WO2024101589A1

WO2024101589A1 - Method and system for controlling traveling of mobile robot by using lidar sensor

Info

Publication number: WO2024101589A1
Application number: PCT/KR2023/011097
Authority: WO
Inventors: 김세헌; 황은민
Original assignee: 주식회사 클로봇
Priority date: 2022-11-10
Filing date: 2023-07-31
Publication date: 2024-05-16
Also published as: KR20240068158A

Abstract

The present disclosure relates to a method and a system for controlling the traveling of a mobile robot by using a LiDAR sensor. The method of the present disclosure comprises the steps of: setting, on the basis of departure information, destination information and map information that includes static obstacles, a traveling path on which a mobile robot is to move; recognizing, to be any one of a static region and a dynamic region, a region in which the mobile robot is to travel on the traveling path according to whether there is at least one dynamic obstacle that can be detected through a LiDAR sensor; and controlling the traveling of the mobile robot on the basis of the traveling path, the type of the recognized region, and distance information between the traveling path and an obstacle, acquired through the LiDAR sensor.

Description

Method and system for controlling the driving of a mobile robot using a lidar sensor

This disclosure relates to electronic devices. More specifically, the present disclosure relates to a method and system for controlling the driving of a mobile robot using a lidar sensor.

Recently, service robots can be easily seen in various places such as hotels, shopping malls, and public institutions. These service robots can refer to professional service robots used in companies and public places, general home service robots, and personal service robots.

The global service robot market size in 2019 was $9.46 billion, an increase of 14.1% from the previous year. Over the past five years, the service robot market has recorded an average annual growth rate of 21.9% and is expected to grow to $4 billion by 2021.

In particular, service robots are mostly self-driving robots and are widely used in indoor spaces as housekeeping, greeting guests, and educational robots.

Indoor spaces have many obstacles that limit the movement of self-driving robots, such as walls, pillars, chairs, desks, bookshelves, and multi-function printers. On the other hand, there are non-avoidable objects in indoor spaces that are not damaged even if they are hit by a self-driving robot.

However, self-driving robots that mostly drive indoors recognize non-avoidable objects as obstacles and avoid them when driving, which reduces the efficiency of autonomous driving.

Therefore, a method is needed to increase the accuracy and efficiency of automatic driving by independently determining non-avoidable objects indoors.

The purpose of the embodiments disclosed in this disclosure is to appropriately control the running of a mobile robot.

The problems to be solved by the present disclosure are not limited to the problems mentioned above, and other problems not mentioned can be clearly understood by those skilled in the art from the description below.

The system according to the present disclosure for achieving the above-described technical problem includes a lidar sensor, a memory for storing map information including static obstacles, starting point information, and destination point information, a behavior unit for performing behavior, and a memory. A mobile robot including a processor that controls the moving part based on information stored in While moving along the driving path, the area where the mobile robot will drive on the driving path is recognized as either a static area or a dynamic area depending on the presence of at least one dynamic obstacle detectable through a lidar sensor, and the driving path recognition The driving of the mobile robot is controlled based on the type of area and the distance information between the driving path and obstacles obtained through the LiDAR sensor.

In addition, the method of controlling a mobile robot according to the present disclosure for achieving the above-described technical problem sets a driving path for the mobile robot to move based on map information including static obstacles, starting point information, and destination point information. Step: While the mobile robot moves along the driving path, the area in which the mobile robot will drive is selected among the static area and the dynamic area on the driving path depending on the presence of at least one dynamic obstacle detectable through a LiDAR sensor. Recognizing it as one, and controlling the driving of the mobile robot based on the driving path, the type of recognized area, and the distance information between the driving path and obstacles obtained through the LiDAR sensor.

In addition to this, a computer program stored in a computer-readable recording medium for implementing the present disclosure may be further provided.

In addition, a computer-readable recording medium recording a computer program for implementing the present disclosure may be further provided.

According to the above-described problem solving means of the present disclosure, the present disclosure provides the effect of appropriately controlling the running of a mobile robot.

The effects of the present disclosure are not limited to the effects mentioned above, and other effects not mentioned may be clearly understood by those skilled in the art from the description below.

1 is a block diagram for explaining a system according to example embodiments of the present disclosure.

Figure 2 is a block diagram for explaining a mobile robot according to example embodiments of the present disclosure.

FIG. 3 is a flowchart illustrating a method of controlling a mobile robot according to example embodiments of the present disclosure.

FIG. 4 is a flowchart illustrating a method of setting a driving route according to exemplary embodiments of the present disclosure.

FIG. 5 is a diagram for conceptually explaining the flowchart shown in FIG. 4.

FIG. 6 is a flowchart illustrating a method of controlling the movement of a mobile robot in a dynamic region according to example embodiments of the present disclosure.

FIG. 7 is a diagram for conceptually explaining the flowchart shown in FIG. 6.

FIG. 8 is a flowchart illustrating in detail a method of controlling the behavior of a mobile robot in a temporarily narrow area due to a dynamically determined dynamic obstacle according to example embodiments of the present disclosure.

FIG. 9 is a diagram for conceptually explaining the flowchart shown in FIG. 8.

FIG. 10 is a flowchart illustrating a method of controlling the driving of a mobile robot in a static area according to example embodiments of the present disclosure.

FIG. 11 is a diagram for conceptually explaining the flowchart shown in FIG. 10.

Like reference numerals refer to like elements throughout this disclosure. This disclosure does not describe all elements of the embodiments, and general content or overlapping content between embodiments in the technical field to which this disclosure pertains is omitted. The term 'part, module, member, block' used in the specification may be implemented as software or hardware, and depending on the embodiment, a plurality of 'part, module, member, block' may be implemented as a single component, or It is also possible for one 'part, module, member, or block' to include multiple components.

Throughout the specification, when a part is said to be “connected” to another part, this includes not only direct connection but also indirect connection, and indirect connection includes connection through a wireless communication network. do.

Additionally, when a part "includes" a certain component, this means that it may further include other components rather than excluding other components, unless specifically stated to the contrary.

Throughout the specification, when a member is said to be located “on” another member, this includes not only cases where a member is in contact with another member, but also cases where another member exists between the two members.

Terms such as first and second are used to distinguish one component from another component, and the components are not limited by the above-mentioned terms.

Singular expressions include plural expressions unless the context clearly makes an exception.

The identification code for each step is used for convenience of explanation. The identification code does not explain the order of each step, and each step may be performed differently from the specified order unless a specific order is clearly stated in the context. there is.

Hereinafter, the operating principle and embodiments of the present disclosure will be described with reference to the attached drawings.

In this specification, the 'system according to the present disclosure' includes all various devices that can perform computational processing and provide results to the user. For example, the 'system according to the present disclosure' may include all of a computer, a server device, and a portable terminal, or may be in any one form.

Here, the computer may include, for example, a laptop equipped with a web browser, a desktop, a laptop, a tablet PC, a slate PC, etc.

A server device is a server that processes information by communicating with external devices and may include an application server, computing server, database server, file server, game server, mail server, proxy server, and web server.

Portable terminals are, for example, wireless communication devices that ensure portability and mobility, such as PCS (Personal Communication System), GSM (Global System for Mobile communications), PDC (Personal Digital Cellular), PHS (Personal Handyphone System), and PDA ( Personal Digital Assistant), IMT (International Mobile Telecommunication)-2000, CDMA (Code Division Multiple Access)-2000, W-CDMA (W-Code Division Multiple Access), WiBro (Wireless Broadband Internet) terminal, smart phone All types of handheld wireless communication devices, such as watches, rings, bracelets, anklets, necklaces, glasses, contact lenses, or head-mounted-device (HMD), etc. It can be included.

Referring to FIG. 1 , the system 10 may include a plurality of LiDAR sensors 100 and a mobile robot 200.

The plurality of LiDAR sensors 100 are sensors that measure the position coordinates of a reflector by emitting millions of laser pulses per second and measuring the time it takes for them to reflect and return from an object.

The driving method of the plurality of LIDAR sensors 100 may include, for example, a scanning scanner or a scintillation scanner. The main scanner is a method of measuring the distance between the LiDAR sensor and surrounding objects by measuring the time it takes for the laser pulse from the LiDAR sensor to reflect from the subject and return to the LiDAR sensor. Channel units can be divided depending on how much can be divided and scanned during one rotation. The laser emitting unit of the LiDAR sensor, which operates as a scanning scanner, can emit a laser beam split as much as the LiDAR channel. The higher the number of channels, the wider the vertical range that can be scanned per rotation, so more detailed measurements can be obtained with high precision. A scintillation scanner may consist of a pulsed laser, a precisely calibrated lens, and a high-performance image sensor. The beam fired by a specific lens called a beam splitter is divided into thousands of branches and fired, and when the beam reflected by the object is received by the photomultiplier tube (PMT) and CCD (Charge Coupled Device) respectively, the returned light is sent to the PMT. The lidar sensor calculates when the reception time of the beam arrived, and the lidar sensor calculates when the specific beam arrived using the image with the pattern reflected on the CCD, so a specific area can be scanned as a whole at once. Scintillation scanners can have the advantage of very high sampling rates.

In some embodiments, the plurality of LiDAR sensors 100 may be implemented as two-dimensional (2D) LiDAR sensors.

A plurality of LIDAR sensors 100 may communicate with the mobile robot 200. The plurality of LIDAR sensors 100 may provide various sensed information to the mobile robot 200.

The mobile robot 200 may be an object that can move freely using a moving member. For example, the mobile robot 200 may include wheels. However, it is not limited to this, and for another example, the mobile robot 200 may operate as a caterpillar or may be applied to a drone, ship, or automobile that operates as a propeller.

The mobile robot 200 can travel in various directions. The mobile robot 200 may move in a straight line and/or rotate. Here, straight movement may include forward movement or backward movement. Rotational movement may include, for example, left-turning movement or right-turning movement.

The mobile robot 200 may provide various sensed information to the mobile robot 200 through the plurality of LIDAR sensors 100.

Referring to FIG. 2, the mobile robot 200 includes a communication unit 210, a processor 220, a memory 230, a display 240, a user input unit 250, a behavior unit 260, and an interface unit 270. may include.

The communication unit 210 may include one or more components that enable communication with an external device, and may include, for example, at least one of a wireless communication module, a short-range communication module, and a location information module.

In addition to Wi-Fi modules and WiBro (Wireless broadband) modules, wireless communication modules include GSM (global System for Mobile Communication), CDMA (Code Division Multiple Access), WCDMA (Wideband Code Division Multiple Access), and UMTS (universal mobile telecommunications system). ), TDMA (Time Division Multiple Access), LTE (Long Term Evolution), 4G, 5G, 6G, etc. may include a wireless communication module that supports various wireless communication methods.

The wireless communication module may include a wireless communication interface including an antenna and a transmitter that transmits a transmission signal. Additionally, the wireless communication module may further include a transmission signal conversion module that modulates a digital control signal into an analog wireless signal through a wireless communication interface.

The wireless communication module may include a wireless communication interface including an antenna and a receiver for receiving received signals. Additionally, the wireless communication module may further include a reception signal conversion module for demodulating an analog wireless signal received through a wireless communication interface into a digital control signal.

The short-range communication module is for short-range communication and includes Bluetooth™, RFID (Radio Frequency Identification), Infrared Data Association (IrDA), UWB (Ultra Wideband), ZigBee, and NFC (Near Field). Communication), Wi-Fi (Wireless-Fidelity), Wi-Fi Direct, and Wireless USB (Wireless Universal Serial Bus) technology can be used to support short-distance communication.

The location information module is a module for acquiring the location (or current location) of the mobile robot 200 according to the present disclosure, and representative examples thereof include a Global Positioning System (GPS) module or a Wireless Fidelity (WiFi) module. For example, by using a GPS module, the location of the mobile robot 200 can be acquired using signals sent from GPS satellites. As another example, by using a Wi-Fi module, the location of the mobile robot 200 can be obtained based on information from the Wi-Fi module and a wireless AP (Wireless Access Point) that transmits or receives wireless signals. If necessary, the location information module may replace or additionally perform any of the functions of other modules of the communication unit to obtain data regarding the location of the mobile robot 200. The location information module is a module used to obtain the location (or current location) of the mobile robot 200, and is not limited to a module that directly calculates or obtains the location of the mobile robot 200.

The processor 220 may perform an algorithm for controlling the operations of components within the mobile robot 200. The processor 220 can control the memory 230 that stores data for a program that reproduces the algorithm. The processor 220 may perform the above-described operations using data stored in the memory 230. At this time, the memory 230 and the processor 220 may each be implemented as separate chips. Alternatively, the memory 230 and processor 220 may be implemented as a single chip. In addition, the processor 220 can control any one or a combination of the above-described components in order to implement various embodiments according to the present disclosure described in FIGS. 3 to 11 below on the mobile robot 200. You can.

The processor 220 may control the action unit 260 based on information stored in the memory 230. The processor 220 may set a driving path for the mobile robot 200 to move based on map information, departure point information, and destination point information. And, while the mobile robot 200 moves along the driving path, the processor 220 uses a LiDAR sensor (for example, at least one of the plurality of LiDAR sensors 100 shown in FIG. 1). Depending on the presence or absence of at least one dynamic obstacle that can be detected, the area in which the mobile robot 200 will travel on the travel path may be recognized as either a static area or a dynamic area. Specifically, the processor 220 can dynamically determine the nature of the area in which the mobile robot 200 will drive while the mobile robot 200 is traveling, and can determine the nature of the area in which the mobile robot 200 will drive, and can determine the nature of the area in which the mobile robot 200 will drive, and can dynamically determine the nature of the area in which the mobile robot 200 will drive. It can be recognized as an area (dynamically narrow area), a constant narrow area caused by obstacles on the map (statically narrow area), or a wide area. The processor 220 may control the driving of the mobile robot through the moving unit 260 based on the driving path, the type of recognized area, and the distance information between the driving path and obstacles obtained through the LiDAR sensor.

The memory 230 can store data and programs that support various functions of the mobile robot 200, and can store input/output data (e.g., music files, still images, videos, etc.), and can store data and programs that support various functions of the mobile robot 200. A plurality of application programs (application programs or applications) running in 200, data for operation of the mobile robot 200, and commands may be stored. At least some of these applications may be downloaded from an external server via wireless communication.

The memory 230 may be a flash memory type, a hard disk type, a solid state disk type, an SDD type (Silicon Disk Drive type), or a multimedia card micro type. micro type), card-type memory (e.g. SD or XD memory, etc.), random access memory (RAM), static random access memory (SRAM), read-only memory (ROM), EEPROM (electrically erasable) It may include at least one type of storage medium among programmable read-only memory (PROM), programmable read-only memory (PROM), magnetic memory, magnetic disk, and optical disk. Additionally, the memory 230 is separate from the mobile robot 200, but may be a database connected wired or wirelessly.

The memory 230 may store map information, departure point information, and arrival point information. Map information may include information about the surrounding area where the mobile robot 200 will drive. There may be static obstacles around the mobile robot 200 that do not move. Accordingly, map information may include information about static obstacles. The starting point information may be information indicating the starting point of the mobile robot 200. The arrival point information may be information indicating the arrival point of the mobile robot 200.

The display unit 240 can implement a touch screen by forming a layered structure or being integrated with the touch sensor. This touch screen can function as a user input unit that provides an input interface between the mobile robot 200 and the user, and at the same time, can provide an output interface between the mobile robot 200 and the user.

The display unit 240 displays (outputs) information processed by the mobile robot 200. For example, the display unit 240 displays execution screen information of an application program (for example, an application) running on the mobile robot 200, or a UI (User Interface) or GUI (Graphic User Interface) according to this execution screen information. Information can be displayed.

The user input unit 250 is for receiving information from the user, and information can be input through the user input unit 250. This user input unit 250 is a hardware-type physical key (e.g., a button, dome switch, jog wheel, jog switch, etc. located on at least one of the front, rear, and side of the mobile robot 200). and software touch keys. As an example, the touch key consists of a virtual key, soft key, or visual key displayed on the touch screen type display unit 240 through software processing, or It may consist of a touch key placed in a part other than the touch screen. On the other hand, virtual keys or visual keys can be displayed on the touch screen in various forms, for example, graphics, text, icons, videos, or these. It can be done in combination.

The moving unit 260 may be a physical component that performs the movements of the mobile robot 200. For example, the moving unit 260 may include wheels for driving the mobile robot 200.

The interface unit 270 serves as a passageway for various types of external devices connected to the mobile robot 200. This interface unit 270 includes a device equipped with a wired/wireless headset port, an external charger port, a wired/wireless data port, a memory card port, and an identification module (SIM). It may include at least one of a connection port, an audio input/output (I/O) port, a video input/output (I/O) port, and an earphone port. The mobile robot 200 can perform appropriate control related to external devices connected to the interface unit 270.

Although not shown, the mobile robot 200 may further include at least one camera. The camera processes image frames, such as still images or moving images, obtained by the image sensor in shooting mode. The processed image frame may be displayed on the display unit 240 or stored in memory. On the other hand, when there are multiple cameras, they can be arranged to form a matrix structure. In this way, a plurality of image information with various angles or focuses can be input through the cameras forming the matrix structure, and the cameras can produce three-dimensional stereoscopic images. It may be arranged in a stereo structure to obtain left and right images to implement.

Although not shown, the mobile robot 200 may further include at least one sensing unit. The sensing unit senses at least one of the internal information of the mobile robot 200, the surrounding environment information surrounding the mobile robot 200, and the user information, and generates a sensing signal corresponding thereto. The sensing unit includes a proximity sensor, illumination sensor, touch sensor, acceleration sensor, magnetic sensor, G-sensor, and gyroscope sensor. sensor, motion sensor, RGB sensor, infrared sensor, fingerprint scan sensor, ultrasonic sensor, optical sensor (e.g. camera) ), microphone, environmental sensor (e.g., including at least one of a barometer, hygrometer, thermometer, radiation detection sensor, heat detection sensor, gas detection sensor), chemical sensor (e.g., healthcare sensor, biometric sensor etc.) may include at least one of the following. Meanwhile, the mobile robot 200 can utilize information sensed by at least two of these sensors by combining them.

According to the above, there may be an advantage in appropriately controlling the travel of the mobile robot 200 by determining the nature of the travel area by recognizing whether a dynamic obstacle exists in the surrounding area of the mobile robot 200.

Referring to FIG. 3, a method of controlling a mobile robot may be performed by the processor 220 shown in FIG. 2.

A step of setting a driving route based on map information, departure point information, and arrival point information is performed (S100). Specifically, the processor 220 may set a driving path for the mobile robot 200 to move based on map information including static obstacles, departure point information, and destination point information.

A step of recognizing the area in which the mobile robot 200 will travel on the travel path is performed depending on the presence or absence of a dynamic obstacle (S200). For example, while the mobile robot 200 moves along the travel path, the processor 220 controls the mobile robot 200 on the travel path according to the presence or absence of at least one dynamic obstacle detectable through a lidar sensor. The driving area can be recognized as either a static area or a dynamic area. Specifically, for example, the processor 220 determines the nature of the area in which the mobile robot 200 will drive on the driving path, whether it is a temporary narrow area (dynamically narrow area) caused by dynamic obstacles that are not in the map, or the nature of the area in which the mobile robot 200 will drive. It can be recognized as either a narrow area (statically narrow area) with a constant character caused by existing obstacles, or a wide area.

In some embodiments, in step S200, the processor 220 determines the nature of the area in which the mobile robot 200 will drive on the travel path as a dynamic area in response to at least one dynamic obstacle being recognized by the LiDAR sensor. It can be recognized. Embodiments for this will be described later with reference to FIGS. 6 to 9.

In some embodiments, in step S200, the processor 220 may recognize the area in which the mobile robot will drive on the travel path as a static area in response to only static obstacles being recognized by the LiDAR sensor. Embodiments of this will be described later with reference to FIGS. 10 and 11 .

A step of controlling the driving of the mobile robot 200 is performed based on the driving path, the type of recognized area, and distance information (S300). Specifically, the processor 220 controls the driving path, the type of recognized area, and And based on the distance information, the driving of the mobile robot 200 may be controlled. Here, the distance information may be information indicating the distance between the driving path and the obstacle obtained through the LiDAR sensor.

Referring to FIG. 4, the method of setting the driving route shown in FIG. 4 may be an embodiment in which step S100 shown in FIG. 3 is embodied.

A step of generating a plurality of simulation paths is performed (S110). Specifically, the processor 220 may generate a plurality of simulation paths on which the mobile robot 200 can travel from a departure point according to the departure point information to an arrival point according to the arrival point information on a map according to the map information.

A step of setting a simulation path selected among a plurality of simulation paths as a driving path is performed (S120). Specifically, the processor 220 may set a simulation path selected according to a preset selection criterion among a plurality of simulation paths as a driving path. At this time, the selection criterion may be, for example, selecting the shortest distance between the departure point and the destination point. However, it is not limited to this.

FIG. 5 is a diagram for conceptually explaining the flowchart shown in FIG. 4.

Referring to FIG. 5 , the system 10 may include a plurality of LIDAR sensors 100 and a mobile robot 200, as described above with reference to FIG. 1 . System 10 may travel in a first direction D1 and/or a second direction D2.

Map information according to example embodiments of the present disclosure may include static obstacles SO1 and SOP2.

The system 10 can recognize the departure point (SP) from departure point information and the arrival point (GP) from arrival point information. Additionally, the system 10 may generate a plurality of simulation paths (SP1 to SP5) between the starting point (SP) and the destination point (GP). In FIG. 5, the number of simulation paths is shown as 5, but this is only for explaining example embodiments of the present disclosure and is not limited to what is shown in FIG. 5.

The system 10 may set a simulation path (eg, SP3) selected according to a preset selection criterion among the plurality of simulation paths (SP1 to SP5) as the driving path (DP).

The system 10 can start from a starting point (SP), drive on a driving path (DP), and move towards a destination point (GP).

Referring to FIG. 6, the embodiments shown in FIG. 6 may be a specific method of step S300 that can be performed when at least one dynamic obstacle is recognized by the LiDAR sensor. Specifically, in step S200 shown in FIG. 3, when the processor 220 recognizes the area on the travel path in which the mobile robot 200 will drive as a dynamic area, step S300 is specifically performed as in the method shown in FIG. 6. It can be.

A step is performed to obtain information on the shortest distance between the driving path and obstacles using a LiDAR sensor (S310). Specifically, each of the plurality of LIDAR sensors 100 may measure the shortest distance between the traveling path of the mobile robot 200 and the obstacle for each obstacle. Additionally, each of the plurality of LIDAR sensors 100 may provide shortest distance information indicating the shortest distance to the mobile robot 200. The processor 220 may obtain the shortest distance information from each of the plurality of LIDAR sensors 100.

A step of calculating the number of obstacles existing within the reference distance is performed using the shortest distance information (S330). Specifically, the processor 220 may use the shortest distance corresponding to each obstacle to count the number of obstacles corresponding to the shortest distance less than the reference distance.

A step of comparing the number of obstacles and the reference number is performed (S350). Specifically, the processor 220 may compare the number of obstacles existing within a reference distance with a preset reference number.

A step of controlling the behavior of the mobile robot is performed based on the comparison result (S370). For example, the processor 220 causes the mobile robot ( The behavior of 200) (i.e., the behavior unit 260) can be controlled. Specifically, based on the result of comparing the number of obstacles and the reference number, the processor 220 determines whether a temporary narrow area (dynamically narrow area) caused by a dynamic obstacle that is not in the map is a temporary wide area (dynamically narrow area). wide area), and control the moving unit 260 of the mobile robot 200 to perform at least one of an avoidance driving operation of the mobile robot 200 and a running waiting operation of the mobile robot 200. .

In some embodiments, the number of obstacles may be less than the reference number. In this case, it may be relatively advantageous for the mobile robot 200 to travel while avoiding dynamic obstacles. Accordingly, in step S370, the processor 220 may control the moving unit 260 to perform an evasive driving operation of the mobile robot 200. Embodiments for this will be described later with reference to FIGS. 8 and 9 .

In some embodiments, the number of obstacles may be equal to or greater than the reference number. In this case, it may be relatively advantageous for the mobile robot 200 to wait instead of driving while avoiding dynamic obstacles. Accordingly, in step S370, the processor 220 may control the moving unit 260 to perform a driving standby operation of the mobile robot 200. Embodiments for this will be described later with reference to FIGS. 8 and 9 .

FIG. 7 is a diagram for conceptually explaining the flowchart shown in FIG. 6.

Referring to FIG. 7, the system 10 can travel a driving path (DP) formed between a starting point (SP) and a destination point (DP).

Map information stored in system 10 may include static obstacles SO1 and SOP2.

A plurality of obstacles may be present in the driving region DR of system 10. The system 10, specifically the plurality of LiDAR sensors 100, can detect a plurality of dynamic obstacles existing in the driving area DR. Additionally, the system 10 can measure the shortest distances between each of the plurality of dynamic obstacles and the driving path DP. System 10 can recognize dynamic obstacles that exist within a reference distance. For example, with reference to Figure 7, system 10 may detect dynamic obstacles DO1, DO2, DO3, and DO4. Additionally, the system 10 can measure the shortest distances (SD1, SD2, SD3, SD4) between each of the dynamic obstacles (DO1, DO2, DO3, DO4) and the driving path (DP). The shortest distances (SD1, SD2, SD3, SD4) are assumed to be smaller than the reference distance. In this case, the number of dynamic obstacles may be four.

Referring to FIG. 8, the embodiments shown in FIG. 8 may be a specific method of step S370 described above with reference to FIG. 6.

A step is performed to compare whether the number of obstacles is smaller than the reference number (S371). Here, the number of obstacles may be the number of dynamic obstacles counted.

If the number of obstacles is greater than the reference number (S371, example), a step of determining the number of simulation paths that overlap with the dynamic obstacles among the plurality of simulation paths is performed (S372). Specifically, the processor 220 may determine the number of simulation paths that overlap with at least one dynamic obstacle among the remaining simulation paths excluding the selected simulation path from the plurality of simulation paths.

A step of selecting one of the avoidance driving operation and the driving waiting operation is performed depending on the number of overlapping simulation paths (S373). For example, as a specific example, the processor 220 may select a driving standby operation as the number of overlapping simulation paths increases. For another example, the processor 220 may select an avoidance driving operation as the number of overlapping simulation paths is relatively small.

A step of controlling the moving unit 260 of the mobile robot 200 to perform the selected operation is performed (S374).

On the other hand, when the number of obstacles is less than or equal to the reference number (S371, No), the moving unit 260 of the mobile robot 200 is configured to perform an avoidance driving operation by changing parameters such as driving speed and reducing the gap margin between obstacles. ) is performed (S375).

FIG. 9 is a diagram for conceptually explaining the flowchart shown in FIG. 8.

Referring to FIG. 9, when the number (e.g., 4) of dynamic obstacles (DO1, DO2, DO3, DO4) is less than the reference number, the system 10 creates a plurality of simulation paths (SP1 to SP4, DP). It is possible to determine the number of simulation paths that overlap with at least one dynamic obstacle among the remaining simulation paths (SP1 to SP4) excluding the simulation path (eg, driving path (DP)) selected in . At this time, the first simulation path (SP1) overlaps the first dynamic obstacle (DO1), the second simulation path (SP2) overlaps the second dynamic obstacle (DO2), and the third simulation path (SP3) overlaps the third dynamic obstacle (DO1). It overlaps with the dynamic obstacle (DO3), and the fourth simulation path (SP1) may overlap with the third dynamic obstacle (DO3) and the fourth dynamic obstacle (DO4). Accordingly, the number of simulation paths overlapping with at least one dynamic obstacle may be four.

As shown in FIG. 9, since the number of overlapping simulation paths is 4, which is the number of the remaining simulation paths (SP1 to SP4), the system 10 can perform a driving standby operation.

If there is a non-overlapping simulation path among the remaining simulation paths (SP1 to SP4), the system 10 may perform an evasive driving operation by temporarily performing the corresponding simulation path.

If there is a non-overlapping simulation path among the remaining simulation paths (SP1 to SP4), the system 10 may set the corresponding simulation path as the new driving path (DP) and drive on the new driving path (DP). .

Referring to FIG. 10, the embodiments shown in FIG. 10 may be a specific method of step S300 that can be performed when a dynamic obstacle is not recognized by the LIDAR sensor. Specifically, in step S200 shown in FIG. 3, when the processor 220 recognizes the area on the travel path in which the mobile robot 200 will drive as a static area, step S300 is specifically performed in the same manner as shown in FIG. 10. It can be.

A step of acquiring information on the shortest distance between the driving path and static obstacles is performed through the LiDAR sensor (S320).

A step of controlling the behavior of the mobile robot to perform one of the avoidance driving operation of the mobile robot and the running waiting operation of the mobile robot according to the shortest distance information is performed (S340).

Referring to FIG. 11, while the system 100 is traveling along the driving path DP, static obstacles SO1 and SO2 may exist in the driving area DR of the system 10. These static obstacles (SO1, SO2) may be included in map information. The system 100, specifically the plurality of LIDAR sensors 100, calculates the shortest distances (SD, SD') between each of the static obstacles (SO1, SO2) and the driving path (DP) to generate shortest distance information. can do. The processor 220 may recognize whether the area formed by the static obstacles SO1 and SO2 in the driving area DR is a narrow area or a wide area based on the shortest distances SD and SD'. If the shortest distances SD and SD' are relatively small, the area formed by the static obstacles SO1 and SO2 in the driving area DR may be recognized as a narrow area. Accordingly, the processor 220 can view the statically narrow area as an area that must be passed unconditionally, unlike the dynamically narrow area. Therefore, the processor 220 changes the driving method or parameters to enable passage. You can control the eastern part (260). Meanwhile, the shortest distances SD and SD' are relatively large, so the area formed by the static obstacles SO1 and SO2 in the driving area DR can be recognized as a wide area. Accordingly, the processor 220 may control the moving unit 260 to perform an evasive driving operation. In some embodiments, the avoidance driving operation may be an operation of driving on any one simulation path among the remaining simulation paths that have not been previously selected among a plurality of simulation paths, as described above with reference to FIGS. 5 and 9. .

Meanwhile, the disclosed embodiments may be implemented in the form of a recording medium that stores instructions executable by a computer. Instructions may be stored in the form of program code, and when executed by a processor, may create program modules to perform operations of the disclosed embodiments. The recording medium may be implemented as a computer-readable recording medium.

Computer-readable recording media include all types of recording media storing instructions that can be decoded by a computer. For example, there may be Read Only Memory (ROM), Random Access Memory (RAM), magnetic tape, magnetic disk, flash memory, optical data storage device, etc.

As described above, the disclosed embodiments have been described with reference to the attached drawings. A person skilled in the art to which this disclosure pertains will understand that the present disclosure may be practiced in forms different from the disclosed embodiments without changing the technical idea or essential features of the present disclosure. The disclosed embodiments are illustrative and should not be construed as limiting.

Claims

LiDAR sensor; and

It includes a mobile robot including a memory that stores map information including static obstacles, starting point information, and destination point information, a moving unit that performs a movement, and a processor that controls the moving unit based on the information stored in the memory. do,

The processor,

Setting a driving path for the mobile robot to move based on the map information, the departure point information, and the destination point information,

While the mobile robot moves along the travel path, the area in which the mobile robot will drive on the travel path is selected as either a static area or a dynamic area depending on the presence or absence of at least one dynamic obstacle detectable through the lidar sensor. Recognized as one,

The system is characterized in that it controls the driving of the mobile robot based on the driving path, the type of recognized area, and the distance information between the driving path and obstacles obtained through the LiDAR sensor.
According to claim 1,

When setting the driving route, the processor

Generating a plurality of simulation paths on which the mobile robot can travel from a starting point according to the starting point information to a destination point according to the destination point information on a map according to the map information,

A system comprising the step of setting a simulation path selected according to a preset selection criterion among the plurality of simulation paths as the driving path.
According to clause 2,

When the processor recognizes one of the static area and the dynamic area,

In response to the at least one dynamic obstacle being recognized by the LiDAR sensor, the system is characterized in that it recognizes an area in which the mobile robot will travel on the travel path as the dynamic area.
According to clause 3,

When controlling the movement of the mobile robot, the processor

Obtain information on the shortest distance between the driving path and each obstacle using the LiDAR sensor,

Calculate the number of obstacles existing within the reference distance using the shortest distance information,

Compare the number of obstacles and the standard number,

The system is characterized in that it controls the behavior of the mobile robot to perform at least one of an avoidance driving operation of the mobile robot and a running waiting operation of the mobile robot based on a result of comparing the number of obstacles with the reference number. .
According to clause 4,

When controlling the behavior of the mobile robot, the processor

If the number of obstacles is greater than the reference number, determine the number of simulation paths that overlap with the at least one dynamic obstacle among the remaining simulation paths excluding the selected simulation path from the plurality of simulation paths, A system characterized in that one of the avoidance driving operation and the driving waiting operation is selected according to the number of overlapping simulation paths, and the moving part of the mobile robot is controlled to perform the selected operation.
According to clause 4,

When controlling the behavior of the mobile robot, the processor

When the number of obstacles is less than or equal to the reference number, the system is characterized in that it controls the moving part of the mobile robot to perform an avoidance driving operation by changing driving-related parameters.
According to clause 2,

When the processor recognizes one of the static area and the dynamic area,

In response to only the static obstacle being recognized by the LiDAR sensor, the system is characterized in that it recognizes the area in which the mobile robot will drive on the travel path as the static area.
According to clause 7,

When controlling the movement of the mobile robot, the processor

Obtain information on the shortest distance between the driving path and the static obstacle through the LiDAR sensor,

A system comprising controlling the behavior of the mobile robot to perform one of an avoidance driving operation of the mobile robot and a running waiting operation of the mobile robot according to the shortest distance information.
In a method of controlling a mobile robot, performed by a system,

Setting a driving path for the mobile robot to move based on map information including static obstacles, starting point information, and destination point information;

While the mobile robot moves along the travel path, the area in which the mobile robot will drive on the travel path is divided into one of a static area and a dynamic area depending on the presence or absence of at least one dynamic obstacle detectable through a lidar sensor. Recognizing step; and

A method comprising controlling the driving of the mobile robot based on the driving path, the type of recognized area, and the distance information between the driving path and obstacles obtained through the LiDAR sensor.
A computer-readable recording medium that is combined with a hardware computer and stores a program for performing the method of controlling a mobile robot of claim 9.