Underground sewage plant inspection robot adaptive control method based on environment perception

Abstract

The application provides an environmental perception-based self-adaptive control method for an underground sewage plant inspection robot, and relates to the technical field of inspection control.The method comprises the following steps: collecting environmental data of an inspection area through multiple sensors;determining a risk index of an un-inspected area according to the environmental data;obtaining a position coordinate of a current inspection robot; determining a priority of the un-inspected area according to the risk index and the position coordinate of the inspection robot; judging whether the moving speed of the inspection robot needs to be adjusted according to the risk index and a preset risk index; and if the moving speed of the inspection robot needs to be adjusted, determining an adjusted moving speed of the inspection robot according to the risk index.According to the application, the priority of the un-inspected area and the moving speed of the inspection robot can be adaptively controlled according to the position of the inspection robot and the risk index, thereby improving the accuracy of risk identification and the inspection efficiency.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of inspection control, and particularly relates to an underground sewage plant inspection robot adaptive control method based on environment perception. BACKGROUND

[0002] In the prior art, although the priority of the inspection task is adjusted by the environmental parameters and the inspection speed is controlled based on the feature point matching result, the influence of the position of the inspection robot on the priority result and the influence of the risk index on the moving speed are not considered, that is, the priority of the un-inspected area and the moving speed of the inspection robot cannot be adaptively controlled according to the position of the inspection robot and the risk index.

[0003] The information disclosed in the background section of this application is only intended to deepen the understanding of the general background of the application and should not be regarded as acknowledging or implying in any form that the information constitutes prior art known to those skilled in the art. SUMMARY

[0004] The present application provides an underground sewage plant inspection robot adaptive control method based on environment perception, which can solve the technical problem that the priority of the un-inspected area and the moving speed of the inspection robot cannot be adaptively controlled according to the position of the inspection robot and the risk index in the related art.

[0005] According to the present application, an underground sewage plant inspection robot adaptive control method based on environment perception is provided, comprising: dividing the underground sewage plant into a plurality of inspection areas, when the inspection robot completes the inspection of one of the inspection areas, collecting environmental data of the inspection area by a plurality of sensors, wherein the environmental data includes harmful gas concentration, environmental temperature, environmental humidity and a plurality of device vibration data; determining a risk index of the un-inspected area according to the environmental data; obtaining the coordinates of the current position of the inspection robot; determining the priority of the un-inspected area according to the risk index and the coordinates of the position of the inspection robot; determining whether the moving speed of the inspection robot needs to be adjusted according to the risk index and the preset risk index; if the moving speed of the inspection robot needs to be adjusted, determining the adjusted moving speed of the inspection robot according to the risk index.

[0006] Further, the determination of the risk index of the un-inspected area according to the environmental data comprises: determining the importance level of the inspection area; determining the risk index of the un-inspected area according to the importance level and the environmental data.

[0007] Further, the determination of the risk index of the un-inspected area according to the importance level and the environmental data comprises: according to the formula: determining a risk index of the s-th un-inspected area wherein, is an importance level of the s-th un-inspected area, is an ambient temperature of the s-th un-inspected area, is a preset ambient temperature, is an ambient humidity of the s-th un-inspected area, is a preset ambient humidity, is a maximum value of a plurality of equipment vibration data of the s-th un-inspected area, is a preset vibration data, is a concentration of the i-th harmful gas of the s-th un-inspected area, is a preset concentration of the i-th harmful gas, N is a number of harmful gases, i≤N, and s, i and N are positive integers, and max is a maximum value function.

[0008] Further, according to the risk index and the position coordinate of the inspection robot, a priority of the un-inspected area is determined, including: obtaining a center position coordinate of a plurality of un-inspected areas; determining a Euclidean distance from the position of the inspection robot to the center position of the plurality of un-inspected areas according to the position coordinate of the inspection robot and the center position coordinate of the un-inspected area; determining a probability of the inspection robot selecting the s-th un-inspected area for inspection according to the Euclidean distance and the risk index, wherein s is a positive integer; arranging the probability of the inspection robot selecting each un-inspected area for inspection in descending order to obtain a first order; and determining the priority of the un-inspected area according to the first order.

[0009] Further, according to the Euclidean distance and the risk index, the probability of the inspection robot selecting the s-th un-inspected area for inspection is determined, including: according to the formula: determining a probability of the inspection robot selecting the s-th un-inspected area for inspection wherein, is a Euclidean distance from the position of the inspection robot to the center position of the s-th un-inspected area, is a risk index of the s-th un-inspected area, is a distance attenuation coefficient, is an adjustment coefficient, M is a number of un-inspected areas, s≤M, and s and M are positive integers.

[0010] Further, judging whether the moving speed of the inspection robot needs to be adjusted according to the risk indexes and a preset risk index, including: if all the risk indexes of the un-inspected areas are less than the preset risk index, the moving speed of the inspection robot does not need to be adjusted; if the risk index of one of the un-inspected areas is greater than or equal to the preset risk index, the moving speed of the inspection robot needs to be adjusted.

[0011] Further, if the moving speed of the inspection robot needs to be adjusted, determining the adjusted moving speed of the inspection robot according to the risk indexes, including: obtaining historical risk indexes of a plurality of historical un-inspected areas when the inspection robot completes the inspection of a previous inspection area; averaging the historical risk indexes of the plurality of historical un-inspected areas corresponding to the current un-inspected area of the inspection robot to obtain a historical average risk index; averaging the risk indexes of the plurality of un-inspected areas to obtain an average risk index; obtaining a current moving speed of the inspection robot; and determining the adjusted moving speed of the inspection robot according to the historical average risk index, the average risk index and the current moving speed.

[0012] Further, determining the adjusted moving speed of the inspection robot according to the historical average risk index, the average risk index and the current moving speed, including: determining the adjusted moving speed of the inspection robot according to the following formula: determined adjusted moving speed of the inspection robot wherein, is the average risk index, is the historical average risk index, is the preset risk index, is the current moving speed of the inspection robot.

[0013] Technical effects: According to the present application, the potential risk degree of each area can be more accurately judged by the risk index based on actual environmental data. In combination with the risk index and the position coordinates of the inspection robot, the priority of the un-inspected area can be determined, so that the inspection robot can preferentially process the area with higher risk and closer distance, reasonably allocate inspection resources, and improve the inspection efficiency. According to the risk index and the preset risk index, it is determined whether the moving speed of the inspection robot needs to be adjusted. The dynamic judgment mechanism can respond to environmental changes, and when the environmental risk exceeds the preset range, the speed is adjusted in time to ensure the safety of the inspection process. When determining the risk index of the un-inspected area, the importance level of the un-inspected area and various environmental data can be used to determine the risk index of the un-inspected area, so as to more comprehensively and accurately evaluate the potential risk degree of the un-inspected area. Since the environmental data is constantly changing, new environmental data is collected after one inspection area is inspected, and the risk index is calculated by substituting the formula, so as to timely understand the risk condition change of the un-inspected area, and improve the comprehensiveness, accuracy and timeliness of the risk index. When determining the probability of the inspection robot selecting the s-th un-inspected area for inspection, the probability of the inspection robot selecting the s-th un-inspected area for inspection can be determined based on the Euclidean distance and the risk index, which combines the risk index and the spatial distance, helps to reasonably plan the inspection route, makes the inspection robot preferentially process the area with higher risk and closer distance, avoids blind inspection and resource waste, improves the inspection efficiency, and ensures the safe and stable operation of the underground sewage plant. When determining the adjusted moving speed of the inspection robot, the adjusted moving speed of the inspection robot can be determined based on the historical average risk index, the average risk index and the current moving speed. The speed is dynamically adjusted according to the risk change, which realizes the rapid response and energy optimization in the environmental mutation, and improves the adaptability and inspection effect of the inspection robot.

[0014] It should be understood that the above general description and the following detailed description are exemplary and explanatory, but not limiting the present application. Other features and aspects of the present application will be more apparent from the following detailed description of exemplary embodiments with reference to the accompanying drawings. BRIEF DESCRIPTION OF DRAWINGS

[0015] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the drawings needed in the embodiment or prior art description will be briefly introduced below. Obviously, the drawings in the following description are only some embodiments of the present application, and those skilled in the art can also obtain other embodiments according to these drawings without creative labor;

[0016] Figure 1 Exemplarily, a flowchart of an environmental perception-based self-adaptive control method of an underground sewage plant inspection robot according to an embodiment of the present application is shown;

[0017] Figure 2 A flow chart of calculating a risk index according to an embodiment of the present application is exemplarily shown;

[0018] Figure 3 A flow chart of determining a priority of an un-inspected area according to an embodiment of the present application is exemplarily shown;

[0019] Figure 4 A flow chart of judging adjustment of a moving speed according to an embodiment of the present application is exemplarily shown;

[0020] Figure 5 A flow chart of calculating an adjusted moving speed of an inspection robot according to an embodiment of the present application is exemplarily shown. DETAILED DESCRIPTION

[0021] To make the objects, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only a part but not all of the embodiments of the present application. Based on the embodiments in the present application, all other embodiments obtained by a person of ordinary skill in the art without creative work fall within the protection scope of the present application.

[0022] The technical solutions of the present application will be described in detail below with specific embodiments. The following specific embodiments can be combined with each other, and some embodiments can not be described again for the same or similar concepts or processes.

[0023] Figure 1 A flow chart of an underground sewage plant inspection robot adaptive control method based on environment perception according to an embodiment of the present application is exemplarily shown, and the method comprises the following steps: S1, dividing an underground sewage plant into a plurality of inspection areas, collecting environment data of the inspection area through a plurality of sensors when an inspection robot completes inspection of one of the inspection areas, wherein the environment data comprises harmful gas concentration, environment temperature, environment humidity and a plurality of device vibration data; S2, determining a risk index of an un-inspected area according to the environment data; S3, obtaining a position coordinate of a current inspection robot; S4, determining a priority of the un-inspected area according to the risk index and the position coordinate of the inspection robot; S5, judging whether the moving speed of the inspection robot needs to be adjusted according to the risk index and a preset risk index; and S6, if the moving speed of the inspection robot needs to be adjusted, determining an adjusted moving speed of the inspection robot according to the risk index.

[0024] The environment-aware adaptive control method for underground sewage plant inspection robots according to the embodiment of the present application can more accurately determine the potential risk degree of each area based on the risk index based on actual environment data. In combination with the risk index and the position coordinates of the inspection robot, the priority of the un-inspected area is determined, so that the inspection robot can preferentially process the area with higher risk and closer distance, reasonably allocate inspection resources, and improve the inspection efficiency. According to the risk index and the preset risk index, it is determined whether the moving speed of the inspection robot needs to be adjusted. The dynamic determination mechanism can respond to environmental changes, and when the environmental risk exceeds the preset range, the speed is adjusted in time to ensure the safety of the inspection process.

[0025] According to one embodiment of the present application, in step S1, according to the overall layout and structural characteristics of the underground sewage plant, a scientific and reasonable planning method is used to accurately divide it into multiple independent inspection areas, so that each inspection area has a clear boundary, for example, the water treatment area, the sludge dewatering area, the electrical control room area, and the water pump room area. When the inspection robot completes the comprehensive inspection of a certain inspection area, it is determined that the inspection work of the area has been completed, at which time the robot is at the boundary position of the inspection area. The environment data of the inspection area is collected in real time by a gas concentration sensor, a temperature and humidity sensor, and a vibration sensor. The gas concentration sensor is used to detect harmful gas concentration (for example, hydrogen sulfide, ammonia), the temperature and humidity sensor is used to measure the environmental temperature and humidity, and the vibration sensor is used to monitor the vibration data of the equipment (for example, water grille, water pump).

[0026] According to one embodiment of the present application, in step S2, the risk index of the un-inspected area is determined according to the environment data.

[0027] Figure 2 An exemplary flow chart for calculating the risk index according to the embodiment of the present application is shown.

[0028] According to one embodiment of the present application, step S2 includes: step S21, determining the importance level of the inspection area; and step S22, determining the risk index of the un-inspected area according to the importance level and the environment data.

[0029] According to one embodiment of the present application, all inspection areas can be divided into three major areas of sludge treatment area, sewage treatment area, and equipment room area according to the function. The importance level of the sludge treatment area is 3, the importance level of the sewage treatment area is 5, and the importance level of the equipment room area is 7. The environment data includes various harmful gas concentrations, environmental temperature, environmental humidity, and various equipment vibration data, reflecting the current environmental conditions and equipment operation status of multiple un-inspected areas. The risk index can accurately quantify the risk degree of the un-inspected area.

[0030] According to one embodiment of the present application, the risk index of the un-inspected area is determined according to the importance level and the environmental data, comprising: determining the risk index of the s-th un-inspected area according to formula (1) ,

[0031] (1),

[0032] wherein, is the importance level of the s-th un-inspected area, is the environmental temperature of the s-th un-inspected area, is the preset environmental temperature, is the environmental humidity of the s-th un-inspected area, is the preset environmental humidity, is the maximum value of the plurality of equipment vibration data of the s-th un-inspected area, is the preset vibration data, is the concentration of the i-th harmful gas of the s-th un-inspected area, is the preset concentration of the i-th harmful gas, N is the number of harmful gases, i≤N, and s, i and N are positive integers, and max is the maximum value function.

[0033] According to one embodiment of the present application, in formula (1), is the logarithm of the importance level of the s-th un-inspected area, so that the influence of the importance level on the risk index is more smooth and reasonable. is the relative difference between the environmental temperature of the s-th un-inspected area and the preset environmental temperature (for example, 28℃) plus 1, the larger the result is, the greater the actual environmental temperature deviates from the preset environmental temperature, which will adversely affect the normal operation of the equipment, and the greater the risk of equipment failure, for example, high temperature causes equipment overheating and damage, and low temperature reduces the operation efficiency of the equipment or causes failure. is the relative difference between the environmental humidity of the s-th un-inspected area and the preset environmental humidity (for example, 70%) plus 1, the larger the result is, the greater the actual environmental humidity deviates from the preset environmental humidity, which will also adversely affect the normal operation of the equipment, and the greater the risk of equipment failure, for example, high humidity will cause equipment to be damp, short circuit, and low humidity will cause static electricity and other problems. is the ratio of the maximum value of the plurality of equipment vibration data of the s-th un-inspected area to the preset vibration data (for example, vibration amplitude of 5mm), the larger the ratio is, the greater the actual vibration data deviates from the preset vibration data, the more serious the abnormality of the equipment vibration is, and the greater the risk of the un-inspected area. The maximum value of the ratio of the concentration of each harmful gas to the preset concentration of the harmful gas in the s-th un-inspected area is larger, which indicates that the concentration of a certain harmful gas is seriously over-standard, and the personnel safety and normal operation of the equipment are threatened, thereby increasing the risk of the un-inspected area. Multiplying the above , , , and , the risk index of the s-th un-inspected area can be obtained. The larger the risk index is, the higher the risk of the un-inspected area is.

[0034] In this way, the risk index of the un-inspected area can be determined through the importance level of the un-inspected area and the environmental data, so that the potential risk degree of the un-inspected area can be more comprehensively and accurately evaluated. Since the environmental data is constantly changing, new environmental data can be collected after an inspection area is inspected, and the risk index can be calculated by substituting the new environmental data into the formula, so that the risk status of the un-inspected area can be understood in a timely manner, and the comprehensiveness, accuracy and timeliness of the risk index can be improved.

[0035] According to an embodiment of the present application, in step S3, the position coordinates of the current inspection robot can be obtained by a positioning device (for example, a GPS) in the inspection robot.

[0036] According to an embodiment of the present application, in step S4, the priority of the un-inspected area is determined according to the risk index and the position coordinates of the inspection robot.

[0037] Figure 3 An exemplary flowchart for determining the priority of the un-inspected area according to an embodiment of the present application is shown.

[0038] According to an embodiment of the present application, step S4 includes: step S41, obtaining the center position coordinates of the plurality of un-inspected areas; step S42, determining the Euclidean distance from the position of the inspection robot to the center positions of the plurality of un-inspected areas according to the position coordinates of the inspection robot and the center position coordinates of the un-inspected areas; step S43, determining the probability that the inspection robot selects to inspect the s-th un-inspected area according to the Euclidean distance and the risk index, wherein s is a positive integer; step S44, arranging the probabilities that the inspection robot selects to inspect each un-inspected area in descending order to obtain a first order; and step S45, determining the priority of the un-inspected area according to the first order.

[0039] According to one embodiment of the present application, the center position coordinates of each un-inspected area are obtained through the building map of the underground sewage plant. The Euclidean distance is a commonly used method for measuring the straight-line distance between two points in space. After obtaining the coordinates of the current position of the inspection robot and the center position coordinates of each un-inspected area, the Euclidean distance formula is used for calculation, which can quantify the proximity of the inspection robot to the center position of each un-inspected area. The risk index reflects the risk degree of the un-inspected area, while the Euclidean distance reflects the convenience of the inspection robot to reach the area. The probability of the inspection robot selecting a certain un-inspected area is determined by comprehensively considering these two factors. The probability values are arranged in descending order to obtain a first order. The first order directly determines the priority of the un-inspected area. The higher the priority of the un-inspected area, the higher the priority, indicating that the inspection robot will preferentially inspect it.

[0040] According to one embodiment of the present application, the probability of the inspection robot selecting the s-th un-inspected area for inspection is determined according to the Euclidean distance and the risk index, including: determining the probability of the inspection robot selecting the s-th un-inspected area for inspection according to formula (2) ,

[0041] (2),

[0042] wherein, is the Euclidean distance from the position of the inspection robot to the center position of the s-th un-inspected area, is the risk index of the s-th un-inspected area, is a distance attenuation coefficient, is an adjustment coefficient, M is the number of un-inspected areas, s≤M, and s and M are positive integers.

[0043] According to one embodiment of the present application, in formula (2), is the reciprocal of the Euclidean distance from the position of the inspection robot to the center position of the s-th un-inspected area, wherein, is a distance attenuation coefficient, which can be 0.5, indicating that the distance factor has a negative effect on the selection probability of the inspection robot. The larger the Euclidean distance, the smaller the value, indicating that the farther the un-inspected area, the lower the probability of being selected by the inspection robot. is an exponential function of the risk index of the s-th un-inspected area. As increases, the value increases, wherein, is an adjustment coefficient, which can be 1.5, used to adjust the influence degree of the risk index on the probability, is the sum of the exponential functions of the risk indexes of all un-inspected areas, To normalize the exponential function of the risk index, the positive influence of the risk index factor on the selection probability of the inspection robot is represented, and the higher the risk index of the un-inspected area, the greater the probability of being selected by the inspection robot. The above and are multiplied to obtain the probability of the inspection robot selecting the s-th un-inspected area for inspection. The greater the probability, the greater the probability of the inspection robot prioritizing the un-inspected area for inspection.

[0044] In this way, the probability of the inspection robot selecting the s-th un-inspected area for inspection can be determined based on the Euclidean distance and the risk index, combining the risk index and the spatial distance, which helps to reasonably plan the inspection route, makes the inspection robot prioritize the areas with higher risk and closer distance, avoids blind inspection and resource waste, improves the inspection efficiency, and ensures the safe and stable operation of the underground sewage plant.

[0045] According to an embodiment of the present application, in step S5, it is judged whether the moving speed of the inspection robot needs to be adjusted according to the risk index and a preset risk index.

[0046] Figure 4 An exemplary flowchart of judging the adjustment of the moving speed according to an embodiment of the present application is shown.

[0047] According to an embodiment of the present application, step S5 includes: step S51, if the risk index of all un-inspected areas is less than the preset risk index, the moving speed of the inspection robot does not need to be adjusted; and step S52, if the risk index of one of the multiple un-inspected areas is greater than or equal to the preset risk index, the moving speed of the inspection robot needs to be adjusted.

[0048] According to an embodiment of the present application, if the risk index of all un-inspected areas is less than the preset risk index (for example, 4.5), it indicates that the risk of all un-inspected areas is at a relatively low and acceptable level, and the moving speed of the inspection robot does not need to be adjusted. If the risk index of one of the multiple un-inspected areas is greater than or equal to the preset risk index, it indicates that there is a high-risk area that may cause potential harm to personnel, equipment or the environment, and in order to enable the inspection robot to timely discover and handle possible safety hazards, the moving speed of the inspection robot needs to be adjusted.

[0049] According to an embodiment of the present application, in step S6, if the moving speed of the inspection robot needs to be adjusted, the adjusted moving speed of the inspection robot is determined according to the risk index.

[0050] Figure 5 An exemplary flowchart of calculating the adjusted moving speed of the inspection robot according to an embodiment of the present application is shown.

[0051] According to one embodiment of the present application, step S6 comprises: step S61, obtaining historical risk indexes of a plurality of historical un-inspected areas when the inspection robot completes the inspection of the last inspection area; step S62, averaging the historical risk indexes of the plurality of historical un-inspected areas corresponding to the current un-inspected area of the inspection robot to obtain a historical average risk index; step S63, averaging the risk indexes of the plurality of un-inspected areas to obtain an average risk index; step S64, obtaining a current moving speed of the inspection robot; and step S65, determining an adjusted moving speed of the inspection robot according to the historical average risk index, the average risk index and the current moving speed.

[0052] According to one embodiment of the present application, the historical risk index reflects the risk degree of each historical un-inspected area when the inspection robot completes the inspection of the last inspection area, wherein the number of historical un-inspected areas is one more than the number of current un-inspected areas, i.e. the area that the current inspection robot has just completed the inspection. For the current un-inspected area, the corresponding area is selected from the historical un-inspected areas, i.e. the area that the current inspection robot has just completed the inspection is subtracted from the historical un-inspected areas, the historical risk indexes of the corresponding historical un-inspected areas are averaged to obtain a historical average risk index, which represents the historical risk situation of all current un-inspected areas (i.e. the area that the current inspection robot has just completed the inspection is subtracted from the historical un-inspected areas) when the inspection robot completes the inspection of the last inspection area. The risk indexes of the plurality of un-inspected areas are averaged to obtain an average risk index, which represents the current risk situation of all un-inspected areas when the inspection robot completes the inspection of one of the inspection areas, i.e. at the current time. The current moving speed of the inspection robot is obtained by a speed sensor built in the inspection robot. The purpose of adjusting the moving speed of the inspection robot is to make the inspection robot inspect at a more appropriate speed according to the risk situation of the current inspection area and historical experience, which can improve the inspection efficiency and make the inspection task successfully completed.

[0053] According to one embodiment of the present application, the adjusted moving speed of the inspection robot is determined according to the historical average risk index, the average risk index and the current moving speed, comprising: determining the adjusted moving speed of the inspection robot according to formula (3) ,

[0054] (3),

[0055] wherein, is the average risk index, is the historical average risk index, is a preset risk index, is the current moving speed of the inspection robot.

[0056] According to one embodiment of the present application, in formula (3), is the ratio of the difference between the average risk index and the historical average risk index to the preset risk index, which is positive, indicating that the current un-inspected area is more risky than the historical situation, and needs to speed up to reach the un-inspected area for inspection to respond to the risk situation in time, and negative, indicating that the current un-inspected area is less risky than the historical situation, and can slow down to save power. is the adjusted speed of the inspection robot according to the change in risk.

[0057] In this way, the adjusted speed of the inspection robot can be determined based on the historical average risk index, the average risk index and the current speed, and the speed is dynamically adjusted according to the change in risk, realizing fast response and energy optimization in the case of environmental mutation, and improving the adaptability and inspection effect of the inspection robot.

[0058] According to the environment-aware underground sewage plant inspection robot adaptive control method of the embodiment of the present application, the potential risk degree of each area can be more accurately judged through the risk index based on the actual environment data. In combination with the risk index and the position coordinates of the inspection robot, the priority of the un-inspected area can be determined, so that the inspection robot can preferentially process the area with higher risk and closer distance, the inspection resources can be reasonably allocated, and the inspection efficiency can be improved. According to the risk index and the preset risk index, it is judged whether the moving speed of the inspection robot needs to be adjusted. The dynamic judgment mechanism can respond to the environmental changes, and when the environmental risk exceeds the preset range, the speed is timely adjusted to ensure the safety of the inspection process. When determining the risk index of the un-inspected area, the importance level of the un-inspected area and various environment data can be used to determine the risk index of the un-inspected area, so that the potential risk degree of the un-inspected area can be more comprehensively and accurately evaluated. Since the environment data is constantly changing, new environment data can be collected after one inspection area is inspected and substituted into the formula to calculate the risk index, so that the risk status change of the un-inspected area can be understood in time, and the comprehensiveness, accuracy and timeliness of the risk index can be improved. When determining the probability of the inspection robot selecting the s-th un-inspected area for inspection, the probability of the inspection robot selecting the s-th un-inspected area for inspection can be determined based on the Euclidean distance and the risk index, which combines the risk index and the spatial distance, helps to reasonably plan the inspection route, makes the inspection robot preferentially process the area with higher risk and closer distance, avoids blind inspection and resource waste, improves the inspection efficiency, and ensures the safe and stable operation of the underground sewage plant. When determining the adjusted moving speed of the inspection robot, the adjusted moving speed of the inspection robot can be determined based on the historical average risk index, the average risk index and the current moving speed, the speed is dynamically adjusted through the risk change, the rapid response and energy consumption optimization in the environmental mutation are realized, and the adaptability and inspection effect of the inspection robot are improved.

[0059] The present application can be a method, device, system and / or computer program product. The computer program product can include a computer readable storage medium having computer readable program instructions loaded thereon for performing various aspects of the present application.

[0060] Those skilled in the art will understand that the embodiments of the present application shown in the above description and the drawings are only examples and do not limit the present application. The purpose of the present application has been fully and effectively achieved. The function and structural principle of the present application has been shown and explained in the embodiments, and the embodiments of the present application can be any modification or modification without departing from the principle.

Claims

1. An adaptive control method for an underground wastewater treatment plant inspection robot based on environmental perception, characterized in that, include: The underground sewage plant is divided into multiple inspection areas. When an inspection robot completes the inspection of one of the inspection areas, environmental data of the inspection area is collected through various sensors, wherein the environmental data includes harmful gas concentration, environmental temperature, environmental humidity, and various equipment vibration data. According to the environmental data, a risk index of an un-inspected area is determined. The coordinates of the current position of the inspection robot are obtained. According to the risk index and the coordinates of the position of the inspection robot, the priority of the un-inspected area is determined, including: obtaining the central position coordinates of multiple un-inspected areas; according to the coordinates of the position of the inspection robot and the central position coordinates of the un-inspected areas, the Euclidean distance from the position of the inspection robot to the central position of the multiple un-inspected areas is determined; according to the Euclidean distance and the risk index, the probability that the inspection robot selects to inspect the s-th un-inspected area is determined, including: according to the formula: determining the probability that the inspection robot selects to inspect the s-th un-inspected area , wherein, is the Euclidean distance from the position of the inspection robot to the central position of the s-th un-inspected area, is the risk index of the s-th un-inspected area, is the distance attenuation coefficient, is the adjustment coefficient, M is the number of un-inspected areas, s≤M, and s and M are positive integers; the probability that the inspection robot selects to inspect each un-inspected area is arranged in descending order to obtain a first order; according to the first order, the priority of the un-inspected area is determined; according to the risk index and a preset risk index, it is judged whether the moving speed of the inspection robot needs to be adjusted; if the moving speed of the inspection robot needs to be adjusted, the adjusted moving speed of the inspection robot is determined according to the risk index; according to the environmental data, the risk index of the un-inspected area is determined, including: determining the importance level of the inspection area; according to the importance level and the environmental data, the risk index of the un-inspected area is determined; according to the importance level and the environmental data, the risk index of the un-inspected area is determined, including: according to the formula: determining the risk index of the s-th un-inspected area , wherein, is the importance level of the s-th un-inspected area, is the environmental temperature of the s-th un-inspected area, is a preset environmental temperature, is the environmental humidity of the s-th un-inspected area, is a preset environmental humidity, is the maximum value of the various equipment vibration data of the s-th un-inspected area, is a preset vibration data, Let be the concentration of the i-th type of harmful gas in the s-th uninspected area. Let s be the concentration of the i-th type of harmful gas, N be the quantity of harmful gas, i ≤ N, and s, i and N are all positive integers, and max is the function to take the maximum value.

2. The adaptive control method for an underground sewage treatment plant inspection robot based on environmental perception as described in claim 1, characterized in that, Based on the risk indicators and preset risk indicators, determine whether the movement speed of the inspection robot needs to be adjusted, including: if the risk indicators of all uninspected areas are less than the preset risk indicators, then the movement speed of the inspection robot does not need to be adjusted; if the risk indicator of one of the uninspected areas is greater than or equal to the preset risk indicators, then the movement speed of the inspection robot needs to be adjusted.

3. The adaptive control method for an underground sewage treatment plant inspection robot based on environmental perception as described in claim 2, characterized in that, If it is necessary to adjust the movement speed of the inspection robot, the adjusted movement speed of the inspection robot is determined according to the risk indicators, including: obtaining historical risk indicators of multiple historically uninspected areas when the inspection robot completed the inspection of the previous inspection area; averaging the historical risk indicators of multiple historically uninspected areas corresponding to the current uninspected area of ​​the inspection robot to obtain a historical average risk indicator; averaging the risk indicators of multiple uninspected areas to obtain an average risk indicator; obtaining the current movement speed of the inspection robot; and determining the adjusted movement speed of the inspection robot based on the historical average risk indicator, the average risk indicator, and the current movement speed.

4. The adaptive control method for an underground sewage treatment plant inspection robot based on environmental perception as described in claim 3, characterized in that, The adjusted movement speed of the inspection robot is determined based on the historical average risk index, the average risk index, and the current movement speed, including: according to the formula: Determine the adjusted movement speed of the inspection robot ,in, This is an average risk indicator. This is a historical average risk indicator. To preset risk indicators, This represents the current moving speed of the inspection robot.

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