An intelligent inspection method based on automatic door recognition

Abstract

The present invention discloses an intelligent inspection method based on automatic door recognition. By adjusting the inspection sequence, the number of round trips of the inspection robot between different areas is significantly reduced, the task completion time and energy consumption are reduced, and in addition, the priority inspection of high-priority automatic doors is ensured, thereby improving the inspection frequency and safety of key areas; by setting the automatic door opening and closing strategy, it is ensured that the robot can safely and efficiently pass through each automatic door during the inspection process, thereby reducing inspection interruptions or delays caused by improper door operation; by linking the real-time monitoring system and analyzing the operation data of the automatic door, the abnormal behavior of the automatic door can be timely identified and processed; the present invention combines the automatic access control technology with the intelligent inspection system, realizes efficient and accurate inspection operation, and by setting a specific automatic door as a landmark point in the inspection path, the position and status of the inspection equipment can be automatically identified, thereby dynamically adjusting the inspection strategy and improving the inspection coverage and efficiency.

Description

Technical Field

[0001] The present invention relates to the technical field of data processing, and in particular to an intelligent inspection method based on automatic door recognition. Background Art

[0002] With the rapid development of artificial intelligence and automation technology, intelligent inspection robots are increasingly used in industry, commerce and public places. Traditional inspection methods rely on manual patrols, which have problems such as high labor costs, low efficiency, and easy to miss inspections. Intelligent inspection robots, with their technical advantages such as autonomous navigation, real-time monitoring and data analysis, have effectively improved the efficiency and accuracy of inspection work. In the existing technology, inspection robots mainly patrol the area through preset inspection routes, and complete obstacle recognition and path planning based on built-in sensors and preset algorithms.

[0003] However, the path planning algorithms in existing inspection technologies are mostly based on static environment assumptions and cannot fully consider the behavioral characteristics of dynamic obstacles, such as the switch status, position and frequency of automatic doors. This results in inspection robots often being unable to perform tasks efficiently in complex environments, especially in areas where automatic doors are frequently operated. The robot may fail to obtain door status information in real time, resulting in path planning errors or low inspection efficiency. In addition, traditional inspection robots respond slowly to abnormal conditions and are unable to identify and handle abnormal behaviors of automatic doors in a timely manner, increasing potential safety hazards. Although some technologies attempt to solve these problems by increasing the number of sensors or increasing the complexity of path planning algorithms, this often results in increased robot energy consumption and increased computational burden, with limited results.

[0004] The above information is presented as background information only to assist with understanding the present disclosure and no determination or admission is made as to whether any of the above may be used as prior art with respect to the present disclosure. Summary of the invention

[0005] The invention provides an intelligent inspection method based on automatic door recognition to solve the problems existing in the prior art.

[0006] To achieve the above object, the present invention provides the following technical solutions:

[0007] In a first aspect, the present invention provides an intelligent inspection method based on automatic door recognition, the method comprising:

[0008] Generate a first inspection route according to the inspection area map data, based on the inspection task requirements and the parameter set of the inspection robot;

[0009] Combining the automatic door priority and the first inspection route, optimizing the inspection sequence and route, and generating a second inspection route;

[0010] Formulate an opening and closing strategy for each automatic door according to the parameter set of the inspection robot and the type of automatic door;

[0011] Starting a real-time monitoring system to analyze the operation data of the automatic door in real time and identify abnormal behavior;

[0012] When abnormal behavior of the automatic door is detected, an alarm system is immediately triggered.

[0013] Furthermore, in the intelligent inspection method based on automatic door recognition, generating the first inspection route includes:

[0014] Define route costs and motion constraints;

[0015] Initialize an open list and a closed list according to the inspection area map data and the parameter set of the inspection robot, wherein the open list contains nodes to be evaluated and the initial state is the starting node, and the closed list contains evaluated nodes and is initially empty;

[0016] In the first inspection route generation process, the following steps are looped and executed until the target point is found or the open list is empty:

[0017] Selecting a node with a minimum route cost value from the open list as the current node;

[0018] If the current node is the target node, build the route and end;

[0019] When calculating neighbor nodes, it is necessary to verify whether the route satisfies all motion constraints;

[0020] For each of the neighbor nodes, perform the following operations:

[0021] If the neighbor node is in the closed list or does not meet the motion constraint condition, it is ignored;

[0022] The actual cost and the heuristic estimated cost of the neighbor nodes are calculated and adjusted by applying motion constraints.

[0023] Furthermore, in the intelligent inspection method based on automatic door recognition, the route cost includes:

[0024] ;

[0025] in, is the total route cost of the current node n, is the actual cost from the starting point to the current node n, is the heuristic estimate of the cost from the current node n to the goal point.

[0026] Furthermore, in the intelligent inspection method based on automatic door recognition, if the neighbor node is not in the open list, the node information is updated and added to the open list.

[0027] Furthermore, in the intelligent inspection method based on automatic door recognition, the combining of the automatic door priority and the first inspection route, optimizing the inspection sequence and route, and generating the second inspection route comprises:

[0028] In the first inspection route, identify the positions of all automatic doors passed by the route;

[0029] According to the urgency of the current inspection task, set the emergency weight factor and adjust the priority of the automatic door;

[0030] Use a weighted calculation method to comprehensively consider the frequency of use, importance, and urgency of each automatic door to calculate the priority value of each automatic door:

[0031] ;

[0032] in, is the priority value of the i-th automatic door, The usage frequency of each automatic door in the historical inspection tasks, is the weight of the usage frequency, Score the functional importance of automatic doors in inspection tasks, is the importance score weight, is the emergency weight factor;

[0033] All automatic doors are prioritized Sort from high to low to get the automatic door priority list;

[0034] According to the automatic door priority data and the first inspection route, the inspection sequence and route are optimized to generate the second inspection route.

[0035] Furthermore, in the intelligent inspection method based on automatic door recognition, the optimization goal of optimizing the inspection sequence and route is:

[0036] Optimize the inspection sequence of automatic doors;

[0037] While meeting the door priority, the overall route is minimized to reduce the robot's movement time and energy consumption;

[0038] For automatic doors with similar priorities, arrange adjacent doors to be checked in sequence.

[0039] Furthermore, in the intelligent inspection method based on automatic door recognition, the following optimization algorithms and strategies are used to achieve the optimization goal:

[0040] For each high-priority automatic door, calculate the insertion position in the current route to minimize the total route length:

[0041] ;

[0042] in, For and Insert automatic door between The resulting increase in routes, From route point To the automatic door The distance For automatic door To route point The distance For automatic door not inserted When, route point arrive distance;

[0043] When deciding the insertion position, not only the increase in route length is considered, but also the priority of the automatic door:

[0044] ;

[0045] in, For automatic doors The relative priority weight of Represents the route cost after inserting a certain automatic door;

[0046] For each high priority automatic door , calculate the time it takes to insert it into different positions of the inspection route ; Select The smallest insertion position is used to adjust the inspection route; the above process is repeated until all automatic doors are inserted and an optimized second inspection route is generated.

[0047] In a second aspect, the present invention provides an intelligent inspection system based on automatic door recognition, based on the intelligent inspection method based on automatic door recognition provided in the first aspect above, the system comprises:

[0048] An inspection route generation module is used to generate a first inspection route according to the inspection area map data, based on the inspection task requirements and the inspection robot parameter set;

[0049] A path optimization module, used to optimize the inspection sequence and path by combining the automatic door priority and the first inspection route, and generate a second inspection route;

[0050] The door control strategy formulation module is used to formulate an opening and closing strategy for each automatic door based on the parameter set of the inspection robot and the type of automatic door;

[0051] A real-time monitoring module, used to start a real-time monitoring system, analyze the operation data of the automatic door in real time, and identify abnormal behavior;

[0052] The abnormal alarm module is used to immediately trigger the alarm system when abnormal behavior of the automatic door is detected.

[0053] In a third aspect, the present invention provides a computer device including a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, the intelligent inspection method based on automatic door recognition as provided in the first aspect above is implemented.

[0054] In a fourth aspect, the present invention provides a computer-readable storage medium having computer-executable instructions stored thereon, wherein the computer-executable instructions are executed by a computer processor to implement the intelligent inspection method based on automatic door recognition as provided in the first aspect above.

[0055] Compared with the prior art, the present invention has the following beneficial effects:

[0056] The present invention provides an intelligent inspection method based on automatic door recognition, which significantly reduces the number of round trips of the inspection robot between different areas by adjusting the inspection sequence, reduces the task completion time and energy consumption, and ensures priority inspection of high-priority automatic doors, thereby improving the inspection frequency and safety of key areas; by setting the automatic door opening and closing strategy, it ensures that the robot can pass through each automatic door safely and efficiently during the inspection process, reducing inspection interruptions or delays caused by improper door operation; by linking the real-time monitoring system, the operation data of the automatic door is analyzed in real time, and the abnormal behavior of the automatic door can be timely identified and processed; in summary, the present invention combines the automatic access control technology with the intelligent inspection system to realize efficient and accurate inspection operations, and by setting specific automatic doors as landmarks in the inspection path, it can automatically identify the position and status of the inspection equipment, thereby dynamically adjusting the inspection strategy and improving the inspection coverage and efficiency.

[0057] The present invention has other features and advantages, which will be apparent from or will be described in detail in the accompanying drawings and the following detailed description incorporated herein, which together serve to explain the specific principles of the invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0058] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0059] Figure 1 It is a flowchart of an intelligent inspection method based on automatic door recognition provided by the first embodiment of the present invention;

[0060] Figure 2 It is a complete flow chart of an intelligent inspection method based on automatic door recognition provided by the first embodiment of the present invention;

[0061] Figure 3 This is a functional module diagram of an intelligent inspection system based on automatic door recognition provided by Embodiment 2 of the present invention;

[0062] Figure 4 It is a structural diagram of a computer device provided in Embodiment 3 of the present invention. DETAILED DESCRIPTION

[0063] In order to explain in detail the possible application scenarios, technical principles, specific schemes that can be implemented, and the purposes and effects that can be achieved, the following is a detailed description of the specific embodiments listed in conjunction with the accompanying drawings. The embodiments described herein are only used to more clearly illustrate the technical solutions of the present application, and are therefore only used as examples, and cannot be used to limit the scope of protection of the present application.

[0064] Reference to "embodiment" herein means that the specific features, structures or characteristics described in conjunction with the embodiment may be included in at least one embodiment of the present application. The term "embodiment" appearing in various places in the specification does not necessarily refer to the same embodiment, nor does it particularly limit its independence or association with other embodiments. In principle, in the present application, as long as there is no technical contradiction or conflict, the various technical features mentioned in the embodiments can be combined in any way to form a corresponding implementable technical solution.

[0065] Unless otherwise defined, the technical terms used in this document have the same meanings as those generally understood by those skilled in the art to which this application belongs; the use of relevant terms in this document is only for describing specific embodiments and is not intended to limit this application.

[0066] In the description of this application, the term "and / or" is an expression used to describe the logical relationship between objects, indicating that three relationships may exist, for example, A and / or B, which means: A exists, B exists, and A and B exist at the same time. In addition, the character " / " in this article generally indicates that the objects before and after are in an "or" logical relationship.

[0067] In the present application, terms such as “first” and “second” are merely used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship of quantity, priority or sequence between these entities or operations.

[0068] Without further limitations, in this application, the words "include", "comprises", "has" or other similar expressions used in the sentences are intended to cover non-exclusive inclusion. These expressions do not exclude the presence of additional elements in the process, method or product including the elements, so that the process, method or product including a series of elements may include not only those limited elements, but also other elements not explicitly listed, or also include elements inherent to such process, method or product.

[0069] In this application, expressions such as "greater than", "less than", "exceed" and the like are understood to exclude the number itself; expressions such as "above", "below", "within" and the like are understood to include the number itself. In addition, in the description of the embodiments of this application, "multiple" means more than two (including two), and similar expressions related to "multiple" are also understood in this way, such as "multiple groups", "multiple times", etc., unless otherwise clearly and specifically limited.

[0070] In the description of the embodiments of the present application, space-related expressions used, such as "center", "longitudinal", "lateral", "length", "width", "thickness", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "vertical", "top", "bottom", "inside", "outside", "clockwise", "counterclockwise", "axial", "radial", "circumferential", etc., indicate the orientation or position relationship based on the orientation or position relationship shown in the specific embodiments or drawings, and are only for the convenience of describing the specific embodiments of the present application or facilitating the reader's understanding, and do not indicate or imply that the referred device or component must have a specific position, a specific orientation, or be constructed or operated in a specific orientation, and therefore cannot be understood as a limitation on the embodiments of the present application.

[0071] Unless otherwise expressly specified or limited, in the description of the embodiments of the present application, the terms such as "install", "connect", "connect", "fix", "set", etc. used should be understood in a broad sense. For example, the "connection" can be a fixed connection, a detachable connection, or an integrated setting; it can be a mechanical connection, an electrical connection, or a communication connection; it can be a direct connection, or it can be indirectly connected through an intermediate medium; it can be the internal connection of two elements or the interaction relationship between two elements. For technicians in the technical field to which the present application belongs, the specific meanings of the above terms in the embodiments of the present application can be understood according to the specific circumstances.

[0072] Embodiment 1

[0073] Please refer to Figure 1-2 , is a flow chart of an intelligent inspection method based on automatic door recognition provided by Embodiment 1 of the present invention. The method specifically comprises the following steps:

[0074] S1. Generate a first inspection route according to the inspection area map data, based on the inspection task requirements and the inspection robot parameter set.

[0075] S1.1: Receive input inspection area map data and inspection task requirements, where the inspection area map data includes information such as regional plane layout and obstacle distribution, and the inspection task requirements include parameters such as inspection targets and time limits.

[0076] S1.2: Obtain a parameter set of the inspection robot, wherein the parameter set includes information such as the type, size, power status, sensor configuration, etc. of the robot, which is used for subsequent generation of a matching inspection route.

[0077] S1.3: Based on the inspection area map data and inspection task requirements obtained in S1.1, combined with the robot parameter set in S1.2, a first inspection route covering the inspection target is generated through a route planning algorithm. The first inspection route must meet the robot's motion constraints and task time limits. The specific operation process is as follows:

[0078] Defining route costs for:

[0079] ;

[0080] in, is the total route cost of the current node n, is the actual cost from the starting point to the current node n (such as route length or energy consumption); A heuristic estimate of the cost (e.g. straight-line distance) from the current node n to the target point.

[0081] The motion constraints C include: ,in, The maximum speed allowed for the robot during inspection; is the minimum turning radius that the robot can turn safely; The maximum energy consumption allowed by the robot's current battery status; is the maximum detection range of the robot sensor.

[0082] According to the inspection area map data and the robot parameter set, the open list and the closed list are initialized. The open list contains the nodes to be evaluated and the initial state is the starting node. The closed list contains the evaluated nodes and is initially empty.

[0083] During the first inspection route generation process, the following steps are looped until the target point is found or the open list is empty:

[0084] Select the one with the minimum The node with the value is taken as the current node;

[0085] If the current node is the target node, build the route and end;

[0086] When calculating neighbor nodes, it is necessary to verify whether the route meets all motion constraints, that is, the extension of each route must meet:

[0087] , , .

[0088] For each neighbor node, do the following:

[0089] If the neighbor node is in the closed list or does not satisfy the motion constraint C, it is ignored.

[0090] Calculate the actual cost of neighbor nodes and heuristic cost estimates , and apply motion constraints to adjust these costs. For example, if the route will cause the robot to run out of power, its cost needs to be increased as follows:

[0091] ;

[0092] ;

[0093] in, is the total distance of the current route, is the weight of battery consumption, is the Euclidean distance from the current node n to the target node; The priority of turning radius in route planning.

[0094] It should be noted that if the neighbor node is not in the open list, or a better route is found, the node information is updated and added to the open list.

[0095] Furthermore, during the route planning process, the accumulated time of route generation is monitored in real time to see if it exceeds the task time limit. If so, backtrack and try other routes, or adjust the weight of the heuristic estimated cost so that the route can be completed within the time limit.

[0096] S2. Combine the automatic door priority and the first inspection route to optimize the inspection sequence and route and generate the second inspection route.

[0097] S2.1: Based on the first inspection route, identify all automatic doors on the route, obtain the location coordinates, door type (such as sliding door, revolving door, etc.) and operating parameters (such as opening angle, speed, etc.) of each automatic door; according to the urgency of the current inspection task, combined with the frequency and importance of each automatic door, the priority value of each automatic door is obtained through weighted calculation.

[0098] Specifically, the first inspection route generated in step S1 is used, and the route includes all route points of the robot in the inspection area and their sequence.

[0099] In the first inspection route, the positions of all automatic doors along the route are identified, where the automatic door information is stored in a database or data table, including the specific coordinates of each automatic door, the door type (such as a sliding door, a revolving door, etc.), and the operating parameters (such as the opening angle, speed, etc.), as follows:

[0100] ;

[0101] in, represents the position coordinates of the i-th automatic door, Indicates the type of door. are the operating parameters of the gate, is the number of automatic doors.

[0102] According to the urgency of the current inspection task, set the emergency weight factor (for example, assign different values ​​to the emergency weight factor according to the urgency), which is used to adjust the priority of the automatic door, so that the importance and frequency of use have a greater impact in the emergency task; use the weighted calculation method to comprehensively consider the frequency of use, importance and urgency of each automatic door, and calculate the priority value of each automatic door:

[0103] ;

[0104] in, is the priority value of the i-th automatic door, The usage frequency of each automatic door in the historical inspection tasks, is the weight of the usage frequency, Score the functional importance of automatic doors in inspection tasks, is the importance score weight, is the emergency weight factor.

[0105] All automatic doors are prioritized Sort from high to low to get a priority list. According to the task requirements and inspection route requirements, set different high, medium and low priority automatic doors, and select high-priority automatic doors for special attention or special treatment.

[0106] S2.2: Combine the automatic door priority data obtained in step S2.1 with the first inspection route generated in step S1.3 to optimize the inspection sequence and route, wherein the optimization objectives include:

[0107] (1) Optimize the inspection order of automatic doors so that high-priority doors can be inspected as early as possible;

[0108] (2) While meeting the door priority, the overall route is minimized to reduce the robot's movement time and energy consumption;

[0109] (3) For automatic doors with similar priorities, try to arrange the inspection of adjacent doors in sequence to avoid unnecessary round trips.

[0110] To achieve the above goals, the following optimization algorithms and strategies are used:

[0111] For each high-priority automatic door, calculate its insertion position in the current route to minimize the total route length. The insertion loss estimation formula can be used to determine the best position:

[0112] ;

[0113] in, exist and Insert automatic door between The resulting increase in routes, From route point To the automatic door The distance For automatic door To route point The distance For automatic door not inserted When, route point arrive distance; by minimizing , you can find each automatic door Insert the best location for the inspection route.

[0114] When deciding the insertion position, not only the increase in route length but also the priority of the automatic door should be considered. For high-priority doors, even if their insertion will cause a slight increase in the route, they should be given priority:

[0115] ;

[0116] in, For automatic doors The relative priority weight of Represents the route cost after inserting an automatic door. The smaller the cost, the more suitable the insertion position is. The route can satisfy the priority of the door without increasing the total route length too much.

[0117] For each high priority automatic door , calculate the time it takes to insert it into different positions of the inspection route ; Select The smallest insertion position is used to adjust the inspection route; the above process is repeated until all automatic doors are inserted and an optimized second inspection route is generated.

[0118] Optionally, for further optimization, a constraint can be added to the route adjustment process: when the priorities of two or more automatic doors are similar, adjacent doors should be arranged to be inspected in sequence as much as possible to ensure the continuity of the route and minimize unnecessary distances. This problem can be solved by dynamic programming or heuristic search (such as greedy algorithm or genetic algorithm). Through the iterative process of the above algorithm, the inspection route is gradually adjusted to finally obtain the optimized second inspection route.

[0119] It should be noted that similar priorities mean that the priority difference between the two automatic doors is less than a set threshold.

[0120] S3. According to the parameter set of the inspection robot and the type of automatic door, a personalized opening and closing strategy is formulated for each automatic door.

[0121] Preferably, a personalized opening and closing strategy is developed for each automatic door including:

[0122] (1) Calculate the optimal opening angle or distance based on the size of the robot and the type of automatic door to ensure that the robot can pass safely.

[0123] Preferably, the formula for calculating the optimal opening angle or opening distance is:

[0124] For sliding doors, the optimal opening distance Should meet:

[0125] ;

[0126] in, is the width of the robot, To provide a safety margin, prevent the robot from colliding with the door frame;

[0127] For revolving doors, the optimum opening angle Should meet:

[0128] ;

[0129] in, is the rotation radius of the revolving door.

[0130] The optimal opening distance or angle of each automatic door is calculated to ensure that the robot can pass safely.

[0131] (2) Based on the robot’s travel speed and current position, combined with the second inspection route, estimate the time it takes for the robot to reach each automatic door , determine the best opening time for each automatic door ,in, It is the time required for the door to open, ensuring that the door is open when the robot arrives.

[0132] (3) Considering the robot’s power status and the amount of remaining inspection tasks, adjust the opening speed of the automatic door to maximize energy saving while ensuring safety.

[0133] Preferably, if the battery is sufficient (such as ), then maintain the normal opening speed of the automatic door;

[0134] If the battery is low (such as ), adjust the door opening speed to reduce energy consumption:

[0135] ;

[0136] in, is the critical value of electricity, is the robot's power, It is the standard opening speed of the door.

[0137] (4) According to the robot's sensor configuration, set the duration of the automatic door opening to ensure that the robot can successfully complete the inspection task and pass.

[0138] Specifically, according to the time required for the robot to pass through the automatic door The robot position detected by the sensor sets the door opening duration :

[0139] ;

[0140] in, Provide extra time margin to cope with unexpected situations.

[0141] Furthermore, an adaptive gate control instruction set is generated to convert the personalized opening and closing strategy formulated in S3.3 into an executable instruction sequence so as to control the opening and closing of each automatic door in real time during the inspection process.

[0142] It can be seen that the present invention ensures that the opening and closing strategy of each automatic door is optimized according to the specific situation of the robot and the requirements of the inspection task. By combining the robot size, travel speed, power status and sensor configuration, the optimal opening and closing strategy is obtained, which ensures the safety and efficiency of the inspection task and optimizes energy use.

[0143] S4. Start the real-time monitoring system to analyze the operation data of the automatic door in real time and identify abnormal behavior.

[0144] Specifically, based on the second inspection route generated in step S2.2 and the adaptive gate control instruction set in step S3.4, the estimated time point when the inspection robot approaches each automatic door is determined. When the distance between the inspection robot and a specific automatic door is less than a preset distance threshold, the real-time monitoring system of the door is activated.

[0145] After the real-time monitoring system is activated, the operation data of the automatic door is collected in real time, and the actual opening and closing frequency is compared with the preset frequency. If the deviation exceeds the threshold, it is marked as a frequency abnormality; the difference between the actual opening angle or distance and the optimal parameter is calculated. If it exceeds the allowable range, it is marked as an opening amplitude abnormality; the difference between the actual opening and closing speed and the set speed is evaluated. If there is a significant deviation, it is marked as a speed abnormality.

[0146] For each abnormality type (frequency abnormality, opening amplitude abnormality and speed abnormality), set multi-level severity thresholds; according to the degree to which the abnormal parameters deviate from the normal range, the abnormal behavior is divided into three levels: mild, moderate and severe; considering the combination of multiple abnormality types, establish a comprehensive severity assessment matrix. If multiple abnormalities exist at the same time, the assessment matrix can be used to calculate the comprehensive severity.

[0147] Establish an abnormal behavior database to record all detected abnormal behaviors, including: abnormal type and occurrence time, specific parameter data related to the abnormality, severity assessment results of single abnormalities and comprehensive abnormalities, and abnormal duration and frequency.

[0148] S5. When abnormal behavior of the automatic door is detected, the alarm system is immediately triggered.

[0149] When abnormal behavior markers are detected, the alarm system is immediately activated and an alarm message containing the abnormality type and severity is sent to the inspection robot; at the same time, detailed abnormal behavior data is sent to the control center, including the abnormality type, occurrence time, related data, and specific abnormal parameters identified.

[0150] Based on the type and severity of the anomaly and combined with the second inspection route, formulate a response strategy for the inspection robot, including:

[0151] For minor abnormalities, the robot is instructed to slow down and continue the inspection task;

[0152] For moderate anomalies, the robot is instructed to pause the current task and wait for further instructions;

[0153] For serious anomalies, a detour route is calculated to instruct the robot to avoid the problematic automatic door and continue to perform the remaining inspection tasks.

[0154] Furthermore, the key information of the inspection process is recorded throughout, and the recorded data is regularly analyzed, such as generating a weekly data statistics report, including the operating status of the automatic door, the frequency and type distribution of abnormalities, etc.

[0155] With reference to Table 1, in order to verify the beneficial effects of the present invention, a scientific demonstration is then carried out through experiments.

[0156] An experiment of an intelligent inspection system was conducted in a large commercial complex to verify the effectiveness of the intelligent inspection method based on automatic door recognition. The commercial complex covers an area of ​​about 50,000 square meters and contains multiple floors and different types of automatic doors. In the experimental preparation stage, detailed map data of the complex was first collected, including information such as floor plans, obstacle distribution, and automatic door locations. At the same time, inspection task requirements were set, including key areas to be inspected, inspection cycles, and time limits.

[0157] The experiment used a new type of inspection robot with the following parameters: dimensions of 80cm×60cm×120cm (length×width×height), maximum travel speed of 1.5m / s, minimum turning radius of 0.8m, battery capacity of 10000mAh, equipped with high-precision lidar, depth camera and infrared sensor, and maximum detection range of 15m.

[0158] First, based on the collected map data and robot parameters, the improved A* algorithm is used to generate the first inspection route. The route cost function is set as f(n) = g(n) + h(n) in the algorithm, where g(n) is the actual cost from the starting point to the current node n, and h(n) is the heuristic estimated cost from the current node n to the target point. At the same time, the robot's motion constraints are taken into account.

[0159] During the route generation process, the accumulated time is monitored in real time to see if it exceeds the task time limit (set to 120 minutes). If it exceeds the time limit, the route is optimized by adjusting the weight of the heuristic estimated cost. The total length of the first inspection route generated is 2500m, and the estimated completion time is 110 minutes.

[0160] Next, the first inspection route is optimized based on the priority of the automatic doors. First, all the automatic doors on the route are identified, a total of 20, including 12 sliding doors and 8 revolving doors. The priority value of each door is calculated based on the frequency of use, importance and current task urgency of each door (the urgency weight factor is set to 1.2).

[0161] Based on the calculated priorities, the inspection routes are optimized using the insertion loss estimation formula.

[0162] After optimization, the second inspection route was obtained, with a total length increased to 2650m, but high-priority doors were scheduled earlier, with an estimated completion time of 118 minutes.

[0163] Subsequently, a personalized opening and closing strategy was developed for each automatic door based on the robot parameters and the type of automatic door. For the sliding door, the optimal opening distance was calculated, and the optimal opening distance was 80 cm. For the revolving door, the optimal opening angle was calculated, and the optimal opening angle was about 31°.

[0164] During the experiment, the real-time monitoring system was activated. When the robot approached the automatic door (the distance threshold was set to 5m), the monitoring of the door was activated. The system collected the door operation data in real time, including the opening and closing frequency, opening angle / distance, and opening and closing speed, and compared them with the preset parameters. Multi-level severity thresholds were set to divide abnormal behaviors into three levels: mild, moderate, and severe.

[0165] During the entire inspection process, the system detected multiple abnormal behaviors and triggered corresponding alarms and response strategies based on the type and severity of the abnormalities. The system recorded key information during the inspection process, including the operating status of the automatic door, the frequency of abnormalities, and the distribution of types.

[0166] The following are some statistical results of this experiment:

[0167] Table 1: Partial statistical results:

[0168]

[0169] It can be seen from the table that the number of times doors with higher priorities (such as Door_01 and Door_03) are opened is significantly higher than that of doors with lower priorities, which shows that the priority sorting method based on frequency of use, importance and task urgency in the present invention is effective and can ensure that important automatic doors are checked more frequently.

[0170] The average opening time data shows that different types of doors have different opening times. The average opening time of sliding doors (such as 4.2s for Door_01 and 3.8s for Door_03) is significantly shorter than that of revolving doors (such as 5.1s for Door_02 and 5.3s for Door_04), which reflects the effectiveness of the personalized opening and closing strategy formulated according to robot parameters and door types in the present invention, which can optimize the opening time for different types of doors and improve the passing efficiency.

[0171] The energy saving rate column shows that all doors have achieved different degrees of energy saving. High-priority doors (such as Door_01 and Door_03) have achieved 12.5% ​​and 14.2% savings, while low-priority doors (such as Door_04) have also achieved 9.5% savings. This proves that the strategy of adjusting the door opening speed based on the robot's power status in the present invention is effective and can significantly reduce energy consumption while ensuring functionality.

[0172] It can be seen that compared with traditional methods, the present invention has significant improvements in efficiency, energy consumption and anomaly detection. This intelligent inspection method based on automatic door recognition not only improves the efficiency and accuracy of inspection, but also brings practical economic benefits to users through energy consumption optimization.

[0173] An intelligent inspection method based on automatic door recognition provided by an embodiment of the present invention significantly reduces the number of round trips of the inspection robot between different areas by adjusting the inspection order, reduces the task completion time and energy consumption, and ensures priority inspection of high-priority automatic doors, thereby improving the inspection frequency and safety of key areas; by setting the automatic door opening and closing strategy, it ensures that the robot can pass through each automatic door safely and efficiently during the inspection process, thereby reducing inspection interruptions or delays caused by improper door operation; by linking the real-time monitoring system, the operation data of the automatic door is analyzed in real time, and the abnormal behavior of the automatic door can be timely identified and processed; in summary, the present invention combines automatic access control technology with an intelligent inspection system to achieve efficient and accurate inspection operations, and by setting specific automatic doors as landmarks in the inspection path, it can automatically identify the position and status of the inspection equipment, thereby dynamically adjusting the inspection strategy and improving the inspection coverage and efficiency.

[0174] Embodiment 2

[0175] Please refer to Figure 3, is a structural diagram of an intelligent inspection system based on automatic door recognition provided in Embodiment 2 of the present invention, which is suitable for executing the intelligent inspection method based on automatic door recognition provided in Embodiment 2 of the present invention. The system specifically includes the following modules:

[0176] The inspection route generation module 201 is used to generate a first inspection route according to the inspection area map data, based on the inspection task requirements and the inspection robot parameter set;

[0177] A path optimization module 202, used to optimize the inspection sequence and path by combining the automatic door priority and the first inspection route, and generate a second inspection route;

[0178] The door control strategy formulation module 203 is used to formulate an opening and closing strategy for each automatic door according to the parameter set of the inspection robot and the type of automatic door;

[0179] A real-time monitoring module 204 is used to start a real-time monitoring system, analyze the operation data of the automatic door in real time, and identify abnormal behavior;

[0180] The abnormal alarm module 205 is used to immediately trigger an alarm system when abnormal behavior of the automatic door is detected.

[0181] The above system can execute the method provided by any embodiment of the present invention, and has the corresponding functional modules and beneficial effects of the execution method.

[0182] Embodiment 3

[0183] Figure 4 A schematic diagram of the structure of a computer device provided in Embodiment 3 of the present invention. Figure 4 A block diagram of an exemplary computer device 12 suitable for use in implementing embodiments of the present invention is shown. Figure 4 The computer device 12 shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present invention.

[0184] like Figure 4 As shown, the computer device 12 is in the form of a general-purpose computing device. The components of the computer device 12 may include, but are not limited to: one or more processors or processing units 16, a system memory 28, and a bus 18 that connects various system components (including the system memory 28 and the processing unit 16).

[0185] Bus 18 represents one or more of several types of bus structures, including a memory bus or memory controller, a peripheral bus, an accelerated graphics port, a processor or a local bus using any of a variety of bus architectures. By way of example, these architectures include, but are not limited to, an Industry Standard Architecture (ISA) bus, a Micro Channel Architecture (MAC) bus, an Enhanced ISA bus, a Video Electronics Standards Association (VESA) local bus, and a Peripheral Component Interconnect (PCI) bus.

[0186] The computer device 12 typically includes a variety of computer system readable media. These media can be any available media that can be accessed by the computer device 12, including volatile and non-volatile media, removable and non-removable media.

[0187] The system memory 28 may include computer system readable media in the form of volatile memory, such as random access memory (RAM) 30 and / or cache memory 32. The computer device 12 may further include other removable / non-removable, volatile / non-volatile computer system storage media. By way of example only, the storage system 34 may be used to read and write non-removable, non-volatile magnetic media ( Figure 4 not shown, usually called a "hard drive"). Although Figure 4 Not shown in the figure, a disk drive for reading and writing to a removable non-volatile disk (e.g., a "floppy disk"), and an optical disk drive for reading and writing to a removable non-volatile optical disk (e.g., a CD-ROM, a DVD-ROM, or other optical media) may be provided. In these cases, each drive may be connected to the bus 18 via one or more data medium interfaces. The memory 28 may include at least one program product having a set (e.g., at least one) of program modules that are configured to perform the functions of the various embodiments of the present invention.

[0188] A program / utility 40 having a set (at least one) of program modules 42 may be stored, for example, in the memory 28, such program modules 42 including but not limited to an operating system, one or more application programs, other program modules, and program data, each of which or some combination may include an implementation of a network environment. The program modules 42 generally perform the functions and / or methods of the embodiments described herein.

[0189] The computer device 12 may also communicate with one or more external devices 14 (e.g., keyboards, pointing devices, displays 24, etc.), one or more devices that enable a user to interact with the computer device 12, and / or any device that enables the computer device 12 to communicate with one or more other computing devices (e.g., a network card, a modem, etc.). Such communication may be performed via an input / output (I / O) interface 22. In addition, the computer device 12 may also communicate with one or more networks (e.g., a local area network (LAN), a wide area network (WAN), and / or a public network, such as the Internet) via a network adapter 20. As shown, the network adapter 20 communicates with the other modules of the computer device 12 via a bus 18. It should be understood that although Figure 4 Not shown, other hardware and / or software modules may be used in conjunction with computer device 12, including but not limited to microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage systems.

[0190] The processing unit 16 executes various functional applications and data processing by running the programs stored in the system memory 28, such as implementing the intelligent inspection method based on automatic door recognition provided by the embodiment of the present invention.

[0191] Embodiment 4

[0192] Embodiment 4 of the present invention provides a computer-readable storage medium having computer-executable instructions stored thereon. When the instructions are executed by a processor, the intelligent inspection method based on automatic door recognition as provided in all the embodiments of the invention of this application is implemented.

[0193] Any combination of one or more computer-readable media may be used. A computer-readable medium may be a computer-readable signal medium or a computer-readable storage medium. A computer-readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device, or device, or any combination thereof. More specific examples (a non-exhaustive list) of computer-readable storage media include: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination thereof. In this document, a computer-readable storage medium may be any tangible medium containing or storing a program that may be used by or in conjunction with an instruction execution system, device, or device.

[0194] Computer-readable signal media may include data signals propagated in baseband or as part of a carrier wave, which carry computer-readable program code. Such propagated data signals may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. Computer-readable signal media may also be any computer-readable medium other than a computer-readable storage medium, which may send, propagate, or transmit a program for use by or in conjunction with an instruction execution system, apparatus, or device.

[0195] Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing.

[0196] Computer program code for performing the operations of the present invention may be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, C++, and conventional procedural programming languages ​​such as "C" or similar programming languages. The program code may be executed entirely on the user's computer, partially on the user's computer, as a separate software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., through the Internet using an Internet service provider).

[0197] Finally, it should be noted that although the above embodiments have been described in the specification and drawings of this application, this does not limit the scope of patent protection of this application. All technical solutions generated by replacing or modifying equivalent structures or equivalent processes based on the essential concept of this application using the contents recorded in the specification and drawings of this application, as well as directly or indirectly implementing the technical solutions of the above embodiments in other related technical fields, are included in the scope of patent protection of this application.

Claims

1. An intelligent inspection method based on automatic door recognition, characterized in that: The method comprises: Generate a first inspection route according to the inspection area map data, based on the inspection task requirements and the parameter set of the inspection robot; Combining the automatic door priority and the first inspection route, optimizing the inspection sequence and route, and generating a second inspection route that can reduce task completion time and energy consumption; Formulate an opening and closing strategy for each automatic door according to the parameter set of the inspection robot and the type of automatic door; Starting a real-time monitoring system to analyze the operation data of the automatic door in real time and identify abnormal behavior; When abnormal behavior of the automatic door is detected, an alarm system is immediately triggered; The step of combining the automatic door priority and the first inspection route to optimize the inspection sequence and route and generate a second inspection route that can reduce task completion time and energy consumption includes: In the first inspection route, identify the positions of all automatic doors passed by the route; According to the urgency of the current inspection task, set the emergency weight factor and adjust the priority of the automatic door; Use a weighted calculation method to comprehensively consider the frequency of use, importance, and urgency of each automatic door to calculate the priority value of each automatic door: ； in, is the priority value of the i-th automatic door, The usage frequency of each automatic door in the historical inspection tasks, is the weight of the usage frequency, Score the functional importance of automatic doors in inspection tasks, is the importance score weight, is the emergency weight factor; All automatic doors are prioritized Sort from high to low to get the automatic door priority list; According to the automatic door priority data and the first inspection route, the inspection sequence and route are optimized to generate the second inspection route; The optimization goal of optimizing the inspection sequence and route is: Optimize the inspection sequence of automatic doors; While meeting the door priority, the overall route is minimized to reduce the robot's movement time and energy consumption; For automatic doors with similar priorities, arrange for adjacent doors to be checked in sequence; The following optimization algorithms and strategies are used to achieve the optimization goals: For each high-priority automatic door, calculate the insertion position in the current route to minimize the total route length: ； in, For and Insert automatic door between The resulting increase in routes, From route point To the automatic door The distance For automatic door To route point The distance For automatic door not inserted When, route point arrive distance; When deciding the insertion position, not only the increase in route length is considered, but also the priority of the automatic door: ； in, For automatic doors The relative priority weight of Represents the route cost after inserting a certain automatic door; For each high priority automatic door , calculate the time it takes to insert it into different positions of the inspection route ; Select The smallest insertion position is used to adjust the inspection route; the above process is repeated until all automatic doors are inserted and an optimized second inspection route is generated.

2. The intelligent inspection method based on automatic door recognition according to claim 1 is characterized in that: Generating the first inspection route comprises: Define route costs and motion constraints; Initialize an open list and a closed list according to the inspection area map data and the parameter set of the inspection robot, wherein the open list contains nodes to be evaluated and the initial state is the starting node, and the closed list contains evaluated nodes and is initially empty; In the first inspection route generation process, the following steps are looped and executed until the target point is found or the open list is empty: Selecting a node with a minimum route cost value from the open list as the current node; If the current node is the target node, build the route and end; When calculating neighbor nodes, it is necessary to verify whether the route satisfies all motion constraints; For each of the neighbor nodes, perform the following operations: If the neighbor node is in the closed list or does not meet the motion constraint condition, it is ignored; The actual cost and the heuristic estimated cost of the neighbor nodes are calculated and adjusted by applying motion constraints.

3. The intelligent inspection method based on automatic door recognition according to claim 2 is characterized in that: The route costs include: ； in, is the total route cost of the current node n, is the actual cost from the starting point to the current node n, is the heuristic estimate of the cost from the current node n to the goal point.

4. The intelligent inspection method based on automatic door recognition according to claim 3 is characterized in that: If the neighbor node is not in the open list, update the node information and add it to the open list.

5. An intelligent inspection system based on automatic door recognition, based on the intelligent inspection method based on automatic door recognition as claimed in any one of claims 1 to 4, characterized in that: The system comprises: An inspection route generation module is used to generate a first inspection route according to the inspection area map data, based on the inspection task requirements and the inspection robot parameter set; A path optimization module, used to optimize the inspection sequence and path by combining the automatic door priority and the first inspection route, and generate a second inspection route that can reduce task completion time and energy consumption; The door control strategy formulation module is used to formulate an opening and closing strategy for each automatic door based on the parameter set of the inspection robot and the type of automatic door; A real-time monitoring module, used to start a real-time monitoring system, analyze the operation data of the automatic door in real time, and identify abnormal behavior; An abnormal alarm module is used to immediately trigger an alarm system when abnormal behavior of the automatic door is detected; The path optimization module is specifically used for: In the first inspection route, identify the positions of all automatic doors passed by the route; According to the urgency of the current inspection task, set the emergency weight factor and adjust the priority of the automatic door; Use a weighted calculation method to comprehensively consider the frequency of use, importance, and urgency of each automatic door to calculate the priority value of each automatic door: ； in, is the priority value of the i-th automatic door, The usage frequency of each automatic door in the historical inspection tasks, is the weight of the usage frequency, Score the functional importance of automatic doors in inspection tasks, is the importance score weight, is the emergency weight factor; All automatic doors are prioritized Sort from high to low to get the automatic door priority list; According to the automatic door priority data and the first inspection route, the inspection sequence and route are optimized to generate the second inspection route; The optimization goal of optimizing the inspection sequence and route is: Optimize the inspection sequence of automatic doors; While meeting the door priority, the overall route is minimized to reduce the robot's movement time and energy consumption; For automatic doors with similar priorities, arrange for adjacent doors to be checked in sequence; The following optimization algorithms and strategies are used to achieve the optimization goals: For each high-priority automatic door, calculate the insertion position in the current route to minimize the total route length: ； in, For and Insert automatic door between The resulting increase in routes, From route point To the automatic door The distance For automatic door To route point The distance For automatic door not inserted When, route point arrive distance; When deciding the insertion position, not only the increase in route length is considered, but also the priority of the automatic door: ； in, For automatic doors The relative priority weight of Represents the route cost after inserting a certain automatic door; For each high priority automatic door , calculate the time it takes to insert it into different positions of the inspection route ; Select The smallest insertion position is used to adjust the inspection route; the above process is repeated until all automatic doors are inserted and an optimized second inspection route is generated.

6. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that: When the processor executes the computer program, an intelligent inspection method based on automatic door recognition as described in any one of claims 1 to 4 is implemented.

7. A computer-readable storage medium having computer-executable instructions stored thereon, characterized in that: The computer executable instructions are executed by a computer processor to implement the intelligent inspection method based on automatic door recognition as described in any one of claims 1 to 4.

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