KR20230092422A - System for generation of indoor map, autonomous robot and method for creating indoor map using multi-robot - Google Patents

Abstract

The present invention relates to an autonomous robot, a local map generation method of an autonomous robot, and an indoor map generation method using a plurality of autonomous robots, which can shorten the time for generating a map for a wide space. The local map generation method of a robot is configured to search a mapping area corresponding to mapping area information at a pre-set initial location when the mapping area information to generate a local map is received from the indoor map generation system, and collect surrounding environment information based on the initial location to mark the information on an occupancy grid map The local map generation method of a robot is configured to extract a plurality of points corresponding to a division surface of a detected area and a non-detected area on the occupancy grid map on which the surrounding environment information is marked to form the points as a point group, and set a central point extracted from the point group as a next driving destination to move from the initial location. The local map generation method of a robot is configured to mark the surrounding environment information collected while moving to the next driving destination on the occupancy grid map to generate a local map.

Description

An autonomous robot, a method for generating a regional map of an autonomous robot, and a method for generating an indoor map using a plurality of autonomous robots {System for generation of indoor map, autonomous robot and method for creating indoor map using multi-robot}

The present invention relates to an autonomous robot in which a plurality of autonomous robots create an indoor map using a segmentation mapping strategy and a map synthesis method, a method for generating a region map of an autonomous robot, and a method for generating an indoor map using a plurality of autonomous robots. it's about

As the self-driving service robot market gradually expands, self-driving robots are applied and used in various fields. In particular, it is time to easily access self-driving robots used in factories or distribution centers, as well as self-driving robots that provide daily services in hotels and restaurants.

As the robot market expands in this way, there are naturally many places that operate two or more robots in one place. Therefore, research on technology for the efficient operation of multi-robots is also expanding.

In order for self-driving robots to provide quality service in indoor spaces, they must move stably in consideration of their surroundings and their location. While driving using SLAM (Simultaneous Localization and Mapping), an autonomous robot senses the surrounding space with a sensor to estimate its own location and create a map for the detected space.

At this time, through SLAM, the self-driving robot can map the space on its own. However, when mapping with a single robot, mapping takes a lot of time in proportion to the size of the space to be mapped. In addition, when a person maps a space by manually manipulating the self-driving robot or pushing the self-driving robot, map loss or errors may occur.

In particular, in a space with a large area (for example, a hotel or a distribution center), a situation arises in which a new space needs to be mapped on a map or a space already mapped on a map needs to be modified according to the characteristics of the space. Therefore, the method of mapping with a single robot is inefficient, and in the case of mapping a multi-story building, a long time of one week or more is consumed.

On the other hand, when a robot cleaner travels on its own in a home and creates a map, the space of the house is narrow and the robot cleaner is equipped with a bumper, so the map can be created without any major problems. However, if a serving robot in a restaurant or a hotel service robot put into a hotel collides with a wall or a customer/employee while driving through a restaurant or hotel to create a map by itself, there is a risk of injury to the customer or damage to the robot.

In addition, because the created map is shared with other robots and used together, precise scans are required, and path planning to scan the space is important. In particular, a method of detecting the map boundary and setting the movement coordinates in the corresponding area requires a lot of research.

Therefore, in the present invention, a specific place is divided into a plurality of spaces, a plurality of self-driving robots create and share maps of different spaces, and each self-driving robot separates a mapped space from a non-mapped space to route It provides an autonomous robot that plans itself, a method for generating a local map of the autonomous robot, and a method for generating an indoor map using a plurality of autonomous robots.

As a method for generating a region map of a robot, which is one feature of the present invention for achieving the technical problem of the present invention,

Receiving mapping area information to generate a local map from an indoor map generating system at a preset initial location, searching for a mapping area corresponding to the mapping area information, and collecting and occupying surrounding environment information based on the initial location displaying on a grid map, forming a point group by extracting a plurality of points corresponding to the boundary between the detection area and the undetected area on the occupied grid map on which the surrounding environment information is displayed, extracting the center point of the point group and setting the extracted center point as the next driving destination to be moved from the initial location, and displaying the surrounding environment information collected while moving to the next driving destination on the occupancy grid map to generate the area map. do.

In the forming of the point groups, points of the boundary surface may be extracted based on a topic message on the occupied grid map and a topic message indicating a mapping range included in the mapping area information.

The displaying on the occupied grid map may include setting an arbitrary node at an arbitrary location in the mapping area based on the initial location, detecting a node closest to the arbitrary node, and The method may further include generating a new node between the closest nodes, and expanding the tree by including the new node in a tree when there is no obstacle around the robot.

After the step of including the new node in the tree, checking whether the new node is the next driving destination, and ending expansion of the tree if the new node corresponds to the next driving destination.

The step of setting as the next driving destination may include filtering at least one point located outside the bandwidth, which is a scan range of the robot, and extracting remaining points located inside the bandwidth excluding the filtered points as candidate center points. and setting one of the candidate center points as the next driving destination.

In the setting of the next driving destination, the next driving destination may be set through a gain calculation of each of the candidate center points.

As another feature of the present invention for achieving the technical problem of the present invention, an indoor map generation system in conjunction with a plurality of robots generates an indoor map,

Receiving area information obtained by dividing an indoor space into a plurality of areas so that the plurality of robots create area maps, respectively; Transmitting the received area information to the plurality of robots; Receiving regional maps generated by a plurality of robots, and generating one indoor map by merging the regional maps.

The generating of the indoor map may include checking whether all area maps have been received from the plurality of robots, and if the area map has not been transmitted from a specific robot, information on the area allocated to the specific robot and detection by the specific robot It may include identifying an undetected area within the area to be detected, and reallocating the undetected area so that a partial area of the undetected area is detected by one robot among at least one robot located in the waiting area. there is.

In the reallocating of the undetected area, an area outside the sensing range of the specific robot among the undetected areas may be reallocated to the one robot.

As another feature of the present invention for achieving the technical problem of the present invention, a robot that generates a local map during autonomous driving,

It includes an interface for receiving mapping area information from an interlocked indoor map generating system, a sensor for detecting a mapping area included in the mapping area information, and a processor, wherein the processor searches for the mapping area and displays an occupied grid map. Environment information is displayed, points on the boundary between the detection area and the undetected area are extracted based on the occupancy grid map to form a point group, and the center point extracted from the point group is set as the next driving destination.

The processor may extract a point of the boundary surface based on a topic message on the occupancy grid map and a topic message indicating a mapping range included in the mapping area information.

The processor may sample an arbitrary node among a plurality of nodes around the initial position based on the initial position, detect a node closest to the arbitrary node, and then create a new node between the arbitrary node and the nearest node. there is.

The processor may extend the tree by including the new node in the tree when there is no obstacle around the robot.

The processor filters at least one point included outside the bandwidth, which is the scannable range of the robot, extracts points other than the filtered points as candidate center points, and calculates a gain of any one of the candidate center points. The center point may be set as the next driving destination.

According to the present invention, by using a plurality of robots to create regional maps of a large place divided into several spaces, and synthesizing the plurality of regional maps into one global map, an indoor map, the map production time for a large space is reduced. can be shortened

In addition, since the robot can plan its own path by dividing the mapped space from the non-mapped space, the space can be efficiently mapped.

1 is an exemplary view of an environment in which multiple robots generating an indoor map are applied according to an embodiment of the present invention.
2 is a flowchart of a method for generating a global map according to an embodiment of the present invention.
3 is a flowchart of an operation method in which multiple robots operate to generate a region map according to an embodiment of the present invention.
4 is an exemplary view of a mapping area search method according to an embodiment of the present invention.
5 is an exemplary view of a center point detected according to an embodiment of the present invention.
6 is an exemplary view showing a next driving destination according to a route plan according to an embodiment of the present invention.
7 is an exemplary diagram of kernel density estimation used in accordance with an embodiment of the present invention.
8 is an exemplary view of obtaining a scan gain according to an embodiment of the present invention.
9 is an exemplary view of a global map created according to an embodiment of the present invention.
10 is an exemplary diagram in which a mapping range is reset to a robot according to an embodiment of the present invention.
11 is a structural diagram of a robot according to an embodiment of the present invention.

Hereinafter, with reference to the accompanying drawings, embodiments of the present invention will be described in detail so that those skilled in the art can easily carry out the present invention. However, the present invention may be embodied in many different forms and is not limited to the embodiments described herein. And in order to clearly explain the present invention in the drawings, parts irrelevant to the description are omitted, and similar reference numerals are attached to similar parts throughout the specification.

Throughout the specification, when a certain component is said to "include", it means that it may further include other components without excluding other components unless otherwise stated.

Hereinafter, an indoor map creation method using an indoor map generation system, an autonomous robot, and a multi-robot according to an embodiment of the present invention will be described in detail with reference to the drawings.

1 is an exemplary view of an environment in which multiple robots generating an indoor map are applied according to an embodiment of the present invention.

As shown in FIG. 1 , multiple self-driving robots (hereinafter referred to as 'robots') 100 - 1 to 100 - 4 are located in the indoor space 10 . In the embodiment of the present invention, for convenience of description, when using an expression collectively referring to each of the robots 100-1 to 100-4, the term is expressed as 'multiple robots' and the reference numeral is indicated as '100'.

The indoor space 10 may be divided into a plurality of areas. In the embodiment of the present invention, the indoor space 10 is described as being divided into four areas 10-1 to 10-4 as an example, but is not necessarily limited thereto. Dividing the indoor space 10 into a plurality of areas can be executed by a manager or a user, and the criteria for dividing the areas is not limited to any one.

Each of the robots 100-1 to 100-4 creates a regional map while driving in the respectively assigned areas 10-1 to 10-4. In addition, each robot (100-1 to 100-4) interworks with the indoor map generation system 200, and each area (10-1 to 10-4) created by each robot (100-1 to 100-4) The area map generated while driving is transferred to the indoor map generating system 200 . The indoor map generation system 200 receives a plurality of local maps, synthesizes them into one global map, and uses the synthesized global map as an indoor map.

Here, as an example, the robots 100-1 to 100-4 stand by at a preset waiting position 20 of the indoor space 10 until the areas 10-1 to 10-4 for generating a region map are allocated. to explain. In the embodiment of the present invention, the waiting position 20 corresponds to the center of the indoor space 10 as an example, but is not limited thereto.

In addition, when the robots 100-1 to 100-2 complete the generation of area maps in the respectively assigned areas 10-1 to 10-4, each robot 100-1 to 100-2 is placed in a standby position 20 ) and may wait until the other robots 100-1 to 100-2 complete regional map generation.

Each of the robots 100-1 to 100-4 travels in the respective assigned area 10-1, senses the surrounding area using a sensor, and then creates a local map. The area map is created in the form of an occupancy grid map, and when the robot 100 displays a detection area (eg, a drivable area, a non-drivable area, etc.) on the occupancy grid map, the area map is generated.

The robots 100-1 to 100-4 extract boundary points in the process of generating regional maps. The boundary point refers to the boundary between the detection area and the undetected area on the occupancy grid map.

The robots 100-1 to 100-4 check the boundary point and select the next driving destination based on the boundary point. When selecting the next driving destination, the robots 100-1 to 100-4 extract the center point of the boundary point, calculate the mapping gain and path gain based on the extracted center point, and select the center point with the highest value as the next driving destination. select as This will be described in detail later.

In the environment described above, see FIG. 2 for a method in which the plurality of robots 100-1 to 100-4 generate regional maps and the indoor map generating system 200 generates a global map using the regional maps. be explained by

2 is a flowchart of a method for generating a global map according to an embodiment of the present invention.

As shown in FIG. 2 , if an area for creating a regional map is mapped, the multi-robot 100 waits in a predetermined area within the mapped area. However, the multi-robot 100 first put into the indoor space 10 waits at the preset standby position 20 until area information is received from the indoor map generating system 200 (S100).

That is, when the preliminary space information is mapped to the multi-robot 100, the initial position of the multi-robot 100 waits in the center of the mapped space. This case corresponds to a case in which a region map of a corresponding region is updated for reasons such as movement or change of an internal structure in a region where mapping has been previously completed and information such as spatial structures and obstacles is known.

On the other hand, if the multi-robot 100 does not have prior space information, the multi-robot 100 waits until an area is mapped at a predetermined location, such as around a doorway. At this time, in order to prevent collisions that may occur while the multi-robot 100 is moving and to prevent overlapping of areas occupied by the multi-robot 100, the interval between each robot 100-1 to 100-4 is set to 1 m. Setting will be described as an example. Here, the distance between the robots 100-1 to 100-4 depends on the size of the robots 100-1 to 100-4 and the recognition range of the sensors, which are information collection means mounted on the robots 100-1 to 100-4. may be set differently.

In the embodiment of the present invention, a case where the multi-robot 100 is initially introduced into the indoor space 10 will be described as an example.

The indoor map generating system 200 visualizes a map of the indoor space 10 into which the multi-robot 100 is input, and provides the map to a manager who manages the multi-robot 100 and the indoor map generating system 200 . Then, when the manager divides the indoor space 10 in which the multi-robot 100 will create a local map into a plurality of areas, the indoor map generating system 200 receives information on a plurality of areas of the indoor space (S101). .

At this time, in the embodiment of the present invention, the administrator determines the robots 100-1 to 100-4 to create a regional map in each region as an example. That is, the indoor map generating system 200 generates area information input by a manager in which the indoor space 10 is divided into a plurality of areas 10-1 to 10-4, and each area 10-1 to 10-4. When receiving the identification information of the robots 100-1 to 100-4 to generate the area map, the mapping area information including the area information and the identification information of the robots 100-1 to 100-4 is sent to the robot 100-100-1. 1 to 100-4) (S103).

Based on the mapping area information received in step S102, the multi-robot 100 checks the area to which the robots 100-1 to 100-4 themselves are mapped to create a regional map. Then, the robots 100-1 to 100-4 generate regional maps respectively while driving in each area (S103), and transmit the generated regional maps to the indoor map generating system 200 (S104). At this time, all of the robots 100-1 to 100-4 may or may not complete the region map generation at the same time.

Accordingly, the indoor map generation system 200 synthesizes the regional maps transmitted from the multi-robot 100 in step S104 to generate a global map (S105). The indoor map generation system 200 checks whether area maps have been received from all robots 100-1 to 100-4 (S106), and if all area maps have been received, the global map generated in step S106 is converted to multiple robots 100. ) (S107). However, if there are robots 100-1 to 100-4 for which some area map generation has not been completed, the indoor map generation system 200 moves the robots 100-1 to 100-4 that have completed area map generation, A procedure for reallocating the work areas of the multi-robot 100 is performed so that a region map can be created by inputting into the mapping areas of the robots 100-1 to 100-4 that have not completed map creation (S108).

At this time, a method for the multi-robot 100 to generate a region map in step S103 will be described with reference to FIG. 3 .

3 is a flowchart of an operation method in which multiple robots operate to generate a region map according to an embodiment of the present invention.

As shown in FIG. 3, when the multi-robot 100 receives mapping area information from the indoor map generating system 200 (S200), it collects environmental information about the surrounding environment using an information collecting means based on the current location. Collect (S201).

The environment information collected by the multi-robot 100 includes dynamic object information and static object information, and since the method for collecting environment information by the information collection unit is a known technology, the embodiment of the present invention is limited to one method. I never do that. Further, in the embodiment of the present invention, an example in which a LiDAR (Light Detection And Ranging) sensor is used as an information collection means is described, but is not necessarily limited thereto.

The multi-robot 100 displays environment information on the occupancy grid map (S202). After displaying on the occupied grid map, the multi-robot 100 extracts the boundary between the detected area and the undetected area based on the occupied grid map (S203). In order for the multi-robot 100 to extract the boundary between the detected area and the undetected area, the manager sets the topic message '/robot_N/gridmap' in the form of an occupied grid map using the detection module implemented in the multi-robot 100. The point of the boundary is extracted by subscribing to the topic message 'local_renged_point_N' indicating a mapping range.

At this time, the technique of dividing the detection area and the non-detection area based on the occupied grid map by the multi-robot 100 is a known technology. That is, among the ROS packages provided by the open source-based robot middleware, a method of extracting a boundary surface based on a RRT (Rapidly-exploring Random Tree) algorithm, which is a kind of path search and planning method, can be used.

RRT creates a random point in space through a sampling process, and grows a tree using the created random point as a target point. The multi-robot 100 gradually grows the tree by adding a new node of the tree within the already detected area.

At this time, when the node added by the multi-robot 100 is created in the undetected area, the multi-robot 100 detects a point on the boundary of the corresponding node. The boundary point obtained by the detection module through this process is transmitted to the multi-robot 100 in a preset message standard, and the multi-robot 100 receiving the topic message delivered in the message standard is referred to as subscription.

After extracting the boundary surface through step S203, the multi-robot 100 checks the point group of the boundary surface and extracts a center point from the checked point group (S204). The multi-robot 100 extracts the center point of a group of points on the boundary surface through a mean shift method, and the mean shift method is a known technique and detailed description is omitted in the embodiment of the present invention.

Then, the multi-robot 100 sets the extracted central point as the next driving destination to be moved from the current location (S205). The multi-robot 100 moves to the driving destination after setting in step S205 (S206), and repeats the procedure after step S201 of collecting surrounding environment information in the moved area.

The multi-robot 100 repeatedly performs the procedure after step S201 until all mapped mapping areas are detected. And until all mapping areas are detected, the occupied grid map on which the multi-robot 100 displays environment information is used as the area map.

In the process of generating the region map by the above-described multi-robot 100, a method of searching for a mapping region according to step S203 and extracting a boundary point between an undetected region and a detected region on an occupied grid map is described with reference to FIG. 4 . Explain.

4 is an exemplary view of a mapping area search method according to an embodiment of the present invention.

As shown in FIG. 4, assuming that the multi-robot 100 is located at a point indicated as an initial node, the corresponding location is referred to as a start node (x _init ). In the embodiment of the present invention, the meaning of "node" means the coordinates of the multi-robot 100.

The multi-robot 100 samples a random node (x _rand ) among a plurality of nodes around the multi-robot 100 based on the starting node. That is, a random point in the space to be searched by the multi-robot 100 is created.

The multi-robot 100 detects the closest node (x _nearest ) in distance from the sampled random node, and creates a new node (x _new ) between the random node and the nearest node.

And, if there are no obstacles around the multi-robot 100, the multi-robot 100 includes the newly created node in the tree. Then, the tree is grown by repeating the same process until the new node becomes the next destination (x _target ). If the mapping area search method is expressed as a program, it is shown in Table 1 below.

V ← X _init ; E ← Φ
while x _new ≠ x _target do
x _rand ← SampleFree;
x _nearest ← Nearest(G(V, E), x _rand );
x _new ← Steer(x _nearest , x _rand );
if ObstacleFree(x _nearest , x _new ) then
V ← V ∪ {x _new }; E ← E ∪ {(x _nearest , x _new )};
End if
End while
Return G = (V, E);

Here, V denotes a node, and E denotes a set of nodes generated while growing the tree. The nodes included in the set become a point candidate group that the multi-robot 100 refers to when planning a path. The mapping area search method will be described in detail, as shown in (a) of FIG. 4, the multi-robot 100 In the process of exploring the mapping area of , the starting node, which is the initial node of the Rapidly Exploring Random Tree (RRT) tree, is set in the occupied grid map. The multi-robot 100 corrects the set start node to the current position (x _current ) of the robot.

As shown in (b) of FIG. 4, the multi-robot 100 extends the scan area by increasing the length of the tree as shown in the first display line ① while adding a new node within the already scanned area. At this time, when a new node is created in the undetected area, the multi-robot 100 records the location of the new node created in the undetected area, and removes a point (Frontier) corresponding to the boundary between the detection area and the undetected area. 2 Detected in the same way as display means (②).

After the multi-robot 100 detects the point of the boundary surface, the central point for the multi-robot 100 to travel is detected through filtering. This will be described with reference to FIG. 5 .

5 is an exemplary view of a center point detected according to an embodiment of the present invention.

As shown in (a) of FIG. 5, the multi-robot 100 checks the boundary point with the second display means (②), and checks the bandwidth with the third display means (③). Here, the bandwidth means a range that can be scanned when multiple robots 100 are located in a corresponding node.

The multi-robot 100 filters the points searched for outside the bandwidth indicated by the third display means (③), and extracts the same center point as the fourth display means (④) as shown in FIG. 5 (b). Here, the center point may be extracted to a different position according to the characteristics of the multi-robot 100 (eg, size of the robot, sensing range, etc.).

After extracting a plurality of center points, the multi-robot 100 selects a center point corresponding to the next driving destination through a gain calculation process among the extracted center points. In addition, the multi-robot 100 plans a route to move from the current location to the center point corresponding to the next driving destination. This will be described with reference to FIG. 6 .

6 is an exemplary view showing a next driving destination according to a route plan according to an embodiment of the present invention.

As shown in FIG. 6 , the multi-robot 100 selects the next driving destination by using a clustering algorithm in the process of selecting the next driving destination from the current location.

)라고 가정하면, 다중 로봇(100)은 추출한 복수의 중심점들 중 밀도가 가장 높은 쪽인 위치(

, … ,

)로 이동하면서 군집화를 수행한다. 이때, 다중 로봇(100)은 데이터의 대표점을 추출하는 군집화 알고리즘인 평균 이동(Mean Shift)을 이용하여, 중심점들이 모여 있는 밀도가 가장 높은 쪽으로 평균을 이동하면서 군집화를 수행한다. 이를 통해 다중 로봇(100)은 이동할 수 있는 중심점을 찾을 수 있고, 불필요한 동선으로 이동하지 않도록 경로 계획을 최소화할 수 있다.That is, the current position of the multi-robot 100 is the first position (

), the multi-robot 100 has the highest density among the extracted plurality of center points (

, … ,

) to perform clustering. At this time, the multi-robot 100 performs clustering while moving the average to the side with the highest density where the central points are gathered using mean shift, which is a clustering algorithm that extracts representative points of data. Through this, the multi-robot 100 can find a movable central point, and can minimize route planning so as not to move in an unnecessary movement line.

At this time, the multi-robot 100 finds a probability density function using Kernel Density Estimation (KDE) in order to use the average movement. This will be described with reference to FIG. 7 .

7 is an exemplary diagram of kernel density estimation used in accordance with an embodiment of the present invention.

As shown in FIG. 7 , in kernel density estimation, a probability density function f(x) for a random variable x is estimated by Equation 1.

In Equation 1, x ₁ , x ₂ , … , x _n are coordinates acquired in the process of scanning the surroundings of the multi-robot 100, and K means a kernel function. A kernel function centered on each coordinate obtained by scanning the multi-robot 100 is generated, and the kernel density is estimated by dividing by the total number of coordinates after adding all the kernel functions.

Next, a process of obtaining a scan gain by the multi-robot 100 will be described with reference to FIG. 8 .

8 is an exemplary view of obtaining a scan gain according to an embodiment of the present invention.

As shown in FIG. 8 , the multi-robot 100 obtains a scan gain by calculating an information gain and a navigation cost of the center point of the boundary surface. Here, the information gain is obtained by calculating the number of cells in the unexplored area after forming a radius circle of a sensor, which is an information collection means mounted on the multi-robot 100, based on the center point of the boundary surface.

That is, a goal for the multi-robot 100 to search a space is to plan a path to a point with a high scan gain. At this time, the scan gain is calculated by calculating the information gain and navigation cost of the center point of the boundary surface.

The multi-robot 100 obtains an information gain by calculating the number of cells in the unexplored area by forming a circle with a sensor radius based on the center point of the boundary surface. As the number of unexplored regions increases, the information gain is calculated to be higher. When a point having a high information gain is acquired, the obtained point is designated as a destination of the multi-robot 100, and the multi-robot 100 calculates a navigation cost to the destination.

Then, the multi-robot 100 obtains a navigation cost through a norm operation targeting the current position of the multi-robot 100 and the center point of the boundary surface. In this way, the multi-robot 100 calculates an information gain and a navigation cost to plan an optimal route for space search, performs route planning to set the next driving destination, and moves to the next driving destination based on the route planning. move

Next, an example of generating a global map using the regional maps generated by each of the robots 100-1 to 100-4 will be described with reference to FIG. 9 .

9 is an exemplary view of a global map created according to an embodiment of the present invention.

As shown in FIG. 9 , the indoor map generation system 200 receiving regional maps generated by each of the plurality of robots 100-1 to 100-4 merges the regional maps to generate a single global map. . To this end, the indoor map generating system 200 defines nodes and topics of the map synthesizing module as shown in Table 2 below, and generates a plurality of regional maps as one global map by using them.

Since the indoor map generating system 200 uses the topics defined in Table 2 to merge a plurality of local maps into an indoor map, which is a global map, it can be performed using an open package such as the multirobot_map_merge package. In the examples, description is not limited to any one method.

Class Name Message_Type node Map_merge Topic(publish) /map Nav_msgs/occupancyGrid.msg Topic (subscriber) /robot_N/map Nav_msgs/occupancyGrid.msg

Next, an example in which the indoor map generation system 200 resets the mapping range of the multi-robot 100 will be described with reference to FIG. 10 .

10 is an exemplary diagram in which a mapping range is reset to a robot according to an embodiment of the present invention.

As shown in FIG. 10, robots 100-1 and 100-2 that have completed generating area maps are waiting in the initial waiting area 20, and robots 100-3 and 100 that have not completed generating area maps -4) Suppose you are creating a local map in this mapping area.

Then, the indoor map generation system 200 checks the undetected area of the third robot 100-3 (⑤), and some areas of the undetected area according to the sensing range of the third robot 100-3 (⑥). ) adjusts the range so that the third robot 100-3 continuously detects. The remaining area (⑦) is set to be detected by the first robot 100-1 waiting in the waiting area 20, and mapping area information is provided to the first robot 100-1.

Next, the structure of the robot will be described with reference to FIG. 11 .

11 is a structural diagram of a robot according to an embodiment of the present invention.

As shown in FIG. 11, the robot 300 includes a processor 310 communicating through a bus 320, a memory 330, an information collection unit 340, an interface 350, a storage device 360, and driving Device 370 is included.

The processor 310 is a device for controlling the operation of the robot 300, and may be various types of processors that process commands included in a program, for example, a Central Processing Unit (CPU) or a Micro Processor Unit (MPU). , MCU (Micro Controller Unit), GPU (Graphic Processing Unit), and the like. Alternatively, the processor 310 may be a semiconductor device that executes commands stored in the memory 330 or the storage device 160 . Processor 310 may be configured to execute the functions and methods described above.

The memory 330 may include various types of volatile or non-volatile storage media. For example, memory 330 loads corresponding programs so that instructions described to execute the operations of the present invention are processed by processor 310, and read only memory (ROM) 331 and random access memory (RAM) (332).

In an embodiment of the present invention, the memory 330 may be located inside or outside the processor 310, and the memory 330 may be connected to the processor 310 through various known means.

The information collection unit 340 includes various sensors (eg, lidar, depth camera, inertial measurement unit (IMU), etc.) through which the robot 300 traveling according to the operation of the present invention collects information. corresponds to In an embodiment of the present invention, the use of lidar as the sensor 340 is described as an example, but is not necessarily limited thereto.

The interface 350 interworks with the indoor map generating system 200 and transfers the area map generated by the robot 300 to the indoor map generating system 200 . In addition, the interface 350 may receive mapping area information and a global map transmitted from the indoor map generation system 200 and transmit them to the processor 310 .

The storage device 360 may store a region map of a space in which the robot 300 travels. Also, the storage device 360 stores the global map received from the indoor map generating system 200 .

The driving device 370 drives the robot 300 in the mapping area under the control of the processor 310 .

Although the embodiments of the present invention have been described in detail above, the scope of the present invention is not limited thereto, and various modifications and improvements made by those skilled in the art using the basic concept of the present invention defined in the following claims are also included in the scope of the present invention. that fall within the scope of the right.

Claims (14)

As a method for generating a region map of a robot,
Receiving mapping area information to generate a local map from an indoor map generating system at a preset initial location;
Searching for a mapping area corresponding to the mapping area information, collecting surrounding environment information based on the initial location, and displaying it on an occupancy grid map;
Forming a point group by extracting a plurality of points corresponding to a boundary between a detection area and an undetected area on the occupied grid map on which the surrounding environment information is displayed;
extracting the center point of the point group, and setting the extracted center point as the next driving destination to be moved from the initial location; and
Displaying the surrounding environment information collected while moving to the next driving destination on the occupancy grid map to create the area map
Including, how to create a region map of the robot. According to claim 1,
The step of forming the point group,
A method for generating an area map of a robot, wherein a point of the boundary surface is extracted based on a topic message on the occupancy grid map and a topic message indicating a mapping range included in the mapping area information. According to claim 2,
The step of displaying on the occupied grid map,
Setting an arbitrary node at an arbitrary position in the mapping area based on the initial position;
Detecting a node closest to the arbitrary node, and creating a new node between the arbitrary node and the closest node, and
Expanding the tree by including the new node in the tree when there is no obstacle around the robot
Further comprising a method for generating a region map of the robot. According to claim 3,
After the step of including the new node in the tree,
Checking whether the new node is the next driving destination, and terminating expansion of the tree if corresponding to the next driving destination
Including, how to create a region map of the robot. According to claim 4,
In the step of setting the next driving destination,
Filtering at least one point located outside of a bandwidth that is a scannable range by the robot;
Extracting remaining points located inside the bandwidth, excluding the filtered points, as candidate center points; and
Setting one of the candidate center points as the next driving destination
Including, how to create a region map of the robot. According to claim 5,
In the step of setting the next driving destination,
A method for generating a region map of a robot, which is set as the next driving destination through a gain calculation of each of the candidate center points. A method for generating an indoor map by an indoor map generation system linked with a plurality of robots,
Receiving area information dividing an indoor space into a plurality of areas so that the plurality of robots respectively create a area map;
Transmitting the received area information to the plurality of robots;
Receiving regional maps generated by each of the plurality of robots based on the region information; and
merging the local maps to create one indoor map;
Including, indoor map generation method. According to claim 7,
The step of generating the indoor map,
Checking whether all area maps have been received from the plurality of robots;
If a region map is not transmitted from a specific robot, checking region information allocated to the specific robot and an undetected region within the region detected by the specific robot; and
Re-allocating the undetected area so that a partial area of the undetected area is detected by one of at least one robot located in the waiting area.
Including, indoor map generation method. According to claim 8,
The step of reallocating the undetected area,
An indoor map generation method of reallocating an area outside the sensing range of the specific robot among the undetected areas to the one robot. As a robot that creates a local map during autonomous driving,
An interface for receiving mapping area information from an interlocked indoor map generation system;
A sensor detecting a mapping area included in the mapping area information; and
processor
including,
the processor,
The mapping area is searched, environment information is displayed on the occupied grid map, points on the boundary between the detection area and the undetected area are extracted based on the occupancy grid map, and a point group is formed, and the center point extracted from the point group is A robot set to the next driving destination. According to claim 10,
the processor,
The robot extracts a point of the boundary surface based on a topic message on the occupancy grid map and a topic message indicating a mapping range included in the mapping area information. According to claim 11,
the processor,
A robot that samples a random node among a plurality of nodes around the initial position, detects a node closest to the random node, and then creates a new node between the random node and the nearest node. According to claim 12,
the processor,
When there is no obstacle around the robot, the robot includes the new node in the tree to expand the tree. According to claim 13,
the processor,
At least one point included outside the bandwidth, which is the scannable range of the robot, is filtered, points other than the filtered points are extracted as candidate center points, and any one center point among the candidate center points is selected as the next center point through gain calculation. A robot to set as a driving destination.

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