Method, robot and program for generating monitoring path of facility monitoring robot

Abstract

The present invention relates to a method for generating a facility monitoring path of a robot, and may comprise the steps of: generating one or more candidate monitoring paths on the basis of state data of a robot for monitoring a space to be monitored; selecting an optimal monitoring path from among the candidate monitoring paths on the basis of state data and monitoring paths of other robots for monitoring the space to be monitored; and monitoring, on the basis of the optimal monitoring path, the space to be monitored.

Description

Method for generating surveillance paths for facility surveillance robots, robots, and programs

[0001] The present invention relates to a technology for generating a surveillance path for a facility surveillance robot.

[0002] Traditionally, facility surveillance tasks were often performed using a single robot. This approach required a single robot to move along a fixed path, limiting the scope of its surveillance. This presented a significant problem, particularly in facilities with large areas or complex structures, where blind spots could arise beyond the robot's reach.

[0003] Furthermore, because a single robot performs tasks with limited resources, it is difficult to respond immediately to unexpected situations in a specific area. For example, in the event of an unexpected event such as a fire, intrusion, or equipment failure, the robot's ability to immediately detect or respond by changing its path is limited because it follows a fixed path.

[0004] To overcome the limitations of these single-robot-based surveillance systems, multi-robot surveillance systems have emerged. Multi-robot systems have the advantage of enabling surveillance over a wider area by allowing multiple robots to operate simultaneously, each monitoring a different area.

[0005] However, new problems can arise even in multi-robot systems that move independently without collaboration.

[0006] If each robot performs tasks independently and in a non-collaborative manner, paths between robots can overlap or tasks can be unnecessarily repeated. This can lead to resource waste, with multiple robots performing duplicate tasks in certain areas, and can also lead to a lack of oversight of other critical areas.

[0007] Additionally, in situations where each robot operates independently without cooperating in real time, changes in the status of other robots or changes in the environment are not taken into account, so monitoring may be missed if a specific robot stops working due to reasons such as low battery, the occurrence of an obstacle, or a sensor malfunction.

[0008] Therefore, a method for generating surveillance paths for facility surveillance robots is required to overcome the limitations of these non-collaborative multi-robot systems.

[0009] The purpose of the present invention is to propose a method, robot, and program for generating a surveillance path for a facility surveillance robot.

[0010] Specifically, the present invention aims to propose a method for generating a surveillance path of a facility surveillance robot by taking into account the surveillance path of another robot.

[0011] The objectives of the present invention are not limited to those mentioned above. Other objectives and advantages of the present invention not mentioned above can be understood through the following description and will be more clearly understood through the embodiments of the present invention. Furthermore, it will be readily apparent that the objectives and advantages of the present invention can be realized by the means and combinations thereof set forth in the claims.

[0012] According to an embodiment of the present invention for achieving the above-described purpose, a method for generating a facility surveillance path performed by a robot may include a step of generating at least one candidate surveillance path based on status data of a robot that monitors a target space, a step of selecting an optimal surveillance path among the candidate surveillance paths based on status data and surveillance paths of another robot that monitors the target space, and a step of performing a surveillance task of the target space based on the optimal surveillance path.

[0013] Additionally, the selecting step may select the surveillance path so that the surveillance ranges between each robot monitoring the target space do not overlap.

[0014] Additionally, the status data may include at least one of battery level, sensor status, movement speed, and current location.

[0015] Additionally, the generating step may generate the candidate surveillance paths by considering the surveillance priority area within the target space.

[0016] Additionally, the generating step may generate candidate surveillance paths by considering a specific event when the specific event occurs within the target space.

[0017] Additionally, the generating step can predict a dynamic change area that is likely to be affected by the specific event, and generate candidate surveillance paths by considering the predicted dynamic change area.

[0018] Meanwhile, a robot performing a facility surveillance path generation method may include a control unit that generates at least one candidate surveillance path based on status data of a robot that monitors a target space, selects an optimal surveillance path among the candidate surveillance paths based on status data and surveillance paths of other robots that monitor the target space, and performs surveillance work of the target space based on the optimal surveillance path.

[0019] Additionally, the control unit can select the surveillance path so that the surveillance ranges between each robot monitoring the target space do not overlap.

[0020] Additionally, the status data may include at least one of battery level, sensor status, movement speed, and current location.

[0021] Additionally, the control unit can generate the candidate surveillance paths by considering the surveillance priority area within the target space.

[0022] Additionally, the control unit can generate candidate surveillance paths by considering a specific event when a specific event occurs within the target space.

[0023] Additionally, the control unit can predict dynamic change areas that are likely to be affected by the specific event, and generate candidate surveillance paths by considering the predicted dynamic change areas.

[0024] Meanwhile, a computer program stored in a computer-readable recording medium according to an embodiment of the present invention for achieving the above-described purpose may include a program code for performing the above-described driving path generation method.

[0025] In addition, a computer-readable recording medium according to an embodiment of the present invention for achieving the above-described purpose may record a computer program for executing the above-described driving path generation method.

[0026] According to the present invention, by receiving surveillance paths and status data of other robots in real time and selecting surveillance paths based on the same, surveillance range duplication between robots can be prevented and surveillance efficiency can be maximized.

[0027] In addition, the present invention enables the robot to continuously optimize a path based on real-time status data of the target space, thereby enabling it to immediately respond to dynamic environmental changes, unlike existing fixed path monitoring methods.

[0028] The effects of the present invention are not limited to the effects mentioned above, and other effects not mentioned will be clearly understood by those skilled in the art from the description below.

[0029] Figures 1 and 2 are drawings showing a robot according to one embodiment of the present invention.

[0030] FIG. 3 is a drawing showing the configuration of a robot control system according to one embodiment of the present invention.

[0031] Figure 4 is a drawing showing the configuration of a robot according to one embodiment of the present invention.

[0032] FIG. 5 is a diagram illustrating a map creation method according to one embodiment of the present invention.

[0033] Figure 6 is a drawing showing some of the maps described in Figure 5.

[0034] FIG. 7 is a diagram illustrating a map generation method according to an exemplary embodiment of the present invention.

[0035] FIG. 8 and FIG. 9 are flowcharts illustrating a method for generating a surveillance path according to one embodiment of the present invention.

[0036] The following merely illustrates the principles of the present invention. Therefore, those skilled in the art will be able to implement the principles of the present invention and invent various devices within the scope and spirit of the present invention, even if not explicitly described or illustrated herein. Furthermore, all conditional terms and embodiments listed herein are expressly intended, in principle, to facilitate understanding of the concepts of the present invention, and should be understood as being in no way limiting to the specifically enumerated embodiments and conditions.

[0037] The above-described objects, features and advantages will become more apparent through the following detailed description with reference to the attached drawings, so that a person having ordinary skill in the art to which the present invention pertains can easily practice the technical idea of ​​the present invention.

[0038] In addition, in describing the present invention, if it is determined that a detailed description of a known technology related to the present invention may unnecessarily obscure the gist of the present invention, the detailed description will be omitted.

[0039] Hereinafter, various embodiments of the present invention will be described in detail with reference to the attached drawings.

[0040] Figures 1 and 2 are drawings showing a robot (10) according to an exemplary embodiment of the present invention. Here, the robot (10) can be divided into a robot (10a) that drives in an indoor environment and a robot (10b) that drives in an outdoor environment.

[0041] For example, in the case of a robot (10a) that is equipped with a display unit (111) on the front as shown in Fig. 1 and requires information exchange with a user, it may be suitable for driving in an indoor environment, and in the case of a robot (10b) that is sealed by a housing (12) as shown in Fig. 2 and does not have a separate display unit, it may be suitable for driving in an outdoor environment.

[0042] The robot (10a) of Fig. 1 may include a body part (11), a driving part (151, 153), and a head part (13).

[0043] The head (13) is equipped with a display (131) on the front to display information for communication with the user, and a sensor (133) is equipped on the upper part of the head (13) to collect various information necessary for the driving of the robot (10a).

[0044] The body part (11) is provided with a display part (111) on the front to display information required by the user or the status of the robot, etc. For example, the display part (131) of the head part can display information in the form of feedback according to the input value of the user or administrator, and the display part (111) of the body part can display the time, weather, information of the target space, the status of the robot, etc., and can display the above-described information in various ways according to the user's operation.

[0045] The driving part of this embodiment may be provided in the form of a wheel at the lower part of the body part (11), and may include a main wheel (151) that rotates directly by a motor and an auxiliary wheel (153) that prevents the robot (10a) from overturning and rotates by friction with the ground according to the movement of the robot (10a).

[0046] The robot (10b) of Fig. 2 has a structure in which the internal structure of the robot is firmly sealed by a housing (12), and unlike the robot (10a) of Fig. 1, structures such as the display portion (111, 113) that are relatively less durable are omitted.

[0047] More specifically, the housing (12) forms a combined structure of an upper housing (12u) and a lower housing (12d), and a sensor (121) is provided on the upper surface of the upper housing (12u), and a sensor (123) is also provided on the front surface of the lower housing (12d). Of course, various types of sensors can be adopted for each sensor (121, 123) depending on the purpose.

[0048] In addition, as described above, the wheels (141) forming the driving part of the robot (10b) of the present embodiment for driving in an outdoor environment can be directly rotated by the power transmission of the motor.

[0049] The robots (10a, 10b) described above are exemplary drawings for expressing the robots described in the following embodiments, and are a type of robot that constitutes the logic and system described below, and therefore should not be interpreted as being limited thereto.

[0050] FIG. 3 is a drawing showing the configuration of a robot control system according to an exemplary embodiment of the present invention, and FIG. 4 is a drawing showing the configuration of a robot according to an exemplary embodiment of the present invention.

[0051] The following description is provided with reference to Figures 3 and 4.

[0052] The robot control system of this embodiment may include a robot (10), a database (30), and a server (50).

[0053] The robot (10) may include a robot of various shapes and configurations that can drive indoors and outdoors as described above, and may perform a mission by transmitting and receiving information such as map information, driving information, and driving route information with a database (30) and a server (50).

[0054] Referring to FIG. 4, the robot (10) of the present embodiment may include a control unit (210), a movement module (220), a sensor unit (230), a photographing unit (240), a display unit (250), a storage unit (260), a communication unit (270), a map generation unit (280), and a map merging unit (290).

[0055] First, the movement module (220) can be composed of a motor, a gear assembly, and wheels, and can provide driving force for movement (driving) of the robot (10).

[0056] Specifically, the motor is a core component of the movement module, which directly transmits driving force to the robot's wheels, and the gear assembly appropriately converts the rotational force generated by the motor and transmits it to the wheels, and the wheels transmit this driving force to the ground, allowing the robot to move in the desired direction.

[0057] The movement module (220) can be controlled based on the current flowing to the motor while the robot is moving.

[0058] The sensor unit (230) may include various sensors that can acquire information about the target space while the robot moves within the target space. For example, the sensor unit (230) may include at least two of an image sensor, a lidar sensor, and a radar sensor. Here, the target space refers to a specific area or region where the robot (10) moves or performs work. This refers to a physical location where the robot (10) must move, and may mainly refer to an indoor or outdoor space, and may include a destination or work environment where the robot's route setting, driving, and work are performed.

[0059] Specifically, the sensor unit (230) may include several sensors for measuring the status of the robot (10), thereby generating status data regarding the status of the robot (10). For example, the status data may include battery status (e.g., temperature, remaining capacity, etc.), motor status, location information (e.g., current location, inclination, acceleration, etc.), temperature information, wind direction, vibration information, communication strength between other robots, and network delay time.

[0060] The photographing unit (240) may include a real-image sensor unit (not shown) for photographing real-image images, a thermal image sensor unit (not shown) for acquiring thermal images, etc. For example, the real-image sensor unit (not shown) may be implemented as an RGB camera, and the thermal image sensor unit (not shown) may be implemented as an infrared (infra-red) camera. Through the configuration of the photographing unit (240), the robot (10) can accurately identify objects not only in a high-illuminance environment such as during the day, but also in a low-illuminance environment such as at night.

[0061] The display unit (250) can display the status of the robot (10), time, weather, information on the target space, etc. In terms of the robot control system of the present embodiment, for example, when the robot (10) is unable to drive or perform a mission (or perform a task) due to an event occurring, the robot (10) can transmit status information of the robot (10) to the server (50) and then display at least a part of the status information of the robot (10) through the display unit (250) while waiting until a worker arrives at the location at which the status information was transmitted to the server (50) and a separate command is input.

[0062] That is, the display unit (250) can display the general status of the robot, information required for the mission, information to be provided to the user or worker, and of course, information required for the robot control system can also be displayed.

[0063] The storage unit (260) can store various data required for the operation of the robot (100) or various data generated during the operation, and can store various data received from the outside. For example, the storage unit (260) can store programs for the operation of the robot (100), map information, captured images, scenarios for mission execution, etc.

[0064] Additionally, the storage unit (260) can store status data of the robot (10) acquired in real time, status data of other robots, or a monitoring path.

[0065] The communication unit (270) may include one or more modules that enable the robot (10) to communicate with other devices (e.g., a remote control system, a server (50), another robot, a database (30), etc.). For example, the communication unit (270) may receive real-time weather information about the current location or purpose of the robot (10) from an external server.

[0066] For example, the communication unit (270) can transmit status data to another robot or receive status data or a monitoring path of another robot from another robot.

[0067] Additionally, the communication unit (270) may include a GPS (Global Positioning System) module, and the communication unit (270) may receive signals from satellites to determine the current location of the robot (10).

[0068] Meanwhile, the control unit (210) may include a processor (211), a path generation unit (2131), a driving path map generation unit (2133), a driving control unit (215), and an event detection unit (217).

[0069] The processor (211) can process information obtained from various components included in the above-described robot.

[0070] The path generation unit (2131) and the driving path map generation unit (2133) can select any one of the maps formed by arranging (merging) at least two different format maps generated through the map generation unit (280), and can generate a driving path of the robot through the path generation unit (2131) within the selected map, or can generate a driving path map used by the robot based on the driving path generated through the driving path map generation unit (2133).

[0071] The above driving path map means a simplified map composed of nodes, edges, and context information included in each node or edge, generated according to the example described below. Nodes may represent objects that are targets of a robot's mission or points where a change in the robot's status (e.g., change in driving direction) occurs on the driving path. Edges may connect nodes and represent the robot's driving path between nodes. Context information may represent control command values ​​for the robot at nodes or edges, information about nodes, etc.

[0072] Meanwhile, the path generation unit (2131) can generate a driving path between objects using a map generated by the global map generation unit (281), and in the vicinity of the object (a predetermined area based on the object), a path can be generated using a map generated by the local map generation unit (283), thereby generating a driving path more effectively. Similarly, when modifying the generated driving path for other reasons, the driving path can be modified based on the exemplary criteria described above, thereby enabling a quick response to other reasons. Here, the object may mean an object that affects the driving of the robot (10), and may include an obstacle or a target for surveillance.

[0073] In addition, by way of example, the path generation unit (2131) can generate a plurality of candidate driving paths for the robot (10) to perform a mission in a target space (map information), and select an optimal surveillance path from the generated candidate surveillance paths based on preset criteria, thereby generating an optimal driving path for the robot (10).

[0074] Additionally, the path generation unit (2131) can generate an optimal driving path based on status data of other robots.

[0075] Specifically, the path generation unit (2131) generates multiple candidate surveillance paths for monitoring a surveillance target within a target space from the robot's position, and selects at least one of the candidate surveillance paths as the optimal surveillance path based on preset selection criteria. This will be described later in FIGS. 8 to 10.

[0076] Meanwhile, the driving control unit (215) can generate or transmit a signal for controlling the movement module (220). More specifically, the signal for controlling the movement module (220) may be generated by a control signal input from the server (50) through the communication unit (270), or the signal for controlling the movement module (220) may be generated based on a result of processing through the processor (211) based on information about the target space acquired from the sensor unit (230) or the photographing unit (240).

[0077] Additionally, the drive control unit (215) can generate a control signal to provide optimal driving force to the movement module (220) according to real-time current changes analyzed through the processor (211).

[0078] For example, if the current increases above a certain level, the robot may be facing a situation where it experiences high resistance (e.g., a slope or an uneven surface), so the gear ratio may be adjusted or the rotation speed of the motor may be adjusted accordingly to ensure stable driving.

[0079] The event detection unit (217) can detect an abnormal situation occurring in any of the objects existing in the target space, an abnormal situation occurring on the robot's driving path, or an abnormal situation occurring in the robot, through the sensor unit (230), the camera unit (240), the communication unit (270), and the process (211).

[0080] The map generation unit (280) can convert the target space where the robot (10) drives into various formats and then generate a map for each format, and the map merging unit (290) can perform conversion and alignment of maps generated in each format.

[0081] This is explained in more detail with reference to examples in Figures 5 and 6 below.

[0082] Meanwhile, the database (30) may store information on map information for the target space, multiple scenarios, driving routes, types of events, etc. For example, the map information may include various map information for expressing the target space, and may include, for example, a satellite map (2D Map), SLAM information (Simultaneous Localization and Mapping), PCD (Point Cloud Data), a topological map, a semantic map, an HD map (High-Definition Map), etc. for the target space.

[0083] The server (50) may transmit map information to the robot (10), or may assign a mission to the robot (10) or perform a robot (10) control task according to the assigned mission.

[0084] Of course, the server (50) may also serve as an information relay point between the robot (10) and the database (30) on the robot control system, and some of the above-described vehicle event type confirmation, map information transmission, and robot control command transmission may be performed in the database (30) or through a configuration installed in the robot (10).

[0085] FIG. 5 is a drawing showing a map creation method according to an exemplary embodiment of the present invention, and FIG. 6 is a drawing showing some maps described in FIG. 5.

[0086] The following description is provided with reference to Figures 4 to 6.

[0087] In this embodiment, the map used by the robot (10) to perform the mission is a map (hereinafter referred to as a hybrid map) in which maps of different formats are merged (overlapping, aligned, and stacked), and can be divided into a global map and a local map depending on the form of the map.

[0088] A global map may mean a 2D map generated through a global map generation unit (281) based on a satellite map received from a communication unit (270) or a database (30), and a local map may mean a 3D map (spatial map, feature map) generated through a local map generation unit (283) based on point cloud information (Point Cloud Data, PCD) received from a communication unit (270) or a database (30).

[0089] Of course, the point cloud information required for the above local map creation may be collected through the sensor unit (230) while the robot (10) drives for mapping the target space and may be stored in the storage unit (260).

[0090] The map merging unit (290) can generate a hybrid map using maps of different formats. More specifically, the map merging unit (290) can include a map conversion unit (291) and a map alignment unit (293). The map conversion unit (291) can convert one of the different formats of maps into a reference format to generate a specific map, and the map alignment unit (293) can generate the specific map by overlapping and aligning maps that have been converted and formed into the same format.

[0091] Of course, the map alignment unit (293) can also create a single map by overlapping and aligning map information of different formats as described above, and for example, objects that are mission targets based on the global map can be expressed as nodes, and detailed information of objects expressed as each node can be overlapping and aligning information of the local map to create a hybrid map.

[0092] Referring to FIG. 5, a series of processes divided into steps S11 (S111 to S117) for generating a first map represents a process for generating the global map described above, a series of processes divided into steps S14 (S141 to S147) represents a process for generating a local map, and a series of processes divided into steps S16 (S161 to S165) represents a process for converting some information during the local map generation process into a 2D map and generating an intermediate map by merging the necessary information with the first map.

[0093] More specifically, first, looking at the process of creating a global map, the robot (10) can receive satellite information (S111) from a database (30) or server (50) through a communication unit (270).

[0094] The above satellite information may include aerial photographs, orthophotos, and true orthophotos of the target space, and may be expressed as photographs or images such as d1 in FIG. 6, for example.

[0095] After receiving satellite information, the global map generation unit (281) can generate a first map (S117) by dividing an area (S113) and performing labeling (S115) based on the received satellite information.

[0096] More specifically, information included in 2D Layout Data, such as road boundaries, building boundaries, and roads usable by robots (d51), can be expressed through division of areas (S113), as exemplarily expressed in d5, and labeling (S115) can be performed by inputting context information for each divided area, required area, or expressed information.

[0097] The 2D map generated through the above-described process may be referred to as the first map (d5) in this embodiment.

[0098] Next, looking at the process of generating a local map, the robot (10) can collect point cloud information of the target space (S141), which can be expressed as d2 in Fig. 6 as an example. The collection refers to various methods of obtaining point cloud information (3D data), as described above.

[0099] Meanwhile, the spatial map generation unit (2833) can generate a spatial map (d3) based on the above point cloud information. Briefly, the generation of the spatial map can be generated through a postprocessing step of the acquired raw data (PCD, 3D data). For example, after performing outlier removal (noise removal) through the acquired raw information, each data set can be aligned and merged to perform a rendering operation.

[0100] After a series of processes for generating the above spatial map are performed, or during a series of processes, the feature map generation unit (2831) can generate a feature map (d4) (S147) through a step (S145) of extracting feature points for objects.

[0101] That is, the 3D map generated through the above-described process may be referred to as the second map (d4) in the present embodiment.

[0102] Meanwhile, the map merging unit (290) can convert a spatial map generated based on PCD into a 2D map (S161) through the map conversion unit (291), and then merge the converted map with the first map (S163) through the map alignment unit (293) to generate a third map (d5) (S165).

[0103] The third map can express some of the information not expressed in the satellite information by overlaying and aligning a 2D map converted through a spatial map (3D data) onto the first map generated based on the satellite information (2D layout data). Therefore, in Fig. 6, the first and third maps are expressed as d5 for convenience.

[0104] Meanwhile, the control unit (210) can create a hybrid map (d6) by merging the first map, the second map, and the third map through the map generation unit (280) and the map merging unit (290) (S18).

[0105] Additionally, according to various embodiments of the present invention, a hybrid map may be formed by merging a second map and a third map.

[0106] FIG. 7 is a diagram illustrating a map generation method according to an exemplary embodiment of the present invention.

[0107] The following description is provided with reference to Figure 7, but the above-described content is omitted.

[0108] The robot (10) of the present embodiment can create a global map (S11) through the above-described configuration and method, and the path creation unit (2131) can extract a path (d51 of FIG. 5) that the robot (10) can use based on the created global map (S13).

[0109] The path that the above robot (10) can use can be set as an area that includes a portion of the boundary demarcated as an area where a person can drive from the boundary demarcated as an area where a vehicle can drive, for example.

[0110] And the robot (10) can receive (S151) the PCD stored in the database (30) through the communication unit (270). More specifically, the PCD reception can be based on the robot's usage path extracted in the above step (S13).

[0111] That is, rather than receiving a large amount of PCDs for the target space, it will be possible to more effectively generate the robot's driving path or map by receiving PCDs on the path that the robot can use.

[0112] Meanwhile, the spatial map generation unit (2833) generates a PCD-based spatial map (S153), and when the generated spatial map is converted into a 2D map by the map conversion unit (291) (S155: Yes), the map alignment unit (293) can merge the converted 2D map and the map (first map, global map) generated in the above step (S11) to generate a hybrid map (S171).

[0113] The hybrid map generated in the above step (S171) can be referred to as a hybrid map in the sense that two maps containing different information are overlapping, but it is clear that the information contained is different from that of the hybrid map generated in the subsequent step S19.

[0114] After the above step (S171), the map alignment unit (293) can compare the matching rate (degree of overlap) of the two maps with a reference value, and if the matching rate exceeds the reference value (S173: No), the two overlapping maps can be aligned to create an intermediate map (S175).

[0115] Alternatively, for example, the hybrid map generated in the step (S171) may mean a map in which two maps containing different information (the first map and the converted 2D map) are overlapped and aligned, and in this case, if the matching rate (degree of overlap) in the step (S173) exceeds the reference value by comparing it with the reference value (S173: No), the intermediate map referred to in the step S175 may mean a map already generated in the step (S171).

[0116] The above degree of overlap can be determined based on elements (e.g., robot usage path boundary lines) commonly included in the first map (2D layout data map based on satellite information) and the 2D map converted from the spatial map (3D data).

[0117] Meanwhile, if the spatial map generated in the above step (S155) is not converted into a 2D map (S155: No), the feature map generation unit (2831) can extract feature points for objects from the spatial map and generate a feature map (S157), as described above.

[0118] And the control unit (210) can create a hybrid map (S19) by merging two or more maps created through the above-described process through the map creation unit (280) and the map merging unit (290).

[0119] Next, a method for generating a surveillance path of a facility surveillance robot is described with reference to FIG. 8.

[0120] Figure 8 is a flowchart illustrating a method for creating a surveillance path according to one embodiment of the present invention.

[0121] Referring to FIG. 8, a robot (10) monitoring a target space can generate multiple candidate surveillance paths based on the status data of the robot (10) through a path generation unit (2131) (S1000). At this time, the robot (10) can generate a candidate surveillance path that can perform a mission (or task) based on a hybrid map. Here, the candidate surveillance path may refer to a path along which the robot (10) repeatedly moves to monitor a surveillance target within the target space.

[0122] Specifically, the robot (10) can determine the location of obstacles within the target space through a hybrid map and generate a candidate surveillance path that can monitor the surveillance target while bypassing the obstacles.

[0123] Additionally, the robot (10) can generate candidate surveillance routes by considering priority surveillance zones within the target space. Rather than simply setting priority surveillance zones based on fixed criteria, the robot can dynamically assess risk based on real-time data and automatically reset priority surveillance zones. For example, a temperature change occurring in a specific area or a motion detection sensor alert can be used to determine whether that area requires more priority surveillance, and candidate surveillance routes can be generated accordingly.

[0124] In addition, the robot (10) can generate a candidate surveillance path that does not create a blind spot of the surveillance target within the target space by considering the angle of view of the camera.

[0125] And, the robot (10) can receive the surveillance path of another robot and status data of another robot from another robot in the target space through the communication unit (270) (S2000).

[0126] Next, the robot (10) can select an optimal surveillance path among candidate surveillance paths generated based on the status data and surveillance paths of other robots monitoring the target space (S3000).

[0127] Specifically, the robot (10) can select a path among the generated candidate surveillance paths that does not collide with the surveillance paths of other robots and does not duplicate surveillance of an area already being monitored by another robot. At this time, the surveillance path can be selected by comprehensively considering the robots' camera field of view (FOV), surveillance angle, and sensor range, rather than simply considering the movement path.

[0128] That is, the robot (10) can select the surveillance path so that the surveillance ranges between each robot monitoring the target space do not overlap.

[0129] Additionally, the robot (10) can select an optimal surveillance path among candidate surveillance paths generated by considering communication strength and network delay between other robots. This allows the robot to prevent work disruptions due to communication failures or data transmission delays and perform stable surveillance operations.

[0130] And, the robot (10) can monitor the surveillance target while driving in the target space according to the selected surveillance path (S4000).

[0131] Meanwhile, the robot (10) may repeat the above-described path generation and selection process (steps S1000 to S3000) according to a preset cycle while driving along the surveillance path. Here, the preset cycle may be variably determined depending on the number of surveillance targets of the robot (10), the travel distance, the size of the target area, the robot's battery consumption status, the stability of the surveillance task, etc.

[0132] For example, the more objects there are to monitor or the wider the monitoring area, the more the robot (10) can re-perform the path generation and selection process in a shorter cycle.

[0133] As another example, a robot with a high battery consumption may have a shorter re-run cycle of the path generation and selection process.

[0134] Through this, rather than the robot (10) simply selecting a surveillance path once and then driving, the robot (10) can actively respond to changing situations through a process of optimizing the surveillance path in real time.

[0135] Additionally, the robot (10) may repeat the aforementioned path generation and selection process (steps S1000 to S3000) when a specific event occurs. Here, specific events may include a decrease in battery power, detection of additional obstacles, weakening of communication strength, occurrence of fire or gas, etc. This will be further described with reference to FIG. 9.

[0136] Figure 9 is a flowchart illustrating a method for creating a surveillance path according to another embodiment of the present invention.

[0137] Referring to FIG. 9, the robot (10) can detect the occurrence of a specific event and determine whether the occurrence of the specific event affects the monitoring path of the robot (10) (S5000).

[0138] Specifically, the robot (10) may determine that a detected specific event does not affect the surveillance path if it is a minor problem such as a simple sensor malfunction or movement of a small object, and may determine that it affects the path if it is an event that involves a great risk (e.g., fire, intruder detection).

[0139] Additionally, if a specific event detected occurs within or in an area close to the robot's (10) surveillance path, the robot (10) may determine that the event affects the path. Additionally, if a specific event occurs in an area physically distant from the surveillance path, the robot (10) may determine that the event does not affect the surveillance path.

[0140] Additionally, the robot (10) can evaluate the importance of a specific event that has occurred and determine whether the specific event has an impact based on the evaluated importance. In this case, the robot (10) can determine the importance differently depending on whether the specific event that has occurred is temporary or occurs continuously.

[0141] For example, the robot (10) may evaluate certain temporary or non-repeating events as having lower importance, and may evaluate certain continuous events as having higher importance.

[0142] That is, the robot (10) can analyze the nature, location, importance, and relationship with the current surveillance path of a specific event that has occurred to determine whether it is necessary to change the current surveillance path.

[0143] Next, if it is determined that the surveillance path is affected (S5000, YES), the robot (10) can generate and select candidate surveillance paths by considering a specific event (S6000).

[0144] Specifically, the robot (10) can determine an area where a specific event has occurred as a new surveillance area or avoidance area based on a specific event, generate a candidate surveillance path that can monitor the new surveillance area, and select an optimal surveillance path by considering the surveillance paths and status data of other robots.

[0145] For example, if a fire warning is issued within a factory, the robot (10) can designate the area as a new surveillance zone and create a route for intensive surveillance of the fire zone. At this time, the robot can change the route to prioritize surveillance of an area close to the fire zone, and select a route that allows for real-time monitoring of the spread of the fire and changes in the surrounding environment within the area.

[0146] As another example, if an intruder is detected in a specific area, the robot (10) can set that area as a new surveillance area and create a path including an entrance / exit passage to prevent the intruder from leaving the area any longer. In this case, the robot (10) can track the movement paths of other robots and the intruder and select a surveillance path that expands the surveillance range.

[0147] Additionally, the robot (10) can determine an area where a specific event has occurred as an avoidance area based on a specific event, and generate a candidate surveillance path to avoid the avoidance area.

[0148] For example, in the event of a chemical spill, the robot can designate the area as an avoidance zone because it is a hazardous area, create a route that bypasses the area where the chemical spill occurred, and prioritize the safest surveillance route.

[0149] As another example, in areas with high electromagnetic interference, where communication becomes unstable, the robot can designate the area as an avoidance zone, generate candidate surveillance routes that bypass the avoidance zone, and select the surveillance route with the strongest communication signal among them.

[0150] Additionally, the robot (10) can monitor a new surveillance zone while maintaining part of the existing surveillance path or can generate a candidate surveillance path that can bypass the avoidance zone.

[0151] In addition, the robot (10) can additionally predict dynamic change areas that are likely to be further affected by a specific event, and generate candidate surveillance routes by considering the predicted dynamic change areas. At this time, the dynamic change area may refer to an area where a specific event is likely to spread (a surrounding area adjacent to the area where a specific event occurred), and the dynamic change area may be an area that needs to be safely bypassed or, conversely, an area that requires intensive surveillance. At this time, the robot can predict dynamic change areas that may be potentially affected by utilizing the event's spread pattern and surrounding environmental data (e.g., wind direction, terrain slope, humidity, temperature, etc.). For example, in the event of a fire, the robot can predict the area where smoke will spread by considering the wind direction and speed, and in the event of a hazardous substance leaking in liquid form, the robot can predict the area where the substance is likely to flow by considering the terrain slope.

[0152] Then, the robot (10) predicts the dynamic change zone and then generates a candidate surveillance route considering the dynamic change zone. For example, if a fire breaks out in Zone A within a factory and smoke is predicted to likely spread to Zone B, which is adjacent to Zone A, the robot (10) can generate a candidate surveillance route that bypasses Zone A (the event occurrence zone) and Zone B (the dynamic change zone).

[0153] Meanwhile, if it is determined that there is no effect on the surveillance path (S5000, NO), the robot (10) can continue to drive along the previously selected surveillance path and perform the mission of monitoring the surveillance target.

[0154] According to the present invention described above, by receiving surveillance paths and status data of other robots in real time and selecting surveillance paths based on the same, overlapping surveillance ranges between robots can be prevented and surveillance efficiency can be maximized.

[0155] In addition, the present invention enables the robot to continuously optimize a path based on real-time status data of the target space, thereby enabling it to immediately respond to dynamic environmental changes, unlike existing fixed path monitoring methods.

[0156] Furthermore, the present invention can predict dynamically changing areas where a specific event is likely to spread when it occurs, thereby generating a path. This allows for proactive response to hazards such as fires and hazardous material spills before they spread to surrounding areas, enabling safe surveillance based on advance predictions.

[0157] Furthermore, the present invention allows the robot to reflect environmental changes in real time by re-evaluating its path at set intervals. This provides the ability to proactively respond to changing situations by quickly altering the path when the risk level in a specific area increases or a new obstacle is detected.

[0158] The various embodiments described herein may be implemented in a recording medium readable by a computer or similar device, for example, using software, hardware, or a combination thereof.

[0159] In terms of hardware implementation, the embodiments described herein can be implemented using at least one of ASICs (application specific integrated circuits), DSPs (digital signal processors), DSPDs (digital signal processing devices), PLDs (programmable logic devices), FPGAs (field programmable gate arrays), processors, controllers, micro-controllers, microprocessors, and other electrical units for performing functions. In some cases, the embodiments described herein can be implemented as a control module itself.

[0160] In a software implementation, the procedures and functions described herein, as well as other embodiments, may be implemented as separate software modules. Each of these software modules may perform one or more of the functions and operations described herein. The software code may be implemented as a software application written in a suitable programming language. The software code may be stored in a memory module and executed by a control module.

[0161] The above description is merely an example of the technical idea of ​​the present invention, and those skilled in the art will appreciate that various modifications, changes, and substitutions can be made without departing from the essential characteristics of the present invention.

[0162] Accordingly, the embodiments disclosed in the present invention and the accompanying drawings are intended to illustrate, rather than limit, the technical concept of the present invention, and the scope of the technical concept of the present invention is not limited by these embodiments and the accompanying drawings. The protection scope of the present invention should be interpreted by the following claims, and all technical concepts within the scope equivalent thereto should be interpreted as being included within the scope of the rights of the present invention.

Claims

1. In a method for creating a robot facility surveillance path, A step of generating at least one candidate surveillance path based on status data of a robot monitoring a target space; A step of selecting an optimal surveillance path among the candidate surveillance paths based on the status data and surveillance path of another robot monitoring the target space; and A method for generating a surveillance path, comprising: a step of performing surveillance work on the target space based on the surveillance path; 2. In paragraph 1, A method for generating a surveillance path, characterized in that the selecting step selects the surveillance path so that the surveillance ranges between each robot monitoring the target space do not overlap.

3. In paragraph 1, A method for generating a surveillance path, characterized in that the above status data includes at least one of battery level, sensor status, movement speed, and current location.

4. In paragraph 1, A method for generating a surveillance path, characterized in that the generating step generates the candidate surveillance paths by considering a surveillance priority area within a target space.

5. In paragraph 1, A method for generating a surveillance path, characterized in that the generating step generates candidate surveillance paths by considering a specific event when the specific event occurs within the target space.

6. In paragraph 5, A method for generating a surveillance path, characterized in that the generating step predicts a dynamic change area likely to be affected by the specific event, and generates candidate surveillance paths by considering the predicted dynamic change area.

7. In a robot that performs a method for generating a facility surveillance path, A robot comprising a control unit that generates at least one candidate surveillance path based on status data of a robot monitoring a target space, selects an optimal surveillance path among the candidate surveillance paths based on status data and surveillance paths of other robots monitoring the target space, and performs surveillance work of the target space based on the surveillance path.

8. In paragraph 7, A robot characterized in that the control unit selects the surveillance path so that the surveillance ranges between each robot monitoring the target space do not overlap.

9. In paragraph 7, A robot characterized in that the above status data includes at least one of battery level, sensor status, movement speed, and current location.

10. In paragraph 7, A robot characterized in that the control unit generates the candidate surveillance paths by considering the surveillance priority area within the target space.

11. In paragraph 7, A robot characterized in that the control unit generates candidate surveillance paths by considering a specific event when a specific event occurs within the target space.

12. In paragraph 11, A robot characterized in that the control unit predicts a dynamic change area that is likely to be affected by the specific event, and generates candidate surveillance paths by considering the predicted dynamic change area.

13. A computer-readable recording medium storing a program for performing a method for generating a surveillance path according to any one of paragraphs 1 to 6.

14. A program stored on a computer-readable recording medium including a program code for executing a method for generating a surveillance path according to any one of paragraphs 1 to 6.

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