Inspection robot autonomous charging dynamic control system

Abstract

The invention discloses an autonomous charging dynamic control system for an inspection robot, and relates to the technical field of inspection robot management, and the system comprises a condition triggering module, a robot sensing module, a task decision module, a dynamic charging control module, a safety monitoring module and a log recording module. When a new inspection task packet is issued to a waiting or charging robot, a condition triggering module starts judgment, and a robot sensing module collects real-time electric quantity, task attributes and a charging pile state and encapsulates data; the task decision module calculates a task emergency degree and constructs a priority, and compares a charging basic priority to trigger a temporary or safe charging strategy; the dynamic charging control module dynamically adjusts charging parameters or calls safety parameters according to the dynamic charging parameters; the safety monitoring module monitors and intervenes in the charging process in real time, the log recording module records key operation and abnormity, and the system can dynamically adapt to task requirements, improves response efficiency and safety and is suitable for complex inspection scenes.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of inspection robot management, and more particularly to a dynamic control system for autonomous charging of an inspection robot. BACKGROUND

[0002] In the field of inspection robot management, with the development of automation and intelligent technology, the autonomous charging capability of inspection robots has become a key factor in improving system operation efficiency. However, existing autonomous charging technology for inspection robots still has deficiencies in task assignment and coordination of charging tasks, dynamic scheduling strategies, and charging efficiency optimization, etc., which may lead to problems such as insufficient power or charging conflicts during task execution, affecting the overall system operation efficiency and reliability.

[0003] After searching, a charging pile dynamic scheduling method for adapting to real-time task of artificial intelligence transport robot is disclosed in patent CN114435175B. This patent dynamically calculates the number of charging piles required based on charging pile management strategies and the state of charge of the work robot, and allocates charging resources as needed, thereby improving the utilization efficiency of charging piles and the overall power level of the robot fleet. However, this technical solution has a simple coordination mechanism for task and charging priority, which may lead to delays in the execution of key inspection tasks due to charging tasks in a multi-task concurrent scenario, affecting the response speed and task completion rate of the system.

[0004] After searching, a parking lot dynamic charging task allocation method and device for a multi-robot system is disclosed in patent CN118052401B. This patent divides the parking lot into regions using a clustering algorithm and uses utility value evaluation and alliance information updating to achieve dynamic allocation of charging tasks, improving the robustness and efficiency of task allocation. However, this technical solution lacks a comprehensive evaluation mechanism for the real-time power state of the inspection robot and the urgency of the task, which may lead to inaccurate allocation of charging tasks and inability to meet the efficient charging needs of the inspection robot in complex task environments.

[0005] In summary, existing autonomous charging technology for inspection robots still has certain deficiencies in task and charging priority coordination, flexibility of dynamic scheduling strategies, and adaptability to complex environments. SUMMARY

[0006] In view of the deficiencies of the prior art, the purpose of the present application is to overcome the fundamental contradiction in the prior art that the autonomous charging strategy of the inspection robot lacks an energy supply model and control strategy that is targeted at a single robot, faces specific task requirements, and has fine prediction and dynamic adaptive capability, especially in complex inspection scenarios with multiple concurrent tasks and urgent time windows, the existing system cannot intelligently calculate the minimum power supply and the optimal power supply rate, thereby causing the technical problems of limited task response speed, completion rate, system reliability, and continuous operation capability.

[0007] Therefore, the present application provides an autonomous charging dynamic control system for an inspection robot, which can perceive the task state of the inspection robot and environmental changes in real time, and on this basis, deeply integrates the task urgency, accurate power consumption prediction, and charging pile performance parameters, thereby dynamically and adaptively adjusting the charging strategy to ensure that the inspection robot can efficiently complete various inspection tasks with the minimum charging time cost.

[0008] To achieve the above purpose, the present application provides the following technical solutions: An autonomous charging dynamic control system for an inspection robot, comprising: A condition triggering module triggers a task linkage logic judgment condition when a task dispatch platform issues a new inspection task package to a waiting or charging inspection robot; A robot perception module acquires real-time power data of the inspection robot, a newly dispatched inspection task package attribute, and a current working state parameter of the charging pile, and encapsulates the acquired information into a structured data package; A task decision module calculates a task urgency according to the newly dispatched inspection task package attribute, constructs a dispatched task priority according to the task urgency, compares the dispatched task priority with a preset charging task basic priority, and triggers a temporary power supply strategy or a safe power supply strategy according to the comparison result; A dynamic charging control module calculates the minimum power supply required to complete the new inspection task package according to the real-time power data, the newly dispatched inspection task package attribute, and a preset basic energy consumption when the temporary power supply strategy is triggered, dynamically adjusts the charging parameters according to the minimum power supply, the battery state of the inspection robot, and the charging pile restrictions, and retrieves a preset safe charging parameter when the safe power supply strategy is triggered; A safety monitoring module monitors various operating parameters of the battery in real time, and performs real-time intervention and feedback calibration on the charging process according to a preset safety threshold.

[0009] Further, the temporary power supply strategy includes a high dispatched task processing step and a temporary power supply step. The high-dispatch task processing step triggers a temporary power compensation mode and starts a power dynamic calculation strategy to calculate the minimum power compensation required to complete the task when the current battery level of the inspection robot reaches a first node; when the current battery level of the inspection robot does not reach the first node, a time-consuming dynamic calculation strategy is started to calculate the estimated total time of task completion and the available charging time before the task deadline, and it is decided whether to compensate power or transfer the task; The temporary power compensation step performs real-time charging parameter dynamic adjustment, temperature real-time monitoring, and power calibration feedback after starting the power dynamic calculation strategy.

[0010] Further, the safety power compensation strategy includes a low-dispatch task processing step, which starts a safety power compensation mode and periodically feeds back the real-time power state of the inspection robot and the time required to fully charge to the task dispatch platform, while setting task priority update instructions and task feasible power as wake-up conditions.

[0011] Further, the power dynamic calculation strategy includes an average power consumption retrieval sub-step, a total estimated power consumption calculation sub-step, and a minimum power compensation calculation sub-step; The average power consumption retrieval sub-step retrieves the average power consumption of all inspection points in the task package from the preset task power consumption database; The total estimated power consumption calculation sub-step accumulates the power consumption of all inspection points in the task package to obtain the total estimated power consumption of completing the newly dispatched task; The minimum power compensation calculation sub-step calculates the minimum power compensation required to complete the task according to the current real-time power of the inspection robot and the total estimated power consumption.

[0012] Further, the time-consuming dynamic calculation strategy includes a chargeable time calculation sub-step and a condition judgment sub-step; The chargeable time calculation sub-step accumulates the inspection time required by all inspection points in the task package and calculates the available charging time according to the task deadline; The condition judgment sub-step compares the time required for the inspection robot to reach the first node with the available charging time, and outputs a task transfer instruction or a power compensation instruction.

[0013] Further, the temporary power compensation strategy further includes a step of ladder power compensation. If the conditional judgment sub-step outputs a power compensation instruction, the step of ladder power compensation includes calculating a remaining chargeable time according to the available charge time and the time required for the estimated power of the inspection robot to reach a first node, calculating a temporary power compensation power according to the remaining chargeable time and the additional power to be compensated, performing power limitation evaluation and thermal safety evaluation at the temporary power compensation power, and if both evaluations are safe and up to standard, performing ladder power compensation, which reflects charging at a regular charging power to the first node and then automatically switching to a temporary charging power to charge the additional power to be compensated; if either evaluation is not safe and up to standard, the current task is abandoned and a task transfer instruction is output.

[0014] Further, the dynamic power calculation strategy further includes a real-time current calculation sub-step. The real-time current calculation sub-step includes calculating a theoretical current value for reaching the target power according to the difference between the target power and the current power, the remaining charge time, and the preset charging efficiency and average charging voltage, calculating a temperature correction coefficient by a piecewise function according to the real-time temperature of the battery, calculating a remaining capacity correction coefficient according to the current battery state of charge percentage, and calculating a power limitation correction current according to the theoretical current value, the temperature correction coefficient, and the remaining capacity correction coefficient, and selecting the maximum value between the power limitation correction current and the minimum protection current as the final real-time charging current.

[0015] Further, the safety monitoring module includes a temperature double monitoring strategy. The double monitoring strategy includes two different sets of temperature safety thresholds. According to the comparison between the monitored real-time temperature and the temperature safety threshold, a power reduction instruction or a switching regular instruction is output.

[0016] Further, the task decision module includes an urgency determination strategy. The urgency determination strategy includes calculating an urgency coefficient of the task according to the deadline of the newly dispatched inspection task package in the task package attribute, setting a coefficient range corresponding to the task urgency level one by one in a corresponding table, and indexing the task urgency level in the corresponding table according to the urgency coefficient.

[0017] Further, a log recording module is included. When a charging pile fails, the communication between the inspection robot and the charging pile is interrupted, the communication between the inspection robot and the task dispatching platform is interrupted, and the battery temperature abnormally rises, an emergency response instruction is output, and an unforgeable transaction log of all key operation processes is generated and stored.

[0018] The beneficial effects of the present application are: 1. The condition trigger module captures the new task dispatch signal in real time, combines the robot perception module to accurately obtain the task attributes such as the deadline and the inspection point information, and then combines the real-time state of the robot, and the task decision module constructs a dynamic priority based on the task urgency, when the priority of the new task is higher, the temporary power compensation strategy is triggered, and the minimum power compensation required to complete the task is accurately calculated through the power dynamic calculation strategy, avoiding task delay caused by excessive charging, when the priority of the task is lower, the safe power compensation strategy is started and the task wake-up mechanism is maintained, which solves the problem of simple task and charging priority coordination and response lag in the prior art in the multi-task concurrent scene, significantly improves the response speed of the emergency task and the overall task completion rate, and is especially suitable for complex inspection scenes with urgent time window; 2. The dynamic charging control module dynamically adjusts the charging parameters through the minimum power compensation calculation combined with the real-time power, task energy consumption and charging pile limit, in the temporary power compensation mode, the power is accurately supplemented through the step power compensation step; in the safe power compensation mode, the preset safety parameters are used to ensure the stability of the charging, compared with the extensive mode of charging full power and then executing the task in the prior art, the unnecessary charging time is greatly reduced in the present application, the minimum charging cost meets the task demand, and the continuous operation ability of the inspection robot is improved; 3. The safety monitoring module adopts temperature double monitoring strategy and power limitation evaluation, combines the temperature correction coefficient and the remaining capacity correction coefficient in the real-time current calculation sub-step, dynamically limits the charging current, and avoids damage caused by battery overheating or high capacity stage large current charging; at the same time, the safe power compensation strategy sets the wake-up condition through periodic feedback power state, and ensures that the charging process is controllable, which significantly reduces the risk of battery failure and prolongs the service life of the inspection robot and the charging pile. BRIEF DESCRIPTION OF DRAWINGS

[0019] Figure 1 is the overall flowchart in the present application; Figure 2 is the temporary power compensation strategy flowchart in the present application; Figure 3 is the safe power compensation strategy flowchart in the present application. DETAILED DESCRIPTION

[0020] The present application will be further described in detail below in combination with the drawings and examples. Wherein the same parts are denoted by the same reference numerals. It should be noted that the words "front", "back", "left", "right", "up" and "down" used in the following description refer to the directions in the drawings, and the words "bottom surface" and "top surface", "inner" and "outer" refer to the directions towards or away from the geometric center of a particular part.

[0021] Due to the fundamental contradiction between the existing patrol robot autonomous charging strategy and the energy supply model and control strategy that are targeted at a single robot, oriented to specific task requirements, and have refined prediction and dynamic self-adaptation capabilities, especially in complex patrol scenarios with multiple tasks concurrently and tight time windows, the existing system cannot intelligently calculate the minimum amount of replenishment and the optimal charging rate, which leads to technical problems such as limited task response speed, completion rate, system reliability and continuous operation capability. Therefore, the present invention discloses a patrol robot autonomous charging dynamic control system, which can solve the fundamental contradiction between the existing patrol robot autonomous charging strategy and the energy supply model and control strategy that are targeted at a single robot, oriented to specific task requirements, and have refined prediction and dynamic self-adaptation capabilities, especially in complex patrol scenarios with multiple tasks concurrently and tight time windows, the existing system cannot intelligently calculate the minimum amount of replenishment and the optimal charging rate, which leads to technical problems such as limited task response speed, completion rate, system reliability and continuous operation capability.

[0022] In order to achieve the above-mentioned purpose, the present invention provides a patrol robot autonomous charging dynamic control system, which comprises: at least one patrol robot, at least one charging pile and a task dispatching platform, the control part is as follows: Figure 1 As shown, it includes: a condition trigger module, a robot perception module, a task decision module, a dynamic charging control module, a safety monitoring module and a log recording module.

[0023] Specifically, when the inspection robot starts the charging process, that is, when the inspection robot is at the designated position and the charging interface at the bottom is aligned with or connected to the charging interface of the charging pile or enters the wireless charging sensing area of ​​the charging pile, the conditional trigger module automatically activates the task linkage trigger monitoring state. In this state, if the task dispatching platform sends a new inspection task package containing a unique task identifier to the inspection robot through the message queue protocol, when the conditional trigger module receives this information, it determines that the trigger condition has been met and immediately starts the preset linkage logic judgment mechanism.

[0024] At the same time, the robot perception module simultaneously performs three types of core information collection operations, including: First, the current battery power data of the inspection robot is collected in real time. This data is retrieved in real time by the inspection robot's built-in battery management system. The power data includes the current state of charge of the battery, as well as the real-time voltage, real-time current and internal temperature of the battery pack; Second, fully obtain all attribute information of the newly assigned inspection task package. Task attribute information includes but is not limited to the task unique identifier, task type, task creation time, task deadline, the number of inspection points included in the task, the specific three-dimensional coordinates of each inspection point, the specific sensor detection tasks required to be performed at each inspection point (infrared temperature measurement, voiceprint analysis, gas detection, etc.), and the device identification code corresponding to each inspection point; Third, query the current real-time working status parameters of the charging pile, including the maximum output charging power supported by the charging pile, the current actual output power, the current output voltage, the current output current, the internal ambient temperature of the charging pile, the charging gun interface temperature, and the fault status identification of the charging pile.

[0025] After receiving the information collected by the robot perception module, the task decision module calculates the real-time urgency of the task based on the deadline of the newly dispatched inspection task package. The urgency is calculated through the urgency coefficient K=1 / (task deadline-current time). According to the calculation result of the urgency coefficient K, the task decision module further determines the urgency level of the task: if K≥0.5, it is judged as a "high urgency task"; if 0.2≤K<0.5, it is judged as a "medium urgency task"; if K<0.2, it is judged as a "low urgency task".

[0026] Subsequently, the module establishes a dynamic priority conversion formula based on the three types of urgency levels to determine the final priority of the newly assigned task. The assigned task priority = n × urgency level, where n is the coefficient, and the urgency coefficient level is an integer value, specifically defined as: high urgency corresponds to level 3, medium urgency corresponds to level 2, and low urgency corresponds to level 1.

[0027] After the calculation is completed, the module compares the priority of the dispatch task with the default priority of the charging task: if the calculated dispatch task priority is greater than m, it is determined that the priority of the dispatch task is higher than the current charging task, and the temporary power replenishment strategy is triggered, and the control is transferred to the high-priority dispatch task processing; conversely, if the dispatch task priority is less than or equal to m, it is determined that the priority of the dispatch task is lower than or equal to the current charging task, and the safe power replenishment strategy is triggered, and the control is transferred to the low-priority dispatch task processing.

[0028] like Figure 2 As shown in the figure, the temporary power replenishment strategy includes a high-priority task dispatching processing step, and performs two logical branch processing according to the current real-time power status of the inspection robot; The first logical branch is: when the current battery level of the inspection robot is greater than the first node, which is 20% of the total capacity of the battery, the temporary power supplement mode is triggered, and the internal power dynamic calculation strategy is started. The power dynamic calculation strategy first retrieves the average power consumption of all inspection points in the task package from a preset task power consumption database. The task power consumption database is generated by machine learning algorithm training based on historical inspection data, which records the average energy consumption value of each inspection point under different environmental types, different equipment types, different sensor usage modes, and different inspection path complexities.

[0029] The power dynamic calculation strategy accumulates the power consumption of all inspection points in the task package to obtain the total estimated power consumption for completing the newly assigned task Then, combined with the current real-time power of the inspection robot , the minimum power supplement required to complete the task is calculated The calculation formula is: Wherein is the estimated basic energy consumption loss of the inspection robot during task execution. If the calculated value is less than or equal to zero, it indicates that the existing power of the inspection robot is sufficient to complete the task, and the system will immediately send a stop charging instruction to the charging pile and a task execution instruction to the inspection robot to terminate charging and execute the task immediately. If the value is greater than zero, it indicates that supplementary charging is needed, and the system will enter the charging parameter adjustment stage.

[0030] The second logical branch is: when the current battery level of the inspection robot is less than or equal to the first node, the high-priority task dispatching step first calculates two time parameters. The first parameter is the estimated total time for task completion which is based on the optimization planning of the paths between all inspection points in the inspection task package and the accumulation of the time required for each inspection point to execute the inspection, including sensor startup, data collection, preliminary processing, etc. The second parameter is the available charging time before the task deadline which Then, by communicating with the charging pile control system, the safe charging parameters are queried, including the constant charging power that the charging pile can provide in the normal mode Then, the estimated time required to charge from the current power of the inspection robot to the first node of the total capacity of the battery is calculated which is: Wherein is the rated total capacity of the battery of the inspection robot.

[0031] If the calculated value is greater than If the value is less than 0, it means that the inspection robot cannot complete the necessary charging and perform the task before the task deadline. The system will immediately start the task transfer mechanism and send a task transfer request to the task dispatch platform, along with the transfer reason, such as insufficient time. Value is less than or equal to When the value is , it means that there is enough time to recharge before the task ends. At this time, the remaining available charging time is calculated. , and the additional power required On this basis, the temporary charging power required to complete the remaining power replenishment is calculated ,That: , where 3600 is the time unit conversion factor.

[0032] The temporary power replenishment strategy also includes a step-by-step power replenishment step. Conduct a rigorous safety assessment, first, determine Is it less than or equal to the maximum safe charging power of the charging pile? Secondly, call a built-in battery thermal simulation model, which is based on the material properties, internal resistance, current ambient temperature and estimated charging power of the inspection robot battery. Real-time prediction is performed to ensure that the battery core temperature does not exceed the safety temperature threshold of 45 degrees Celsius at this power. If the value is within the maximum safe power limit and the thermal simulation model predicts that the battery temperature will not exceed the limit, the system will perform step-by-step charging, first with the normal charging power. Charge until the inspection robot battery reaches the first node, which is 20% of the total capacity; then the charging power will automatically switch to the temporary charging power , and continue charging until the target charge is reached. If the value exceeds the maximum safe charging power limit of the charging pile or the thermal simulation model predicts that the battery temperature will exceed the preset threshold, the system will abandon the current task and transfer the task to other inspection robots in the same area that have sufficient power and are currently idle through the task dispatch platform.

[0033] When charging parameters need to be improved, the dynamic power calculation strategy can accurately calculate the current power, charging efficiency, charging pile power limit, target power, and total charging time to obtain the charging current that should be executed at each moment. The real-time charging current is sent to the safety monitoring module and the log recording module in the form of a data table. The specific calculation steps include: First, the basic demand current Calculation, Indicates the theoretical current value required to reach the target power within the remaining time. The calculation formula is:

[0034] wherein, is the theoretical current value, is the target electric quantity, is the current remaining capacity, is the total capacity of the battery, is the average charging voltage, is the charging efficiency, is the total charging time, is the charged time; Second, the calculation of the temperature correction coefficient is used to quantify the impact of battery temperature on charging acceptance ability, and the correction coefficient adopts a segmented function form:

[0035] wherein, is the temperature correction coefficient, is the battery temperature, when the battery temperature is lower than or equal to 25℃, the correction coefficient increases linearly with the temperature, when the battery temperature is higher than 25℃ and less than 45℃, the correction coefficient decreases linearly with the temperature, when the battery temperature reaches or exceeds 45℃, the correction coefficient is set to 0.5, so as to strictly limit the charging current and prevent the battery from being damaged by overheating.

[0036] Third, the calculation of the remaining capacity correction coefficient is used to reflect the acceptance ability of the battery to the charging current at different states of charge, and its calculation formula is:

[0037] wherein, is the capacity correction coefficient, when the remaining state of charge is 20%, =1.0, indicating that the battery has a higher charging acceptance ability at this time, when the remaining state of charge is 80%, =0.4, indicating that the charging current should be reduced at this time to avoid battery damage or life decay caused by large current charging at high capacity stage.

[0038] Fourth, the calculation of the power limitation correction represents the actual available charging current after considering the maximum output power limitation of the charging pile, and its calculation formula is:

[0039] wherein, is the limited current, is the charging pile power limitation, is the current charging voltage; ​​​Fifth, the final execution current Based on all the above factors, the system determines the final real-time charging current to be applied to the battery, which is calculated as follows:

[0040] Wherein, is the final execution current, is the minimum protection current, which is preset to ensure the stability of the charging connection and prevent the charging process from being accidentally interrupted due to too small charging current.

[0041] After the high-priority task processing starts the temporary power compensation mode, the temporary power compensation mode performs three linkage operations in real time to ensure the accuracy, efficiency and safety of the charging process; First, dynamic adjustment of charging parameters: based on the minimum power compensation calculated dynamically and the specified power compensation time , An adaptive proportional control algorithm is deployed to dynamically adjust the output voltage and current of the charging pile, and the system ensures that the power compensation task is accurately completed within the specified power compensation time.

[0042] Second, real-time temperature monitoring: using a "double monitoring mechanism" to ensure that the battery temperature is within a safe range, a high-precision infrared probe is built into the charging pile to non-contact monitor the real-time temperature of the battery surface of the inspection robot at a sampling frequency of 1 per second, at the same time, multiple NTC thermistor sensors are integrated inside the battery pack of the inspection robot to accurately monitor the core temperature of the battery at a sampling frequency of 2 per second, when the temperature monitored by any sensor reaches 40 degrees Celsius, the system will automatically start the power derating mechanism, immediately reduce the current charging power, when the temperature monitored by any sensor reaches 45 degrees Celsius, the system will immediately send an instruction to the charging pile to suspend the current fast charging mode and forcibly switch to the preset regular charging mode to quickly reduce the battery temperature and ensure the safety of the battery.

[0043] Third, power calibration feedback: every 30 seconds, the actual charging capacity of the inspection robot is compared with the theoretical calculated value calculated by the power dynamic calculation module based on the current charging parameters, the actual charging capacity is accurately measured by the coulomb meter built into the BMS, if the deviation between the two exceeds the threshold, which is the acceptable calibration error threshold, the system will automatically trigger the power calibration program to re-evaluate and calibrate and values, this calibration mechanism aims to effectively deal with the aging phenomena such as capacity decay and internal resistance increase of the battery during long-term use, thereby avoiding insufficient or excessive power compensation due to the mismatch between the calculation model and the actual battery state, and ensuring the continuous accuracy of the charging strategy.

[0044] As shown in Figure 3 The safety power compensation strategy includes a low priority task dispatching processing step. When the task urgency and priority determination module determines that the priority of the newly dispatched task is lower than or equal to the priority of the current charging task, the safety power compensation mode is directly started. In this mode, the inspection robot will use the preset regular charging parameters for charging, and the charging process is not affected by the current power level of the inspection robot. During the execution of the safety power compensation mode, the real-time power state and the time required to fully charge of the inspection robot are fed back to the task dispatching platform periodically every 5 minutes. This feedback mechanism ensures that the task dispatching platform can master the state of the robot in real time, so as to perform subsequent task scheduling. In addition, two wake-up conditions are set to deal with sudden changes in task priority or to meet the task execution conditions in advance. The first wake-up condition is that if the task dispatching platform sends a task priority update instruction and the new priority is higher than the priority of the current charging task, the system will immediately interrupt the safety power compensation mode being executed and jump to the high priority task dispatching processing module to re-determine and execute the corresponding charging strategy.

[0045] The second wake-up condition is that if the current battery power of the inspection robot reaches the task feasible power, that is, the power reaches the sum of the estimated power consumption of the low priority task and 10% redundant power, the system will automatically push a prompt information to the task dispatching platform to inform that the robot has the ability to execute the task, and wait for the task execution instruction issued by the task dispatching platform.

[0046] If neither of the above two wake-up conditions is triggered during charging, the inspection robot will continue to perform safety power compensation until its battery reaches the full power state, and then automatically enters the standby state to wait for a new task instruction.

[0047] The security monitoring module is linked with the log recording module, the security monitoring module is used for monitoring the operation parameters of the battery in real time, the log recording module is used for continuously monitoring the system state in the linkage operation process of the whole inspection robot autonomous charging dynamic control system, and the output result of the security monitoring module is received, and an emergency mechanism is started for various sudden abnormal conditions, and all key operations are recorded in the log recording module; Specifically, if a charging pile fault occurs, such as overvoltage, overcurrent, internal communication interruption, charging module overheating and the like, the fault code reported by the charging pile internal diagnosis system, the communication interruption between the inspection robot and the charging pile, the communication interruption between the inspection robot and the task dispatching platform, and the abnormal temperature rise of the battery and the like, the log recording module will immediately start the emergency response mechanism, the emergency mechanism includes: immediately sending an emergency stop charging instruction to the charging pile; if the robot is executing a task, immediately send a task pause or return instruction to the inspection robot; at the same time, the system will start the sound and light alarm device, and the log recording module will also upload the detailed information of the abnormal event to the management platform in real time, including the abnormal type, the occurrence time, the involved device ID, the current system state parameter and the processing result, so as to perform remote monitoring and fault elimination.

[0048] All operation processes, including power change record, charging parameter adjustment (set value and actual value of voltage, current and power), mode switching (switching between temporary power compensation mode and safety power compensation mode) and detailed information of all abnormal events, generate non-tamperable transaction logs and are stored, the non-tamperable log data not only provides a reliable basis for subsequent fault analysis and responsibility identification of the system, but also provides high-quality training data and feedback mechanism for continuous iteration and performance optimization of various algorithm models.

[0049] The above is only the preferred embodiment of the present application, the protection scope of the present application is not limited to the above-mentioned embodiments, all technical solutions belonging to the idea of the present application belong to the protection scope of the present application. It should be pointed out that for ordinary skilled in the art, some improvements and decorations without departing from the principle of the present application, these improvements and decorations should also be regarded as the protection scope of the present application.

Claims

1. A patrol robot autonomous charging dynamic control system, characterized by: include: Condition trigger module: When the task dispatching platform sends a new inspection task package to the inspection robot that is waiting or charging, the task linkage logic judgment condition is triggered; The robot perception module obtains the current real-time power data of the inspection robot, the attributes of the newly dispatched inspection task package, and the current working status parameters of the charging pile, and encapsulates the above information into a structured data packet; A task decision module calculates the task urgency based on the attributes of the newly assigned inspection task package, establishes a dispatched task priority based on the task urgency, compares the dispatched task priority with a preset charging task basic priority, and triggers a temporary charging strategy or a safe charging strategy based on the comparison result; The dynamic charging control module calculates the minimum amount of charging required to complete the new inspection task package based on the real-time power data, the attributes of the newly dispatched inspection task package, and the preset basic energy consumption when the temporary charging strategy is triggered. The module dynamically adjusts the charging parameters based on the minimum amount of charging, the battery status of the inspection robot, and the charging pile limit. When the safe charging strategy is triggered, the module retrieves the preset safe charging parameters. The safety monitoring module monitors the various operating parameters of the battery in real time, and performs real-time intervention and feedback calibration on the charging process based on preset safety thresholds.

2. The autonomous charging dynamic control system for an inspection robot according to claim 1, characterized in that: The temporary power replenishment strategy includes a high dispatch task processing step and a temporary power replenishment step; The high dispatch task processing step, when the current battery power of the inspection robot reaches the first node, triggers the temporary power replenishment mode and starts the power dynamic calculation strategy to calculate the minimum power replenishment required to complete the task; When the current battery level of the inspection robot does not reach the first node, a dynamic time calculation strategy is activated to calculate the estimated total time to complete the task and the available charging time before the task deadline, and decide whether to recharge or transfer the task; The temporary power replenishment step performs real-time dynamic adjustment of charging parameters, real-time temperature monitoring, and power calibration feedback after the power dynamic calculation strategy is started.

3. The autonomous charging dynamic control system for an inspection robot according to claim 1, characterized in that: The safe power replenishment strategy includes a low-dispatching task processing step, which starts the safe power replenishment mode and periodically feeds back the real-time power status of the inspection robot and the estimated time required for full charging to the task dispatching platform, while setting the task priority update instruction and the task feasible power as wake-up conditions.

4. The autonomous charging dynamic control system for an inspection robot according to claim 2, characterized in that: The power dynamic calculation strategy includes an average power consumption retrieval sub-step, a total estimated power consumption calculation sub-step, and a minimum replenishment power calculation sub-step; The average power consumption retrieving sub-step is to retrieve the average power consumption of all inspection points in the task package from a preset task power consumption database; The total estimated power consumption calculation sub-step is to accumulate the power consumption of all inspection points in the task package to obtain the total estimated power consumption for completing the newly assigned task; The minimum power replenishment calculation sub-step calculates the minimum power replenishment required to complete the task based on the current real-time power consumption of the inspection robot and the total estimated power consumption.

5. The autonomous charging dynamic control system for an inspection robot according to claim 4, characterized in that: The time-consuming dynamic calculation strategy includes a rechargeable time-limited calculation sub-step and a condition judgment sub-step; The charging time limit calculation sub-step accumulates the inspection time required for all inspection points in the task package and calculates the available charging time based on the task deadline; The condition judgment sub-step estimates the time it takes for the inspection robot's power to reach the first node, compares it with the available charging time, and outputs a task transfer instruction or a power replenishment instruction.

6. The autonomous charging dynamic control system for an inspection robot according to claim 5, characterized in that: The temporary power replenishment strategy also includes a step-by-step power replenishment step. If the conditional judgment sub-step outputs a power replenishment instruction, the step-by-step power replenishment step includes calculating the remaining charging time based on the available charging time and the estimated time required for the inspection robot to reach the first node, calculating the temporary power replenishment power by combining the remaining charging time with the additional power required to be replenished, performing a power limit assessment and a thermal safety assessment under the temporary power replenishment power, and executing the step-by-step power replenishment if both meet safety standards. The step-by-step power replenishment reflects charging to the first node at the conventional charging power, and then automatically switching to the temporary charging power to complete charging the additional power required to be replenished. If any of the assessments fail to meet the safety standards, the current task will be abandoned and the task transfer instruction will be output.

7. The autonomous charging dynamic control system for an inspection robot according to claim 6, characterized in that: The dynamic power calculation strategy also includes a real-time current calculation sub-step, which includes calculating the theoretical current value required to reach the target power based on the target power, the difference between the current power, the remaining charging time, the preset charging efficiency, and the average charging voltage; calculating the temperature correction coefficient through a piecewise function based on the collected real-time battery temperature; calculating the remaining capacity correction coefficient based on the current battery state of charge percentage; calculating the power limit correction current based on the theoretical current value, the temperature correction coefficient, and the remaining capacity correction coefficient; and selecting the maximum value between the power limit correction current and the minimum protection current as the real-time charging current finally applied.

8. The autonomous charging dynamic control system for an inspection robot according to claim 7, characterized in that: The safety monitoring module includes a temperature dual monitoring strategy, which includes two sets of different temperature safety thresholds. According to the comparison between the monitored real-time temperature and the temperature safety threshold, a power reduction instruction is output or a normal instruction is switched.

9. The autonomous charging dynamic control system for an inspection robot according to claim 1, characterized in that: The task decision module includes an urgency determination strategy, which includes calculating the urgency coefficient of the task based on the deadline of the newly dispatched inspection task package in the task package attributes, setting a one-to-one correspondence table between the coefficient range and the task urgency level, and indexing the urgency coefficient into the corresponding table to the task urgency level.

10. The autonomous charging dynamic control system for an inspection robot according to claim 1, characterized in that: It also includes a log recording module, which outputs emergency response instructions when a charging pile failure occurs, communication between the inspection robot and the charging pile is interrupted, communication between the inspection robot and the task dispatch platform is interrupted, and the battery temperature rises abnormally. It also generates and stores tamper-proof transaction logs for all key operation processes.

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