Wireless charging method and system for inspection robots

Abstract

This application discloses a wireless charging method and system for an inspection robot, relating to the technical fields of industrial automation and robotics. The method includes: acquiring the current location and battery level of the inspection robot; sending a charging request to the cloud based on the battery level, so that the cloud provides a target charging station identifier and target charging station location based on the charging request; determining a driving strategy based on the current location and the target charging station location; and sending a docking signal to a wireless charger based on the driving strategy and the target charging station identifier, so that the wireless charger wirelessly charges the inspection robot according to the docking signal. This application improves the utilization rate of charging stations and ensures the charging safety of inspection robots in high-risk scenarios through environmental monitoring and precise positioning and docking.

Description

Technical Field

[0001] This application relates to the technical field of industrial automation and robotics, and in particular to a wireless charging method and system for an inspection robot. Background Technology

[0002] In the fields of industrial automation and robotics, inspection robots are increasingly widely used in high-risk scenarios such as power plants and chemical plants. Their safe and efficient operation is of great significance for ensuring production safety. Wireless charging stations, as an emerging technology, have gradually replaced traditional electrode-connecting charging stations, becoming a key support means for powering inspection robots. Wireless charging provides power to inspection robots without physical contact through electromagnetic induction, magnetic resonance, and other methods, effectively improving the working efficiency and operational stability of inspection robots.

[0003] However, existing wireless charging pile technology for inspection robots still has many shortcomings, specifically in the following aspects: Limited functionality: Traditional wireless charging piles only provide energy replenishment, failing to fully utilize their potential as environmental monitoring nodes, resulting in low efficiency. Low equipment utilization: One charging pile typically only supports the charging of one inspection robot, unable to meet the needs of multiple robots charging simultaneously or quickly switching charging, limiting the efficient use of the equipment. Data silos: Charging behavior and environmental monitoring data are independent of each other, lacking effective spatiotemporal alignment analysis methods, making it difficult to achieve a comprehensive assessment of the inspection robot's operating status and environmental conditions. Redundant deployment: The need to deploy charging piles and environmental sensors separately not only increases costs but also raises the system's maintenance complexity, hindering large-scale deployment and application.

[0004] Therefore, how to achieve wireless charging of inspection robots in complex and dangerous environments while ensuring the safety of charging is an urgent problem to be solved. Summary of the Invention

[0005] The main purpose of this application is to provide a wireless charging method and system for inspection robots, aiming to solve the technical problem of how to achieve wireless charging of inspection robots in complex and dangerous environments while ensuring the charging safety of inspection robots.

[0006] To achieve the above objectives, this application proposes a wireless charging method for an inspection robot, wherein the wireless charging method is applied to the inspection robot and the method includes:

[0007] Obtain the current location and battery level of the inspection robot;

[0008] Based on the battery level, a charging request is sent to the cloud, so that the cloud can provide the target charging station identifier and target charging station location based on the charging request;

[0009] Determine a driving strategy based on the current location and the location of the target charging station;

[0010] According to the driving strategy and the target charging station identifier, a docking signal is sent to the wireless charger so that the wireless charger can wirelessly charge the inspection robot according to the docking signal.

[0011] In one embodiment, the step of sending a docking signal to the wireless charger according to the driving strategy and the target charging station identifier includes:

[0012] The control parameters of the inspection robot are obtained according to the driving strategy, and the control parameters include the direction of movement and the distance of movement.

[0013] An encrypted verification code is obtained based on the target charging pile identifier, and the encrypted verification code is sent to the cloud so that the cloud can perform identity authentication based on the encrypted verification code and return the charging identifier.

[0014] The system sends a docking signal to the wireless charger based on the control parameters and the charging identifier.

[0015] In one embodiment, the step of obtaining the control parameters of the inspection robot according to the driving strategy includes:

[0016] When the driving strategy is the first driving strategy, the radio frequency identification (RFID) positioning signal of the wireless charger is received according to the first preset frequency band, and the moving direction and the first displacement distance are calculated according to the signal strength of the RFID positioning signal.

[0017] When the driving strategy is the second driving strategy, the radio frequency identification (RFID) positioning signal of the wireless charger is received according to the second preset frequency band, and the second displacement distance is calculated according to the phase difference of the RFID positioning signal.

[0018] In one embodiment, the step of sending a docking signal to the wireless charger based on the control parameters and the charging identifier includes:

[0019] When the charging identifier is a charging permission identifier, the inspection robot is controlled to move to the first preset range of the wireless charger according to the moving direction and the first displacement distance.

[0020] When the robot moves to the first preset range, it is controlled to move to the coil position of the wireless charger according to the second displacement distance, and sends a docking signal to the wireless charger.

[0021] In one embodiment, the step of determining a driving strategy based on the current location and the target charging station location includes:

[0022] The relative distance is obtained based on the current location and the location of the target charging station;

[0023] When the relative distance is greater than a preset relative distance threshold, the first driving strategy is activated;

[0024] When the relative distance is less than or equal to a preset relative distance threshold, the second driving strategy is activated.

[0025] Furthermore, to achieve the above objectives, this application also proposes a wireless charging method for an inspection robot, wherein the wireless charging method for the inspection robot is applied to a wireless charger, and the method includes:

[0026] Receive docking signals sent by the inspection robot;

[0027] The docking deviation distance is obtained based on the docking signal;

[0028] When the docking deviation distance is less than a preset docking deviation threshold, the inspection robot is wirelessly charged.

[0029] In one embodiment, after the step of wirelessly charging the inspection robot when the docking deviation distance is less than a preset docking deviation threshold, the method further includes:

[0030] Environmental monitoring data are collected according to the first preset frequency;

[0031] The humidity change rate and temperature change rate were obtained based on the environmental monitoring data.

[0032] When the humidity change rate is greater than a preset humidity change threshold or the temperature change rate is greater than a preset temperature change threshold, the first preset frequency is switched to the second preset frequency, and the environmental monitoring data is collected according to the second preset frequency.

[0033] The environmental monitoring data and charging status parameters are synchronously packaged to obtain charging status data, and the charging status data is uploaded to the cloud according to a preset transmission strategy so that the cloud can provide fault warnings based on the charging status data.

[0034] In one embodiment, the step of uploading the charging status data to the cloud according to a preset transmission strategy includes:

[0035] The charging status data is split into normal charging status data and abnormal charging status data.

[0036] The normal charging status data is uploaded to the cloud according to the bandwidth mode in the preset transmission strategy;

[0037] The abnormal charging status data is uploaded to the cloud according to the priority mode in the preset transmission strategy.

[0038] Furthermore, to achieve the above objectives, this application also proposes a wireless charging method for an inspection robot, wherein the wireless charging method for the inspection robot is applied in the cloud, and the method includes:

[0039] Receive charging requests and encrypted verification codes sent by the inspection robot.

[0040] The target charging pile number, target charging pile location, and target charging pile identifier are obtained by matching the current location in the charging request with the preset charging pile deployment map.

[0041] The charging identifier is obtained by retrieving a preset key based on the target charging pile number and verifying the encrypted verification code.

[0042] The target charging pile location, the target charging pile identifier, and the charging identifier are sent to the inspection robot terminal, so that the inspection robot terminal controls the inspection robot to perform wireless charging based on the target charging pile location, the target charging pile identifier, and the charging identifier.

[0043] Furthermore, to achieve the above objectives, this application also proposes a wireless charging system for an inspection robot. The wireless charging system for the inspection robot includes: an inspection robot terminal, a wireless charger, and a cloud platform. The inspection robot terminal executes the wireless charging method for the inspection robot terminal as described above, the wireless charger executes the wireless charging method for the inspection robot terminal as described above, and the cloud platform executes the wireless charging method for the inspection robot terminal as described above.

[0044] This application provides a method for wirelessly charging an inspection robot. The method includes: acquiring the current location and battery level of the inspection robot; sending a charging request to the cloud based on the battery level, so that the cloud provides a target charging station identifier and target charging station location based on the charging request; determining a driving strategy based on the current location and the target charging station location; and sending a docking signal to a wireless charger based on the driving strategy and the target charging station identifier, so that the wireless charger wirelessly charges the inspection robot according to the docking signal. In summary, this application solves the problem of how to achieve wireless charging of inspection robots in complex and dangerous environments while ensuring the charging safety of the inspection robot through environmental monitoring and precise positioning docking, thereby improving the utilization rate of charging stations and ensuring the charging safety of inspection robots in high-risk scenarios. Attached Figure Description

[0045] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application.

[0046] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, for those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0047] Figure 1 A flowchart illustrating the first embodiment of the wireless charging method for the inspection robot in this application;

[0048] Figure 2 A flowchart illustrating the second embodiment of the wireless charging method for the inspection robot in this application;

[0049] Figure 3 This is a schematic diagram of the working process of the wireless charger in one embodiment of the wireless charging method for the inspection robot of this application;

[0050] Figure 4 A flowchart illustrating the third embodiment of the wireless charging method for the inspection robot in this application;

[0051] Figure 5 This is a schematic diagram of the system architecture for the wireless charging method for the inspection robot in this application.

[0052] The purpose, features, and advantages of this application will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0053] It should be understood that the specific embodiments described herein are merely illustrative of the technical solutions of this application and are not intended to limit this application.

[0054] To better understand the technical solution of this application, a detailed description will be provided below in conjunction with the accompanying drawings and specific implementation methods.

[0055] The main solution of this application embodiment is: to obtain the current location and battery level of the inspection robot; to send a charging request to the cloud based on the battery level, so that the cloud can provide a target charging pile identifier and target charging pile location based on the charging request; to determine a driving strategy based on the current location and the target charging pile location; and to send a docking signal to the wireless charger based on the driving strategy and the target charging pile identifier, so that the wireless charger can wirelessly charge the inspection robot according to the docking signal.

[0056] In the fields of industrial automation and robotics, inspection robots are increasingly widely used in high-risk scenarios such as power plants and chemical plants. Their safe and efficient operation is of great significance for ensuring production safety. Wireless charging stations, as an emerging technology, have gradually replaced traditional electrode-connecting charging stations, becoming a key support means for powering inspection robots. Wireless charging provides power to inspection robots without physical contact through electromagnetic induction, magnetic resonance, and other methods, effectively improving the working efficiency and operational stability of inspection robots.

[0057] However, existing wireless charging technology for inspection robots still has many shortcomings, specifically in the following aspects: Limited functionality: Traditional wireless charging piles only provide energy replenishment, failing to fully utilize their potential as environmental monitoring nodes, resulting in low efficiency. Low equipment utilization: One charging pile typically only supports the charging of one inspection robot, unable to meet the needs of multiple robots charging simultaneously or quickly switching charging, limiting the efficient use of the equipment. Data silos: Charging behavior and environmental monitoring data are independent, lacking effective spatiotemporal alignment analysis methods, making it difficult to achieve a comprehensive assessment of the inspection robot's operating status and environmental conditions. Redundant deployment: The need for separate deployment of charging piles and environmental sensors not only increases costs but also raises system maintenance complexity, hindering large-scale application. Therefore, how to achieve wireless charging for inspection robots in complex and hazardous environments while ensuring charging safety is a pressing issue that needs to be addressed.

[0058] This application improves the utilization rate of charging piles and ensures the charging safety of inspection robots in high-risk scenarios by using methods such as environmental monitoring and precise positioning and docking.

[0059] It should be noted that the executing entity in this embodiment can be a wireless charging system for an inspection robot, a computing service device with data processing, network communication, and program execution functions, or an electronic device capable of implementing the aforementioned wireless charging function for an inspection robot. This embodiment does not specifically limit it in this way. The following uses a wireless charging system for an inspection robot as an example to describe this embodiment and the following embodiments.

[0060] Based on this, this application provides a wireless charging method for an inspection robot, referring to... Figure 1 , Figure 1 This is a flowchart illustrating the first embodiment of the wireless charging method for the inspection robot of this application.

[0061] In this embodiment, the wireless charging method for the inspection robot is applied to the inspection robot itself, and the wireless charging method for the inspection robot includes steps S10~S40:

[0062] Step S10: Obtain the current location and battery level of the inspection robot.

[0063] It should be noted that in this step, the inspection robot obtains its current location through its built-in positioning module (such as GPS or an RFID reader), which refers to the robot's specific coordinates in space. Simultaneously, the battery management module monitors the battery's power status in real time. Essentially, this step determines whether the robot needs charging and which charging station to proceed to.

[0064] Step S20: Send a charging request to the cloud based on the battery level, so that the cloud can provide feedback on the target charging station identifier and target charging station location based on the charging request.

[0065] It's important to note that after determining the need for charging based on battery level, the inspection robot will send a charging request to the cloud via its communication unit (such as a LoRa / 5G module). Upon receiving the request, the cloud will select the nearest available charging station based on the robot's current location and the distribution of charging stations, and then send the charging station's identifier and location information back to the robot. For example, assuming a chemical plant scenario, when the inspection robot sends a charging request to the cloud, the cloud will select the nearest charging station, such as "Charging Station No. 1 in Area A," based on the robot's current coordinates, and send the target charging station's identifier (such as "CHG001") and location (such as coordinates or geographic location) back to the robot.

[0066] Additionally, it should be noted that a charging request refers to a command sent by the inspection robot to the cloud, containing its current location and battery level information, requesting charging. The target charging station identifier is a radio frequency identification code used to uniquely identify the target charging station, selected by the cloud based on the distribution of charging stations and fed back to the robot. The target charging station location refers to the specific coordinates or geographical location of the target charging station in space, provided to the robot by the cloud so that the robot can travel to the charging station.

[0067] Step S30: Determine a driving strategy based on the current location and the location of the target charging station.

[0068] It should be noted that in this step, after receiving the location information of the target charging station, the inspection robot determines the necessary driving strategy based on its current location and the location of the target charging station, and then plans an optimal driving path. For example, during the driving process, the robot will first use a global path planning algorithm for long-distance driving, and then switch to a local obstacle avoidance algorithm for short-distance driving when approaching the target charging station.

[0069] In one feasible implementation, step S30 specifically includes:

[0070] Step S301: Obtain the relative distance based on the current location and the location of the target charging pile.

[0071] It should be noted that in this step, the inspection robot obtains its current location through its built-in positioning module and receives the target charging station location from the cloud. The robot then uses its built-in path planning algorithm or distance calculation module to calculate the relative distance between these two locations. This relative distance refers to the straight-line distance between the robot's current location and the target charging station location. Essentially, this step determines the spatial distance between the robot and the target charging station, providing a basis for selecting an appropriate driving strategy.

[0072] Step S302: When the relative distance is greater than the preset relative distance threshold, the first driving strategy is activated.

[0073] It should be noted that when the relative distance calculated by the inspection robot is greater than the preset relative distance threshold (e.g., 1 meter), the inspection robot will activate the first driving strategy, namely the long-distance driving strategy. Under this strategy, the robot mainly uses the UHF frequency band for coarse positioning, plans an optimal long-distance driving path through a global path planning algorithm, and drives along the path to the target charging station.

[0074] Step S303: When the relative distance is less than or equal to a preset relative distance threshold, activate the second driving strategy.

[0075] It should be noted that when the relative distance calculated by the inspection robot is less than or equal to a preset relative distance threshold (e.g., 1 meter), the inspection robot will activate the second driving strategy, namely the short-distance driving strategy. Under this strategy, the robot mainly uses the LF band for precise positioning, and fine-tunes its driving path through local obstacle avoidance algorithms and phase difference calculations to ensure that the robot can accurately and safely connect to the target charging station.

[0076] Step S40: Send a docking signal to the wireless charger according to the driving strategy and the target charging pile identifier, so that the wireless charger can wirelessly charge the inspection robot according to the docking signal.

[0077] It's important to note that in this step, the inspection robot follows its planned route to the target charging station. Upon approaching the station, it docks with the station's positioning module via its built-in receiver module, such as a dual-frequency RFID (Radio Frequency Identification) reader. At this point, the robot sends an encrypted verification code obtained from the target charging station's identifier to the cloud to verify its identity. After successful verification, it sends a docking signal to the wireless charger, activating the charging process through magnetic field coupling. Furthermore, it's crucial to understand that the docking signal refers to the signal sent by the inspection robot to the wireless charger as it approaches the target charging station, triggering the charging process.

[0078] In one feasible implementation, step S40 specifically includes:

[0079] Step S401: Obtain the control parameters of the inspection robot according to the driving strategy. The control parameters include the direction of movement and the distance of movement.

[0080] It should be noted that control parameters refer to the specific action instructions that the inspection robot must follow when executing its driving strategy. Specifically, in this step, the inspection robot calculates the specific control parameters based on the driving strategy (long-distance driving strategy or short-distance driving strategy) determined in step S30, using its built-in path planning algorithm and motion control module. These control parameters include the direction of movement (such as forward, backward, left turn, right turn) and the distance of movement (such as a precise distance in meters or centimeters).

[0081] Step S402: Obtain an encrypted verification code based on the target charging pile identifier, and send the encrypted verification code to the cloud so that the cloud can perform identity authentication based on the encrypted verification code and return the charging identifier.

[0082] It's important to note that the encrypted verification code is an encrypted string generated by the inspection robot using a specific encryption algorithm based on the unique identifier of the target charging station. This string is used for authentication and secure communication. The charging identifier, on the other hand, is an identifier returned to the robot by the cloud server after verifying its identity and charging permissions. This identifier indicates whether the robot is permitted to wirelessly charge. Specifically, in this step, when the inspection robot approaches the target charging station, it sends the target charging station's identifier to the station. The target charging station uses this identifier to generate an encrypted verification code, which is obtained by encrypting the identifier using a preset encryption algorithm (such as AES or RSA). The inspection robot then sends the encrypted verification code to the cloud server. Upon receiving the verification code, the cloud server decrypts it using a pre-stored key and compares it with records in its database to verify the inspection robot's identity and charging permissions. Once verified, the cloud server returns a charging identifier (i.e., a permission identifier indicating whether charging is permitted) to the inspection robot.

[0083] Step S403: Send a docking signal to the wireless charger according to the control parameters and the charging identifier.

[0084] It's important to note that in this step, after receiving the charging identifier from the cloud server, the inspection robot first checks if the identifier indicates that charging is permitted (e.g., "ALLOW"). If charging is permitted, the inspection robot adjusts its position and posture according to control parameters (movement direction and distance) to gradually approach the target charging station. When the inspection robot reaches the charging range of the charging station, it sends a docking signal to the wireless charger (i.e., the target charging station). The docking signal contains the robot's charging request and expected charging parameters.

[0085] In one feasible implementation, step S401 specifically includes:

[0086] Step A10: When the driving strategy is the first driving strategy, receive the radio frequency identification (RFID) positioning signal from the wireless charger according to the first preset frequency band, and calculate the moving direction and the first displacement distance according to the signal strength of the RFID positioning signal.

[0087] It should be noted that the first displacement distance refers to the approximate distance between the inspection robot and the charging pile, estimated by the robot based on the radio frequency identification positioning signal received in the UHF (Ultra High Frequency) band under the first driving strategy (long-distance driving strategy). The first preset frequency band refers to the UHF band (860-960MHz), which is used for long-distance detection and coarse positioning.

[0088] Additionally, it should be noted that when the inspection robot determines that it is adopting the first driving strategy (i.e., the long-distance driving strategy), the robot uses the UHF band (860-960MHz) in its built-in dual-frequency RFID reader to receive the radio frequency identification (RFID) positioning signal from the wireless charger. The UHF band is suitable for long-distance detection and can cover a large area. The robot receives the radio frequency signal from the charging pile through a multi-antenna array and calculates the orientation of the charging pile relative to the robot based on the difference in signal strength received by each antenna, thereby determining the direction of movement. At the same time, based on the signal attenuation, the robot can also estimate the approximate distance between itself and the charging pile, i.e., the first displacement distance. It can be understood that the purpose of this step is to enable the inspection robot to quickly and accurately locate the approximate position of the charging pile at a long distance and plan an initial path to approach the charging pile.

[0089] Step A20: When the driving strategy is the second driving strategy, receive the radio frequency identification positioning signal of the wireless charger according to the second preset frequency band, and calculate the second displacement distance according to the phase difference of the radio frequency identification positioning signal.

[0090] It should be noted that the second displacement distance refers to the displacement distance between the inspection robot and the charging pile, precisely calculated by the robot based on the radio frequency identification positioning signal received in the LF (Low Frequency) band under the second driving strategy (near-field driving strategy). The second preset frequency band refers to the LF band (125kHz), which is used for precise near-field alignment and accurate calculation of horizontal offset.

[0091] Additionally, it should be noted that when the inspection robot determines that it is adopting the second driving strategy (i.e., the close-range driving strategy), the robot switches to the LF band (125kHz) of its built-in dual-frequency RFID reader to receive the radio frequency identification positioning signal from the wireless charger. The LF band is suitable for precise near-field alignment and can provide higher positioning accuracy. By measuring the phase difference of the received radio frequency signal, the robot accurately calculates the horizontal offset between itself and the charging pile, i.e., the second displacement distance. This step allows the inspection robot to precisely adjust its position and attitude at close range, ensuring accurate alignment with the charging coil of the charging pile, thereby achieving efficient wireless charging.

[0092] In one feasible implementation, step S403 specifically includes:

[0093] Step B10: When the charging identifier is a charging permission identifier, control the inspection robot to move to the first preset range of the wireless charger according to the moving direction and the first displacement distance.

[0094] It should be noted that when the inspection robot receives a charging identifier from the cloud server, and this identifier is an authorized charging identifier (such as "ALLOW"), the robot will activate its motion control module based on the calculated movement direction and initial displacement distance from previous steps, and move towards the wireless charger according to a predetermined path and speed. The first preset range refers to a relatively broad area (such as approximately 1 meter from the wireless charger). The size of this range depends on the low-frequency signal coverage of the wireless charger and the positioning accuracy requirements of the inspection robot. Within this area, the inspection robot can receive the RFID positioning signal from the wireless charger's LF band, thus enabling more precise positioning.

[0095] Step B20: When moving to the first preset range, control the inspection robot to move to the coil position of the wireless charger according to the second displacement distance, and send a docking signal to the wireless charger.

[0096] It should be noted that when the inspection robot moves to the first preset range (e.g., within 1 meter of the wireless charger), it switches to the LF band. Utilizing the high-precision positioning capability of this band, it further adjusts its position and attitude based on the second displacement distance (i.e., horizontal offset) calculated in the previous steps. The inspection robot, through its built-in multi-antenna array and signal processing algorithm, accurately calculates its relative position to the wireless charger's charging coil and controls its wheels to fine-tune until it is accurately aligned with the charging coil. After alignment, the inspection robot sends a docking signal to the wireless charger. This signal contains the robot's charging request and expected charging parameters. Upon receiving the docking signal, the wireless charger performs a charging alignment check. If everything is correct, it begins wireless charging the robot.

[0097] This embodiment provides a method for wireless charging an inspection robot. The method includes: acquiring the current location and battery level of the inspection robot; sending a charging request to the cloud based on the battery level, so that the cloud provides a target charging station identifier and target charging station location based on the charging request; determining a driving strategy based on the current location and the target charging station location; and sending a docking signal to a wireless charger based on the driving strategy and the target charging station identifier, so that the wireless charger wirelessly charges the inspection robot according to the docking signal. In summary, this embodiment solves the problem of how to achieve wireless charging of an inspection robot in complex and dangerous environments while ensuring the charging safety of the inspection robot through environmental monitoring and precise positioning docking, thereby improving the utilization rate of charging stations and ensuring the charging safety of inspection robots in high-risk scenarios.

[0098] Based on the first embodiment of this application, in the second embodiment of this application, the same or similar content as the first embodiment described above can be referred to the above description, and will not be repeated hereafter.

[0099] Based on this, this application provides a wireless charging method for an inspection robot, which is applied to a wireless charger. Please refer to [link / reference needed]. Figure 2 , Figure 2 This is a flowchart illustrating the second embodiment of the wireless charging method for the inspection robot in this application.

[0100] In this embodiment, the wireless charging method for the inspection robot includes steps S10'~S30':

[0101] Step S10': Receive the docking signal sent by the inspection robot.

[0102] It's important to note that during this step, the wireless charger's built-in communication module continuously monitors a specific frequency band (such as LoRa or 5G) to receive docking signals from the inspection robot. These docking signals are sent by the inspection robot to the wireless charger after initial positioning and before precise docking. The signals contain a charging request, authentication information, and expected charging parameters. Upon receiving the docking signal, the wireless charger performs preliminary analysis to verify its validity and integrity.

[0103] Step S20': Obtain the docking deviation distance based on the docking signal.

[0104] It's important to note that after receiving the docking signal, the wireless charger further analyzes the location information contained in the signal (such as location information sent via RFID tags) and combines this information with its built-in positioning module (such as the RFID tag) to calculate the docking deviation distance between itself and the inspection robot. The docking deviation distance refers to the actual distance difference between the inspection robot's current position and the center position of the wireless charger's charging coil. For example, after receiving the docking signal from the inspection robot, the wireless charger analyzes the RFID tag information in the signal and learns that the inspection robot is currently located approximately 1 meter northeast, but the exact horizontal offset is unknown. Using its built-in positioning module and signal processing algorithm, the wireless charger calculates the horizontal offset distance between the inspection robot and the center position of the charging coil to be 20 centimeters to the left (meaning the robot needs to adjust slightly to the right by 20 centimeters to align with the charging coil).

[0105] Step S30': When the docking deviation distance is less than the preset docking deviation threshold, the inspection robot is wirelessly charged.

[0106] It's important to note that in this step, after calculating the docking deviation distance, the wireless charger compares this distance with a preset docking deviation threshold. This preset threshold is a safe distance range, such as 30cm, set based on the wireless charger's technical characteristics and the actual application scenario. When the docking deviation distance is less than the preset threshold, the wireless charger considers the inspection robot to be accurately aligned with the charging coil and can begin wireless charging. At this point, the wireless charger activates its wireless charging module, providing power to the inspection robot through electromagnetic induction or magnetic resonance.

[0107] In one feasible implementation, after step S30', the method further includes:

[0108] Step S40': Collect environmental monitoring data according to the first preset frequency.

[0109] It should be noted that the first preset frequency refers to the initial frequency of environmental monitoring data collection, which is set to 0.5Hz in this embodiment, meaning data is collected once every 2 seconds. Specifically, as shown... Figure 3 As shown, in this step, after the inspection robot successfully docks with the wireless charger and begins wireless charging, the environmental monitoring module built into the wireless charger starts collecting environmental monitoring data at a first preset frequency (e.g., 0.5Hz). The environmental monitoring data includes, but is not limited to, temperature and humidity. It is understandable that by periodically collecting this data, potential safety hazards can be detected in a timely manner, ensuring the safe operation of the wireless charging process.

[0110] Step S50': Obtain the humidity change rate and temperature change rate based on the environmental monitoring data.

[0111] It's important to note that in this step, after collecting environmental monitoring data, the wireless charger further calculates the humidity and temperature change rates. These rates are obtained by comparing the currently collected data with the previously collected data, and are used to assess the dynamic changes in environmental conditions. Understandably, calculating the humidity and temperature change rates helps to promptly detect abnormal fluctuations in environmental conditions, allowing for appropriate measures to be taken. For example, suppose the wireless charger collects an ambient temperature of 25°C and humidity of 60% at a certain moment; and two seconds later, the data shows a temperature of 26°C and humidity of 62%. Through calculation, the temperature change rate can be obtained as 0.5°C / s (or 30°C / min), and the humidity change rate as 1% / s (or 60% / min).

[0112] Step S60': When the humidity change rate is greater than a preset humidity change threshold or the temperature change rate is greater than a preset temperature change threshold, switch the first preset frequency to the second preset frequency, and collect the environmental monitoring data according to the second preset frequency.

[0113] It should be noted that when the wireless charger detects a humidity change rate exceeding a preset humidity change threshold or a temperature change rate exceeding a preset temperature change threshold, it will consider the current environmental conditions potentially abnormal. Therefore, it will switch the environmental monitoring data collection frequency from the first preset frequency (0.5Hz) to the second preset frequency (5Hz). Understandably, by increasing the collection frequency, dynamic changes in environmental conditions can be captured more promptly, providing more accurate data support for subsequent early warning and processing.

[0114] Step S70': Synchronously package the environmental monitoring data and charging status parameters to obtain charging status data, and upload the charging status data to the cloud according to a preset transmission strategy, so that the cloud can provide fault warnings based on the charging status data.

[0115] It should be noted that, as Figure 3 As shown, in this step, the wireless charger collects environmental monitoring data while simultaneously monitoring charging status parameters (such as voltage and current) in real time. This data is synchronously packaged into charging status data and uploaded to the cloud according to a preset transmission strategy (such as uploading at fixed time intervals, every 1 or 2 hours). Upon receiving this data, the cloud server analyzes and processes it to detect potential faults or safety hazards. If any anomalies are detected, the cloud server immediately issues an early warning signal, notifying relevant personnel to handle the situation promptly.

[0116] In one feasible implementation, the step of uploading the charging status data to the cloud according to a preset transmission strategy includes:

[0117] Step C10: The charging status data is split into normal charging status data and abnormal charging status data.

[0118] It should be noted that normal charging status data refers to data where all monitored environmental and charging parameters are within safe ranges during the charging process, while abnormal charging status data refers to data where any monitored environmental or charging parameters exceed the preset safe range during the charging process.

[0119] Specifically, before uploading charging status data to the cloud, this data needs to be segmented. The segmentation is based on whether the data reflects a normal state. Normal charging status data refers to data where, during charging, environmental monitoring data (such as temperature and humidity) and charging status parameters (such as voltage and current) are within preset safety ranges, without triggering any warning mechanisms. Abnormal charging status data, on the other hand, refers to data that exceeds preset safety ranges and may cause malfunctions or safety hazards. For example, assuming that during a single charge, the rate of change in ambient temperature remains within 5℃ / min, the rate of change in humidity remains within 10% / min, and the charging voltage and current are stable within normal ranges, then this data will be classified as normal charging status data. Conversely, if the rate of change in ambient temperature suddenly rises to 10℃ / min, or if the charging current fluctuates abnormally, then this data will be classified as abnormal charging status data.

[0120] Step C20: Upload the normal charging status data to the cloud according to the bandwidth mode in the preset transmission strategy.

[0121] It should be noted that, as Figure 3 As shown, normal charging status data is uploaded using the bandwidth mode in the preset transmission strategy. In this embodiment, bandwidth mode refers to the method of allocating transmission resources based on data transmission priority and available bandwidth. For normal data, since it does not contain urgent or important information, it can be transmitted using lower bandwidth to save network resources. For example, suppose the preset transmission strategy stipulates that normal charging status data is uploaded once per hour and transmitted using low bandwidth mode. Then, at the end of each hour, the system will package all normal charging status data collected in the current hour and upload it to the cloud through a low bandwidth channel. Additionally, it should be noted that the charging status data also includes the charging pile number, inspection robot number, charging pile coordinates, and timestamp.

[0122] Step C30: Upload the abnormal charging status data to the cloud according to the priority mode in the preset transmission strategy.

[0123] It should be noted that, as Figure 3 As shown, abnormal charging status data, containing important fault or safety hazard information, needs to be uploaded using the priority mode in the preset transmission strategy. Priority mode means that this data will be transmitted before normal data to ensure that the cloud can receive and process this critical information in a timely manner. For example, suppose that during a charging process, the system detects a sudden increase in ambient temperature, triggering the generation of abnormal charging status data. In this case, the system will immediately upload this abnormal data to the cloud through a high-priority channel, without waiting for the next hour's normal data upload cycle.

[0124] In this embodiment, by receiving the docking signal of the inspection robot, calculating the docking deviation, and controlling wireless charging, combined with multi-frequency environmental monitoring data acquisition and dynamic adjustment strategies, the collaborative work of charging and environmental monitoring is realized. This solves the problems of single function and data silos in traditional charging piles, improves the utilization efficiency of charging piles, the accuracy of data synchronization, and the timeliness of fault warning, and ensures the safe and efficient operation of the inspection robot in high-risk scenarios.

[0125] Based on the first and second embodiments of this application, in the third embodiment of this application, the contents that are the same as or similar to those in the first and second embodiments described above can be referred to the above description and will not be repeated hereafter.

[0126] Based on this, this application provides a wireless charging method for an inspection robot. This wireless charging method is applied in the cloud. Please refer to [link / reference needed]. Figure 4 , Figure 4 This is a flowchart illustrating the third embodiment of the wireless charging method for the inspection robot in this application.

[0127] In this embodiment, the wireless charging method for the inspection robot includes steps S10''~S40'':

[0128] Step S10'': Receive the charging request and encryption verification code sent by the inspection robot.

[0129] It should be noted that the cloud first receives a charging request from the inspection robot. This request includes the robot's current battery status, location information, and an encrypted verification code. The encrypted verification code is used to ensure the legitimacy and security of the charging request and prevent unauthorized charging.

[0130] Step S20'': Match the current location in the charging request with the preset charging pile deployment map to obtain the target charging pile number, target charging pile location, and target charging pile identifier.

[0131] It should be noted that in this step, the cloud platform matches the received location information of the inspection robot with a pre-set charging station deployment map to determine the nearest and available target charging station. The matching result includes the target charging station's number, specific location, and identifier (RFID ID).

[0132] Step S30'': Retrieve the preset key based on the target charging pile number to verify the encrypted verification code and obtain the charging identifier.

[0133] It's important to note that the cloud platform retrieves the corresponding key from a pre-defined key store based on the target charging station's ID, and then decrypts and verifies the encrypted verification code sent by the inspection robot. Upon successful verification, a charging identifier is generated for authentication and authorization during subsequent charging processes. For example, after receiving the target charging station's ID, the cloud platform finds the corresponding key in the key store and decrypts the encrypted verification code. If decryption is successful and the verification code is valid, a unique charging identifier is generated and bound to the association information between the inspection robot and the charging station.

[0134] Step S40'': Send the target charging pile location, the target charging pile identifier, and the charging identifier to the inspection robot terminal, so that the inspection robot terminal controls the inspection robot to perform wireless charging based on the target charging pile location, the target charging pile identifier, and the charging identifier.

[0135] It should be noted that in this step, the cloud will send the matched target charging station location, identifier (RFID ID), and charging identifier to the inspection robot. Based on this information, the inspection robot will plan a route to the target charging station and use the charging identifier for authentication and authorization, thereby controlling the inspection robot to perform wireless charging.

[0136] In this embodiment, the inspection robot receives charging requests from the cloud and verifies the encrypted verification code. It then matches the nearest charging station using the charging station deployment map, generates a charging identifier, and sends it to the robot. This enables the inspection robot to autonomously find and connect to the wireless charger for wireless charging, solving the problems of excessive manual intervention and low efficiency in traditional charging methods, and improving the automation efficiency and safety of charging.

[0137] In addition, such as Figure 5 As shown, this application also provides a wireless charging system for an inspection robot. The system includes a wireless charger, an inspection robot terminal, and a cloud platform. The inspection robot terminal interacts with both the wireless charger and the cloud platform. The wireless charging system for an inspection robot provided in this application, employing the wireless charging method described in the above embodiments, solves the technical problem of how to achieve wireless charging of an inspection robot in complex and hazardous environments while ensuring charging safety. Compared with the prior art, the beneficial effects of the wireless charging system for an inspection robot provided in this application are the same as those of the wireless charging method provided in the above embodiments, and other technical features of this wireless charging system are the same as those disclosed in the previous embodiment, and will not be repeated here.

[0138] In addition, this application also provides a computer program product, including a computer program that, when executed by a processor, implements the steps of the wireless charging method for the inspection robot as described above.

[0139] The computer program product provided in this application solves the technical problem of how to achieve wireless charging of inspection robots in complex and hazardous environments while ensuring the charging safety of the inspection robots. Compared with the prior art, the beneficial effects of the computer program product provided in this application are the same as those of the wireless charging method for inspection robots provided in the above embodiments, and will not be repeated here.

[0140] It should be understood that the various parts disclosed in this application can be implemented using hardware, software, firmware, or a combination thereof. In the description of the above embodiments, specific features, structures, materials, or characteristics can be combined in any suitable manner in one or more embodiments or examples.

[0141] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

[0142] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of this application. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, can be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0143] The modules described in the embodiments of this application can be implemented in software or hardware. The names of the modules do not necessarily limit the functionality of the unit itself.

[0144] The above description is only a part of the embodiments of this application and does not limit the patent scope of this application. All equivalent structural transformations made under the technical concept of this application and using the contents of the specification and drawings of this application, or direct / indirect applications in other related technical fields, are included in the patent protection scope of this application.

Claims

1. A wireless charging method for an inspection robot, characterized in that, The wireless charging method for the inspection robot is applied to a wireless charger, and the method includes: Receive docking signals sent by the inspection robot; The docking deviation distance is obtained based on the docking signal; When the docking deviation distance is less than a preset docking deviation threshold, the inspection robot is wirelessly charged. Environmental monitoring data are collected according to the first preset frequency; The humidity change rate and temperature change rate were obtained based on the environmental monitoring data. When the humidity change rate is greater than a preset humidity change threshold or the temperature change rate is greater than a preset temperature change threshold, the first preset frequency is switched to the second preset frequency, and the environmental monitoring data is collected according to the second preset frequency. The environmental monitoring data and charging status parameters are packaged together to obtain charging status data. The charging status data is split into normal charging status data and abnormal charging status data. The normal charging status data is uploaded to the cloud according to the bandwidth mode in the preset transmission strategy; The abnormal charging status data is uploaded to the cloud according to the priority mode in the preset transmission strategy, so that the cloud can issue a fault warning based on the charging status data.

2. A wireless charging system for an inspection robot, characterized in that, The wireless charging system for the inspection robot includes: an inspection robot terminal, a wireless charger, and a cloud platform. The wireless charger interacts with both the inspection robot terminal and the cloud platform. The wireless charger executes the wireless charging method for the inspection robot as described in claim 1.

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