Charging early warning method, device and equipment of mobile robot and readable storage medium

Abstract

The invention provides a charging early warning method, device and equipment for a mobile robot and a readable storage medium, and the method comprises the steps: building corresponding battery standard models according to historical charging key index parameters of different types of mobile robots; threshold values corresponding to the charging key indexes of the corresponding mobile robots are determined according to the different battery standard models, and the threshold values corresponding to the different charging key indexes of the mobile robots of different models are dynamically adjusted in combination with the current environment and the battery aging coefficient; and performing linkage charging early warning on the mobile robot according to the relationship between the current different charging key index parameters of the mobile robots of different models and the corresponding dynamic threshold values and the change trend of the current different charging key index parameters of the mobile robots of different models. According to the scheme, unified management of charging of the mobile robots of different manufacturers is achieved, more accurate early warning can be achieved through the charging early warning method combining threshold value early warning and change trend early warning, and early warning can be carried out by finding charging faults in the early stage.

Description

Technical Field

[0001] The present invention belongs to the technical field related to mobile robot charging, and in particular relates to a charging early warning method, device, equipment and readable storage medium for a mobile robot. Background Art

[0002] The statements in this section merely provide background information related to the present invention and do not necessarily constitute prior art.

[0003] Warehousing is a crucial component of modern logistics and plays a vital role in the logistics system. Introducing a large number of AMRs (autonomous mobile robots) in warehouse management can shorten sorting cycles by 30% to 50%. Especially during peak hours like e-commerce promotions, AMRs can respond more than twice as fast as manual labor, saving not only labor costs but also energy consumption by 40% and reducing cargo damage by over 99%.

[0004] However, current AMR devices come from different suppliers, the battery systems of AMR devices lack unified management, and charging history data is missing, which makes battery maintenance and management more difficult. Summary of the Invention

[0005] In order to overcome the shortcomings of the above-mentioned prior art, the present invention provides a charging warning method, device, equipment and readable storage medium for mobile robots, so as to realize unified management of charging of mobile robots from different manufacturers. Through the charging warning method that combines threshold warning and change trend warning, more accurate warning can be achieved.

[0006] In order to achieve the above object, the present invention adopts the following technical solutions: In a first aspect, the present invention provides a charging early warning method for a mobile robot, comprising: According to the key charging parameters of different models of mobile robots, corresponding battery standard models are established respectively; Determine the thresholds corresponding to the key charging indicators of the corresponding mobile robots according to different battery standard models, and dynamically adjust the thresholds corresponding to different key charging indicators of different models of mobile robots based on the current environment and battery aging coefficient; Based on the relationship between the current key charging indicator parameters of different models of mobile robots and the corresponding dynamic thresholds, as well as the changing trends of the current key charging indicator parameters of different models of mobile robots, a linkage charging warning is issued for the mobile robots.

[0007] Optionally, based on the historical charging key indicator parameters of different models of mobile robots, corresponding battery standard models are established, specifically: Collect key charging parameters of different types of mobile robots; Analyze the complete charging records of different models of mobile robots, calculate the charging efficiency of different models of mobile robots each time, and determine the standard charging efficiency range of different models of mobile robots; Based on the standard reference ranges of key charging indicators of different models of mobile robots and the standard charging efficiency ranges of different models of mobile robots, the initial battery standard models corresponding to different models of mobile robots are established; According to the collected maximum and minimum values ​​corresponding to each key charging indicator in the current preset historical time period of different models of mobile robots, combined with the standard reference range of each key charging indicator in the corresponding initial battery standard model, the standard reference range of each key charging indicator is updated to obtain the updated battery standard model of different models of mobile robots.

[0008] Optionally, the key charging indicators include current, voltage and temperature.

[0009] Optionally, the thresholds corresponding to different key charging indicators of different models of mobile robots can be dynamically adjusted based on the current environment and battery aging coefficient. Specifically: Dynamically adjust the current threshold of the mobile robot according to the battery aging coefficient, the temperature compensation coefficient, and the difference between the current battery temperature of the mobile robot and the reference temperature; Dynamically adjust the temperature threshold of the mobile robot based on the current reference temperature limit of the mobile robot, the difference between the current ambient temperature and the reference ambient temperature, and the impact factor of the battery health status on the temperature; The voltage threshold of the mobile robot is dynamically adjusted according to the influence factor of the battery health status on the voltage, the temperature compensation coefficient, the reference voltage threshold of the mobile robot, and the battery temperature rise deviation of the mobile robot.

[0010] Optionally, the changing trends of the current different charging key indicator parameters of the different models of mobile robots are determined as follows: According to the preset warning thresholds corresponding to the first-order derivatives and second-order derivatives of different key charging indicators, combined with the first-order derivatives and second-order derivatives of different key charging indicator parameters calculated at different times, it is determined whether the current key charging indicator parameters of the mobile robot show an abnormal change trend.

[0011] Optionally, the method further includes: determining whether to issue a charging warning for the mobile robot based on the relationship between the current battery temperature of different models of mobile robots and the Pearson correlation coefficient of the battery charging efficiency in the corresponding battery standard model, and a preset correlation coefficient threshold.

[0012] Optionally, it also includes: taking the key charging indicator parameters of the mobile robot as nodes, determining the causal dependency of the key indicator parameters through historical data, and forming a parameter causal network; according to the abnormal situation of the key charging indicator parameters, tracing back according to the parameter causal network, calculating the causal contribution of each node, and locating the root cause of the abnormality.

[0013] In a second aspect, the present invention provides a charging warning device for a mobile robot, comprising: A construction module is used to establish corresponding battery standard models based on the key charging indicator parameters of different models of mobile robots; The threshold dynamic adjustment module is used to determine the thresholds corresponding to the key charging indicators of the corresponding mobile robots according to different battery standard models, and dynamically adjust the thresholds corresponding to different key charging indicators of different models of mobile robots in combination with the current environment and battery aging coefficient; The linkage warning module is used to provide linkage charging warnings for mobile robots based on the relationship between the current key charging indicator parameters of different models of mobile robots and the corresponding dynamic thresholds, as well as the changing trends of the current key charging indicator parameters of different models of mobile robots.

[0014] In a third aspect, the present invention provides an electronic device comprising a memory and a processor, and computer instructions stored in the memory and executed on the processor, wherein the computer instructions, when executed by the processor, perform the method described in the first aspect.

[0015] In a fourth aspect, the present invention provides a computer-readable storage medium for storing computer instructions, wherein when the computer instructions are executed by a processor, the method described in the first aspect is performed.

[0016] One or more of the above technical solutions have the following beneficial effects: In the present invention, corresponding battery standard models are established based on the historical key charging indicator parameters of different models of mobile robots. The threshold values ​​corresponding to the key charging indicators of the corresponding mobile robots are determined based on the different battery standard models, and the threshold values ​​corresponding to the different key charging indicators of different models of mobile robots are dynamically adjusted in combination with the current environment and battery aging coefficient. Based on the relationship between the current key charging indicator parameters of different models of mobile robots and the corresponding dynamic threshold values, as well as the changing trends of the current key charging indicator parameters of different models of mobile robots, a coordinated charging warning is provided for the mobile robots. The solution of the present invention realizes the unified management of the charging of mobile robots from different manufacturers. Through the charging warning method that combines threshold warning and change trend warning, it can achieve more accurate warnings and can detect charging failures early and issue warnings.

[0017] Advantages of additional aspects of the present invention will be given in part in the following description and in part will be obvious from the following description, or will be learned through practice of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] The accompanying drawings, which constitute a part of the present invention, are used to provide a further understanding of the present invention. The exemplary embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute improper limitations on the present invention.

[0019] Figure 1 This is a flow chart of a charging warning method for a mobile robot according to an embodiment of the present invention; Figure 2 A schematic diagram of the process of constructing a battery standard model in an embodiment of the present invention; Figure 3 Schematic diagram of dynamic adjustment of thresholds corresponding to key charging indicators in an embodiment of the present invention; Figure 4 Schematic diagram of a charging warning device for a mobile robot according to an embodiment of the present invention; Figure 5 This is a structural block diagram corresponding to the computer device in an embodiment of the present invention. DETAILED DESCRIPTION

[0020] It should be noted that the following detailed descriptions are exemplary and intended to provide further explanation of the present invention. Unless otherwise specified, all technical and scientific terms used herein have the same meaning as commonly understood by those skilled in the art to which the present invention belongs.

[0021] It should be noted that the terms used herein are for describing particular embodiments only and are not intended to limit the exemplary embodiments according to the present invention.

[0022] In the absence of conflict, the embodiments of the present invention and the features thereof may be combined with each other.

[0023] First, the mobile robot involved in the charging early warning method for a mobile robot provided in this embodiment is introduced in detail.

[0024] Mobile robots, or AMR devices, are automatic guided vehicles, which are unmanned automated transport vehicles used for automatic transportation and handling in factories, warehouses and other places. AMRs are usually equipped with various sensors and navigation equipment, and can move independently in the workplace according to pre-set paths and behavior rules, and complete designated tasks. AMRs can be customized according to the layout and needs of the workplace. Common types include forklifts, carriers, trailers, etc. The application scope of AMRs includes but is not limited to raw material transportation, semi-finished product handling, finished product transportation, warehouse management, production line material replenishment and other fields. With the development of the logistics industry and the advancement of automation technology, warehousing AMR logistics carts are being used more and more widely in the field of warehousing and logistics, becoming one of the important tools to improve production efficiency and intelligence level.

[0025] A battery is a device that converts stored chemical energy into electrical energy. A battery consists of one or more cells, each containing a positive electrode, a negative electrode, and an electrolyte. When the battery is connected to an external circuit, ions in the electrolyte migrate from the negative electrode to the positive electrode under the influence of an electric field. Simultaneously, electrons flow from the negative electrode to the positive electrode through the external circuit, generating an electric current.

[0026] Figure 1 This is a flow chart of the charging warning method for a mobile robot provided in this embodiment, including: S101: Establish corresponding battery standard models based on historical charging key indicator parameters of different models of mobile robots.

[0027] Since mobile robots from different manufacturers have different models, by real-time monitoring of key charging parameter data of each AMR device, a dedicated battery model is established for each model of AMR, enabling centralized management of different AMR devices.

[0028] S102: Determine thresholds corresponding to key charging indicators of corresponding mobile robots according to different battery standard models, and dynamically adjust thresholds corresponding to different key charging indicators of different models of mobile robots in combination with the current environment and battery aging coefficient.

[0029] S103: Based on the relationship between different current key charging indicator parameters of different models of mobile robots and the corresponding dynamic thresholds, and the change trends of different current key charging indicator parameters of different models of mobile robots, a linkage charging warning is issued to the mobile robots.

[0030] This embodiment establishes corresponding battery standard models based on the historical charging key indicator parameters of different models of mobile robots; determines the threshold values ​​corresponding to the corresponding mobile robot charging key indicators based on the different battery standard models, and dynamically adjusts the threshold values ​​corresponding to the different charging key indicators of different models of mobile robots in combination with the current environment and battery aging coefficient; and performs a linked charging warning for the mobile robots based on the relationship between the current different charging key indicator parameters of different models of mobile robots and the corresponding dynamic threshold values, as well as the changing trends of the current different charging key indicator parameters of different models of mobile robots. This embodiment achieves unified management of the charging of mobile robots from different manufacturers. Through a charging warning method that combines threshold warnings with changing trend warnings, it can achieve more accurate warnings and can detect charging failures early and issue warnings.

[0031] like Figure 2 As shown, in S101, corresponding battery standard models are established according to the historical charging key indicator parameters of different models of mobile robots, including: S201: Collect key charging indicator parameters of different models of mobile robots.

[0032] Optionally, key charging indicator parameters of the mobile robot such as charging voltage, battery temperature, charging current, and changes in charging power.

[0033] S202: Analyze the complete charging records of each time of the mobile robots of different models, calculate the charging efficiency of each time of the mobile robots of different models, and determine the standard charging efficiency range of the mobile robots of different models.

[0034] In this embodiment, since the AMR charging action is a continuous process, this process is not a fixed time. During the production process of different demand scenarios, the AMR charging time will also change dynamically. Based on the real-time status data reported by each AMR, the start and end time of each charging is automatically analyzed, and a file is created for each AMR, recording in detail key parameters such as the equipment supplier of each AMR, the brand of key components, and the threshold range of operating parameters.

[0035] Through the real-time reporting of key charging data by each AMR, such as changes in charging voltage, battery temperature, charging current, and charging power, each charging process is dynamically monitored. By analyzing the complete historical records of each AMR charging, the charging efficiency of each time can be calculated, and the standard charging efficiency range can be determined based on the charging efficiency calculated each time.

[0036] As an implementation method, the key charging indicator parameters corresponding to each complete charging process of the AMR are obtained, and the charging event data that is completed normally and without errors is screened out, and the events of abnormal interruption, BMS error, and serious data loss are excluded. The average value and standard deviation of the charging efficiency of qualified charging events are calculated, according to the standard charging efficiency range: [ μ- N*σ, μ + M*σ ], where μ is the mean value and σ is the standard deviation. N and M The value of is determined according to the business tolerance, such as N=2, M=3.

[0037] S203: establishing initial battery standard models corresponding to different models of mobile robots based on the standard reference ranges of key charging indicators of different models of mobile robots and the standard charging efficiency ranges of different models of mobile robots.

[0038] The values ​​of key parameters of different AMRs are used as standard reference indicators. Through long-term historical data collection, a reasonable range of variation for each indicator is established, thereby establishing an initial standard model for the battery of each AMR device.

[0039] S204: Based on the collected maximum and minimum values ​​corresponding to each key charging indicator in the current preset historical time period of different models of mobile robots, combined with the standard reference range of each key charging indicator in the corresponding initial battery standard model, the standard reference range of each key charging indicator is updated to obtain the updated battery standard model of different models of mobile robots.

[0040] In this embodiment, the status history records of the past six months are collected, and the maximum and minimum values ​​of the corresponding charging key indicators within this range are counted. Combined with the normal working range of the AMR standard indicators, the charging key indicator variation range is set as a reasonable variation range of the charging key indicators.

[0041] Optionally, data is automatically updated at the end of each month, using the latest data to produce a new version of the AMR battery standard model. By comparing historical versions of the standard charging model, the changing trends of key parameters of the AMR battery can be analyzed.

[0042] As a possible implementation, a monitoring system connected to the charging equipment should collect key charging indicator data at regular intervals (e.g., every 10 minutes) over the past six months. These key charging indicators may include charging voltage, charging current, charging power, and battery temperature. To ensure data accuracy and integrity, the monitoring system should have high-precision sensors and reliable data transmission and storage capabilities. The collected charging data should be organized chronologically to form a status history. Each record should include the collection time and the values ​​of each key charging indicator at that moment. For example, at 10:00 AM on January 1, 2024, the charging voltage was X volts, the charging current was Y amperes, the charging power was Z kilowatts, and the battery temperature was T degrees Celsius. The organized status history records should be analyzed to determine the maximum and minimum values ​​collected for each key charging indicator.

[0043] The reasonable variation range of the key charging indicators is set by combining the maximum and minimum values ​​of the key charging indicators calculated in the past six months and the normal working range of the AMR standard reference indicators.

[0044] For example, if the maximum charging voltage recorded over the past six months is 235 volts and the minimum is 205 volts, the AMR charging voltage standard operating range is 200-240 volts. Taking into account practical conditions and a certain safety margin, the reasonable charging voltage range can be set to 195-245 volts, with the lower limit slightly lower than the standard lower limit by 5 volts and the upper limit slightly higher than the standard upper limit by 5 volts to accommodate possible temporary fluctuations.

[0045] Assuming the maximum charging current recorded over the past six months is 28 amps and the minimum is 6 amps, and the AMR charging current standard operating range is 5-30 amps, the charging current can be set within a reasonable range of 4-32 amps. The lower limit is 1 amp lower than the standard lower limit, and the upper limit is 2 amps higher than the standard upper limit. This accounts for actual extreme values ​​while ensuring a reasonable safety range.

[0046] In this embodiment S102, as Figure 3 As shown, the thresholds corresponding to the key charging indicators of the corresponding mobile robots are determined according to different battery standard models, and the thresholds corresponding to different key charging indicators of different models of mobile robots are dynamically adjusted in combination with the current environment and battery aging coefficient, including: S301: Dynamically adjust the current threshold of the mobile robot according to the battery aging coefficient, the temperature compensation coefficient, and the difference between the current battery temperature of the mobile robot and the reference temperature.

[0047] In this embodiment, the current threshold adjustment formula is:

[0048] in, is the adjusted current threshold, is the initial current threshold, α is the temperature compensation coefficient, ΔT is the difference between the current battery temperature and the reference temperature, is the battery aging coefficient.

[0049] S302: Dynamically adjust the temperature threshold of the mobile robot according to the current reference temperature limit value of the mobile robot, the difference between the current ambient temperature and the reference ambient temperature, and the impact factor of the battery health status on the temperature.

[0050] In this embodiment, the dynamic correction of the temperature threshold needs to comprehensively consider related factors such as ambient temperature, battery aging coefficient (SOH) and humidity. The specific formula can be expressed as follows:

[0051] in, The reference temperature limit, such as the maximum allowable temperature stated by the battery manufacturer; It is the ambient temperature compensation coefficient, which is used to correct the effect of ambient temperature on heat dissipation efficiency. For example, when the ambient temperature rises, the threshold needs to be lowered. is the difference between the current ambient temperature and the reference ambient temperature, that is , is the current ambient temperature, i.e. the real-time ambient measurement value, The reference ambient temperature is 25°C. is the influence factor of battery health status on temperature. For example, when SOH decreases, <1, the threshold is further lowered. It is the humidity compensation coefficient. When the ambient humidity exceeds the safe range, the threshold is dynamically adjusted downward. For example, when the humidity is >80%, additional correction is triggered.

[0052] S303: Dynamically adjust the voltage threshold of the mobile robot according to the impact factor of the battery health status on the voltage, the temperature compensation coefficient, the reference voltage threshold of the mobile robot, and the battery temperature rise deviation of the mobile robot.

[0053] In this embodiment, the voltage threshold is adjusted in combination with battery aging (SOH), internal resistance change, and temperature-related effects. The formula is:

[0054] in, is the adjusted voltage threshold; is the internal resistance compensation coefficient, internal resistance As the battery ages, the voltage drop increases, and the voltage upper limit needs to be lowered. is the impact factor of battery health status on voltage. For example, when SOH decreases by 10%, Decrease by 0.05; is the temperature compensation coefficient; is the battery temperature rise deviation, = is the actual battery temperature.

[0055] In this embodiment S103, based on the relationship between the current different charging key indicator parameters of different models of mobile robots and the corresponding dynamic thresholds, as well as the changing trends of the current different charging key indicator parameters of different models of mobile robots, a linkage charging warning is performed on the mobile robots, specifically: If the current key charging indicator parameters of different models of mobile robots exceed the corresponding dynamic thresholds, a charging warning will be triggered; According to the preset warning thresholds corresponding to the first-order derivatives and second-order derivatives of different key charging indicators, combined with the first-order derivatives and second-order derivatives of different key charging indicator parameters calculated at different times, it is determined whether the current key charging indicator parameters of the mobile robot show an abnormal change trend. If so, a charging warning is issued.

[0056] In this embodiment, early perception of dynamic evolution identifies abnormal parameter change trends through time series analysis, and issues early warnings before the dynamic threshold is broken. Abnormal trends such as voltage drops are identified through first-order derivative analysis 5 to 15 seconds before the threshold is triggered.

[0057] A time series analysis method based on a mathematical model is used to achieve trend warning. The core is to identify abnormal change trends in key charging indicator parameters through derivative calculation.

[0058] Set the time series data to be 】The monitoring value at the moment is explained using voltage as an example: First derivative (instantaneous rate of change):

[0059] Second derivative (changing acceleration):

[0060] Warning trigger conditions:

[0061] in = -0.5V / s, k=5~15 seconds.

[0062] This embodiment also includes: determining whether to issue a charging warning for the mobile robot based on the relationship between the current battery temperature of different models of mobile robots and the Pearson correlation coefficient of the battery charging efficiency in the corresponding battery standard model, and a preset correlation coefficient threshold.

[0063] As an implementation method, the correlation coefficient between battery temperature and charging efficiency is calculated as:

[0064]

[0065]

[0066]

[0067] in, For the i Battery temperature value at each sampling point; For the i Charging efficiency of each sampling point (%); represents the mean of the temperature series, ; ; represents the mean of the efficiency series; n Indicates the sequence length; For the j The charging efficiency value of each sampling point.

[0068] As an implementation method, determining whether to issue a charging warning to the mobile robot is specifically as follows:

[0069] In this embodiment, early warning is performed through the correlation coefficient between temperature and charging efficiency, which has significant advantages over traditional single-parameter threshold monitoring. It can detect hidden faults in advance, quantify performance degradation, and reduce false alarm rates.

[0070] In this embodiment, it also includes: taking the key indicator parameters of charging of the mobile robot as nodes, determining the causal dependency of the key indicator parameters through historical data, and forming a parameter causal network; according to the abnormal situation of the key indicator parameters of charging, tracing back according to the parameter causal network, calculating the causal contribution of each node, and locating the root cause of the abnormality.

[0071] Specifically, based on the key charging indicator parameters of the mobile robot, using historical data and linear non-Gaussian models or conditional independence test methods, combined with expert knowledge, different key charging indicator parameters are used as nodes to determine the causal dependency of the key indicator parameters and form a parameter causal network; based on historical data, conditional probabilities are calculated, such as the probability value of P (electrolyte decomposition | temperature anomaly), and the edge weights of the causal transmission links such as temperature anomaly → electrolyte decomposition → internal resistance increase → voltage fluctuation are determined.

[0072] Starting from the abnormal parameter, trace back to the possible upstream nodes along the parameter causal network (increased internal resistance → electrolyte decomposition → abnormal temperature), calculate the causal contribution of each node, such as calculating the intervention effect through the structural causal model (SCM), and then locate the root cause. Each root cause corresponds to a warning prompt. For example, the charging current is normal, but the current fluctuation frequency is strongly correlated with the vibration sensor data, which triggers the warning of "loose contactor"; or when the ambient humidity is >80%, the insulation resistance decreases 3 times faster, which triggers the "leakage risk in humid environment" prompt.

[0073] Among them, when constructing the parameter causal network, the key charging indicator parameters are not limited to voltage, current and temperature, but can also include SOH, internal resistance, charging efficiency, ambient temperature and humidity, vibration data, insulation resistance, current fluctuation frequency, etc.

[0074] This embodiment forms a parameter causal network with the key charging indicator parameters of the mobile robot as nodes. When an abnormality occurs in the key charging indicator parameters, the parameter causal network can be used to trace and locate the abnormality, realizing a complete closed loop of data collection → intelligent analysis → dynamic decision-making, and realizing active prediction from "single parameter exceeding the threshold" to "multi-parameter root cause location", significantly improving the accuracy of AMR battery safety management.

[0075] like Figure 4 As shown, this embodiment also provides a charging warning device for a mobile robot, including: A construction module is used to establish corresponding battery standard models based on the key charging indicator parameters of different mobile robot models; The threshold dynamic adjustment module is used to determine the thresholds corresponding to the key charging indicators of the corresponding mobile robots according to different battery standard models, and dynamically adjust the thresholds corresponding to different key charging indicators of different models of mobile robots in combination with the current environment and battery aging coefficient; The linkage warning module is used to provide linkage charging warnings for mobile robots based on the relationship between the current key charging indicator parameters of different models of mobile robots and the corresponding dynamic thresholds, as well as the changing trends of the current key charging indicator parameters of different models of mobile robots.

[0076] Figure 5The following is a block diagram of the structure of a computer device 600 provided by an exemplary embodiment of the present application. The computer device 600 can be a portable mobile terminal, such as a smart phone, a tablet computer, an MP3 player (Moving Picture Experts Group Audio Layer III, Moving Picture Experts Group Audio Layer 3), an MP4 player (Moving Picture Experts Group Audio Layer IV, Moving Picture Experts Group Audio Layer 4), a laptop computer, or a desktop computer. The computer device 600 may also be referred to as a user device, a portable terminal, a laptop terminal, a desktop terminal, or other names. Optionally, the computer device 600 can also be implemented as a movable device, such as a mobile smart terminal such as an in-vehicle terminal.

[0077] Typically, the computer device 600 includes a processor 601 and a memory 602 .

[0078] The processor 601 may include one or more processing cores, such as a 4-core processor, an 8-core processor, etc. The processor 601 may be implemented in at least one hardware form of DSP (Digital Signal Processing), FPGA (Field-Programmable Gate Array), or PLA (Programmable Logic Array). The processor 601 may also include a main processor and a coprocessor. The main processor is a processor for processing data in the awake state, also known as a CPU (Central Processing Unit); the coprocessor is a low-power processor for processing data in the standby state. In some embodiments, the processor 601 may be integrated with a GPU (Graphics Processing Unit), which is responsible for rendering and drawing the content to be displayed on the display screen. In some embodiments, the processor 601 may also include an AI (Artificial Intelligence) processor, which is used to process computing operations related to machine learning.

[0079] The memory 602 may include one or more computer-readable storage media, which may be non-transitory. The memory 602 may also include a high-speed random access memory and a non-volatile memory, such as one or more disk storage devices and flash memory storage devices. In some embodiments, the non-transitory computer-readable storage medium in the memory 602 is used to store at least one instruction, which is used to be executed by the processor 601 to implement the model training method or behavior coding method provided in the method embodiment of the present application.

[0080] In some embodiments, computer device 600 may optionally include a peripheral device interface 603 and at least one peripheral device. Processor 601, memory 602, and peripheral device interface 603 may be connected via a bus or signal lines. Each peripheral device may be connected to peripheral device interface 603 via a bus, signal lines, or circuit boards. For example, the peripheral device may include at least one of a radio frequency circuit 604, a display screen 605, a camera assembly 606, an audio circuit 607, a positioning assembly 615, and a power supply 608.

[0081] The peripheral device interface 603 can be used to connect at least one I / O (Input / Output)-related peripheral device to the processor 601 and the memory 602. In some embodiments, the processor 601, the memory 602, and the peripheral device interface 603 are integrated on the same chip or circuit board; in some other embodiments, any one or two of the processor 601, the memory 602, and the peripheral device interface 603 can be implemented on separate chips or circuit boards, which is not limited in this embodiment.

[0082] The radio frequency circuit 604 is used to receive and transmit RF (Radio Frequency) signals, also known as electromagnetic signals. The radio frequency circuit 604 communicates with communication networks and other communication devices via electromagnetic signals. The radio frequency circuit 604 converts electrical signals into electromagnetic signals for transmission, or converts received electromagnetic signals into electrical signals. Optionally, the radio frequency circuit 604 includes: an antenna system, an RF transceiver, one or more amplifiers, a tuner, an oscillator, a digital signal processor, a codec chipset, a user identity module card, etc. The radio frequency circuit 604 can communicate with other terminals via at least one wireless communication protocol. Such wireless communication protocols include, but are not limited to, the World Wide Web, a metropolitan area network, an intranet, various generations of mobile communication networks (2G, 3G, 4G, and 5G), a wireless local area network, and / or a WiFi (Wireless Fidelity) network. In some embodiments, the radio frequency circuit 604 may also include circuits related to NFC (Near Field Communication), which is not limited in this application.

[0083] Display screen 605 is used to display a user interface (UI). This UI can include graphics, text, icons, videos, or any combination thereof. If display screen 605 is a touchscreen display, it can also capture touch signals on or above the surface of display screen 605. These touch signals can be input as control signals to processor 601 for processing. Display screen 605 can also be used to provide virtual buttons and / or a virtual keyboard, also known as soft buttons and / or a soft keyboard. In some embodiments, there can be a single display screen 605, located on the front panel of computer device 600. In other embodiments, there can be at least two display screens 605, located on different surfaces of computer device 600 or in a foldable design. In still other embodiments, display screen 605 can be a flexible display screen, located on a curved or foldable surface of computer device 600. Display screen 605 can also be configured as a non-rectangular, irregular shape, also known as a special-shaped screen. Display screen 605 can be made of materials such as LCD (Liquid Crystal Display) and OLED (Organic Light-Emitting Diode).

[0084] The camera assembly 606 is used to capture images or videos. Optionally, the camera assembly 606 includes a front camera and a rear camera. Typically, the front camera is set on the front panel of the terminal, and the rear camera is set on the back of the terminal. In some embodiments, there are at least two rear cameras, which are any one of a main camera, a depth of field camera, a wide-angle camera, and a telephoto camera, so as to realize the fusion of the main camera and the depth of field camera to realize the background blur function, the fusion of the main camera and the wide-angle camera to realize panoramic shooting and VR (Virtual Reality) shooting function or other fusion shooting functions. In some embodiments, the camera assembly 606 may also include a flash. The flash can be a single-color temperature flash or a dual-color temperature flash. A dual-color temperature flash refers to a combination of a warm light flash and a cold light flash, which can be used for light compensation at different color temperatures.

[0085] The audio circuit 607 may include a microphone and a speaker. The microphone is used to collect sound waves from the user and the environment, and convert the sound waves into electrical signals that are input into the processor 601 for processing, or input into the radio frequency circuit 604 to achieve voice communication. For the purpose of stereo sound collection or noise reduction, there can be multiple microphones, each located in different parts of the computer device 600. The microphone can also be an array microphone or an omnidirectional collection microphone. The speaker is used to convert electrical signals from the processor 601 or the radio frequency circuit 604 into sound waves. The speaker can be a traditional thin film speaker or a piezoelectric ceramic speaker. When the speaker is a piezoelectric ceramic speaker, it can not only convert electrical signals into sound waves audible to humans, but also convert electrical signals into sound waves inaudible to humans for purposes such as distance measurement. In some embodiments, the audio circuit 607 may also include a headphone jack.

[0086] The positioning component 615 is used to locate the current geographic location of the computing device 600 to implement navigation or LBS (Location Based Service). The positioning component 615 can be a positioning component based on the US GPS (Global Positioning System) or China's Beidou system.

[0087] Power supply 608 is used to power various components in computer device 600. Power supply 608 can be AC ​​power, DC power, a disposable battery, or a rechargeable battery. When power supply 608 includes a rechargeable battery, the rechargeable battery can be a wired rechargeable battery or a wireless rechargeable battery. A wired rechargeable battery is a battery that is charged via a wired line, while a wireless rechargeable battery is a battery that is charged via a wireless coil. The rechargeable battery can also be used to support fast charging technology.

[0088] In some embodiments, the computer device 600 further includes one or more sensors 609 , including but not limited to: an acceleration sensor 610 , a gyroscope sensor 611 , a pressure sensor 612 , an optical sensor 613 , and a proximity sensor 614 .

[0089] The accelerometer 610 can detect the magnitude of acceleration along the three coordinate axes of the coordinate system established by the computer device 600. For example, the accelerometer 610 can be used to detect the components of gravity acceleration along the three coordinate axes. The processor 601 can control the display screen 605 to display the user interface in a landscape or portrait view based on the gravity acceleration signal collected by the accelerometer 610. The accelerometer 610 can also be used to collect game or user motion data.

[0090] The gyroscope sensor 611 can detect the orientation and rotation angle of the computer device 600. It can also work with the accelerometer 610 to collect 3D motions of the user on the computer device 600. Based on the data collected by the gyroscope sensor 611, the processor 601 can implement the following functions: motion sensing (e.g., changing the UI based on the user's tilt), image stabilization during shooting, game control, and inertial navigation.

[0091] The pressure sensor 612 can be installed on the side frame of the computer device 600 and / or below the display screen 605. When the pressure sensor 612 is installed on the side frame of the computer device 600, it can detect the user's grip signal of the computer device 600. The processor 601 can perform left and right hand recognition or shortcut operations based on the grip signal collected by the pressure sensor 612. When the pressure sensor 612 is installed below the display screen 605, the processor 601 controls the operational controls on the UI interface based on the user's pressure operation on the display screen 605. The operational controls include at least one of a button control, a scroll bar control, an icon control, and a menu control.

[0092] The optical sensor 613 is used to detect ambient light intensity. In one embodiment, the processor 601 can control the display brightness of the display screen 605 based on the ambient light intensity detected by the optical sensor 613. For example, when the ambient light intensity is high, the display brightness of the display screen 605 is increased; when the ambient light intensity is low, the display brightness of the display screen 605 is decreased. In another embodiment, the processor 601 can also dynamically adjust the shooting parameters of the camera assembly 606 based on the ambient light intensity detected by the optical sensor 613.

[0093] Proximity sensor 614, also known as a distance sensor, is typically located on the front panel of computer device 600. Proximity sensor 614 is used to detect the distance between the user and the front of computer device 600. In one embodiment, when proximity sensor 614 detects that the distance between the user and the front of computer device 600 is gradually decreasing, processor 601 controls display screen 605 to switch from the screen-on state to the screen-off state. When proximity sensor 614 detects that the distance between the user and the front of computer device 600 is gradually increasing, processor 601 controls display screen 605 to switch from the screen-off state to the screen-on state.

[0094] Those skilled in the art will understand that Figure 5 The structure shown in the figure does not constitute a limitation on the computer device 600, and the computer device 600 may include more or fewer components than shown in the figure, or combine some components, or adopt a different arrangement of components.

[0095] The present application also provides a computer-readable storage medium, which stores at least one instruction, at least one program, code set or instruction set. The at least one instruction, the at least one program, the code set or instruction set is loaded and executed by a processor to implement the charging warning method for a mobile robot provided in the above method embodiment.

[0096] The present application provides a computer program product or computer program, which includes computer instructions stored in a computer-readable storage medium. A processor of a computer device reads the computer instructions from the computer-readable storage medium and executes the computer instructions, causing the computer device to perform the mobile robot charging warning method provided in the above method embodiment.

[0097] Those skilled in the art will understand that all or part of the steps to implement the above embodiments may be accomplished by hardware, or by a program to instruct the relevant hardware, and the program may be stored in a computer-readable storage medium, which may be a read-only memory, a disk, or an optical disk, etc.

[0098] The above description is merely an optional embodiment of the present application and is not intended to limit the present application. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principles of the present application shall be included in the scope of protection of the present application.

Claims

1. A charging warning method for a mobile robot, characterized in that: include: According to the key charging parameters of different models of mobile robots, corresponding battery standard models are established respectively; Determine the thresholds corresponding to the key charging indicators of the corresponding mobile robots according to different battery standard models, and dynamically adjust the thresholds corresponding to different key charging indicators of different models of mobile robots based on the current environment and battery aging coefficient; Based on the relationship between the current key charging indicator parameters of different models of mobile robots and the corresponding dynamic thresholds, as well as the changing trends of the current key charging indicator parameters of different models of mobile robots, a linkage charging warning is issued for the mobile robots.

2. The charging warning method for a mobile robot according to claim 1, characterized in that: According to the key charging parameters of different models of mobile robots, corresponding battery standard models are established, specifically: Collect key charging parameters of different types of mobile robots; Analyze the complete charging records of different models of mobile robots, calculate the charging efficiency of different models of mobile robots each time, and determine the standard charging efficiency range of different models of mobile robots; Based on the standard reference ranges of key charging indicators of different models of mobile robots and the standard charging efficiency ranges of different models of mobile robots, the initial battery standard models corresponding to different models of mobile robots are established; According to the collected maximum and minimum values ​​corresponding to each key charging indicator in the current preset historical time period of different models of mobile robots, combined with the standard reference range of each key charging indicator in the corresponding initial battery standard model, the standard reference range of each key charging indicator is updated to obtain the updated battery standard model of different models of mobile robots.

3. The charging warning method for a mobile robot according to claim 1, wherein: The key charging indicators include current, temperature and voltage.

4. The charging warning method for a mobile robot according to claim 1 or 3, characterized in that: The thresholds corresponding to different key charging indicators of different models of mobile robots are dynamically adjusted based on the current environment and battery aging coefficient. Specifically: Dynamically adjust the current threshold of the mobile robot according to the battery aging coefficient, the temperature compensation coefficient, and the difference between the current battery temperature of the mobile robot and the reference temperature; Dynamically adjust the temperature threshold of the mobile robot based on the current reference temperature limit of the mobile robot, the difference between the current ambient temperature and the reference ambient temperature, and the impact factor of the battery health status on the temperature; The voltage threshold of the mobile robot is dynamically adjusted according to the influence factor of the battery health status on the voltage, the temperature compensation coefficient, the reference voltage threshold of the mobile robot, and the battery temperature rise deviation of the mobile robot.

5. The charging warning method for a mobile robot according to claim 1, wherein: The changing trends of the current different charging key indicator parameters of the different models of mobile robots are determined as follows: According to the preset warning thresholds corresponding to the first-order derivatives and second-order derivatives of different key charging indicators, combined with the first-order derivatives and second-order derivatives of different key charging indicator parameters calculated at different times, it is determined whether the current key charging indicator parameters of the mobile robot show an abnormal change trend.

6. The charging warning method for a mobile robot according to claim 1, wherein: The method further includes: determining whether to issue a charging warning for the mobile robot based on the relationship between the current battery temperature of different models of mobile robots and the Pearson correlation coefficient of the battery charging efficiency in the corresponding battery standard model, and a preset correlation coefficient threshold.

7. The charging warning method for a mobile robot according to any one of claims 1 to 6, characterized in that: Also includes: Taking the key charging indicator parameters of the mobile robot as nodes, the causal dependency of the key indicator parameters is determined through historical data to form a parameter causal network; According to the abnormal situation of the key charging indicator parameters, the causal network of the parameters is traced back, the causal contribution of each node is calculated, and the root cause of the abnormality is located.

8. A charging warning device for a mobile robot, characterized in that: include: A construction module is used to establish corresponding battery standard models based on the key charging indicator parameters of different models of mobile robots; The threshold dynamic adjustment module is used to determine the thresholds corresponding to the key charging indicators of the corresponding mobile robots according to different battery standard models, and dynamically adjust the thresholds corresponding to different key charging indicators of different models of mobile robots in combination with the current environment and battery aging coefficient; The linkage warning module is used to provide linkage charging warnings for mobile robots based on the relationship between the current key charging indicator parameters of different models of mobile robots and the corresponding dynamic thresholds, as well as the changing trends of the current key charging indicator parameters of different models of mobile robots.

9. An electronic device, characterized in that: The method comprises a memory and a processor, and computer instructions stored in the memory and executed on the processor, wherein when the computer instructions are executed by the processor, the method according to any one of claims 1 to 7 is completed.

10. A computer-readable storage medium, characterized in that Used to store computer instructions, which, when executed by a processor, complete the method according to any one of claims 1 to 7.

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