KR20180044486A - Robot for generating 3d indoor map using autonomous driving and method for controlling the robot - Google Patents

Abstract

Disclosed are a robot for automatically generating a 3d indoor precise map using an autonomous driving technology and a method for controlling a robot. A mapping robot comprises: a sensor for sensing surrounding information for collecting internal environments of a target facility; a drive line for movement of the interior of the target facility; and a controller for generating a path plan for the indoor self-driving in the target facility of the mapping robot using the information sensed by the sensor, controlling the drive line depending on the generated path plan to move the mapping robot and collecting information for producing the indoor map of the target facility through the sensor in the course of the indoor self-driving.

Description

TECHNICAL FIELD [0001] The present invention relates to an automatic generation of a three-dimensional indoor precision map using a self-driving technique, and a control method of the robot.

The following explanation is about the control method of the robot and the robot that generates the 3D precision map automatically using the autonomous driving technology.

An autonomous mobile robot is a robot that looks for the optimal route to a destination by using wheels or legs while looking around itself and detecting obstacles. It is being developed and used for various fields such as autonomous vehicles, logistics, hotel service, and robot cleaner. Korean Patent Laid-Open No. 10-2005-0024840, for example, describes a route planning method for an autonomous mobile robot, in which a mobile robot autonomously moving at home or office can safely and quickly move to a target point while avoiding obstacles Lt; RTI ID = 0.0 > a < / RTI > optimal path.

1 is a diagram showing an example of a basic technique applied to a robot for indoor autonomous navigation in the prior art. 1 is a diagram illustrating mapping robots 110, localization 120, path planning 130, and obstacle avoidance 140, which are applied to the service robot 100 of the related art. And sensing (150).

The mapping 110 may include a technique for creating a peripheral map while the service robot 100 performs an autonomous running and / or a technique for importing and managing a map already prepared. For example, when the service robot 100 travels in an unknown environment, it is possible to precisely map the environment without external help by only the sensors attached to the robot, or to estimate the current position by matching the surrounding environment with the stored map , Technology such as SLAM (Simultaneous Localization And Mapping) or CML (Concurrent Mapping and Localization) can be utilized, and a technique such as SFM (Structure from motion) for converting two-dimensional data of a camera into three- And can be utilized for generation of a dimensional map.

The localization 120 may include a technique for the service robot 100 to recognize the surrounding environment and estimate its own location. For example, GPS (Global Positioning System) coordinates, sensing values of IMU (Inertial Measurement Unit), and SLAM described above can be utilized.

The path planning 130 may include a technique for setting a path for an autonomous running of the service robot 100. For example, a Rapidly-exploring Random Tree (RRT), an A star algorithm for finding a path, a D star algorithm, and a Dijkstra algorithm can be utilized.

The obstacle avoidance 140 may include a technique for avoiding an unplanned obstacle (for example, a person or an object) while the service robot 100 proceeds the autonomous travel according to the route set according to the route plan 130 have.

The sensing 150 may be implemented using various sensors included in the service robot 100 such as a camera, a lidar, an IMU, an ultrasonic sensor, a GPS module and the like and performs the mapping 110, the localization 120, (130) and obstacle avoidance (140).

The drive 160 may include a technique for actually moving the service robot 100 in accordance with the path plan 130 or by controlling the wheels, legs, etc. included in the service robot 100 for obstacle avoidance 140 have.

In this way, in the prior art, it is necessary to include various sensors for autonomous navigation of the service robot 100, process the information of these sensors, and obtain the mapping 110, localization 120, And obstacle avoidance 140 and at the same time should include components such as wheels or legs to handle the movement of the service robot 100 according to the processing results of the processor . In addition, the service robot 100 should further include specific components for providing services desired by the users of the service robot 100. For example, a cleaning robot should further include components for sucking and storing dust to suit individual characteristics, and a robot for logistics management should further include components for identifying and moving objects, and the like.

As described above, the indoor autonomous mobile robot has a problem that the manufacturing cost is very large because the robot must include various components requiring close connection.

The service provider generates an indoor map of the facilities of a user such as a large shopping mall, an airport, a hotel, and the like, communicates with the user's individual service robots through the cloud service, and generates localization and route plans for the individual service robots A control method for an indoor autonomous mobile robot which can reduce autonomous mobile robots based on result data provided by individual service robots by innovatively reducing the production cost of the service robots by processing based on indoor maps and providing the resultant data And a system.

When a plurality of service robots operate in one facility, a service plan for a plurality of service robots is controlled through the cloud service, so that a plurality of service robots share a target service more efficiently in one facility The present invention provides a control method and system for an indoor autonomous mobile robot that can be used for an indoor autonomous mobile robot.

In making indoors maps of users' facilities, it is not necessary to create indoors maps by controlling the observation equipment directly on the service provider side, but it is also possible to automatically create indoors maps including functions for indoor self-running and mapping functions The present invention also provides a system and a control method thereof for an indoor autonomous navigation mapping robot.

A mapping robot comprising: a sensor for sensing peripheral information for collecting an internal environment of a target facility; a drive line for movement inside the target facility; and information sensed by the sensor, The method includes generating a path plan for indoor self-running, controlling the drive line according to the generated path plan to move the mapping robot, and generating an indoor map of the target facility in the course of the indoor self- And a controller for collecting information via the sensor.

According to an aspect of the present invention, the mapping robot further includes a power supply unit for supplying power to the sensor, the drive line, and the controller using a battery pack.

According to another aspect, the sensor includes: a three-dimensional real-time rider measuring a distance to an object around the mapping robot; And a camera for photographing an image around the mapping robot, wherein the controller collects the output values of the three-dimensional real-time rider and the camera as information for manufacturing the indoor map.

According to another aspect of the present invention, the sensor further includes a localization sensor for detecting a near obstacle, and the controller controls the deira blade to move the mapping robot in accordance with the path plan for the indoor self- Wherein the obstacle avoiding process is performed based on the output value of the localization sensor.

According to another aspect of the present invention, the controller analyzes a distance between the image photographed by the camera and the distance measured through the 3D real-time rider to determine a shaded area obscured by an object, and calculates a position at which the shaded area can be photographed And updates the route plan for the indoor self-driving.

A method of controlling a mapping robot, the method comprising: sensing peripheral information from a mapping robot located inside a target facility through a sensor; Generating a path plan for the indoor self-running in the target facility of the mapping robot using the sensed peripheral information; Controlling movement of the mapping robot according to the generated path plan; Sensing peripheral information that is changed according to movement of the mapping robot through the sensor; Updating the route plan using the changed peripheral information; And recording surrounding information continuously sensed through the sensor as information for manufacturing an indoor map of the target facility.

There is provided a computer-readable recording medium having recorded thereon a program for causing a computer to execute the control method.

There is provided a computer program stored in a computer-readable recording medium for causing a computer to execute the control method described above in combination with a computer.

The service provider generates an indoor map of the facilities of a user such as a large shopping mall, an airport, a hotel, and the like, communicates with the user's individual service robots through the cloud service, and generates localization and route plans for the individual service robots By processing based on the indoor map and providing the resultant data, the individual service robots can process the autonomous travel based on the provided result data, and the production cost of the service robot can be innovatively reduced.

When a plurality of service robots operate in one facility, a service plan for a plurality of service robots is controlled through the cloud service, so that a plurality of service robots share a target service more efficiently in one facility can do.

In making indoors maps of users' facilities, it is not necessary to create indoors maps by controlling the observation equipment directly on the service provider side, but it is also possible to automatically create indoors maps including functions for indoor self-running and mapping functions have.

1 is a diagram showing an example of a technique applied to a robot for indoor autonomous navigation in the prior art.
2 is a diagram illustrating an example of an overall control system for indoor self-running of a robot according to an embodiment of the present invention.
3 is a block diagram illustrating an example of a schematic configuration of a mapping robot according to an embodiment of the present invention.
4 is a block diagram illustrating an example of a schematic configuration of a cloud system according to an embodiment of the present invention.
5 is a block diagram illustrating an example of a schematic configuration of a service robot according to an embodiment of the present invention.
6 is a block diagram for explaining an internal configuration of a physical server constituting a cloud system according to an embodiment of the present invention.
7 is a flowchart for explaining a control method in an embodiment of the present invention.
8 is a diagram illustrating an example of limiting the position of a service robot in an embodiment of the present invention.
9 is a flowchart illustrating an example of a process in which a cloud system controls a service provided by a service robot, according to an embodiment of the present invention.
10 to 13 are photographs showing an embodiment of a mapping robot according to an embodiment of the present invention.
14 to 18 are diagrams showing an internal configuration of an embodiment of a mapping robot according to an embodiment of the present invention.
19 is a diagram showing a configuration example of a mapping robot according to an embodiment of the present invention.
20 and 21 are views showing an example of the operation structure of a mapping robot according to an embodiment of the present invention.

Hereinafter, embodiments will be described in detail with reference to the accompanying drawings.

The overall control system for the indoor self-running of the robot according to the embodiments of the present invention includes a control system (hereinafter referred to as a 'mapping robot system') for collecting map data in a room of a facility A control system (hereinafter referred to as a "cloud system") for producing indoor maps of the facilities based on the map data, a cloud service for localization and route planning for self-running service robots operating in the facilities (Hereinafter, referred to as a " service robot system ") for providing a service targeted by the user of the facility through autonomous travel within the service robot.

2 is a diagram illustrating an example of an overall control system for indoor self-running of a robot according to an embodiment of the present invention. 2 shows the cloud system 210 and the mapping robot 220 on the service provider side, and the service robots 230 for users' facilities and the user side. First, the service provider can input the mapping robot 220 to create an indoor map of facilities of users. At this time, the service provider may generate an indoor map of various facilities such as a large-sized shopping mall, a hospital, an airport, a hotel, etc., or may generate an indoor map of facilities of a user requesting service through a separate contract have. For example, the service provider can generate the indoor map of the facility A by inputting the mapping robot 220 into the facility A at the request of the user of the facility A. The mapping robot 220 may include various sensors such as a 3D rider, a 360-degree camera, and an IMU (Inertial Measurement Unit) for autonomous navigation and guidance as an indoor autonomous mobile robot, The generated sensing data may be transmitted to the cloud system 210. At this time, the sensing data may be input to the cloud system 210 through the computer-readable recording medium in which the sensing data is stored after the self-running of the mapping robot 220 for generating the indoor map is completed, The mapping robot 220 may transmit the communication module to the cloud system 210 via the network. The sensing data generated by the mapping robot 220 may be transmitted to the cloud system 210 in real time from the mapping robot 220. After the mapping robot 220 completes the sensing of the facility, (Not shown).

The cloud system 210 can create an indoor map of the facility A based on the sensing data provided by the mapping robot 220 and communicate with the service robot 230 disposed in the facility A based on the created indoor map The service robot 230 can be controlled. For example, the cloud system 210 receives sensing data (for example, data for grasping the current position of the service robot 230) generated through the sensors included in the service robot 230, The service robot 230 processes the localization and path planning for the service robot 230 using the data and the indoor map of the facility A and outputs the resultant data (for example, route data that the service robot 230 should move in the autonomous traveling) To the robot 230. At this time, the service robot 230 can provide the desired service in the facility A while processing the autonomous running based on the result data provided by the cloud system 210. [

The mapping robot 220 can be used only when the facility A is changed for the first time only or when changes are made to the indoor map, or when the indoor map is changed at a time period (for example, one year) It works. Accordingly, since one mapping robot 220 can be used to produce an indoor map of a plurality of facilities in accordance with the number of facilities required to produce indoor maps and time scheduling, a large number of mapping robots are not required, Even if it is made using the equipment, it does not put a heavy burden on the service user side. On the other hand, when service robots operating individually for individual purposes are individually manufactured and used by users, service robots must be continuously operated in the corresponding one facility, and multiple services must be operated simultaneously in one facility . Therefore, there is a problem that it is difficult to use expensive equipment in terms of the user. Accordingly, in the embodiments of the present invention, the mapping robot 220 is put on the service provider side to produce an indoor map of the facility A, and the service robot 230 is controlled through the cloud system 210, ) May allow the targeted service to be processed within the facility without using expensive equipment.

For example, a lidar is a radar developed by using a laser beam having a property close to radio waves. It is an expensive sensor device mounted for autonomous driving. When utilizing such a rider, basically, two or more riders Of the vehicle. For example, assuming that a user uses 60 service robots for logistics management, more than 120 expensive riders are required in the prior art. On the other hand, in the embodiments of the present invention, when the cloud system 210 on the service provider side processes the localization and path planning required for the autonomous travel and provides the resultant data, the service robots are notified from the cloud system 210 It travels in accordance with the provided result data, so that it is possible to drive the vehicle indoors with only an inexpensive ultrasonic sensor and / or an inexpensive camera without expensive sensor equipment. The service robots according to the embodiments of the present invention substantially operate in accordance with the result data provided from the cloud system 210, and thus can travel indoors without a separate sensor for indoor self-running. However, inexpensive sensors such as low-cost ultrasonic sensors and / or low-cost cameras can be used for grasping the current position of the service robot 230 and avoiding obstacles of the service robot 230. Therefore, users can utilize service robots manufactured at low cost, and there are a large number of users who want to use service robots. Considering that each of these users can utilize a plurality of service robots, It is possible to reduce the manufacturing cost of the apparatus. For example, it is possible to handle the self-running of the service robot with the smartphone-level sensing capability alone.

The sensing data transmitted by the service robot 230 to the cloud system 210 may include information for defining the current position of the service robot 230 within the facility. The information for defining the position may include image information recognized by the low-cost camera. For example, the cloud system 210 can compare the received image information with the image of the indoor map to determine the position of the service robot 230. As another example, well known techniques may be utilized to identify existing indoor locations. For example, existing well-known technologies for identifying the indoor location by utilizing a Wi-Fi signal, a beacon recognized by the facility, a sound not recognized by a person, a Bluetooth fingerprint, etc., It will be understood by those skilled in the art that the present invention can be utilized for understanding the present invention. In addition, it is possible to grasp the approximate position of the service robot 230 through such existing technologies, and then grasp the exact position of the service robot 230 through image matching. In this case, it is not necessary to process the matching with the images corresponding to the entire indoor map, and the range of the image matching can be reduced through the roughly grasped position.

FIG. 3 is a block diagram for explaining an example of a schematic configuration of a mapping robot according to an embodiment of the present invention. FIG. 4 is a block diagram for explaining an example of a schematic configuration of a cloud system according to an embodiment of the present invention And FIG. 5 is a block diagram for explaining an example of a schematic configuration of a service robot according to an embodiment of the present invention.

3, the mapping robot may be a physical device, and may include a control unit 310, a driving unit 320, a sensor unit 330, and a communication unit 340, as shown in FIG.

3, the control unit 310 may include a path planning module 311, a mapping module 312, a drive control module 313, a local And a data processing module 315. The data processing module 315 may be a microprocessor, Here, the components included in the control unit 310 may be representations of different functions performed by the control unit 310 as a physical processor. For example, the control unit 310 may process various functions according to a control command according to a code of a computer program such as an OS or firmware.

The driving unit 320 may include physical equipment for flight of the mapping robot 220 in the form of a wheel or a bridge for moving the mapping robot 220, or a flying object such as a drones.

The sensor unit 330 may include various sensors for collecting information on the internal environment of the facility where the mapping robot 220 is located. For example, the sensor unit 330 may include sensors required among various sensors such as a lidar, a 360-degree camera, an IMU, an ultrasonic sensor, a GPS module, and a PDS (Position Sensitive Detector).

The communication unit 340 may include a communication function for transmitting the sensed data through the sensor unit 330 to the cloud system 210 through the network.

When the mapping robot 220 located inside the target facility is driven, the sensor unit 330 may generate first sensor data including output values of various sensors and transmit the generated first sensor data to the control unit 310. The data processing module 415 of the control unit 310 may transmit the received first sensor data to the localization processing module 314 for autonomous navigation of the mapping robot 220, The controller 310 may control the communication unit 340 to transmit the first sensor data to the cloud system 210 via the network so that an indoor map of the target facility can be generated.

The localization processing module 314 is a technique for the mapping robot 220 to recognize the surrounding environment and estimate its own position and can operate to determine the current position of the mapping robot 220 in the target facility . At this time, the localization processing module 314 processes the mapping between the indoor map (for example, the design blueprint of the target facility) and the current location of the pre-stored target facilities through interlocking with the mapping processing module 312, If there is no stored indoor map, the indoor map of the target facility can be generated.

At this time, the path planning processing module 311 can generate a path for the autonomous running of the mapping robot 220. In this case, the information about the path determined by the path planning processing module 311 can be transferred to the drive control module 313, and the drive control module 313 controls the drive robot 300 to move the mapping robot 220 according to the provided path. (320).

The mapping robot 220 can autonomously run the target facility while repeating the process of generating and transmitting the first sensing data, determining the autonomous travel route using the first sensing data, and moving according to the determined autonomous travel route, The first sensing data for the facilities can be continuously transmitted to the cloud system 210.

Referring to FIG. 4, the cloud system 210 may be implemented by linking one physical server device or two or more physical server devices. As shown in FIG. 4, the map generation module 410, Processing module 420, a path planning processing module 430, and a service operating module 440. The components of the cloud system 210 may be implemented in different ways by at least one processor included in the cloud system 210 in accordance with the operating system code or control instructions according to the code of the at least one computer program May be expressions of different functions.

The map generating module 410 generates an indoor map of the target facility using the first sensing data generated by the mapping robot 220 autonomously traveling within the target facility, as described in FIG. 3, with respect to the interior of the target facility Lt; / RTI >

At this time, the localization processing module 420 uses the second sensing data received through the network from the service robot 230 and the indoor map of the target facility generated through the map generation module 410, The position of the service robot 230 can be determined.

The path planning processing module 430 may generate a control signal for controlling the indoor autonomous travel of the service robot 230 using the second sensing data and the generated indoor map. For example, the path planning processing module 430 may generate path data of the service robot 230. The cloud system 210 may transmit the generated path data to the service robot 230 via the network. For example, the information for the path may include information indicating the current position of the service robot 230, information for mapping the current position and the indoor map, and path planning information.

The service operation module 440 may include a function for controlling the service provided by the service robot 230 in the target facility. For example, a service provider operating the cloud system 210 may provide an integrated development environment (IDE) for a cloud service provided by the cloud system 210 to a user or producer of the service robot 230. At this time, the user or producer of the service robot 230 can create software for controlling the service provided by the service robot 230 in the target facility through the IDE and register the software in the cloud system 210. In this case, the service operation module 440 can control the service provided by the service robot 230 using the registered software in association with the service robot 230. As a concrete example, it is assumed that the service robot 230 provides a service of delivering the goods requested by the customer to the guest room of the customer at the hotel. At this time, the cloud system 210 controls the indoor autonomous travel of the service robot 230 to control the service robot 230 to move to the guest room, and when it reaches the destination location, the cloud system 210 presses the bell of the room door, And transmit the related command to the service robot 230 so that the service robot 230 proceeds a series of services for delivering the desired object to the customer.

5, the service robot 230 may be a physical device and includes a control unit 510, a driving unit 520, a sensor unit 530, and a communication unit 540, as shown in FIG. 5 .

5, the control unit 510 may include a path planning module 511, a mapping module 512, a drive control module 513, a local Processing module 514, a data processing module 515, and a service processing module 516. The service processing module 516 may be, At this time, the path planning processing module 511, the mapping processing module 512, and the localization processing module 514 are executed in order to enable indoor autonomous travel even when communication with the cloud system 210 is not performed And may be selectively included in the control unit 510 according to the example.

The data processing module 515 may receive the second sensing data including the output value of the sensors of the sensor unit 530 and transmit the second sensing data to the cloud system 210 through the communication unit 540. As described above, the cloud system 210 can generate route data using the second sensing data and the indoor map of the target facility, and can transmit the generated route data to the service robot 230. In this case, the path data may be transmitted to the data processing module 515 through the communication unit 540. [

The drive control module 513 controls the drive unit 520 in accordance with the path data to transmit the path data to the interior of the service robot 230 Autonomous driving can be controlled.

The data processing module 515 transmits the second sensing data to the localization processing module 514 and the path planning processing module 511 and the path planning processing module 511. [ The path data may be generated through the mapping processing module 512 to directly process the indoor autonomous travel of the service robot 230. Unlike the mapping robot 220, the service robot 230 does not include an expensive sensing device. Therefore, the service robot 230 can process the indoor self-running using the output values of sensors such as a low-cost ultrasonic sensor and / have. However, if the service robot 230 has already processed indoor autonomous travel through communication with the cloud system 210, mapping data or the like included in the path data received from the cloud system 210 may be further utilized More accurate indoor autonomous travel can be achieved while using low-cost sensors.

The service processing module 516 may receive a command received through the cloud system 210 through the communication unit 540 or through the communication unit 540 and the data processing module 515. [ In this case, the driving unit 520 may further include equipment related to the service provided by the service robot 230, as well as equipment for moving the service robot 230. In the above-described hotel service, the driving unit 520 of the service robot 230 may further include a robot arm for pressing a bell of a door of a passenger compartment or a speaker for outputting a customer-facing voice. In this case, the service processing module 516 may transmit a drive command for the service to be provided to the drive control module 513, and the drive control module 513 may further include, A robot arm or a speaker can be controlled so that a service can be provided.

6 is a block diagram for explaining an internal configuration of a physical server constituting a cloud system according to an embodiment of the present invention. The cloud system 210 described above may be implemented as a single physical server device or may be implemented through interworking of two or more physical server devices. The server 600 configuring the cloud system 210 may include a memory 610, a processor 620, a communication module 630, and an input / output interface 640 as shown in FIG. The memory 610 may be a computer-readable recording medium and may include a permanent mass storage device such as a random access memory (RAM), a read only memory (ROM), and a disk drive. Here, the ROM and the non-decaying mass storage device may be separate from the memory 610 and included as a separate persistent storage device. The memory 610 may also store an operating system and at least one program code. These software components may be loaded from a computer readable recording medium separate from the memory 610. [ Such a computer-readable recording medium may include a computer-readable recording medium such as a floppy drive, a disk, a tape, a DVD / CD-ROM drive, and a memory card. In other embodiments, the software components may be loaded into the memory 610 via the communication module 630 rather than from a computer readable recording medium.

The processor 620 may be configured to process instructions of a computer program by performing basic arithmetic, logic, and I / O operations. The command may be provided to the processor 620 by the memory 610 or the communication module 630. [ For example, the processor 620 may be configured to execute instructions received in accordance with the program code loaded into the memory 610. The processor 620 may be included in at least one processor included in the cloud system 210 described with reference to FIG.

The communication module 630 may provide functionality for communicating with other physical devices via an actual computer network. For example, the communication module 630 may provide a function for the server 600 to communicate with and communicate with the mapping robot 220 or the service robot 230.

The input / output interface 640 may be a means for interfacing with the input / output device 650. For example, in the input / output device 650, the input device may include a device such as a keyboard or a mouse, and the output device may include a device such as a display or a speaker. 6, the input / output device 650 is illustrated as a separate device from the server 600. However, the server 600 may be implemented such that the input / output device 650 is included in the server 600 according to the embodiment.

Also, in other embodiments, the server 600 may include more components than the components of FIG. However, there is no need to clearly illustrate most prior art components. For example, the server 600 may be implemented to further include various components such as various physical buttons, touch panels, or optical output devices.

7 is a flowchart for explaining a control method in an embodiment of the present invention.

In operation S710, the mapping robot 220 may generate the first sensing data for the interior of the target facility through the sensor while autonomously running the interior of the target facility. For example, as described with reference to FIG. 3, the mapping robot 220 may transmit the first sensing data including the output values of the sensors to the data processing module 315 through the sensing unit 330. The mapping robot 220 may be a device operating on the service provider side providing cloud services for controlling the indoor self-running of the service robot 230 through the cloud system 210. [ In addition, the service robot 230 may be a device operating on the user side requesting the cloud service in association with the target facility.

In step S720, the mapping robot 220 may transmit the generated first sensing data. For example, as described with reference to FIG. 3, the data processing module 315 may transmit the first sensing data received from the sensing unit 330 to the cloud system 210 through the communication unit 340.

In step S730, the cloud system 210 may generate an indoor map of the target facility using the received first sensing data. For example, the cloud system 210 may receive the first sensing data from the mapping robot 220 through the communication module 630 described with reference to FIG. 6, and the map generation module 410 described with reference to FIG. 4 The indoor map of the target facility can be generated using the first sensing data received via the first sensing data. At this time, the indoor map can be generated as an image-based three-dimensional indoor map. As described above, the first sensing data may be transmitted to the cloud system collectively after the autonomous running of the mapping robot 220.

According to an embodiment, the cloud system 210 may generate an indoor map of the target facilities of each of a plurality of users. For example, mapping robots 220 may be input for each target facility to obtain first sensing data for each target facility, and an indoor map may be generated for each target facility. In this case, the cloud system 210 can be stored and managed by associating the indoor map generated for each target facility with at least one identifier of the user's identifier, the corresponding target facility identifier, and the identifier of the corresponding service robot of the user . When the indoor autonomous travel of one of the plurality of service robots of a plurality of users is controlled, the cloud system 210 can identify the indoor map for the service robot through the identifier associated with the indoor map, Indoor self-driving for the service robot can be controlled using the indoor map.

In step S740, the service robot 230 may generate second sensing data for the interior of the target facility through the sensor within the target facility. For example, as described with reference to FIG. 5, the service robot 230 may transmit the second sensing data including the output values of the sensors to the data processing module 515 through the sensing unit 530. While the mapping robot 220 uses expensive sensing devices such as a rider and a 360 degree camera as sensors, the service robot 230 uses low-cost sensing devices such as low-cost cameras and / or low-cost ultrasonic sensors as sensors So that the second sensing data can be generated. The cloud system 210 has already generated the indoor map of the target facility through the mapping robot 220 and thus can control the indoor autonomous travel of the service robot 230 by only mere image mapping. The cost of the service robot 230 operated by the users can be significantly lowered.

In step S750, the service robot 230 may transmit the generated second sensing data. 5, the data processing module 515 of the service robot 230 may transmit the second sensing data to the cloud system 210 through the communication unit 540. For example, as shown in FIG.

In step S760, the cloud system 210 may generate path data using the received second sensing data and the generated indoor map. The path data may include processed mapping data according to an indoor map of the target facility and path planning data in the cloud system 210 and location data determined for the service robot 230. The processed mapping data may be, for example, a portion of the indoor map associated with the location data and path planning data determined for the service robot 230 at the current time. As a more specific example, the mapping data may include the indoor map data corresponding to the position where the service robot 230 should move from the current position.

In step S770, the cloud system 210 may transmit the generated path data. For example, the cloud system 210 may route the path data generated by the path planning processing module 430 described with reference to FIG. 4 in cooperation with the localization processing module 420 and the map generation module 410, To the service robot 230 through the communication module 630 described above. Steps 760 and 770 for generating and transmitting the route data are a process for controlling the indoor self-running of the target facility of the service robot 230 using the second sensing data and the generated indoor map . As described above, when a plurality of users use the cloud service, the cloud system 210 generates an indoor map for each of a plurality of target facilities, generates an indoor map corresponding to the corresponding user's identifier, An indoor map associated with the service robot to control the indoor self-running can be identified by storing and managing the indoor map in association with at least one identifier of the identifier of the service robot of the corresponding user.

In addition, a plurality of service robots may exist in one target facility. In other words, a single user may operate multiple service robots. In this case, the cloud system 210 may receive the second sensing data from each of the plurality of service robots in step 760. In step 770, the cloud system 210 determines whether or not the service robot 210 is located on the basis of the compartment of the indoor map generated by using the positions of the plurality of service robots grasped through the second sensing data received from each of the plurality of service robots, According to the service provided by the target facility, it is possible to control the indoor self-running of each of the plurality of service robots. For example, a plurality of service robots can provide a logistics management service in a logistics warehouse. In this case, the areas (zones) for managing the distribution within the warehouse may be divided in advance by the plurality of service robots, and the cloud system 210 may classify the service robots The indoor self-running can be controlled. Depending on the service, there may be a possibility that the movement paths of a plurality of service robots are overlapped or each of a plurality of service robots moves all the divisions of the indoor map. To this end, the cloud system 210 may control the indoor self-running of each of a plurality of service robots according to a service provided by a plurality of service robots. For example, the cloud system 210 may calculate an optimal travel path for all of the plurality of service robots through the current location of the plurality of service robots. As another example, there may be service robots that provide different services at one target facility. In this way, when there are a plurality of service robots in one target facility, the cloud service 210 can calculate the optimal travel route considering the entirety of the plurality of service robots since the location of each of the plurality of service robots can be known It is possible.

In step 780, the service robot 230 may control the movement based on the received path data. For example, the service robot 230 may receive the path data through the communication unit 540 described with reference to FIG. 5 and transmit the path data to the data processing module 515. In this case, the data processing module 515 may transmit the path data to the drive control module 513 in a general case so that the drive control module 513 controls the drive unit 520 according to the path data. At this time, steps S740 to S780 may be repeated until the service robot 230 terminates its service.

8 is a diagram illustrating an example of limiting the position of a service robot in an embodiment of the present invention. 8 shows a simplified example of a two-dimensional indoor map 800 of a target facility. It is assumed that the solid line circle 810 indicates the position of the service robot 230 and the dotted lines 820 and 830 are the view angle of the low cost camera included in the service robot 230. At this time, the second sensing data including the image photographed through the low-cost camera may be transmitted from the service robot 230 to the cloud system 210. In this case, each time the cloud system 210 wants to check the position of the service robot 230, the cloud system 210 matches all the images collected corresponding to the two-dimensional indoor map 800 with the image included in the second sensing data Since the image must be matched until an image is found, a lot of operation costs may be incurred.

Accordingly, the first sensing data and the second sensing data received by the cloud system 210 according to the present embodiment include not only the internal image information of the target facility, but also a signal for identifying the specific zone And may further include information. For example, the mapping robot 220 and the service robot 230 may transmit a radio wave signal or a sound signal (e.g., a radio wave) generated by a Wi-Fi signal generated by access points (APs) installed in a target facility, And the signal information recognized by the signal sensing sensor is included in the first sensing data and the second sensing data, respectively, so that the cloud system 210, Lt; / RTI > At this time, Wi-Fi signals of different APs can be distinguished, and signal generators separately constructed can generate signal information that can be distinguished from each other.

In this case, since the location of the mapping robot 220 can be easily grasped by the cloud system 210, the zone corresponding to the signal information included in the first sensing data can be identified. In this case, the cloud system 210 can limit the area of the service robot 230 through the signal information included in the second sensing data, thereby reducing the computation cost for image matching.

For example, it is assumed that the dotted circles shown in FIG. 8 are each the recognizable range of signal information generated at the target facility. At this time, the service robot 230 located at the position of the solid line circle 810 transmits signal information corresponding to the first dotted circle 840 to the cloud system 210 by including the signal information in the second sensing data. In this case, the cloud system 210 can limit the computation cost for image matching by limiting only the images of the region transmitted by the mapping robot 220 including the same signal information as the first sensing data to the object of image matching do. Two or more different signal information may be included depending on the position of the mapping robot 220 or the service robot 230. In this case, however, the calculation cost may be reduced as compared with image matching with all images corresponding to the entire indoor map do.

9 is a flowchart illustrating an example of a process in which a cloud system controls a service provided by a service robot, according to an embodiment of the present invention. There is a need for the cloud system 210 to control the service of the service robot as described above. To this end, an integrated development environment (IDE) for a cloud service provided to control the indoor self-running of the service robot 230 through the cloud system 210 may be provided to the user or the manufacturer of the service robot 230. The IDE is an integrated development environment software application interface for efficiently developing software, and the cloud system 210 can be provided with a function for controlling the service of the service robot 230 through the IDE.

In step S910, the cloud system 210 may register software for controlling the service provided by the service robot 230 in the target facility through the IDE. This step S910 may be performed before the step S740 described with reference to FIG. In other words, the cloud system 210 can register the software in advance before communicating with the service robot 230 to control the indoor autonomous travel of the service robot 230. For example, the cloud system 210 can register software and manage software through the service operation module 440 described with reference to FIG.

In step S920, the cloud system 210 can use the registered software to control the service provided by the service robot 230 in the target facility. At this time, the cloud system 210 can transmit a service related command to the service robot 230 according to the program code of the registered software through the service operation module 440 described with reference to FIG. Thus, how the cloud system 210 controls the service of the service robot 230 may vary depending on the software registered in the cloud system 210. This step S920 may be performed after the service robot 230 reaches a position to provide the service through the indoor self-running of the service robot 230 through steps S740 to S780. For example, in the embodiment of the hotel, after the service robot 230 arrives at the desired room, the start of a service such as pressing a room door bell or outputting a customer service voice can be controlled through the cloud system 210 have. The service started through the cloud system 210 may be provided through the service processing module 516 of the service robot 230 described with reference to FIG. For example, the service robot 230 may provide a corresponding service according to a control command provided by the cloud system 210. [ To this end, the service processing module 516 may proceed with a processing procedure for providing a service suitable for the control command.

FIGS. 10 to 13 are photographs showing an embodiment of a mapping robot according to an embodiment of the present invention, and FIGS. 14 to 18 show an internal structure of an embodiment of a mapping robot according to an embodiment of the present invention admit.

An embodiment 1000 of the mapping robot 220 includes an upper sensor unit including a 360 degree camera 1010 and two riders 1020 and 1030 and a driving unit 1040 for processing movement of the mapping robot, And a control unit 1050 that processes the output value from the sensor unit and controls the driving unit 1040 so that the mapping robot 220 can autonomously travel. At this time, the output values from the sensor unit (for example, the images taken by the 360 degree camera 1010 and the output values of the two riders 1020 and 1030) are transmitted to the cloud system 210 as described above, So that the cloud system 210 can generate an indoor map of the self-running facility. As described above, the output value from the sensor unit may be transmitted to the cloud system 210 from the mapping robot 220 through the network in real time or at regular intervals. However, according to the embodiment, And may be input to the cloud system 210 through a separate recording medium after the inside of the facility is completely sensed.

The embodiment of the mapping robot 220 according to the present embodiment is intended to facilitate understanding of the explanation and the mapping robot according to the embodiments of the present invention is not limited to the forms of FIGS. 10 to 13. For example, the control unit 1050 may include an additional rider, or the driving unit 1040 may be implemented as a bridge type or a wheeled bridge type. More specifically, it is possible to consider a scenario in which a bridge-shaped mapping robot 220 with wheels is moved on a flat ground using wheels, and on a staircase or an escalator using a bridge.

The mapping robot 220 receives the basic layout such as the blueprint of the target facility, and generates the first sensing data for generating the three-dimensional indoor map while autonomously running the entire area according to the basic layout. In addition, the mapping robot 220 photographs the room of the facility at a position where the view is not blocked by the obstacle in order to eliminate the shade caused by obstacles such as pillars due to limitation of the view of the 360 degrees camera 1010 inside the facility And an algorithm capable of controlling the movement of the mapping robot 220 in order to allow the robot 220 to move.

19 is a diagram showing a configuration example of a mapping robot according to an embodiment of the present invention. 19 shows an embodiment in which the mapping robot 220 includes a controller 1910, a power management system 1920, a sensor 1930, and a drive line 1940.

The controller 1910 may correspond to the control unit 310 described with reference to FIG. 3 and may include a computing module 1911 and a communication module 1912 as shown in FIG.

The computing module 1911 may be implemented by one or more computers, such as a PC, and operations for autonomous navigation of the mapping robot 220 may be processed through such a computer. For example, the path planning processing module 311, the mapping processing module 312, the drive control module 313, the localization processing module 314, and the data processing module 315 described with reference to FIG. .

The communication module 1912 may include various modules for communicating with the outside such as an Ethernet switching hub, a USB hub, an LTE module, a wireless control receiver, a WiFi bridge, and the like. The communication module 1912 may include a module for communicating with a wireless mouse and a keyboard as an interface for the operator of the mapping robot 220 to control the mapping robot 220.

The PSM 1920 is a component for managing power of the mapping robot 220 and may include a battery pack 1921 and a power supply 1922.

The battery pack 1921 may be a power supply source of the mapping robot 220 that autonomously travels inside the facility.

The power supply 1922 may be a component for supplying a regulated power to the controller and the sensor and supplying the unregulated power to the drive line 1940, respectively.

The sensor 1930 may include a 3D lidar 1931 and a camera system 1932 and may include an LCLS (Low Cost Localization Sensor) for detecting a local obstacle for obstacle avoidance . For example, an ultrasonic sensor, an IMU, a PSD sensor, or the like may be further included in the sensor 1930.

The drive line 1940 may include wheels or legs for moving the mapping robot 220, and components for actually driving such wheels or legs. Basically, the drive line 1940 can operate under the control of the controller 1910. On the other hand, the mapping robot 220 needs to be operated under the control of the operator, not the controller 1910. For example, in a case where the indoor robot is not in the indoor self-running mode (for example, when the mapping robot 220 is to be moved to the facility) or when an error occurs during the indoor self-running, There may be a need to control the movement of the robot 220. To this end, the drive line 1940 may include a command module 1941 for communicating with an operator's terminal (e.g., a mobile device) to receive control commands from an operator. The drive line 1940 may also include a drive module 1942 that actually handles movement of the mapping robot 220, such as a motor, a drive shaft, and a wheel. As a specific example, the drive line 1940 in the embodiment 1000 of the mapping robot 220 described with reference to FIGS. 10 to 18 may include four drive module sets for four wheels operating independently. Such a set of four drive modules may be implemented as one master drive module and three slave drive modules.

At this time, the controller 1910 generates a path plan for the indoor self-running in the target facility of the mapping robot 230 using the information sensed by the sensor 1930, 1940 to move the mapping robot 220 and collect information for producing the indoor map of the target facility through the sensor 1930 in the course of the indoor autonomous travel. At this time, the controller 1910 can continuously collect surrounding information that is changed according to the movement of the mapping robot 220 through the sensor 1930, and continuously collects peripheral information, which is continuously collected and changed according to the movement of the mapping robot 220 Information can be used to continually update the route plan. When the path plan is changed, the controller 1910 can control the drive line 1940 so that the mapping robot 220 moves according to the changed path plan.

The controller 1910 also analyzes the distance measured through the image captured through the camera (camera system 1932) included in the sensor 1930 and the three-dimensional real-time rider (three-dimensional rider 1931) It is possible to determine a shaded area covered by the obstacle, and calculate a position at which the shaded area can be photographed, thereby updating the path plan for the indoor autonomous travel of the mapping robot 220. Accordingly, the mapping robot 220 acquires images and distance information of the entire interior of the target facility, and obtains a more accurate indoor map of the target facility.

The controller 1910 controls the drive line 1940 so that the mapping robot 220 moves according to the path plan for the indoor autonomous travel while a localization sensor (LCLS) ), ≪ / RTI > the obstacle avoidance can be handled.

20 and 21 are views showing an example of the operation structure of a mapping robot according to an embodiment of the present invention. FIG. 20 shows an example of function modules that the controller 1910 can include for processing autonomous running and mapping of the mapping robot 220, FIG. 21 shows an example of the operation structure of the mapping robot 220 through the function modules, Fig.

The interface module may include a Camera Wizard, a Velodyne Wizard, an IMU Wizard, a Control Wizard, and a Motor Wizard. The Camera Wizard can manage functions such as automatic camera connection, camera input / output management, and spherical projection. The Velodyne Wizard can be a function for managing 3D real-time riders and can handle the projection and colorization of 3D particles sensed through a 3D real-time rider. The IMU Wizard can handle connections with IMU sensors, gyro calibration, IMU sensor input / output management, and Euler angle filtering. The control wizard can correspond to the controller 1910 and can handle functions such as connection between the controller 1910 and other components, input / output management of the controller 1910, and input / output management of control packets. The motor wizard may correspond to the motor controller and may handle functions such as connection of the motor to other components (e.g., controller 1910), input / output management of the motor controller, speed filtering, and encoder filtering.

The Logging Module is an element for recording the operating state of the system of the mapping robot 220 and includes a cloud recording of three-dimensional particles, a spherical image logging, a SLAM Pose Logging, An odometry recording of the robot 220, and an output value recording of the IMU sensor.

The recognition module (Perception Module) is a module for recognizing the surrounding environment during autonomous navigation of the mapping robot 220, and includes a SLAM Wizard for processing rider scan matching, three-dimensional map generation, and three-dimensional postural localization And an Obstacle Wizard for obstacle avoidance. The obstacle wizard can handle functions such as update of the probability area, update of the height map, update of the traversability map, frontier update, and value map update.

An intelligence module may include an action FSM (Finite State Machine) and an action FSM. Behavior FSM can handle functions such as user override handling, target posture update, motion plan update, target posture and target rate update. In addition, the operation FSM can handle functions such as processing of kinematic problems such as forward and backward movement of the mapping robot 220 and processing of the wheel speed.

FIG. 21 shows an example of the operation structure of the mapping robot 220 through the interaction between the functional modules of FIG.

As described above, according to the embodiments of the present invention, it is possible for a service provider to generate an indoor map of facilities of a user such as a large shopping mall, an airport, and a hotel in advance and communicate with individual service robots of users through a cloud service, By processing the localization and route plan based on the generated indoor map and providing the resultant data, the individual service robot can process the autonomous travel based on the provided result data, thereby reducing the production cost of the service robot . Further, when a plurality of service robots operate in one facility, a service plan for a plurality of service robots is controlled through the cloud service, so that a plurality of service robots share a target service more efficiently in one facility . In addition, in producing the indoor map of the facilities of the users, the service provider does not create the indoor map by controlling the observation equipment directly, but the indoor map including the functions for the indoor self-driving and the mapping function is automatically provided. Can be produced.

The system or apparatus described above may be implemented as a hardware component, a software component or a combination of hardware components and software components. For example, the apparatus and components described in the embodiments may be implemented within a computer system, such as, for example, a processor, a controller, an arithmetic logic unit (ALU), a digital signal processor, a microcomputer, a field programmable gate array (FPGA) , A programmable logic unit (PLU), a microprocessor, or any other device capable of executing and responding to instructions. The processing device may execute an operating system (OS) and one or more software applications running on the operating system. The processing device may also access, store, manipulate, process, and generate data in response to execution of the software. For ease of understanding, the processing apparatus may be described as being used singly, but those skilled in the art will recognize that the processing apparatus may have a plurality of processing elements and / As shown in FIG. For example, the processing unit may comprise a plurality of processors or one processor and one controller. Other processing configurations are also possible, such as a parallel processor.

The software may include a computer program, code, instructions, or a combination of one or more of the foregoing, and may be configured to configure the processing device to operate as desired or to process it collectively or collectively Device can be commanded. The software and / or data may be in the form of any type of machine, component, physical device, virtual equipment, computer storage media, or device , Or may be embodyed temporarily. The software may be distributed over a networked computer system and stored or executed in a distributed manner. The software and data may be stored on one or more computer readable recording media.

The method according to an embodiment may be implemented in the form of a program command that can be executed through various computer means and recorded in a computer-readable medium. The computer-readable medium may include program instructions, data files, data structures, and the like, alone or in combination. The program instructions to be recorded on the medium may be those specially designed and configured for the embodiments or may be available to those skilled in the art of computer software. Examples of computer-readable media include magnetic media such as hard disks, floppy disks, and magnetic tape; optical media such as CD-ROMs and DVDs; magnetic media such as floppy disks; Magneto-optical media, and hardware devices specifically configured to store and execute program instructions such as ROM, RAM, flash memory, and the like. Examples of program instructions include machine language code such as those produced by a compiler, as well as high-level language code that can be executed by a computer using an interpreter or the like.

While the present invention has been particularly shown and described with reference to exemplary embodiments thereof, it is to be understood that the invention is not limited to the disclosed exemplary embodiments. For example, it is to be understood that the techniques described may be performed in a different order than the described methods, and / or that components of the described systems, structures, devices, circuits, Lt; / RTI > or equivalents, even if it is replaced or replaced.

Therefore, other implementations, other embodiments, and equivalents to the claims are also within the scope of the following claims.

Claims (10)

In the mapping robot,
A sensor that senses ambient information for acquisition of the internal environment of the target facility;
A drive line for movement of the interior of the target facility; And
Generating a path plan for indoor self-running in the target facility of the mapping robot using information sensed by the sensor, controlling the drive line according to the generated path plan to move the mapping robot, A controller for collecting, through the sensor, information for producing an indoor map of the target facility in the course of the indoor self-
And a mapping robot for mapping the robot to the robot. The method according to claim 1,
A power supply for supplying power to the sensor, the drive line and the controller using a battery pack
Further comprising: a mapping processor for mapping the robot to the mapping robot. The method according to claim 1,
The sensor includes:
A three-dimensional real time rider measuring a distance to an object around the mapping robot; And
A camera for photographing an image around the mapping robot,
Lt; / RTI >
Wherein the controller collects the output values of the three-dimensional real-time rider and the camera as information for producing the indoor map. The method of claim 3,
The sensor includes:
Localization sensor for detecting near obstacles
Further comprising:
Wherein the controller controls the deira brine to move the mapping robot according to the path plan for the indoor self-running, and processes the obstacle avoidance based on the output value of the localization sensor. The method of claim 3,
The controller analyzes a distance between the image photographed by the camera and the distance measured through the 3D real-time rider to determine a shaded area covered by an object, calculates a position at which the shaded area can be photographed, And updates the path plan for the mapping robot. A method of controlling a mapping robot,
Sensing a surrounding information through a sensor in a mapping robot located inside the target facility;
Generating a path plan for the indoor self-running in the target facility of the mapping robot using the sensed peripheral information;
Controlling movement of the mapping robot according to the generated path plan;
Sensing peripheral information that is changed according to movement of the mapping robot through the sensor;
Updating the route plan using the changed peripheral information; And
Recording surrounding information continuously sensed through the sensor as information for producing an indoor map of the target facility
The control method comprising the steps of: The method according to claim 6,
Wherein the sensor comprises: a three-dimensional real-time rider measuring a distance to an object around the mapping robot; And a camera for photographing an image around the mapping robot,
Wherein the recording step comprises:
Wherein the 3D real time rider and the camera output values are collected as information for producing the indoor map. 8. The method of claim 7,
The sensor further includes a localization sensor for detecting a near obstacle,
The step of controlling the movement of the mapping robot includes:
Wherein the controller controls the mapping robot to move according to the path plan for the indoor self-running, and processes the obstacle avoidance based on the output value of the localization sensor. 8. The method of claim 7,
The step of updating the path plan comprises:
A controller for determining a shadow area obscured by an object by analyzing an image photographed by the camera and a distance measured through the three-dimensional real-time rider, calculating a position at which the shaded area can be photographed, Is updated. A computer-readable recording medium storing a program for causing a computer to execute the method according to any one of claims 6 to 9.

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