KR20220152464A - method of generating sterilizing and pollution measurement work path for mobile robot - Google Patents

Abstract

The present invention relates to a method for generating a sterilizing and pollution measurement work path for a mobile robot. The method comprises the steps of: selecting a work area, in which a mobile robot works, for a drawing created in AutoCAD and loaded; creating an obstacle map for a recognized obstacle within a shape space for the selected work area; creating intermediate target points for creation of primary sterilizing and pollution measurement path for the work area by using obstacle information; creating the primary sterilizing and pollution measurement path by using the intermediate target points; creating a collision avoidance path for avoidance of collision with the obstacle by using the obstacle map and mobile robot information when there is a path in which collision with the obstacle occurs on the primary sterilizing and pollution measurement path; and creating a final sterilizing and pollution measurement path for the mobile robot by reflecting the created collision avoidance path to the primary sterilizing and pollution measurement path. The mobile robot having a pollution measurement sensor for measuring pollution and a disinfector capable of spraying disinfectant is used. Therefore, the method can set the work area by using the drawing, created in AutoCAD, as it is, and can easily calculate the path for performing sterilizing and pollution measurement while avoiding collision with the obstacle so that the mobile robot can travel therealong.

Description

{method of generating sterilizing and pollution measurement work path for mobile robot}

The present invention relates to a method for generating a disinfection and contamination measurement work path of a mobile robot, and more particularly, to a method for disinfection and contamination measurement of a mobile robot to generate a disinfection and contamination measurement route for the mobile robot to work using a drawing made in AutoCAD and It relates to a method for creating a contamination measurement work path.

In recent years, the application of robots has been expanded from the use in factories to the use of general tasks. In particular, these days when corona virus and fine dust environmental pollution are intensifying, robotization for tasks such as disinfection and pollution measurement of large buildings and public facilities through mobile robots is strongly demanded and researched. The path planning for this task requires a motion plan to walk around the empty space of the two-dimensional surface area, which is the work area, and it is called disinfection and contamination measurement path plan. The operation planning method for disinfection and contamination measurement work is largely divided into an on-line method and an off-line method. The online method is a method in which the robot moves around the work area and recognizes the work environment with a sensor and directly reflects it in the action. However, since this online work method does not use the entire map during work, the robot cannot guarantee the completion of disinfection and contamination measurement tasks within a given time, and its work ability depends on the shape of the environment. In addition, there is a problem of falling into a dead-lock phenomenon that hovers in the same area depending on the obstacle environment. Due to this problem, most existing robots that actually perform plastering work have only the function of repeating a certain motion pattern, and are semi-automatic types controlled by the operator, which is a function. The off-line method is a method of creating disinfection and contamination measurement work routes under the assumption that information about the working environment is known. As a study on the automatic generation of disinfection and contamination measurement work paths, there is a method proposed by D.Kurabashi et al. This is a method of applying the Voronoi diagram for route planning. This method does not create a collision-free path in the Voronoi diagram, but rather as a centerline or point connection between the obstacle and the workspace in Cartesian coordinates, so the generated path is not too close to the obstacle. When an actual robot is driven, a problem may arise in which the path control must be elaborated, and in some cases, the actual robot cannot go on the created non-collision path between obstacles.

The present invention was invented to improve the above problems, and provides a method for generating a disinfection and contamination measurement work path of a mobile robot that can easily create a disinfection and contamination measurement route while avoiding obstacles from work environment map drawing information. But it has a purpose.

Another object of the present invention is to provide a method for generating a disinfection and contamination measurement work path for a mobile robot that can easily create a disinfection and contamination measurement work route using a drawing prepared in AutoCAD.

In order to achieve the above object, a method for generating a disinfection and contamination measurement work path of a mobile robot according to the present invention is a. Selecting a work area for a mobile robot to work on a drawing prepared and loaded in AutoCAD; me. generating an obstacle map for obstacles recognized in the shape space for the selected work area; All. generating an intermediate target point for generating a primary disinfection and contamination measurement path for the work area by using the obstacle information; la. generating the primary disinfection and contamination measurement path using the intermediate target points; mind. generating a collision avoidance path for collision avoidance with an obstacle when there is a path in which a collision with an obstacle occurs on the primary disinfection and contamination measurement path using the obstacle map and the mobile robot information; bar. generating a final disinfection and contamination measurement work path for the mobile robot by reflecting the collision avoidance path generated in step D on the primary disinfection and contamination measurement path, wherein the mobile robot measures contamination A contamination measurement sensor and a sterilizer capable of spraying a disinfectant solution are installed.

According to the method for creating a work path for disinfection and contamination measurement of a mobile robot according to the present invention, a work area can be set using a drawing created in AutoCAD, and a work route for disinfection and contamination measurement can be created while avoiding collision with an obstacle. It can be easily calculated and provided so that the mobile robot can drive.

1 is a block diagram showing a disinfection and contamination measuring work path generator of a mobile robot according to the present invention;
2 is a flowchart showing a process of generating a disinfection and contamination measurement work path of a mobile robot according to the present invention;
3 is a diagram for explaining a process of generating an intermediate target point for generating a disinfection and contamination measurement path;
4 is a view showing an example of a work space having five obstacles;
5 is a view showing an intermediate target point generated according to the present invention for the workspace of FIG. 4;
6 is a diagram showing a disinfection and contamination measurement path created in a state in which collision avoidance is not applied to the workspace shown in FIG. 5;
7 is a diagram schematically showing a connection process of entangled cells;
8 is a flow diagram showing a process of generating a collision avoidance path;
9 is a view showing a collision avoidance path generated through a collision avoidance path generation process with respect to FIG. 6;
10 is a view showing a disinfection and contamination measurement path finally created by applying the collision avoidance path of FIG. 9;
11 to 16 are diagrams showing final disinfection and contamination measurement work paths generated by applying the method of the present invention for cases where there are 1, 2, 4, 6, and 9 obstacles, respectively,
17 is a graph showing the number of intermediate goal points generated and the number of collision paths for the obstacle conditions of FIGS. 11 to 16;
18 is a graph showing the calculation time for each item for the condition of the obstacles in FIGS. 11 to 16;
19 to 21 are diagrams showing the disinfection and contamination measurement work routes as a result of applying the method of the present invention to another obstacle condition,
22 is a view showing an example of a construction CAD drawing,
23 is a diagram showing an example of a menu screen provided by an interface module interfaced with the construction CAD of FIG. 22;
FIG. 24 is a diagram showing a disinfection and contamination measurement work path created for the work area selected for the CAD drawing of FIG. 22 .

Hereinafter, a method for generating a disinfection and contamination measurement work path of a mobile robot according to a preferred embodiment of the present invention will be described in more detail with reference to the accompanying drawings.

1 is a block diagram showing a disinfection and contamination measurement work path generator of a mobile robot according to the present invention.

Referring to FIG. 1, the disinfection and contamination measurement work path generator 10 of the mobile robot includes a CAD interface module 20, an obstacle map formation module 30, an intermediate target point generation module 40, and disinfection and contamination measurement work route generation. A module 50, a collision avoidance path generation module 60, an input unit 61, a display unit 65, a main control module 70, a mobile robot drive module 80, and a storage unit 90 are provided.

The mobile robot 100 is capable of driving and is equipped with a contamination measurement sensor 110 for measuring contamination and a disinfector 120 for disinfecting the surrounding environment.

The pollution measuring sensor 110 may be applied with various known sensors capable of measuring the pollution level, such as a method of measuring the air pollution level by inhaling ambient air.

The sterilizer 120 may be applied to spray a disinfectant solution stored in a reservoir (not shown) through a spray nozzle.

The CAD interface module 20 provides a menu for setting a work area and selecting a robot type from a link with AutoCAD (AUTO CAD) and a drawing of a CAD file created and loaded with AutoCAD, and a work area selected for the provided menu The data corresponding to is extracted so that it can be used in the disinfection and contamination measurement work path generator 10.

The obstacle mapping module 30 creates an obstacle map from obstacles recognized from the selected work area data.

The intermediate target point generation module 40 generates an intermediate target point (SP) required for generating a disinfection and contamination measurement path.

The disinfection and contamination measurement work path generation module 50 generates a primary disinfection and contamination measurement work path using the intermediate target point information generated by the intermediate target point generation module 40, and then uses the collision avoidance path generation module to be described later. Create a final disinfection and contamination measurement work path using the collision avoidance path information generated by

The collision avoidance path generation module 60 generates a collision avoidance path within a work area using the applied mobile robot 100 and obstacle information.

The input unit 61 supports selection of a work area, robot model, and the like.

The display unit 65 is controlled by the main control module 70 to display display information.

The main control module 70 controls each of the modules 20 to 60 to generate a disinfection and contamination measurement work path.

The storage unit 90 stores data generated in the process of creating a disinfection and contamination measurement work path.

The mobile robot drive module 80 generates a driving command capable of driving the mobile robot 100 corresponding to the finally generated disinfection and contamination measurement work path.

Hereinafter, a process of creating a disinfection and contamination measurement work path will be described with reference to FIG. 2 .

First, a work area to be worked by the mobile robot 100 is selected from a drawing prepared and loaded in AutoCAD using the input unit 61 under the support of the CAD interface module 20 (step 210).

Next, obstacles are recognized on the drawing of the selected work area, and an obstacle map is created in the shape space for the recognized obstacles (step 220).

Thereafter, intermediate target points for generating primary disinfection and contamination measurement routes for the work area are created from the obstacle map (step 230), and primary disinfection and contamination measurement routes are generated using the intermediate target points (step 240).

If a collision with an obstacle occurs during the primary disinfection and contamination measurement path creation process, a collision avoidance path is created to avoid collision with the obstacle using the obstacle map and mobile robot information, and the created collision avoidance path is first disinfected. and a final disinfection and contamination measurement work path for the mobile robot is created by reflecting the contamination measurement path (step 250).

Finally, a driving command for the mobile robot 100 is generated from the generated final disinfection and contamination measurement path (step 260).

Here, the intermediate target points are positional information of contact with a wall or obstacle when the mobile robot 100 is moved while scanning in a zigzag manner within the workspace with a set width, and the obstacle information is the direction and direction corresponding to the scanning direction of the mobile robot Contains obstacle attribute information.

Hereinafter, the process of generating the disinfection and contamination measurement work path will be described in more detail.

First, since the disinfection and contamination measurement operations are performed on a two-dimensional plane, the mobile robot 100 and the target workpiece are modeled on a two-dimensional plane. The mobile robot 100 is modeled as an arbitrary polygon, and those capable of omni-directional motion and self-rotation are applied. Here, the shape of the mobile robot 100 supports the user to select or model.

In addition, the object in the work space is modeled in a polygonal form.

Obstacles in the work environment are divided into polygonal shapes and curved shapes. A polygonal shape has information about each vertex, and a curved obstacle is divided into straight line segments having a resolution of a certain length, and the curve is displayed as a set of points. And when displaying on the screen, these points are curve-fitted to display curved obstacles. The data structure for obstacles is as follows.

Struct object {

double *x_position;

double * y_position;

double radius_x, radius_y;

int edge_No;

char status;

} *object_posture;

Here, status is a status flag indicating that the obstacle has a polygonal, circular, elliptical, or curved shape, and edge_No indicates the number of vertices when the object has a polygonal shape. In the case of a circle or ellipse, variables of radius_x and radius_y are used, and in the case of an arbitrary curve, it is divided into regular segments with sufficient resolution to represent the shape and position data.

로 표시한다.

를

내에서의 j번째 배치된 정지물체, 즉 고정된 장애물이라 하면 모양공간(configuration space) 에서의 장애물 영역은 아래의 수학식 1로 표현된다.The target area of the work is a two-dimensional Eucridian space.

indicated by

cast

Assuming that the j -th disposed stationary object in , that is, a fixed obstacle, the obstacle area in the configuration space is expressed by Equation 1 below.

는 이동 로봇의 위치 x, y 및 자세

를 나타내는 집합이며

는 x, y, 그리고 q로 결정되는 이동 로봇(100)의 위치 및 자세이다.

내에 고정 장애물의 갯수를 p라 할때 장애물 영역의 총 공간은

이므로 모양공간내의 장애물이 없는 자유공간

는 아래의 수학식2와 같이 표현된다. where C is space,

are the position x, y and posture of the mobile robot

is a set representing

is the position and posture of the mobile robot 100 determined by x, y, and q .

When p is the number of fixed obstacles in the area, the total space of the obstacle area is

Therefore, free space without obstacles in the shape space

Is expressed as in Equation 2 below.

에 포함되는 모든 q에 대하여

로 구성되는 영역을

이라 하고, 이를 소독 및 오염 측정 작업 가능 영역이라 하면,

은 영역

내에서 이동 로봇이 물리적으로 진입 가능한 영역으로 표시되며, 소독 및 오염 측정 작업은

공간 내에서 수행된다. 그 조건하에서, 경로

가 아래의 수학식3을 만족할 때 소독 및 오염 측정 작업이 만족된다. 여기서d(τ, A(q))는 경로

와 로봇

사이의 거리를 나타낸다. Here, the symbol "\" means subtraction of a set.

For all q contained in

area consisting of

, and if this is the area where disinfection and contamination measurement work is possible,

silver area

It is displayed as an area where mobile robots can physically enter within, and disinfection and contamination measurement work

performed in space. Under that condition, the path

When satisfies Equation 3 below, the disinfection and contamination measurement tasks are satisfied. where d(τ, A(q)) is the path

and robot

represents the distance between

Here, r is the scanning width when the robot disinfects and measures contamination.

을 소독 및 오염 측정 작업을 하는 연속 경로를 생성한다. Next is a mobile robot (100)

to create a continuous path that disinfects and measures contamination.

First, the AUTO CAD interface module 20 provides an interactive menu using the CAD language Auto LISP and DCL (Dialog Control Library) method, and extracts the robot shape and selected work area data.

In the AUTO CAD interface module 20, thread data to be used by the robot for disinfection and contamination measurement work is acquired through drawing information retrieved using CAD entities, and it is possible to detect obstacles (lines, circles, polygons, arcs, etc.) in the selected area. Retrieve informational data about

인 3차원의 자유 모양공간(Configuration space)

를 형성한다. The Obstacle Map Building module 30 uses the obstacle and work environment data obtained from the CAD interface module 20 to determine x, y, and

3D free shape space (Configuration space)

form

에서 장애물과 이동 로봇(100)의 충돌형태에 따라 중간 목표점을 생성한다. The subgoal generation module 40 is

An intermediate target point is created according to the collision type between the obstacle and the mobile robot 100.

에서 장애물을 회피하면서 목표점까지 갈 수 있는 최단 거리의 충돌회피 경로를 생성한다.The collision avoidance path generation module 60 generates an obstacle collision avoidance path for the collision path generated in the process of generating the primary disinfection and contamination measurement operation path by the disinfection and contamination measurement operation path generation module 50 . That is, from the primary disinfection and contamination measurement work path described above.

Creates a collision avoidance path with the shortest distance to the target point while avoiding obstacles.

The intermediate target point generation module 40 scans the work area with a scanning width r with respect to the work space on a two-dimensional plane, and stores contact points between the robot and the obstacle and between the robot and the work area during scanning. The smaller the scan width r , the smaller the sweeping width and the larger the overlapping area, but the more dense the cleaning or plastering work.

While the robot scans the selected work area, it stores the contact positions and collision states between the robot and the robot and obstacles, and between the robot and the walls of the work area. These locations serve as intermediate target points for disinfection and contamination measurement work routes. The data structure of the intermediate target point for storage is as follows.

Struct Subgoal{

int position[DIMENSION];

char status;

char tracked_flag;

int obstacleNo;

} *SubgoalPositions;

를 유지한다. Here, position[DIMENSION] is the contact position between the mobile robot 100 and the obstacle or wall of the work area, and status is the contact type. Depending on the contact type, LEFT_WALL is in contact with the left side of the robot, and LEFT_WALL is in contact with the right side of the robot and the wall. RIGHT_WALL in case of contact with the left side of the robot, LEFT_OBSTACLE in case of contact with the left side of the robot, and RIGHT_OBSTACLE in case of contact with the right side of the robot, respectively. And tracked_flag is displayed as TRACKED when an intermediate target point is selected and inserted into list S for the creation of a disinfection and contamination measurement work path, and as UNTRACKED when not selected. And obstacleNo represents the number of the obstacle that the robot contacted when creating the intermediate target. To create an intermediate target point, the robot scans the work area from the upper left to the lower right, and the posture of the robot is

keep

The process for generating intermediate target points is as follows.

라 하자. 그리고 리스트 S를 SP의 집합인 S={S1, S2, ..., Si_max}라 하자. 여기서 i_max는 Si에 저장된 SP의 최대수이다. 로봇의 초기위치를 (x,y,

)=(0,0,0)라하며

x,

y를 각각 X축과 Y축 스캔 폭이라 하면 이하의 스텝 1A 내지 4A의 과정을 거치며 도 3을 함께 참조하여 설명한다.Let SP be a subgoal point, and the ith subgoal point data list entry

let's say And let the list S be a set of SPs, S={S1, S2, ..., Si_max}. Here, i_max is the maximum number of SPs stored in Si. The initial position of the robot ( x,y ,

) = (0,0,0)

x,

If y denotes the X-axis and Y-axis scan widths, respectively, the following steps 1A to 4A will be described with reference to FIG. 3 .

에 기록하며, 상태를 LEFT_WALL(LW)로 표기하며, tracked_flag을 UNTRACKED라 표기한다. 이후 i를 1증가시킨다.Step 1A: Set x, y and i to 0 respectively. And move the robot to make contact with the top left in the work area, set that position as the initial position, and set its x, y position

, the status is marked as LEFT_WALL (LW), and the tracked_flag is marked as UNTRACKED. After that, i is incremented by 1.

에 기록하고 접촉상태는 RIGHT_OBSTACLE(RO) 이라 기록하며 i를 증가시킨다. 그리고 로봇을 계속 x축선상에서 이동 시켜 장애물벽과 접촉하면 접촉상태를 RIGHT_WALL(RW) 이라 기록한다. tracked_flag은 UNTRACKED 로 기록한다.Step 2A: Move the robot along the x-axis with the position of the y-axis fixed. If the robot encounters an obstacle in the work area, it

and record the contact state as RIGHT_OBSTACLE (RO) and increase i. Then, if the robot continuously moves along the x-axis and contacts the obstacle wall, the contact state is recorded as RIGHT_WALL(RW). tracked_flag is recorded as UNTRACKED.

y만큼 이동한다. 그리고 Y축을 고정시킨 상태에서 로봇을 X축을 따라 왼쪽으로 이동 시킨다. 만일 로봇이 작업 영역내의 장애물과 접촉하면 그 위치를

에 기록하고 접촉 상태를 LEFT_OBSTACLE이라 기록하며, 그때의 장애물 넘버를 기록한다. 그리고 로봇을 계속 오른쪽 작업영역 벽까지 이동시켜 로봇이 벽과 접촉할 때는 접촉위치를 기록하고 접촉 상태를 LEFT_WALL(LW)로 기록한다. 이 때 Tracked_flag은 UNTRACKED라 기록한다. Step 3A: If the robot meets the bottom of the Y-axis of the work area, it moves to Step 5A described below. Otherwise, move the robot along the Y-axis.

move by y And move the robot to the left along the X-axis while the Y-axis is fixed. If the robot touches an obstacle in the work area, it changes its position.

, record the contact status as LEFT_OBSTACLE, and record the obstacle number at that time. Then, when the robot makes contact with the wall by continuously moving the robot to the right workspace wall, the contact position is recorded and the contact state is recorded as LEFT_WALL (LW). At this time, Tracked_flag is recorded as UNTRACKED.

y만큼 이동하고 Step 1A로 이동한다.Step 4A: Move the robot along the Y axis

Move by y and go to Step 1A.

Step 5A: Record i as i-max , the maximum number of intermediate target points for the disinfection and contamination measurement work path.

4 is an example of a work area including 5 obstacles, and FIG. 5 shows the result of finding an SP by applying the proposed intermediate goal point creation process.

를 생성하는 방법이 결정된다. As a next process, when the intermediate target point generation process is completed, the generated intermediate target point is scanned to create a primary disinfection and contamination measurement work path. Here, for the intermediate target points created in the intermediate target point creation process, first, all intermediate target points are not connected more than twice, and second, the primary disinfection and contamination measurement work path formed by connecting the intermediate target points is made as short as possible. create a path This process finds the next intermediate target point to be connected according to the contact state of the current intermediate target point. The process of finding the disinfection and contamination measurement work path is performed by performing the process of CASE I described later when the state of the intermediate target point is LEFT_WALL or LEFT_OBSTACLE, and by performing the process of CASE II described later when the status of the intermediate target point is RIGHT_WALL or RIGHT_OBSTACLE. Disinfection and contamination measurement work path

How to generate is determined.

의 초기 엔트리에 저장된 로봇의 위치 데이터는 작업영역의 좌측 상단을 기르키며, 그 때의 접촉 상태는 LEFT_WALL이된다. 소독 및 오염 측정 작업경로를 생성하기위한 과정은 다음과 같다.As the robot scans from the upper left corner of the work area to the lower right corner in order to create an intermediate target point, the list

The position data of the robot stored in the initial entry of raises the top left of the work area, and the contact state at that time becomes LEFT_WALL. The process for creating a disinfection and contamination measurement work path is as follows.

의 Y축 최대 영역, x_max 를 X축최대 영역이라하고,

를 소독 및 오염 측정 작업 경로를 위한 리스트라한다.First, set y_max to the workspace

The Y-axis maximum area of , x_max is called the X-axis maximum area,

are listed for disinfection and contamination measurement work routes.

CASE 1: If the contact state of the current intermediate target point is LEFT_WALL or LEFT_OBSTACLE, the following steps are performed.

공간상에서 리스트 S에서 같은 y값이 같은 SP중에서 접촉상태가 RIGHT_WALL 이거나 RIGHT_OBSTACLE 인 중간 목표점을 찾는다. Step 1B:

Among the SPs with the same y value in the list S in space, find the intermediate target point whose contact state is RIGHT_WALL or RIGHT_OBSTACLE.

This case is marked as (A) in Figure 3. That is, since the current contact state of the robot is LEFT_WALL, search for SP in list S, but search for SP whose contact state is RIGHT_WALL on the same Y-axis line to form a disinfection and contamination measurement path segment. As in the case of (B) in FIG. 3, if the contact state of the current SP is LEFT_WALL, an SP whose contact state is RIGHT_WALL or RIGHT_OBSRACLE is found among SPs having the same y position value in list S.

에 삽입한다. 만일 찾은 SP가 TRACKED 라고 표기됐고 현재 SP에서 연결될 다음 SP까지 로봇을 이동했을 경우 장애물과 충돌이 일어나면 후술되는 Step 6B로 가고 그렇지 않으면 Step 3B으로 간다.Step 2B: Among the SPs found in Step 1B, find the SP with the shortest distance and list it

insert into If the found SP is marked as TRACKED and the robot moves from the current SP to the next SP to be connected, if a collision with an obstacle occurs, go to Step 6B, otherwise go to Step 3B.

에 삽입한다.For reference, the case of (B) in FIG. 3 is a case in which the contact state of the current SP is LEFT_WALL and the SP of the next contact state is RIGHT_OBSTACLE or RIGHT_WALL and has two SPs. In this case, among the candidate SPs, an SP with a short distance and a generated path line that does not collide with an obstacle is selected as the SP to be connected, and the list is selected.

insert into

y, 만일 y < 0 이면, Step 5B로 간다.Step 3B: y← y +

y, if y < 0, go to Step 5B.

에 삽입한다. 즉, 도 3에서 (C)의 경우로서, 여기서 SP의 현재 접촉 상태는 RIGHT_WALL이며 y값을 스캐닝 폭

y만큼 증가시킨 후 같은 접촉상태를 찾는다.Step 4B: Find the SP whose contact state is RIGHT_WALL or RIGHT_OBSTACLE on the same Y-axis line, and list those SPs if the path segment is non-collision

insert into That is, in the case of (C) in FIG. 3, where the current contact state of the SP is RIGHT_WALL and the y value is the scanning width

After increasing by y, the same contact state is found.

Step 5B: Find the SP marked UNTRACKED among the S data list, and determine the SP closest to the current SP as the next SP to be connected. If a path from the current SP to the next connected SP collides with an obstacle, a collision avoidance path generation module 60 described later is called. That is, as the path of FIG. 3 (D), in this case, the collision avoidance path generation module 60 is called. FIG. 6 shows a case in which a primary disinfection and contamination measurement work path is found without applying the collision avoidance path generation process to the obstacle condition of FIG. 4 . In Fig. 6, five collision path segments are shown.

에 삽입하고 해당 tracked_flag을 TRACKED로 표시한다. 링크된 SP의 상태에 따라 CASE I 이나 CASE II의 Step 1B로 간다.Step 6B: If the number of connected SPs is equal to i_max , the program ends. Otherwise, add the SP to the path list

and mark the corresponding tracked_flag as TRACKED. Depending on the status of the linked SP, go to Step 1B of CASE I or CASE II.

CASE II: In case the contact status of the currently connected SP is RIGHT_WALL or RIGHT_OBSTACLE;

In the case of CASE II, RIGHT_WALL and RIGHT_OBSTACLE are replaced with LEFT_WALL and LEFT_OBSTACLE respectively in Step 1B to Step 4B of CASE I, and the rest of the process is the same as in CASE I.

Next, a process of creating a collision avoidance path will be described with reference to FIGS. 7 and 8 .

로 표시되는 3차원의 모양공간을 일정한 크기의 격자로 분할한 격자화된 모양공간(grid-based configuration space)에서 경로를 계획한다. 격자화된 셀(quantized cell)은 장애물에 포함된 경우 장애물 셀, 포함되지 않은 경우 자유 셀이라 한다. 경로 계획 방법은 먼저, 기본 크기의 격자를 몇 개 합친 셀( 격자화된 3차원 모양공간에서 최소 셀의 3

3

3 또는 2

2

2 크기의 셀)을 하나의 큰 셀로 보아 이 큰 셀들을 연결하여 로봇의 시작 자세가 포함된 큰셀과 목표자세가 포함된 큰셀 들 사이의 연결통로를 만들되 큰 셀의 선택은 선택하고자 하는 큰 셀과 목표 셀과의 거리, 시작 자세의 셀과의 거리 그리고 큰 셀내의 장애물 셀의 갯수 등으로 표현되는 평가함수를 최소로 하는 큰 셀들을 선택하여 연결한다. 연결된 큰 셀들에 의해 생성된 통로를 탐색하고(단계 310), 뒤엉킴 셀이 있으면 이를 제거한다(단계 320). 여기서 뒤엉킴 셀이란 큰셀로 통로를 구성함에 있어서 큰셀 연결 가지가 도 7과 같이 여러 갈래로 나뉘어 져있는 상태를 말하고, 도 7에서 2번, 3번, 4번의 셀이 뒤엉킴 셀에 해당한다. 즉 셀을 연결하는 리스트에서 헤드(head)와 테일(tail)에 하나씩 만의 셀이 연결된 것이 아니라 두개 이상 연결된 상태를 말한다. 이러한 데이터 구조는 뒤엉킴이 시작된 셀을 중간 목표점으로 하여 역추적(backtracking)하면 뒤엉킴이 없는 셀들의 집합으로 재구성된다. The collision avoidance path generation process uses a two-stage path planning method. This method is a hierarchical local search algorithm.

A path is planned in a grid-based configuration space in which the three-dimensional shape space represented by is divided into grids of a certain size. A quantized cell is called an obstacle cell when it is included in an obstacle, and a free cell when it is not included. In the path planning method, first, a cell obtained by combining several lattices of the basic size (3 of the minimum cell in the lattice 3-dimensional shape space)

3

3 or 2

2

2 size cell) as one large cell, connect these large cells to create a connection passage between the large cell containing the starting posture of the robot and the large cells containing the target posture. Select and connect large cells that minimize the evaluation function expressed by the distance to the target cell, the distance to the cell in the starting posture, and the number of obstacle cells in the large cell. Paths created by connected large cells are searched for (step 310), and entangled cells are removed if present (step 320). Here, the entangled cell refers to a state in which the large cell connection branch is divided into several branches as shown in FIG. 7 in constructing a passage with a large cell, and cells numbered 2, 3, and 4 in FIG. 7 correspond to the entangled cells. That is, in the list connecting cells, it means that not only one cell is connected to the head and tail, but two or more cells are connected. This data structure is reconstructed into a set of cells without entanglement by backtracking with the cell where entanglement started as an intermediate target point.

In step 330, it is determined whether there is an entangled cell, and if it is determined that there is no entangled cell, a path to a basic cell within the passage is searched (step 340). If it is determined that the path search is not successful in step 350, the large cell in which the path creation fails is stored as a virtual obstacle cell (step 360), and the process returns to step 310. Unlike this, if it is determined that the route search is successful in step 350, a collision avoidance route is created (step 370).

That is, if there is a entanglement phenomenon during the connection of large cells, a connection state without entanglement is made by the re-tracking method, and then a final path composed of connections of basic unit cells is made in a connection path composed of connections of large cells. In addition, if the final path is not created in step 350, large cells are stored as virtual obstacle cells and excluded from the connection of large cells in step 320.

A collision avoidance path generated by the collision avoidance path creation process is shown in FIG. 9 .

On the other hand, in FIG. 6 showing the SP generation result for FIG. 4, collisions on the path are shown in five places. For this, the collision avoidance path generation process is performed in Step 5B of CASE I and CASE II, and the result is shown in FIG. 9, and the result of the final disinfection and contamination measurement work path considering collision avoidance is shown in FIG. 10.

In FIG. 10 , the movement path represented in white is a plastering (or cleaning) work path, and the path represented in blue represents a path in which the robot moves through an overlapping area of the plastering work (or cleaning work) area.

- mock experiment

의 크기는 최대 21m

21m이며, 로봇은 한 변이 41.42cm인 정팔각형 형태로 모델링하였다. 충돌회피 경로 탐색을 위한 모양공간은 작업영역을 10cm 단위로 나누어 격자화 시켰으며 모양공간내의 기본 셀의 갯수는 210

210 = 44,100개로 이루어져 있다. 스갠 폭은 75cm로 하였다. workspace

size up to 21m

21 m, and the robot was modeled in the form of a regular octagon with a side of 41.42 cm. The shape space for collision avoidance path search was gridded by dividing the work area into 10 cm units, and the number of basic cells in the shape space was 210.

210 = 44,100 pieces. The span width was 75 cm.

- Experiment 1

240cm의 정사각형 형태의 장애물을 도 11 내지 도 15에 도시된 바와 같이 1개, 2개, 4개, 6개 그리고 9개를 임의로 설치하여 SP생성 시간, 생성 개수, 그리고 모양공간의 생성 시간과 충돌회피 경로생성 계산시간을 분석하였다. 경로의 최종결과는 그림 도 11 내지 도 15에 도시된 바와 같고, 계산 시간 및 분석표는 아래의 표 1과 도 16 및 도 17에 나타내었다. 240 cm within the workspace

As shown in FIGS. 11 to 15, 1, 2, 4, 6, and 9 240cm square obstacles are randomly installed to collide with the SP creation time, the number of creation times, and the creation time of the shape space. The avoidance path creation calculation time was analyzed. The final results of the path are shown in Figs. 11 to 15, and the calculation time and analysis table are shown in Table 1 and Figs. 16 and 17 below.

Item
/
number of obstacles SP
produce
Count crash
Route
Count SP
produce
hour shape space
creation time Create collision avoidance path
hour final route
creation time One 70 One 3.516 6.593 1.593 11.703 2 86 5 5.384 8.131 2.362 15.879 4 106 5 8.571 11.099 4.560 24.231 6 122 6 11.538 13.736 11.923 37.198 9 160 10 14.725 16.978 13.846 45.549

As shown in Table 1 and FIGS. 16 and 17, the number of collision paths is not proportional to the number of obstacles. The reason is that the collision path is determined by the position of the obstacle. However, it shows that a lot of collision paths occur when there are many obstacles in the workspace.

- Experiment 2

4m이고 작업 로봇의 크기는 반경 30cm이다. By applying the method proposed in the present invention, the disinfection and contamination measurement path was created and the final path length was calculated. The size of the working area is 4m

4 m and the size of the working robot is 30 cm in radius.

18 to 20 show disinfection and contamination measurement paths created by applying the method proposed in the present invention. Table 2 below also shows the generated path lengths.

In the case of Fig. 18 In the case of Fig. 19 In the case of Fig. 20 method 3484.09 cm 2900 cm 2627.17 cm

As can be seen from FIGS. 18 to 20, the disinfection and contamination measurement work path created by the method proposed in the present invention is in the form of a direction parallel moving in a zigzag pattern.

- Experiment 3

The proposed disinfection and contamination measurement work path generation method was applied to actual construction drawings. The construction drawings were made with AUTO CAD R 14, and the interface menu with CAD SW was made with AUTO LISP. In the interface made with AUTO LISP, it is built to determine the shape of the robot and the size of the work area. The test results using the constructed work path generator are shown in FIGS. 21 to 23, and it can be seen that the disinfection and contamination measurement work paths are precisely generated by the proposed method even when applied to actual drawings.

"This patent application is the result of a regional innovation project based on cooperation between local governments and universities carried out with the support of the National Research Foundation of Korea funded by the Ministry of Education in 2020."

Fig. 10: Disinfection and contamination measurement workflow generator
20: CAD interface module
30: obstacle mapping module
40: Intermediate target point generation module
50: Disinfection and contamination measurement work path creation module
60: collision avoidance path generation module
61: input unit
65: display unit
70:: Main control module
80: mobile robot drive module
90: storage unit
100: mobile robot
110: contamination measuring sensor
120: Disinfector

Claims (2)

go. Selecting a work area for a mobile robot to work on a drawing prepared and loaded in AutoCAD;
me. generating an obstacle map for obstacles recognized in the shape space for the selected work area;
All. generating an intermediate target point for generating a primary disinfection and contamination measurement path for the work area by using the obstacle information;
la. generating the primary disinfection and contamination measurement path using the intermediate target points;
mind. generating a collision avoidance path for collision avoidance with an obstacle when there is a path in which a collision with an obstacle occurs on the primary disinfection and contamination measurement path using the obstacle map and the mobile robot information;
bar. Including; generating a final disinfection and contamination measurement work path for the mobile robot by reflecting the collision avoidance path generated in step D on the primary disinfection and contamination measurement path,
Wherein the mobile robot is equipped with a contamination measurement sensor for measuring contamination and a disinfector capable of spraying a disinfectant solution. The method of claim 1, wherein the intermediate target points are positional information of contact with a wall or an obstacle when the mobile robot is moved while scanning in a zigzag pattern within the workspace with a set width, and the obstacle information is information about a contact point of the mobile robot in a scan pattern of claim 1 A method for generating a disinfection and contamination measurement work path of a mobile robot, characterized in that it includes direction and obstacle attribute information corresponding to the direction.

Images