Patrol inspection system and patrol inspection method

Abstract

To provide a patrol inspection system and patrol inspection method making it possible to reduce a risk that a robot may fail during patrol.SOLUTION: A patrol inspection system 1 that inspects a patrol route 50 including a difficult movement place includes a robot 200 that moves along the patrol route 50 so as to perform inspection, and a controller 120 that controls the robot 200. When the robot 200 inspects the difficult movement place, if the controller 120 determines that a difficult movement place situation, which is a situation of the difficult movement place, is dangerous, the controller 120 causes the robot 200 to avoid inspection of the patrol route 50.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] The present disclosure relates to a patrol inspection system and a patrol inspection method that perform patrol inspections using a robot that moves along a patrol route. [Background technology]

[0002] There is a demand for automation in maintenance and inspection work at plants and the like. Accordingly, attempts have been made to have autonomously mobile robots perform tasks such as inspecting plant equipment instead of workers. For example, Patent Document 1 discloses a robot control device that schedules start times for each patrol route, allowing multiple robots to automatically start patrol inspection work at registered times. Furthermore, as an example of an autonomously mobile robot, Patent Document 2 discloses a robot that has locomotion means such as legs and is capable of ascending and descending stairs. Patent Document 3 discloses a leg-wheel type mobile robot. Patent Document 4 discloses a four-legged robot. In addition, multi-legged robots such as spider legs are also known. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Application Laid-Open No. 2005-324278 [Patent Document 2] International Publication No. 2005 / 087452 [Patent Document 3] Japanese Patent Application Laid-Open No. 2003-205480 [Patent Document 4] Special Publication No. 2020-501918 Summary of the Invention [Problem to be solved by the invention]

[0004] By using legged robots such as those disclosed in Patent Documents 2 to 4 to perform the patrol inspection work disclosed in Patent Document 1, it is possible to perform patrol inspection work on multiple floors with a single robot. However, these are technologies that automatically perform patrol inspection work at registered times along registered indoor patrol routes. When these technologies are applied to patrol inspection work on routes that include difficult-to-travel locations, such as outdoors, there is a risk that the robot will break down due to falling or slipping during patrol inspection work in bad weather such as rain or strong winds.

[0005] In order to solve the above-mentioned problems, the present disclosure aims to provide a patrol inspection system and a patrol inspection method that can reduce the risk of a robot breaking down during patrol. [Means for solving the problem]

[0006] According to one embodiment of the present disclosure, (1) a patrol inspection system inspects a patrol route that includes a difficult-to-travel location. The patrol inspection system includes a robot that moves along the patrol route to perform the inspection, and a control device that controls the robot. When the control device determines that the difficult-to-travel location is in a dangerous state when the robot inspects the difficult-to-travel location, the control device causes the robot to avoid inspecting the patrol route.

[0007] (2) In the patrol inspection system described in (1) above, the control device may determine whether the difficult-to-travel location situation is dangerous based on at least one of advance information about the difficult-to-travel location or measurement data about the difficult-to-travel location situation.

[0008] (3) In the patrol inspection system described in (2) above, the control device may perform a preliminary assessment of the difficult-to-travel location situation based on the preliminary information before the robot starts inspecting the patrol route, and if the preliminary assessment determines that the difficult-to-travel location situation is not dangerous, cause the robot to start inspecting the patrol route, and while the robot is inspecting along the patrol route, may perform a re-assessment of the difficult-to-travel location situation based on the measurement data.

[0009] (4) In the patrol inspection system described in (2) or (3), the difficult-to-travel location may be an outdoor portion of the patrol route, and the advance information may include at least one of a weather forecast for the outdoor portion and past weather observation data.

[0010] (5) In the patrol inspection system described in (4) above, the measurement data may include at least one of an index representing the slipperiness of the outdoor portion or a wind speed in the outdoor portion.

[0011] (6) In the patrol inspection system described in (5) above, the robot may be equipped with an anemometer that measures wind speed in the outdoor area.

[0012] (7) In the patrol inspection system described in (6) above, the anemometer may be an ultrasonic anemometer.

[0013] (8) In the patrol inspection system described in any one of (1) to (7) above, the control device may determine whether the difficult-to-travel location is a dangerous location, such as at least one of a step section or a slope section located outdoors on the patrol route.

[0014] According to one embodiment of the present disclosure, a patrol inspection method (9) is a method for inspecting a patrol route including a difficult-to-travel location. The patrol inspection method includes a patrol step in which a control device moves a robot along the patrol route, and an inspection step in which the robot inspects the patrol route. In the patrol step, if the control device determines that the difficult-to-travel location situation is dangerous when the robot inspects the difficult-to-travel location, the control device causes the robot to avoid inspecting the patrol route. [Effects of the Invention]

[0015] According to the patrol inspection system and patrol inspection method disclosed herein, the risk of the robot breaking down during patrol is reduced by avoiding inspection of the patrol route when the situation is dangerous when the robot inspects difficult-to-reach locations, such as outdoors. [Brief explanation of the drawings]

[0016] [Figure 1] 1 is a block diagram illustrating a configuration example of a patrol inspection system according to the present disclosure. [Figure 2] FIG. 10 is a diagram showing an example of a tour route. [Figure 3] 1 is a flowchart illustrating an example of a procedure for a patrol inspection method according to the present disclosure. [Figure 4] 10 is a graph showing an example of the relationship between the slipperiness of a patrol route and whether or not a slip occurs. DETAILED DESCRIPTION OF THE INVENTION

[0017] Hereinafter, embodiments of a patrol inspection system and a patrol inspection method according to the present disclosure will be described with reference to the drawings. The drawings are schematic and may differ from the actual product. Furthermore, the following embodiments exemplify devices or methods for embodying the technical ideas of the present disclosure, and are not intended to limit the configuration to those described below. In other words, the technical ideas of the present disclosure can be modified in various ways within the technical scope described in the claims.

[0018] (Configuration example of Patrol Inspection System 1) As shown in FIG. 1 , a patrol inspection system 1 according to an embodiment of the present disclosure includes a robot 200. The patrol inspection system 1 moves the robot 200 along a patrol route registered in advance within an inspection target such as a plant, and inspects the patrol route using the robot 200. Here, the patrol route is not necessarily limited to a route that visits multiple inspection locations, but also includes a route that moves only to one desired inspection location. A patrol inspection method according to the present disclosure includes a patrol step of moving the robot 200 along the patrol route, and an inspection step of inspecting the patrol route using the robot 200.

[0019] The robot 200 includes a control device 120. The control device 120 controls the robot 200 so that the robot 200 moves along a patrol route and performs inspection. That is, the control device 120 executes the patrol inspection method according to the present disclosure. The control device 120 may be an edge computing system.

[0020] The patrol inspection system 1 further includes an OT layer control device 110. The OT layer control device 110 is a computer or the like used in a plant that is the target of inspection by the patrol inspection system 1. When the patrol inspection system 1 includes the OT layer control device 110, in another embodiment, the OT layer control device 110 may execute the patrol inspection method according to the present disclosure. In this case, the control device 120 of the robot 200 may control the robot 200 based on instructions from the OT layer control device 110. The patrol inspection system 1 does not need to include the OT layer control device 110.

[0021] The robot 200 and the OT layer control device 110 are communicatively connected via a network 112 within the plant. The robot 200 is communicatively connected to the network 112 wirelessly. The OT layer control device 110 is communicatively connected to the network 112 via a hub 111 via a wired or wireless connection. The patrol inspection system 1 further includes a charging station 210. The charging station 210 is connected to the robot 200 via a wired or wireless connection so as to charge the battery of the robot 200 when the robot 200 is driven by battery power. The charging station 210 is communicatively connected to the network 112 via the hub 111 via a wired or wireless connection. The robot 200 may be communicatively connected to the OT layer control device 110 via the charging station 210 while the battery is being charged by the charging station 210.

[0022] The network 112 is configured to enable communication throughout the entire plant or a portion of the plant that is served by a circular route. The network 112 may be configured to enable communication using various methods, such as 4th Generation (4G), Long Term Evolution (LTE), local 5th Generation (5G), mesh WiFi, or millimeter waves.

[0023] The patrol inspection system 1 further includes an IT layer control device 100 and an IT layer terminal device 102. The IT layer control device 100 is a computer or the like used in an operation center that operates the plant. The IT layer terminal device 102 is a computer or the like that runs a browser for checking the status of the plant at the operation center. When the patrol inspection system 1 includes the IT layer control device 100, in another embodiment, the IT layer control device 100 may execute the patrol inspection method according to the present disclosure. In this case, the control device 120 of the robot 200 may control the robot 200 based on instructions from the IT layer control device 100. The patrol inspection system 1 does not necessarily include the IT layer control device 100 and the IT layer terminal device 102.

[0024] The IT layer control device 100 and the IT layer terminal device 102 are communicably connected to a network 112 within the plant via a firewall 113. The network 112 within the plant is communicably connected to an external network 101 such as the Internet via the firewall 113. The firewall 113 is a general term for a configuration that executes security measures to protect the network 112 within the plant, the IT layer control device 100, and the IT layer terminal device 102 from the external network 101.

[0025] The following describes an example configuration of the robot 200. As described above, the robot 200 includes the control device 120. The robot 200 further includes an anemometer 201, a driving device 202, a movement amount measuring device 203, and an inspection device 204.

[0026] The control device 120 acquires information or data from each component of the robot 200 and controls the driving device 202 of the robot 200 to move the robot 200 along the patrol route. The control device 120 also acquires inspection results of the patrol route performed by the inspection device 204 and outputs them to the OT layer control device 110 or the IT layer control device 100. The control device 120 may be configured to store the inspection results in the robot 200 rather than automatically output them. In this case, the control device 120 may be configured to manually retrieve the inspection results stored in the robot 200, for example. The control device 120 may be configured to include at least one processor such as a CPU (Central Processing Unit) or a GPU (Graphics Processing Unit). The control device 120 may be configured with one or more processors. The processor constituting the control device 120 may control the robot 200 by reading and executing a program stored in a storage unit (described later).

[0027] The control device 120 may include a storage unit. The storage unit stores various types of information, data, and the like. The storage unit may store, for example, a program executed by the control device 120, or data used in a process executed by the control device 120, or processing results, inspection results, and the like. The storage unit may also function as a work memory for the control device 120. The storage unit may be configured to include, for example, a semiconductor memory, etc., but is not limited to this. For example, the storage unit may be configured as an internal memory of a processor used as the control device 120, or as a hard disk drive (HDD) accessible from the control device 120. The storage unit may be configured as a non-transitory readable medium. The storage unit may be configured integrally with the control device 120, or may be configured separately from the control device 120.

[0028] The control device 120 may include a communication interface for communicating with other devices via a wired or wireless connection. The communication interface may be configured to be able to communicate with the OT layer control device 110, etc., via the network 112 within the plant. The communication interface may include an input / output port for inputting and outputting data to and from other devices. The control device 120 may transmit and receive necessary data or signals to and from the OT layer control device 110 or the IT layer control device 100, etc., via the communication interface.

[0029] The communication interface may be configured to enable communication based on a wired or wireless communication standard. Wired communication standards may include USB (Universal Serial Bus), RS-232C, RS-485, etc. Wireless communication standards may include IEEE802.11, Bluetooth (registered trademark), etc., and may also include cellular phone communication standards such as 3G, 4G, or 5G. The communication interface may support one or more of these communication standards. The communication interface is not limited to these examples and may communicate with other devices or input and output data based on various communication standards. The communication interface may be configured integrally with the control device 120 or may be configured separately from the control device 120.

[0030] The control device 120 may include an output device. The output device may include a display device that displays the status of the robot 200, the progress of the inspection, or the inspection results. The display device may include, for example, an LCD (Liquid Crystal Display), an organic EL (Electro-Luminescence) display or an inorganic EL display, or a PDP (Plasma Display Panel). The display device is not limited to these displays and may include various other types of displays. The output device may include a light-emitting device such as a lamp. The output device may include an audio output device such as a speaker. The output device is not limited to these examples and may include various other types of devices.

[0031] The drive unit 202 moves the robot 200 by driving wheels, crawlers, legs, or the like of the robot 200. The drive unit 202 may include wheels, crawlers, legs, or the like. The drive unit 202 may include power, such as an engine or a motor, for driving the wheels, crawlers, legs, or the like. The robot 200 may be configured in various ways as long as it can move autonomously along a patrol route. If the patrol route includes steps, the robot 200 may be equipped with crawlers or legs as the drive unit 202 so that it can move over the steps.

[0032] The movement amount measurement device 203 may include an encoder if the robot 200 moves using wheels or crawlers. The encoder may measure the angle or number of rotations of the wheels or the distance traveled by the crawlers caused by the drive device 202. The movement amount measurement device 203 may include a step counter if the robot 200 moves using legs. The movement amount measurement device 203 may include a camera or the like that reads an identifier installed at any point on the patrol route. The identifier is configured to identify the point where the identifier is installed by coordinates, name, or the like. By reading the identifier, the movement amount measurement device 203 can measure to which point on the patrol route the robot has moved. The control device 120 may control the drive device 202 based on measurement data from the movement amount measurement device 203. The movement amount measurement device 203 may be included in the drive device 202.

[0033] Furthermore, the movement amount measurement device 203 may be configured to use a technique called SLAM (Simultaneous Localization and Mapping) to calculate the movement amount from an output obtained based on the position identification that is the result of the robot 200 simultaneously estimating its own position and creating an environmental map around the robot. In this case, the movement amount measurement device 203 may include sensors necessary for SLAM. Furthermore, the movement amount measurement device 203 may be configured to calculate the movement amount based on data output from a satellite positioning system or a system configured with various positioning technologies.

[0034] The inspection device 204 inspects the patrol route along which the robot 200 moves. The inspection device 204 may include a robotic arm, a sensor, a camera, or the like. The robotic arm may be configured to open and close control panels located on the patrol route, or operate switches or valves, etc. The sensor may include a gas sensor that measures gas concentrations along the patrol route, or a thermal camera or temperature sensor that measures the temperature of an inspection target located on the patrol route. The camera may be configured to photograph or read the indicated or displayed values ​​of meters located on the patrol route. The camera may be configured to photograph or check for damage, such as cracks or peeling, of equipment, facilities, or devices located on the patrol route. The inspection device 204 is not limited to the above examples and may include various devices or equipment.

[0035] The anemometer 201 is mounted on the robot 200, measures the wind speed at the robot 200's position, and outputs the measurement result to the control device 120. The wind speed is determined by the wind direction and wind strength (speed). The anemometer 201 may be a cup anemometer, a windmill anemometer, a hot wire anemometer, an ultrasonic anemometer, or the like. Here, a cup anemometer or a windmill anemometer has a cup or a windmill that continues to rotate by inertia and is therefore difficult to follow changes in wind strength. A hot wire anemometer is difficult to follow large changes in wind speed. Therefore, in the patrol inspection method according to the present disclosure, in order to estimate the local risk of slipping on steps or slopes included in the patrol route, an ultrasonic anemometer that can grasp the wind direction and speed in three dimensions and has high followability to large changes in wind direction and speed is suitable as the anemometer 201.

[0036] The control device 120 may control the driving device 202 based on the measurement data of the anemometer 201. The robot 200 may not be equipped with the anemometer 201. If the robot 200 is not equipped with the anemometer 201, the control device 120 may acquire measurement data of the wind speed on the patrol route from an anemometer installed on the patrol route, and control the driving device 202 based on the acquired measurement data.

[0037] (Example of a tour route configuration) Referring to FIG. 2 , an example configuration of a patrol route 50 of a plant 10 to be inspected by a patrol inspection system 1 according to the present disclosure will be described. The patrol route 50 is set as a route along which a robot 200 patrols and inspects the plant 10. The plant 10 includes an indoor section 11 and an outdoor section 12. The patrol route 50 includes an indoor route passing through the indoor section 11 and an outdoor route passing through the outdoor section 12. The outdoor section 12 is an example of a difficult-to-travel location in the present disclosure, and corresponds to a section affected by weather such as rain or wind. The difficult-to-travel location is a section where there is a high risk of the robot 200 falling or slipping while moving. The outdoor section 12 includes a section where rain or wind may enter from the side or diagonally, even if there is a roof directly above it. The patrol route to be inspected by a patrol inspection system 1 according to the present disclosure may be composed only of an outdoor section, excluding an indoor section.

[0038] The patrol route 50 includes point S, which is the starting point of the robot 200, point A, which is the starting point of the outdoor route, and point B, which is a point a predetermined distance away from the starting point of the outdoor route. Point S is located in the indoor section 11. Points A and B are located in the outdoor section 12. The route from point A to point B is assumed to be a route with a low risk of the robot 200 experiencing an incident such as a fall or slip. The route from point A to point B may be, for example, a flat route.

[0039] The circular route 50 includes step portions 51 and 52 located beyond point B when viewed from point S, which is the starting point. Step portion 51 or 52 may include stairs. The circular route 50 includes point L1 located before step portion 51 when viewed from point S. The circular route 50 includes point L2 located before step portion 52 when viewed from point S.

[0040] The patrol route 50 may include an identifier that can be read by the movement amount measuring device 203 of the robot 200 so that the robot 200 itself can confirm that it has moved to points A and B. An identifier placed at point A identifies point A. An identifier placed at point B identifies point B. In other words, by reading an identifier, the robot 200 can recognize that it has moved to the point identified by that identifier. The identifier may be configured as, for example, a two-dimensional code. The identifier is not limited to a two-dimensional code and may be configured in various other ways.

[0041] The patrol route 50 may include a sensor that detects that the robot 200 has moved to points A and B. The sensor may output a detection result that the robot 200 has moved to points A and B to the control device 120 of the robot 200. The sensor may be a proximity sensor or the like. The sensor may be a camera that photographs points A and B to detect the robot 200. The sensor may be installed near points A and B, or may be installed at a location away from points A and B. The sensor is not limited to points A and B, and may be installed so as to detect that the robot 200 has moved to any other point on the patrol route 50.

[0042] An anemometer may be installed on an outdoor route that passes through the outdoor portion 12 of the patrol route 50. The anemometer installed on the outdoor route outputs wind speed measurement data to the control device 120 of the robot 200. The anemometer installed on the outdoor route may be an ultrasonic anemometer, similar to the anemometer 201 mounted on the robot 200.

[0043] The route to be patrolled and inspected by the patrol inspection system 1 according to the present disclosure is not limited to the patrol route 50 exemplified in Fig. 2, and may be any other route. The patrol inspection system 1 may inspect routes that include slopes in addition to flat routes or steps.

[0044] (Example of operation of Patrol Inspection System 1) In the patrol inspection system 1 according to an embodiment of the present disclosure, the control device 120 may execute a patrol inspection method including the steps of the flowchart illustrated in Fig. 3 so that the robot 200 moves along a patrol route and performs inspections. The patrol inspection method may be realized as a patrol inspection program executed by a processor included in the control device 120. The patrol inspection program may be stored in a non-transitory computer-readable medium such as a USB memory, a hard disk, or an SSD.

[0045] The control device 120 determines whether the patrol route includes outdoors, i.e., whether it includes an outdoor route (step S1). If the patrol route does not include outdoors (step S1: NO), i.e., if the patrol route includes only indoors, the control device 120 causes the robot 200 to patrol an indoor route (step S2). After executing the patrol procedure for the indoor route in step S2, the control device 120 ends the execution of the flowchart in FIG. 3.

[0046] If the patrol route includes outdoors (step S1: YES), the control device 120 determines whether the outdoor situation is dangerous based on prior information about the outdoor situation (step S3). If the patrol route includes a difficult-to-travel location, the control device 120 determines whether the difficult-to-travel location situation is dangerous based on prior information about the difficult-to-travel location situation. A determination made based on prior information about the difficult-to-travel location situation or the outdoor situation before the robot 200 starts inspecting the patrol route is also referred to as a prior determination. The outdoor situation includes whether there is a high risk of the robot 200 experiencing an event such as a fall or slip when moving outdoors. The difficult-to-travel location situation includes whether there is a high risk of the robot 200 experiencing an event such as a fall or slip when moving through a difficult-to-travel location. The prior information about the outdoor situation may include a forecast of outdoor weather. The weather forecast may include a forecast of rainfall, including snowfall or hail. The weather forecast may include a forecast of wind speed, including wind direction or strength. The prior information may include past weather observation data. The past weather observation data may include time-series data of rainfall or accumulated rainfall. The past weather observation data may include time-series data of wind speed. The control device 120 may acquire the prior information from an external source via the network 101. In the following description, a determination of whether an outdoor situation is dangerous may be replaced with a determination of whether a difficult-to-travel location situation is dangerous.

[0047] The control device 120 may determine that the outdoor situation is dangerous when the probability of an event such as a fall or a slip of the robot 200 occurring is equal to or greater than a determination threshold. The determination threshold may be set to a value such as 1%, for example. The determination threshold may be set based on the magnitude of the cost incurred when an event such as a fall or a slip of the robot 200 occurs. The cost may include the cost required for an operator or other device to intervene with the robot 200 when the robot 200 breaks down due to an event such as a fall or a slip of the robot 200. The cost may include the cost required for an operator or other device to intervene with the robot 200 when the robot 200 is unable to continue patrol due to an event such as a fall or a slip of the robot 200. The intervention with the robot 200 may include, for example, work such as repairing or recovering the robot 200.

[0048] If the control device 120 determines that the outdoor situation is dangerous (step S3: YES), the process proceeds to step S7. If the control device 120 determines that the outdoor situation is not dangerous (step S3: NO), the control device 120 causes the robot 200 to start an inspection along a patrol route that includes the outdoors (step S4). While patrolling the outdoors, the robot 200 measures its own movement amount using the movement amount measuring device 203. Also, while patrolling the outdoors, the robot 200 measures the wind speed at its own position using the anemometer 201.

[0049] The control device 120 determines whether the outdoor situation is dangerous based on the slipperiness of the patrol route (step S5). The slipperiness of the patrol route is an index that represents how slippery the robot 200 is when moving along the patrol route. The control device 120 may estimate the slipperiness of the patrol route based on measurement data obtained by the movement amount measurement device 203 while the robot 200 is moving along the flat route from point A to point B in FIG. 2, and determine whether the outdoor situation is dangerous.

[0050] When the robot 200 walks using its legs, the control device 120 may acquire, as the measured number of steps, the number of steps required for the robot 200 to move from point A to point B on the patrol route 50 of FIG. 2 from the movement distance measurement device 203. The control device 120 may acquire in advance, as the reference number of steps, the number of steps required for the robot 200 to move safely along the section from point A to point B on the patrol route 50 of FIG. 2 without the robot 200 experiencing an event such as a fall or a slip, etc. When the robot 200 walks along a slippery route, the number of steps required tends to increase. The control device 120 may calculate the rate of increase in the measured number of steps relative to the reference number of steps as an index representing the slipperiness of the patrol route 50. When the rate of increase in the measured number of steps is equal to or greater than a step threshold, the control device 120 may determine that there is an increased possibility that the robot 200 will experience an event such as a fall or a slip. In other words, the control device 120 may determine that the outdoor conditions along the patrol route 50 along which the robot 200 is traveling are dangerous. The step count threshold is set appropriately as will be explained in the examples below.

[0051] When the robot 200 travels using wheels or crawlers, the control device 120 may acquire, as the measured number of rotations, the number of rotations required for the robot 200 to travel from point A to point B on the patrol route 50 in FIG. 2 from the movement distance measurement device 203. The control device 120 may acquire in advance, as the reference number of rotations, the number of rotations required for the robot 200 to travel safely along the section from point A to point B on the patrol route 50 in FIG. 2 without the robot 200 experiencing an event such as a fall or a slip, or the like. When the robot 200 travels along a slippery route, the required number of rotations tends to increase. The control device 120 may calculate the rate of increase in the measured number of rotations relative to the reference number of rotations as an index representing the slipperiness of the patrol route 50. When the rate of increase in the measured number of rotations is equal to or greater than a rotation number threshold, the control device 120 may determine that there is an increased possibility that the robot 200 will experience an event such as a fall or a slip. In other words, the control device 120 may determine that the outdoor conditions along the patrol route 50 along which the robot 200 is traveling are dangerous. The rotation speed threshold is set as appropriate as will be explained in the embodiments below. The control device 120 may calculate the reference rotation speed using the rotation speed commanded to a power source such as a motor when driving the wheels or crawlers. If there are multiple motors that drive the wheels or crawlers, the control device 120 may calculate the reference rotation speed based on the rotation speed commanded to each motor.

[0052] When the robot 200 ascends or descends a step, if there is a risk of the robot 200 slipping off the step during the ascending or descending operation, i.e., if there is a risk of the robot 200 failing the ascending or descending operation, the robot 200 may stop the ascending or descending operation and return to its original position. In other words, the robot 200 may redo its ascent or descent of the step. The movement amount measurement device 203 or the control device 120 may count the number of times the robot 200 redoes its ascent or descent of the step. The more times the robot 200 redoes its ascent or descent of the step, the more likely it is that the robot 200 will be slippery on that step. Therefore, the number of times the robot 200 redoes its ascent or descent of the step may be used as an index representing the slipperiness of the step on which the robot 200 redoes its ascent or descent, or as an index representing the slipperiness of the patrol route that includes that step. The control device 120 may determine whether to cause the robot 200 to enter the next step 52 based on, for example, the number of times the robot 200 tries to ascend or descend the step 51 of the patrol route 50 in FIG.

[0053] If the control device 120 determines that the outdoor conditions are dangerous based on the slipperiness of the patrol route (step S5: YES), the control device 120 proceeds to step S7. If the control device 120 determines that the outdoor conditions are not dangerous based on the slipperiness of the patrol route (step S5: NO), the control device 120 determines whether the outdoor conditions are dangerous based on the wind speed along the patrol route (step S6). The control device 120 may acquire wind speed measurement data at the current position of the robot 200 from the anemometer 201 of the robot 200. The control device 120 may acquire wind speed measurement data at the current position of the robot 200 or in its vicinity from an anemometer installed along the patrol route. If the wind speed is equal to or greater than a wind speed threshold, the control device 120 may determine that there is an increased possibility that the robot 200 will fall or slip. In other words, the control device 120 may determine that the outdoor conditions along the patrol route 50 along which the robot 200 is traveling are dangerous. The wind speed threshold is set as appropriate, as will be described in the following examples.

[0054] If the control device 120 determines that the outdoor situation is dangerous based on the wind speed on the patrol route (step S6: YES), the process proceeds to step S7. If the control device 120 determines that the outdoor situation is dangerous based on various conditions (step S3, S5, or S6: YES), the control device 120 causes the robot 200 to avoid patrolling outdoors (step S7).

[0055] If the control device 120 determines that outdoor conditions are dangerous when the robot 200 has not yet begun patrolling outdoors, the control device 120 may cause the robot 200 to avoid patrolling outdoors by having the robot 200 patrol only indoors.

[0056] If the control device 120 determines that outdoor conditions are dangerous while the robot 200 is moving along an outdoor route, the control device 120 may cause the robot 200 to avoid patrolling the outdoors by having it remain at its current location until the outdoor conditions are no longer dangerous. If the robot 200 remains at its current location, it may assume a stable posture. The control device 120 may cause the robot 200 to avoid patrolling the outdoors by returning indoors. The control device 120 may also cause the robot 200 to avoid patrolling portions of the outdoor route where conditions are dangerous by having the robot 200 move only on flat routes, avoiding routes that include steps or slopes.

[0057] On the patrol route, an available escape location may be set in advance when the outdoor conditions are dangerous. When the outdoor conditions are determined to be dangerous based on, for example, slipperiness or wind speed, a location where it is expected that these factors can be reduced may be set in advance as the escape location. When, for example, rain or wind is expected as a factor, setting the escape location may include selecting a location with a cover or enclosure to protect against rain or wind. When the control device 120 determines that the outdoor conditions are dangerous while the robot 200 is moving along an outdoor route, the control device 120 may move the robot 200 to the nearest escape location to avoid patrolling outdoors.

[0058] An avoidance route may be set in advance for the patrol route, which can be used when the outdoor situation is dangerous. If the control device 120 determines that the outdoor situation is dangerous while the robot 200 is moving along the outdoor route, the control device 120 may move the robot 200 along the avoidance route to avoid patrolling outdoors.

[0059] As described above, avoiding outdoor patrol in the patrol inspection system 1 according to the present disclosure may include various modes. Avoiding outdoor patrol before the robot 200 starts outdoor patrol may include not having the robot 200 start outdoor patrol. Not having the robot 200 start outdoor patrol may include not having the robot 200 start patrol at all, starting patrol but patrolling only the indoor portion of a patrol route that includes outdoors, or switching to patrol of another patrol route that is composed only of indoor routes, etc. Avoiding outdoor patrol while the robot 200 is patrolling outdoors may include having the robot 200 stay at its current position, having the robot 200 return indoors, moving the robot 200 to an avoidance location, or moving the robot 200 to a route that avoids steps or slopes, etc.

[0060] The control device 120 may notify the worker by an output device that the robot 200 has been prevented from patrolling outdoors. The control device 120 may notify the worker that the robot 200 has been prevented from patrolling outdoors by outputting the information to the OT layer control device 110, the IT layer control device 100, or the IT layer terminal device 102.

[0061] In the patrol inspection system 1, the control device 120, the OT layer control device 110, the IT layer control device 100, or the IT layer terminal device 102 may be configured to receive instructions from a worker to operate the robot 200. When an instruction for an alternative route for the robot 200 to patrol is input from the worker, the control device 120 may move the robot 200 along the alternative route to continue the patrol.

[0062] 3 after executing the avoidance procedure in step S7. If the robot 200 is stopped midway along the outdoor route when executing the avoidance procedure in step S7, the control device 120 may repeatedly determine whether the outdoor situation is dangerous, and when it determines that the outdoor situation is no longer dangerous, may cause the robot 200 to resume outdoor patrol. The control device 120 may cause the robot 200 to remain at its current position until the robot 200 is retrieved by a worker, a device, or the like.

[0063] If the control device 120 determines that the outdoor conditions are not dangerous based on the wind speed along the patrol route (step S6: NO), that is, if it determines that the outdoor conditions are not dangerous based on various conditions, it causes the robot 200 to continue patrolling the outdoors and determines whether the outdoor patrol has ended (step S8). If the outdoor patrol has not ended (step S8: NO), the control device 120 returns to the procedure of step S5 or S6 and repeats the procedure of determining whether the outdoor conditions are dangerous based on slipperiness or wind speed. If the outdoor patrol has ended (step S8: YES), the control device 120 ends execution of the flowchart of FIG. 3.

[0064] In other words, the patrol inspection method described above may include the steps of: the control device 120 performing a preliminary determination of outdoor conditions based on preliminary information; causing the robot 200 to start inspecting the patrol route if the control device 120 determines in the preliminary determination that the outdoor conditions are not dangerous; and re-determining whether the outdoor conditions are dangerous based on measurement data while the robot 200 is inspecting the patrol route. The preliminary information may include at least one of a forecast of outdoor weather or past weather observation data. The measurement data may include at least one of an index representing slipperiness or wind speed.

[0065] (summary) As described above, according to the patrol inspection system 1 and the patrol inspection method of the present disclosure, before the robot 200 starts patrolling outdoors, that is, in advance, it is determined whether the outdoor situation is dangerous based on advance information including weather information. By determining the outdoor situation in advance, it is possible to prevent the robot 200 from patrolling outdoors in dangerous outdoor conditions.

[0066] Furthermore, whether the outdoor conditions are dangerous is determined based on measurement data of the slipperiness or wind speed of the patrol route obtained while the robot 200 moves and inspects the outdoor portion of the patrol route. If the outdoor conditions during the robot 200's patrol are determined to be dangerous, the robot 200 avoids patrolling the outdoor area during the patrol. For example, even if the weather information does not include rainfall information, localized rainfall may cause localized slipperiness, i.e., increased slipperiness. Furthermore, even if the weather information does not include strong wind information, localized high wind speeds in the upper floors of a semi-outdoor plant, for example, may locally increase the likelihood of incidents such as falls or slips. By determining whether the outdoor conditions are dangerous based on measurement data during the outdoor patrol, it is automatically determined whether to continue the patrol or whether to patrol steps or slopes included in the patrol route.

[0067] By having the robot 200 avoid outdoor patrol when outdoor conditions are dangerous, whether before or during patrol, the possibility of an incident occurring in the robot 200, such as a fall or slip, is reduced. By reducing the possibility of an incident occurring in the robot 200, such as a fall or slip, the frequency at which intervention is required for the robot 200 is reduced. As a result, labor savings or efficiency improvements are realized in outdoor patrol inspection work using the robot 200.

[0068] In the above-described embodiment, the control device 120 makes a decision based on both prior information and measurement data during patrol. In another embodiment, the control device 120 may determine whether to cause the robot 200 to avoid patrolling outdoors by making a decision based on either prior information or measurement data during patrol.

[0069] (Example) An example will now be described.

[0070] <Judgment based on slipperiness> The control device 120 may calculate an index representing the slipperiness of the patrol route and determine whether the outdoor situation is dangerous based on the index representing the slipperiness. If the robot 200 is a legged robot, the control device 120 may calculate the index representing the slipperiness of the patrol route based on the number of steps required for the robot 200 to move, as described above. In this case, the index representing the slipperiness may be calculated based on the reference number of steps and the measured number of steps.

[0071] In a preliminary experiment, a reference number of steps may be measured. The reference number of steps is the number of steps required for the robot 200 to move safely, i.e., without any incidents such as a fall or a slip. In this embodiment, a preliminary experiment was conducted in which the robot 200 was moved between points A and B after it was confirmed that the route from point A to point B on the patrol route 50 in FIG. 2 was safe. Then, the number of steps taken by the robot 200 when it moved between points A and B in the preliminary experiment was measured as the reference number of steps. The preliminary experiment was conducted in a manner in which the robot 200 was instructed to move between points A and B. The instruction was performed by controlling the robot 200 from the OT layer control device 110. In the preliminary experiment, the number of steps taken by the robot 200 when it moved between points A and B, i.e., the reference number of steps, was 150.

[0072] Next, the number of steps taken by the robot 200 when it autonomously moved between A and B in various actual situations, i.e., the number of measured steps, was measured. In each trial, after moving between A and B, the robot 200 was made to ascend and descend the step sections 51 and 52, and it was confirmed whether the robot 200 slipped down the step sections 51 and 52. In this example, the number of trials for measuring the number of measured steps was nine.

[0073] Then, where the reference number of steps is Y and the measured number of steps is X, an index a representing the slipperiness of the patrol route 50 was calculated using the formula (X / Y)-1. Table 1 below shows data that correlates the calculation results of index a for each trial with index b, which represents whether or not a slip occurred. Index b is 1 if a slip occurred, and 0 if a slip did not occur. In other words, index b distinguishes between the occurrence of a slip and the occurrence of a slip using two values.

[0074] [Table 1]

[0075] A graph plotting the relationship between index a and index b is shown in Fig. 4. The horizontal axis of Fig. 4 represents index a, and the vertical axis represents index b.

[0076] The control device 120 can calculate the index a as measurement data during the patrol of the robot 200. The relationship between the index a and the index b was further analyzed so that the control device 120 can determine whether the outdoor situation is dangerous based on the index a, i.e., based on slipperiness.

[0077] In this example, binomial logistic regression was performed with index a as the explanatory variable and index b as the objective variable. Specifically, the probability of a slip occurring when ascending or descending a step, i.e., the conditional probability that index b is 1, was calculated as the risk of a slip when ascending or descending a step, given index a, which represents the slipperiness of the route.

[0078] As a result of the analysis, the value of index a was 2.03% when the probability that index b was 1, i.e., the probability that the robot 200 would slip while ascending or descending a step, was 1%. In this embodiment, this value, i.e., 2.03%, was set as the step count threshold.

[0079] When the step count threshold is set to 2.03%, in the judgment procedure of step S5 in Figure 3, the control device 120 judges that the outdoor situation is dangerous based on slipperiness if index a, which represents the slipperiness of the patrol route, is 2.03% or more, and judges that the outdoor situation is not dangerous based on slipperiness if index a is less than 2.03%.

[0080] In this embodiment, the value of index a when the probability that index b becomes 1 is 1% is set as the step count threshold. In other words, the judgment threshold is set to 1%. A 1% probability that index b becomes 1 can be rephrased as 1 / 99 odds that index b becomes 1. The reason why 1% is used as the standard for the probability that index b becomes 1 is because the present disclosure aims to reduce the risk of an event such as a fall or slip of the robot 200 occurring and to allow the robot 200 to continue autonomous patrol without intervention by a worker or other device as much as possible. 1%, which is sometimes used as a risk rate in statistics, is used as a standard value for sufficiently reducing risk. The standard value for the probability that index b becomes 1 used to set the step count threshold is not limited to 1% and may be changed to another value as appropriate.

[0081] The control device 120 may set the step count threshold based on data correlating the measured number of steps obtained in a trial in a preliminary experiment with whether or not the robot 200 has slipped, and then update the step count threshold based on new data obtained when the robot 200 performs an outdoor patrol inspection. Specifically, when the control device 120 has the robot 200 perform an outdoor patrol inspection, the control device 120 may acquire data correlating the measured number of steps when the robot 200 moves between A and B on the patrol route 50 in FIG. 2 with whether or not the robot 200 has slipped at the stepped sections 51 and 52. The control device 120 may perform binomial logistic regression on a data set accumulated by adding data obtained when the robot 200 actually patrols to the data from the preliminary experiment, calculate the value of index a when the probability that index b becomes 1 is 1%, and update the step count threshold to the newly calculated value of index a.

[0082] As described above, by updating the step count threshold using data obtained when the robot 200 actually patrols, the accuracy of determining the risk of the robot 200 falling or slipping when moving over a step or the like is improved.

[0083] In the above-described embodiment, the step count threshold is set and updated by the control device 120. The OT layer control device 110 or the IT layer control device 100 may set and update the step count threshold.

[0084] The method for determining the risk of an event such as a fall or slip occurring to the robot 200 is not limited to the method described in the above embodiment, and various other methods may be adopted, such as a method of constructing logic using a decomposition tree.

[0085] In another example, a multivariate analysis was performed using weather data from each trial of the preliminary experiment as an explanatory variable and index a, which represents the slipperiness of the patrol route, as a dependent variable. Table 2 below shows data used in the multivariate analysis, which associates the calculation results of index a from each trial with indexes c to g, which represent weather data. Index c represents the weather. Index c is 0 when it is clear, i.e., there is sunshine, 1 when it is cloudy, i.e., there is no sunshine, and 2 when it is raining. Index c may be replaced with the hours of sunshine. Index d is the accumulated value of rainfall over the past six hours. Index e is the average humidity over the past six hours. Index f is the average temperature over the past six hours. Index g is the average wind speed over the past six hours.

[0086] [Table 2]

[0087] By performing the above-described multivariate analysis, a prediction formula for predicting index a from weather data is generated. The control device 120 may acquire weather data as prior information and apply the weather data to the prediction formula to calculate a predicted value of index a. The control device 120 may determine that the outdoor situation is dangerous based on the prior information when the predicted value of index a is equal to or greater than the step count threshold. The control device 120 may determine that the outdoor situation is not dangerous based on the prior information when the predicted value of index a is less than the step count threshold.

[0088] The prediction formula for predicting the index a from the weather data may be updated based on new data obtained when the robot 200 performs an outdoor patrol inspection. Specifically, the control device 120 may acquire data that associates weather data obtained when the robot 200 performs an outdoor patrol inspection with the number of steps measured when the robot 200 moves between A and B on the patrol route 50 in Fig. 2. The control device 120 may generate a prediction formula by performing multivariate analysis on a data set that is accumulated by adding data obtained when the robot 200 actually patrols to data from a preliminary experiment, and then update the prediction formula.

[0089] The above-described prediction formula may be generated using index b as the objective variable. However, because the prediction formula is used for advance determination, if it is determined in advance that the outdoor situation is dangerous, the robot 200 will avoid patrolling. As a result, the robot 200 will not actually fall or slip, and there is a low possibility that new data will be acquired that will cause index b to be 1 when the robot 200 performs an outdoor patrol inspection. In this case, the accuracy of the prediction formula using index b as the objective variable may not improve even if new data obtained when the robot 200 performs an outdoor patrol inspection is reflected. Therefore, when updating the prediction formula to improve accuracy, it is preferable to use index a as the objective variable.

[0090] The weather data is not limited to the combination of indices c to g as described above, but may be one index or a combination of any two or more indices.

[0091] The method for generating a prediction formula is not limited to the multivariate analysis described above, but may also be logistic regression using weather data such as indicators c to g as explanatory variables and indicator b as the dependent variable, or various other methods may be used.

[0092] In the above-described embodiment, the prediction equation is generated and updated by the control device 120. The OT layer control device 110 or the IT layer control device 100 may generate and update the prediction equation.

[0093] In the above-described embodiments, when the robot 200 is a legged robot, whether the outdoor situation is dangerous is determined based on slipperiness by setting a step count threshold. When the robot 200 moves using wheels or crawlers, whether the outdoor situation is dangerous may be determined based on slipperiness by setting a rotation count threshold in the same way as the step count threshold.

[0094] <Determination based on wind speed> The control device 120 may acquire measurement data of wind speed along the patrol route and determine whether the outdoor conditions are dangerous based on the measurement data of wind speed. When the robot 200 moves to points L1 and L2 located just before the step portions 51 and 52 on the patrol route 50 in FIG. 2 , the control device 120 may determine whether the outdoor conditions at the step portions 51 and 52 are dangerous based on the measurement data of wind speed at points L1 and L2.

[0095] Based on the wind speed measurement data, the control device 120 may estimate the probability of an event such as the robot 200 tipping over or sliding down. Based on data associating the wind speed measurement data, including the wind direction and strength, with whether or not an event such as the robot 200 tipping over or sliding down has occurred, the control device 120 may estimate the probability of an event such as the robot 200 tipping over or sliding down.

[0096] As a preliminary experiment, the robot 200 was moved to points L1 and L2 just before the step sections 51 and 52, and wind speed measurement data at points L1 and L2 was obtained from the anemometer 201. The robot 200 was also made to enter the step sections 51 and 52, and whether or not the robot 200 had slipped off the step sections 51 and 52 was confirmed. In this example, nine trials were conducted. Table 3 below shows data that associates the wind speed measurement data for each trial with an index b indicating whether or not a slip occurred. The wind speed measurement data includes the absolute value of the wind speed and components of the wind speed on each axis of the x-y-z coordinate system. The index b is 1 if a slip occurred, and 0 if a slip did not occur.

[0097] [Table 3]

[0098] In this example, binomial logistic regression was performed with the wind speed measurement data as the explanatory variable and the index b as the objective variable. Specifically, for the wind speed measurement data, the probability that the robot 200 will slip at the step sections 51 and 52, i.e., the conditional probability that the index b will be 1, was calculated as the risk of slipping when entering the step sections 51 and 52.

[0099] By executing the binomial logistic regression described above, a prediction formula is generated for predicting the probability that index b will be 1 from the wind speed measurement data. The control device 120 may acquire the wind speed measurement data when the robot 200 moves to points L1 and L2, and apply the wind speed measurement data to the prediction formula to calculate the probability that index b will be 1, i.e., the predicted value of the probability that the robot 200 will slip.

[0100] When the probability that the index b will be 1 is less than 1%, the control device 120 may determine that the outdoor situation at the stepped portions 51 and 52 is not dangerous based on the wind speed, and may allow the robot 200 to enter the stepped portions 51 and 52. When the probability that the index b will be 1 is 1% or more, the control device 120 may determine that the outdoor situation at the stepped portions 51 and 52 is dangerous based on the wind speed, and may not allow the robot 200 to enter the stepped portions 51 and 52. In other words, the control device 120 causes the robot 200 to avoid entering the stepped portions 51 and 52. In this case, the determination threshold is set to 1%, but may be set to another value.

[0101] When the control device 120 has caused the robot 200 to avoid entering the step sections 51 and 52, the control device 120 may cause the robot 200 to wait at the points L1 and L2 until the outdoor conditions at the step sections 51 and 52 are no longer dangerous. When the control device 120 has caused the robot 200 to avoid entering the step sections 51 and 52, the control device 120 may cause the robot 200 to return to an avoidance location on the patrol route 50 or the indoor section 11, etc.

[0102] The control device 120 may determine whether the outdoor situation is dangerous based on the wind speed even while the robot 200 is moving up and down the step sections 51 and 52. If the control device 120 determines that the outdoor situation is dangerous while the robot 200 is ascending and descending the step sections 51 and 52, the control device 120 may stop the robot 200 from ascending and descending the step sections 51 and 52 and cause the robot 200 to assume a stable posture. If the control device 120 determines that the outdoor situation is no longer dangerous, the control device 120 may cause the robot 200 to resume ascending and descending the step sections 51 and 52.

[0103] The prediction formula for predicting the probability that the index b will be 1 from the wind speed measurement data may be updated based on new data obtained when the robot 200 performs an outdoor patrol inspection. Specifically, the control device 120 may acquire data correlating the wind speed measurement data obtained when the robot 200 is made to perform an outdoor patrol inspection with the occurrence or non-occurrence of a slip when the robot 200 ascends and descends the stepped sections 51 and 52. The control device 120 may generate a prediction formula by performing binomial logistic regression on a data set accumulated by adding data obtained when the robot 200 actually patrols to data from a preliminary experiment, and may update the prediction formula.

[0104] The control device 120 may calculate the wind speed when the probability that the index b will be 1 is 1% based on a prediction formula for the probability that the index b will be 1. The control device 120 may set the wind speed when the probability that the index b will be 1 is 1% as the wind speed threshold.

[0105] In addition to the prediction formula for predicting the probability that index b will be 1 described above, a prediction formula for predicting index a may be generated by performing multivariate analysis using wind speed measurement data as an explanatory variable and index a, which represents slipperiness and is calculated based on the wind speed measurement data, as a response variable. When the robot 200 moves to points L1 and L2, the control device 120 may calculate a predicted value of index a by applying local wind speed measurement data at points L1 and L2 to the prediction formula. When the predicted value of index a is equal to or greater than a step count threshold or a rotation count threshold, the control device 120 may determine that the outdoor situation is dangerous based on the wind speed and cause the robot 200 to avoid entering the step sections 51 and 52. When the predicted value of index a is less than a step count threshold or a rotation count threshold, the control device 120 may determine that the outdoor situation is not dangerous based on the wind speed and cause the robot 200 to enter the step sections 51 and 52.

[0106] The control device 120 may apply the wind speed forecast to the prediction formula to obtain the probability that the index b will be 1 or the predicted value of the index a, and perform a preliminary determination based on the predicted value.

[0107] In the above-described embodiments, the generation and updating of the prediction equation is performed by the control device 120. The OT layer control device 110 or the IT layer control device 100 may also generate and update the prediction equation. Furthermore, in the above-described embodiments, the control device 120 determines whether the outdoor situation is dangerous based on the wind speed measurement data. The OT layer control device 110 or the IT layer control device 100 may also determine whether the outdoor situation is dangerous based on the wind speed measurement data. When the wind speed measurement data changes significantly over time, it is preferable that the control device 120 mounted on the robot 200 determine whether the outdoor situation is dangerous based on the wind speed measurement data so as to avoid delays in the determination due to communication delays.

[0108] Although the embodiments of the present disclosure have been described based on the drawings and examples, it should be noted that those skilled in the art could make various modifications or alterations based on the present disclosure. Therefore, it should be noted that these modifications and alterations are included within the scope of the present disclosure. For example, the functions included in each component or step can be rearranged so as not to cause logical inconsistencies, and multiple components or steps can be combined or divided into one. The embodiments of the present disclosure can also be realized as a program executed by a processor included in an apparatus or a storage medium on which a program is recorded. It should be understood that these are also included within the scope of the present disclosure.

[0109] Furthermore, in the above embodiment, the difficult-to-move location is an outdoor portion of the patrol route. However, the difficult-to-move location in the present disclosure is not limited to outdoor locations. Even if the patrol route is composed entirely of indoor routes, if there is a section of the indoor route where robot movement is more difficult than other sections, the present disclosure can be applied to that section as a difficult-to-move location. Examples of difficult-to-move locations include locations where there is a source of dust, oil, moisture, etc., which causes localized slipperiness, or locations where wind power equipment such as fans is installed and causes localized high wind speeds. In this case, the control device 120 can determine whether the difficult-to-move location is dangerous, as in the above embodiment, using data indicating the operating status of the source of dust, oil, moisture, etc., or the operating status of the wind power equipment as "prior information." [Explanation of symbols]

[0110] 1 Patrol inspection system 10 Plant (11: Indoor part, 12: Outdoor part) 50 patrol route (51, 52: step section) 100 IT layer control equipment 101 External Network 102 IT layer terminal device 110 OT layer control device 111 Hub 112 Plant Network 113 Firewall 120 Control device 200 Robot (201: Anemometer, 202: Driving device, 203: Displacement measuring device, 204: Inspection device) 210 Charging Station

Claims

1. A patrol inspection system that inspects a patrol route including a difficult-to-move location, a robot that moves along the patrol route and performs inspections; a control device for controlling the robot; Equipped with the control device causes the robot to avoid inspecting the patrol route when it determines that a difficult-to-travel location situation, which is a situation of the difficult-to-travel location, is dangerous when the robot inspects the difficult-to-travel location, Patrol inspection system.

2. The patrol inspection system according to claim 1, wherein the control device determines whether the difficult-to-travel location situation is dangerous based on at least one of advance information regarding the difficult-to-travel location situation or measurement data regarding the difficult-to-travel location situation.

3. The control device Before the robot starts inspecting the patrol route, it performs a preliminary determination of the difficult-to-travel location situation based on the preliminary information; When it is determined in the advance determination that the difficult-to-travel location situation is not dangerous, the robot is caused to start inspecting the patrol route; The patrol inspection system according to claim 2 , wherein the robot re-evaluates the status of the difficult-to-travel location based on the measurement data while inspecting along the patrol route.

4. The patrol inspection system of claim 2, wherein the difficult-to-travel location is an outdoor portion of the patrol route, and the advance information includes at least one of a weather forecast for the outdoor portion or past weather observation data.

5. The patrol inspection system according to claim 4 , wherein the measurement data includes at least one of an index representing slipperiness of the outdoor portion and a wind speed in the outdoor portion.

6. The patrol inspection system according to claim 5 , wherein the robot is equipped with an anemometer that measures wind speed in the outdoor portion.

7. The patrol inspection system according to claim 6 , wherein the anemometer is an ultrasonic anemometer.

8. The control device determines whether the difficult-to-travel location is a dangerous location, such as at least one of a step or a slope located outdoors on the patrol route.

9. A patrol inspection method for inspecting a patrol route including a difficult-to-move location, a patrol step in which a control device moves the robot along the patrol route; an inspection step in which the robot inspects along the patrol route; Including, In the patrol step, when the control device determines that a difficult-to-travel location situation is dangerous when the robot inspects the difficult-to-travel location, the control device causes the robot to avoid inspecting the patrol route. Patrol inspection method.

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