CN108507578B - Navigation method of robot - Google Patents
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- G—PHYSICS
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- G01C21/26—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 specially adapted for navigation in a road network
- G01C21/28—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 specially adapted for navigation in a road network with correlation of data from several navigational instruments
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Abstract
The invention discloses a navigation method of a robot, firstly, a virtual cleaning subarea is framed in a working space when the robot is started, then boundary characteristic information of a navigation boundary is marked in the process of cleaning the virtual cleaning subarea, and a local boundary map is constructed; then converting the data of the local boundary map to a global coordinate system; after the virtual cleaning subareas are cleaned, moving to an uncleaned area, framing a next virtual cleaning subarea, continuously marking the boundary characteristic information, repeating the steps in a circulating manner, and exiting the circulation when the whole working space is cleaned to complete the construction of the global boundary map; and finally, selecting the navigation boundary as a navigation path for navigation. According to the invention, by the method for constructing the local boundary map and the global boundary map, the robot can realize rapid navigation under the condition of keeping the boundary characteristic information, simultaneously save the system memory, and improve the flexibility and the high efficiency of the robot navigation.
Description
Technical Field
The invention relates to the technical field of robot indoor navigation and intelligent control, in particular to a construction method of a global boundary map and a navigation method thereof.
Background
Robots based on inertial navigation are increasingly popular, and more representative robots are family floor sweeping and cleaning robots. The sweeping robot combines the data of the gyroscope, the acceleration and the wheel odometer to realize the real-time positioning and map building of the indoor environment, and then realizes the positioning navigation according to the built map. The robot based on inertial navigation is based on a global grid map to navigate back to a charging seat, when the inertial navigation based on a gyroscope is realized under an actual home environment, because various unknown conditions exist in a complex home environment, errors caused by wheel slip, gyroscope drift and the like can be accumulated more and more along with the lapse of time, so that the machine slips, a constructed map has larger deviation, and if the global map is continuously used for navigation, the deviation between the robot and a target point is increased.
In practical applications, a grid map is mainly used to divide the working environment (environment information including, but not limited to, temperature, humidity, light intensity, etc. of the environment) of the robot into a series of grids, wherein each grid is assigned a probability value representing the probability of the grid being occupied by an obstacle. The grid map is easy to create and maintain, the perception information of a certain grid can directly correspond to a certain area in the environment, and the grid map is suitable for processing ultrasonic measurement data. However, in the environment map represented by the grid, the resolution of the environment space is related to the size of the grid, and increasing the resolution increases the time and space complexity of the operation. If a precise grid map is to be obtained, a relatively high cost is required, such as a laser sensor or an image sensor, and a relatively large amount of computing resources are required, which results in a relatively high requirement on the storage space of a CPU, and is not favorable for the cost reduction of the product. In order to reduce the resources used by the CPU and improve the success rate of robot navigation, a new global map needs to be provided for the robot to navigate.
Chinese patent CN100449444 proposes a method for simultaneously positioning and mapping a mobile robot in an unknown environment, and realizes high-precision positioning navigation by constructing a global line segment feature map and a global occupied grid map, but the algorithm for updating the match line segment feature and the grid map in the map has high requirements on the performance of a processor, and the calculated amount of line segment feature matching is large; in the method of using the topological map in chinese patent CN107121142, whether to divide sub-regions and how to divide the sub-regions are determined by combining with the current environmental characteristics of the robot, and then the sensor data is fused to perform path planning, but the division of the sub-regions is affected by the detection range of the laser sensor. There is a need to develop a robot that has low requirements for storage space and computing resources and is suitable for rapid navigation of a robot under indoor conditions.
Disclosure of Invention
The invention is based on the navigation technology for constructing the global map, and in order to save the memory of the navigation map in the movement process of the robot, the global boundary map is constructed by recording the boundary characteristic information of the navigation boundary in the clean area, so that the robot selects a proper boundary path for navigation movement. The technical scheme of the invention is as follows:
a method for constructing a global boundary map is characterized in that the construction process of the global boundary map comprises the following steps:
step S1: when the robot is started, a virtual cleaning subarea is framed in a working space, boundary characteristic information of a navigation boundary is marked in the process of cleaning the virtual cleaning subarea, a local boundary map is constructed, and the step S2 is carried out;
step S2: converting the coordinate system of the data of the local boundary map in the virtual cleaning partition, adding the data into a global coordinate system, and entering the step S3;
step S3: after the virtual cleaning subarea is cleaned, moving to an area which is not cleaned, and repeating the steps S1-S2 until a complete working space is cleaned to obtain the global boundary map;
the boundary characteristic information comprises a start point coordinate of a navigation boundary, an end point coordinate of the navigation boundary and a rotation angle of the robot walking along the navigation boundary.
Further, the robot defines the current virtual cleaning partition, marks boundary characteristic information of a navigation boundary in the cleaning process, constructs a local boundary map, and constructs a local grid map according to marked obstacle information at the same time, wherein the local grid map is not deleted until the robot starts to clean the next virtual cleaning partition, and is replaced by the local grid map constructed in the next virtual cleaning partition.
Further, the global boundary map is constructed by determining a global coordinate system with the initial starting point position of the robot as the origin and the forward direction of the robot from the initial starting point position as the positive direction of the Y axis.
Furthermore, the virtual cleaning partition is determined by making a straight line parallel to the Y axis through the current entrance position of the robot on the global coordinate system, and making a straight line n meters away from and parallel to the vertical boundary line as another vertical boundary line, and the robot sets a vertical boundary line in the Y axis direction; drawing a straight line perpendicular to the vertical boundary line as a horizontal boundary line passing through the current entrance position of the robot, and taking a straight line which is m meters away from and parallel to the horizontal boundary line as another horizontal boundary line; the vertical boundary line and the horizontal boundary line are encircled to form the virtual cleaning subarea; the robot continues to move after finishing sweeping the current virtual cleaning subarea, and when an uncleaned area is detected, the current position is taken as the next entrance position, and the next virtual cleaning subarea is continuously framed according to the method;
wherein the variable n represents the preset length of the virtual cleaning partition, and the variable m represents the preset width of the virtual cleaning partition.
Further, the navigation boundary is composed of a solid boundary and a virtual boundary, wherein the solid boundary is connected according to coordinate points of the edge of a wall body or a wall obstacle in the virtual cleaning partition; the virtual boundary is a virtual route which is fit into the virtual cleaning subarea and forms a closed area with the solid boundary in order to realize navigation back to the initial starting point position;
the closed area is the actual cleaning area provided for navigation back to the initial starting position.
Further, the distance between the starting point and the end point of the virtual boundary is larger than the width of the robot body.
A navigation method of a robot, which is planned based on the boundary feature information, comprising the steps of:
step 1: when the robot starts navigation, acquiring the current position of the robot, determining the position of a target point, and entering step 2;
step 2: selecting a navigation path by taking the current position of the robot as a starting point and a target point position as an end point according to the global boundary map and the current local grid map and combining the boundary characteristic information of the navigation boundary, and entering step 3;
and step 3: and the robot navigates according to the selected navigation path.
Further, the specific method for selecting the navigation path in step 2 of the navigation method includes:
step 21: according to the starting point position and the end point position determined by the robot, the navigation boundary is used for planning a navigation path, and the step 22 is carried out;
step 22: judging whether the length of the entity boundary existing on the planned and selected path is larger than the preset boundary length, if so, selecting the path with the largest entity boundary length as a navigation path; otherwise, entering step 23;
step 23: judging whether the rotation angle of the robot on the planned and selected path is smaller than a preset rotation angle or not, if so, selecting one with the largest length of the entity boundary as a navigation path, and otherwise, selecting one with the smallest rotation angle of the robot as the navigation path;
wherein the preset boundary length is a reference length used for weighing the priority of the length of the entity boundary in planning a navigation path; the preset rotation angle is a reference angle used for balancing the priority of the robot rotation angle in planning a navigation path.
Compared with the prior art, the method has the advantages that the global boundary map is constructed by recording the virtual boundary and the entity boundary in the local boundary map, the data of the local boundary map are reasonably recorded, the complexity of an algorithm is reduced, and the computing resources of a CPU are saved; the navigation method based on the global boundary map disclosed by the invention improves the navigation efficiency and flexibility of the cleaning robot.
Drawings
FIG. 1 is a flow chart of a method of constructing a global boundary map and a navigation method thereof;
FIG. 2 is a labeled diagram of a navigation path of a robot in a typical indoor environment;
FIG. 3 is a schematic diagram of coordinate system conversion;
FIG. 4 is a schematic view of a framed cleaning area;
Detailed Description
The technical solutions in the embodiments of the present invention will be described in detail below with reference to the accompanying drawings in the embodiments of the present invention. It should be understood that the following specific examples are illustrative only and are not intended to limit the invention.
In the present patent application, it is to be understood that the terms "upper", "lower", "left", "right", "front", "rear", and the like, indicate orientations or positional relationships based on the orientations or positional relationships shown in the drawings, and are used for convenience in describing embodiments of the present invention and simplifying the description, but do not indicate or imply that the referred device or element must have a specific orientation, be constructed in a specific orientation, and be operated, and thus, should not be construed as limiting the present patent application.
The robot can meet different obstacles in the process of walking along the edge, and in order to effectively simplify the description of the indoor environment and provide a reasonable corresponding strategy in path planning, the robot can process the indoor obstacles as follows: 1. and as long as the distance between the barrier and the wall does not meet the minimum distance for the robot to pass through, the robot cannot pass through smoothly, and the barrier is processed by pressing against the wall. 2. For a straight-line obstacle, the outline characteristic of the straight-line obstacle is represented by a rectangle; and for the nonlinear obstacles, processing by adopting a broken line approximation method. 3. When the distance between the two obstacles is very close and the robot cannot pass through the two obstacles smoothly, the two obstacles can be regarded as one obstacle to be treated.
The robot carrier is provided with a gyroscope for detecting a rotation angle, a mileometer for detecting a travel distance and a sensor capable of detecting a wall distance, wherein the sensor for detecting the wall distance can be an ultrasonic distance sensor, an infrared intensity detection sensor, an infrared distance sensor, a physical switch detection collision sensor, a capacitance or resistance change detection sensor and the like.
As shown in fig. 1, the implementation of the present invention provides a method for constructing a global boundary map and a navigation method thereof, including the steps of, when a robot is started in step S1, framing a virtual clean partition in a working space, and then marking boundary feature information of a navigation boundary in the process of cleaning the virtual clean partition to construct a local boundary map; step S2, converting the coordinate system of the data of the local boundary map in the virtual cleaning partition, and adding the data into the global coordinate system; in step S3, after the virtual cleaning partition is cleaned, the mobile station moves to an uncleaned area, frames a new virtual cleaning partition, completes simultaneous positioning and map building in the cleaning process, and continues moving, and the loop repeats, and exits when the whole working space is cleaned. Wherein the simultaneous localization and mapping comprises the construction of a local boundary map; converting the data of the local boundary map through a coordinate system, adding the data into a global coordinate system, and constructing the global boundary map; in step S4, the navigation boundary is selected as a navigation path back to the departure position. According to the invention, the boundary characteristic information is obtained by constructing the local boundary map and the global boundary map, so that the robot can quickly navigate back to the seat, the system memory is saved, and the flexibility and the efficiency of robot navigation are improved.
The specific steps of the construction process of the global boundary map are as follows:
in step S1, when the robot is started, a virtual cleaning partition is framed in the working space, boundary characteristic information of a navigation boundary is marked in the process of cleaning the virtual cleaning partition, a local boundary map is constructed, and the process goes to step S2; as shown in fig. 2, when the robot starts moving forward in the Y-axis direction of the global coordinate system with the charging seat position O as an initial starting point, a virtual cleaning partition is framed on the right side of the Y-axis, the robot then sweeps in a zigzag manner in the virtual cleaning partition, and a local boundary map is constructed by marking boundary feature information of a navigation boundary according to data of a sensor.
In step S2, converting the coordinate system of the data of the local boundary map in the virtual clean partition, adding the converted data into the global coordinate system, and proceeding to step S3; when the robot cleans an area, the local boundary map data corresponding to the area is converted to a global coordinate system through the coordinate system, so that an initial global boundary map is obtained, and the robot can be positioned immediately;
in step S3, after the virtual cleaning partition is cleaned, moving to an area which is not cleaned, and repeating steps S1-S2 until a complete working space is cleaned, thereby obtaining the global boundary map; after the robot cleans the current virtual cleaning partition, the robot returns to the entrance position of the current virtual cleaning partition according to the constructed global boundary map navigation, and then continues to advance along the Y-axis direction of a global coordinate system; or not returning to the current entrance position of the virtual cleaning partition, and moving to an uncleaned area across the virtual cleaning partition; and then continuously framing the next virtual cleaning subarea, completing simultaneous positioning and map construction in the cleaning process, continuously moving, repeating the cycle, and exiting the cycle when the whole working space is cleaned. By marking the boundary characteristic information in each region, cross-region navigation is facilitated.
The robot provided by the embodiment adopts a Chinese character 'gong' type walking method, firstly moves straight along the positive direction of the Y axis of a global coordinate system until an obstacle is found or the boundary of the virtual cleaning partition is reached, then rotates 90 degrees clockwise (or anticlockwise), then moves straight by 150mm (about half of the diameter or width of the intelligent robot) or finds the obstacle, then rotates 90 degrees in the same direction, then moves straight, and repeats the cycle all the time, so that the Chinese character 'gong' type walking method can be realized.
Specifically, the boundary feature information includes a start coordinate of a navigation boundary, an end coordinate of the navigation boundary, and a rotation angle of the robot walking along the navigation boundary. And the recorded XY coordinate information and the angle information of the starting point and the end point on the navigation boundary are fused into the global boundary map by converting the walking distance detected by the odometer of the robot and the angle value detected by the gyroscope into a global coordinate system, so that the robot can quickly and accurately find the continuous scanning position and the navigation path in the subsequent movement according to the navigation boundary.
As shown in fig. 2, it is assumed that regions # 1, #2, and #3 constitute the workspace. Initially, the area # 1 and the area # 2 are two local areas which are successively cleaned during the process that the robot advances along the positive direction of the Y axis of the global coordinate system, the local boundary map marks the boundary feature information of the local areas during the working process of the robot, when the area # 2 is cleaned, the local boundary map in the area # 2 is converted into the global coordinate system through the conversion of the coordinate system, and the boundary feature information constructed in the area # 1 and the area # 2 is combined. Similarly, after cleaning the area # 3, the local boundary map in the area # 3 is converted into a global coordinate system, and the boundary feature information constructed in the area # 1, the area # 2 and the area # 3 is combined, so that the global boundary map in the whole working space is constructed. According to the construction method, the global boundary map only reserves the boundary characteristic information, and compared with the global map in the prior navigation technology, the memory space is saved.
Preferably, the robot defines the current virtual cleaning partition, marks boundary characteristic information of a navigation boundary in the cleaning process, constructs a local boundary map, and constructs a local grid map according to marked obstacle information at the same time, wherein the local grid map is not deleted until the robot starts to clean the next virtual cleaning partition, and is replaced by the local grid map constructed in the next virtual cleaning partition. As shown in fig. 2, assuming that an area # 1 and an area # 2 are two local areas to be cleaned by the robot, the robot returns to the entrance position of the area # 1 after cleaning the area # 1 and continues to clean the area # 2, and the local grid map in the area # 2 is retained to mark obstacle information, and the local grid map in the area # 1 is deleted; similarly, if the area # 3 is cleaned continuously after the areas # 1 and #2 are cleaned, the robot keeps the local grid map marked obstacle information in the area # 3, and deletes the local grid map in the area # 2 and the area # 1, so that the memory space of the map is saved, and the local grid map can be used for positioning and navigating the position of the current area.
In order to determine the position of an obstacle in the environment, in a particular embodiment of the invention, it must be determined by the position of the robot itself and the distance of the obstacle relative to the robot measured by the sensors on it. Therefore, it is necessary to model the working environment of the robot, and establish two coordinate systems for the local boundary map and the global boundary map, that is, the coordinate system UHV of the local boundary map is used to describe the pose information of the robot in the current virtual cleaning zone, and the global coordinate system YOX is used to describe the working space of the robot and provide a navigation path.
Specifically, the local boundary map adopts a coordinate system in which the current position of the robot is used as an origin, and the advancing direction of the robot at the current position is used as the V-axis direction. Since the robot detects the current environmental information during the movement, and the distance information detected each time is quantitatively measured in the movement posture of the current robot, the local boundary map is established to describe the currently detected local information. After the coordinate origin of the local boundary map is determined, acquiring the rotation speed coding information and turning information of the wheels of the robot to obtain the coordinate information and angle information of the robot in the coordinate system of the local boundary map. The local coordinate systems of the robot at different positions have different expression modes, need to be processed uniformly and are converted to a uniform global coordinate system.
Preferably, the global boundary map is constructed by first determining the global coordinate system with the initial starting point position of the robot as the origin and the forward direction of the robot from the initial starting point position as the positive direction of the Y axis. The robot should select a specific reference coordinate system to implement a regular path planning, as shown in fig. 2, and in the area # 1, the most ideal reference object is the wall. The wall has good linear characteristic, and meanwhile, the distribution of the wall has certain regularity, so that the outline of the whole working space is drawn. Therefore, the global coordinate system uses the position of the initial starting point O of the robot as the coordinate origin, and the robot is established as the Y-axis direction along the wall advancing direction from the initial starting point position to describe the environment information of the whole working space, indicating the position of the robot in the whole working space.
In step S2 of the global boundary map construction method, the mathematical method of coordinate system transformation is performed on the data of the local boundary map, and as shown in fig. 3, the current position of the robot is taken as the origin of coordinates H of the coordinate system UHV, which is expressed as (X) in the coordinate system YOX0,Y0) The right front of the robot is taken as the V direction, the included angle between the Y axis in the coordinate system YOX and the V axis in the coordinate system UHV is theta 0, and the rotation matrix is
The translation vector of the coordinate system UHV relative to the coordinate system YOX is
The coordinate vector corresponding to the coordinate of the entity boundary starting point A in the coordinate system UHV is recorded as
The coordinate vector of the coordinate of the solid boundary starting point A in the coordinate system YOX is recorded as
The transformation of the coordinate system of the local boundary map into the global coordinate system is carried out by transforming the coordinate system UHV along the translation vector
Is translated to the origin of the coordinate system YOX such that point O coincides with point H; then the starting point A is changed into a point A ', the coordinates of the point A' are set as (Xh, Yh), and the vector is obtained
The included angle between the X axis and the X axis is theta 1 degree; then, the translation coordinate system UHV is rotated anticlockwise by theta 0 degrees, the point A ' is changed into a point A ', the coordinates of the point A ' are set to be (Xp, Yp), and the vector is expressed
The included angle between the vector conversion relation and the X axis is (theta 1+ theta 0), and the vector conversion relation of the entity boundary starting point A from the coordinate system UHV to the coordinate system YOX is
Preferably, the virtual cleaning partition is determined by making a straight line parallel to the Y axis through the current entrance position of the robot on the global coordinate system, and making a straight line n meters away from and parallel to the vertical boundary line as another vertical boundary line, and the robot sets a vertical boundary line in the Y axis direction; drawing a straight line perpendicular to the vertical boundary line as a horizontal boundary line passing through the current entrance position of the robot, and taking a straight line which is m meters away from and parallel to the horizontal boundary line as another horizontal boundary line; the vertical boundary line and the horizontal boundary line are encircled to form the virtual cleaning subarea; the robot continues to move after finishing sweeping the current virtual cleaning subarea, and when an uncleaned area is detected, the current position is taken as the next entrance position, and the next virtual cleaning subarea is continuously framed according to the method; wherein the entry location represents a location of entry into the virtual cleaning zone and is also a starting location for the robot to frame the virtual cleaning zone; the virtual cleaning zone is framed in a left or right region of the Y-axis. The variable n represents the preset length of the virtual cleaning partition, and the variable m represents the preset width of the virtual cleaning partition.
Preferably, the determination method of the virtual cleaning partition is as shown in fig. 4, and the value of the variable m is set to 5 in meters; the value of the variable n is set to 5 in meters; area #5 is a concave area enclosed by the solid line in fig. 4, and the robot sweeps a motion track from left to right in a zigzag manner in the area # 5. In the mathematical model, the Y-axis direction of the coordinate system YOX represents the vertical direction, and the X-axis direction represents the horizontal direction. When the robot starts from an initial starting point position O in an area #5, taking a position D as an entrance position of the virtual cleaning partition, taking a straight line DA in the forward direction of the robot as a vertical boundary line if the forward direction of the robot is the positive direction of the Y axis of the global coordinate system, taking a straight line CB parallel to the straight line DA at the position 5 m on the right side of the vertical boundary line as another vertical boundary line, and setting the vertical boundary line in the Y axis direction by the robot; the straight line DC perpendicular to the boundary line in the Y-axis direction at the crossing position D is a horizontal boundary line in the X-axis direction, and the straight line AB is parallel to the horizontal boundary line 5 meters above the horizontal boundary line, so that the line segment AD, the line segment BC, the line segment CD, and the line segment BA enclose the virtual cleaning partition ABCD in the area #5 as shown in fig. 4.
As one mode, after the robot cleans the cleaning partition ABCD, when moving to the position F, it detects that the current position is not cleaned, and the robot will continue to frame the next virtual cleaning partition in the non-cleaned area with the position F as the next entrance position; as a mode, after the robot cleans the cleaning partition ABCD, the robot navigates back to the position a according to the navigation boundary, continues to move forward to the position E in the positive direction of the Y axis, detects an uncleaned area, and continues to frame the next virtual cleaning partition in the uncleaned area by using the position E as the next entrance position.
Preferably, the navigation boundary is composed of a solid boundary and a virtual boundary, wherein the solid boundary is connected according to coordinate points of the edge of a wall or a wall-close obstacle in the cleaning area. The virtual boundary is a virtual route which is fit in the virtual cleaning partition and encloses a closed area with the solid boundary in order to realize navigation back to the initial starting point position. The virtual boundary is actually formed by connecting line segments, and the starting point and the end point of the virtual boundary are arranged on the boundary line of the wall body or the obstacle close to the wall or the virtual cleaning subarea. The closed area is an actual cleaning area that is set for navigation back to the initial starting position because the presence of wall obstacles causes the actual cleaning area coverage to be less than or equal to the coverage of the framed virtual cleaning zone.
Preferably, the distance between the starting point and the end point of the virtual boundary is larger than the width of the robot body, so that the robot directly crosses the boundary.
In the embodiment of the present invention, the area #1, the area #2 and the area #3 are planned as a working space, the navigation boundary is marked as shown in fig. 2, a charging seat of the robot is set as an initial position O, the robot moves in a positive direction of a Y axis from the point O, an uncleaned area is detected at a position h1 on the right side of the Y axis in the area #1 (including a rectangular area a1h1d1c1 and a rectangular area a1b1j2k2), the rectangular area a1c1d1h1 on the right side of the Y axis in the area #1 is framed as the virtual cleaning partition with the position h1 as an entrance position, wherein the route b1c1, the route c1d1, the route g1f1 and the route d1e1 are walls in the cleaning area and are marked as the entity boundary, and for the purpose of navigation backseat after cleaning is completed, a virtual cleaning area is fitted based on a navigation backseat function of a boundary line a boundary a1h1 of the virtual cleaning area of the virtual cleaning partition, for example, the route e1f1, the route h1a1, the route a1b1 and the route h1g1 can enclose a closed area a1c1d1h1 with the solid boundary, and the closed area a1c1d1h1 is used as the actual cleaning area, and the virtual routes are set as the virtual boundary in the virtual cleaning partition.
In the process of cleaning the virtual cleaning subarea, the robot marks the physical boundary and the virtual boundary as an obstacle boundary, cleans from left to right in a zigzag track form within the limit range of the obstacle boundary (within the actual cleaning area), marks boundary characteristic information of the physical boundary and the virtual boundary, constructs a local boundary map, and constructs a local grid map for marking obstacle information, such as position information representing the dotted line part of the dining table in the mark map 2. Since the rightmost boundary line of the virtual cleaning zone a1c1d1h1 is a wall, the robot cannot continue to sweep after reaching the rightmost boundary, and then navigate back to the entry position h1 of the virtual cleaning zone along the marked navigation boundary and then proceed in the positive Y-axis direction to detect an uncleaned area. As shown in fig. 2, the robot arrives at the position a1, and senses that there is an uncleaned area on the right side of the Y axis, and then, with the position a1 as the entrance position, new virtual cleaning partitions are framed in the area on the right side of the Y axis, such as a rectangular area k2j2b1a1, a route a1k2, a route k2j2 and a route a1b1, and enclose a closed area with the solid boundary j2b1, so as to be recorded as the virtual boundary.
When the robot finishes sweeping the virtual cleaning subarea k2j2b1a1, because a wall obstacle exists at the rightmost boundary line of the virtual cleaning subarea k2j2b1a1, the robot cannot continue sweeping after reaching the rightmost side, so the robot navigates back to the entrance position a1 of the virtual cleaning subarea along the marked navigation boundary and continues to advance to the position k2 along the positive direction of the Y axis, an uncleaned area exists in the area # 2 at the right side of the Y axis is detected, the position k2 is used as the entrance position, and the rectangular area k2l2h2g2 at the right side of the Y axis in the area #2 (including the rectangular area l2h2g2k2) is framed as the virtual cleaning subarea. Since the virtual clean zone has wall-by-wall obstacles such as sofas and bookcases, according to the above-described method of handling indoor obstacles, route d2a2, route a2b2, route b2c2, route i2f2, route f2e2, and route e2m2 are introduced, and these wall-by-wall obstacle edge lines are all recorded as the physical boundaries. And the route l2k2 and the route k2j2 are virtual routes for fitting around the solid boundary as the virtual boundary.
As an embodiment, when the robot continues to advance to the position k2 along the positive direction of the Y axis, it is detected that there is an uncleaned area in the area #3 (including the rectangular area j3l2i3l3 and the rectangular area j3h3g3k3) on the left side of the Y axis, and with the position k2 as the current entrance position, the rectangular area j3l2i3l3 on the left side of the Y axis is framed as the current virtual cleaning partition, so that the virtual routes i3l3, i3j3 and the physical boundaries are fitted in the rectangular area j3l2i3l3 to form a closed area, which is referred to as the virtual boundary. When the robot has cleaned rectangular area j3l2i3l3, the robot moves to position j3, detects an uncleaned area, and frames rectangular area j3h3g3k3 in area # 3 as the next virtual cleaning zone with position j3 as the next entrance position. In the rectangular area j3h3g3k3, like corner cabinets and beds, can be regarded as wall-approaching obstacles, so besides the routes f3d3, c3j3, i3h3, g3h3 and g3e3 as walls, the edge lines of the wall-approaching obstacles (corner cabinets and beds) are also recorded as the solid boundaries, such as the routes e3f3, d3a3, a3b3 and b3c3, and the fitted virtual route i3j3 encloses a closed area with the solid boundaries.
A navigation method of a robot, which is planned based on the boundary feature information, comprising the steps of: in the step 1, when the robot starts navigation, the current position of the robot is obtained, the position of a target point is determined, and the step 2 is entered; in step 2, according to the global boundary map and the local grid map in the current area, taking the current position of the robot as a starting point and the position of a target point as an end point, combining the boundary characteristic information of the navigation boundary, selecting a navigation path, and entering step 3; and 3, navigating the robot according to the selected navigation path.
The specific method for selecting the navigation path in step 2 of the navigation method comprises the steps of planning the navigation path by using the navigation boundary according to the position conditions of the starting point and the end point determined by the robot in step 21, and entering step 22; in step 22, judging whether the length of the entity boundary exists on the path selected by planning and is greater than the preset boundary length, if so, selecting the path with the largest length of the entity boundary as a navigation path, wherein the length of the entity boundary is the navigation factor which is considered preferentially; otherwise, entering step 23; step 23, judging whether the rotation angle of the robot on the planned and selected path is smaller than a preset rotation angle, if so, selecting one of the paths with the largest length of the entity boundary as a navigation path, wherein the length of the entity boundary is smaller than or equal to the length of the preset boundary, but the rotation angle of the robot on the selected path is smaller than the preset rotation angle, and the length of the entity boundary is still set as a navigation factor to be considered preferentially; and if not, selecting one with the smallest rotation angle of the robot as a navigation path, wherein the rotation angle of the robot on the selected path is larger than or equal to the preset rotation angle, and setting the rotation angle of the robot on the selected path as a navigation factor to be considered preferentially in order to reduce the error rate caused by the turning of the robot.
The physical boundary is selected to enable the robot to walk along the wall, because the wall is straight and the surrounding wall should form a rectangle, when the robot walks along the wall, the collected distance information from the wall is reliable relative to the virtual boundary, so that the larger the length of the physical boundary on the navigation path is, the lower the navigation error rate is; the path having a small turning angle is selected to reduce the error in the rotation angle of the robot.
Specifically, the preset boundary length is a reference length used for weighing priority of the length of the physical boundary in a planned navigation path, and in order to implement recoil charging using a navigation boundary, the preset boundary length is determined according to the virtual cleaning partition, and is generally equal to the preset length of the virtual cleaning partition, and the value of the preset boundary length is set to 5, and the unit is meter.
Specifically, the preset rotation angle is a reference angle used for balancing the priority of the rotation angle of the robot in a planned navigation path, the preset rotation angle is determined according to the distribution situation of obstacles in the working space, and the preset rotation angle is set to be 180 degrees in order to reduce the error rate caused by the rotation of the robot.
The invention provides a comparative analysis of an embodiment of a backseat navigation, as shown in fig. 2, after the robot cleans a rectangular virtual cleaning partition a1c1d1h1 framed in an area #1, the robot stops at a position a, and then according to boundary characteristic information recorded by the global boundary map, a navigation path 1 and a navigation path 2 with the physical boundary are preliminarily planned to serve as paths for the robot to navigate from the position a to a position h1, wherein the navigation path 1 is composed of the physical boundary b1c1, the virtual boundary a1b1 and the virtual boundary a1h1, the navigation path 2 is composed of the physical boundary c1d1, the physical boundary g1f1, the physical boundary e1d1, the virtual boundary h1g1 and the virtual boundary f1e1, and the rotation angle of the robot on the two navigation paths is 90 degrees and is smaller than the preset rotation angle; and the virtual boundary in the navigation path 1 is significantly more than that of the navigation path 2, that is, the entity boundary on the navigation path 2 is longer than that of the navigation path 1, but the lengths of the entity boundaries on the navigation path 2 and the navigation path 1 are both smaller than the preset boundary length, so that under the condition that the length of the entity boundary on the selected path is smaller than that of the preset boundary, according to the judgment whether the rotation angle of the robot on the path selected by planning is smaller than the preset rotation angle or not, if so, the one with the largest length of the entity boundary is selected as the navigation path, and the robot preferentially selects the navigation path 2 to carry back the seat charging in the virtual cleaning partition a1c1d1h1 is obtained.
In combination with the characteristics of the rotation angle and the physical boundary length during the robot walking process, the present invention provides another embodiment of seat returning navigation for comparative analysis, as shown in fig. 2, after the robot cleans the rectangular virtual cleaning partition k2l2h2g2 framed in the area # 2, the robot stops at the position B, and the path navigated by the position B to seat returning has navigation path 3 and navigation path 4. On a navigation path 3, according to boundary feature information recorded by the global boundary map and the local grid map reserved in the current area, the robot plans that a 90-degree corner is located at a position n2 pointing to the physical boundary B2c2 (composed of a wall-approaching obstacle sofa) from a position B, then the robot reaches the physical boundary j2i2 along a route n2i2, and then the robot has a 90-degree corner, points to the virtual boundary l2k2 on the Y axis of the coordinate system of the global boundary map through the virtual boundary j2k2, and finally achieves recoil charging along the Y-axis negative direction, wherein the rotation angle of the robot on the path is equal to a preset rotation angle; similarly, the robot navigates back along the navigation path 4 to charge, and compared with the navigation path 3, the robot rotates 90 degrees at the position i2, the position f2 and the position e2 of the navigation path 4, rotates 270 degrees altogether, is greater than the preset rotation angle, and rotates 90 degrees more than the navigation path 3, the physical boundary of the navigation path 4 has a wall j2i2, an edge line e2f2 and an edge line e 2i2 of a bookcase, the length of the physical boundary used by the robot is greater than the length of the physical boundary in the navigation path 3, but is less than the length of the preset boundary, so that when the length of the physical boundary on the selected path is less than the length of the preset boundary, according to the judgment in step 23 whether the rotation angle of the robot on the path selected by planning is less than the preset rotation angle, if so, the one with the largest length of the physical boundary is selected as the navigation path, otherwise, the smallest rotation angle of the robot is selected as the navigation path, and obtaining a preferential navigation path 3 for seat returning charging.
According to the characteristics of the lengths of the physical boundaries on the navigation path, the invention further provides a comparative analysis of an embodiment of the backseat navigation, as shown in fig. 2, after the robot cleans the rectangular virtual cleaning partition h3g3k3j3 framed in the area #3, the robot stops at the position C, the navigation path of the backseat from the position C is composed of a navigation path 5 and a navigation path 6 according to the boundary characteristic information recorded by the global boundary map and the local grid map reserved in the current area, as shown in fig. 2, the navigation path 5 is composed of the physical boundary Cg3, the physical boundary g3h3, the physical boundary h3i3 and the virtual boundary i3l3, the physical boundary used for navigation is longer than the lengths of the physical boundaries f3d3, d3a3 and a3b3 used by the navigation path 6, and the lengths of the physical boundaries on the navigation path 5 and the navigation path 6 are both longer than the preset boundary length, and the rotation angle of the robot on the navigation path 6 is as large as the rotation angle of the robot on the navigation path 5, is both 270 degrees and larger than the preset rotation angle, so that whether the length of the entity boundary on the path selected by the planning judgment in the step 22 is larger than the preset boundary length or not is judged, if so, the path with the largest length of the entity boundary is selected as the navigation path, and the navigation path 5 is preferentially selected for navigation.
Those of ordinary skill in the art will understand that: all or a portion of the steps of implementing the above-described method embodiments may be performed by hardware associated with program instructions. These programs may be stored in a computer-readable storage medium (such as a ROM, a RAM, a magnetic or optical disk, or various other media that can store program codes). Which when executed performs steps comprising the method embodiments described above.
Finally, it should be noted that: the above embodiments are only used to illustrate the technical solution of the present invention, and not to limit the same; while the invention has been described in detail and with reference to the foregoing embodiments, it will be understood by those skilled in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some or all of the technical features may be equivalently replaced; and the modifications or the substitutions do not make the essence of the corresponding technical solutions depart from the scope of the technical solutions of the embodiments of the present invention.
Claims (5)
1. A navigation method of a robot is characterized in that the navigation method is planned based on boundary characteristic information and comprises the following steps:
step S1: when the robot is started, a virtual cleaning subarea is framed in a working space, boundary characteristic information of a navigation boundary is marked in the process of cleaning the virtual cleaning subarea, a local boundary map is constructed, and the step S2 is carried out;
step S2: converting the coordinate system of the data of the local boundary map in the virtual cleaning partition, adding the data into a global coordinate system, and entering the step S3;
step S3: after the virtual cleaning subareas are cleaned, moving to an area which is not cleaned, and repeating the steps S1-S2 until a complete working space is cleaned to obtain a global boundary map;
the boundary characteristic information comprises a starting point coordinate of a navigation boundary, an end point coordinate of the navigation boundary and a rotation angle of the robot walking along the navigation boundary;
the navigation boundary consists of an entity boundary and a virtual boundary, wherein the entity boundary is connected according to coordinate points of the edge of a wall body or a wall-close obstacle in the virtual cleaning partition; the virtual boundary is a virtual route which is fit into the virtual cleaning subarea and forms a closed area with the solid boundary in order to realize navigation back to the initial starting point position;
wherein the closed area is an actual cleaning area provided for navigation back to the initial starting position;
the navigation method further comprises the following steps:
step 1: when the robot starts navigation, acquiring the current position of the robot, determining the position of a target point, and entering step 2;
step 2: selecting a navigation path by taking the current position of the robot as a starting point and a target point position as an end point according to a global boundary map and a current local grid map and combining boundary characteristic information of the navigation boundary, and entering step 3;
and step 3: the robot navigates according to the selected navigation path;
the specific method for selecting the navigation path in step 2 of the navigation method comprises the following steps:
step 21: according to the starting point position and the end point position determined by the robot, the navigation boundary is used for planning a navigation path, and the step 22 is carried out;
step 22: judging whether the length of the entity boundary existing on the planned and selected path is larger than the preset boundary length, if so, selecting the path with the largest entity boundary length as a navigation path; otherwise, entering step 23;
step 23: judging whether the rotation angle of the robot on the planned and selected path is smaller than a preset rotation angle or not, if so, selecting one with the largest length of the entity boundary as a navigation path, and otherwise, selecting one with the smallest rotation angle of the robot as the navigation path;
wherein the preset boundary length is a reference length used for weighing the priority of the length of the entity boundary in planning a navigation path; the preset rotation angle is a reference angle used for balancing the priority of the robot rotation angle in planning a navigation path.
2. The navigation method according to claim 1, wherein the robot frames the current virtual cleaning zone, marks boundary feature information of a navigation boundary during cleaning, constructs a local boundary map, and constructs a local grid map according to the marked obstacle information, until the robot starts cleaning the next virtual cleaning zone, the local grid map is deleted and replaced by the local grid map constructed in the next virtual cleaning zone.
3. The navigation method according to claim 1, wherein the global boundary map is constructed by first determining the global coordinate system with the initial starting position of the robot as the origin and the forward direction of the robot from the initial starting position as the positive direction of the Y-axis.
4. The navigation method according to claim 1 or 3, wherein the virtual cleaning partition is determined by making a straight line parallel to the Y-axis passing through the current entrance position of the robot on the global coordinate system as a vertical boundary line, making a straight line n meters away from and parallel to the vertical boundary line as another vertical boundary line, and setting the vertical boundary line in the Y-axis direction by the robot; drawing a straight line perpendicular to the vertical boundary line as a horizontal boundary line passing through the current entrance position of the robot, and taking a straight line which is m meters away from and parallel to the horizontal boundary line as another horizontal boundary line; the vertical boundary line and the horizontal boundary line are encircled to form the virtual cleaning subarea; the robot continues to move after finishing sweeping the current virtual cleaning subarea, and when an uncleaned area is detected, the current position is taken as the next entrance position, and the next virtual cleaning subarea is continuously framed according to the method;
wherein the variable n represents the preset length of the virtual cleaning partition, and the variable m represents the preset width of the virtual cleaning partition.
5. The navigation method of claim 1, wherein the distance between the start point and the end point of the virtual boundary is greater than the robot body width.
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