WO2024242249A1 - Vps integrated mobile robot unit, mobile robot system, and method for controlling vps integrated mobile robot unit - Google Patents

Abstract

The present invention provides a VPS integrated mobile robot unit (20), a VPS integrated mobile robot system (1), and a control method thereof, wherein the VPS integrated mobile robot unit (20) comprises: a unit storage unit (23) that stores an integrated map that links a grid map and a VPS map; a unit control unit (22) that performs precise position estimation by comparing and matching surrounding environment distance measurement information executed through a sampling range that may vary according to a kinematic driving type of a unit driving unit (28) and a VPS position information signal derived from surrounding environment image information, on the basis of the integrated map.

Description

VPS integrated mobile robot unit, mobile robot system and VPS integrated mobile robot unit control method

The present invention relates to a mobile robot unit, a mobile robot system and a control method thereof, and more particularly, to a mobile robot system, a mobile robot and a control method for achieving accurate position estimation in the case where marker or automation information is excluded.

Robots are expanding their scope of application in various industrial fields and daily life. From robot vacuum cleaners used in the home to manufacturing robots used in welding and press processes in automobile factories, various robots used in logistics systems such as AGVs and AMRs are being researched, produced, and used in various ways.

In particular, in the case of guided or autonomous transport logistics robots such as AGV (Automatic Guided Vehicle) or AMR (Autonomous Mobile Robot), the scope of utilization and application is increasing rapidly. In other words, due to the development of driving technology, beyond the necessity of operation in clean facilities such as semiconductor factories, the trend is to expand application not only in the transportation service industry for services such as shopping malls and cargo transport, but also in various logistics delivery industries that operate fulfillment systems, and even in heavy industries that require the transport of large loads such as heavy industry.

Conventional AGVs or AMRs, especially AGVs, follow a floor line as a guide line within the driving environment or provide passive or active markers such as optical identification codes such as QR codes or additional external sensors to drive. However, when complex path formation in the driving environment is required or multiple robots are operated, complex challenges such as crossing or avoidance of paths are encountered.

In addition, in the case of conventional unmanned vehicles, a method of determining one's own location was used using odometry information input from an encoder. However, in the case of such detection sensors, the probability of fatigue or malfunction due to repetitive or long-term operation rapidly increases, which can act as a significant obstacle to location estimation.

Accordingly, the present invention aims to provide a VPS integrated mobile robot unit, a control method and system thereof, which enables driving control through more accurate position estimation when the conventional marker-based position recognition or odometry-based position information acquisition structure is excluded during driving or when the odometry information is unreliable due to an error in the odometry information or damage to an encoder, etc.

According to one aspect of the present invention, the present invention provides a mobile robot unit (20, hereinafter referred to as a mobile robot unit) including a unit storage unit (23) that stores an integrated map that links a grid map and a VPS map, and a unit control unit (22) that performs precise position estimation by comparing and matching surrounding environment distance measurement information executed through a sampling range that can be changed according to a kinematic driving type of a unit driving unit (28) based on the integrated map and a VPS position information signal calculated from surrounding environment image information.

In the above mobile robot unit, the unit control unit (22) may include: a driving control module (221) that applies a driving control signal to the unit driving unit (28) using set destination information, a position estimation module (223) that extracts distance measurement features from the surrounding environment distance measurement information while driving to the destination, compares and matches the distance measurement features and the VPS location information signal using the integrated map to calculate a current estimated location, and a position confirmation module (225) that confirms the location calculated by the position estimation module (223).

In the above mobile robot unit, the position estimation module (223) may include: a data feature extraction unit (2231) that extracts distance measurement measurements from at least the distance measurement information during driving to the destination, a feature comparison and matching unit (2233) that compares and matches the distance measurement features extracted during driving to the destination, and an estimated position calculation unit (2235) that calculates the orientation and position of the robot using the distance measurement feature information compared and matched by the feature comparison and matching unit (2233).

In the above mobile robot unit, the estimated position calculation unit (2235) may also calculate orientation information and position information using the distance measurement feature information compared and matched by the feature comparison and matching unit (2233) and the VPS position information signal.

In the above mobile robot unit, the update cycle of the VPS position information signal used in the estimated position calculation unit (2235) may be longer than the update cycle of the distance measurement feature information.

In the above mobile robot unit, the surrounding environment distance measurement information and the surrounding environment image information are detected by the unit detection unit (21), and the unit detection unit (21) may include: an image sensor (211) that detects the surrounding environment image information, and a distance measurement sensor (213) that detects the surrounding environment distance measurement information.

In the above mobile robot unit, a unit communication unit (26) may be further provided that transmits surrounding environment image information detected by the image sensor (211) and receives the VPS location information signal.

In the above mobile robot unit, the sampling range may be at least one of a circular range, an elliptical range and an arc range when projected onto the ground.

In the above mobile robot unit, the integrated map may be a map that is produced by comparing and matching grid map features extracted from the grid map and VPS map features extracted from the VPS map using an ICP algorithm.

In the above mobile robot unit, a drone mapping unit (20a, 20a') that acquires surrounding environment information for forming the grid map and the VPS map may be further provided.

According to another aspect of the present invention, the present invention may include a provision step (S10) of providing a mobile robot unit (20) including a unit storage unit (23) storing an integrated map linking a grid map and a VPS map, and a unit control unit (22) executing position estimation and driving control, at least a preparation step (S20) of confirming driving information for driving to a destination and a kinematic driving type of a unit driving unit (28), and a driving control step (S30) of executing driving control to a destination, and executing precise position estimation by comparing and matching surrounding environment distance measurement information executed through a sampling range that can be changed according to the kinematic driving type of the unit driving unit (28) based on the integrated map, and a VPS position information signal calculated from surrounding environment image information.

In the above mobile robot unit control method, the preparation step (S20) may include: a type confirmation step (S21) for confirming a sampling range that can be changed according to the kinematic driving type of the unit driving unit (28), and a driving information confirmation step (S23) including at least destination information.

In the above mobile robot unit control method, the type confirmation step (S21) may include: a unit type check step (S211) for confirming the kinematic drive type of the unit drive unit (28), and a sampling range selection step (S213) for selecting a sampling range corresponding to the kinematic drive type of the unit drive unit (28) confirmed in the unit type check step (S211).

In the above mobile robot unit control method, a map preparation step (S25) of preparing a grid map and a VPS map and comparing and matching the grid map and the VPS map to prepare an integrated map may be further included.

In the above mobile robot unit control method, the map preparation step (S25) may include: a grid map and VPS map confirmation step (S251) of confirming a grid map and a VPS map for a surrounding environment in which the mobile robot unit (20) is to drive, a map feature extraction step (S253) of extracting features from the grid map and the VPS map, a map feature matching step (S255) of comparing and matching the map features extracted in the map feature extraction step (S253), and an integrated map calculation step (S257) of calculating an integrated map by linking the grid map and the VPS map based on the matching features matched in the map feature matching step (S255).

In the above mobile robot unit control method, the driving control step (S30) may include: an initial VPS position information confirmation step (S31) of receiving the VPS position information at the start of driving and confirming the current position information, a driving drive step (S33) of executing a driving drive control so that the mobile robot unit (20) drives to a destination, a driving position estimation step (S35) of executing a precise position estimation by comparing and matching feature information using the surrounding environment distance measurement information executed through the sampling range based on the integrated map and the VPS position information signal, based on the driving drive, simultaneously with the execution of the driving drive, and executing a precise position estimation, and an arrival confirmation step (S35) of confirming whether the mobile robot unit (20) has reached the destination.

In the above mobile robot unit control method, the driving position estimation step (S35) may include: a sampling range scan step (S351) of executing distance measurement with the sampling range through the distance measurement sensor (213) of the unit detection unit (21) to derive surrounding environment distance measurement information; a driving matching step (S353) of extracting feature information using the integrated map and the surrounding environment distance measurement information and executing matching while driving using the feature information derived during driving to derive current location information; a VPS location information confirmation step (S355) of confirming updated VPS location information; a precision matching step (S357) of confirming the precision of the current location information using the current location information derived in the driving matching step (S353) and the VPS location information; and a precision position update step (S359) of updating the current location information with new driving location information of the mobile robot unit (20) if the precision of the current location information is confirmed in the precision matching step (S357).

In the above mobile robot unit control method, the update cycle of the VPS position information signal used in the estimated position calculation unit (2235) may be longer than the update cycle of the distance measurement feature information.

In the above mobile robot unit control method, the sampling range may be at least one of a circular range, an elliptical range and an arc range when projected onto the ground.

In the above mobile robot unit control method, the sampling range may be formed and selected to reflect the steering angle of the mobile robot unit (20).

According to another aspect of the present invention, the present invention provides a mobile robot system (1) including a plurality of mobile robot units (20), and a mobile robot managing server (10) which provides a driving path including a destination to which the mobile robot units (20) drive and manages the driving, and the mobile robot unit (20) which performs data transmission and reception including driving information from the mobile robot managing server (10), the mobile robot unit (20) including a unit storage unit (23) which stores an integrated map linking a grid map and a VPS map, and a unit control unit (22) which performs precise position estimation by comparing and matching surrounding environment distance measurement information executed through a sampling range that can be changed according to the kinematic driving type of the unit driving unit (28) based on the integrated map and a VPS position information signal calculated from surrounding environment image information.

In the above mobile robot system, the mobile robot managing server (10) may include: an operation control unit (11) that controls and manages driving along a reference path of the mobile robot unit (20), and a map generation unit (13) that generates the integrated map.

In the above mobile robot system, the map generation unit (13) may include: a VPS map verification unit (131) that verifies a VPS map for the surrounding environment in which the mobile robot unit (20) intends to drive, a grid map verification unit (133) that verifies a grid map for the surrounding environment in which the mobile robot unit (20) intends to drive, and a map integration unit (135) that extracts, compares, and matches map features from the grid map and the VPS map.

In the above mobile robot system, the VPS map verification unit (131) may include: an image verification unit (1311) that verifies an image of a surrounding environment in which the mobile robot unit (20) is to drive, a visual feature extraction unit (1313) that extracts a visual feature from the image, and a VPS map generation unit (1315) that generates a VPS map that links the image of the surrounding environment and the visual feature.

In the above mobile robot system, the map integration unit (135) may include: a map feature extraction unit (1351) that extracts and verifies grid map features and visual map features of the grid map and the VPS map, a map feature matching unit (1353) that compares and matches the grid map features and visual map features using an ICP algorithm, and an integrated map verification unit (1355) that generates an integrated map in which the grid map and the VPS map are linked and integrated based on the matched matching features.

The effects of the mobile robot unit, mobile robot unit control method, and mobile robot system of the present invention configured as described above are as follows.

First, the mobile robot system and the mobile robot system control method of the present invention use an integrated map that links a VPS map and a grid map to secure the reliability of position estimation in cases where odometry information cannot be utilized or must be excluded, and utilizes distance measurement information and image information about the surrounding environment to enable more accurate position estimation.

Second, the mobile robot system and the mobile robot system control method of the present invention use an integrated map that links a VPS map and a grid map to secure the reliability of position estimation in cases where odometry information cannot be utilized or must be excluded, and utilizes distance measurement information and image information about the surrounding environment to enable more accurate position estimation, and at the same time, changes the sampling range according to the driving type reflecting the driving type and/or the steering type by reflecting the kinematic behavior characteristics of the mobile robot unit, thereby enabling more precise positioning information collection for the subsequent estimated position according to the change in time, thereby excluding or minimizing accumulated errors and deriving more accurate position estimation.

FIG. 1 is a schematic configuration diagram of a VPS integrated mobile robot system according to one embodiment of the present invention.

FIG. 2 is a schematic configuration diagram of a mobile robot managing server of a VPS integrated mobile robot system according to an embodiment of the present invention.

FIG. 3 is a schematic diagram of a map generation unit of a mobile robot managing server of a VPS integrated mobile robot system according to an embodiment of the present invention.

FIG. 4 is a schematic configuration diagram of a VPS map verification unit of a VPS integrated mobile robot system according to an embodiment of the present invention.

FIG. 5 is a schematic configuration diagram of a map integration unit of a VPS integrated mobile robot system according to an embodiment of the present invention.

Figure 6 is an exemplary state diagram illustrating distance measurement information forming a grid map.

Figure 7 is an exemplary state diagram illustrating features extracted from image information detected through an image sensor of a unit detection unit.

Figure 8 is an example of a VPS map produced by utilizing image information from which features of Figure 7 are extracted.

Figure 9 is a state diagram in which the outline feature (VOL) is extracted as a VPS map feature of the VPS map of Figure 8.

Figure 10 is an exemplary state diagram of a state in which an outline is extracted as a grid map feature from the grid map of Figure 6.

Figure 11 is a state diagram showing a state in which grid map features and VPS map features are compared and aligned and overlapped.

Figure 12 is an exemplary state diagram of the VPS integrated mobile robot unit of the present invention.

Fig. 13 is an exemplary configuration diagram of a VPS integrated mobile robot unit of the present invention.

Figure 14 is a configuration diagram of a position estimation module of the VPS integrated mobile robot unit of the present invention.

Figures 15 to 21 are schematic flowcharts of the control process of the VPS integrated mobile robot unit of the present invention.

Figure 22 is an exemplary state diagram of a sampling range according to the driving type of the VPS integrated mobile robot unit of the present invention.

FIG. 23 and FIG. 25 are schematic state change diagrams explaining a process of performing position correction according to the sampling range of the VPS integrated mobile robot unit of the present invention.

Figures 26 to 30 are state diagrams showing examples of changes in sampling ranges considering kinematic behavioral characteristics such as driving type and steering type of the VPS integrated mobile robot unit of the present invention.

Figure 31 is a state change diagram explaining the position estimation control process of the VPS integrated mobile robot unit of the present invention.

Figure 32 is a configuration state diagram of a VPS integrated mobile robot unit according to another example of the present invention.

Figure 33 is a block diagram of a VPS integrated mobile robot unit according to another example of the present invention.

Figure 34 is a configuration state diagram of a VPS integrated mobile robot unit according to another example of the present invention.

Hereinafter, specific details for implementing the configuration of the VPS integrated mobile robot unit, the VPS integrated mobile robot system, and the control method thereof according to the present invention will be described based on embodiments with reference to the drawings. These embodiments will be described in sufficient detail to enable those skilled in the art to implement the present invention. It should be understood that the various embodiments of the present invention are different from each other, but are not necessarily mutually exclusive. For example, specific shapes, structures, and characteristics described herein may be implemented in other embodiments without departing from the spirit and scope of the present invention with respect to one embodiment. In addition, it should be understood that the positions or arrangements of individual components within each disclosed embodiment may be changed without departing from the spirit and scope of the present invention. Accordingly, the following detailed description is not intended to be limiting, and the scope of the present invention is defined only by the appended claims, along with the full scope equivalent to what such claims claim, if properly described. Like reference numerals in the drawings designate the same or similar functions throughout the several aspects.

Unless otherwise defined, all terms (including technical and scientific terms) used in this specification may be used with a meaning that can be commonly understood by a person of ordinary skill in the art to which the present invention belongs. In addition, terms defined in commonly used dictionaries shall not be ideally or excessively interpreted unless explicitly specifically defined.

In the embodiments described below, the server may be implemented as a standalone device or as part of a general-purpose processing device in the form of a collection of hardware including a central processing unit, a user I/F, an operating system (not shown), a memory storing various necessary data, an external communication port, a printer I/F, etc., and software that operates the same, which performs various functions required for the present invention described below by executing various software programs and/or command sets stored in a memory section.

The VPS integrated mobile robot unit (20) according to one embodiment of the present invention is implemented as an autonomous driving robot, and may be configured to be operationally controlled by the mobile robot system (1) to assign driving information and tasks including a driving destination when multiple mobile robot units (20) are driving, and may be configured to be individually controlled by the mobile robot system (1) in the case of an emergency. Various configurations are possible, such as:

The mobile robot system (1) includes one or more mobile robot units (20) and a mobile robot managing server (10), and in some cases, an administrator terminal (30), such as a task manager's computer, may also be included in the overall system. Each of the components constituting the mobile robot system (1) can perform mutual communication operations through a communication network and transmit and receive data.

Communication, a communication network or a communication network may include, for example, a cellular communication protocol, for example, at least one of LTE, LTE-A, 5G, WCDMA, CDMA, UMTS, Wibro, and GSM. In addition, the communication network may be configured regardless of the communication type, such as wired and wireless, and may be implemented as various communication networks, such as a Personal Area Network (PAN), a Local Area Network (LAN), a Metropolitan Area Network (MAN), and a Wide Area Network (WAN). In addition, the communication, communication network or communication network may be the well-known World Wide Web (WWW), and include various communication methods, such as Infrared Data Association (IrDA) or Bluetooth or Bluetooth Lowenergy and RF wireless communication.

Fig. 12 illustrates an example of a mobile robot unit (20), and Fig. 13 illustrates a schematic block diagram of a mobile robot unit (20). In this embodiment, one or more mobile robot units (20) are provided, and the mobile robot unit (20) autonomously drives to a destination, which will be described later, to perform a predetermined task, thereby enabling stable task performance.

The mobile robot unit (20) of the present invention includes a unit storage unit (23) and a unit control unit (22). The unit storage unit (23) stores an integrated map that links a grid map and a VPS map, and the unit control unit (22) performs precise position estimation by comparing and matching surrounding environment distance measurement information executed through a sampling range that can be changed according to the kinematic driving type of the unit driving unit (28) based on the integrated map and a VPS position information signal derived from surrounding environment image information.

More specifically, the mobile robot unit (20) of the present invention includes a unit detection unit (21), a unit control unit (22), a unit storage unit (23), a unit operation unit (24), a unit input unit (25), a unit communication unit (26), a unit output unit (27), and a unit driving unit (28).

The unit detection unit (21) is a detection means for acquiring information on the driving status and surrounding environment of the mobile robot unit (20), and the unit detection unit (21) includes an image sensor (211) and a distance measurement sensor (213). The image sensor (211) can capture an image of the surroundings while the mobile robot unit (20) is driving and convert and provide image information.

The distance measurement sensor (213) can be selected in a variety of ways in the range of detecting distance measurement through an ultrasonic sensor, a laser sensor, etc., but in this embodiment, a component that performs a scan detection function, such as a lidar as a laser sensor, is implemented to extract point cloud data of surrounding objects, etc., and detect the presence of obstacles, that is, objects that affect driving operations, such as other mobile robot units that require crossing or objects that can collide, and enable recognition of the current location through comparison with a grid map, etc.

The unit control unit (22) applies a detection operation control signal to the unit detection unit (21) of the mobile robot unit (20), or receives the detected detection information and transmits it to the mobile robot managing server (10), so that the corresponding data can be transmitted and stored in the operation data storage module (17) of the mobile robot managing server (10).

In this embodiment, the driving of the mobile robot unit (20) is structured to perform an independent and individual autonomous driving function under the control of the unit control unit (22), but it is clear from this technology that a case may be taken where partial driving information provision or driving control is controlled by the mobile robot managing server (10).

The unit storage unit (23) is operated according to the unit storage control signal of the unit control unit (22), and has the function of storing unit pre-data for driving operation or storing image information or detection data in the form of a point cloud detected by the unit detection unit (21), and can perform integrated map storage linked to a grid map and a VPS map.

The unit operation unit (24) may execute a predetermined operation process according to the unit operation control signal of the unit control unit (22) by utilizing unit dictionary data, etc. stored in the unit storage unit. In addition, the unit input unit (25) may enable direct data input into the mobile robot unit (20) in addition to input through the terminal (30) of the user or management operator.

The unit communication unit (26) communicates with the mobile robot managing server (10) through wired or wireless communication, and can receive a motion control signal transmitted from the mobile robot managing server (10) or transmit detection data detected by the unit detection unit (21) of the mobile robot unit (20). The unit communication unit (26) in the present embodiment transmits surrounding environment image information detected by the image sensor (211) and can also receive the VPS location information signal described below. In some cases, the VPS location information signal may be directly processed by the unit control unit (22), or in some cases, it may be quickly processed by the mobile robot managing server (10) and then transmitted to the mobile robot unit (20).

The unit output unit (27) is attached to the mobile robot unit (20) to output signals externally. The unit output unit (27) can be implemented with various output elements such as a speaker or display.

The unit drive unit (28) includes various power generation and power transmission means such as wheels, drive motors, and reducers of the mobile robot unit. In the present embodiment of Fig. 12, the unit drive unit (28) takes a differential type drive type, but is not limited thereto. That is, the mobile robot unit (20) of the present embodiment is not limited to a specific drive type, such as a single drive type, a differential type, and a quad type, and can be modified in various ways.

Meanwhile, the unit control unit (22) of the present invention can perform precise position estimation of the current position of the mobile robot unit (20) by comparing and matching feature information using the surrounding environment distance measurement information and the VPS position information signal based on an integrated map that links the grid map and the VPS map stored in the unit storage unit (23). Here, the surrounding environment distance measurement information refers to point cloud data on the surrounding environment of the mobile robot unit (20) that is executed through a sampling range that can be changed according to the kinematic driving type of the unit driving unit (28).

As described above, the unit detection unit (21) includes an image sensor (211) and a distance measurement sensor (213). The image sensor (211) detects image information of the surrounding environment, and the distance measurement sensor (213) detects distance measurement information of the surrounding environment.

As shown in Fig. 6, the grid map is formed through the surrounding environment distance measurement information using point cloud data detected by the distance measurement sensor (213).

In addition, FIG. 7 illustrates a state in which visual feature information acquired from image information, such as vertices or lines, among visual feature information having high importance, has been acquired and confirmed, and FIG. 8 illustrates a VPS map including visual feature information similar to that in FIG. 7, and the VPS location information signal refers to location information that has been confirmed by comparing and matching feature points in acquired surrounding environment image information with visual features on a VPS map (Visual Positioning System map) as a visual map.

The unit control unit (22) of the present invention uses an integrated map. Here, the integrated map is an integrated map derived by linking a grid map and a VPS map, and in one embodiment of the present invention, it may be input and stored in the unit storage unit (23) and used as a reference map when the unit control unit (22) performs location estimation.

The creation of an integrated map may be executed directly on the mobile robot unit (20), but due to problems of computational load or processing time, the derivation of an integrated map through linking the grid map and the VPS map may be structured to be executed on the mobile robot managing server (10).

FIGS. 9 and 10 illustrate a case where map features are derived from a VPS map and a grid map, respectively. That is, a VPS map feature indicated by the reference symbol VOL in FIG. 9 can be extracted from a VPS map including a VPS feature, and an outline feature can be extracted as a grid map feature from a grid map as illustrated in FIG. 10. Here, outline features such as VPS map features and grid map features are extracted using a Canny edge in this embodiment, but the present invention is not limited thereto.

Then, through ICP matching between the points of each outline feature, an integrated map can be derived in which the two maps are linked and integrated, as in Fig. 11. That is, it is achieved through ICP matching of outline features. In this embodiment, the integrated map is linked and produced by comparing and matching grid map features extracted from the grid map and VPS map features extracted from the VPS map using the ICP algorithm.

Meanwhile, the unit control unit (22) of the present invention is illustrated in Fig. 13. More specifically, as illustrated in Fig. 13, the unit control unit (22) includes a driving control module (221), a position estimation module (223), and a position confirmation module (225). The driving control module (221) applies a driving control signal to the unit driving unit (28) using the set destination information.

The location estimation module (223) extracts distance measurement features from the surrounding environment distance measurement information during the process of driving to the destination, and compares and matches the distance measurement features and VPS location information signals using an integrated map to calculate the current estimated location.

The location confirmation module (225) confirms the location calculated by the location estimation module (223). That is, a region that can move at each time period can be demarcated through the unit driving unit. If it is determined that newly updated location information has made an unrealistic location movement, the location confirmation module (225) may execute an abnormal notification or request the location estimation module (223) to re-execute location estimation.

More specifically, in this embodiment, the location estimation module (223) includes a data feature extraction unit (2231), a feature comparison matching unit (2233), and an estimated location calculation unit (2235).

The data feature extraction unit (2231) extracts distance measurement features from at least the distance measurement information during driving to the destination. That is, it extracts features from the surrounding environment distance measurement information in the form of a point cloud detected by the distance measurement sensor (213) of the unit detection unit (21).

The feature comparison matching unit (2233) of the position estimation module (223) of the unit control unit (22) compares and matches distance measurement features extracted during driving to the destination. That is, it performs comparison and matching between distance measurement features detected in the order of driving time of the mobile robot unit (20), such as time t-1, t, t+1, etc. during driving.

The estimated position calculation unit (2235) calculates the orientation and position of the robot using the distance measurement feature information compared and matched by the feature comparison and matching unit (2233). That is, the position information of the current mobile robot unit (20) is confirmed and derived through the relative position change between the distance measurement features compared and matched by the feature comparison and matching unit (2233). In this embodiment, the comparison and matching between these distance measurement features uses the ICP (Iterative Closest POint) algorithm and the ICP matching method, but the comparison and matching of the present invention is not limited to this and various selections are possible.

In addition, in the case of the present embodiment, in addition to comparing and matching between distance measurement features, the estimated position calculation unit (2235) can calculate orientation information and position information using the distance measurement feature information and VPS position information signal compared and matched by the feature comparison and matching unit (2233). That is,

Here, the surrounding environment distance measurement information and the surrounding environment image information are detected by the unit detection unit (21), and as described above, the unit detection unit (21) includes an image sensor (211) and a distance measurement sensor (213). The image information acquired by the image sensor (211) may be directly acquired by the unit control unit (22) through calculation of VPS location information, but may also be transmitted to the mobile robot managing server (10) to calculate VPS location information through a VPS map, and transmitted by the server's operation communication module (19) described below and received through the unit communication unit (26), thereby being used for location estimation.

In particular, in the case of the present embodiment, the update cycle of the VPS location information signal used in the estimated location calculation unit (2235) is longer than the update cycle of the distance measurement feature information. The location estimation for each detailed time period between the location estimation cycles using the VPS location information signal can be derived through the temporal relative position change of the feature derived from the surrounding environment distance measurement information as a point cloud derived from the distance measurement sensor.

In the case of the present invention, the range of the area detected by the distance measurement sensor used for position estimation between the reception cycles of such VPS position information signals may vary depending on the kinematic drive type of the mobile robot unit (20). That is, when the surrounding environment distance measurement information is detected by the mobile robot unit (20), the sampling range may be selected depending on the kinematic characteristics of the mobile robot unit (20), that is, the drive type. The sampling range may be at least one of a circular range, an elliptical range, and an arc-shaped range when projected onto the ground. Here, the shape of the sampling range may refer to a comprehensive form of coverage that takes into account the steering range of the area being scanned.

FIG. 22, FIG. 26 to FIG. 29 illustrate changes in sampling ranges according to the kinematic driving type of the unit driving unit (28) of the mobile robot unit (10). FIG. 22 illustrates a case where the sampling range at time t-1 takes an arc, and by forming the sampling range as a detection area of the distance measurement sensor detected at time t-1 into an arc and forming it so as to overlap as much as possible within the range of the area that can move at time t, more accurate position estimation can be enabled.

As illustrated in Fig. 23, a mobile robot unit (20) is depicted on an integrated map (IM), and the mobile robot unit (20) sets a sampling range (SR) according to a kinematic drive type. As illustrated in Fig. 24, by using the surrounding environment distance measurement information detected in the sampling range (SR), features (F1, F2) are extracted, and by using the integrated map (IM) to confirm the change in the position of the features over time, accurate position (P) correction of the mobile robot unit (20) can be performed, as illustrated in Fig. 25.

FIGS. 26 to 30 illustrate various variations of sampling ranges (SR1, SR2, SR3, SR4, SR5) according to the driving types in which the arrangement positions of the driving wheels and the arrangement positions of the steering wheels are different. According to the driving type, each sampling range (SR1, SR2, SR3, SR4, SR5) has a maximum steering angle (Max, St1; Max, St2; Max, St3; Max, St4; Max, St5), and for each area, a trajectory (TRJ1, TRJ2, TRJ3, TRJ4, TRJ5) while moving from time t to time t+1, time t+2, ... is provided. Since the kinematic behavior characteristics are different according to each driving type, by selecting an appropriate sampling range according to the driving type, it is possible to obtain distance measurement information and image information for an area in which the mobile robot unit is likely to move after a detailed cycle, thereby enabling more precise position estimation.

Meanwhile, the mobile robot unit (20) of the present invention may further include a drone mapping unit (20a, 20a'). The drone mapping unit (20a, 20a') may acquire surrounding environment information for forming a grid map and a VPS map. That is, the mobile robot unit (20) of the present invention may directly drive and acquire distance measurement information and image information for forming a grid map and a VPS map for the surrounding environment, but may further include a sub-unit for acquiring surrounding environment information for the surrounding environment depending on the case.

That is, as illustrated in Fig. 32, an openable unit withdrawal portion (20b) is formed on the side of the housing of the mobile robot unit (20) of the present invention, and a drone mapping unit (20a) is positioned in a withdrawable manner on the unit withdrawal portion (20b).

More specifically, as illustrated in FIG. 33, the drone mapping unit (20a) of the present invention includes a drone unit detection unit (21), a drone unit control unit (22), a drone unit storage unit (23), a drone unit operation unit (24), a drone unit input unit (25), a drone unit communication unit (26), a drone unit output unit (27), and a drone unit driving unit (28), and the configuration and function thereof are identical or substantially identical to those of the mobile robot unit described above, and therefore, a duplicate description is omitted.

In this way, the distance measurement information and image information detected by the drone unit detection unit (21a) are transmitted to the mobile robot unit (20) through the drone unit communication unit (26a) or to the operation control unit (11) and operation data storage module (17) through the operation server communication module (19) of the mobile robot managing server (10), and can enable the formation of a grid map and a VPS map.

In the case of Fig. 32, a direct road driving method was used, but in some cases, as shown in Fig. 34, the drone mapping unit (20b) may be implemented as a flying drone mapping unit, and various modifications are possible.

Hereinafter, a method for controlling a mobile robot unit of the present invention will be described with reference to the drawings.

First, as illustrated in Fig. 15, the mobile robot unit control method of the present invention includes a providing step (S10), a preparation step (S20), and a driving control step (S30).

In the provision step (S10), a mobile robot unit (20) is provided, which includes a unit storage unit (23) that stores an integrated map that links a grid map and a VPS map, and a unit control unit (22) that executes position estimation and driving control. The mobile robot unit (20) has been described above, and thus, duplicate descriptions thereof are omitted.

After that, a preparation step (S20) is executed, in which at least the driving information for driving to the destination and the kinematic driving type of the unit driving unit (28) are confirmed. Here, the driving information for driving refers to the destination information to which the mobile robot unit (20) must drive and the task to be executed, and the kinematic driving type of the unit driving unit (28) refers to a driving type such as a quad type, a single type, etc. and/or a steering type. Depending on the type, a group of future position candidates to be moved according to the driving and/or steering changes, and accordingly, the sampling range can be changed to enable more precise position estimation.

More specifically, the preparation step (S20) includes a type confirmation step (S21) and a driving information confirmation step (S23). As illustrated in Fig. 16, in the type confirmation step (S21), a sampling range that can be changed according to the kinematic driving type of the unit driving unit (28) is confirmed.

In more detail, as illustrated in Fig. 17, the type verification step (S21) includes a unit type check step (S211) and a sampling range selection step (S213).

In the unit type check step (S211), the kinematic drive type of the unit drive unit (28) is confirmed. The kinematic drive type of the unit drive unit (28) may be included in the preset storage information stored in the unit storage unit (23), or may be implemented as data input through the unit input unit (25). That is, the driving control module (221) of the unit control unit (22) can confirm the corresponding information from the preset data stored in the unit storage unit (23), etc.

In the sampling range selection step (S213), a sampling range corresponding to the kinematic drive type of the unit drive unit (28) confirmed in the unit type check step (S211) is selected. The type information of the sampling range may also be included in the preset storage information stored in the unit storage unit (23), or may be implemented as data input through the unit input unit (25). That is, the driving control module (221) of the unit control unit (22) can confirm the corresponding information from the preset data stored in the unit storage unit (23), etc.

After that, a driving information confirmation step (S23, see FIG. 16) is executed. In the driving information confirmation step (S23), driving information including at least destination information is confirmed. This may be included in preset storage information stored in the unit storage unit (23), may be implemented as data input through the unit input unit (25), or may be structured to be received from the mobile robot managing server (10) through the unit communication unit (26) and stored in the unit storage unit (23). That is, the driving control module (221) of the unit control unit (22) can confirm the corresponding information from preset data or updated stored data stored in the unit storage unit (23), etc.

Meanwhile, in some cases, a map preparation step (S25) may be further included as illustrated in Fig. 18. In the map preparation step (S25), a grid map and a VPS map are prepared, and an integrated map is prepared by comparing and matching the grid map and the VPS map.

In more detail, as illustrated in FIG. 19, the map preparation step (S25) includes a grid map and VPS map verification step (S251), a map feature extraction step (S253), a map feature matching step (S255), and an integrated map calculation step (S257). First, in the grid map and VPS map verification step (S251), a grid map and VPS map for the surrounding environment in which the mobile robot unit (20) is to drive are verified.

In the map feature extraction step (S253), features are extracted from the grid map and the VPS map. As described above, features are extracted using the Canny edge, but the present invention is not limited thereto.

In the map feature matching step (S255), the map features extracted in the map feature extraction step (S253) are compared and matched.

In the integrated map generation step (S257), the integrated map is generated by linking the grid map and the VPS map based on the matching features aligned in the map feature matching step (S255). This map preparation step may be executed by the unit control unit (22), but considering the data processing amount and processing speed, etc., it may be executed by the mobile robot managing server (10) and stored in the unit storage unit (23), and various options are possible depending on the design specifications.

After that, a driving control step (S30) is executed to control the autonomous driving operation of the mobile robot unit (20) to the destination. That is, in the driving control step (S30), driving control to the destination is executed, and a precise position estimation is executed by comparing and matching the surrounding environment distance measurement information executed through a sampling range that can be changed according to the kinematic driving type of the unit driving unit (28) based on the integrated map and the VPS position information signal calculated from the surrounding environment image information.

Fig. 20 illustrates detailed steps of the driving control step (S30). The driving control step (S30) includes an initial VPS position information confirmation step (S31), a driving drive step (S33), a driving position estimation step (S35), and an arrival confirmation step (S37).

First, in the initial VPS location information confirmation step (S31), the current location information is confirmed by receiving the VPS location information at the start of driving. The location estimation module (223) of the unit control unit (22) may directly generate the initial VPS location information, but in this embodiment, a VPS location information processing structure is formed through the mobile robot managing server (10). That is, the image information acquired from the image sensor (211) of the unit detection unit (21) is transmitted to the mobile robot managing server (10) through the unit communication unit (26), and is signal-processed to produce predetermined visual-based VPS location information, which can be transmitted and received to the mobile robot unit (20) through the operation communication module (19).

In the driving drive stage (S33), driving drive control is executed so that the mobile robot unit (20) drives to the destination. That is, the driving control module (221) applies a driving control signal to the unit driving unit (28) to execute a predetermined driving, stopping, or steering operation control.

In the driving position estimation step (S35), while the driving drive is being executed, a precise position estimation is executed by comparing and matching the surrounding environment distance measurement information executed through the sampling range based on the integrated map and the feature information using the VPS position information signal.

In the arrival confirmation step (S37), it is confirmed whether the mobile robot unit (20) has reached the destination. The driving control module (221) of the unit control unit (22) confirms whether the current mobile robot unit (20) has reached the destination from the driving information and current estimated position information stored in the unit storage unit (23). At this time, if the driving control module (221) determines that the current mobile robot unit (20) has not reached the destination, the control flow switches to step S33 to repeat the driving drive and driving position estimation steps.

On the other hand, if the driving control module (221) determines that the current mobile robot unit (20) has reached the destination, the control flow switches to step S38 to end driving and perform a task execution step (S39) to execute a task.

Here, the detailed steps of the driving position estimation step (S35) are illustrated in FIG. 21 and FIG. 31. The driving position estimation step (S35) includes a sampling range scan step (S351), a driving alignment step (S353), a VPS position information confirmation step (S355), a precision alignment step (S357), and a precision position update step (S359).

In the sampling range scan step (S351), distance measurement is performed in the sampling range through the distance measurement sensor (213) of the unit detection unit (21), and the surrounding environment distance measurement information is calculated. As illustrated in Fig. 22, the surrounding environment distance measurement information is acquired by performing distance measurement through the distance measurement sensor (213) in the sampling range selected according to the driving type of Figs. 26 to 29. The sampling range may be at least one of a circular range, an elliptical range, and an arc-shaped range when projected onto the ground.

In addition, the sampling range may be formed and selected to reflect the steering angle of the mobile robot unit (20). That is, in addition to the driving type of the unit driving unit (28), the sampling range may be changed to reflect the kinematic behavioral characteristics of the mobile robot unit (20) depending on the steering angle or steering point. By reflecting such behavioral characteristics, more accurate position estimation of the mobile robot unit (20) is enabled.

In the driving alignment step (S353), feature information is extracted using the integrated map and surrounding environment distance measurement information, and driving alignment is performed using the feature information calculated during driving to derive current location information.

In the VPS location information confirmation step (S355), the updated VPS location information is confirmed. That is, in the initial stage, location estimation starts using the provided VPS location information. At this time, the update cycle of the VPS location information signal used in the estimated location calculation unit (2235) is longer than the update cycle of the distance measurement feature information. Therefore, in the detailed cycles between the update cycles of the VPS location information, location estimation can be performed based on the grid map and/or the integrated map with the ICP algorithm using the surrounding environment distance measurement information, and more precise location estimation can be performed by reflecting the VPS location information of the new update cycle. That is, in the precise matching step (S357), the precision of the current location information is confirmed using the current location information derived in the driving matching step (S353) and the VPS location information. The VPS location information can be calculated by comparing and matching visual features extracted from image information acquired by the image sensor with visual features already secured in the VPS map, and through the positional relationship with these aligned visual features.

In some cases, VPS position information may be delayed from the actual position of the mobile robot unit (20) due to the computational speed. Therefore, in the detailed cycle, a method may be adopted to verify the reliability of the estimated position by comparing the previous position derived from the inverse kinematics with the VPS position information from the estimated position based on the grid map and/or the integrated map using the ICP algorithm using the surrounding environment distance measurement information.

After going through a series of processes like this, in the precision position update step (S359), if the precision of the current position information is confirmed in the precision alignment step (S357), the current position information is updated with new driving position information of the mobile robot unit (20).

Fig. 31 illustrates a series of position estimation processes. That is, when initial VPS position information is input and driving control is executed, the unit control unit (22) searches the surrounding environment and executes driving based on the input initial VPS position information. During detailed time periods of time t-5, t-4, t-3, and t-2, surrounding distance measurement information is detected through a continuous distance measurement sensor, features are extracted therefrom, and the position information of the mobile robot unit is estimated and updated for each detailed time period from relative distance information according to the temporal position change of the features using a grid map and/or an integrated map. During this process, the image information of the surrounding environment acquired by the image sensor is transmitted to the mobile robot managing server, and an operation for VPS-based position estimation is executed to compare and match the visual feature information expressed as particles in the image information with the VPS map, thereby executing a predetermined VPS position estimation.

Then, based on the updated VPS position information transmitted and received at time t-2, the consistency or accuracy of the position estimation of the mobile robot unit is verified, and then the acceptance within the preset range is determined or a new confirmed position information is updated through a predetermined correction process.

Meanwhile, according to another aspect of the present invention, the present invention can provide a mobile robot system (1) including a mobile robot managing server (10) that operates the driving of a plurality of mobile robot units (20).

As illustrated in FIG. 1, the mobile robot system (1) of the present invention includes a plurality of mobile robot units (20) and a mobile robot managing server (10).

The mobile robot managing server (10) provides a driving route including a destination to which the mobile robot unit (20) is driving and manages the driving. At this time, the mobile robot unit (20) transmits and receives data including driving information from the mobile robot managing server (10).

In addition, the mobile robot unit (20) includes a unit storage unit (23) that stores an integrated map that links a grid map and a VPS map, and a unit control unit (22) that performs precise position estimation by comparing and matching surrounding environment distance measurement information executed through a sampling range that can be changed according to the kinematic drive type of the unit drive unit (28) based on the integrated map and a VPS position information signal derived from surrounding environment image information. Since this is the same as described above, duplicate descriptions will be replaced with the above, and explanations will be given focusing on differences.

The administrator terminal (30) may also be included in the overall system as described above. The administrator terminal (30) may transmit and receive data by intercommunicating with other components, such as by individually applying a control signal to the mobile robot unit (20) or to the mobile robot unit (20) and the mobile robot managing server (10) through a communication network, or by acquiring current driving situation information.

Meanwhile, the mobile robot managing server (10) includes an operation control unit (11), and may include a map generation unit (13) and/or a position estimation module (15) as the case may be. The operation control unit (11) controls and manages the driving of the mobile robot unit (20) along a reference path. The mobile robot managing server (10) includes an operation data storage module (17). The operation data storage module (17) can store preset data and detection data, such as driving information for the driving of the mobile robot unit (20), and can also store map data, i.e., map data of a grid map and a VPS map.

In addition, the mobile robot managing server (10) includes an operational communication module (19), through which data can be transmitted and received with the unit communication unit (26) of the mobile robot unit (20) described above.

The map generation unit (13) generates an integrated map. As described in the previous embodiment, the integrated map may be formed directly in the mobile robot unit (20), and the VPS location information calculation through the VPS map may also be directly calculated in the mobile robot unit (20). However, in this embodiment, a structure for generating an integrated map in the map generation unit (13) of the mobile robot managing server (10) is described.

More specifically, the map generation unit (13) may include a VPS map verification unit (131), a grid map verification unit (133), and a map integration unit (135).

First, the VPS map verification unit (131) verifies the VPS map for the surrounding environment in which the mobile robot unit (20) intends to drive. The grid map verification unit (133) verifies the grid map for the surrounding environment in which the mobile robot unit (20) intends to drive. As described above, the VPS map and the grid map can be generated in various ways, such as directly generated in the mobile robot unit (20) or generated through the drone mapping unit (20a, 20a'), and the VPS map verification unit (131) and the grid map verification unit (133) verify whether the VPS map and the grid map are ready. In some cases, the VPS map verification unit (131) and the grid map verification unit (133) can directly generate the grid map and the VPS map by using the input surrounding distance measurement information and surrounding environment image information. Here, there are various options available for providing distance measurement information for forming a grid map as preparatory data, such as utilizing an odometry-based mapping robot unit in the case of a grid map.

The VPS map verification unit (131) includes an image verification unit (1311), a visual feature extraction unit (1313), and a VPS map generation unit (1315). The image verification unit (1311) verifies an image of the surrounding environment in which the mobile robot unit (20) is to drive. The visual feature extraction unit (1313) extracts visual features from the image. Extraction of visual features can be performed through various feature extraction methods such as the Canny Edge described above. In this way, the VPS map generation unit (1315) generates a VPS map by linking the image of the surrounding environment and the visual features.

When the provision of grid maps and VPS maps is confirmed in the VPS map verification unit (131) and the grid map verification unit (133), the map integration unit (135) extracts map features from the grid map and VPS map and compares and matches them. The map integration unit (135) includes a map feature extraction unit (1351), a map feature matching unit (1353), and an integrated map verification unit (1355).

The map feature extraction unit (1351) extracts and verifies grid map features and visual map features of the grid map and the VPS map. As described above, FIGS. 9 and 10 illustrate a case where map features are derived from the VPS map and the grid map, respectively. In FIG. 9, a VPS map feature as a visual feature indicated by the reference symbol VOL can be extracted from a VPS map including the VPS feature by the map feature extraction unit (1351), and as illustrated in FIG. 10, an outline feature can be extracted as a grid map feature from the grid map. Here, the outline features such as the VPS map feature and the grid map feature are extracted using a Canny edge in this embodiment, but the present invention is not limited thereto.

Using the features extracted from the map feature extraction unit (1351), a comparison and matching between features is performed in the map feature matching unit (1353). The map feature extraction unit (1351) extracts and verifies grid map features and visual map features of the grid map and the VPS map. The map feature matching unit (1353) compares and matches the grid map features and the visual map features using the ICP algorithm. That is, an integrated map in which two maps are linked and integrated, as in Fig. 11, can be derived through ICP matching between points of each outline feature, which is achieved through ICP matching of the outline features. In this embodiment, the integrated map is produced by comparing and matching the grid map features extracted from the grid map and the VPS map features extracted from the VPS map using the ICP algorithm.

When comparative matching is performed in the map feature matching unit (1353), the integrated map verification unit (1355) generates an integrated map in which the grid map and the VPS map are linked and integrated based on the matched matching features. That is, the integrated map verification unit (1355) can check whether there is an error within a preset range, and if the reliability of comparative matching is confirmed, the map in which the grid map and the VPS map are integrated can be confirmed as the final integrated map.

The position estimation module (15) estimates the current position of the mobile robot unit using map data, accumulated sensing surrounding environment distance measurement information, and surrounding environment image information. It structurally has the same or substantially the same structure as the position estimation module (223) provided in the unit control unit (22) of the mobile robot unit (20) described above, and is replaced with the above.

While the present invention has been illustrated and described with reference to preferred embodiments for illustrating the principles of the present invention, the present invention is not limited to the exact construction and operation as illustrated and described. Rather, it will be readily apparent to those skilled in the art that numerous changes and modifications can be made to the present invention without departing from the spirit and scope of the appended claims.

The VPS integrated mobile robot unit of the present invention can be used in various applications, such as in delivery robots for commercial purposes in addition to logistics robots in industrial sites.

Claims (25)

As a VPS integrated mobile robot unit (20), A unit storage unit (23) that stores an integrated map that links the grid map and the VPS map, A VPS integrated mobile robot unit (20) including a unit control unit (22) that performs precise position estimation by comparing and matching surrounding environment distance measurement information executed through a variable sampling range according to the kinematic driving type of the unit driving unit (28) based on the above integrated map and VPS position information signal derived from surrounding environment image information. In paragraph 1, The above unit control unit (22): A driving control module (221) that applies a driving control signal to the unit driving unit (28) using the set destination information, A location estimation module (223) that extracts distance measurement features from the above-mentioned surrounding environment distance measurement information while driving to the destination, compares and matches the distance measurement features and the VPS location information signal using the integrated map to calculate the current estimated location, and A VPS integrated mobile robot unit (20) characterized by including a position confirmation module (225) that confirms the position calculated by the above position estimation module (223). In the second paragraph, The above position estimation module (223): A data feature extraction unit (2231) that extracts distance measurement measurements from at least the above distance measurement information while driving to the destination, and A feature comparison and matching unit (2233) that compares and matches the above distance measurement features extracted during driving to the destination, and A VPS integrated mobile robot unit (20) characterized by including an estimated position calculation unit (2235) that calculates the orientation and position of the robot by using the distance measurement feature information compared and matched in the above feature comparison and matching unit (2233). In the third paragraph, The above estimated location calculation unit (2235) is A VPS integrated mobile robot unit (20) characterized in that it calculates orientation information and position information by using the distance measurement feature information compared and matched in the above feature comparison matching unit (2233) and the VPS position information signal. In paragraph 4, A VPS integrated mobile robot unit (20), characterized in that the update cycle of the VPS location information signal used in the estimated location calculation unit (2235) is longer than the update cycle of the distance measurement feature information. In paragraph 5, The above-mentioned surrounding environment distance measurement information and the above-mentioned surrounding environment image information are detected by the unit detection unit (21), The above unit detection unit (21): An image sensor (211) that detects image information of the surrounding environment, A VPS integrated mobile robot unit (20) characterized by including a distance measurement sensor (213) that detects the above-mentioned surrounding environment distance measurement information. In paragraph 6, A VPS integrated mobile robot unit (20) characterized in that it further comprises a unit communication unit (26) that transmits surrounding environment image information detected by the image sensor (211) and receives the VPS location information signal. In paragraph 1, A VPS integrated mobile robot unit (20), characterized in that the above sampling range is at least one of a circular range, an elliptical range, and an arc range when projected onto the ground. In paragraph 1, The above integrated map is a VPS integrated mobile robot unit (20) characterized in that it is a map that is produced by comparing and matching grid map features extracted from the grid map and VPS map features extracted from the VPS map using the ICP algorithm. In paragraph 1, A VPS integrated mobile robot unit (20) characterized in that it further comprises a drone mapping unit (20a, 20a') that acquires surrounding environment information for forming the grid map and the VPS map. A provision step (S10) for providing a mobile robot unit (20) including a unit storage unit (23) that stores an integrated map that links a grid map and a VPS map, and a unit control unit (22) that executes position estimation and driving control; At least, a preparatory step (S20) for checking the driving information for driving to the destination and the kinematic driving type of the unit drive unit (28), A VPS integrated mobile robot unit control method characterized by including a driving control step (S30) for executing driving control to a destination, and executing precise position estimation by comparing and matching surrounding environment distance measurement information executed through a sampling range that can be changed according to the kinematic driving type of the unit drive unit (28) based on the integrated map, and VPS position information signal calculated from surrounding environment image information. In Article 11, The above preparation step (S20) is: A type confirmation step (S21) for confirming a sampling range that can be changed according to the mechanical drive type of the above unit drive unit (28), A VPS integrated mobile robot unit control method characterized by including a driving information confirmation step (S23) including at least destination information. In Article 12, The above type verification step (S21) is: A unit type check step (S211) for confirming the kinematic driving type of the above unit driving unit (28), A VPS integrated mobile robot unit control method characterized by including a sampling range selection step (S213) for selecting a sampling range corresponding to the kinematic drive type of the unit drive unit (28) confirmed in the unit type check step (S211). In Article 12, A VPS integrated mobile robot unit control method characterized by further comprising a map preparation step (S25) of preparing a grid map and a VPS map and comparing and matching the grid map and the VPS map to prepare an integrated map. In Article 14, The above map preparation step (S25) is: A grid map and VPS map confirmation step (S251) for confirming the grid map and VPS map for the surrounding environment in which the above mobile robot unit (20) is to drive, A map feature extraction step (S253) for extracting features from the above grid map and VPS map, A map feature matching step (S255) for comparing and matching the map features extracted in the above map feature extraction step (S253), A VPS integrated mobile robot unit control method characterized by including an integrated map calculation step (S257) for calculating an integrated map by linking the grid map and the VPS map centered on the aligned features aligned in the above map feature matching step (S255). In Article 11, The above driving control step (S30) is: An initial VPS location information confirmation step (S31) in which the above VPS location information is received at the start of driving and the current location information is confirmed, A driving drive step (S33) for executing driving drive control so that the above mobile robot unit (20) can drive to the destination, At the same time as the driving drive is executed, a driving position estimation step (S35) is executed to execute a precise position estimation by comparing and matching the surrounding environment distance measurement information executed through the sampling range and the feature information using the VPS position information signal based on the integrated map, and A VPS integrated mobile robot unit control method characterized by including an arrival confirmation step (S35) for confirming whether the above mobile robot unit (20) has reached the destination. In Article 16, The above driving position estimation step (S35) is: A sampling range scan step (S351) for executing distance measurement with the sampling range through the distance measurement sensor (213) of the unit detection unit (21) to produce distance measurement information of the surrounding environment, A driving matching step (S353) for extracting feature information using the above integrated map and the surrounding environment distance measurement information, performing matching while driving using the feature information calculated during driving, and deriving current location information; A VPS location information verification step (S355) for checking the updated VPS location information, A precision alignment step (S357) for verifying the precision of the current location information using the current location information derived from the above driving alignment step (S353) and the above VPS location information, A VPS integrated mobile robot unit control method characterized by including a precision position update step (S359) for updating the current position information with new driving position information of the mobile robot unit (20) when the precision of the current position information is confirmed in the precision alignment step (S357). In Article 17, A VPS integrated mobile robot unit control method, characterized in that the update cycle of the VPS location information signal used in the estimated location calculation unit (2235) is longer than the update cycle of the distance measurement feature information. In Article 17, A VPS integrated mobile robot unit control method, characterized in that the above sampling range is at least one of a circular range, an elliptical range, and an arc range when projected onto the ground. In Article 19, A VPS integrated mobile robot unit control method characterized in that the above sampling range is formed and selected to reflect the steering angle of the mobile robot unit (20). A plurality of mobile robot units (20), It includes a mobile robot managing server (10) that provides a driving path including a destination to which the above mobile robot unit (20) drives and manages the driving. The mobile robot unit (20) that transmits and receives data including driving information from the mobile robot managing server (10) comprises a unit storage unit (23) that stores an integrated map that links a grid map and a VPS map, and a unit control unit (22) that compares and matches surrounding environment distance measurement information executed through a sampling range that can be changed according to the kinematic driving type of the unit driving unit (28) based on the integrated map and a VPS position information signal calculated from surrounding environment image information to execute precise position estimation. The VPS integrated mobile robot system (1) is characterized by: In Article 21, The above mobile robot managing server (10): An operation control unit (11) that controls and manages the driving along the reference path of the above mobile robot unit (20), A VPS integrated mobile robot system (1), characterized by including a map generation unit (13) that generates the above integrated map. In Article 22, The above map generation unit (13): A VPS map verification unit (131) that verifies the VPS map for the surrounding environment in which the above mobile robot unit (20) is to drive, A grid map verification unit (133) that verifies the grid map of the surrounding environment in which the above mobile robot unit (20) is to drive, A VPS integrated mobile robot system (1) characterized by including a map integration unit (135) that extracts, compares, and matches map features from the above grid map and VPS map. In Article 23, The above VPS map verification unit (131) is: An image verification unit (1311) that verifies an image of the surrounding environment in which the above mobile robot unit (20) is to drive, A visual feature extraction unit (1313) that extracts visual features from the above image, A VPS integrated mobile robot system (1), characterized by including a VPS map generation unit (1315) that generates a VPS map linking an image of the surrounding environment and the visual features. In Article 23, The above map integration unit (135) is: A map feature extraction unit (1351) for extracting and confirming grid map features and visual map features of the above grid map and the above VPS map, A map feature matching unit (1353) that compares and matches the grid map features and visual map features using the ICP algorithm, A VPS integrated mobile robot system (1) characterized by including an integrated map verification unit (1355) that generates an integrated map in which the grid map and the VPS map are linked and integrated based on matching matching features.

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