the joint module under different operating conditions.

[0046] Through the above technical solution, the calculation of the peak boundary current I_mode is no longer a single fixed value, but can be adaptively adjusted according to the actual operating conditions and the thermal dynamic characteristics of the joint module. This allows the protection strategy to effectively distinguish between "benign overload" and true "fault overload" that may occur when the robot performs highly dynamic tasks, avoiding false triggering of protection due to brief current peaks. This allows the joint module to briefly break through static limitations and fully release its performance when dealing with instantaneous impacts or explosive force demands, while avoiding damage caused by prolonged overload. This solves the "one-size-fits-all" problem of traditional protection strategies and significantly improves the operating efficiency and reliability of the robot system.

[0047] In some implementations, the dynamic current protection threshold is calculated according to the following formula: I_safe=a*I_thermal+b*I_mode; I_safe is the dynamic current protection threshold, I_thermal is the static current protection value, a is the first weighting factor, and b is the second weighting factor.

[0048] The solution in this application uses the above formula to weight and combine the static current protection value I_thermal with the peak boundary current I_mode, thereby achieving adaptive calculation of the dynamic current protection threshold I_safe. The static current protection value I_thermal ensures the thermal safety of the joint module during long-term operation, preventing damage caused by continuous overload. The peak boundary current I_mode allows the joint module to withstand higher current surges in a short period of time when performing highly dynamic tasks, based on actual operating conditions, thus fully utilizing its performance. The introduction of the first weighting factor a and the second weighting factor b allows the system to flexibly adjust the emphasis between static protection and dynamic adaptability according to the real-time operating status of the joint module and the current task requirements. For example, when the joint module is in a task requiring fine control, the first weighting factor a may be assigned a higher value to ensure stricter current limits; while when the joint module needs to provide high burst power, the second weighting factor b may be increased to allow for larger current peaks. This weighted calculation method enables the dynamic current protection threshold I_safe to accurately reflect the actual safety boundary of the joint module in different scenarios, avoiding the limitations of the traditional "one-size-fits-all" protection strategy.

[0049] In some implementations, the operating status information includes the current position, current speed, and current output torque of the joint module; Step S3 includes: Based on the current position, current speed and current output torque, and combined with the preset state prediction model, the future operating state of the joint module within the preset time window is predicted. The future motion state includes at least the future position, future speed and future acceleration. Based on the future motion state, combined with the joint dynamics model and the transmission characteristics of the joint module, the future torque information required by the joint module at each time point within the preset time window is obtained. Based on future torque information, the future current value generated by the joint module at each time point within a preset time window is determined according to the number of pole pairs and flux linkage parameters of the motor in the joint module and the preset electrode control strategy; and the future current peak value of the joint module is determined from the future current value.

[0050] The operational status information refers to the operational status data of the joint module at a specific moment, specifically including the current position, current speed, and current output torque of the joint module. The current position can refer to the rotational angle or linear displacement of the joint module, acquired in real time by position sensors such as encoders, Hall effect sensors, or potentiometers. The current speed can refer to the angular velocity or linear velocity of the joint module, obtained through differential calculation of the position information or using a speed sensor (such as a tachogenerator). The current output torque can refer to the actual torque output by the joint module, measured directly by a torque sensor or estimated using parameters such as motor current and voltage combined with a motor model. This information directly reflects the real-time operational status of the joint module, providing fundamental data for subsequent predictions of its future status.

[0051] The preset state prediction model refers to the mathematical model or algorithm used to predict the future operating state of the joint module. Specifically, it can employ physical model-based methods, such as Kalman filters, extended Kalman filters, or unscented Kalman filters, to establish the kinematic and dynamic equations of the joint module and combine them with sensor data for state estimation and prediction. Alternatively, it can use data-driven methods, such as deep learning models like recurrent neural networks (RNNs), long short-term memory networks (LSTMs), or gated recurrent units (GRUs), which learn the motion patterns and state evolution laws of the joint module by training on a large amount of historical operating data, thereby predicting the future state. When predicting the future operating state of the joint module within a preset time window, this model can output future motion state information such as future position, future velocity, and future acceleration. The preset time window refers to a future time period, for example, from tens to hundreds of milliseconds, depending on the real-time requirements of the robot task and the limitations of computing resources.

[0052] The joint dynamics model refers to the mathematical model describing the relationship between the motion and forces acting on the joint module. Specifically, it can be established using the Newton-Euler equations or the Lagrange equations. These models consider factors such as the mass, inertia, friction, and gravity of the joint module, and can calculate the required driving torque based on the joint's motion state. Transmission characteristics refer to the physical characteristics of the internal transmission mechanism (such as reducers and gear sets) of the joint module. This includes parameters such as reduction ratio and transmission efficiency. The reduction ratio is the ratio of the motor speed to the joint's output speed, and the transmission efficiency is the ratio of input power to output power. These parameters are necessary when converting the torque requirement at the joint level into the torque requirement at the motor level. By combining the joint dynamics model and the transmission characteristics of the joint module, the future torque information required by the joint module at each time point within a preset time window can be obtained, i.e., the torque that the motor needs to generate.

[0053] The predicted torque information T-pred required by the joint module can be used to obtain the predicted torque Tm-pred of the motor through the reduction ratio i and the transmission efficiency η, where T-pred=Tm-pred× i×η, Tm-pred= T-pred / ( i×η).

[0054] The number of pole pairs in a motor refers to the number of magnetic pole pairs on the motor rotor, and the flux linkage parameter refers to the degree of coupling between the motor windings and the magnetic field; these are inherent physical parameters of the motor. The preset electrode control strategy refers to the algorithm used to control the motor current to generate the required torque. Specifically, a field-oriented control (FOC) strategy can be used, such as the id=0 control strategy. This strategy simplifies the relationship between torque and q-axis current by controlling the d-axis current to zero, making torque control more direct.

[0055] Specifically, after obtaining the predicted torque of the motor, the currents of the two rotating axes d and q of the motor can be calculated using the following formula: Tm-pred=3 / 2·p·(λd·iq-λq·id), where p is the number of pole pairs of the motor, and λd and λq are the flux linkages of the motor's d and q axes (unit: Wb). The torque Tm-pred generated by the motor is determined by the d-axis current id and the q-axis current iq. After obtaining the expected motor torque, there may be countless combinations of (id, iq) that can produce the same torque value. In this case, it is necessary to combine the motor control strategy used by the controller to obtain the optimal (id, iq). For example, a motor control strategy with id=0 can be used. This strategy simplifies the torque formula to Tm-pred=(3 / 2)*p*λd*iq by setting the d-axis current id = 0, thus directly solving for the unique q-axis current iq. This strategy is simple to control, and the obtained (id, iq) value is in the rotating dq coordinate system. Subsequently, through inverse Park transformation, the (id, iq) coordinates in the dq coordinate system are transformed into the stationary α-β two-phase coordinate system by combining the real-time position and angle of the rotor. Next, through inverse Clark transformation, the two-phase currents in the α-β coordinate system are transformed into the final natural three-phase coordinate system, obtaining the expected instantaneous current values ​​of the motor's three-phase windings, i.e., the future current values ​​Ia, Ib, and Ic. After obtaining the three-phase current waveforms through the above transformations, the future peak current of the joint module can be analyzed.

[0056] As a preferred embodiment, the solution of this application is specifically implemented as follows: In a current protection system for the leg joint module of a bipedal robot, it is necessary to predict the future peak current of the joint module.

[0057] First, the current joint angle (position information) is obtained through an encoder installed on the joint module. The current angular velocity (speed information) is obtained by differential calculation of the encoder data. Finally, the current output torque is estimated using the current sensor and motor model inside the motor driver. For example, if the current position is 30 degrees, the current speed is 50 degrees / second, and the current output torque is 5 Nm.

[0058] Next, this operational status information is input into a preset state prediction model. This model is a neural network model based on LSTM (Long Short-Term Memory), which has been trained with a large amount of robot motion data and is capable of learning and predicting the motion trajectory of the joint modules. The preset time window is set to 100 milliseconds. Based on the input current position, velocity, and torque, the model predicts the future position, future velocity, and future acceleration at 10-millisecond intervals within the next 100 milliseconds. For example, it predicts that in the next 50 milliseconds, the joint position will be 35 degrees, the velocity will be 60 degrees / second, and the acceleration will be 100 degrees / second².

[0059] Then, based on the predicted future motion state, and combined with the joint dynamics model of the leg joint module (including parameters such as joint mass, inertia, friction, and gravity) and transmission characteristics (e.g., a reduction ratio of 100:1 and a transmission efficiency of 90%), the required future torque information of the motor at each time point within the next 100 milliseconds is calculated. For example, in the next 50 milliseconds, to achieve the predicted motion state, the motor needs to generate 0.5 Nm of torque.

[0060] Finally, based on this future torque information, combined with the number of pole pairs (e.g., 4 pole pairs) and flux linkage parameters of the motor in the joint module (e.g., 0.01 Weber flux linkage on the d-axis and 0.005 Weber flux linkage on the q-axis), and the preset id=0 control strategy, the future current values ​​generated in the motor windings at each time point within the next 100 milliseconds are determined. Specifically, the required motor torque is converted into d-axis and q-axis currents, and then the instantaneous current values ​​of the three-phase windings are obtained through inverse Park and inverse Clark transformations. These instantaneous current values ​​are analyzed to identify potential current peaks within the next 100 milliseconds. For example, it is predicted that the current peak may reach 15 amperes in the next 70 milliseconds.

[0061] Through the above technical solution, this method can accurately predict the future operating state and current peak of the joint module. This makes the determination of the dynamic current protection threshold more forward-looking and accurate, thus avoiding the problems of false protection or protection lag caused by inaccurate prediction in traditional methods. As a result, when the robot performs complex or highly dynamic tasks, the performance of its joint module can be fully utilized, while ensuring the safe operation and service life of the equipment.

[0062] In some implementations, step S4 includes: The dynamic current protection threshold and the predicted future current peak value within the future prediction time window are obtained, resulting in a dynamic current protection threshold sequence and a future current peak value sequence. Calculate the difference between the dynamic current protection threshold sequence and the future current peak sequence at each time point to obtain the difference sequence; Based on the difference sequence, risk points where future current peak values ​​exceed the dynamic current protection threshold are identified, and a risk point time set is obtained. Based on the risk point time set, the risk time sequence is obtained, and it is determined whether the risk time sequence exceeds the preset maximum allowable overload time. If the risk timing time does not exceed the maximum allowable overload time, the dynamic current protection threshold is adjusted according to the maximum difference of the difference sequence and the preset adjustment coefficient to obtain the optimal current protection threshold. If the risk timing exceeds the maximum allowable overload time, the dynamic current protection threshold is adjusted according to the preset rules to obtain the optimal current protection threshold, and the risk information is fed back to the controller, which then readjusts the robot's state.

[0063] Specifically, determining the optimal current protection threshold for the joint module first requires obtaining the dynamic current protection threshold and the predicted future current peak value within a future prediction time window. The future prediction time window refers to a preset time period during which the operating status of the joint module is predicted. The dynamic current protection threshold sequence refers to the dynamic current protection threshold corresponding to each time point within the future prediction time window; the future current peak value sequence refers to the predicted current peak value that the joint module may reach at each time point within the future prediction time window. Obtaining these sequences allows for fine-grained management of the current protection threshold adjustment based on the time dimension.

[0064] Furthermore, by calculating the difference between the dynamic current protection threshold sequence and the future current peak sequence at each time point, a difference sequence can be obtained. This difference sequence intuitively reflects the margin or over-limit situation between the predicted current peak and the current dynamic protection threshold at various future time points.

[0065] Based on this, and according to the difference sequence, risk points where future current peak values ​​exceed the dynamic current protection threshold can be identified, thus obtaining the risk point time set, i.e., T_risk={t_1, t_2, t_3, ..., t_m}, where m is the total number of risk points. Risk points refer to the time points when the predicted current peak value is higher than the dynamic current protection threshold; these points indicate potential overload risks.

[0066] Subsequently, based on the risk point time set, the risk timing time needs to be obtained to determine whether the risk timing time exceeds the preset maximum allowable overload time. The risk timing time refers to the length of time that the future current peak value continuously exceeds the dynamic current protection threshold. The maximum allowable overload time is a key parameter, and its setting is based on the physical characteristics, thermal capacity, and tolerance to instantaneous overload of the joint module, used to distinguish between benign instantaneous overload and harmful continuous overload.

[0067] If the judgment result indicates that the risk time series does not exceed the maximum allowable overload time, it means that the current overload is an acceptable instantaneous overload. At this point, the dynamic current protection threshold is adjusted based on the maximum difference in the difference sequence and a preset adjustment coefficient to obtain the optimal current protection threshold. This adjustment process is achieved using the formula I_soft(t) = I_safe(t) + α(t) * max{D(t_i)|t_i∈T_risk}, where I_soft(t) is the adjusted optimal current protection threshold, I_safe(t) is the original dynamic current protection threshold, T_risk is the risk point time set, t_i is the i-th specific time point in the risk point time set, and D(t_i) is the difference between the dynamic current protection threshold at time i and the future current peak value. α(t) is a gradual adjustment coefficient, whose value increases from 0 to its maximum value αmax within the risk time series according to the following formula. ; Where τ=∣t_i∣·Δ t , Δ t The sampling time interval; Where β is a preset adjustment coefficient, τmax is the maximum allowable overload time, and τ is the risk timing time. This adjustment method allows for a moderate increase in the protection threshold during acceptable short-term overload periods to avoid false triggering of protection, while ensuring that the protection threshold gradually tightens as the overload time increases, thereby balancing performance and safety.

[0068] Conversely, if the risk timing exceeds the maximum permissible overload time, it means the joint module faces a continuous overload risk, which may lead to damage. In this case, the dynamic current protection threshold is adjusted according to preset rules to obtain the optimal current protection threshold, and the risk information is fed back to the controller, which then readjusts the robot's state. The preset rules may include immediately reducing the protection threshold to a safe level or triggering more stringent protection measures. Feeding risk information to the controller aims to enable the robot system to respond promptly, such as slowing down, stopping, or adjusting the task execution strategy to avoid further damage to the joint module.

[0069] This application's solution addresses the limitations of traditional protection strategies in handling instantaneous overloads by introducing a refined analysis of the relationship between future peak currents and dynamic current protection thresholds, combined with risk assessment over a time dimension. Specifically, by acquiring dynamic current protection threshold sequences and future peak current sequences, the system can predict current change trends and protection needs over a future period. Calculating the difference sequence and identifying risk points allows the system to accurately pinpoint potential overload moments. Furthermore, by determining whether the risk timing exceeds the maximum permissible overload time, this solution can intelligently distinguish between "benign" instantaneous overloads and "malicious" sustained overloads. For benign instantaneous overloads, a progressively adjusting coefficient α(t) is introduced to dynamically increase the optimal current protection threshold, enabling the joint module to withstand higher currents in a short time, fully utilizing its performance potential, and avoiding the problem of limiting robot mobility due to overly conservative protection. For malicious sustained overloads, risk information is promptly fed back to the controller, and the protection threshold is adjusted to ensure timely and effective protection of the joint module, preventing damage caused by prolonged overload. This adaptive adjustment mechanism, based on time and risk level, makes protection strategies more flexible and intelligent.

[0070] In some preferred embodiments, a specific example is given below. Suppose a robot is performing a jumping task, and its leg joint modules generate a large electrical surge at the moment of takeoff and landing.

[0071] First, within the future prediction time window, the system acquires the dynamic current protection threshold sequence and the predicted future current peak sequence for the joint module. For example, at a certain time point t1, the predicted current peak is 15A, while the dynamic current protection threshold is 12A; at a certain time point t2, the predicted current peak is 18A, and the dynamic current protection threshold is 13A.

[0072] By calculating the difference sequence, it can be found that from t1 to t2, the predicted current peak value exceeds the dynamic current protection threshold, thus identifying these time points as risk points and forming a risk point time set.

[0073] The system then determines whether the risk time series formed by these risk points (e.g., 0.5 seconds from t1 to t2) exceeds the preset maximum allowable overload time (e.g., set to 0.8 seconds).

[0074] Since 0.5 seconds does not exceed 0.8 seconds, this indicates an acceptable instantaneous overload. At this point, the system dynamically adjusts the dynamic current protection threshold based on the maximum difference in the difference sequence (e.g., 18A-13A=5A at point t2) and the preset stepwise adjustment coefficient α(t). For example, at time t1, α(t) may be relatively small, causing the optimal current protection threshold I_soft(t1) to be slightly higher than I_safe(t1); while at time t2, as the risk timing time τ increases, the value of α(t) increases, causing I_soft(t2) to further increase, but still within a safe range. This allows the joint module to briefly output a higher current during the jump to complete a high-burst action without immediately triggering protection.

[0075] If an accident occurs during the jump, causing the current in the joint module to exceed the dynamic current protection threshold for an extended period—for example, if the risk timing reaches 1.0 second, exceeding the preset maximum allowable overload time of 0.8 seconds—the system will adjust the protection threshold according to preset rules (e.g., immediately reducing the optimal current protection threshold to the static protection value) and report the risk information to the controller. The controller may then instruct the robot to stop jumping or adjust its posture to reduce joint load, thereby preventing damage to the joint module due to prolonged overload.

[0076] In this way, the solution proposed in this application can intelligently cope with current surges in high-dynamic tasks of robots, and maximize the performance of the joint module while ensuring safety.

[0077] In some implementations, step S5 includes: Obtain the actual output current of the joint module; Based on the optimal current protection threshold, a first current threshold and a second current threshold are determined. The first current threshold is less than the optimal current protection threshold, and the second current threshold is equal to the optimal current protection threshold. If the actual output current is greater than or equal to the first current threshold and less than the second current threshold, a first warning message is sent to the controller. If the actual output current is greater than or equal to the second current threshold, the joint module is current-limited and the current operating status information of the robot body is obtained. Based on the current operating status information, determine whether the robot body is in an abnormal state; If the robot body is in an abnormal state, the joint module will be shut down for protection. Record protection operation information and feed the recorded information back to the controller. The protection operation information includes at least one of the following: first warning information, current limiting output operation, and shutdown protection operation.

[0078] Specifically, after monitoring the actual output current of the joint module in real time, two key protection limits are set based on the optimal current protection threshold: a first current threshold and a second current threshold. The first current threshold is set to be less than the optimal current protection threshold to provide an early warning trigger point; the second current threshold is set to be equal to the optimal current protection threshold as a trigger point for higher-level protection measures. This tiered threshold setting aims to provide multi-level protection responses for the joint module.

[0079] When the actual output current reaches or exceeds the first current threshold but is less than the second current threshold, the system sends a first warning message to the controller. This first warning message can be understood as a mild overload alert, designed to remind the controller to pay attention to the current status of the joint module so that the controller can adjust the robot's operating strategy in a timely manner, such as reducing the task load or adjusting the motion trajectory, to avoid further current increases.

[0080] Furthermore, when the actual output current reaches or equals the second current threshold, the system will perform a current-limiting output operation on the joint module. Current-limiting output refers to actively limiting the current flowing through the joint module by adjusting the output of the motor driver to prevent the current from continuously increasing and damaging the joint module. Simultaneously, at this stage, the system will also acquire the current operating status information of the robot body. This operating status information may include, but is not limited to, the robot's overall posture, balance, the load status of other joints, and environmental perception data, used to comprehensively determine whether the robot body is in an abnormal state. Abnormal states may include robot falls, collisions, jamming, or sensor malfunctions, which are often accompanied by abnormal current output from the joint module.

[0081] Based on this, if the current operating status information indicates that the robot itself is indeed in an abnormal state, the joint module will be immediately shut down for protection. Shutdown protection is the highest level of protection, designed to completely cut off the power output of the joint module to minimize further damage to the robot and its surrounding environment.

[0082] Finally, regardless of the protective measures taken (including sending an initial warning message, performing current limiting output operations, or executing shutdown protection operations), the relevant protection operation information will be recorded and fed back to the controller. This protection operation information is of great significance for subsequent fault diagnosis, performance analysis, and optimization of protection strategies. For example, the controller can use this recorded information to analyze the frequency and duration of overload occurrences and their correlation with specific tasks or environments, thereby adaptively adjusting the robot's behavior patterns or protection parameters.

[0083] This application's solution achieves refined, tiered protection for joint modules by introducing multi-level current thresholds and combining them with the robot's operating status assessment. Specifically, setting a first current threshold allows the system to issue an early warning before the current reaches a dangerous level, providing the controller with an opportunity for early intervention, thus avoiding unnecessary shutdowns and ensuring task continuity. When the current further increases and reaches the second current threshold, the system first implements current limiting measures. This is a flexible protection method that effectively suppresses current overload while also providing time to assess the overall condition of the robot. By acquiring and analyzing the robot's current operating status information, the system can distinguish between normal instantaneous overload (e.g., the robot performing a high-explosive action) and overload caused by robot abnormalities (e.g., falls or jamming). This differentiation mechanism avoids false shutdowns due to current peaks under normal high-load conditions, while ensuring that the highest level of shutdown protection can be implemented promptly when a true abnormality occurs, effectively preventing further damage to the robot. Recording protection operation information and feeding it back to the controller provides a data foundation for the system's self-learning and optimization, allowing the protection strategy to continuously improve with the accumulation of robot operating experience.

[0084] In some preferred embodiments, a specific example is given below. Suppose a robot is performing a task of moving a heavy object. Initially, the actual output current of the joint modules is within the normal range. As the robot accelerates or encounters resistance, the actual output current of a certain joint module begins to increase.

[0085] Specifically, when the actual output current reaches and exceeds a preset first current threshold (e.g., 80% of the optimal current protection threshold) but has not yet reached a second current threshold, the system will immediately send a first warning message to the robot controller. Upon receiving this warning, the controller can, according to a preset strategy, such as slightly reducing the robot's moving speed or adjusting the grasping posture, attempt to reduce the load on the joint module, thereby causing the current to fall back to a safe range.

[0086] If the current continues to rise and reaches or equals the second current threshold (i.e., the optimal current protection threshold), the system will immediately limit the current output of the joint module to prevent the current from rising further. Simultaneously, the system will quickly acquire information about the robot's current operating status. For example, it will use inertial measurement unit (IMU) data to determine if the robot has tilted or fallen, and use visual sensors to determine if the robot has collided with or gotten stuck on an obstacle.

[0087] If the robot's operating status information shows that the robot is in normal working condition (e.g., performing a high-explosive action, but with stable posture and no collision), the system will maintain current-limited output and continuously monitor, allowing the joint module to continue to complete the task under current-limited conditions, thus avoiding unnecessary downtime.

[0088] However, if the robot's operational status information indicates that the robot has malfunctioned (for example, IMU data shows that the robot is falling, or the vision system detects that the robot arm is stuck), the system will immediately implement a shutdown protection for the joint module to prevent further damage to the robot or a safety accident.

[0089] All these operations, including sending the first warning message, current limiting output, and shutdown protection, are recorded in detail and fed back to the robot controller. This recorded information can be used for subsequent fault analysis, such as analyzing under what task conditions warnings or current limiting are likely to be triggered, and the reasons for shutdown protection, thereby guiding the optimization of robot control algorithms or the improvement of hardware design.

[0090] Secondly, referring to Figure 2 This application provides an adaptive dynamic current protection device for use in robots, including: Module 21 is used to acquire the running status information and task condition information of the joint module; The first determining module 22 is used to determine the dynamic current protection threshold of the joint module based on the operating status information and task condition information. The prediction module 23 is used to predict the future operating status of the joint module based on the operating status information, and to determine the future peak current of the joint module based on the future operating status. The second determining module 24 is used to determine the optimal current protection threshold of the joint module based on the dynamic current protection threshold and the future current peak value. The protection module 25 is used to monitor the actual output current of the joint module in real time and to perform graded protection of the joint module based on the actual output current and the optimal current protection threshold.

[0091] The acquisition module 21 can be configured to acquire the operating status information and task condition information of the joint module. In one implementation, the acquisition module 21 may include a series of sensors, such as encoders, speed sensors, and torque sensors, which are directly integrated into the joint module to collect joint position information, velocity, and output torque in real time. Furthermore, the acquisition module 21 can also interact with the robot's upper-level controller via wired or wireless communication interfaces to receive task condition information, such as load data from running, walking, and jumping. In some embodiments, the acquisition module 21 can be a standalone hardware unit that integrates data acquisition circuitry and a communication interface, responsible for preprocessing raw sensor data and external command information and transmitting it to other modules.

[0092] The first determining module 22 can be configured to determine the dynamic current protection threshold of the joint module based on the operating status information and task condition information provided by the acquiring module 21. This module can be an embedded processor internally storing preset lookup tables, algorithm models, or rule sets. For example, the first determining module 22 can consult a preset adaptive control factor table based on the current task condition to obtain the adaptive control factor; and, combined with the time decay constant determined by the thermodynamic model of the joint module and experimental data from actual operation, as well as the static current protection value set based on motor thermal protection, calculate the dynamic current protection threshold. In practical applications, the first determining module 22 can be a digital signal processor (DSP) or a microcontroller (MCU) specifically responsible for performing complex mathematical operations and logical judgments.

[0093] The prediction module 23 can be configured to predict the future operating state of the joint module based on the operating state information provided by the acquisition module 21, and determine the future peak current of the joint module based on the future operating state. This module can be a high-performance computing unit that internally stores the kinematic and dynamic models of the robot joint. For example, the prediction module 23 can predict the future operating state of the joint module within a preset time window, including future position and future speed information, based on the current position, current speed, and current output torque of the joint module, combined with the preset joint kinematic and dynamic models. Subsequently, based on these future motion states, combined with the joint dynamic model and the transmission characteristics of the joint module, the future torque information required by the joint module at each time point within the preset time window is obtained, and finally, based on the future torque information and the motor control parameters of the joint module, the future current value generated by the joint module at each time point within the preset time window is determined, thereby determining the future peak current.

[0094] The second determining module 24 can be configured to determine the optimal current protection threshold of the joint module based on the dynamic current protection threshold output by the first determining module 22 and the future current peak value output by the prediction module 23. This module can be a logic processing unit internally implementing comparison and adjustment algorithms. For example, the second determining module 24 can acquire the dynamic current protection threshold sequence and the predicted future current peak value sequence within a future prediction time window, calculate the difference between the two at each time point, and obtain a difference sequence. Subsequently, based on the difference sequence, it identifies risk points where the future current peak value exceeds the dynamic current protection threshold, obtains a risk point time set, and determines whether the risk timing exceeds the preset maximum allowable overload time. If the risk timing does not exceed the maximum allowable overload time, the dynamic current protection threshold is adjusted according to the maximum difference in the difference sequence and a preset adjustment coefficient to obtain the optimal current protection threshold. If the risk timing exceeds the maximum allowable overload time, the dynamic current protection threshold is adjusted according to a preset rule to obtain the optimal current protection threshold, and the risk information is fed back to the controller.

[0095] The protection module 25 can be configured to monitor the actual output current of the joint module in real time and perform graded protection on the joint module according to the optimal current protection threshold determined by the second determining module 24. This module may include a current sensor and an actuator interface. For example, the protection module 25 can acquire the actual output current of the joint module in real time and determine a first current threshold and a second current threshold based on the optimal current protection threshold. If the actual output current is greater than or equal to the first current threshold and less than the second current threshold, a first warning message is sent to the controller. If the actual output current is greater than or equal to the second current threshold, current limiting is applied to the joint module, and the current operating status information of the robot body is acquired to determine if there is an abnormal state in the robot body. If an abnormal state exists, the joint module is shut down for protection. Simultaneously, the protection module 25 records protection operation information and feeds the recorded information back to the controller. The protection operation information includes at least one of the first warning message, current limiting output operation, and shutdown protection operation. The protection module 25 can be a dedicated controller integrating current detection, logic judgment, and execution control functions.

[0096] The core innovation of this application lies in its device's ability to implement "adaptive" and "predictive" mechanisms. First, through the acquisition module 21 and the first determination module 22, the device can dynamically determine a dynamic current protection threshold that better suits the current actual needs based on the joint module's operating status information and task condition information. For example, when the robot performs a running task, the device recognizes this as a highly dynamic and high-load condition, allowing the joint module to withstand higher current peaks within a certain range, avoiding false protection by traditional methods in such scenarios. Second, through the prediction module 23 and the second determination module 24, the device further introduces the prediction of future operating states and future current peaks. This means that the protection strategy is no longer solely based on the current instantaneous state, but can anticipate potential overcurrent risks and adjust the optimal current protection threshold in advance. For example, if it is predicted that the robot is about to perform a jump action that will generate a brief but high current peak, the device can adjust the optimal current protection threshold before the jump occurs, allowing the robot to complete the action smoothly without triggering protection due to a brief current surge.

[0097] The adaptive dynamic current protection device provided in this embodiment is used to perform the steps in the adaptive dynamic current protection method provided in the first aspect above. The principle of the adaptive dynamic current protection device provided in this embodiment is the same as that of the adaptive dynamic current protection method provided in the first aspect above, and will not be discussed in detail here.

[0098] Please refer to Figure 3 , Figure 3 This application provides a schematic diagram of the structure of an electronic device 13, comprising a processor 1301 and a memory 1302. The processor 1301 and the memory 1302 are interconnected and communicate with each other via a communication bus 1303 and / or other forms of connection mechanism (not shown). The memory 1302 stores computer-readable instructions executable by the processor 1301. When the electronic device is running, the processor 1301 executes the computer-readable instructions to perform the method in any optional implementation of the above embodiments, thereby achieving the following functions: acquiring the running status information and task condition information of the joint module; determining the dynamic current protection threshold of the joint module based on the running status information and task condition information; predicting the future running status of the joint module based on the running status information, and determining the future current peak value of the joint module based on the future running status; determining the optimal current protection threshold of the joint module based on the dynamic current protection threshold and the future current peak value; monitoring the actual output current of the joint module in real time, and performing graded protection of the joint module based on the actual output current and the optimal current protection threshold.

[0099] This application provides a computer-readable storage medium storing a computer program thereon. When the computer program is executed by a processor, it performs the method in any optional implementation of the above embodiments to achieve the following functions: acquiring the operating status information and task condition information of the joint module; determining the dynamic current protection threshold of the joint module based on the operating status information and task condition information; predicting the future operating status of the joint module based on the operating status information, and determining the future current peak value of the joint module based on the future operating status; determining the optimal current protection threshold of the joint module based on the dynamic current protection threshold and the future current peak value; monitoring the actual output current of the joint module in real time, and performing graded protection of the joint module based on the actual output current and the optimal current protection threshold. The computer-readable storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as Static Random Access Memory (SRAM), Electrically Erasable Programmable Read-Only Memory (EEPROM), Erasable Programmable Read Only Memory (EPROM), Programmable Red-Only Memory (PROM), Read-Only Memory (ROM), magnetic storage, flash memory, magnetic disk, or optical disk.

[0100] In the embodiments provided in this application, it should be understood that the disclosed apparatus and methods can be implemented in other ways. The apparatus embodiments described above are merely illustrative. For example, the division of units is only a logical functional division, and there may be other division methods in actual implementation. Furthermore, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Additionally, the coupling or direct coupling or communication connection shown or discussed may be through some communication interface; the indirect coupling or communication connection between apparatuses or units may be electrical, mechanical, or other forms.

[0101] Furthermore, the units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0102] Furthermore, the functional modules in the various embodiments of this application can be integrated together to form an independent part, or each module can exist independently, or two or more modules can be integrated to form an independent part.

[0103] In this document, relational terms such as first and second are used only to distinguish one entity or operation from another entity or operation, without necessarily requiring or implying any such actual relationship or order between these entities or operations.

[0104] The above description is merely an embodiment of this application and is not intended to limit the scope of protection of this application. Various modifications and variations can be made to this application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the scope of protection of this application.

Claims

1. A self-adaptive dynamic current protection method applied to a robot, characterized in that, The method comprises the steps of: S1. obtaining the running state information and task working condition information of the joint module; S2. determining the dynamic current protection threshold of the joint module according to the running state information and the task working condition information; S3. predicting the future running state of the joint module according to the running state information, and determining the future current peak value of the joint module according to the future running state; S4. determining the optimal current protection threshold of the joint module according to the dynamic current protection threshold and the future current peak value; S5. monitoring the actual output current of the joint module in real time, and performing hierarchical protection on the joint module according to the actual output current and the optimal current protection threshold.

2. The adaptive dynamic current protection method of claim 1, wherein, Step S2 comprises: obtaining the static current protection value of the joint module; According to the task working condition information, the preset working condition adaptive control factor table is consulted to obtain the working condition adaptive control factor; According to the thermodynamic model of the joint module and the actual running experimental data, the time decay constant is determined; According to the working condition adaptive control factor, the time decay constant and the preset first current based on the maximum demagnetization current of the joint module, the working condition peak boundary current is calculated; According to the running state information and the position of the joint module on the robot body and the task demand, the first weight factor of the thermal protection boundary and the second weight factor of the working condition peak boundary are determined; According to the static current protection value, the working condition peak boundary current, the first weight factor and the second weight factor, the dynamic current protection threshold is calculated.

3. The adaptive dynamic current protection method of claim 2, wherein, The working condition peak boundary current is calculated according to the following formula: I_mode=k_mode* f(t)*I_set; In the formula, k_mode is the working condition adaptive control factor, f(t) is the time decay constant, I_set is the preset first current, and I_mode is the working condition peak boundary current.

4. The adaptive dynamic current protection method of claim 3, wherein, The dynamic current protection threshold is calculated according to the following formula: I_safe=a*I_thermal+b*I_mode; I_safe is the dynamic current protection threshold, I_thermal is the static current protection value, a is the first weight factor, and b is the second weight factor.

5. The adaptive dynamic current protection method of claim 1, wherein, The running state information includes the current position, current speed and current output torque of the joint module; Step S3 comprises: According to the current position, current speed and current output torque, the future running state of the joint module in the preset time window is predicted by combining the preset state prediction model, and the future motion state includes future position, future speed and future acceleration; According to the future motion state, the future torque information required by the joint module at each time point in the preset time window is obtained by combining the joint dynamics model and the transmission characteristics of the joint module; According to the future torque information, the future current value generated by the joint module at each time point in the preset time window is determined based on the number of pole pairs and flux linkage parameters of the motor in the joint module and the preset electrode control strategy; and the future current peak value of the joint module is determined from the future current value.

6. The adaptive dynamic current protection method of claim 1, wherein, Step S4 comprises: obtaining the dynamic current protection threshold and the predicted future current peak value in the future prediction time window to obtain the dynamic current protection threshold sequence and the future current peak value sequence; a difference value sequence is obtained by calculating the difference between the dynamic current protection threshold sequence and the future current peak value sequence at each time point; a risk point time set is obtained by identifying the risk points at which the future current peak value exceeds the dynamic current protection threshold according to the difference value sequence; a risk timing time is obtained according to the risk point time set, and it is determined whether the risk timing time exceeds a preset maximum allowable overload time; if the risk timing time does not exceed the maximum allowable overload time, the dynamic current protection threshold is adjusted according to the maximum difference value of the difference value sequence and a preset adjustment coefficient to obtain an optimal current protection threshold; if the risk timing time exceeds the maximum allowable overload time, the dynamic current protection threshold is adjusted according to a preset rule to obtain an optimal current protection threshold, and risk information is fed back to the controller, and the state of the robot is re-adjusted by the controller.

7. The adaptive dynamic current protection method of claim 1, wherein, Step S5 includes: obtaining the actual output current of the joint module; determining a first current threshold and a second current threshold according to the optimal current protection threshold, the first current threshold being less than the optimal current protection threshold, and the second current threshold being equal to the optimal current protection threshold; if the actual output current is greater than or equal to the first current threshold and less than the second current threshold, sending a first warning information to the controller; if the actual output current is greater than or equal to the second current threshold, performing current limiting output on the joint module, and obtaining the current running state information of the robot body; determining whether the robot body has an abnormal state according to the current running state information; if the robot body has an abnormal state, performing shutdown protection on the joint module; recording protection operation information, and feeding back the recorded information to the controller, wherein the protection operation information includes at least one of the first warning information, the current limiting output operation, and the shutdown protection operation.

8. An adaptive dynamic current protection device applied to a robot, characterized in that, It includes: an acquisition module for acquiring the running state information and task working condition information of the joint module; a first determination module for determining the dynamic current protection threshold of the joint module according to the running state information and the task working condition information; a prediction module for predicting the future running state of the joint module according to the running state information, and determining the future current peak value of the joint module according to the future running state; a second determination module for determining the optimal current protection threshold of the joint module according to the dynamic current protection threshold and the future current peak value; a protection module for monitoring the actual output current of the joint module in real time, and performing graded protection on the joint module according to the actual output current and the optimal current protection threshold.

9. An electronic device, comprising: It includes a processor and a memory, the memory stores computer readable instructions, when the computer readable instructions are executed by the processor, the steps of the adaptive dynamic current protection method in any one of claims 1-7 are run.

10. A computer-readable storage medium having stored thereon a computer program, characterized in that, The computer program is executed by the processor to run the steps of the adaptive dynamic current protection method in any one of claims 1-7. The computer program is executed by the processor to run the steps of the adaptive dynamic current protection method in any one of claims 1-7.

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