A low obstacle detection method, device and electronic equipment

Abstract

The application provides a low obstacle detection method and device and electronic equipment, the method is applied to a server, comprising: acquiring a magnetic field reference range on a preset route, the preset route being a preset inspection route of an inspection robot; acquiring a plurality of magnetic field strengths on the preset route; determining whether the magnetic field strengths are within the magnetic field reference range, if the magnetic field strengths are not within the magnetic field reference range, acquiring a change condition of the magnetic field strengths; determining whether the change condition conforms to a preset standard, if the change condition conforms to the preset standard, determining that there is a metal obstacle on the preset route. The application has the effect of improving the detection accuracy of metal low obstacles.

Description

Technical Field

[0001] This application relates to the technical field of obstacle detection, specifically to a method, apparatus, and electronic device for detecting low-lying obstacles. Background Technology

[0002] In the daily operation and maintenance work of rail transit companies, the inspection of the computer room environment and equipment is a crucial task. The equipment within the computer room encompasses critical devices such as servers, switches, fire-fighting equipment, and video surveillance. The inspection includes checking the completeness and compliance of the fire-fighting facilities, as well as detecting any water damage or leaks. By inspecting the computer room environment and various equipment, malfunctions can be effectively prevented, and accurate data can be provided for subsequent troubleshooting, ensuring the stable operation and safety of the rail transit system.

[0003] Due to the large number and variety of equipment requiring inspection, the inspection personnel are highly skilled, and each piece of equipment needs to be inspected individually, resulting in low efficiency for data center inspections. Therefore, a solution using inspection robots has been proposed. By installing relevant sensors and cameras on these robots, automated inspections of data center equipment can be achieved, improving the efficiency of data center inspections.

[0004] During the inspection of a server room by an inspection robot, low-lying metal obstacles, such as wrenches, screwdrivers, and metal sheets, may obstruct its path. These obstacles can hinder the robot's movement and even cause it to tip over. In dimly lit environments, the poor image quality captured by the camera results in low accuracy in detecting low-lying metal obstacles using machine vision methods. Therefore, a method is needed to improve the accuracy of low-lying metal obstacle detection. Summary of the Invention

[0005] This application provides a method, apparatus, and electronic device for detecting low-lying obstacles, which improves the detection accuracy of low-lying metallic obstacles.

[0006] The first aspect of this application provides a method for detecting low-lying obstacles, the method being applied to a server, comprising: Obtain the magnetic field reference range on the preset route, where the preset route is the preset inspection route of the inspection robot; Obtain multiple magnetic field strengths along the preset route; Determine whether the magnetic field strength is within the magnetic field reference range; if the magnetic field strength is not within the magnetic field reference range, then obtain the change in the magnetic field strength. Determine whether the change meets a preset standard. If the change meets the preset standard, then determine that there is a metal obstacle on the preset route.

[0007] By employing the above technical solution, the server first compares the collected magnetic field strength with a magnetic field reference range. If the magnetic field strength is outside the reference range, it indicates a potential anomaly, possibly due to the presence of a low-lying metal obstacle. The server further determines whether the changes in magnetic field strength conform to a preset standard. If the changes conform to the preset standard, the presence of a metal obstacle may be causing the change in magnetic field strength, and the change is consistent with the preset standard for magnetic field changes when a metal obstacle is present. In this case, the presence of a metal obstacle is further confirmed. By combining the magnetic field reference range and the changes in magnetic field strength, the detection accuracy of metal obstacles is improved.

[0008] Optionally, if the magnetic field strength is not within the magnetic field reference range, then obtaining the change in the magnetic field strength specifically includes: Obtain the time value corresponding to each of the magnetic field intensities; Determine the difference in magnetic field strength between any two adjacent magnetic field strengths, and the duration between any two adjacent time values; Based on the difference in magnetic field strength and the corresponding duration, the change in the magnetic field strength between two adjacent magnetic fields is determined; Based on multiple said change values, an average change value is determined, which is used to reflect the change situation.

[0009] By employing the above technical solution, the time values ​​corresponding to each magnetic field strength can be obtained, allowing determination of the difference and corresponding duration between any two adjacent magnetic field strengths. This provides the magnitude and time span of the magnetic field strength variation. Based on the difference and duration of the magnetic field strength, the variation between two adjacent magnetic field strengths can be determined. This variation value more accurately reflects the magnitude of the magnetic field strength variation, aiding in further analysis and judgment. The average variation value reflects the average degree of change in magnetic field strength over a period of time and can be used to comprehensively assess the variation in magnetic field strength.

[0010] Optionally, determining whether the change meets a preset standard, and if the change meets the preset standard, then determining that there is a metal obstacle on the preset route, specifically includes: Determine whether the average change value is greater than or equal to a preset first threshold. If the average change value is greater than or equal to the preset first threshold, determine whether the multiple magnetic field strengths show an increasing trend. If the strength of multiple magnetic fields shows an increasing trend, then it is determined that there is a metal obstacle on the preset route.

[0011] By employing the above technical solution, it is determined whether the average change value meets the preset standard. By comparing the average change value with a preset first threshold, it can be determined whether the change in magnetic field strength has reached a certain threshold. If the average change value is greater than or equal to the preset first threshold, it indicates that the change in magnetic field strength is significant, possibly due to the presence of a metal obstacle. If the average change value meets the preset standard, further analysis is conducted to determine whether multiple magnetic field strengths show an increasing trend. If multiple magnetic field strengths show an increasing trend, it may be because the inspection robot is gradually approaching the metal obstacle, leading to an increase in magnetic field strength, which can further confirm the presence of a metal obstacle on the preset route.

[0012] Optionally, obtaining the magnetic field reference range along the preset route specifically includes: Obtain information that the preset route does not contain the metal obstacle; Obtain multiple standard values ​​of magnetic field strength along the preset route; Based on multiple standard values ​​of magnetic field strength, the mean and standard deviation of magnetic field strength are determined. Based on the mean magnetic field strength and the standard deviation of the magnetic field strength, the upper limit and lower limit of the magnetic field strength are determined; The magnetic field reference range is determined based on the upper limit and the lower limit of the magnetic field strength.

[0013] By employing the above technical solution, the mean and standard deviation of the magnetic field strength can be calculated based on multiple standard values ​​of magnetic field strength along a preset route. The mean reflects the central location of the magnetic field strength, while the standard deviation indicates the degree of variation in the magnetic field strength. Based on the mean and standard deviation, the upper and lower limits of the magnetic field strength can be determined. The upper limit represents the higher threshold of the magnetic field strength, and the lower limit represents the lower threshold. These two thresholds are used to define the upper and lower bounds of the magnetic field reference range. Since it is determined that there are no metal obstacles along the preset route at this point, the magnetic field reference range can be determined based on the upper and lower limits of the magnetic field strength. This range includes the range of magnetic field strength variation under normal conditions along the preset route. Subsequently, by comparing the collected magnetic field strength with the magnetic field reference range, it can be determined whether the magnetic field strength is abnormal and whether there are metal obstacles.

[0014] Optionally, after obtaining multiple magnetic field strengths along the preset route, the method further includes: Determine whether the target magnetic field strength is greater than or equal to a preset second threshold, wherein the target magnetic field strength is any one of the plurality of magnetic field strengths; If the target magnetic field strength is determined to be greater than or equal to the preset second threshold, a stop command is sent to the inspection robot to stop the inspection robot from moving forward.

[0015] By employing the above technical solution, the magnetic field strength can be compared with a preset second threshold to determine whether the magnetic field strength exceeds the set threshold. If the target magnetic field strength is greater than or equal to the preset second threshold, it indicates that the magnetic field strength has reached a high level, and there may be a significant metallic obstacle. Once it is determined that the target magnetic field strength exceeds the preset second threshold, the server can send a stop command to the inspection robot to stop its movement. This avoids potential problems or damage that might occur if the inspection robot continues to move forward.

[0016] Optionally, after determining that a metal obstacle exists on the preset route if the change meets a preset standard, the method further includes: An image acquisition command is sent to the inspection robot to enable the inspection robot to capture a target image along the preset route, the target image including the metal obstacle; Receive the target image; Obtain the current position data of the inspection robot; The location data is marked in the target image.

[0017] By employing the above technical solution, the server acquires target images containing metal obstacles and associates the inspection robot's position data with the images, providing more intuitive information. This helps operators quickly understand the location and status of the metal obstacles, enabling them to take appropriate measures for subsequent processing, such as notifying relevant personnel to move them.

[0018] Optionally, after determining that a metal obstacle exists on the preset route if the change meets a preset standard, the method further includes: Obtain verification information that the preset route does not contain the metal obstacle; Based on the average change value, the preset first threshold is adjusted until the average change value is less than the preset first threshold.

[0019] By adopting the above technical solution, if the preset route is determined to have no metal obstacles, but the server determines that there are metal obstacles, it indicates that the parameter settings may be incorrect, and the preset first threshold needs to be adjusted according to the actual situation. This can improve the detection accuracy of low-lying metal obstacles and more accurately determine the presence or absence of metal obstacles. Through continuous optimization and adjustment, it can adapt to the inspection needs of different environments and conditions, and improve the accuracy of metal obstacle detection by the inspection robot.

[0020] A second aspect of this application provides a low-profile obstacle detection device, the device being a server, comprising a first acquisition module, a second acquisition module, a first judgment module, and a second judgment module, wherein: The first acquisition module is used to acquire the magnetic field reference range on the preset route, wherein the preset route is the preset inspection route of the inspection robot; The second acquisition module is used to acquire multiple magnetic field strengths along the preset route; The first judgment module is used to determine whether the magnetic field strength is within the magnetic field reference range. If the magnetic field strength is not within the magnetic field reference range, the change in the magnetic field strength is obtained. The second judgment module is used to determine whether the change meets the preset standard. If the change meets the preset standard, it is determined that there is a metal obstacle on the preset route.

[0021] A third aspect of this application provides an electronic device including a processor, a memory, a user interface, and a network interface, wherein the memory is used to store instructions, the user interface and the network interface are both used to communicate with other devices, and the processor is used to execute the instructions stored in the memory to cause the electronic device to perform the method as described in any of the foregoing.

[0022] A fourth aspect of this application provides a computer-readable storage medium storing instructions that, when executed, perform the method described in any of the preceding descriptions.

[0023] In summary, one or more technical solutions provided in the embodiments of this application have at least the following technical effects or advantages: 1. The server first compares the collected magnetic field strength with a magnetic field reference range. If the magnetic field strength is outside the reference range, it indicates a potential anomaly, possibly due to the presence of a low-lying metal obstacle. The server further determines whether the changes in magnetic field strength conform to preset standards. If the changes conform to the preset standards, the presence of a metal obstacle may be causing the change in magnetic field strength, and the change is consistent with the preset standard for the presence of a metal obstacle. In this case, the presence of a metal obstacle is confirmed. By combining the magnetic field reference range and the changes in magnetic field strength, the detection accuracy of metal obstacles is improved.

[0024] 2. Determine if the average change value meets the preset standard. By comparing the average change value with a preset first threshold, it can be determined whether the change in magnetic field strength has reached a certain threshold. If the average change value is greater than or equal to the preset first threshold, it indicates that the change in magnetic field strength is significant, possibly due to the presence of a metal obstacle. If the average change value meets the preset standard, further analysis is performed to determine if multiple magnetic field strengths show an increasing trend. If multiple magnetic field strengths show an increasing trend, it may be because the inspection robot is gradually approaching the metal obstacle, causing the magnetic field strength to increase, which can further confirm the presence of a metal obstacle on the preset route. Attached Figure Description

[0025] Figure 1 This is a flowchart illustrating a low obstacle detection method disclosed in an embodiment of this application; Figure 2 This is a schematic diagram of the structure of a low obstacle detection device disclosed in an embodiment of this application; Figure 3 This is a schematic diagram of the structure of an electronic device disclosed in an embodiment of this application.

[0026] Explanation of reference numerals in the attached drawings: 201, First acquisition module; 202, Second acquisition module; 203, First judgment module; 204, Second judgment module; 301, Processor; 302, Communication bus; 303, User interface; 304, Network interface; 305, Memory. Detailed Implementation

[0027] To enable those skilled in the art to better understand the technical solutions in this specification, the technical solutions in the embodiments of this specification will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments.

[0028] In the description of the embodiments of this application, the words "for example" or "for instance" are used to indicate examples, illustrations, or explanations. Any embodiment or design that is described as "for example" or "for instance" in the embodiments of this application should not be construed as being more preferred or advantageous than other embodiments or design options. Rather, the use of the words "for example" or "for instance" is intended to present the relevant concepts in a specific manner.

[0029] In the description of the embodiments of this application, the term "multiple" means two or more. For example, multiple systems means two or more systems, and multiple screen terminals means two or more screen terminals. Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the indicated technical features. Thus, a feature defined with "first" or "second" may explicitly or implicitly include one or more of that feature. The terms "comprising," "including," "having," and variations thereof all mean "including but not limited to," unless otherwise specifically emphasized.

[0030] In the daily operation and maintenance work of rail transit companies, the inspection of the computer room environment and equipment is a crucial task. The equipment within the computer room encompasses critical devices such as servers, switches, fire-fighting equipment, and video surveillance. The inspection includes checking the completeness and compliance of the fire-fighting facilities, as well as detecting any water damage or leaks. By inspecting the computer room environment and various equipment, malfunctions can be effectively prevented, and accurate data can be provided for subsequent troubleshooting, ensuring the stable operation and safety of the rail transit system.

[0031] Due to the large number and variety of equipment requiring inspection, the inspection personnel are highly skilled, and each piece of equipment needs to be inspected individually, resulting in low efficiency for data center inspections. Therefore, a solution using inspection robots has been proposed. By installing relevant sensors and cameras on these robots, automated inspections of data center equipment can be achieved, improving the efficiency of data center inspections.

[0032] During the inspection of a server room by an inspection robot, low-lying metal obstacles, such as wrenches, screwdrivers, and metal sheets, may obstruct its path. These obstacles can hinder the robot's movement and even cause it to tip over. In dimly lit environments, the poor image quality captured by the camera results in low accuracy in detecting low-lying metal obstacles using machine vision methods. Therefore, a method is needed to improve the accuracy of low-lying metal obstacle detection.

[0033] This embodiment discloses a method for detecting low-lying obstacles, referring to... Figure 1 This includes the following steps S110-S140: S110, obtain the magnetic field reference range on the preset route.

[0034] Specifically, the low obstacle detection method disclosed in this application is applied to a server. The server includes, but is not limited to, electronic devices such as mobile phones, tablets, wearable devices, and PCs (Personal Computers), and can also be a backend server running a low obstacle detection method. The server can be implemented using a standalone server or a server cluster composed of multiple servers.

[0035] Based on the structure of the computer room, the distribution of equipment, and the inspection requirements, the inspection route for the inspection robot needs to be pre-defined. Understanding the structure and layout of the computer room is the first step in setting the inspection route. Analyze the rooms, corridors, passageways, server racks, and other areas in the computer room to determine the area that the inspection robot can cover. It is also necessary to clarify the specific inspection objectives and requirements. Based on the inspection purpose, such as obtaining equipment operating status, temperature, humidity, and other indicators, determine the key areas and equipment that the inspection robot needs to cover. Simultaneously, the obstacle avoidance and passage capabilities of the inspection robot need to be considered. Identify potential obstacles, narrow passages, or complex paths in the computer room and ensure that the inspection robot can pass through these areas smoothly. Based on the above factors, a path planning algorithm is used to determine the optimal inspection route, i.e., the preset route. The path planning algorithm can consider factors such as time, distance, obstacle avoidance, and energy saving to ensure that the inspection robot can complete the inspection task efficiently.

[0036] To facilitate the determination of whether there are metal obstacles directly in front of the inspection robot during its inspection process based on real-time magnetic field strength, it is first necessary to obtain the magnetic field baseline range along the preset route, that is, the distribution range of magnetic field strength along a certain section of the path.

[0037] First, the server obtains information indicating that there are no metal obstacles along the preset route. Metal obstacles are low-lying metal objects, typically less than 20cm in height, such as wrenches, screwdrivers, and metal sheets. These low obstacles can impede the inspection robot's movement and may even cause it to tip over. Since this is the robot's first inspection, the user can determine the presence of obstacles along the preset route beforehand. If the user confirms that there are no metal obstacles along the preset route, they input this information into the server.

[0038] S120, obtain multiple magnetic field strengths along the preset route.

[0039] The server then sends an initial inspection command to the inspection robot. This command is an instruction or command to direct the electronic equipment; it can be understood as code specifying the execution of a certain operation or function. After receiving the initial inspection command, the inspection robot performs an inspection according to a preset route. A magnetic field sensor is positioned slightly below and directly in front of the inspection robot. This sensor (such as a Hall effect sensor or magnetoresistive sensor) measures the magnetic field strength near external metallic objects. These sensors can detect changes in the magnetic field and convert them into electrical signals for measurement and recording.

[0040] During the inspection process, the inspection robot monitors the magnetic field strength directly in front of it in real time, or acquires the magnetic field strength at regular intervals, marking these acquired magnetic field strength values ​​as standard values. The average value of the magnetic field strength is calculated based on multiple standard values. The standard deviation of the magnetic field strength is then calculated based on these standard values. A range factor also needs to be determined, based on actual needs and the characteristics of the inspection task. Typically, using 1 or 2 times the standard deviation is a common choice. Smaller factors include more data, while larger factors restrict the benchmark range to a more stringent range. Finally, the upper and lower limits of the magnetic field strength are calculated based on the above data: Upper limit = Average magnetic field strength + Standard deviation of magnetic field strength × Factor; Lower limit = Average magnetic field strength - Standard deviation of magnetic field strength × Factor. These calculated upper and lower limits serve as the boundaries of the benchmark range for the magnetic field strength, encompassing the magnetic field strength values ​​in the absence of metal obstacles.

[0041] It should be noted that, in practical applications, to improve detection accuracy, a magnetic field strength reference range is usually determined for different road sections. The preset route is divided into several segments, and the magnetic field strength reference range for each segment is calculated. Subsequently, the presence of metal obstacles in each segment is determined based on the changes in magnetic field strength. However, the processing method for each segment is the same as that for the entire preset route. For ease of understanding, this application uses the entire preset route as an example.

[0042] Based on multiple standard values ​​of magnetic field strength along the preset route, the mean and standard deviation of the magnetic field strength can be calculated. The mean reflects the center position of the magnetic field strength, while the standard deviation indicates the degree of variation in the magnetic field strength. Based on the mean and standard deviation, the upper and lower limits of the magnetic field strength can be determined. The upper limit represents the higher threshold of the magnetic field strength, and the lower limit represents the lower threshold. These two thresholds are used to define the upper and lower bounds of the magnetic field reference range. Since it is determined that there are no metal obstacles along the preset route at this point, the magnetic field reference range can be determined based on the upper and lower limits of the magnetic field strength. This range includes the range of magnetic field strength variation under normal conditions along the preset route. Subsequently, by comparing the collected magnetic field strength with the magnetic field reference range, it can be determined whether the magnetic field strength is abnormal and whether there are metal obstacles.

[0043] S130: Determine whether the magnetic field strength is within the magnetic field reference range. If the magnetic field strength is not within the magnetic field reference range, obtain the change in magnetic field strength.

[0044] According to steps S110-S120, during the initial inspection by the inspection robot, the magnetic field reference range of the preset route is calculated. Then, during the inspection robot's operation, the magnetic field strength along the preset route is measured in real time. The inspection robot sends the magnetic field strength data to the server. The server, based on the magnetic field strength value and the upper and lower limits of the magnetic field reference range, determines whether the magnetic field strength is within the magnetic field reference range. When the magnetic field strength is within the magnetic field reference range, it indicates that the magnetic field strength along the preset route is within the normal range, which can be interpreted as the absence of metal obstacles along the preset route. When the magnetic field strength is not within the magnetic field reference range, it indicates that the magnetic field strength along the preset route is not within the normal range, which can be preliminarily determined as the presence of metal obstacles along the preset route.

[0045] S140, determine whether the change meets the preset standard. If the change meets the preset standard, then determine that there is a metal obstacle on the preset route.

[0046] To improve the accuracy of judging changes, the server calculates the average change in magnetic field strength based on multiple magnetic field strength values ​​to reflect the changes in magnetic field strength.

[0047] Specifically, after receiving multiple magnetic field strengths from the inspection robot, the server obtains the corresponding time value for each magnetic field strength. For example, if the server receives the data for the third magnetic field strength at 14:03:26, it binds this magnetic field strength data with 14:03:26. The server then selects two adjacent magnetic field strength values, subtracting the previous magnetic field strength from the latter to calculate the difference between them. Simultaneously, it calculates the duration between their corresponding time values, again by subtracting the previous time value from the latter. This yields the difference and duration between any two adjacent magnetic field strengths. Next, based on the magnetic field strength difference and corresponding duration, the change value between two adjacent magnetic field strengths is calculated. The change value can be calculated simply by dividing the difference value by the duration value, reflecting the rate of change of the magnetic field strength. Finally, multiple magnetic field strength change values ​​are collected, and their average is calculated. The average change value is the sum of multiple change values, used to reflect the overall change in magnetic field strength.

[0048] By employing the above technical solution, the time values ​​corresponding to each magnetic field strength can be obtained, allowing determination of the difference and corresponding duration between any two adjacent magnetic field strengths. This provides the magnitude and time span of the magnetic field strength variation. Based on the difference and duration of the magnetic field strength, the variation between two adjacent magnetic field strengths can be determined. This variation value more accurately reflects the magnitude of the magnetic field strength variation, aiding in further analysis and judgment. The average variation value reflects the average degree of change in magnetic field strength over a period of time and can be used to comprehensively assess the variation in magnetic field strength.

[0049] Furthermore, based on the average change value calculated in the above steps, it is determined whether the average change value is greater than or equal to a preset first threshold. The preset first threshold needs to be set according to the actual situation, therefore this embodiment does not impose a specific limitation. When the average change value is less than the preset first threshold, it indicates that the change in magnetic field strength has not reached the set standard, that is, the change in magnetic field strength is small, and therefore there is no metal obstacle. When the average change value of magnetic field strength is greater than or equal to the preset first threshold, it indicates that the change in magnetic field strength is significant and has reached the preset standard, possibly due to the presence of a metal obstacle.

[0050] If it is initially determined that there is a metal obstacle directly in front of the inspection robot, the magnetic field strength detected by the robot will gradually increase as it moves forward. Therefore, if the magnetic field strength is not within the magnetic field reference range, it indicates that the magnetic field strength on the preset route is not within the normal range, and it can be preliminarily judged that there is a metal obstacle on the preset route. The server sorts the multiple magnetic field strengths detected by the inspection robot in chronological order and then analyzes the changing trends of the multiple magnetic field strength values. It checks whether the collected multiple magnetic field strength values ​​are increasing, that is, whether the magnetic field strength value at any position is greater than the magnetic field strength value at the previous position. If the magnetic field strength value at any position is greater than the magnetic field strength value at the previous position, it is determined that the magnetic field strength is increasing, and the change in magnetic field strength meets the preset standard, thus determining that there is a metal obstacle on the preset route. It judges whether the average change value meets the preset standard. By comparing the average change value with the preset first threshold, it can be determined whether the change in magnetic field strength has reached a certain threshold. If the average change value is greater than or equal to the preset first threshold, it indicates that the change in magnetic field strength is significant, which may be due to the presence of a metal obstacle. If the average change value reaches the preset standard, further analysis is performed to determine whether the multiple magnetic field intensities show an increasing trend. If multiple magnetic field intensities show an increasing trend, it may be because the inspection robot is gradually approaching the metal obstacle, causing the magnetic field intensity to increase, which can further confirm the presence of a metal obstacle on the preset route.

[0051] By employing the above technical solution, the server first compares the collected magnetic field strength with a magnetic field reference range. If the magnetic field strength is outside the reference range, it indicates a potential anomaly, possibly due to the presence of a low-lying metal obstacle. The server further determines whether the changes in magnetic field strength conform to a preset standard. If the changes conform to the preset standard, the presence of a metal obstacle may be causing the change in magnetic field strength, and the change is consistent with the preset standard for magnetic field changes when a metal obstacle is present. In this case, the presence of a metal obstacle is further confirmed. By combining the magnetic field reference range and the changes in magnetic field strength, the detection accuracy of metal obstacles is improved.

[0052] Furthermore, after receiving the magnetic field strength data sent by the inspection robot, the server compares the target magnetic field strength with a preset second threshold in real time. The target magnetic field strength can be any one of multiple magnetic field strengths. The setting of the preset second threshold needs to be determined according to different embodiments, and this embodiment does not impose a specific limitation. When the target magnetic field strength is greater than or equal to the preset second threshold, it indicates that the inspection robot is close to the metal obstacle. The server then sends a stop command to the inspection robot to stop its movement, thereby preventing the metal obstacle from affecting the robot's progress.

[0053] By comparing the target magnetic field strength with a preset second threshold, it can be determined whether the magnetic field strength exceeds the set threshold. If the target magnetic field strength is greater than or equal to the preset second threshold, it indicates that the magnetic field strength has reached a high level, and there may be a significant metallic obstacle. Once it is determined that the target magnetic field strength exceeds the preset second threshold, the server can send a stop command to the inspection robot to stop its movement. This avoids potential problems or damage that might occur if the inspection robot continues to move forward.

[0054] Furthermore, after confirming the presence of metal obstacles along the preset route, to facilitate quick location of the obstacles and their rapid removal by relevant personnel, the server first sends an image acquisition command to the inspection robot. Prior to this, an image acquisition command needs to be defined, containing the relevant parameters and settings to trigger the inspection robot to acquire images. These parameters may include image resolution, acquisition frequency, and acquisition method. Upon receiving the image acquisition command, the inspection robot begins executing the image acquisition task according to the command's settings. The inspection robot captures images of the target, including the metal obstacles. After completing image acquisition, the robot transmits the images to the receiving end. The server parses and processes the received image data. This may include steps such as image format conversion and image quality assessment to ensure the integrity and usability of the received image data.

[0055] Simultaneously, the current position data of the inspection robot is acquired. Since the inspection robot has a positioning function, its current position data can be obtained through a positioning system (such as UWB). This data can be used to mark the inspection robot's position in the target image. Based on the acquired position data, the inspection robot's position is marked in the target image. Image processing techniques, such as image overlay, drawing markers, and borders, can be used to mark the position information on the target image.

[0056] The server acquires target images containing metal obstacles and correlates the inspection robot's location data with the images, providing more intuitive information. This helps operators quickly understand the location and status of metal obstacles, enabling them to take appropriate follow-up measures, such as notifying relevant personnel to move them.

[0057] Based on the target image and location data, relevant personnel proceed to confirm the presence of any metal obstacles. If manual confirmation confirms the absence of metal obstacles, it indicates an error in the detection process, requiring adjustments to relevant parameters to improve detection efficiency. The personnel then input verification information indicating the absence of metal obstacles along the preset route into the server. Upon receiving this verification, the server increments a preset first threshold value. This first threshold, as mentioned earlier, determines whether the average change in the preset magnetic field strength meets a preset standard. A value greater than or equal to the first threshold indicates a significant change in magnetic field strength, suggesting the potential presence of metal obstacles along the route. Since manual confirmation confirms the absence of metal obstacles, and the inspection robot's detection equipment is functioning correctly, it suggests that the preset first threshold value was set too low, resulting in high detection sensitivity. Therefore, the server increments the first threshold value until the calculated average change value is less than the first threshold, at which point the server ceases to report the presence of metal obstacles along the route.

[0058] If the preset route is determined to be free of metal obstacles, but the server indicates the presence of metal obstacles, this suggests a possible error in the parameter settings. The preset first threshold needs adjustment based on the actual situation. This improves the detection accuracy of low-lying metal obstacles, allowing for a more precise determination of their presence. Through continuous optimization and adjustment, the system can adapt to inspection needs in different environments and conditions, further enhancing the accuracy of metal obstacle detection for the inspection robot.

[0059] This embodiment also discloses a low-profile obstacle detection device, which is a server, as shown in the following figure. Figure 2 It includes a first acquisition module 201, a second acquisition module 202, a first judgment module 203, and a second judgment module 204, wherein: The first acquisition module 201 is used to acquire the magnetic field reference range on the preset route, where the preset route is the preset inspection route of the inspection robot. The second acquisition module 202 is used to acquire multiple magnetic field strengths along a preset route; The first judgment module 203 is used to determine whether the magnetic field strength is within the magnetic field reference range. If the magnetic field strength is not within the magnetic field reference range, the change in magnetic field strength is obtained. The second judgment module 204 is used to determine whether the change meets the preset standard. If the change meets the preset standard, it is determined that there is a metal obstacle on the preset route.

[0060] In one possible implementation, a low obstacle detection device further includes a computing module.

[0061] The first acquisition module 201 is used to acquire the time value corresponding to each magnetic field strength; The calculation module is used to determine the difference in magnetic field strength between any two adjacent magnetic field strengths, and the duration between any two adjacent time values. The calculation module is used to determine the change in the magnetic field strength between two adjacent magnetic fields based on the difference in magnetic field strength and the corresponding duration. The calculation module is used to determine the average change value based on multiple change values. The average change value is used to reflect the change situation.

[0062] In one possible implementation, the first judgment module 203 is used to determine whether the average change value is greater than or equal to a preset first threshold. If the average change value is greater than or equal to the preset first threshold, then it is determined whether the multiple magnetic field strengths show an increasing trend. The second judgment module 204 is used to determine that there is a metal obstacle on the preset route if the strength of multiple magnetic fields shows an increasing trend.

[0063] In one possible implementation, the first acquisition module 201 is used to acquire information that there are no metal obstacles on the preset route; The second judgment module 204 is used to obtain multiple standard values ​​of magnetic field strength on the preset route; The calculation module is used to determine the mean and standard deviation of the magnetic field strength based on multiple standard values ​​of magnetic field strength. The calculation module is used to determine the upper limit and lower limit of the magnetic field strength based on the mean and standard deviation of the magnetic field strength. The calculation module is used to determine the reference range of the magnetic field based on the upper limit and lower limit of the magnetic field strength.

[0064] In one possible implementation, the first judgment module 203 is used to determine whether the target magnetic field strength is greater than or equal to a preset second threshold, wherein the target magnetic field strength is any one of a plurality of magnetic field strengths. The second judgment module 204 is used to send a stop command to the inspection robot if it is determined that the target magnetic field strength is greater than or equal to a preset second threshold, so that the inspection robot stops moving forward.

[0065] In one possible implementation, the second judgment module 204 is used to send an image acquisition command to the inspection robot so that the inspection robot can capture a target image of a preset route, the target image including metal obstacles. The first acquisition module 201 is used to receive the target image; The second acquisition module 202 is used to acquire the current position data of the inspection robot; The calculation module is used to mark location data in the target image.

[0066] In one possible implementation, the first acquisition module 201 is used to acquire verification information that there are no metal obstacles on the preset route; The calculation module is used to adjust a preset first threshold based on the average change value until the average change value is less than the preset first threshold value.

[0067] It should be noted that the above embodiments of the apparatus are only illustrated by the division of the above functional modules. In practical applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the device can be divided into different functional modules to complete all or part of the functions described above. In addition, the apparatus and method embodiments provided above belong to the same concept, and the specific implementation process can be found in the method embodiments, which will not be repeated here.

[0068] This embodiment also discloses an electronic device, as shown in the reference. Figure 3 The electronic device may include: at least one processor 301, at least one communication bus 302, user interface 303, network interface 304, and at least one memory 305.

[0069] The communication bus 302 is used to enable communication between these components.

[0070] The user interface 303 may include a display screen and a camera. Optionally, the user interface 303 may also include a standard wired interface and a wireless interface.

[0071] The network interface 304 may optionally include a standard wired interface or a wireless interface (such as a Wi-Fi interface).

[0072] The processor 301 may include one or more processing cores. The processor 301 connects to various parts of the server using various interfaces and lines, and performs various server functions and processes data by running or executing instructions, programs, code sets, or instruction sets stored in the memory 305, and by calling data stored in the memory 305. Optionally, the processor 301 may be implemented using at least one hardware form of Digital Signal Processing (DSP), Field-Programmable Gate Array (FPGA), or Programmable Logic Array (PLA). The processor 301 may integrate one or a combination of several of the following: Central Processing Unit (CPU), Graphics Processing Unit (GPU), and modem. The CPU primarily handles the operating system, user interface, and applications; the GPU is responsible for rendering and drawing the content required for display; and the modem handles wireless communication. It is understood that the modem may also not be integrated into the processor 301 and may be implemented as a separate chip.

[0073] The memory 305 may include random access memory (RAM) or read-only memory. Optionally, the memory 305 may include a non-transitory computer-readable storage medium. The memory 305 may be used to store instructions, programs, code, code sets, or instruction sets. The memory 305 may include a program storage area and a data storage area. The program storage area may store instructions for implementing an operating system, instructions for at least one function (such as touch functionality, sound playback functionality, image playback functionality, etc.), instructions for implementing the various method embodiments described above, etc.; the data storage area may store data involved in the various method embodiments described above, etc. Optionally, the memory 305 may also be at least one storage device located remotely from the aforementioned processor 301. As shown in the figure, the memory 305, as a computer storage medium, may include an operating system, a network communication module, a user interface 303 module, and an application program for a low-profile obstacle detection method.

[0074] exist Figure 3In the electronic device shown, the user interface 303 is mainly used to provide an input interface for the user and to obtain the user input data; while the processor 301 can be used to call an application program stored in the memory 305 for a low obstacle detection method. When executed by one or more processors 301, the electronic device executes one or more methods as described in the above embodiments.

[0075] It should be noted that, for the sake of simplicity, the foregoing method embodiments are all described as a series of actions. However, those skilled in the art should understand that this application is not limited to the described order of actions, as some steps may be performed in other orders or simultaneously according to this application. Furthermore, those skilled in the art should also understand that the embodiments described in the specification are preferred embodiments, and the actions and modules involved are not necessarily essential to this application.

[0076] In the above embodiments, the descriptions of each embodiment have different focuses. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions in other embodiments.

[0077] In the several embodiments provided in this application, it should be understood that the disclosed apparatus can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the shown or discussed mutual couplings or direct couplings or communication connections may be through some service interfaces; indirect couplings or communication connections between apparatuses or units may be electrical or other forms.

[0078] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0079] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0080] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage device 305. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage device 305 and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of this application. The aforementioned storage device 305 includes various media capable of storing program code, such as a USB flash drive, external hard drive, magnetic disk, or optical disk.

[0081] The foregoing description is merely an exemplary embodiment of this disclosure and should not be construed as limiting the scope of this disclosure. Any equivalent changes and modifications made in accordance with the teachings of this disclosure shall still fall within the scope of this disclosure. Those skilled in the art will readily conceive of other embodiments of this disclosure upon considering the specification and the disclosure of practical truth. This application is intended to cover any variations, uses, or adaptations of this disclosure that follow the general principles of this disclosure and include common knowledge or customary techniques in the art not described in this disclosure. The specification and embodiments are considered exemplary only, and the scope and spirit of this disclosure are defined by the claims.

Claims

1. A method for detecting low-lying obstacles, characterized in that, The method is applied to a server and includes: Obtain the magnetic field reference range on the preset route, where the preset route is the preset inspection route of the inspection robot; Obtain multiple magnetic field strengths along the preset route; Determine whether the magnetic field strength is within the magnetic field reference range; if the magnetic field strength is not within the magnetic field reference range, then obtain the change in the magnetic field strength. If the magnetic field strength is not within the magnetic field reference range, then the change in the magnetic field strength is obtained, specifically including: Obtain the time value corresponding to each of the magnetic field intensities; Determine the difference in magnetic field strength between any two adjacent magnetic field strengths, and the duration between any two adjacent time values; Based on the difference in magnetic field strength and the corresponding duration, the change in the magnetic field strength between two adjacent magnetic fields is determined; Based on the multiple change values, an average change value is determined, which is used to reflect the change situation; Determine whether the change meets a preset standard. If the change meets the preset standard, then determine that there is a metal obstacle on the preset route.

2. The method for detecting low obstacles according to claim 1, characterized in that, The step of determining whether the change meets a preset standard, and if the change meets the preset standard, then determining that there is a metal obstacle on the preset route, specifically includes: Determine whether the average change value is greater than or equal to a preset first threshold. If the average change value is greater than or equal to the preset first threshold, determine whether the multiple magnetic field strengths show an increasing trend. If the strength of multiple magnetic fields shows an increasing trend, then it is determined that there is a metal obstacle on the preset route.

3. The method for detecting low obstacles according to claim 1, characterized in that, The acquisition of the magnetic field reference range on the preset route specifically includes: Obtain information that the preset route does not contain the metal obstacle; Obtain multiple standard values ​​of magnetic field strength along the preset route; Based on multiple standard values ​​of magnetic field strength, the mean and standard deviation of magnetic field strength are determined. Based on the mean magnetic field strength and the standard deviation of the magnetic field strength, the upper limit and lower limit of the magnetic field strength are determined; The magnetic field reference range is determined based on the upper limit and the lower limit of the magnetic field strength.

4. The method for detecting low obstacles according to claim 1, characterized in that, After obtaining multiple magnetic field strengths along the preset route, the method further includes: Determine whether the target magnetic field strength is greater than or equal to a preset second threshold, wherein the target magnetic field strength is any one of the plurality of magnetic field strengths; If the target magnetic field strength is determined to be greater than or equal to the preset second threshold, a stop command is sent to the inspection robot to stop the inspection robot from moving forward.

5. The method for detecting low obstacles according to claim 1, characterized in that, After determining that a metal obstacle exists on the preset route if the change meets a preset standard, the method further includes: An image acquisition command is sent to the inspection robot to enable the inspection robot to capture a target image along the preset route, the target image including the metal obstacle; Receive the target image; Obtain the current position data of the inspection robot; The location data is marked in the target image.

6. The method for detecting low obstacles according to claim 2, characterized in that, After determining that a metal obstacle exists on the preset route if the change meets a preset standard, the method further includes: Obtain verification information that the preset route does not contain the metal obstacle; Based on the average change value, the preset first threshold is adjusted until the average change value is less than the preset first threshold.

7. A low-lying obstacle detection device, characterized in that, The device is a server, comprising a first acquisition module (201), a second acquisition module (202), a first judgment module (203), and a second judgment module (204), wherein: The first acquisition module (201) is used to acquire the magnetic field reference range on the preset route, wherein the preset route is the preset inspection route of the inspection robot; The second acquisition module (202) is used to acquire multiple magnetic field strengths along the preset route; The first judgment module (203) is used to determine whether the magnetic field strength is within the magnetic field reference range. If the magnetic field strength is not within the magnetic field reference range, the change of the magnetic field strength is obtained. If the magnetic field strength is not within the magnetic field reference range, then the change in the magnetic field strength is obtained, specifically including: Obtain the time value corresponding to each of the magnetic field intensities; Determine the difference in magnetic field strength between any two adjacent magnetic field strengths, and the duration between any two adjacent time values; Based on the difference in magnetic field strength and the corresponding duration, the change in the magnetic field strength between two adjacent magnetic fields is determined; Based on the multiple change values, an average change value is determined, which is used to reflect the change situation; The second judgment module (204) is used to determine whether the change meets the preset standard. If the change meets the preset standard, it is determined that there is a metal obstacle on the preset route.

8. An electronic device, characterized in that, The device includes a processor (301), a memory (305), a user interface (303), and a network interface (304). The memory (305) is used to store instructions. The user interface (303) and the network interface (304) are both used to communicate with other devices. The processor (301) is used to execute the instructions stored in the memory (305) to cause the electronic device to perform the method as described in any one of claims 1-6.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores instructions that, when executed, perform the method as described in any one of claims 1-6.

Images