CN116907488A

CN116907488A - Method for docking base station, robot and storage medium

Info

Publication number: CN116907488A
Application number: CN202211351144.2A
Authority: CN
Inventors: 张少华; 张国栋; 叶力荣
Original assignee: Shenzhen Nei Innovation Technology Co ltd
Current assignee: Shenzhen Nei Innovation Technology Co ltd
Priority date: 2022-10-31
Filing date: 2022-10-31
Publication date: 2023-10-20

Abstract

The embodiment of the application relates to the technical field of robots and discloses a method for docking a base station. And positioning a docking device on the base station according to the effective point cloud data, and determining rotation parameters. And controlling the robot to rotate according to the rotation parameters so as to enable the docking device of the robot to complete docking with the docking device of the base station. The robot can automatically stop the docking station after the map is reset and when the map is not built or the docking station is powered off, so that the docking station is more stable and reliable. On the other hand, the rotation parameters can be accurately determined through the effective point cloud data reflecting the scanning outline of the base station, so that the robot berthing to the docking base station is more accurate.

Description

Method for docking base station, robot and storage medium

Technical Field

The embodiment of the application relates to the technical field of robots, in particular to a method for docking a docking station, a robot and a storage medium.

Background

The robot can automatically complete work in cooperation with the base station, wherein the base station is an electronic device which automatically completes work in cooperation with the robot. Robots with different functions correspond to base stations with different functions so as to complete work in cooperation with automation. For example, most base stations are capable of providing docking and charging services for robots, which autonomously dock to the base station and interface with a charging interface on the base station for charging. For example, for the cleaning robot, the base station can provide charging service, and the cleaning robot can return to the base station for water replenishment, pollution discharge, cleaning agent replenishment, self-cleaning and the like, and stop at the base station when not in operation.

Currently robots are typically positioned in communication with a base station via signal sensors to dock to and interface with the base station. However, the signal sensor not only increases the cost of the component, but is also susceptible to environmental effects (e.g., shielding, or damage to the component itself, etc.), resulting in unstable signals, interfering with the robot docking to the docking station, and making docking unstable. In addition, through signal communication location, the error is great for the robot can't stop docking station accurately.

Disclosure of Invention

In view of this, some embodiments of the present application provide a method for docking a docking station, a robot, and a storage medium, so as to solve the technical problem that the current robot cannot accurately and stably dock the docking station.

In a first aspect, an embodiment of the present application provides a method for docking a docking station, which is applied to a robot including a laser radar, including:

acquiring laser point cloud data obtained by laser radar scanning;

according to the laser point cloud data, determining whether the robot is located in a base station environment, wherein the base station environment is a space for accommodating the robot to stop in the base station;

if the robot is located in the base station environment, extracting effective point cloud data corresponding to the base station from the laser point cloud data;

according to the effective point cloud data, determining a rotation parameter, and controlling the robot to rotate according to the rotation parameter, so that the docking device of the robot and the docking device of the base station are docked.

In some embodiments, the foregoing determining whether the robot is located in the base station environment according to the laser point cloud data includes:

traversing each laser point in the laser point cloud data, screening out the laser points with the distance within a preset distance interval, and forming a laser point set;

And performing shape fitting on the laser point set, and if the fitted shape is suitable for the base station environment, determining that the robot is positioned in the base station environment.

In some embodiments, the foregoing performing shape fitting on the laser spot set, and if the fitted shape is adapted to the base station environment, determining that the robot is located in the base station environment includes:

and performing circular fitting on the laser point set by adopting a least square method, and if the difference between the fitted circular radius and the radius of the base station environment is within a preset deviation range, determining that the robot is positioned in the base station environment.

In some embodiments, prior to shape fitting the set of laser points, the method further comprises:

and if the number of the laser points in the laser point set is greater than or equal to a number threshold, performing shape fitting on the laser point set.

In some embodiments, the extracting valid point cloud data corresponding to the base station environment from the laser point cloud data includes:

and if the fitted shape is suitable for the base station environment, the laser point set is used as effective point cloud data.

In some embodiments, determining the rotation parameter from the valid point cloud data includes:

acquiring a starting point angle and an end point angle of effective point cloud data;

Determining a target angle of a docking device of the base station according to the starting point angle and the end point angle;

and determining a rotation parameter according to the target angle and the current angle of the docking device of the robot.

In some embodiments, the aforementioned rotation parameters include a rotation angle and a rotation direction;

the determining a rotation parameter according to the target angle and the current angle of the docking device of the robot includes:

acquiring an absolute value of an angle difference between a target angle and a current angle;

if the absolute value of the angle difference is smaller than or equal to 180 degrees and the target angle is larger than the current angle, determining that the rotation angle is the absolute value of the angle difference, and the rotation direction is the scanning direction of the laser radar;

if the absolute value of the angle difference is smaller than or equal to 180 degrees and the target angle is smaller than the current angle, determining the rotation angle as the absolute value of the angle difference, wherein the rotation direction is opposite to the scanning direction of the laser radar;

if the absolute value of the angle difference is larger than 180 degrees and the target angle is larger than the current angle, determining that the rotation angle is 360 degrees minus the absolute value of the angle difference, wherein the rotation direction is opposite to the scanning direction of the laser radar;

if the absolute value of the angle difference is larger than 180 degrees and the target angle is smaller than the current angle, the rotation angle is determined to be 360 degrees minus the absolute value of the angle difference, and the rotation direction is the scanning direction of the laser radar.

In some embodiments, the method further comprises:

when receiving the infrared signal sent by the base station, determining that the robot is located in the base station environment; and/or the number of the groups of groups,

acquiring the inclination angle of the robot, and if the inclination angle is within a preset angle interval, determining that the robot is positioned in the base station environment.

In a second aspect, in an embodiment of the present application, there is provided a robot including:

the laser radar (lidar),

at least one processor in communication with the lidar;

a memory communicatively coupled to the at least one processor; wherein the memory stores instructions executable by the at least one processor to enable the at least one processor to perform a method of docking a docking station as in the first aspect.

In a third aspect, embodiments of the present application provide a computer-readable storage medium having stored thereon computer-executable instructions for causing a computer device to perform a method of docking a docking station as in the first aspect.

The embodiment of the application has the beneficial effects that: in contrast to the situation of the prior art, the method for docking a docking station provided by the embodiment of the application is applied to a robot comprising a laser radar, and the method comprises the steps of firstly, determining whether the robot is located in a base station environment (the base station environment is a space for accommodating the docking robot in the base station) according to laser point cloud data obtained by scanning the laser radar, and extracting effective point cloud data corresponding to the base station from the laser point cloud data if the robot is located in the base station environment. The effective point cloud data corresponding to the base station can reflect the scanning outline of the base station, the position of the docking device of the base station relative to the base station is known, and the position of the docking device of the robot relative to the robot is known, so that the docking device on the base station can be positioned according to the effective point cloud data, and the rotation parameters can be determined. And finally, controlling the robot to rotate according to the rotation parameters so as to enable the docking device of the robot to complete docking with the docking device of the base station. In the embodiment, the robot can identify the environment of the positioning base station and determine the rotation parameters based on the self-scanned laser point cloud data, the docking base station does not need to rely on a signal sensor, and the robot can automatically dock the docking base station after the map is reset or when the map is not built or the base station is powered off, so that the docking base station is more stable and reliable. On the other hand, the rotation parameters can be accurately determined through the effective point cloud data reflecting the scanning outline of the base station, so that the robot berthing to the docking base station is more accurate.

Drawings

One or more embodiments are illustrated by way of example and not limitation in the figures of the accompanying drawings, in which like references indicate similar elements, and in which the figures of the drawings are not to be taken in a limiting sense, unless otherwise indicated.

Fig. 1 is a schematic view of an application environment of a method of docking a docking station in some embodiments of the present application;

fig. 2 is a flow chart of a method of docking a docking station in some embodiments of the application;

FIG. 3 is a schematic diagram of laser point cloud data according to some embodiments of the present application;

FIG. 4 is a schematic illustration of a robot positioned closest and farthest in a base station environment in accordance with some embodiments of the present application;

fig. 5 is a schematic diagram of a base station corresponding to a start point and an end point of valid point cloud data in some embodiments of the present application;

FIG. 6 is a schematic diagram illustrating the determination of rotation parameters according to some embodiments of the application;

fig. 7 is a schematic diagram of an apparatus for docking a docking station in some embodiments of the present application;

fig. 8 is a schematic structural diagram of a robot according to some embodiments of the present application.

Detailed Description

The present application will be described in detail with reference to specific examples. The following examples will assist those skilled in the art in further understanding the present application, but are not intended to limit the application in any way. It should be noted that variations and modifications could be made by those skilled in the art without departing from the inventive concept. These are all within the scope of the present application.

The present application will be described in further detail with reference to the drawings and examples, in order to make the objects, technical solutions and advantages of the present application more apparent. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the application.

It should be noted that, if not in conflict, the features of the embodiments of the present application may be combined with each other, which is within the protection scope of the present application. In addition, while functional block division is performed in a device diagram and logical order is shown in a flowchart, in some cases, the steps shown or described may be performed in a different order than the block division in the device, or in the flowchart. Moreover, the words "first," "second," "third," and the like as used herein do not limit the data and order of execution, but merely distinguish between identical or similar items that have substantially the same function and effect.

Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. The terminology used in the description of the application herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the application. The term "and/or" as used in this specification includes any and all combinations of one or more of the associated listed items.

In addition, the technical features of the embodiments of the present application described below may be combined with each other as long as they do not collide with each other.

The method for docking the docking station in the embodiment of the application is applied to a robot comprising a laser radar, wherein the robot can be a mobile device capable of providing functional services, such as: the robot can be a cleaning robot, a pet robot, a carrying robot, a nursing robot, a remote monitoring robot, a sweeping robot and the like. The robot can automatically complete work in cooperation with the base station, wherein the base station is an electronic device which automatically completes work in cooperation with the robot. It will be appreciated that the functionality of the base station is configured based on the functionality of the corresponding robot. In some embodiments, the robot may be an unmanned vehicle, and the corresponding base station may provide charging services, parking services, or car washing services, etc. for the unmanned vehicle. In some embodiments, the robot may be a cleaning robot, and the corresponding base station is capable of providing docking, charging, water replenishment, blowdown, detergent replenishment, and self-cleaning, drying, etc. services for the cleaning robot.

The following describes an application environment of the docking station method using a robot as an example of a cleaning robot. Wherein the cleaning robot includes, but is not limited to, a sweeping robot, a dust collection robot, a mopping robot, a washing robot, or the like.

Referring to fig. 1, fig. 1 is an application environment schematic diagram of a method for docking a docking station according to an embodiment of the present application. As shown in fig. 1, the robot 10 is located on the ground, which may be the ground of a living room or office or the like. The robot is located in places including a base station 20, a desk, a flowerpot, a sofa and the like.

The robot is provided with a laser radar, wherein the laser radar scans the surrounding environment of the robot to obtain laser point cloud data. The laser radar is in communication connection with the control chip, the laser radar sends laser point cloud data to the control chip, the control chip invokes a program which is preset in advance in a memory of the robot and stops docking the base station, the base station is identified and positioned based on the laser point cloud data, rotation parameters are calculated, and the robot is controlled to rotate according to the rotation parameters, so that the docking device of the robot and the docking device of the base station are docked.

Wherein the robot 10 may be configured in any suitable shape to achieve a particular business function operation, for example, in some embodiments, the robot 10 may be a mobile robot based on a SLAM system. In some embodiments, the robot may include a robot body, a lidar, a control chip, and a running gear, a docking device (not shown).

The robot main body is a main body structure of the robot, and can be made of corresponding shape and structure and manufacturing materials (such as hard plastic or metals such as aluminum and iron) according to the actual needs of the robot, for example, the robot is arranged into a flat cylinder common to sweeping robots.

The walking mechanism is a structural device which is arranged on the robot main body and provides the movement capability for the robot. The running gear may in particular be realized by any type of moving means, such as rollers, crawler-type wheels or the like.

The laser radar is arranged on the body of the robot 10 and used for sensing the obstacle condition of the surrounding environment of the mobile robot 10, scanning to obtain laser point cloud data and sending the laser point cloud data to the control chip so that the control chip can control the robot to walk based on the distance between surrounding objects. In some embodiments, the lidar comprises a pulsed lidar, a continuous wave lidar, or the like.

The control chip is an electronic computing core which is arranged in the robot main body and is used for executing a logic operation step so as to realize intelligent control of the robot. In this embodiment, the control chip is in communication connection with the laser radar, and is configured to identify and locate the base station according to the laser point cloud data, calculate a rotation parameter, and control the robot to rotate according to the rotation parameter, so that the docking device of the robot and the docking device of the base station complete docking.

It will be appreciated that in some embodiments, the robot body may also include a clean water tank, a sewage tank, a cleaner box, a dust box, and the like. The docking device of the robot may include an interface of a clean water tank, an interface of a sewage tank, an interface of a cleaner box, an interface of a dust collection box, or a charging pole piece, etc.

In this embodiment, the base station includes a base, a cleaning device, a water supply device, a dust collection device, a power supply device, a detergent replenishment device, and a sewage storage device. The base, the cleaning device, the water supply device, the dust collection device, the power supply device, the detergent replenishment device, and the sewage storage device are not shown in the drawing. The base is used for stopping the robot, the cleaning device is used for cleaning the robot, the water supply device is used for supplying water for the robot and/or supplying water for the cleaning device, and the dust collecting device is used for collecting dust in the dust collecting box of the robot. The power supply device is used for charging the robot. The sewage storage device is used for collecting sewage in the robot sewage tank.

It is understood that the base is provided with a docking device for docking the above devices with the robot, and the docking device of the base may include an interface of the cleaning device, an interface of the water supply device, an interface of the dust collecting device, an interface of the power supply device, an interface of the cleaning agent supplementing device, or a charging pole piece.

In the embodiment, when the docking device of the robot and the docking device of the base station are in docking, the interface of the clear water tank on the robot is in docking communication with the interface of the water supply device on the base station, so that the water supply device can supply water to the clear water tank; the interface of the sewage tank on the robot is in butt joint communication with the interface of the sewage storage device on the base station, so that the sewage storage device can collect sewage in the sewage tank; the interface of the cleaning agent box on the robot is in butt joint communication with the interface of the cleaning agent supplementing device on the base station, so that the cleaning agent supplementing device can supplement the cleaning agent to the cleaning agent box; the interface of the dust collecting box on the robot is in butt joint communication with the interface of the dust collecting device, so that the dust collecting device can collect dust in the dust collecting box; the charging pole piece on the robot is in butt joint electric connection with the charging pole piece on the base station, so that the power supply device on the base station can charge the robot.

It should be noted that, according to the task to be completed, besides the above functional modules, one or more other different functional modules may be mounted on the main body of the robot, and one or more functional modules for cooperation may be mounted on the base station, so as to cooperate with each other to perform the corresponding task.

Some methods known to the inventors of docking a base station are to communicate with the base station via a signal sensor to locate a docking station to dock with the base station. However, the signal sensor not only increases the cost of the component, but is also susceptible to environmental effects (e.g., shielding, or damage to the component itself, etc.), resulting in unstable signals, interfering with the robot docking to the docking station, and making docking unstable. In addition, through signal communication location, the error is great for the robot can't stop docking station accurately.

In view of the above problems, an embodiment of the present application provides a method for docking a docking station, which is applied to a robot including a laser radar, and the method includes acquiring laser point cloud data obtained by scanning the laser radar, firstly, determining whether the robot is located in a base station environment (the base station environment is a space for accommodating the docking robot in the base station) according to the laser point cloud data, and if the robot is located in the base station environment, extracting valid point cloud data corresponding to the base station from the laser point cloud data. The effective point cloud data corresponding to the base station can reflect the scanning outline of the base station, the position of the docking device of the base station relative to the base station is known, and the position of the docking device of the robot relative to the robot is known, so that the docking device on the base station can be positioned according to the effective point cloud data, and the rotation parameters can be determined. And finally, controlling the robot to rotate according to the rotation parameters so as to enable the docking device of the robot to complete docking with the docking device of the base station. In the embodiment, the robot can identify the environment of the positioning base station and determine the rotation parameters based on the self-scanned laser point cloud data, the docking base station does not need to rely on a signal sensor, and the robot can automatically dock the docking base station after the map is reset or when the map is not built or the base station is powered off, so that the docking base station is more stable and reliable. On the other hand, the rotation parameters can be accurately determined through the effective point cloud data reflecting the scanning outline of the base station, so that the robot berthing to the docking base station is more accurate.

It will be appreciated from the foregoing that the method of docking to a docking station provided by embodiments of the present application may be implemented by a robot including a lidar, for example by a control chip or processor of the robot or by other devices having computing processing capabilities, etc. Other devices with computing processing capabilities may be intelligent terminals communicatively coupled to the robot.

The method for docking the docking station provided by the embodiment of the application is described below in connection with exemplary application and implementation of the robot provided by the embodiment of the application. Referring to fig. 2, fig. 2 is a flowchart of a method for docking a docking station according to an embodiment of the present application. It will be appreciated that the subject of execution of the method of docking the docking station may be one or more processors of the robot.

As shown in fig. 2, the method S100 may specifically include the following steps:

s10: and acquiring laser point cloud data obtained by laser radar scanning.

And the laser radar scans the environment where the robot is located by 360 degrees to generate laser point cloud data. The laser radar transmits the generated laser point cloud data to the processor, so that the processor can acquire the laser point cloud data.

It will be appreciated that lidar typically rotates one revolution from 0 ° in the radar coordinate system, generating a frame of 360 ° laser point cloud data. The angular resolution of the laser point cloud data may be 0.5 °. As shown in fig. 3, a base station and other objects exist in the environment where the robot is located, based on the working principle of the laser radar, the laser radar performs laser scanning ranging on surrounding objects, and its own chip calculates the distance and angle of each light spot (the light spot point formed by laser striking the object) based on the transmitted laser information and the echo laser information. The calculation of the distance and angle of the light spot is a prior calculation mode of the laser radar, and is not described in detail herein. It will be appreciated that the distance and angle of each spot constitutes laser point cloud data based on the continuity of the scan. Thus, after the scanning is completed, laser point cloud data is generated. The laser points in the laser point cloud data are arranged in angular resolution interval order.

In the laser point cloud data, the distance and angle of each laser point can be acquired. The distance is the distance from a light spot formed by laser striking an object to a laser radar, and the angle is the angle of the light spot formed by laser striking the object in a radar coordinate system.

In some embodiments, the laser point cloud data may be synthesized by continuous multi-frame laser point cloud data, for example, the robot continuously scans laser point cloud data of 3 frames of 360 ° at the same position by using the laser radar, if there is no laser point at 50 ° in the 1 st frame of laser point cloud data and there is a laser point at 50 ° in the 2 nd frame of laser point cloud data, the laser point coordinates at 50 ° in the 2 nd frame of laser point cloud data are aligned and then inserted into the 1 st frame of laser point cloud data. By means of continuous multi-frame laser point cloud data synthesis, data loss caused by scanning fluctuation can be avoided, and the information quantity of the laser point cloud data finally obtained by the processor is complete.

S20: and determining whether the robot is located in the base station environment according to the laser point cloud data. The base station environment is a space in the base station for housing the docking robot.

It can be understood that when the robot docks with the base station, the robot can dock in an area near the base station, where docking with the base station can be generated, i.e. in the base station environment, so as to realize docking. In some embodiments, where the robot is an unmanned vehicle and the base station is a cylindrical charging stake, the base station environment may include a matrix area space (equivalent to a parking space) in front of the charging interface on the charging stake. In some embodiments, as shown in fig. 4, the robot is a flat cylindrical sweeping robot, the base station is provided with a docking cavity, the shape of the docking cavity is matched with that of the flat cylindrical sweeping robot, and the docking cavity is provided with a concave semi-cylinder. Considering that the sweeping robot needs to be close to the base station to achieve docking within a certain range when docking with the base station, a sector area space surrounded by line segments OA and OB in fig. 4 and the inner wall of a docking cavity on the base station can be used as a base station environment, and when the sweeping robot enters the sector area space, the sweeping robot is located in the base station environment. Where point O is the furthest distance at which the robot can dock with the base station, and point O' is the closest distance at which the robot can dock with the base station.

The base station and other objects exist in the environment where the robot is located, and the generation principle of the laser point cloud data can be used for indicating the outline of surrounding objects on the laser scanning surface. Therefore, under the condition that the outline of the base station is known, the outline of the base station on the laser scanning surface can be identified from the laser point cloud data, and whether the robot is located in the base station environment can be determined by combining the distance between the robot and the base station. For example, if the contour of an object reflected by a certain segment of the laser spot is similar to the contour of the base station on the laser scanning surface, and the distance between the robot and the object (base station) is reasonable, it may be determined that the robot is located in the base station environment.

In some embodiments, the foregoing step S20 specifically includes:

s21: and traversing each laser point in the laser point cloud data, screening out the laser points with the distance within a preset distance interval, and forming a laser point set.

S22: and performing shape fitting on the laser point set, and if the fitted shape is suitable for the base station environment, determining that the robot is positioned in the base station environment.

Based on the fact that the robot needs to be close to the base station to achieve the butt joint in a certain range when the robot is in butt joint with the base station, a laser point set which possibly corresponds to the base station is screened out through a preset distance interval. The lower limit of the preset distance interval may be the shortest distance that the robot can generate docking with the base station, and the upper limit of the preset distance interval may be the farthest distance that the robot can generate docking with the base station. In the embodiment shown in fig. 4, the lower limit of the preset distance interval, that is, the short distance, may be the radius of the sweeping robot; the upper limit of the preset distance interval, i.e. the furthest distance, may be the diameter of the docking chamber on the base station.

It will be appreciated that the objects corresponding to the laser points in the set of laser points are objects close to the robot, satisfying the docking distance condition, indicating that the robot may be in a similar small area near the base station. Further judgment is required to determine whether the robot is located in the base station environment, i.e., whether the object near the robot is a base station. Here, the laser spot set is subjected to shape fitting, and if the fitted shape is adapted to the base station environment, it is determined that the robot is located in the base station environment.

The shape fitting refers to determining the distribution profile shape of the laser points in the laser point set, namely fitting the profile of an object corresponding to the laser point set on a laser scanning surface. By "fitting a shape that is compatible with the base station environment" is meant that the laser spot set fits a shape that is similar or approximately identical to the profile of the actual base station on the laser scanning surface. In some embodiments, if the robot is an unmanned vehicle, the base station is a cylindrical charging pile, trapezoid chamfers are arranged on two sides of the charging pile, the profile of the charging pile on the laser scanning surface is trapezoid, and if the laser point set fits into a trapezoid with approximately the same size, the fitted shape can be indicated to be suitable for the base station environment.

In this embodiment, the set of laser points that may be the corresponding base station is first screened out by a preset distance interval, that is, the object near the robot is screened out. Then, the laser point set is subjected to shape fitting, and the fitted shape is compared with the outline on the scanning surface of the base station, so that whether the robot is located in the base station environment or not can be accurately judged, and the docking accuracy is improved.

In some embodiments, the step S22 specifically includes: and performing circular fitting on the laser point set by adopting a least square method, and if the difference between the fitted circular radius and the radius of the base station environment is within a preset deviation range, determining that the robot is positioned in the base station environment.

Referring again to fig. 4, in this embodiment, the robot is a flat cylindrical sweeping robot, a docking cavity is provided on the base station, and the docking cavity is matched with the flat cylindrical sweeping robot in shape and has a semi-cylinder with a concave shape. Thus, the profile of the base station on the laser scanning surface is semicircular. Thus, a circular fit, i.e. a circular function curve, is performed on the set of laser points.

It will be appreciated that each laser spot in the set of laser spots has its coordinates in the radar coordinate system, and that since the laser scanning surfaces are of uniform height, the laser spots are substantially in the same plane, and thus a circular function curve can be fitted to these laser spot coordinates using the least squares method. It will be appreciated that the least squares method is a common fitting method in the field of algorithms and is not described in detail herein.

And comparing the radius of the fitted circular function curve with the radius of the base station environment, and if the difference between the fitted circular radius and the radius of the base station environment is within a preset deviation range, indicating that the fitted circular is approximately the same as the circular outline of the actual base station on the laser scanning surface, so that the robot can be determined to be positioned in the base station environment.

It should be noted that, the preset deviation range may be set by a person skilled in the art according to the actual situation, and the preset deviation range is not limited herein.

In the embodiment, based on the outline of the robot and the base station, the laser point set is subjected to circular fitting by adopting a least square method, the fitted circular radius is compared with the radius of the base station environment, and the robot is accurately determined to be positioned in the base station environment by adopting a preset deviation range for constraint, so that the docking accuracy is improved.

In some embodiments, before the foregoing "shape fitting to a set of laser points", the method further comprises: and if the number of the laser points in the laser point set is greater than or equal to a number threshold, performing shape fitting on the laser point set.

It can be appreciated that compared to an open environment, when the robot is located in the base station environment, the laser spot set screened out by the preset distance interval is denser. Therefore, the number threshold is set, and when the number of laser points in the laser point set is smaller than the number threshold, it can be directly determined that the robot is not in the base station environment, and thus, shape fitting is not required. When the number of the laser points in the laser point set is larger than or equal to a number threshold, the laser point set is subjected to shape fitting, invalid fitting operation can be avoided, calculation force is saved, and efficiency is improved.

In some embodiments, before the foregoing "shape fitting to a set of laser points", the method further comprises: the collection of laser spots is filtered to remove outlier laser spots.

Before shape fitting, the laser points in the laser point set are filtered, so that noise points (namely outlier laser points) can be further removed, and the laser point set after noise point removal is used as a new laser point set, so that invalid data can be filtered, and noise interference is reduced. In some embodiments, the laser point set may be subjected to cluster analysis, and it may be understood that the laser points corresponding to the base station have a cluster center to form a cluster. For laser points not belonging to the base station, the laser points not belonging to the cluster correspond to outliers. Therefore, laser points which do not belong to the cluster can be filtered, outlier laser points can be removed, and a new laser point set can be obtained. In some embodiments, as shown in fig. 4, the profile of the base station on the laser scanning surface is semicircular, so that laser points falling on a circle can be used to form a new laser point set, and laser points falling outside the circle are filtered out to remove outlier laser points.

It can be understood that the new laser point set obtained after filtering has few noise points, is beneficial to the accuracy of subsequent shape fitting, and further improves the accuracy of judging whether the laser point set is in the base station environment.

S30: and if the robot is positioned in the base station environment, extracting effective point cloud data corresponding to the base station from the laser point cloud data.

When the robot is located in the base station environment, in order to clearly determine the angle deviation between the docking device of the robot and the docking device of the base station, effective point cloud data corresponding to the base station are firstly extracted from laser point cloud data. Namely, the laser points reflecting other objects in the laser point cloud data are removed, and the effective point cloud data corresponding to the base station are adopted to participate in subsequent calculation, so that the data participating in calculation are tidier and more effective, and the interference caused by invalid data (the laser points corresponding to other objects) can be reduced.

In some embodiments, the foregoing step S30 specifically includes: and if the fitted shape is suitable for the base station environment, the laser point set is used as effective point cloud data.

From the above, if the fitted shape is adapted to the base station environment, it is explained that the robot is located in the base station environment. That is, the object corresponding to the laser point set is a base station, so that the laser point set can be used as effective point cloud data corresponding to the base station. It should be understood that, the "laser spot set" herein may be the laser spot set obtained by distance screening in the step S21, or may be a new laser spot set obtained by filtering the laser spot set.

S40: according to the effective point cloud data, determining a rotation parameter, and controlling the robot to rotate according to the rotation parameter, so that the docking device of the robot and the docking device of the base station are docked.

Based on the effective point cloud data, the outline of the base station on the laser scanning surface can be reflected, the position of the docking device of the base station relative to the base station is known, the position of the docking device of the robot relative to the robot is known, and therefore the docking device on the base station can be positioned according to the effective point cloud data, and the rotation parameters can be determined. The rotation parameter is a parameter that can rotate the docking device of the robot to the position of the docking device of the base station. And finally, controlling the robot to rotate according to the rotation parameters so as to enable the docking device of the robot to complete docking with the docking device of the base station.

The docking device of the robot can comprise an interface of a clean water tank, an interface of a sewage tank, an interface of a cleaning agent box, an interface of a dust collecting box, or a charging pole piece. Correspondingly, the docking device of the base station may comprise an interface of the cleaning device, an interface of the water supply device, an interface of the dust collection device, an interface of the power supply device, an interface of the cleaning agent supplementing device, or a charging pole piece. The man skilled in the art can set the docking device according to the actual requirements without any limitation.

In the embodiment, the robot can identify the environment of the positioning base station and determine the rotation parameters based on the self-scanned laser point cloud data, the docking base station does not need to rely on a signal sensor, and the robot can automatically dock the docking base station after the map is reset or when the map is not built or the base station is powered off, so that the docking base station is more stable and reliable. On the other hand, the rotation parameters can be accurately determined by reflecting the effective point cloud data of the scanning outline of the base station, so that the robot can dock with the docking base station more accurately, and the repeated collision and rotation of the robot in the base station environment can be reduced.

In some embodiments, the foregoing "determining rotation parameters according to the valid point cloud data" specifically includes:

s41: and acquiring a starting point angle and an end point angle of the effective point cloud data.

It can be understood that, based on that the laser radar starts to rotate one circle (for example, rotate clockwise) from 0 ° of the radar coordinate system, a frame of laser point cloud data of 360 ° is generated, and as known, the laser points in the laser point cloud data are sequentially arranged according to the scanning direction, and the angle is larger and larger according to the rotation direction.

In the laser radar scanning process, the laser point corresponding to the first scanned place on the base station is the starting point of the effective point cloud data, and the last laser point corresponding to the last scanned place on the base station is the end point of the effective point cloud data. The starting point angle is the angle corresponding to the starting point of the effective point cloud data, and the end point angle is the angle corresponding to the end point of the effective point cloud data.

It will be appreciated that the radar coordinate system is fixed relative to the robot itself, and that the lidar starts a rotational scan from 0 ° of the radar coordinate system, and therefore the magnitude of the start point angle and the magnitude of the end point angle are related to the orientation of the robot in the base station environment.

In some embodiments, after two end points of the effective point cloud data are obtained, the start point and the end point of the effective point cloud data are determined according to the scanning rotation direction of the laser. It will be appreciated that the start point is located before the end point in terms of scan rotation direction. As shown in (a) of fig. 5, the scanning rotation direction of the lidar is clockwise, so that the start point is point S, the end point is point E, the start point angle is 330 °, and the end point angle is 150 °. As shown in fig. 5 (b), the scanning rotation direction of the lidar is clockwise, the start point angle is 10 °, and the end point angle is 190 °.

In some embodiments, the robot is a flat cylindrical sweeping robot, the base station parking cavity is a semi-cylindrical, the effective point cloud data is a semi-circular arc, the effective point cloud data can be traversed from 0 degrees, and if the angle difference between two adjacent laser points is greater than a preset angle threshold value, the two laser points are respectively determined to be a starting point and an ending point according to the scanning rotation direction. The preset angle threshold may be determined according to the diameter d of the docking cavity and the farthest distance L at which the robot can dock with the base station. Referring again to fig. 4, the angle between the start point and the end point is 2 x arctan (d/L). I.e. the preset angle threshold may be 2 x arctan (d/L).

In some embodiments, the base station may also be subjected to laser scanning to collect a base station laser point cloud, and the preset angle threshold value is calculated from the collected base station laser point cloud.

S42: and determining the target angle of the docking device of the base station according to the starting point angle and the end point angle.

Since the position of the docking device of the base station relative to the base station is known, that is, the positions of the docking device of the base station relative to the edges of both sides of the base station are known, the target angle mid where the docking device of the base station is located can be determined according to the start angle start_angle and the end angle end_angle. As shown in fig. 5 (b), if the docking device of the base station is located in the middle between the start point and the end point of the valid point cloud data, i.e., the target angle mid= (start_angle+end_angle)/2.

S43: and determining a rotation parameter according to the target angle and the current angle of the docking device of the robot.

It will be appreciated that the position of the robot's docking device is known relative to the robot so that the current angle at which the robot's docking device is located can be obtained. For example, the current angle of the docking device of the robot in the radar coordinate system is 90 ° and the target angle is 100 °. Thus, the rotation parameter may be determined from the target angle and the current angle. For example, the rotation parameter is 10 ° in the scanning direction of the laser light.

In some embodiments, the rotation parameters include a rotation angle and a rotation direction. The step S43 specifically includes:

(1) And acquiring an absolute value of an angle difference between the target angle and the current angle.

It will be appreciated that the absolute value of the angle difference can reflect the angular separation between the target angle and the current angle. For example, the target angle is 30 °, the current angle is 50 °, and the absolute value of the angle difference between the two is 20 °. For example, the target angle is 10 °, the current angle is 200 °, and the absolute value of the angle difference between the two is 190 °.

(2) If the absolute value of the angle difference is smaller than or equal to 180 degrees and the target angle is larger than the current angle, determining the rotation angle as the absolute value of the angle difference, wherein the rotation direction is the scanning direction of the laser radar _。

It can be understood that, in the radar coordinate system, the angle range is 0 ° to 360 °, as shown in (a) of fig. 6, the target angle is 150 °, the current angle is 30 °, and the absolute value of the angle difference is 120 ° or less than 180 °, then the docking device of the robot can be quickly rotated to dock with the docking device of the base station by 120 ° according to the scanning direction of the laser radar, and the rotation amount is minimum.

(3) If the absolute value of the angle difference is smaller than or equal to 180 degrees and the target angle is smaller than the current angle, determining the rotation angle as the absolute value of the angle difference, wherein the rotation direction is opposite to the scanning direction of the laser radar.

As shown in fig. 6 (b), the target angle is 60 °, the current angle is 130 °, the absolute value of the angle difference is 70 ° or less than 180 °, and the docking device of the robot can be quickly rotated to dock with the docking device of the base station by rotating by 70 ° in the direction opposite to the scanning direction, and the rotation amount is minimal.

(4) If the absolute value of the angle difference is larger than 180 degrees and the target angle is larger than the current angle, the rotation angle is determined to be 360 degrees minus the absolute value of the angle difference, and the rotation direction is opposite to the scanning direction of the laser radar.

As shown in (c) of fig. 6, the target angle is 220 °, the current angle is 20 °, and the absolute value of the angle difference is 200 °, greater than 180 °, so that the robot docking device can be rotated in a direction opposite to the scanning direction (360 ° -200 °), i.e., rotated by 160 ° in a direction opposite to the scanning direction, and the docking device of the robot can be quickly rotated to dock with the docking device of the base station, and the rotation amount is minimal.

(5) If the absolute value of the angle difference is larger than 180 degrees and the target angle is smaller than the current angle, the rotation angle is determined to be 360 degrees minus the absolute value of the angle difference, and the rotation direction is the scanning direction of the laser radar.

As shown in (d) of fig. 6, the target angle is 40 °, the current angle is 250 °, the absolute value of the angle difference is 210 °, and the angle difference is greater than 180 °, the robot can be rotated in the direction opposite to the scanning direction (360 ° -210 °), i.e., rotated in the direction opposite to the scanning direction by 150 °, so that the docking device of the robot can be rapidly rotated to dock with the docking device of the base station, and the rotation amount is minimum.

In this embodiment, the rotation direction and the rotation angle are determined in the above manner, so that the robot can rotate by the smallest angle, that is, the target angle can be reached, the docking is realized, the rotation angle is as small as possible, and the collision can be reduced.

To further ensure that the robot is in a base station environment, the method, in some embodiments, further comprises:

s50: when receiving the infrared signal transmitted by the base station, it is determined that the robot is located in the base station environment.

Wherein the infrared signal is a signal transmitted by an infrared transmitter on the base station. It will be appreciated that the robot has an infrared receiver that receives the infrared signal. Based on near field propagation characteristics of the infrared signals, when the robot receives the infrared signals, the robot is close to the base station and is located in the base station environment.

Similarly, to further ensure that the robot is in a base station environment, to avoid misleading the robot in a small area similar to the base station environment, in some embodiments the method further comprises:

s60: acquiring the inclination angle of the robot, and if the inclination angle is within a preset angle interval, determining that the robot is positioned in the base station environment.

It will be appreciated that the base station includes a base, one way in which the base may be implemented is: the base comprises a base and an upper end cover, wherein the upper end cover is connected with the base to form a parking cavity with one end open. After returning to the base station, the robot can return to the docking cavity, so that the robot can be docked with a docking device on the base station. The base has a certain gradient, so that the robot can conveniently enter the stopping cavity. Therefore, based on the hardware form of the base station, the base station can judge whether the robot is on the base according to the inclination angle of the robot under the condition that the base grade is known.

Specifically, the inertial sensing unit on the robot can detect the inclination angle of the robot in real time and send the inclination angle to the processor, and if the processor calculates and monitors that the inclination angle is within a preset angle interval, the processor determines that the robot is located in the base station environment. It will be appreciated that the predetermined angular interval is determined based on the base grade.

In this embodiment, through infrared signal and/or inclination monitoring, it can further be ensured that the robot is in the base station environment, and the robot is prevented from being misled in a narrow area similar to the base station environment, and the accuracy of docking the robot to the docking station can be increased.

In summary, the method for docking a docking station provided by the embodiment of the application is applied to a robot including a laser radar, and the method includes the steps of firstly determining whether the robot is located in a base station environment (the base station environment is a space for accommodating the docking robot in the base station) according to laser point cloud data obtained by laser radar scanning, and extracting valid point cloud data corresponding to the base station from the laser point cloud data if the robot is located in the base station environment. The effective point cloud data corresponding to the base station can reflect the scanning outline of the base station, the position of the docking device of the base station relative to the base station is known, and the position of the docking device of the robot relative to the robot is known, so that the docking device on the base station can be positioned according to the effective point cloud data, and the rotation parameters can be determined. And finally, controlling the robot to rotate according to the rotation parameters so as to enable the docking device of the robot to complete docking with the docking device of the base station. In the embodiment, the robot can identify the environment of the positioning base station and determine the rotation parameters based on the self-scanned laser point cloud data, the docking base station does not need to rely on a signal sensor, and the robot can automatically dock the docking base station after the map is reset or when the map is not built or the base station is powered off, so that the docking base station is more stable and reliable. On the other hand, the rotation parameters can be accurately determined through the effective point cloud data reflecting the scanning outline of the base station, so that the robot berthing to the docking base station is more accurate.

Referring to fig. 7, fig. 7 is a schematic structural diagram of an apparatus for docking a docking station according to an embodiment of the present application. The docking station device is applied to a robot, and particularly, the docking station device is applied to one or more processors of the robot.

As shown in fig. 7, the docking station apparatus 200 includes: an acquisition module 201, a base station environment determination module 202, an extraction module 203, and a rotation parameter determination module 204.

The acquisition module 201 is configured to acquire laser point cloud data obtained by laser radar scanning. The base station environment determining module 202 is configured to determine, according to the laser point cloud data, whether the robot is located in a base station environment, where the base station environment is a space in the base station for accommodating the robot to dock. The extraction module 203 is configured to extract valid point cloud data corresponding to the base station from the laser point cloud data if the robot is located in the base station environment. The rotation parameter determining module 204 is configured to determine a rotation parameter according to the valid point cloud data, and control the robot to rotate according to the rotation parameter, so that the docking device of the robot and the docking device of the base station complete docking.

In the embodiment of the present application, the device for docking a docking station may also be built by hardware devices, for example, the device for docking a docking station may be built by one or more than two chips, and each chip may coordinate with each other to complete the method for docking a docking station described in each embodiment above. For another example, the docking station apparatus may also be built from various types of logic devices, such as general purpose processors, digital Signal Processors (DSPs), application Specific Integrated Circuits (ASICs), field Programmable Gate Arrays (FPGAs), singlechips, ARM (Acorn RISC Machine) or other programmable logic devices, discrete gate or transistor logic, discrete hardware components, or any combination of these components.

The device for docking with the docking station in the embodiment of the present application may be a device with an operating system. The operating system may be an Android operating system, an ios operating system, or other possible operating systems, and the embodiment of the present application is not limited specifically.

The device for docking the docking station provided by the embodiment of the application can realize each process which can be realized by the method for docking the docking station, and is not repeated here.

It should be noted that, the device for docking the docking station may execute the method for docking the docking station provided by the embodiment of the present application, and has the corresponding functional module and beneficial effects of the execution method. Technical details not described in detail in the device embodiments of docking stations may be found in the method for docking stations provided by the embodiments of the present application.

The embodiment of the application also provides a robot, please refer to fig. 8, and fig. 8 is a schematic hardware structure of the robot according to the embodiment of the application.

As shown in fig. 8, the robot 300 comprises at least one processor 301, a memory 302 and a lidar 303 (bus connection, one processor being an example in fig. 8) in communication connection.

Wherein the processor 301 is configured to provide computing and control capabilities for controlling the robot 300 to perform corresponding tasks, for example, controlling the robot 300 to perform a method of docking a docking station in any of the method embodiments described above, the method comprising: and acquiring laser point cloud data obtained by laser radar scanning. According to the laser point cloud data, whether the robot is located in a base station environment is determined, wherein the base station environment is a space in a base station for accommodating the robot to stop. And if the robot is positioned in the base station environment, extracting effective point cloud data corresponding to the base station from the laser point cloud data. According to the effective point cloud data, determining a rotation parameter, and controlling the robot to rotate according to the rotation parameter, so that the docking device of the robot and the docking device of the base station are docked.

In the embodiment, the robot can identify the environment of the positioning base station and determine the rotation parameters based on the self-scanned laser point cloud data, the docking base station does not need to rely on a signal sensor, and the robot can automatically dock the docking base station after the map is reset or when the map is not built or the base station is powered off, so that the docking base station is more stable and reliable. On the other hand, the rotation parameters can be accurately determined through the effective point cloud data reflecting the scanning outline of the base station, so that the robot berthing to the docking base station is more accurate.

The processor 301 may be a general purpose processor including a central processing unit (Central Processing Unit, CPU), a network processor (Network Processor, NP), a hardware chip, or any combination thereof; it may also be a digital signal processor (Digital Signal Processing, DSP), application specific integrated circuit (Application Specific Integrated Circuit, ASIC), programmable logic device (programmable logic device, PLD), or a combination thereof. The PLD may be a complex programmable logic device (complex programmable logic device, CPLD), a field-programmable gate array (field-programmable gate array, FPGA), general-purpose array logic (generic array logic, GAL), or any combination thereof.

The memory 302 serves as a non-transitory computer readable storage medium, and may be used to store non-transitory software programs, non-transitory computer executable programs, and modules, such as program instructions/modules corresponding to the method of docking to a base station in an embodiment of the present application. The processor 301 may implement the method for docking to the docking station in any of the above method embodiments by running non-transitory software programs, instructions and modules stored in the memory 302, and will not be described here again to avoid repetition.

In particular, the memory 302 may include Volatile Memory (VM), such as random access memory (random access memory, RAM); the memory 302 may also include a non-volatile memory (NVM), such as read-only memory (ROM), flash memory (flash memory), hard disk (HDD) or Solid State Drive (SSD), or other non-transitory solid state storage devices; memory 302 may also include a combination of the types of memory described above.

In an embodiment of the application, the memory 302 may also include memory located remotely from the processor, which may be connected to the processor via a network. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof.

In some embodiments, lidar 303 comprises a pulsed lidar, a continuous wave lidar, or the like.

In the embodiment of the present application, the robot 300 may further have a wired or wireless network interface, a keyboard, an input/output interface, and other components for implementing the functions of the device, which are not described herein.

Embodiments of the present application also provide a computer readable storage medium, such as a memory, comprising program code executable by a processor to perform the method of docking a docking station in the above embodiments. For example, the computer readable storage medium may be Read-Only Memory (ROM), random-access Memory (Random Access Memory, RAM), compact disc Read-Only Memory (CDROM), magnetic tape, floppy disk, optical data storage device, etc.

Embodiments of the present application also provide a computer program product comprising one or more program codes stored in a computer-readable storage medium. The program code is read from the computer readable storage medium by a processor of the electronic device, which is executed by the processor to perform the method steps of the method of docking to a base station provided in the above-described embodiments.

It should be noted that the above-described apparatus embodiments are merely illustrative, and the units described as separate units may or may not be physically separate, and units shown as units may or may not be physical units, may be located in one place, or may be distributed over a plurality of network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

From the above description of embodiments, it will be apparent to those skilled in the art that the embodiments may be implemented by means of software plus a general purpose hardware platform, or may be implemented by hardware. Those skilled in the art will appreciate that all or part of the processes implementing the methods of the above embodiments may be implemented by a computer program for instructing relevant hardware, where the program may be stored in a computer readable storage medium, and where the program may include processes implementing the embodiments of the methods described above. The storage medium may be a magnetic disk, an optical disk, a Read-Only Memory (ROM), a random access Memory (Random Access Memory, RAM), or the like.

Finally, it should be noted that: the above embodiments are only for illustrating the technical solution of the present application, and are not limiting; the technical features of the above embodiments or in the different embodiments may also be combined within the idea of the application, the steps may be implemented in any order, and there are many other variations of the different aspects of the application as described above, which are not provided in detail for the sake of brevity; although the application has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical scheme described in the foregoing embodiments can be modified or some technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit of the application.

Claims

1. A method of docking a docking station for a robot including a lidar, comprising:

acquiring laser point cloud data obtained by scanning the laser radar;

determining whether the robot is located in a base station environment or not according to the laser point cloud data, wherein the base station environment is a space for accommodating and stopping the robot in a base station;

and determining a rotation parameter according to the effective point cloud data, and controlling the robot to rotate according to the rotation parameter so as to enable the docking device of the robot to be docked with the docking device of the base station.

2. The method of claim 1, wherein determining whether the robot is located in a base station environment based on the laser point cloud data comprises:

and performing shape fitting on the laser point set, and if the fitted shape is matched with the base station environment, determining that the robot is positioned in the base station environment.

3. The method of claim 2, wherein the performing shape fitting on the set of laser points, and if the fitted shape is compatible with the base station environment, determining that the robot is located in the base station environment comprises:

4. The method of claim 2, wherein prior to said shape fitting the set of laser points, the method further comprises:

5. The method according to claim 2, wherein the extracting valid point cloud data corresponding to the base station environment from the laser point cloud data includes:

and if the fitted shape is suitable for the base station environment, the laser point set is used as the effective point cloud data.

6. The method of claim 1, wherein determining rotation parameters from the valid point cloud data comprises:

Acquiring a starting point angle and an end point angle of the effective point cloud data;

determining a target angle of a docking device of the base station according to the starting point angle and the ending point angle;

and determining the rotation parameter according to the target angle and the current angle of the docking device of the robot.

7. The method of claim 6, wherein the rotation parameters include a rotation angle and a rotation direction;

the determining the rotation parameter according to the target angle and the current angle of the docking device of the robot comprises:

acquiring an absolute value of an angle difference between the target angle and the current angle;

if the absolute value of the angle difference is smaller than or equal to 180 degrees and the target angle is smaller than the current angle, determining that the rotation angle is the absolute value of the angle difference, wherein the rotation direction is opposite to the scanning direction of the laser radar;

And if the absolute value of the angle difference is larger than 180 degrees and the target angle is smaller than the current angle, determining that the rotation angle is 360 degrees minus the absolute value of the angle difference, wherein the rotation direction is the scanning direction of the laser radar.

8. The method according to claim 1, wherein the method further comprises:

when receiving an infrared signal transmitted by the base station, determining that the robot is located in the base station environment; and/or the number of the groups of groups,

acquiring an inclination angle of the robot, and if the inclination angle is within a preset angle interval, determining that the robot is located in the base station environment.

9. A robot, comprising:

the laser radar (lidar),

at least one processor, said at least one processor being communicatively coupled to said lidar;

a memory communicatively coupled to the at least one processor; wherein the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the method of docking the docking station of any of claims 1-8.

10. A computer readable storage medium storing computer executable instructions for causing a computer device to perform the method of docking to a docking station of any of claims 1-8.