CN111113364B

CN111113364B - Walking robot, method of controlling walking robot, and walking robot system

Info

Publication number: CN111113364B
Application number: CN202010020642.3A
Authority: CN
Inventors: 马妙武
Original assignee: Shanghai Shanke Robot Co ltd
Current assignee: Shanghai Shanke Robot Co ltd
Priority date: 2020-01-09
Filing date: 2020-01-09
Publication date: 2023-07-07
Anticipated expiration: 2040-01-09
Also published as: CN111113364A

Abstract

The invention provides a walking robot, a walking robot system and a method for controlling the walking robot. The walking robot includes: a main body; and a control mechanism configured to perform operations comprising: controlling the main body to walk along a boundary line of a predetermined operation area, and sampling a walking path to acquire data of a set of all boundary sampling points on the boundary line; dividing the predetermined operation region into at least two sub-regions based on at least three boundary sampling points in the set of boundary sampling points; and for each sub-region, determining information of the sub-region respectively, wherein the information of the sub-region at least comprises coordinates of boundary sampling points in the sub-region.

Description

Walking robot, method of controlling walking robot, and walking robot system

Technical Field

The present invention relates to a walking robot, and more particularly, to a walking robot capable of performing work in a predetermined operation area, a method of controlling the walking robot, and a walking robot system including the walking robot.

Background

There are various walking robots on the market at present, such as a robot for mowing, a robot for sweeping floor, a robot for mopping floor, etc. Taking a mowing robot as an example, a mainstream mowing robot generally performs mowing work in a mode of traveling along a random path. This mowing pattern of walking along a random path is better able to meet the trimming of regular lawns, however, a longer time is required to reach a certain degree of traversal (e.g. at least 99% traversal). Also, this mowing pattern can cause a large number of areas to be repeatedly trimmed, resulting in low energy utilization and accelerated equipment depreciation.

In view of the above problems, some walking robots that walk along a regular path have been proposed in the art. For example, a high-precision positioning device (such as a GPS module) may be mounted on the mowing robot. By accurate positioning of the positioning device, the mowing robot can walk according to a preset regular path, such as a reciprocating zigzag path or a spiral path, and the like, so that the effect of high-efficiency traversal is achieved. However, the effect of such efficient traversal is mainly dependent on the high accuracy of the positioning means mounted on the robot mower, which makes the cost of such a robot mower greatly increased. On the other hand, if the positioning accuracy is insufficient, it is difficult to ensure that the mowing robot operates in accordance with a predetermined route, resulting in omission between adjacent traveling paths.

Disclosure of Invention

In view of at least one of the above problems, in one aspect, the present invention proposes a solution for facilitating a walking robot to traverse an entire operation area by determining feature points of the operation area of the walking robot.

On the other hand, the invention also provides a scheme capable of realizing efficient traversal of the operation area even under the condition of low-precision positioning.

According to some aspects of the present invention, a walking robot is provided. The walking robot includes: a main body; and a control mechanism configured to perform operations comprising: controlling the main body to walk along a boundary line of a predetermined operation area, and sampling a walking path to acquire data of a set of all boundary sampling points on the boundary line; dividing the predetermined operation region into at least two sub-regions based on at least three boundary sampling points in the set of boundary sampling points; and for each sub-region, determining information of the sub-region respectively, wherein the information of the sub-region at least comprises coordinates of boundary sampling points in the sub-region.

According to further aspects of the present invention, a walking robot system is provided. The walking robot system comprises a walking robot as described above and a base station comprising a feed module for feeding a boundary line connected thereto for generating an electromagnetic signal around the boundary line.

According to further aspects of the present invention, a method of controlling a walking robot is provided. The method comprises the following steps: controlling a main body of the walking robot to walk along a boundary line of a predetermined operation area, and sampling a walking path to acquire data of a set of all boundary sampling points on the boundary line; dividing the predetermined operation region into at least two sub-regions based on at least three boundary sampling points in the set of boundary sampling points; and for each sub-region, determining information of the sub-region respectively, wherein the information of the sub-region at least comprises coordinates of boundary sampling points in the sub-region.

Drawings

Fig. 1 shows an external schematic view of a walking robot according to the present invention;

fig. 2 shows a schematic view of an internal structure of the walking robot according to the present invention;

fig. 3 shows a schematic view of an operating area of a walking robot according to the present invention;

Fig. 4 shows a flow chart of a method of operation of the walking robot according to the invention in one mode of operation;

fig. 5 shows a flow chart of a method of operation of the walking robot according to the invention in another mode of operation;

fig. 6 is a schematic view showing a state when the walking robot reaches one boundary feature point according to the present invention;

fig. 7A and 7B are schematic views showing missing parts generated in the vicinity of boundary feature points of a walking robot equipped with a low-precision positioning device;

FIG. 8 shows a schematic diagram of one method of handling missing parts near boundary feature points by a walking robot according to the present invention;

FIG. 9 shows a schematic diagram of another method of processing missing parts near boundary feature points by a walking robot according to the present invention; and

fig. 10 shows a schematic view of an irregular operating region according to the present invention.

Detailed Description

The following detailed description of various embodiments of the present invention will be provided in connection with the accompanying drawings to provide a clearer understanding of the objects, features and advantages of the present invention. It should be understood that the embodiments shown in the drawings are not intended to limit the scope of the invention, but rather are merely illustrative of the true spirit of the invention.

In the following description, for the purposes of explanation of various disclosed embodiments, certain specific details are set forth in order to provide a thorough understanding of the various disclosed embodiments. One skilled in the relevant art will recognize, however, that an embodiment may be practiced without one or more of the specific details. In other instances, well-known devices, structures, and techniques associated with this application may not be shown or described in detail to avoid unnecessarily obscuring the description of the embodiments.

Throughout the specification and claims, unless the context requires otherwise, the word "comprise" and variations such as "comprises" and "comprising" will be understood to be open-ended, meaning of inclusion, i.e. to be interpreted to mean "including, but not limited to.

Reference throughout this specification to "one embodiment" or "an embodiment" means that a particular feature, structure, or characteristic described in connection with the embodiment is included in at least one embodiment. Thus, appearances of the phrases "in one embodiment" or "in an embodiment" in various places throughout this specification are not necessarily all referring to the same embodiment. Furthermore, the particular features, structures, or characteristics may be combined in any suitable manner in one or more embodiments.

As used in this specification and the appended claims, the singular forms "a," "an," and "the" include plural referents unless the context clearly dictates otherwise. It should be noted that the term "or" is generally employed in its sense including "and/or" unless the context clearly dictates otherwise.

In the following description, for the purposes of clarity of presentation of the structure and manner of operation of the present invention, the description will be made with the aid of directional terms, but such terms as "forward," "rearward," "left," "right," "outward," "inner," "outward," "inward," "upper," "lower," etc. are to be construed as convenience, and are not to be limiting.

Fig. 1 shows a schematic view of the appearance of a walking robot 1 according to the invention. Fig. 2 shows a schematic view of the internal structure of the walking robot 1 according to the present invention. The walking robot 1 may be similar in appearance to some walking robots in the prior art, as described in chinese patent application publication No. CN 109673241 a. Specifically, as shown in fig. 1, the walking robot 1 may include a main body 10 and a control mechanism 20. The control mechanism 20 may be provided inside or outside the main body 10 for controlling the travel route of the main body 10. The body 10 further comprises a running gear 30. In some implementations, the running gear 30 includes a pair of drive wheels 32 disposed at the rear of the body 10 and one or more driven wheels (not shown) disposed at the front of the body 10. In these implementations, the body 10 also includes one or a pair of drive motors 12 (see fig. 2) for driving the drive wheels 32 under the control of the control mechanism 20 to drive the body 10 to walk, such as to drive the body 10 forward, backward, steer, etc. The driven wheel may be provided as a universal wheel which supports the body 10 together with the driving wheel 32 and moves with the movement of the driving wheel 32. Those skilled in the art will appreciate that the arrangement of the running gear 30 is not limited to that described herein and shown in the drawings, but may have various arrangements according to the function and structure of the running robot 1. For example, in the case where the walking robot 1 is a floor sweeping robot or a floor mopping robot having a circular outer shape, the driving wheels 32 of the walking mechanism 30 may be provided at both ends of one diameter of the circular bottom surface, and the driven wheels may be provided at one end or both ends of the other diameter perpendicular to the diameter where the driving wheels 32 are provided, or may not be provided.

Further, the walking robot 1 may further include a working mechanism (not shown in the drawing) that performs a specific operation function when the main body 10 walks within a specific operation region. For example, in the case where the walking robot 1 is a mowing robot, the work mechanism may include a work drive motor and a work device, such as a cutting device, provided below the main body 10 and driven by the work drive motor for trimming turf on a walking path as the walking robot 1 walks. Also for example, in the case where the walking robot 1 is a floor sweeping robot, the working mechanism may include a working drive motor and a working device, such as one or more cleaning brushes, dust suction ports, and the like, provided below the main body 10 and driven by the working drive motor.

Furthermore, the walking robot 1 may further include an energy source mechanism (not shown in the figure). In some implementations, the energy source mechanism includes a removable or non-removable lithium ion battery pack or other rechargeable battery, or the like. Alternatively, in some implementations, the energy mechanism may also include a power cord, an ac-to-dc converter, etc. to connect to an external ac power source.

The control mechanism 20 is configured to perform various functions including: the control main body 10 walks along the boundary line of the predetermined operation region, and samples the boundary line to acquire a set of all boundary sampling points on the boundary line.

Fig. 3 shows a schematic view of the operating area 4 of the walking robot 1 according to the invention. As shown in fig. 3, the operation area 4 is a work area where the walking robot 1 performs work such as mowing, sweeping, and the like, and a boundary line 3 is provided in advance around the operation area 4 to define the operation area 4. Fig. 3 shows the operating area 4 exemplarily in a rectangular shape, however, it will be appreciated by a person skilled in the art that the operating area 4 may also be in any other possible shape.

In the initial situation, the walking robot 1 may be located at any point on or in a closed loop constituted by the boundary line 3, for example. For simplicity, it is assumed that the walking robot 1 is initially located at the base station 2 mounted on the boundary line 3, as shown in fig. 3. The base station 2 may for example comprise a feeding module for feeding a boundary line 3 connected thereto, so that an electromagnetic signal is generated around the boundary line 3. The walking robot 1 can continuously sense the electromagnetic signal while walking to walk along the boundary line 3 in different operation modes or judge whether it is located within the operation region 4 according to the polarity of the sensed electromagnetic signal. Here, the boundary line 3 may be, for example, a metal wire capable of receiving a feed and generating an electromagnetic signal, however, it will be appreciated by those skilled in the art that the boundary line 3 may also be other forms of tangible or intangible boundary.

In some implementations, the base station 2 may also include a charging module that charges the walking robot 1 while the walking robot 1 resides thereon.

Fig. 4 shows a flow chart of a method 400 of operation of the walking robot 1 according to the invention in one mode of operation. Specifically, fig. 4 shows a flowchart of a method 400 of determining map information of the operation area 4 in an initial state of the walking robot 1. The method 400 is described below in connection with fig. 1-4.

In the method 400, the control mechanism 20 first determines whether the walking robot 1 is in the initial position in step 410. For simplicity, it is assumed that the walking robot 1 is in an initial position when located at the base station 2, as shown in fig. 3. For example, the control mechanism 20 may determine whether the walking robot 1 is at the base station 2 by determining whether the walking robot 1 is connected to the base station 2 or whether the distance between the two is smaller than a very small value, thereby determining whether the walking robot 1 is at the initial position.

If control mechanism 20 determines that walking robot 1 is not in the initial position, method 400 proceeds to step 420, where walking robot 1 is adjusted to the initial position. Here, the walking robot 1 may be adjusted to the initial position by various means. For example, in some implementations, walking robot 1 may sense electromagnetic signals around boundary line 3, thereby capturing boundary line 3, and return to an initial position (as at base station 2) along boundary line 3. Alternatively, in some other implementations, the walking robot 1 may also be placed at the base station 2 manually by an operator. The invention is not limited in this respect.

On the other hand, if the control mechanism 20 determines that the walking robot 1 is in the initial position, the method 400 proceeds to step 430, wherein the control mechanism 20 establishes a coordinate system for subsequent boundary point sampling. For example, the control mechanism 20 may establish a cartesian plane coordinate system XOY with the center of the walking robot 1 or with a projected position of a midpoint of an axle connecting the pair of driving wheels 32 on a horizontal plane as the origin of coordinates O, with the direction of extension of the walking robot 1 from the base station 2 to the boundary line 3 in the first direction (e.g., clockwise direction) as the X-axis, as shown in fig. 3. However, it will be understood by those skilled in the art that the present invention is not limited thereto, but various other coordinate systems may be established as needed, such as a planar polar coordinate system, etc., and the origin of coordinates is not limited to the center of the walking robot 1, but may be any other reference point, such as a projection position of the geometric center of the walking robot 1 on a horizontal plane, or a projection position of the geometric center of the working mechanism on a horizontal plane, etc. Further, the establishment of the planar coordinate system XOY is not limited to the above manner, and the directions of the X axis and the Y axis shown in fig. 3 may be exchanged, or the directions of the X axis and the Y axis may be arbitrarily set. In the embodiment in which the walking robot 1 is equipped with a geomagnetic sensor, it is also optional to extend the X-axis or the Y-axis toward the geomagnetic north or south pole.

Next, at step 440, the control mechanism 20 controls the walking robot 1 to walk in a predetermined direction (e.g., clockwise) along the boundary line 3 from the base station 2, and samples the boundary line 3.

In some implementations, the control mechanism 20 may further include a main controller 22, a mileage acquisition module 24 and a heading acquisition module 26 coupled to the main controller 22, and a memory 28, as shown in FIG. 2. The mileage acquisition module 24 may be used to acquire the traveling mileage of the traveling robot 1, and the direction acquisition module 26 may be used to acquire the heading deflection angle of the traveling robot 1. Specifically, the driving motor 12 may be provided with a photoelectric encoder to detect the radian of the driving wheel 32 rotated within a certain period of time, and the mileage acquisition module 24 and the heading acquisition module 26 may calculate the movement mileage and the heading deflection angle of the walking robot 1 within a certain period of time according to the result of the detection of the photoelectric encoder in combination with the radius of the driving wheel 32. In other embodiments, gyroscopes may be used in place of photoelectric encoders. In other embodiments, both gyroscopes and photoelectric encoders may be used to make corrections to each other. Further, a geomagnetic sensor may be provided on the main body 10 to compensate for an accumulated error of the photoelectric encoder and/or the gyroscope to improve accuracy.

In step 440, control mechanism 20 samples points on boundary line 3, which are referred to as boundary sampling points, at predetermined times or distances. Further, the control mechanism 20 (e.g., the main controller 22) may calculate coordinates of the boundary sampling points based on the range and the yaw angle, and store the coordinates of the boundary sampling points in the form of a linked list in the memory 28.

The walking robot 1 may walk along the boundary line 3 after being rotated 180 ° in place after being driven away from the initial position in the first direction, or may walk in a backward manner directly in the first direction, depending mainly on whether the walking robot 1 supports the backward walking manner.

Next, at step 450, the control mechanism 20 determines whether data of a set of all boundary sampling points on the boundary line 3 has been obtained. For example, the control mechanism 20 may determine whether its travel path forms a closed curve or whether the walking robot 1 returns to the original position again, such as in contact with the base station 2 or in close proximity, to determine whether the sampling of the entire boundary line 3 has been completed.

Specifically, after the coordinates of all the boundary sampling points are acquired, the control mechanism 20 may store the coordinates of all the boundary sampling points in the memory 28, for example, as shown in table 1.

Table 1 boundary sample point list

Sampling point sequence number	Coordinates of sampling points
		1	(u ₁ ,v ₁ )
2	(u ₂ ,v ₂ )
		…	…
N	(u _n ,v _n )

Here, the full set of boundary sample points shown in Table 1 may be denoted as B _n ＝{b ₁ ,b ₂ ,b ₃ ,…,b _n-1 ,b _n -boundary sampling point b _i (1. Ltoreq.i.ltoreq.n) has a coordinate of (u) _i ,v _i ) N represents the number of boundary sampling points obtained on the boundary line 3, and n is a positive integer.

If it is determined at step 450 that all boundary sample points have not been acquired, the method 400 returns to step 440 to continue.

On the other hand, after the sampling of the entire boundary line 3 is completed, the control mechanism 20 may sample the set B of points from the boundary in step 460 _n Boundary feature points are determined to form map information of the operation area 4. Wherein the map information includes at least a list of coordinates of the boundary feature points.

Based on the coordinate information of the boundary sampling points as shown in table 1, the control mechanism 20 can determine profile information of the operation region 4, such as the area and shape. Further, the control mechanism 20 may determine the number threshold condition of the required boundary feature points, such as a number threshold or a number threshold range, from the profile information of the operation region 4, and then sample the set B of points from the boundary _n Boundary feature points that meet the number threshold or range of number thresholds are selected.

In some embodiments, curve fitting may be performed on boundary sampling points, and points with a larger curvature on the fitted curve may be selected as boundary feature points. For example, a set of boundary sampling points may be fitted using a curvature method, a circumscribed circle method, a vector method, or the like to determine the curvature of each boundary sampling point, thereby selecting a corresponding boundary feature point therefrom.

How the control mechanism 20 selects the boundary feature points from the boundary sampling points will be described in detail below using the curvature method as an example. As described above, the control mechanism 20 can determine the shape and the area of the operation region 4 from the coordinates of the boundary sampling points as shown in table 1, thereby automatically generating the threshold value m of the number of feature points ₀ Or a threshold range of numbers [ m ] _min ,m _max ]. Generally, the more area a particular operating region isThe larger and more complex the shape, the more boundary feature points are needed. For example, if the area of the operation region is too small or the shape is too simple, such as a convex polygon, the threshold value of the number of boundary feature points may be determined to be a small value, such as 3. Threshold m of number of boundary feature points ₀ Or a threshold range of numbers [ m ] _min ,m _max ]May be selected from a list of alternative thresholds or threshold ranges stored in memory 28.

When the number of boundary feature points within the operation region 4 calculated with a certain curvature threshold value is equal to the number threshold value m ₀ Or falls within a number threshold range [ m ] _min ,m _max ]In this case, it can be determined that there are boundary feature points satisfying the condition within the operation region 4 and that corresponding boundary feature points can be determined.

In one implementation, control mechanism 20 sets a curvature threshold k for operating region 4 ₀ . Control mechanism 20 may sample set B of boundary sample points shown in Table 1 _n Curve fitting is performed to calculate the curvature k of each boundary sampling point _i (1. Ltoreq.i.ltoreq.n), and the curvature k of each boundary sampling point is calculated _i Respectively with a curvature threshold k ₀ Comparing to determine that the curvature threshold k is greater than ₀ The number of boundary sampling points is set as m ₁ 。

Control mechanism 20 determines a number m of boundary sampling points greater than curvature threshold k0 ₁ Whether or not it is equal to the number threshold m0 or falls within the number threshold range [ m ] _min ,m _max ]. If m is ₁ Equal to the number threshold m ₀ Or falls within a number threshold range [ m ] _min ,m _max ]Then the m is ₁ The boundary sampling points are determined as boundary feature points.

On the other hand, in some embodiments, if m ₁ Not equal to the number threshold m ₀ Or does not fall within the number threshold range [ m ] _min ,m _max ]The control mechanism 20 may further determine at least two different proper subsets of the set of boundary sample points, wherein the number of elements of each proper subset is the same, n- (k-1), where n is the set of boundary sample points B _n K is the number of proper subsets. Preferably, eachThe spacing between adjacent elements in the true subset is equal. The control mechanism 20 may compare the curvatures of the boundary sampling points in the k true subsets to the curvature threshold, respectively, to determine the number of boundary sampling points in each true subset having a curvature greater than the curvature threshold. If only one proper subset of the k proper subsets meets the quantity threshold condition, selecting boundary sampling points in the proper subset as boundary feature points; if more than one of the k proper subsets satisfies the number threshold condition, selecting a boundary sampling point of any one of the more than one proper subset as a boundary feature point; and if none of the k proper subsets meets the number threshold condition, set B may be further processed _n Dividing into more proper subsets (e.g. l, l>k) And the above operation is repeated.

For example, assuming k=2, control mechanism 20 may determine set B _n Is a proper subset of (2)

And->

Next, the control mechanism 20 performs curve fitting on the two proper subsets, respectively, and calculates the curvature at each boundary sampling point in each proper subset, and compares the obtained curvature with the curvature threshold k, respectively ₀ Comparing to determine that the curvatures in the two proper subsets are greater than the curvature threshold k ₀ The number of boundary sampling points of (1), respectively, is assumed to be m ₂₁ And m ₂₂ . Next, the control mechanism 20 determines the number m ₂₁ And m ₂₂ Whether or not to equal the number threshold m ₀ Or falls within a number threshold range [ m ] _min ,m _max ]. If the number m ₂ 1 or m ₂₂ Equal to the number threshold m ₀ Or falls within a number threshold range [ m ] _min ,m _max ]Will correspond to m ₂₁ Or m ₂₂ The boundary sampling points are selected as boundary feature points. If the number m ₂₁ And m ₂₂ Are all equal to the number threshold m ₀ Or falls within a number threshold range [ m ] _min ,m _max ]Then arbitrarily select the m ₂₁ Or m ₂₂ The boundary sampling points are used as boundary feature points.

Conversely, if the number m ₂₁ And m ₂₂ Are not equal to the quantity threshold m ₀ Or none fall within the number threshold range [ m ] _min ,m _max ]Control mechanism 20 may further determine set B of boundary sampling points _n Wherein the number of elements of each proper subset is the same and n- (l-1), wherein n is set B _n The number of boundary sampling points in (1), i being the number of proper subsets, and i>k. Preferably, the spacing between adjacent elements in each true subset is equal. For example, assuming l=3, control mechanism 20 may determine set B _n Is a proper subset of three of (3)

And->

Next, the control mechanism 20 performs curve fitting on the three proper subsets, respectively, and calculates the curvature at each boundary sampling point in each proper subset, and compares the obtained curvature with the curvature threshold k, respectively ₀ Comparison is performed to determine that the curvatures in the three proper subsets are greater than the curvature threshold k, respectively ₀ The number of boundary sampling points of (1), respectively, is assumed to be m ₃₁ 、m ₃₂ And m ₃₃ . Next, the control mechanism 20 determines the number m ₃₁ 、m ₃₂ And m ₃₃ Whether or not to equal the number threshold m ₀ Or falls within a number threshold range [ m ] _min ,m _max ]. If the number m ₃₁ 、m ₃₂ And m ₃₃ Is equal to the quantity threshold m ₀ Or falls within a number threshold range [ m ] _min ,m _max ]Will correspond to m ₃₁ 、m ₃₂ Or m ₃₃ The boundary sampling points are selected as boundary feature points. If the number m ₃₁ 、m ₃₂ And m ₃₃ At least two of which are equal to the quantity threshold m ₀ Or fall down toThreshold range of number of entries [ m ] _min ,m _max ]The boundary sampling point of any one of the at least two satisfied true subsets is arbitrarily selected as the boundary feature point.

If none of the three proper subsets still satisfies the threshold condition, the algorithm may continue until a subset is found that satisfies the threshold condition for the number of boundary feature points.

The embodiments of determining boundary feature points are not limited to those described above. In other embodiments, the partitioning of the proper subset may take different forms. In particular, if m ₁ Not equal to the number threshold m ₀ Or does not fall within the number threshold range [ m ] _min ,m _max ]The control mechanism 20 may further determine at least two proper subsets of the set of boundary sampling points, wherein elements of each proper subset are different from each other and the number of elements of each proper subset is substantially equal to set B _n Wherein k is the number of proper subsets, i.e. dividing set B substantially equally _n . The control mechanism 20 may compare the curvatures of the boundary sampling points in the k true subsets to the curvature threshold, respectively, to determine the number of boundary sampling points in each true subset having a curvature greater than the curvature threshold. If only one proper subset of the k proper subsets meets the quantity threshold condition, selecting boundary sampling points in the proper subset as boundary feature points; if more than one of the k proper subsets satisfies the number threshold condition, selecting a boundary sampling point of any one of the more than one proper subset as a boundary feature point; and if none of the k proper subsets meets the number threshold condition, set B may be further processed _n Dividing into more proper subsets (e.g. l, l>k) And the above operation is repeated.

And

if the number m is obtained from these two proper subsets ₂₁ And m ₂₂ If none of the number threshold conditions is met, control mechanism 20 may further determine set B of boundary sampling points _n Wherein the elements of each proper subset are different from each other and the number of elements of each proper subset is substantially equal to set B _n 1/l of the number of elements of (1), where l is the number of proper subsets, and l>k, i.e. dividing the set B substantially equally _n . Preferably, the spacing between adjacent elements in each true subset is substantially equal. For example, assuming l=3, control mechanism 20 may determine set B _n Is a proper subset of three of (3)

And

next, the control mechanism 20 performs curve fitting on the three proper subsets, respectively, to determine whether the number threshold condition is satisfied. Similar to the above embodiment, the algorithm may continue until a subset of the number threshold conditions for the boundary feature points are found.

In the above method, the control mechanism 20 may also adjust the curvature threshold k if a subset satisfying the threshold condition of the number of boundary feature points cannot be found at all times ₀ And repeating the above calculation. For example, if each subset calculated as above meets the curvature threshold k ₀ The number of sampling points is smaller than the threshold condition of the number of the characteristic points, so that the curvature threshold k can be reduced ₀ Repeating the calculation; if each subset meets the curvature threshold k ₀ The number of sampling points of the curvature threshold k can be increased if the number of sampling points is larger than the threshold condition of the number of the characteristic points ₀ The above calculation was repeated later.

By the above-described method, the control mechanism 20 can obtain the coordinates of all the boundary feature points, and for example, can store these coordinates in the memory 28 as shown in table 2.

TABLE 2 boundary feature point list

Characteristic point number	Feature point coordinates
		1	(x ₁ ,y ₁ )
2	(x ₂ ,y ₂ )
		…	…
M	(x _m ,y _m )

Where m represents the number of boundary feature points of the entire operation region 4, and m is a positive integer.

Specifically, four boundary feature points (x ₁ ,y ₁ )、(x ₂ ,y ₂ )、(x ₃ ,y ₃ ) And (x) ₄ ,y ₄ )。

Optionally, the method 400 may further include: the control mechanism 20 divides the operation area 4 into at least two sub-areas based on the map information of the operation area 4 obtained in step 460, and records information of each sub-area. Wherein the information of the sub-region comprises at least coordinates of boundary feature points within the sub-region. In addition, the information of the sub-region may further include a shape, an area, coordinates of boundary sampling points within the sub-region, and/or the like of the sub-region.

Specifically, the control mechanism 20 may take each boundary sampling point of the operation region 4 as a vertex of the undirected graph, and determine the set B of the vertex and the boundary sampling point _n Whether or not another boundary sampling point of the boundary sampling points is communicated. Here, the penetration between two points means that the connection lines between the two points all fall within or on a closed boundary region. If the vertex is connected to the other boundary sampling point, an edge (which may be a logical edge rather than a physical edge) may be added between the vertex and the other boundary sampling point. Control mechanism 20 traverses set B of boundary sample points _n To generate a set of all edges such that the generated set of all edges and all boundary sampling points form at least one complete graph, and the control mechanism 20 divides the boundary sampling points located in the same complete graph into a sub-region.

However, in many practical cases, the boundary line 3 cannot be arranged in a standard straight line, but a bending situation will inevitably occur, and the present invention provides a redundant mechanism for the division of the sub-areas in this situation. For example, if two sampling points lie within a straight line segment on the boundary line 3, the line between the two sampling points theoretically coincides with the fitted boundary line, i.e., each sampling point between the two sampling points is on the line. In this case, the line between the two sampling points may not be considered when dividing the sub-regions. On the other hand, in the case where the boundary line 3 is not a straight line, there may be a plurality of intersections between the connecting line and the boundary line 3. In this case, a distance threshold l may be preset ₀ Calculating the distance between two adjacent intersection points and determining whether the distance is less than the distance threshold l ₀ . If the distance is less than the distance threshold l ₀ The intersection point is considered invalid, i.e. the line should not be considered when dividing the sub-area. Specifically, assume that the intersection point of the boundary line 3 and the line between the sampling point a and the sampling point B is { x }, in order ₁ ,x ₂ ,x ₃ ,…,x _n From A to B) then in x _i Based on the standard, judge

And/l ₀ Magnitude relation between the two. If->

Greater than or equal to l ₀ Continue with x _i+1 Judging +.>

And/l ₀ Is a size relationship of (a). As long as the distance between any adjacent nodes is less than the distance threshold l ₀ The connection between a and B is removed from the set of edges (or directly disregarded when creating the set of edges).

In a practical operating scenario, the operating area 4 is often irregular, e.g. the entire operating area 4 is an irregular pattern consisting of rectangles and circles or sectors. Fig. 10 shows a schematic view of an irregular operating region 4 according to the invention.

In the case of the irregular operating region 4 shown in fig. 10, for example, the boundary feature points of the entire operating region 4 are determined to be 101 to 106 in accordance with the methods of steps 410 to 460, which may satisfy the number threshold condition, but in some specific portions of the operating region 4, such as the circular or sector-shaped portion 110, since the boundary lines of these portions are relatively smooth (i.e., the curvature of each point on the boundary line is substantially the same), these points either satisfy the curvature threshold value or neither satisfy the curvature threshold value, so that feature points satisfying the number threshold condition described above cannot generally be obtained in accordance with the curvature method described above.

In this case, the entire operation region 4 may be divided into a plurality of

sub-regions

110, 120, and 130 as described above, and the above-described steps 410 to 460 are performed for each sub-region, respectively. That is, each sub-region is treated as an independent closed figure to determine boundary feature points.

In another embodiment, the operating region 4 may be divided into a plurality of sub-regions based on at least three boundary sampling points therein after all boundary sampling points on the boundary line 3 are obtained (step 440), and for each sub-region, information of the sub-region including at least coordinates of the boundary sampling points within the sub-region is determined separately. For example, the operation region 4 may be divided based on boundary sampling points in a similar manner to the boundary feature points described above. Specifically, each boundary sampling point of the at least three boundary sampling points is used as a vertex of the unoccupied graph, whether the vertex is communicated with another boundary sampling point of the at least three boundary sampling points is judged, if the vertex is communicated with the another boundary sampling point, an edge line (which can be a logical edge line rather than a physical edge line) is added between the vertex and the another boundary sampling point, the at least three boundary sampling points are traversed to generate a set of all edge lines, so that the generated set of all edge lines and the at least three boundary sampling points form at least two complete graphs, and the boundary sampling point in one of the complete graphs is divided into a sub-area. Next, in a similar manner as described in step 460, boundary feature points within the sub-region may be determined for each sub-region to form information of the sub-region, which is not described herein.

The above describes the method of sub-region division based on the boundary feature points and the boundary sampling points, respectively. In either case, however, the above method may still not be able to obtain sufficient boundary feature points in the sub-region with a substantially smooth boundary line, since the curvature of each point on the boundary line is substantially the same. In this case, it may be determined whether the sub-region has a substantially smooth boundary line based on the coordinates of the boundary sampling points within the sub-region. Alternatively, when a feature point satisfying the number threshold condition cannot be found within a sub-region in the manner described above in step 460, it is determined that the sub-region has a substantially smooth boundary line. For a sub-region having a smooth boundary line (e.g., sub-region 110 shown in fig. 10), feature points satisfying a threshold number of conditions, such as feature points 107, 108, and 109 shown in fig. 10, may be randomly selected on the boundary line of the sub-region. For example, the selected feature points may be evenly distributed over the boundaries of the sub-region.

Similarly, for some specially shaped operating regions 4, such as smooth circular regions, the above method may still not be able to obtain sufficient boundary feature points throughout the operating region 4 because the curvature of each point on its boundary line 3 is substantially the same. In this case, it may be determined whether the operation region 4 has a substantially smooth boundary line 3 based on the coordinates of the boundary sampling points within the entire operation region. Alternatively, when the feature points satisfying the number threshold condition cannot be found in the operation region 4 in the manner described in step 460 above, it is determined that the operation region 4 has a substantially smooth boundary line. For such an operating region with smooth boundary lines, feature points satisfying the number threshold condition may also be randomly generated on the boundary line of the operating region, and may be uniformly distributed on the boundary line of the operating region, for example.

The walking robot 1 according to some aspects of the present invention has been described above with reference to fig. 1 to 4, and more particularly, a process in which the walking robot 1 surveys a specific operation area 4 before starting execution of a task in the operation area 4 to form map information for facilitating a subsequent operation is described. Further, the walking robot 1 may also divide the operation area 4 into a plurality of sub-areas so that the entire operation area 4 can be better traversed without missing any portion when performing the work.

In other aspects according to the invention, the walking robot 1 is also able to achieve an efficient traversal of the operation region 4 even with low-precision positioning. Fig. 5 shows a flow chart of a method 500 of operation of the walking robot 1 according to the invention in another mode of operation. The method 500 is described below in conjunction with fig. 3 and 5.

The walking robot 1 may be, for example, the walking robot 1 described above in connection with fig. 1 and 2. Further, in the memory 28 of the control mechanism 20, map information of the operation region 4 is stored, the map information including coordinates of a plurality of boundary feature points within the operation region 4, as shown in table 2. Additionally or alternatively, the memory 28 may also store therein information of a plurality of sub-regions of the operating region 4, the information of the sub-regions comprising at least coordinates of boundary feature points within the respective sub-region.

In one implementation, the map information and/or the information of the sub-areas is obtained by the control mechanism 20 controlling the walking robot 1 in advance to traverse the entire operation area 4, as by the method 400 described above in connection with fig. 4. However, the present invention is not limited thereto, and the above-described map information and/or information of the sub-areas may be set in advance in the memory 28 in other manners. For example, for some walking robots 1 equipped with a cell phone or computer desk side application, it is possible to draw a graph of the operation area 4 on the cell phone or computer side application and manually designate boundary feature points.

In method 500, control mechanism 20 first determines whether walking robot 1 is in an initial position at step 510. Similar to the method 400 of fig. 4, it is assumed that the walking robot 1 is in an initial position when located at the base station 2, as shown in fig. 3. For example, the control mechanism 20 may determine whether the walking robot 1 is located at the base station 2 by determining whether the walking robot 1 is connected to the base station 2 or whether the distance between the two is smaller than a very small value, thereby determining whether the walking robot is at the initial position.

If control mechanism 20 determines that walking robot 1 is not in the initial position, method 500 proceeds to step 520, where walking robot 1 is adjusted to the initial position. Here, the walking robot 1 may be adjusted to the initial position by various means. For example, in some implementations, walking robot 1 may sense electromagnetic signals around boundary line 3, thereby capturing boundary line 3, and return to an initial position (as at base station 2) along boundary line 3. Alternatively, in some other implementations, the walking robot 1 may also be placed at the base station 2 manually by an operator. The invention is not limited in this respect.

On the other hand, if the control mechanism 20 determines that the walking robot 1 is at the initial position, the method 500 proceeds to step 530, wherein the control mechanism 20 controls the body 10 to walk along the boundary line 3 in a predetermined first direction (e.g., clockwise direction) from the initial position. At step 540, when the body 10 reaches the vicinity of one of the boundary feature points, the control mechanism 20 controls the body 10 to adjust the body 10 so that the body 10 enters the operation region 4 along the normal direction of the boundary line 3 at that boundary feature point. Here, on the one hand, for the purpose of the work of the walking robot 1, the walking robot 1 needs to start the work by entering the operation area 4 when reaching the boundary feature point. On the other hand, due to the positioning error of the walking robot 1 itself and the accumulated error, it is difficult for the walking robot 1 to start entering the operation region 4 at the exact boundary feature point, but the boundary feature point is generally considered to be reached in the vicinity of the boundary feature point. This is determined by the working principle of the walking robot 1, and the walking robot 1 retrieves the coordinates of the boundary feature points that it is planning to reach from its memory, and starts from the initial position (e.g. at the base station 2), for example, by using the mileage acquisition module and the direction acquisition module to calculate its own real-time position coordinates. When the calculated real-time position coordinates fall within a specific area (such as a circular or other shape area) centered on the planned-to-reach boundary feature point coordinates, it is determined that the calculated real-time position coordinates themselves reach the planned-to-reach boundary feature point. In this case, a positioning error is generated between the actual position and the boundary feature point to which the plan arrives. Further, an accumulated error occurs due to accumulation of positioning errors, and a positional deviation between an actual position and a boundary feature point when the walking robot 1 enters the operation region 4 becomes larger and larger.

Fig. 6 shows a schematic view of the state when the walking robot 1 according to the present invention reaches one boundary feature point. For example, suppose that the walking robot 1 reaches the boundary feature point (x ₁ ,y ₁ ) The boundary line 3 is defined at the boundary feature point (x ₁ ,y ₁ ) The normal direction at the position is t-t, and the tangential direction is n-n. In this case, the walking robot 1 stops walking along the boundary line 3, and the main body 10 may be rotated so that it enters the operation region 4 along the normal direction t-t.

Hereinafter, a traveling path along the tangential direction n-n may be referred to as a lateral path, and a traveling path along the normal direction t-t may be referred to as a longitudinal path. The transverse path is controlled to be as straight as possible, while the longitudinal path may be straight or curved.

Further, in some implementations, after the subject 10 reaches the boundary feature point (x ₁ ,y ₁ ) When the robot is started, the control unit 20 starts the working mechanism of the walking robot 1 to start the work in the operation area 4. For example, in the case where the walking robot 1 is a robot for mowing, the control mechanism 20 activates its working mechanism so that its working device (mowing device) trims turf on the walking path as the walking robot 1 walks.

Next, in step 550, when the control mechanism 20 determines that the main body 10 is at the boundary feature point (x ₁ ,y ₁ ) The normal direction t-t at the position enters the operation area 4 for a predetermined distance W _l In this case, the body 10 is adjusted so that the body 10 is positioned at the boundary characteristic point (x ₁ ,y ₁ ) The tangential direction n-n of the position walks. Here, the predetermined distance W _l Is generally set to be equal to or smaller than the width of the main body 10, or is set to be equal to or smaller than the effective work width of the work device of the walking robot 1 (such as the mowing device, the brush or the suction port, etc., described above).

Next, in step 560, when the body 10 is positioned at the boundary feature point (x ₁ ,y ₁ ) When the tangential direction n-n at this point has travelled until reaching the boundary line 3, the control mechanism 20 determines whether the travel of the body 10 along this tangential direction n-n has reached a predetermined stop condition.

If it is determined at step 560 that the travel of the body 10 in the tangential direction n-n does not reach the predetermined stop condition, the operation returns to step 540, and the control mechanism 20 adjusts the body 10 so that the body 10 again travels a predetermined distance W toward the operation region 4 along the normal direction t-t of the boundary line 3 at the boundary feature point _l 。

That is, as shown in fig. 6, the walking robot 1 is reciprocally turned back along the longitudinal path and the lateral path within the operation region 4, traveling in an arcuate route.

On the other hand, if it is determined at step 560 that the walk of the body 10 in the tangential direction n-n reaches the predetermined stop condition, the method 500 proceeds to step 570, wherein the control mechanism 20 adjusts the body 10 such that the body 10 returns to the initial position, which may be along the boundary line 3 or otherwise. Here, the initial position may be, for example, the position of the base station 2 as shown in fig. 3.

In one embodiment, the predetermined stop time comprises a predetermined length of time. In this case, when the traveling time of the main body 10 in the operation region 4 reaches or exceeds the predetermined length of time, the predetermined stop condition is determined to be reached in step 560, taking the main body 10 entering the operation region 4 in the normal direction for the first time in step 540 as a starting point of time counting.

In another embodiment, the predetermined stop condition includes a length of the transverse path and a change in length. For example, consider that in many cases the length of the transverse path will typically undergo a change from small to large and then from large to small, as shown in fig. 6. In this case, in step 560, it may be determined whether the distance traveled by the body 10 in the tangential direction is less than or equal to the predetermined value W _h And whether the distance traveled by the main body 10 in the tangential direction (lateral path length) is less than or equal to the last distance traveled in the tangential direction (last lateral path length). In determining that the transverse path length of the main body 10 is less than or equal to the predetermined value W _h And the lateral path length of the body 10 is less than or equal to the last lateral path length, step 560 determines that the predetermined stop condition is met and the method 500 proceeds to step 570. In this way, as compared with the judgment made by the lateral path length alone, occurrence of an error judged to reach the stop condition immediately after the main body 10 enters the operation region 4 is avoided.

Here, a predetermined value W _h May be a value comparable to the length of the body 10, for example 0.3 to 0.5 times the length.

Thus far, one operation of the operation area 4 is completed, and the area in which the walking robot 1 actually operates in this operation may also be referred to as one work block.

After returning to the initial position, the control mechanism 20 may reset the travel mileage acquired by the mileage acquisition module and the heading deflection angle acquired by the direction acquisition module, so as to eliminate the error accumulated in the last operation and avoid affecting the next operation.

Next, the control mechanism 20 controls the main body 10 to travel from the initial position to the next boundary feature point (x ₂ ,y ₂ ) And the operations of the method 500 described above are repeated until all boundary feature points have been traversed.

In the case where the operation area 4 is a regular shape, such as a regular rectangle as shown in fig. 3, the work piece starting with each boundary feature point can cover substantially the entire operation area 4, so that the above-described method can well traverse the entire operation area 4. However, in the case where the operation region 4 is irregularly shaped, as shown in fig. 10, the entire operation region 4 can be better traversed by dividing the entire operation region 4 into sub-regions.

Specifically, in this case, the memory 28 also stores therein information of a plurality of sub-areas of the operation area 4. Here, the method of dividing the operation region 4 into the plurality of sub-regions may be the method described above in connection with fig. 4. However, the present invention is not limited thereto, and the division of the plurality of sub-regions may be performed by other means, such as geometric division or manual pre-specification.

In case the operation area 4 is divided into a plurality of sub-areas, the control mechanism 20 may control the walking robot 1 to perform the operations as described in the method 500, respectively, within each sub-area. In this case, the work block starting with each boundary feature point cannot cover the entire operation region 4, but only one sub-region and a part of the adjacent sub-region. However, the work blocks starting with all the boundary feature points 101 to 109 can cover the entire operation region 4 well.

In particular, in the case where the walking robot 1 is configured not with a high-precision positioning device such as GPS but with a low-precision positioning device such as the above-described photoelectric encoder, gyroscope, and/or geomagnetic sensor, it is likely that the walking robot 1 cannot accurately position each boundary feature point, so that a situation occurs in which the operation area 4 is entered virtually earlier or later than the boundary feature point. In this case, the above figure 5 is followed The operation of method 500 may result in missing portions within operation region 4. Fig. 7A and 7B show schematic diagrams of a missing portion A1 generated in the vicinity of a boundary feature point of the walking robot 1 equipped with the low-precision positioning device. As shown in fig. 7A and 7B, the walking robot 1, when actually reaching the boundary feature point (x ₁ ,y ₁ ) The previous position is judged to have reached the boundary feature point (x ₁ ,y ₁ ) And the operations of the method 500 described above begin to proceed, thereby creating boundary feature points (x ₁ ,y ₁ ) The nearby area A1 is not processed. Similarly, when the walking robot 1 actually reaches the boundary feature point (x ₁ ,y ₁ ) Then, the position is judged to reach the boundary feature point (x ₁ ,y ₁ ) In the case of (2) also at the boundary feature point (x ₁ ,y ₁ ) Similar missing parts are generated nearby.

In this case, it is possible to process the missing portion A1 by performing the above-described work in each of the plurality of work blocks that overlap each other. For example, in the case of the rectangular operation region 4 shown in fig. 3, in the case of the rectangular operation region 4, the operation region is divided from the boundary feature point (x ₁ ,y ₁ ) The missing part A1 that may be generated in the operation of the first work block started will be found in the boundary feature point (x ₂ ,y ₂ ) And boundary feature points (x ₄ ,y ₄ ) The processing is performed in the operation of the first second work block and the fourth work block.

However, for some more complex shaped operating areas, doing so in the manner described above may still be insufficient to cover the missing portions near all boundary feature points. In this regard, the present invention further improves the method 500 described above by performing a radial operation on the region near the boundary feature points to eliminate missing portions. Fig. 8 shows a schematic view of a method of processing a missing portion A1 in the vicinity of boundary feature points by the walking robot 1 according to the present invention. In the method shown in fig. 8, the walking robot 1 can perform work along a path of p0→p1→p2→p3→p4→p5→p6→p7→p8→p9→p10→p11→p12→p13 in the operation region 4. Similarly to the above, the travel path along the tangential direction n-n is referred to as a transverse path or a normal transverse path, and the travel path along the normal direction t-t is referred to as a longitudinal path or a normal longitudinal path. The paths p0→p1, p2→p3, p4→p5, p6→p7, p8→p9, p10→p11 form significant angles with the boundary line 3, and may be referred to as temporary transverse paths, and the paths p1→p2, p3→p4, p5→p6, p7→p8, p9→p10, p11→p12 substantially coincide with the boundary line 3, and may be referred to as temporary longitudinal paths. Among them, the work of the walking robot 1 on the temporary lateral paths p0→p1, p2→p3, p4→p5, p6→p7, p8→p9, p10→p11 can be regarded as radial work at the missing portion A1. It can be seen that, among the paths shown in fig. 8, the temporary longitudinal paths p1→p2, p3→p4, p5→p6, p7→p8, p9→p10, p11→p12 are all short, mainly due to the width of the walking robot 1 itself, so that it has to perform the temporary longitudinal paths as shown in the figure. In fact, in an ideal operating situation, the length of the temporary longitudinal path is 0, i.e. p1/p2 overlap, p5/p6 overlap, p9/p10 overlap, p0/p3/p4/p7/p8/p11/p12 overlap, so that the walking robot 1 starts from p0 each time the angle is changed, ensuring the accuracy of the angle control. Hereinafter, this ideal case will be described as an example, and p0/p3/p4/p7/p8/p11/p12 will be referred to as a first position p0, p1/p2 will be referred to as a second position p1, p5/p6 will be referred to as a third position p5, and p9/p10 will be referred to as a fourth position p9.

Specifically, in the method shown in fig. 8, it is assumed that the boundary feature point (x ₁ ,y ₁ ) The previous first position p0 is erroneously recognized as a boundary feature point (x ₁ ,y ₁ ) While stopping the advance, and assuming that the angle between the direction in which the walking robot 1 walks along the boundary line 3 (i.e., the tangential direction of the boundary line 3 at the first position) and the tangential direction n-n at the boundary feature point (i.e., the normal lateral path direction) is the first angle α ₀ 。

In some embodiments, when the body 10 is stopped at the first position p0, the control mechanism 20 controls the body 10 to enter the operation region 4 from the first position p0 and along the second angle α ₁ Walk until reaching the boundary line 3, for example reaching the second position p1 on the boundary line 3. This isInside, a second angle alpha ₁ Less than the first angle alpha ₀ . For example, the control mechanism 20 may control the body 10 at the second angle α at the first position p0 ₁ Steering toward the operation area 4 and traveling in the operation area 4 along a straight line. When reaching the second position p1, the walking robot 1 completes the first radial operation p0→p1 at the missing portion A1.

In some implementations, control mechanism 20 may be responsive to a first angle α ₀ And possibly other factors such as the width of the body 10 or the working width and/or the size of the operating area 4 or the corresponding operating area, etc.) determines the boundary feature points (x ₁ ,y ₁ ) The number of reciprocations of the radial operation is performed in the vicinity of the area A1, and the second angle α is determined accordingly ₁ . For example, as shown in fig. 8, assume that control mechanism 20 is according to a first angle α ₀ It is determined that q-time (assuming 4 times (1-time for reciprocation in fig. 8)) radial jobs are performed in the area A1, the control mechanism 20 may determine the angle α as shown in fig. 8 ₁ 、α ₂ 、α ₃ And alpha ₄ . Wherein alpha is ₄ ＝α ₀ . Angle alpha ₁ 、α ₂ 、α ₃ And alpha ₄ May be an arithmetic series, i.e. each radial run is offset to the right by an angle relative to the previous run

And the angle of the first radial operation +.>

However, the present invention is not limited thereto, angle α ₁ 、α ₂ 、α ₃ And alpha ₄ An arithmetic progression is not required. Alternatively, the angle α may be determined by other means ₁ 、α ₂ 、α ₃ And alpha ₄ . For example, a small angle Δ may be preset as the angle difference for each adjustment. In fact, as long as it is small in the missing portion A1At a first angle alpha ₀ Is a second angle alpha of (2) ₁ Performing the radial operation as shown in fig. 8 at least once will effectively improve the processing of the missing portion A1.

When the main body 10 is along the second angle alpha ₁ When reaching the second position p1 on the boundary line 3, the control mechanism 20 controls the main body 10 to return from the second position p1 to the first position p0. At this time, the control mechanism 20 may determine that the second angle α is greater than the first angle α ₁ Is a third angle alpha of (2) ₂ For example alpha as described above ₂ ＝α ₁ +Δ, and determining a third angle α ₂ Whether or not it is greater than or equal to the first angle alpha ₀ . If a third angle alpha is determined ₂ Less than the first angle alpha ₀ The control mechanism 20 controls the main body 10 to move from the first position p0 by a third angle alpha ₂ Through the operating area 4 to the boundary line 3, for example to a third position p5 on the boundary line. Thus, the walking robot 1 completes the second radial operation p0→p5 at the missing portion A1. On the other hand, if the third angle alpha ₂ Greater than or equal to the first angle alpha ₀ The control mechanism 20 controls the walking robot 1 to enter the operation area 4 in the lateral path direction (n-n). I.e. if the third angle alpha ₂ Greater than or equal to the first angle alpha ₀ The operation turns to standard operation as described above in connection with fig. 5.

Similarly, the above process may be repeated until the next deflection angle from the first position p0 is greater than or equal to the first angle α ₀ Until that point. For example, in the control mechanism 20 controlling the main body 10 from the first position p0 at the third angle α as described above ₂ After reaching the third position p5 on the boundary line 3 through the operation region 4, the control mechanism 20 may also control the main body 10 to return from the third position p5 to the first position p0 on the boundary line 3. At this time, the control mechanism 20 may determine that the third angle α is greater than ₂ Fourth angle alpha of (2) ₃ For example alpha ₃ ＝α ₂ +Δ, and determining a fourth angle α ₃ Whether or not it is greater than or equal to the first angle alpha ₀ . If a fourth angle alpha is determined ₃ Less than the first angle alpha ₀ The control mechanism 20 controls the main body 10 from the first position p0 at the fourth angle α ₃ Through the operating area 4 to the boundary line 3, for example to a fourth position p9 on the boundary line 3. Thus, the walking robot 1 completes the third radial operation p0→p9 at the missing portion A1. By analogy, the walking robot 1 can walk radially for a plurality of times on the missing part A1 until the next deflection angle is greater than or equal to the first angle alpha ₀ . At this time, the walking robot 1 may be readjusted to the standard lateral path direction (i.e., boundary feature points (x ₁ ,y ₁ ) N-n) of the vehicle.

In the case where the walking robot 1 needs to perform a certain specific work (such as mowing, sweeping, etc.), the control mechanism 20 may activate the work mechanism each time the walking robot 1 enters the operation area 4, for example, work on the operation area 4 from p0→p1 and from p1→p0, from p0→p5 and from p5→p0, and from p0→p9 and from p9→p0. Alternatively, the control unit 20 may control the walking robot 1 to perform the work on the operation area 4 only during each walking from the first position p0, and not to perform the work during the returning. This saves on the one hand the energy consumption of the walking robot 1 and on the other hand avoids repeated operations on certain parts of the operating area 4 and the resulting losses of the walking robot 1.

Further, the travel path of the walking robot 1 in the missing portion A1 is also not limited to the above description, but may include other ways. For example, after the walking robot 1 travels from the first position p0 to the second position p1, it may travel not return to the first position p0 but a certain distance to the third position p2 in the first direction (e.g., clockwise) along the boundary line 3, and return to the first position p0 from the third position p 2. The specific distance may be calculated from the angle delta (angle alpha ₁ 、α ₂ 、α ₃ And alpha ₄ In the case of an arithmetic progression) or may be determined based on other factors, such as the width of the body 10 or the work width. In this way, the number of times the walking robot 1 walks in the operation area 4 can be saved, so that effective work can be performed every time it walks. However, this increases the calculation of the travel path of the traveling robot 1 by the control mechanism 20Is a calculation amount of (a).

Fig. 9 shows a schematic view of another method of processing missing parts in the vicinity of boundary feature points by the walking robot 1 according to the present invention. Fig. 9 may be regarded as a simplified implementation of the method described in fig. 8.

As shown in fig. 9, similarly to fig. 8, it is assumed that the body 10 stops advancing at a first position p0 on the boundary line 3 and follows an angle β from the first position p0 ₁ When reaching the second position p1 on the boundary line 3, the control mechanism 20 controls the main body 10 to rotate by an angle β in the second direction ₂ And into the operating area 4. Wherein the second direction is opposite to the first direction. For example, where the first direction is clockwise, the second direction is counter-clockwise and vice versa. And, angle beta ₂ Is a first angle alpha ₀ And angle beta ₁ The angle of the difference, i.e. beta ₂ ＝360°-(α ₀ -β ₁ )。

At the main body 10 along the second direction by an angle beta ₂ Thereafter, the direction of the main body 10 is parallel to the tangential direction n-n of the boundary line 3 at the boundary feature point (i.e., the normal lateral path direction), and at this time, the control mechanism 20 may control the main body 10 to enter the operation region 4 along the tangential direction n-n of the boundary line 3 at the boundary feature point, thereby starting to perform the operation p1→p2 of the first normal lateral path direction as shown in fig. 9.

It is understood that the stop point (first position p 0) of the walking robot 1 is described as an example before the boundary feature point in fig. 8 and 9, however, it is understood by those skilled in the art that the scheme of the present invention can be easily extended to the case where the stop point is after the boundary feature point. For example, assuming that the first direction is clockwise when the first position is before the boundary feature point, the first direction may be counterclockwise when the first position is after the boundary feature point. In either case, the stopping point should be located uniformly before the boundary feature point or uniformly after the boundary feature point.

In addition, in order to reduce the wear caused to the operation area 4 by the repeated walking at the stopping point p0 (for example, in the case where the walking robot 1 is a lawn mowing robot), it is also possible to set different advance or retard amounts to obtain different stopping points p0 each time.

Further aspects of the present invention are described above in connection with fig. 5 to 9, wherein the walking robot 1 according to the present invention is capable of performing work within the operation area 4 under the control of the control mechanism 20, so that the entire operation area 4 can be more easily traversed. Further, in these aspects, even if the walking robot 1 is equipped with a positioning device of low accuracy, the control mechanism 20 can control the walking robot 1 to traverse the entire operation area 4, thereby avoiding a significant omission.

Various implementations of the invention are described above in connection with the accompanying drawings. In one or more exemplary implementations, the functions described herein may be implemented in hardware, software, firmware, or any combination thereof. For example, if implemented in software, the functions implemented by control mechanism 20 may be stored on or distributed as one or more instructions or code on a computer readable medium, such as memory 28 or the like.

Those of ordinary skill in the art will further appreciate that the control mechanism 20 or its components described in connection with the various embodiments of the present application may be implemented as a plurality of discrete hardware components or may be integrally implemented on one hardware component, such as a processor. For example, the control mechanism 20 or its constituent parts main controller 22, mileage acquisition module 24, or heading acquisition module 26 described in connection with the present disclosure may be implemented or performed with a general purpose processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field Programmable Gate Array (FPGA) or other programmable logic device, discrete gate or transistor logic, discrete hardware components, or any combination thereof for performing the functions described herein.

The previous description of the disclosure is provided to enable any person of ordinary skill in the art to make or use the disclosure. Various modifications to the disclosure will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other variations without departing from the spirit or scope of the disclosure. Thus, the disclosure is not intended to be limited to the examples and designs described herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A walking robot comprising:

a main body; and

a control mechanism configured to perform operations comprising:

controlling the main body to walk along a boundary line of a predetermined operation area, and sampling a walking path to acquire data of a set of all boundary sampling points on the boundary line;

dividing the predetermined operation region into at least two sub-regions based on at least three boundary sampling points in the set of boundary sampling points; and

for each sub-region, determining information of the sub-region respectively, wherein the information of the sub-region at least comprises coordinates of boundary sampling points in the sub-region;

wherein dividing the predetermined operation region into at least two sub-regions comprises:

each boundary sampling point in the at least three boundary sampling points is respectively used as the vertex of the undirected graph,

judging whether the vertex is communicated with another boundary sampling point of the at least three boundary sampling points,

if the vertex is communicated with the other boundary sampling point, adding a side line between the vertex and the other boundary sampling point,

traversing the at least three boundary sampling points to generate a set of all edges, such that the generated set of all edges and the at least three boundary sampling points form at least two complete graphs, an

Boundary sampling points located in the same one of the at least two complete graphs are divided into a sub-region.

2. The walking robot of claim 1, wherein said operations further comprise:

if the edge line coincides with the boundary line, the edge line is removed from the set of all edge lines.

3. The walking robot of claim 1, wherein said operations further comprise:

if the boundary line and the boundary line have a plurality of intersection points, calculating the distance between two adjacent intersection points in the plurality of intersection points;

determining whether the distance is less than a predetermined distance threshold; and

if the distance is less than the predetermined distance threshold, the edge is removed from the set of all edges.

4. The walking robot of claim 1, wherein said operations further comprise:

a number threshold or a number threshold range for boundary feature points of each sub-region is determined based on boundary sampling points within the sub-region, and boundary sampling points satisfying the number threshold or the number threshold range are selected as boundary feature points from the boundary sampling points within the sub-region to form information of the sub-region including coordinates of the boundary feature points within the sub-region.

5. The walking robot of claim 4, wherein said operations further comprise:

determining that the sub-region has a substantially smooth boundary line based on coordinates of boundary sampling points within the sub-region, or determining that the sub-region has a substantially smooth boundary line when a boundary feature point satisfying the number threshold or the number threshold range cannot be found from among the boundary sampling points within the sub-region; and

points satisfying the number threshold or the number threshold range are randomly selected from the boundary line of the sub-region as the boundary feature points.

6. The walking robot of claim 5, wherein said boundary feature points are uniformly distributed on said substantially smooth boundary line.

7. A walking robot system comprising:

the walking robot according to any one of claims 1 to 6, and

a base station, wherein the base station comprises a feeding module for feeding the boundary line connected thereto for generating an electromagnetic signal around the boundary line.

8. A method of controlling a walking robot, comprising:

controlling a main body of the walking robot to walk along a boundary line of a predetermined operation area, and sampling a walking path to acquire data of a set of all boundary sampling points on the boundary line;

9. The method of claim 8, further comprising:

10. The method of claim 8, further comprising:

11. The method of claim 8, further comprising:

12. The method of claim 11, further comprising:

13. The method of claim 12, wherein the boundary feature points are uniformly distributed on the substantially smooth boundary line.