Charging state detection method and system of charging robot

Abstract

The invention discloses a charging state detection method and system for a charging robot, and is applied to a charging state detection system, and the charging state detection method comprises the steps: obtaining the real-time image data around the charging robot through an image collection device; comparing and identifying the original image data of the charging gun head mark position, and judging to obtain the state information of the real-time charging gun head of the robot; and determining the detection result of the accurate state of the charging gun head according to the detection result of the charging signal in the charging interface corresponding to the charging gun head and the charging physical state information of the charging gun head. According to the method and system disclosed by the invention, visual identification and the charging interface are combined to determine the charging state of the charging interface corresponding to the charging gun head, so that the identification accuracy of the charging state of the charging interface is improved, the charging scheduling efficiency of the charging system is improved, and a guarantee is provided for smooth work of the charging robot.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of mobile charging device control, and in particular to a charging robot charging state detection method and system. BACKGROUND

[0002] In order to realize flexible, efficient and space intensive charging, the prior art proposes an air track type small charging robot. The air track type small charging robot transfers the charging facility from the ground to the air through the hanging rail design to solve the charging problem. The charging robot is especially suitable for charging new energy vehicles.

[0003] However, the air track type small charging robot in the prior art can only identify the connection state of the current charging pile through the charging communication connection signal of the charging interface when walking on the track or charging on the track, so it cannot give accurate physical separation indication of the gun head, and cannot meet the efficient charging regulation and control arrangement of the charging robot.

[0004] Therefore, the prior art needs to be further improved. SUMMARY

[0005] The purpose of the present application is to provide a charging robot charging state detection method and system, which overcomes the defect that the charging robot in the prior art cannot accurately identify the separation state of the charging gun head when walking or charging on the track.

[0006] The technical solution adopted by the present application to solve the technical problems is as follows: In a first aspect, the present application provides a charging robot charging state detection method, wherein the charging state detection method is applied to a charging robot charging state detection system, the charging state detection system comprises: a charging robot; the charging robot is provided with an image acquisition device and a charging gun head; The charging state detection method comprises: acquiring the image of the charging gun head provided on the charging robot by using the image acquisition device; analyzing the charging gun head image to determine the real-time physical state information of the charging gun head; determining the charging state detection result of the charging gun head according to the detection result of the charging connection signal of the charging gun head and the corresponding vehicle charging interface, and combining the real-time physical state information of the charging gun head.

[0007] Optionally, the image acquisition device comprises at least one AI camera; the AI camera is located at the front end of the charging robot; the charging robot is arranged on a sliding rail and moves along the sliding rail, or the charging robot is in a fixed position of the sliding rail and is in a charging state; the charging gun head image is image data of the charging gun head shot by the AI camera.

[0008] Optionally, the charging state detection system further comprises a background server connected with the charging robot; wherein the background server is provided with an AI data analysis model for analyzing the received data information and an image database storing historical images of the charging gun head; The step of analyzing the charging gun head image to determine the real-time physical state information of the charging gun head comprises: The charging gun head image is sent to the background server, so that the background server uses the AI data analysis model to perform AI comparative analysis on the charging gun head historical image and the charging gun head image to determine the real-time physical state information of the charging gun head.

[0009] Optionally, the step of constructing the AI data analysis model comprises: The images with the gun head visual identification mark are screened from the historical charging gun head images, and the historical charging gun head images with the gun head visual identification mark are taken as training samples to construct a training sample set; Each historical charging gun head image in the training sample set is input into a preset neural network model to train the preset neural network model, and a trained AI data analysis model is obtained.

[0010] Optionally, the real-time physical state information comprises: a plug-in state of the charging gun head; the charging gun head has a gun head visual identification mark; and the step of analyzing the charging gun head image to determine the real-time physical state information of the charging gun head comprises: identifying whether the charging gun head image contains the gun head visual identification mark; If the charging gun head image contains the gun head visual identification mark, it is determined that the charging gun head of the charging robot is in a physically separated state, otherwise, the charging gun head of the charging robot is in a physically connected state.

[0011] Optionally, the real-time physical state information further comprises: a charging duration of the charging gun head; and the step of analyzing the charging gun head image to determine the real-time physical state information of the charging gun head further comprises: extracting a charging gun head historical image taken within a preset time period before a current time point from the image database; identifying the current charging gun head image and the charging gun head historical image to determine the duration of the charging gun head in the inserted state, and determining the association data of the vehicle stay time and the charging duration according to the duration.

[0012] Optionally, the step of determining the charging state detection result of the charging gun head according to the detection result of the charging connection signal of the charging gun head and the corresponding vehicle charging interface, and combining the real-time physical state information of the charging gun head comprises: Only when the detection result of the charging connection signal of the vehicle charging interface is in the charging state and the real-time physical state information of the charging gun head is in the physical connection state, the charging state detection result of the current charging gun head is in the charging state, otherwise, it is judged that the current charging gun head is in the non-charging state.

[0013] Optionally, after the step of determining the charging state detection result of the charging gun head according to the detection result of the charging connection signal of the charging gun head and the corresponding vehicle charging interface, and combining the real-time physical state information of the charging gun head, the method further comprises: identifying whether the real-time charging gun head image contains a target area with smoke features; if the target area with smoke features is contained, obtaining the area size and position of the target area with smoke features; determining the risk probability of fire occurrence according to the area size and position of the target area with smoke features.

[0014] Optionally, the step of identifying whether the real-time charging gun head image contains a target area with smoke features is started only when the charging state detection result of the current charging gun head is in the charging state.

[0015] In a second aspect, the application further provides a charging state detection system of a charging robot, comprising: a charging robot, an image acquisition device and a charging gun head arranged at the front end of the charging robot, and a processor arranged inside the charging robot. The image acquisition device is configured to acquire an image of the charging gun head arranged on the charging robot. The processor is configured to analyze the charging gun head image, determine the real-time physical state information of the charging gun head, and determine the charging state detection result of the charging gun head according to the detection result of the charging connection signal of the charging gun head and the corresponding vehicle charging interface, and combine the real-time physical state information of the charging gun head.

[0016] Advantages: This application discloses a charging status detection method and system for a charging robot. The method, applied to a charging status detection system, includes: acquiring real-time image data of the visual recognition mark on the charging gun head of the charging robot using an image acquisition device; uploading the data to a backend server for AI analysis and recognition of the original image data to obtain the physical connection status information of the charging gun head; and determining the charging status detection result based on the detection result of the charging communication connection signal in the vehicle charging interface corresponding to the charging gun head, and the physical connection status information of the charging gun head. This invention, by combining visual recognition and the charging gun head interface, determines the physical connection status of the vehicle charging interface corresponding to the current robot charging gun head, thereby improving the accuracy of connection status identification at the charging interface. This avoids the risk of charging gun head retrieval when the charging gun head is in a state of communication disconnection but physical connection is loose, improving the charging scheduling efficiency of the charging system and ensuring the smooth operation of the charging robot. Attached Figure Description

[0017] Figure 1 A flowchart illustrating the steps of the charging status detection method for a charging robot provided by the present invention; Figure 2 A side perspective view of the charging robot provided by the present invention; Figure 3 A frontal perspective view of the charging robot provided by the present invention; Figure 4 This is a schematic diagram showing the positions of various components in the charging robot provided by the present invention. Figure 5 This is a schematic diagram of the structure of the charging gun head in the charging robot provided by the present invention; Figure 6 A flowchart illustrating the steps for determining charging status in the risk perception method provided by this invention; Figure 7 A flowchart illustrating the steps of smoke feature recognition provided by this invention. Detailed Implementation

[0018] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0019] Other embodiments of the invention will readily occur to those skilled in the art upon consideration of the specification and practice of the invention disclosed herein. This invention is intended to cover any variations, uses, or adaptations of the invention that follow the general principles of the invention and include common knowledge or customary techniques in the art not disclosed herein.

[0020] The aerial track type charging robot is a charging device arranged on a suspended track, can move along the track, identify the position of the device to be charged, and complete the butt joint of the charging gun head. The charging robot can realize accurate positioning through the preset track for efficient charging, and is suitable for charging requirements of various scenes such as new energy vehicles, industrial equipment and logistics robots.

[0021] The aerial track type charging robot in the prior art often only detects the charging signal of the charging interface when running on the track, and uses the presence or absence of the charging signal as a means to perceive the charging state, so that the detection method is single and cannot guarantee the safety of the charging robot during charging.

[0022] In order to overcome the above problems, the present application provides a charging state detection method and system of a charging robot, which is applied to a charging state detection system. The charging state detection method comprises: acquiring original image data around the charging robot by using an image acquisition device; identifying the original image data to obtain charging state information of each charging gun head; and determining the detection result of the charging state according to the detection result of the charging signal in the charging interface corresponding to each charging gun head and the charging state information of each charging gun head. The charging state detection provided by the present application combines visual recognition and charging signal detection, improves the safety of the charging robot in the charging state, avoids the occurrence of charging accidents, and guarantees the charging safety of the charging robot.

[0023] In addition, in the scene of multiple charging robots and multiple devices to be charged, the charging sequence can also be coordinated through the charging state detection to improve the use efficiency of the device. The power of each charging robot can also be reasonably coordinated and dynamically allocated through the charging information of each charging robot, so as to ensure the balanced use of the charging robots in the whole area and maintain the performance stability of the charging robots in the whole area.

[0024] The charging state detection method and system of the charging robot provided by the present embodiment will be described in detail below with reference to the accompanying drawings.

[0025] In a first aspect, as shown in the Figure 1 The present application provides a charging state detection system for a charging robot, which comprises: a charging robot; and an image acquisition device and a charging gun head arranged on the charging robot.

[0026] As shown in the Figures 2 to 4As shown, the application provides a charging state detection system of a charging robot, which comprises a charging robot 10, an image acquisition device arranged at the front end of the charging robot, and a charging gun head 30. The image acquisition device is used to capture the image of the charging gun head arranged on the charging robot, and comprises at least one AI camera. In an embodiment, as shown Figure 4 As shown, in order to obtain a panoramic image of the charging gun head, the image acquisition device comprises a first AI camera 101 and a second AI camera 102. It is conceivable that the image acquisition device can be one panoramic camera or more AI cameras arranged at different angles.

[0027] Further, as shown Figure 2 The charging robot has a hexahedral structure as a whole, which can be designed as a cuboid or a cube. A pulley block is arranged on one face of the charging robot, which slides back and forth on the track 20 by using the pulley block. Taking the face provided with the pulley block as the bottom face, the face opposite to the bottom face is called the top face, and the positions of the two edges adjacent to the top face are respectively provided with the image acquisition device and the charging gun head. The image acquisition device is used to acquire the scene image in front of and around the charging robot, so as to identify the current charging state of the charging gun head according to the acquired image of the charging gun head.

[0028] The charging gun head is used to provide a physical interface for the device to be charged, through which the electric energy of the charging station is transmitted to the battery system of the device to be charged. As shown Figure 3 The charging gun head can be arranged below the charging robot, so as to facilitate the connection of the physical interface. When the device to be charged (for example, a new energy vehicle) needs to be charged, the charging robot slides to the specified position along the track, and the charging gun head can automatically or manually establish the connection with the device to be charged, so as to realize the transmission of electric energy.

[0029] The charging state detection method comprises: Step S1, acquiring real-time image data around the charging robot by using the image acquisition device.

[0030] The image acquisition device arranged on the charging robot is used to capture the image of the charging gun head on the charging robot, so as to obtain the real-time charging gun head image. In the embodiment, the image acquisition device comprises a first AI camera and a second AI camera; the first AI camera and the second AI camera are respectively arranged at the two sides of the front end of the charging robot; the charging robot is arranged on the slide rail and moves along the slide rail, or the charging robot is in a fixed position of the slide rail and is in a charging state. The charging gun head image is the image data of the charging gun head captured by the AI camera.

[0031] In an implementation manner, the first AI camera and the second AI camera are respectively 180° fisheye cameras. Since the 180° fisheye camera has an ultra-wide viewing angle, the horizontal viewing angle can be extended to 180°, and the vertical viewing angle can also reach more than 150°, therefore, the 180° fisheye cameras are respectively arranged on the left and right sides, which can realize the all-around coverage of the surrounding environment of the charging gun head, and eliminate the monitoring blind area.

[0032] Further, the camera can be combined with AI algorithm and motion control technology to realize tracking shooting or monitoring of the visual identification mark of the gun head.

[0033] Further, as shown in FIG. 1, Figure 4 Since the lighting device 103 can provide a stable light source, the lighting device 103 is used to supplement the first AI camera and the second AI camera, so as to reduce the image noise increase and detail loss caused by insufficient ambient light, and make the camera capture a clear picture.

[0034] In order to obtain more accurate surrounding environment information, in the specific implementation, the first AI camera and the second AI camera shoot an image every preset time, or shoot an image every preset distance when the charging robot moves on the track. For example, an image is shot every second, or an image is shot every 2 meters. The images shot by the first AI camera and the second AI camera can be saved in a historical image database, so as to facilitate extraction from the historical image database and comparison when it is necessary to compare the currently shot image with the historically shot image, to find the difference, and then perform a corresponding response operation according to the found difference.

[0035] Step S2, analyzing the charging gun head image to obtain real-time physical state information of the charging gun head.

[0036] When the charging gun head image is obtained in the above step S1, the obtained image is identified to obtain the charging state information of the charging gun head in the image. In this step, only the charging gun head installed on the charging robot itself is identified.

[0037] Further, the charging state information includes: the insertion and extraction state of the charging gun head and the charging duration of the charging gun head. The insertion and extraction state of the charging gun head refers to the physical state of the current charging gun head, which is in the inserted state or the extracted state. In detail, the insertion and extraction state of the charging gun head refers to the physical connection state between the charging gun head and the charging interface (such as the electric vehicle charging port or the charging pile socket), which is usually divided into insertion (connection), extraction (disconnection) and intermediate transition state (such as half insertion, poor contact) and the like. In this embodiment, the insertion and extraction state of the charging gun head only detects the inserted state and the extracted state.

[0038] In combination Figure 5 As shown, the charging gun head of the charging robot is provided with a gun head visual identification mark 301 with special marks. When the charging gun head is in the charging state, the gun head visual identification mark 301 cannot be identified because it is covered by the interface. When the charging gun head is not in the charging state, the gun head visual identification mark 301 is exposed and can be identified. Therefore, when identifying the insertion and extraction state of the charging gun head, whether the gun head visual identification mark can be checked to determine the insertion and extraction state of the current charging gun head.

[0039] In addition to the fixed-position risk object and the position-dynamic change risk object, the images captured by the first AI camera and the second AI camera can also include the charging gun head and the smoke and fire generated in the environment, because the charging robot can also include the charging gun head or the harmful gas such as smoke and fire generated in the surrounding environment during the charging process, which poses a risk to the normal operation of the charging robot.

[0040] In detail, the step of analyzing the charging gun head image to obtain the real-time physical state information of each charging gun head includes: Step S21, identifying whether the charging gun head image contains the gun head visual identification mark.

[0041] In this step, in specific implementation, the processor arranged in the charging robot can be used to analyze the information contained in the original image data to identify whether the gun head visual identification mark on the charging gun head is contained. Alternatively, the original image data can be sent to the connected background server, and the background server can be used to identify whether the charging gun head image contains the gun head visual identification mark.

[0042] In detail, in order to more accurately identify the charging state information of the charging gun head, an AI data analysis model corresponding to the detection of the gun head visual identification mark can be established in this step, and the AI data analysis model established and trained can be used to identify the gun head visual identification mark. For example, a database for training the AI data analysis model is established, the database stores charging gun head images taken at different angles, a plurality of images containing the gun head visual identification mark are extracted from the database to create a training sample set, the training sample set is input into a preset neural network training model, and after multiple iterations, the AI data analysis model for identifying the gun head visual identification mark is obtained.

[0043] In specific implementation, the real-time mark image data of the charging gun head of the charging robot is acquired by using the image acquisition device; the real-time image data is sent to the background server and compared with the charging gun head mark original image data in the database by AI; and whether the charging gun head is in the physical separation state is confirmed according to the comparison difference of the gun head mark data.

[0044] If the charging gun head visual identification mark is contained, it is determined that the charging gun head of the charging robot is in a physically separated state, otherwise, the charging gun head of the charging robot is in a physically connected state.

[0045] In this step, the AI camera is arranged to only capture the image of the charging gun head of the current charging robot, and the charging robot only needs to determine the charging state of its own charging gun head.

[0046] In one implementation, the step of identifying the current plug-in state of the charging gun head comprises: J1. First, two AI cameras capture images of the positions where the charging heads are located, respectively, to obtain charging gun head images.

[0047] J2. The captured charging gun head images containing the charging heads are sent to the background server.

[0048] J3. The background server identifies the area where the charging gun head is located in the charging gun head image, and determines whether the charging gun head image contains the gun head visual identification mark.

[0049] J4. If it is detected that the area where the charging gun head is located contains the gun head visual identification mark, it is determined that the charging gun head has been separated from the vehicle, and the charging gun head is in an unplugged state.

[0050] J5. If the gun head visual identification mark is not detected, it is determined that the charging gun head of the charging robot has not been separated from the vehicle, and the charging gun head is in a plugged state.

[0051] The gun head visual identification mark mentioned in the above steps can be a specific pattern arranged on the front end connection port of the charging gun head. In order to realize that the charging pattern can be captured from different angles. In specific implementation, the charging pattern can be a yellow marked ring sleeved on the connection port.

[0052] Further, the real-time physical state information further comprises: a charging duration of the charging gun head; and the step of analyzing the charging gun head image to determine the real-time physical state information of the charging gun head further comprises: extracting a charging gun head historical image captured within a preset time period before the current time point from an image database; identifying the current charging gun head image and the charging gun head historical image, determining the duration of the charging gun head in the plugged state, and determining the charging duration according to the duration.

[0053] When it is detected that the current charging gun head is in the inserted state, then further based on the historically taken charging gun head image, the physical connection duration of the charging gun head is obtained, and according to the correlation between the actual charging duration and the physical connection duration, it is assisted to judge that the current charging gun head and the device to be charged may be in a link internal fault state.

[0054] Specifically, the judgment method of the charging duration is to obtain the historical shooting image of the position before the current time by a first preset time period based on the position of the charging gun head in the currently taken image, and respectively judge whether the charging gun head at the position in the historical shooting image is always in the inserted state, if it is always in the inserted state, then continue to obtain the historical shooting image located before the second preset time period of the first preset time period, and judge whether the charging gun head at the position in the historical shooting image is always in the inserted state, if it is always in the inserted state, then continue to obtain the historical shooting image located in the second preset time period, and judge whether the charging gun head at the position is in the inserted state, until it is detected that the charging gun head at the position is in the pulled-out state at a certain historical time point. The time difference between the time point when the charging gun head at the position changes from the pulled-out state to the inserted state and the current time point is calculated, and the time difference is taken as the charging duration.

[0055] Step S3, according to the detection result of the charging connection signal of the charging gun head and the corresponding vehicle charging interface, and combining the real-time physical state information of the charging gun head, the charging state detection result of the charging gun head is determined.

[0056] In an implementation manner, the charging robot risk perception system further comprises a background server connected with the robot body; wherein the background server is provided with an AI data analysis model for analyzing the received data information.

[0057] The step of judging the real-time physical state information of the charging gun head by analyzing the charging gun head image by the background server comprises: The charging gun head image is sent to the background server, so that the background server analyzes the charging gun head image and the charging gun head image by AI data analysis model, and judges the real-time physical state information of the charging gun head.

[0058] Combined Figure 6 As shown in the specific application embodiment, the step of identifying the current plug state of the charging gun head comprises: J1, first, two AI cameras respectively take images of the position where the charging gun head is located.

[0059] J2, the image containing the charging gun head taken is sent to the background server.

[0060] J3, identify the area of the gun head visual identification mark in the image of the charging gun head, and identify whether the image contains the gun head visual identification mark.

[0061] J4, if it is detected that the area where the charging gun head is located contains the gun head visual identification mark, it is determined that the charging gun head has been separated from the vehicle, and the charging gun head is in an uninserted state.

[0062] J5, if the gun head visual identification mark with the specific mark is not checked, the charging gun head of the charging robot is not separated from the vehicle, and it is determined that the charging gun head is in an inserted state.

[0063] The gun head visual identification mark mentioned in the above steps can be a specific pattern arranged on the front end connection port of the charging gun head. In order to realize that the specific pattern can be shot from different angles. In specific implementation, the specific pattern can be a fluorescent special color or color bar mark ring sleeved on the connection port.

[0064] In specific implementation, the detection result of whether the charging gun head is in an inserted state can also be verified with the data connection state between the charging head and the vehicle to realize accurate judgment of the charging state of the charging gun head.

[0065] Further, the charging risk related to whether the image contains a target area with smoke features. If it is detected that there is smoke feature around the charging robot, timely feedback is required, and the detection result information of the charging state is re-determined according to the detected smoke feature.

[0066] The step of using the AI data analysis model to analyze the received original image data and the charging state information of the current charging robot to determine the corresponding risk perception information further comprises: Using the AI data analysis model to analyze the original image data, identifying whether the original image data contains a target area with smoke features, and determining the risk probability of fire according to the area size and position of the target area with smoke features.

[0067] In combination Figure 7 As shown, the detailed steps of identifying whether the image of the charging gun head contains a target area with smoke features include: K1, transmitting the image of the charging gun head to the background server.

[0068] K2, the background server uses an AI data analysis model to identify whether each image in the image of the charging gun head contains a region corresponding to the features related to "fire, smoke, and fog".

[0069] The third object recognition model for identifying smoke fire can focus on the significant features (such as color and texture) of smoke / fire by embedding an SE module or CBAM in a CNN, or improve the detection ability of dispersed smoke by capturing long-distance dependencies through global interaction in a Transformer architecture (Transformer is a deep learning model architecture based on self-attention mechanism), and can also improve the accuracy of the trained model in identifying smoke fire by adding adversarial samples in the training data.

[0070] K3, if it is identified that the charging gun head image contains a region consistent with the smoke fire feature, the charging robot charging is paused, the region containing the smoke feature detected is recorded, and step K4 is performed, otherwise, it returns to K1.

[0071] K4, the recording is sent to the operation and maintenance platform, so that the operation and maintenance platform determines whether to restart the charging of the charging robot according to the recording.

[0072] In this step, the detection result of the charging state is determined according to the detection result of the charging signal in the charging interface corresponding to each charging gun head and the charging state information of the charging gun head, and specifically includes: The detection of the charging signal in the charging interface and the detection of the visual identification mark of the gun head are combined to improve the accuracy of the charging detection, for example: if it is detected that the charging interface detects the charging signal, and the corresponding charging port does not detect the specific mark, it indicates that the current charging gun is in the charging state from two aspects, if the charging interface does not detect the charging signal, and the charging port also does not detect the specific mark, it indicates that the current charging port may be in the automatic power-off state (the automatic power-off state of charging is that when the battery to be charged is fully charged, the voltage reaches the rated value, the system automatically determines that the charging is completed, so as to control the output of the charging signal to stop, so that the device to be charged is in standby state).

[0073] The charging detection method of the charging robot disclosed in the embodiment is based on visual recognition, realizes the detection of the charging state of the charging interface, and combines the detection result of the charging state and the detection result of the charging signal of the current charging interface to determine the charging state of the current charging robot.

[0074] In a second aspect, the application also provides a charging state detection system of a charging robot, which comprises: a charging robot, an image acquisition device arranged at the front end of the charging robot and a charging gun head, and a processor arranged in the charging robot.

[0075] Specifically, the image acquisition device is configured to acquire an image of a charging gun head arranged on the charging robot; the processor is configured to analyze the image of the charging gun head, determine real-time physical state information of the charging gun head, and determine a charging state detection result of the charging gun head according to a detection result of a charging connection signal between the charging gun head and a corresponding vehicle charging interface and in combination with the real-time physical state information of the charging gun head.

[0076] The application discloses a charging state detection method and system of a charging robot.

[0077] In the description of the present specification, the description of the terms "one embodiment", "some embodiments", "an example", "a specific example", or "some examples" and the like means that the specific features, structures, materials or characteristics described in connection with the embodiment or example are included in at least one embodiment or example of the present application. In the present specification, the illustrative description of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in any one or N embodiments or examples in a suitable manner. Furthermore, the different embodiments or examples described in the present specification and the features of the different embodiments or examples can be combined and modified by those skilled in the art without contradiction.

[0078] Although the embodiments of the present application have been shown and described above, it should be understood that the above-described embodiments are exemplary and should not be construed as limiting the present application, and those skilled in the art can make changes, modifications, replacements and variations to the above-described embodiments within the scope of the present application.

Claims

1. A method for detecting the charging status of a charging robot, characterized in that, A charging status detection system for a charging robot, the charging status detection system comprising: a charging robot; the charging robot being equipped with an image acquisition device and a charging gun; The charging status detection method includes: Use an image acquisition device to acquire images of the charging gun head installed on the charging robot; The real-time physical state information of the charging gun head is obtained by analyzing the image of the charging gun head. The charging status detection result of the charging gun head is determined based on the detection result of the charging connection signal between the charging gun head and the corresponding vehicle charging interface, combined with the real-time physical status information of the charging gun head.

2. The charging status detection method for a charging robot according to claim 1, characterized in that, The image acquisition device includes at least one AI camera; the AI ​​camera is located at the front end of the charging robot; the charging robot is mounted on a slide rail and moves along the slide rail, or the charging robot is in a fixed position on the slide rail and is in a charging state; the charging gun head image is image data of the charging gun head captured by the AI ​​camera.

3. The charging status detection method for a charging robot according to claim 1, characterized in that, The charging status detection system further includes: a back-end server connected to the charging robot; wherein the back-end server is equipped with an AI data analysis model for analyzing received data information and an image database storing historical images of the charging gun head; The step of analyzing the image of the charging gun head to determine the real-time physical state information of the charging gun head includes: The charging gun head image is sent to the backend server, so that the backend server can use an AI data analysis model to perform AI comparative analysis on the historical images of the charging gun head and the current images of the charging gun head to determine the real-time physical status information of the charging gun head.

4. The charging status detection method for a charging robot according to claim 3, characterized in that, The steps for constructing the AI ​​data analysis model include: Images with visual identification marks on the charging gun heads were selected from historical images of charging gun heads, and multiple historical images of charging gun heads with visual identification marks on the charging gun heads were used as training samples to construct a training sample set. The images of each historical charging gun head in the training sample set are input into a preset neural network model to train the preset neural network model and obtain a trained AI data analysis model.

5. The charging status detection method for a charging robot according to claim 1, characterized in that, The real-time physical state information includes: the insertion / removal status of the charging gun head; the charging gun head has a visual identification mark; the step of analyzing the charging gun head image to determine the real-time physical state information of the charging gun head includes: Identify whether the charging gun head image contains visual recognition marks for the gun head; If the charging gun head contains a visual recognition mark, it is determined that the charging gun head of the charging robot is in a physically separated state; otherwise, the charging gun head of the charging robot is in a physically connected state.

6. The charging status detection method for a charging robot according to claim 5, characterized in that, The real-time physical state information also includes: the charging time of the charging gun head; the step of analyzing the image of the charging gun head to determine the real-time physical state information of the charging gun head further includes: Extract historical images of the charging gun head taken within a preset time period before the current time point from the image database; The system identifies the current charging gun image and historical charging gun images to determine the duration of the charging gun being in the insertion state, and then determines the correlation data between the vehicle's dwell time and the charging time based on the duration.

7. The charging status detection method for a charging robot according to claim 6, characterized in that, The step of determining the charging status detection result of the charging gun head based on the detection result of the charging connection signal between the charging gun head and the corresponding vehicle charging interface, and in combination with the real-time physical status information of the charging gun head, includes: The charging status of the current charging gun head is determined to be in a charging state only when the detection result of the charging connection signal of the vehicle charging interface is in a charging state and the real-time physical status information of the charging gun head is in a physical connection state; otherwise, the current charging gun head is determined to be in a non-charging state.

8. The charging status detection method for a charging robot according to claim 1, characterized in that, After determining the charging status detection result of the charging gun head based on the detection result of the charging connection signal between the charging gun head and the corresponding vehicle charging interface, and in combination with the real-time physical status information of the charging gun head, the method further includes: Identify whether the real-time charging gun head image contains a target area with smoke characteristics; If the target area contains smoke features, then obtain the area size and location of the target area containing smoke features; The probability of a fire is determined based on the size and location of the target area exhibiting smoke characteristics.

9. The charging status detection method for a charging robot according to claim 8, characterized in that, The step of identifying whether the real-time charging gun head image contains a target area with smoke characteristics is only initiated when the current charging status detection result of the charging gun head is in a charging state.

10. A charging status detection system for a charging robot, characterized in that, include: A charging robot, an image acquisition device and a charging gun installed at the front end of the charging robot, and a processor installed inside the charging robot; The image acquisition device is used to acquire images of the charging gun head installed on the charging robot; The processor is used to analyze the image of the charging gun head, determine the real-time physical state information of the charging gun head, and determine the charging status detection result of the charging gun head based on the detection result of the charging connection signal between the charging gun head and the corresponding vehicle charging interface, combined with the real-time physical state information of the charging gun head.

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