Control method for operation robot and operation robot

Abstract

The invention discloses a control method for an operation robot and the operation robot, and belongs to the technical field of building construction. The method comprises the following steps: acquiring an initial point cloud of a target construction space acquired by a point cloud acquisition device; on the basis of the initial point cloud, concave angular points of all wall surfaces in the target construction space are recognized; concave corner point distances corresponding to the concave corner points are obtained, and the concave corner point distances corresponding to the concave corner points are the distances between the concave corner points and the operation robot; determining a distance difference value between concave angular point distances corresponding to two concave angular points on at least any side; and controlling the operation robot to move according to the distance difference. The operation precision of the operation robot can be improved.

Description

Technical Field

[0001] The present application relates to the technical field of working robot control, and in particular to a control method for a working robot and a working robot. Background Art

[0002] At present, in work scenarios such as goods transportation and environmental cleaning, work robots have been widely used to perform corresponding work tasks. In the process of performing work tasks, it is usually necessary to control the work robot to move to the target work position, or control the work robot to move along the target movement path, so that the work robot can complete the work task. However, when the existing control method is used to control the movement of the work robot, the work robot has the problem of low operation accuracy. Summary of the invention

[0003] The purpose of the embodiments of the present application is to provide a control method for a working robot and a working robot, so as to solve the problem of low operating accuracy of existing working robots.

[0004] In order to achieve the above-mentioned object, a first aspect of an embodiment of the present application provides a control method for a working robot, wherein the working robot includes a point cloud acquisition device, and the working robot is located in a target construction space. The control method includes:

[0005] Acquire an initial point cloud of a target construction space collected by a point cloud collection device;

[0006] Based on the initial point cloud, identify the concave corner points of each wall in the target construction space;

[0007] Obtain the concave corner point distance corresponding to each concave corner point, where the concave corner point distance corresponding to the concave corner point is the distance between the concave corner point and the operating robot;

[0008] Determine the distance difference between the concave corner point distances corresponding to two concave corner points located on at least any one side;

[0009] According to the distance difference, the working robot is controlled to move.

[0010] In an embodiment of the present application, based on the initial point cloud, the concave corner points of each wall in the target construction space are identified, including: obtaining the first direction coordinate value of each point cloud data in the initial point cloud in the first direction; obtaining the point cloud identifier corresponding to each point cloud data; determining the adjacent point cloud data in the initial point cloud according to the point cloud identifier corresponding to each point cloud data; determining the coordinate value difference between the first direction coordinate values ​​corresponding to the adjacent point cloud data; determining the concave corner point according to the coordinate value difference, the concave corner point being a point corresponding to the point cloud data whose point cloud identifier is the target point cloud identifier in the adjacent point cloud data whose corresponding coordinate value difference is greater than the preset coordinate value difference.

[0011] In an embodiment of the present application, obtaining a point cloud identification corresponding to each point cloud data includes: clustering the point cloud data in the initial point cloud according to the first direction coordinate value to obtain a plurality of point cloud clustering clusters; determining the first direction coordinate value average of the first direction coordinate value corresponding to the point cloud data in each point cloud clustering cluster; merging and clustering the plurality of point cloud clustering clusters according to the first direction coordinate value average to obtain a wall point cloud corresponding to each wall surface; and obtaining a point cloud identification corresponding to each point cloud data in each wall point cloud.

[0012] In an embodiment of the present application, multiple point cloud clustering clusters all have corresponding clustering cluster identifiers, and the clustering cluster identifiers are determined according to the number of point cloud data in the point cloud clustering clusters; based on the average value of the first direction coordinate values, the multiple point cloud clustering clusters are merged and clustered to obtain wall point clouds corresponding to each wall surface, including: determining adjacent point cloud clustering clusters in the multiple point cloud clustering clusters according to the clustering cluster identifiers; determining a first difference in the average values ​​of the first direction coordinate values ​​corresponding to adjacent point cloud clustering clusters; merging and clustering the multiple point cloud clustering clusters according to the first difference to obtain each wall point cloud, and each wall point cloud is obtained by merging and clustering adjacent point cloud clustering clusters whose corresponding first difference is less than the preset average value difference.

[0013] In an embodiment of the present application, the working robot also includes multiple distance detection devices, and the control method also includes: obtaining multiple target distance parameters based on the multiple distance detection devices; and adjusting the position and / or posture of the working robot according to the multiple target distance parameters.

[0014] In an embodiment of the present application, multiple distance detection devices are respectively arranged on each side of the working robot, and the posture of the working robot is adjusted according to multiple target distance parameters, including: determining a second difference between two adjacent target distance parameters among the multiple target distance parameters, wherein the two adjacent target distance parameters are detected by a distance detection device arranged on the same side; when the second difference is greater than a preset target distance parameter difference, controlling the working robot to rotate in a clockwise direction until the second difference is less than a preset target distance parameter difference error; when the second difference is less than the preset target distance parameter difference, controlling the working robot to rotate in a counterclockwise direction until the second difference is less than the preset target distance parameter difference error.

[0015] In an embodiment of the present application, multiple distance detection devices are respectively arranged on each side of the working robot, and the position of the working robot is adjusted according to multiple target distance parameters, including: obtaining a first distance parameter detected by a distance detection device arranged on the first side and a second distance parameter detected by a distance detection device arranged on the second side, wherein the first side and the second side are sides of the working robot that are relatively arranged and parallel to each other, and the multiple target distance parameters include the first distance parameter and the second distance parameter; when the first distance parameter is greater than the second distance parameter, the working robot is controlled to move in the direction of the side where the distance detection device corresponding to the first distance parameter is located.

[0016] In an embodiment of the present application, obtaining multiple target distance parameters based on multiple distance detection devices includes: obtaining multiple initial distance parameters detected by multiple distance detection devices; in the case where there is an out-of-range distance parameter among the multiple initial distance parameters, determining the target side where the distance detection device corresponding to the out-of-range distance parameter is located, wherein the out-of-range distance parameter is an initial distance parameter greater than a preset distance parameter threshold; removing the initial distance parameters detected by the distance detection device on the target side among the multiple initial distance parameters to obtain multiple target distance parameters.

[0017] In an embodiment of the present application, the control method also includes: respectively obtaining the vertical distance between the spraying operation robot and each wall; determining whether any vertical distance is less than a preset anti-collision distance; and controlling the operation robot to stop moving when any vertical distance is less than the preset anti-collision distance.

[0018] A second aspect of an embodiment of the present application provides a processor configured to execute the above-mentioned control method for a working robot.

[0019] A third aspect of an embodiment of the present application provides a working robot, comprising: a robot body; a point cloud acquisition device; and a processor.

[0020] The above technical solution obtains the initial point cloud of the target construction space collected by the point cloud acquisition device, and then identifies the concave corner points of each wall in the target construction space based on the initial point cloud, then obtains the concave corner point distance between each concave corner point and the operating robot, and then determines the distance difference between the concave corner point distances corresponding to two concave corner points located on at least any one side, and finally controls the movement of the operating robot according to the distance difference. This application determines the concave corner point distance between each concave corner point and the operating robot after identifying the concave corner points of each wall in the target construction space, thereby controlling the movement of the operating robot according to the concave corner point distance to ensure the operating accuracy of the operating robot. When this technical solution is applied to a spraying operating robot, it can realize automatic or auxiliary drawing of square lines and can improve the drawing accuracy of square lines.

[0021] Other features and advantages of the embodiments of the present application will be described in detail in the subsequent specific implementation section. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] The accompanying drawings are used to provide a further understanding of the embodiments of the present application and constitute a part of the specification. Together with the following specific implementations, they are used to explain the embodiments of the present application, but do not constitute a limitation on the embodiments of the present application. In the accompanying drawings:

[0023] Figure 1 A schematic diagram of a flow chart of a control method for a working robot according to an embodiment of the present application is schematically shown;

[0024] FIG. 2( a ) and FIG. 2( b ) schematically show a schematic diagram of a ground spraying operation process according to a specific embodiment of the present application;

[0025] Figure 3 A schematic diagram showing the effect of a point cloud cluster before removal according to a specific embodiment of the present application;

[0026] Figure 4 A schematic diagram showing the effect of point cloud cluster removal according to a specific embodiment of the present application;

[0027] FIG. 5( a ), FIG. 5( b ) and FIG. 5( c ) schematically illustrate a process of adjusting the position and posture of a working robot according to a specific embodiment of the present application;

[0028] Figure 6 The structural block diagram of a computer device according to an embodiment of the present application is schematically shown. DETAILED DESCRIPTION

[0029] In order to make the purpose, technical scheme and advantages of the embodiments of the present application clearer, the technical scheme in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. It should be understood that the specific implementation methods described herein are only used to illustrate and explain the embodiments of the present application, and are not used to limit the embodiments of the present application. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of this application.

[0030] It should be noted that if the embodiments of the present application involve directional indications (such as up, down, left, right, front, back...), the directional indications are only used to explain the relative position relationship, movement status, etc. between the components under a certain specific posture (as shown in the accompanying drawings). If the specific posture changes, the directional indication will also change accordingly.

[0031] In addition, if there are descriptions involving "first", "second", etc. in the embodiments of the present application, the descriptions of "first", "second", etc. are only used for descriptive purposes and cannot be understood as indicating or suggesting their relative importance or implicitly indicating the number of technical features indicated. Therefore, the features defined as "first" and "second" may explicitly or implicitly include at least one of the features. In addition, the technical solutions between the various embodiments can be combined with each other, but they must be based on the ability of ordinary technicians in the field to implement them. When the combination of technical solutions is contradictory or cannot be implemented, it should be deemed that such combination of technical solutions does not exist and is not within the scope of protection required by this application.

[0032] Figure 1 The following schematically shows a flow chart of a control method for a working robot according to an embodiment of the present application. Figure 1 As shown, an embodiment of the present application provides a control method for a working robot, the working robot includes a point cloud acquisition device, and the working robot is located in a target construction space. Taking the control method applied to a processor as an example, the control method may include the following steps:

[0033] Step S101: Acquire the initial point cloud of the target construction space collected by the point cloud collection device.

[0034] Step S102: Based on the initial point cloud, identify the concave corner points of each wall in the target construction space.

[0035] Step S103: Obtain the concave corner point distance corresponding to each concave corner point, where the concave corner point distance corresponding to the concave corner point is the distance between the concave corner point and the working robot.

[0036] Step S104: determining the distance difference between the concave corner point distances corresponding to two concave corner points located on at least any one side.

[0037] Step S105: Control the movement of the working robot according to the distance difference.

[0038] The control method for a working robot provided in an embodiment of the present application can be used to control the working robot. The working robot includes a point cloud acquisition device. The point cloud acquisition device can be a multi-line laser radar or other device that can be used to collect point clouds. The target construction space refers to the construction space where the working robot operates, and there are multiple walls in the target construction space. Inside the target construction space, two adjacent walls can form a concave corner point.

[0039] In an embodiment of the present application, the operating robot is located in the target construction space. The initial point cloud of the target construction space can be collected by the point cloud acquisition device. In this way, the processor can obtain the initial point cloud collected by the point cloud acquisition device, and identify the initial point cloud to obtain the concave corner points of each wall in the target construction space. After identifying the concave corner point, the processor can obtain the concave corner point distance corresponding to each concave corner point, that is, the distance between the concave corner point and the operating robot. It can be understood that the concave corner point distance can be determined by the processor according to the initial point cloud, or it can be obtained by setting a distance acquisition device (such as a single-line laser radar) on the operating robot. Further, the processor can determine the distance difference between the concave corner point distances corresponding to two concave corner points located on at least one side, and determine whether the distance difference is less than the preset distance difference. The preset distance difference can be determined according to the actual control accuracy requirements. When the distance difference is less than the preset distance difference, the processor can control the operating robot to move in a direction perpendicular to the side where the two concave corner points are located.

[0040] In some embodiments, the working robot may be a spraying robot, and the processor may control the working robot to spray the ground while moving, thereby drawing a square line. When the distance difference is greater than or equal to a preset distance difference, the working robot is controlled to stop the ground spraying operation, and the working robot is controlled to adjust its position and / or posture, so as to reduce the possibility of deviation of the drawn square line due to the deviation of the moving route of the working robot.

[0041] In other embodiments, the working robot can carry a laser level, and the processor controls the movement of the working robot based on the distance difference until the distance difference is less than a preset distance difference, then the laser level is turned on, making it convenient for the user to draw a square line along the laser line, thereby assisting in the drawing of the square line.

[0042] Of course, by designing the attachments or actuators carried by the working robot, the working robot can be used for other functions, such as transporting goods, etc., and the control method provided in the embodiment of the present application is used to specifically implement the relevant functions, which will not be given one by one here. To simplify the description, the following will mainly take the working robot as an example of a spraying working robot to introduce the control method for the working robot.

[0043] Figures 2(a) and 2(b) schematically show a schematic diagram of a ground spraying operation process according to a specific embodiment of the present application. As shown in Figures 2(a) and 2(b), in a specific embodiment of the present application, after the processor identifies the concave corner points in the target construction space based on the initial point cloud, an isosceles triangle line drawing can be performed, that is, the concave corner point distance between the operating robot and the two concave corner points located on at least one side is determined respectively, and then the distance difference between the concave corner point distances corresponding to the two concave corner points is determined. In this way, the operating robot can be controlled according to the distance difference. During the control process, a certain error is allowed. If the distance difference is less than the preset distance difference, it is considered that the concave corner point distance between the operating robot and the two concave corner points located on the same side is equal at this time, and the operating robot can be controlled to perform ground spraying operations to draw horizontal and vertical square lines.

[0044] The above technical solution obtains the initial point cloud of the target construction space collected by the point cloud acquisition device, and then identifies the concave corner points of each wall in the target construction space based on the initial point cloud, then obtains the concave corner point distance between each concave corner point and the operating robot, and then determines the distance difference between the concave corner point distances corresponding to two concave corner points located on at least any one side, and finally controls the movement of the operating robot according to the distance difference. This application determines the concave corner point distance between each concave corner point and the operating robot after identifying the concave corner points of each wall in the target construction space, thereby controlling the movement of the operating robot according to the concave corner point distance to ensure the operating accuracy of the operating robot. When this technical solution is applied to a spraying operating robot, it can realize automatic or auxiliary drawing of square lines and can improve the drawing accuracy of square lines.

[0045] In an embodiment of the present application, based on the initial point cloud, the concave corner points of each wall in the target construction space are identified, including: obtaining the first direction coordinate value of each point cloud data in the initial point cloud in the first direction; obtaining the point cloud identifier corresponding to each point cloud data; determining the adjacent point cloud data in the initial point cloud according to the point cloud identifier corresponding to each point cloud data; determining the coordinate value difference between the first direction coordinate values ​​corresponding to the adjacent point cloud data; determining the concave corner point according to the coordinate value difference, the concave corner point being a point corresponding to the point cloud data whose point cloud identifier is the target point cloud identifier in the adjacent point cloud data whose corresponding coordinate value difference is greater than the preset coordinate value difference.

[0046] The processor can identify the concave corner points of each wall in the target construction space based on the initial point cloud. Specifically, each point cloud data includes a first direction coordinate value in the first direction, a second direction coordinate value in the second direction, and a third direction coordinate value in the third direction. The processor can decompose each point cloud data to obtain the first direction coordinate value of each point cloud data. It should be noted that before decomposing the point cloud data, the point cloud data can be preprocessed, such as performing angle pass filtering to remove noise points and abnormal point data. In addition, if the point cloud acquisition device uses a multi-line laser radar, the point cloud data collected by the point cloud acquisition device can be compressed to reduce the measurement error. Specifically, the point cloud data collected by each laser radar beam are respectively arranged in ascending order to determine the point cloud identifier corresponding to each point cloud data, and then the point cloud data with the same point cloud identifier in the point cloud data collected by all laser radar beams is determined, and the average value of the coordinate values ​​corresponding to the point cloud data with the same point cloud identifier is used as the coordinate value of the compressed point cloud data.

[0047] After completing the aforementioned point cloud data processing process, the processor can obtain the point cloud identifier corresponding to each point cloud data. It can be understood that the point cloud identifier corresponding to the point cloud data can be determined according to the scanning direction of the point cloud acquisition device, that is, the point cloud identifier corresponding to each point cloud data is determined according to the acquisition sequence of each point cloud data. In this way, according to the point cloud identifier corresponding to each point cloud data, the processor can determine two point cloud data with adjacent point cloud identifiers as adjacent point cloud data, and then determine the coordinate value difference between the first direction coordinate values ​​corresponding to the adjacent point cloud data. When the coordinate value difference corresponding to the adjacent point cloud data is greater than the preset coordinate value difference, the point corresponding to the point cloud data with the point cloud identifier as the target point cloud identifier is determined as a concave corner point. Among them, the preset coordinate value difference can be determined according to the actual operation scene. The target point cloud identifier refers to the larger point cloud identifier or the smaller point cloud identifier in the point cloud identifier corresponding to the adjacent point cloud data, and which point cloud identifier is specifically taken can be set according to the operation situation. In this way, the processor can identify the concave corner points in the target construction space, which is convenient for the subsequent control of the operation robot based on the concave corner point distance corresponding to each concave corner point.

[0048] In an embodiment of the present application, obtaining a point cloud identification corresponding to each point cloud data includes: clustering the point cloud data in the initial point cloud according to the first direction coordinate value to obtain a plurality of point cloud clustering clusters; determining the first direction coordinate value average of the first direction coordinate value corresponding to the point cloud data in each point cloud clustering cluster; merging and clustering the plurality of point cloud clustering clusters according to the first direction coordinate value average to obtain a wall point cloud corresponding to each wall surface; and obtaining a point cloud identification corresponding to each point cloud data in each wall point cloud.

[0049] Specifically, before obtaining the point cloud identifier corresponding to each point cloud data, based on the preset clustering algorithm, the processor can also cluster the point cloud data in the initial point cloud according to the first direction coordinate value, so as to obtain multiple point cloud clustering clusters. In this process, the clustering algorithm can adopt the DENCLUE clustering algorithm, the DBSCAN clustering algorithm or other algorithms that can realize point cloud clustering. Subsequently, according to the first direction coordinate value corresponding to the point cloud data contained in each point cloud clustering cluster, the processor can determine the average value of the first direction coordinate value corresponding to each point cloud clustering cluster. According to the average value of the first direction coordinate value, the processor can merge and cluster multiple point cloud clustering clusters, so as to obtain the wall point cloud corresponding to each wall surface, and realize the merging of the point cloud data of the same wall surface.

[0050] In addition, before clustering, the processor may perform numerical filtering on the first direction coordinate values ​​to determine the first direction coordinate values ​​that need to be filtered out, and remove the point cloud data corresponding to the first direction coordinate values ​​that need to be filtered out as noise points.

[0051] and, Figure 3 The schematic diagram shows the effect of a point cloud clustering before removal according to a specific embodiment of the present application. Figure 4 The schematic diagram shows the effect of removing point cloud clusters according to a specific embodiment of the present application. Figure 3 and Figure 4 As shown, before merging and clustering multiple point cloud clusters, in order to improve the subsequent concave corner point recognition accuracy, the processor can determine the number of point cloud data in each point cloud cluster. If the number of point cloud data in any point cloud cluster is less than the preset number, the point cloud cluster is removed and the point cloud cluster is not merged and clustered. In this way, point cloud data that may interfere with the subsequent concave corner point recognition process can be removed.

[0052] If referring to the above steps, some point cloud clusters are removed according to the number of point cloud data in each point cloud cluster, then after obtaining each wall point cloud, based on the adaptive interpolation method, according to the first direction coordinate value corresponding to each point cloud data in each wall point cloud, the processor can complete each wall point cloud. Specifically, since part of the point cloud data is removed in the above steps, the processor can update the point cloud identifier corresponding to each point cloud data, and determine the adjacent point cloud data according to the updated point cloud identifier, and then determine the coordinate value difference of the first direction coordinate value corresponding to the adjacent point cloud data. Subsequently, according to the difference interval where the coordinate value difference is located, linear interpolation can be performed between the first direction coordinate values ​​corresponding to the adjacent point cloud data, so as to obtain a complete wall point cloud. In one example, if the coordinate value difference is in the first difference interval, p linear interpolation can be performed at this time, and if the coordinate value difference is in the second difference interval, q linear interpolation can be performed at this time. Among them, the maximum value of the first difference interval is less than the minimum value of the second difference interval, and p is less than q. In this way, linear interpolation can be performed according to the coordinate value difference between the first direction coordinate values ​​corresponding to adjacent point cloud data, so that the filled data is more accurate.

[0053] In an embodiment of the present application, multiple point cloud clustering clusters all have corresponding clustering cluster identifiers, and the clustering cluster identifiers are determined according to the number of point cloud data in the point cloud clustering clusters; based on the average value of the first direction coordinate values, the multiple point cloud clustering clusters are merged and clustered to obtain wall point clouds corresponding to each wall surface, including: determining adjacent point cloud clustering clusters in the multiple point cloud clustering clusters according to the clustering cluster identifiers; determining a first difference in the average values ​​of the first direction coordinate values ​​corresponding to adjacent point cloud clustering clusters; merging and clustering the multiple point cloud clustering clusters according to the first difference to obtain each wall point cloud, and each wall point cloud is obtained by merging and clustering adjacent point cloud clustering clusters whose corresponding first difference is less than the preset average value difference.

[0054] After obtaining multiple point cloud clustering clusters, the processor can merge and cluster the multiple point cloud clustering clusters according to the average value of the first direction coordinate value, so as to obtain the wall point cloud corresponding to each wall surface, and realize the merging of the point cloud data of the same wall surface. Specifically, multiple point cloud clustering clusters all have corresponding clustering cluster identifiers, and the clustering cluster identifiers can be determined after arranging the number of point cloud data in the point cloud clustering clusters in descending order. In this way, the processor can determine the adjacent point cloud clustering clusters in the multiple point cloud clustering clusters according to the clustering cluster identifiers. Among them, adjacent point cloud clustering clusters refer to two point cloud clustering clusters with adjacent clustering cluster identifiers. Subsequently, the processor can determine the first difference between the average values ​​of the first direction coordinate values ​​corresponding to the adjacent point cloud clustering clusters according to the average value of the first direction coordinate values ​​corresponding to the adjacent point cloud clustering clusters. When the first difference is less than the preset average value difference, the adjacent point cloud clustering clusters are merged. The preset average value difference is set according to the actual situation. In this way, after completing the merging and clustering of multiple point cloud clustering clusters, the processor can obtain the wall point cloud corresponding to each wall surface.

[0055] In addition, the processor may perform quantile numerical filtering on the point cloud data according to the first direction coordinate value corresponding to each point cloud data in the point cloud cluster, so as to further filter out noise points.

[0056] In an embodiment of the present application, the working robot also includes multiple distance detection devices, and the control method also includes: obtaining multiple target distance parameters based on the multiple distance detection devices; and adjusting the position and / or posture of the working robot according to the multiple target distance parameters.

[0057] The processor can adjust the position and / or posture of the working robot to improve the efficiency of the subsequent control of the working robot to perform ground spraying operations. Specifically, a plurality of distance detection devices are also provided on the working robot. The distance detection device can adopt a single-line laser radar, or adopt other devices that can detect distance parameters. The processor can obtain a plurality of initial distance parameters detected by a plurality of distance detection devices. It can be understood that the initial distance parameter refers to the distance from the wall to the distance detection device. After filtering the plurality of initial distance parameters, the processor can obtain a plurality of target distance parameters. In this way, according to the plurality of target distance parameters, the processor can adjust the position and / or posture of the working robot.

[0058] In an embodiment of the present application, obtaining multiple target distance parameters based on multiple distance detection devices includes: obtaining multiple initial distance parameters detected by multiple distance detection devices; in the case where there is an out-of-range distance parameter among the multiple initial distance parameters, determining the target side where the distance detection device corresponding to the out-of-range distance parameter is located, wherein the out-of-range distance parameter is an initial distance parameter greater than a preset distance parameter threshold; removing the initial distance parameters detected by the distance detection device on the target side among the multiple initial distance parameters to obtain multiple target distance parameters.

[0059] A plurality of distance detection devices are respectively arranged on each side of the working robot to detect the initial distance parameters between the working robot and each wall surface. Each side is provided with more than two distance detection devices. After the processor obtains the plurality of initial distance parameters detected by the plurality of distance detection devices, the plurality of initial distance parameters can be filtered to obtain a plurality of target distance parameters. Specifically, the processor can determine whether there is an over-range distance parameter among the plurality of initial distance parameters, that is, an initial distance parameter greater than a preset distance parameter threshold. The preset distance parameter threshold can be determined according to the size of the target construction space. If there is an over-range distance parameter among the plurality of initial distance parameters, the processor can determine the distance detection device that detects the over-range distance parameter, and further determine the target side where the distance detection device that detects the over-range distance parameter is located. Subsequently, the processor can remove the initial distance parameters detected by the distance detection device on the target side among the plurality of initial distance parameters to obtain a plurality of target distance parameters, thereby completing the filtering process of the plurality of initial distance parameters. For example, if there is an over-range distance parameter among the plurality of initial distance parameters, the target side where the distance detection device that detects the over-range distance parameter is located can be determined. Assuming that three distance detection devices are set on the side of the target, at this time, all the initial distance parameters detected by the three distance detection devices set on the side of the target are removed, so as to obtain multiple target distance parameters. In this way, invalid data can be removed, and only the distance between the working robot and each wall in the target construction space can be focused on, thereby improving the accuracy of adjusting the position and / or posture of the working robot.

[0060] In an embodiment of the present application, multiple distance detection devices are respectively arranged on each side of the working robot, and the posture of the working robot is adjusted according to multiple target distance parameters, including: determining a second difference between two adjacent target distance parameters among the multiple target distance parameters, wherein the two adjacent target distance parameters are detected by a distance detection device arranged on the same side; when the second difference is greater than a preset target distance parameter difference, controlling the working robot to rotate in a clockwise direction until the second difference is less than a preset target distance parameter difference error; when the second difference is less than the preset target distance parameter difference, controlling the working robot to rotate in a counterclockwise direction until the second difference is less than the preset target distance parameter difference error.

[0061] The processor can adjust the posture of the working robot according to the multiple target distance parameters. Specifically, each side is provided with two or more distance detection devices. Thus, based on the installation position of the distance detection device, the processor can determine two adjacent target distance parameters among the multiple target distance parameters. Specifically, it is to determine the two target distance parameters d detected by the distance detection device arranged on the same side. i and d i+1 is the distance parameter of two adjacent target. Then, the processor can further determine the second difference between the two adjacent target distance parameters. If the second difference is greater than the preset target distance parameter difference, the operating robot is controlled to rotate in a clockwise direction. If the second difference is less than the preset target distance parameter difference, the operating robot is controlled to rotate in a counterclockwise direction. During the rotation process, the processor can update the second difference according to the initial distance parameter detected in real time, and control the operating robot to stop rotating when the second difference is less than the preset target distance parameter difference error. Both the preset target distance parameter difference and the preset target distance parameter difference error can be determined according to the actual control accuracy requirements. In addition, it should be noted that the rotation direction of the operating robot is not limited to the aforementioned direction, and can be adjusted according to the installation position of the distance detection device, the difference between the subtrahend and the minuend between the two adjacent target distance parameters. In this way, the posture adjustment of the operating robot can be completed, so that the operating robot remains parallel to the wall, and the efficiency of the subsequent control of the operating robot for ground spraying operations is improved.

[0062] In an embodiment of the present application, multiple distance detection devices are respectively arranged on each side of the working robot, and the position of the working robot is adjusted according to multiple target distance parameters, including: obtaining a first distance parameter detected by a distance detection device arranged on the first side and a second distance parameter detected by a distance detection device arranged on the second side, wherein the first side and the second side are sides of the working robot that are relatively arranged and parallel to each other, and the multiple target distance parameters include the first distance parameter and the second distance parameter; when the first distance parameter is greater than the second distance parameter, the working robot is controlled to move in the direction of the side where the distance detection device corresponding to the first distance parameter is located.

[0063] Because before adjusting the position and / or posture of the working robot, it is necessary to filter the multiple initial distance parameters collected by the multiple distance detection devices. Then, in the case where some of the initial distance parameters (i.e., the initial distance parameters detected by the distance detection device on the target side) have been removed from the multiple initial distance parameters, the processor cannot adjust the position of the working robot only based on the initial distance parameters detected by the distance detection device on the side opposite to the target side and parallel to each other. Therefore, in the case where the first distance parameter detected by the distance detection device on the first side and the second distance parameter detected by the distance detection device on the second side are both included in the multiple target distance parameters, the processor can determine the larger value of the first distance parameter and the second distance parameter. If the first distance parameter is greater than the second distance parameter, the working robot can be controlled to move in the direction of the side where the distance detection device corresponding to the first distance parameter is located, until the third difference between the first distance parameter and the second distance parameter is less than the preset position adjustment threshold. Among them, the first side and the second side refer to the sides opposite to each other and parallel to each other on the working robot, and the preset position adjustment threshold can be adjusted according to the actual control accuracy requirements.

[0064] Alternatively, the first distance parameter average value may be determined based on the first distance parameter, and the second distance parameter average value may be determined based on the second distance parameter, and referring to the aforementioned steps, when the first distance parameter average value is greater than the second distance parameter average value, the working robot is controlled to move in the direction of the side corresponding to the first distance parameter average value.

[0065] In this way, the position of the working robot can be adjusted so that the working robot moves to the middle position of two parallel walls, thereby improving the imaging effect of the point cloud acquisition device and facilitating the point cloud acquisition device to collect the initial point cloud of the target construction space.

[0066] Figures 5(a), 5(b) and 5(c) schematically illustrate a schematic diagram of a process of adjusting the position and posture of a working robot according to a specific embodiment of the present application. Wherein, Figure 5(a) is a schematic diagram of the position and posture of the working robot before adjustment. Figure 5(b) is a schematic diagram of the position and posture of the working robot during the adjustment process. Figure 5(c) is a schematic diagram of the position and posture of the working robot after adjustment. As shown in Figures 5(a), 5(b) and 5(c), in a specific embodiment of the present application, the position and posture of the working robot can be adjusted in accordance with the aforementioned method of controlling the working robot to adjust the position and posture, so that the working robot can accurately move to the middle position of the two walls. In this way, by adjusting the position and posture of the working robot, it is beneficial for the subsequent point cloud acquisition device to collect the initial point cloud of the target construction space.

[0067] In an embodiment of the present application, the control method also includes: respectively obtaining the vertical distance between the working robot and each wall; determining whether any vertical distance is less than a preset anti-collision distance; and controlling the working robot to stop moving when any vertical distance is less than the preset anti-collision distance.

[0068] Specifically, according to the initial point cloud collected by the point cloud acquisition device, or by setting a vertical distance detection device (such as an ultrasonic radar) on the working robot, the processor can respectively obtain the vertical distance between the working robot and each wall. Subsequently, the processor can determine whether any vertical distance is less than the preset anti-collision distance, and control the working robot to stop moving when any vertical distance is less than the preset anti-collision distance. Among them, the preset anti-collision distance can be set according to actual conditions. In this way, the possibility of the working robot colliding with the wall when performing ground spraying operations can be reduced.

[0069] Figure 6 The structure block diagram of a computer device according to an embodiment of the present application is schematically shown. Figure 6 As shown, an embodiment of the present application further provides a computer device, the computer device includes a memory 610 and a processor 620, the memory 610 stores a computer program, and the processor 620 implements the above-mentioned control method for the working robot when executing the computer program.

[0070] Specifically, in an embodiment of the present application, the processor 620 can be configured to: obtain an initial point cloud of the target construction space collected by a point cloud acquisition device; based on the initial point cloud, identify the concave corner points of each wall in the target construction space; obtain the concave corner point distance corresponding to each concave corner point, the concave corner point distance corresponding to the concave corner point is the distance between the concave corner point and the working robot; determine the distance difference between the concave corner point distances corresponding to two concave corner points located on at least any one side; and control the movement of the working robot according to the distance difference.

[0071] In one embodiment, the processor 620 is further configured to: obtain the first direction coordinate value of each point cloud data in the initial point cloud; obtain the point cloud identifier corresponding to each point cloud data; determine the adjacent point cloud data in the initial point cloud according to the point cloud identifier corresponding to each point cloud data; determine the coordinate value difference between the first direction coordinate values ​​corresponding to the adjacent point cloud data; determine the concave corner point according to the coordinate value difference, the concave corner point being the point corresponding to the point cloud data whose point cloud identifier is the target point cloud identifier in the adjacent point cloud data whose corresponding coordinate value difference is greater than the preset coordinate value difference.

[0072] In one embodiment, the processor 620 is further configured to: cluster the point cloud data in the initial point cloud according to the first direction coordinate value to obtain multiple point cloud clustering clusters; determine the first direction coordinate value average of the first direction coordinate value corresponding to the point cloud data in each point cloud clustering cluster; merge and cluster the multiple point cloud clustering clusters according to the first direction coordinate value average to obtain wall point clouds corresponding to each wall; obtain the point cloud identifier corresponding to each point cloud data in each wall point cloud.

[0073] In one embodiment, the processor 620 is further configured to: determine adjacent point cloud clustering clusters among multiple point cloud clustering clusters based on clustering cluster identifiers; determine a first difference between the average values ​​of first direction coordinate values ​​corresponding to adjacent point cloud clustering clusters; merge and cluster multiple point cloud clustering clusters based on the first difference to obtain each wall point cloud, and each wall point cloud is obtained by merging and clustering adjacent point cloud clustering clusters whose corresponding first difference is less than a preset average value difference.

[0074] In one embodiment, the processor 620 is further configured to: obtain multiple target distance parameters based on multiple distance detection devices; and adjust the position and / or posture of the working robot according to the multiple target distance parameters.

[0075] In one embodiment, the processor 620 is further configured to: determine a second difference between two adjacent target distance parameters among a plurality of target distance parameters, wherein the two adjacent target distance parameters are detected by a distance detection device disposed on the same side; when the second difference is greater than a preset target distance parameter difference, control the working robot to rotate in a clockwise direction until the second difference is less than a preset target distance parameter difference error; when the second difference is less than a preset target distance parameter difference, control the working robot to rotate in a counterclockwise direction until the second difference is less than a preset target distance parameter difference error.

[0076] In one embodiment, the processor 620 is further configured to: obtain a first distance parameter detected by a distance detection device arranged on the first side and a second distance parameter detected by a distance detection device arranged on the second side, wherein the first side and the second side are sides arranged opposite to each other and parallel to each other on the working robot, and the multiple target distance parameters include the first distance parameter and the second distance parameter; when the first distance parameter is greater than the second distance parameter, the working robot is controlled to move in the direction of the side where the distance detection device corresponding to the first distance parameter is located.

[0077] In one embodiment, the processor 620 is further configured to: obtain multiple initial distance parameters detected by multiple distance detection devices; when there is an out-of-range distance parameter among the multiple initial distance parameters, determine the target side where the distance detection device corresponding to the out-of-range distance parameter is located, wherein the out-of-range distance parameter is an initial distance parameter greater than a preset distance parameter threshold; remove the initial distance parameters detected by the distance detection device on the target side among the multiple initial distance parameters to obtain multiple target distance parameters.

[0078] In one embodiment, the processor 620 is further configured to: obtain the vertical distance between the working robot and each wall respectively; determine whether any vertical distance is less than a preset anti-collision distance; if any vertical distance is less than the preset anti-collision distance, control the working robot to stop moving.

[0079] The above technical solution obtains the initial point cloud of the target construction space collected by the point cloud acquisition device, and then identifies the concave corner points of each wall in the target construction space based on the initial point cloud, then obtains the concave corner point distance between each concave corner point and the operating robot, and then determines the distance difference between the concave corner point distances corresponding to two concave corner points located on at least any one side, and finally controls the movement of the operating robot according to the distance difference. This application determines the concave corner point distance between each concave corner point and the operating robot after identifying the concave corner points of each wall in the target construction space, thereby controlling the movement of the operating robot according to the concave corner point distance to ensure the operating accuracy of the operating robot. When this technical solution is applied to a spraying operating robot, it can realize automatic or auxiliary drawing of square lines and can improve the drawing accuracy of square lines.

[0080] An embodiment of the present application also provides a working robot, comprising: a robot body; a point cloud acquisition device; and a processor.

[0081] An embodiment of the present application also provides a machine-readable storage medium, on which instructions are stored, and the instructions are used to enable a machine to execute the above-mentioned control method for a working robot.

[0082] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the present application may adopt the form of a computer program product implemented in one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that include computer-usable program code.

[0083] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0084] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0085] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0086] In a typical configuration, a computing device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0087] The memory may include non-permanent memory in a computer-readable medium, random access memory (RAM) and / or non-volatile memory in the form of read-only memory (ROM) or flash RAM. The memory is an example of a computer-readable medium.

[0088] Computer readable media include permanent and non-permanent, removable and non-removable media that can be implemented by any method or technology to store information. Information can be computer readable instructions, data structures, program modules or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, compact disk read-only memory (CD-ROM), digital versatile disk (DVD) or other optical storage, magnetic cassettes, magnetic tape disk storage or other magnetic storage devices or any other non-transmission media that can be used to store information that can be accessed by a computing device. As defined herein, computer readable media does not include temporary computer readable media (transitory media), such as modulated data signals and carrier waves.

[0089] It should also be noted that the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, commodity or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, commodity or device. In the absence of more restrictions, the elements defined by the sentence "comprises a ..." do not exclude the existence of other identical elements in the process, method, commodity or device including the elements.

[0090] The above are only embodiments of the present application and are not intended to limit the present application. For those skilled in the art, the present application may have various changes and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included within the scope of the claims of the present application.

Claims

1. A control method for a working robot, characterized in that: The working robot includes a point cloud acquisition device, the working robot is located in a target construction space, and the control method includes: Acquire the initial point cloud of the target construction space collected by the point cloud collection device; Based on the initial point cloud, identifying the concave corner points of each wall in the target construction space; Obtaining the concave corner point distance corresponding to each concave corner point, where the concave corner point distance corresponding to the concave corner point is the distance between the concave corner point and the working robot; Determine the distance difference between the concave corner point distances respectively corresponding to two concave corner points located on at least any one side; The working robot is controlled to move according to the distance difference.

2. The control method according to claim 1, characterized in that: The step of identifying the concave corner points of each wall surface in the target construction space based on the initial point cloud includes: Acquire a first direction coordinate value of each point cloud data in the initial point cloud in the first direction; Obtaining a point cloud identifier corresponding to each of the point cloud data; Determining adjacent point cloud data in the initial point cloud according to the point cloud identifier corresponding to each point cloud data; Determine a coordinate value difference between the first direction coordinate values ​​corresponding to the adjacent point cloud data; The concave corner point is determined according to the coordinate value difference, and the concave corner point is a point corresponding to the point cloud data whose point cloud identifier is the target point cloud identifier in the adjacent point cloud data whose corresponding coordinate value difference is greater than the preset coordinate value difference.

3. The control method according to claim 2, characterized in that: The obtaining of the point cloud identifier corresponding to each of the point cloud data comprises: Clustering the point cloud data in the initial point cloud according to the first direction coordinate values ​​to obtain a plurality of point cloud clusters; Determine an average value of first direction coordinate values ​​of the first direction coordinate values ​​corresponding to the point cloud data in each of the point cloud clusters; According to the average value of the first direction coordinate value, the plurality of point cloud clusters are merged and clustered to obtain wall point clouds corresponding to the walls; Obtain a point cloud identifier corresponding to each point cloud data in each of the wall point clouds.

4. The control method according to claim 3, characterized in that: The plurality of point cloud clusters all have corresponding cluster identifiers, and the cluster identifiers are determined according to the amount of point cloud data in the point cloud clusters; the plurality of point cloud clusters are merged and clustered according to the average value of the first direction coordinate values ​​to obtain wall point clouds corresponding to each of the wall surfaces, including: Determining adjacent point cloud clusters among the plurality of point cloud clusters according to the cluster identifiers; Determine a first difference between average values ​​of the first direction coordinate values ​​corresponding to the adjacent point cloud clusters; The plurality of point cloud clusters are merged and clustered according to the first difference to obtain each of the wall point clouds, wherein each of the wall point clouds is obtained by merging and clustering adjacent point cloud clusters whose corresponding first difference is less than a preset average value difference.

5. The control method according to claim 1, characterized in that: The working robot further includes a plurality of distance detection devices, and the control method further includes: Acquire multiple target distance parameters obtained based on the multiple distance detection devices; The position and / or posture of the working robot is adjusted according to the multiple target distance parameters.

6. The control method according to claim 5, characterized in that: The multiple distance detection devices are respectively arranged on each side of the working robot, and the posture of the working robot is adjusted according to the multiple target distance parameters, including: Determine a second difference between two adjacent target distance parameters among the plurality of target distance parameters, wherein the two adjacent target distance parameters are detected by a distance detection device disposed on the same side; When the second difference is greater than the preset target distance parameter difference, the working robot is controlled to rotate in a clockwise direction until the second difference is less than the preset target distance parameter difference error; When the second difference is smaller than the preset target distance parameter difference, the working robot is controlled to rotate in a counterclockwise direction until the second difference is smaller than the preset target distance parameter difference error.

7. The control method according to claim 5, characterized in that: The plurality of distance detection devices are respectively arranged on each side of the working robot, and the position of the working robot is adjusted according to the plurality of target distance parameters, including: Acquire a first distance parameter detected by a distance detection device disposed on a first side surface and a second distance parameter detected by a distance detection device disposed on a second side surface, wherein the first side surface and the second side surface are side surfaces disposed opposite to and parallel to each other on the working robot, and the plurality of target distance parameters include the first distance parameter and the second distance parameter; When the first distance parameter is greater than the second distance parameter, the working robot is controlled to move in the direction of the side where the distance detection device corresponding to the first distance parameter is located.

8. The control method according to claim 5, characterized in that: The acquiring of a plurality of target distance parameters obtained based on the plurality of distance detection devices comprises: Acquiring a plurality of initial distance parameters detected by the plurality of distance detection devices; In the case where there is an out-of-range distance parameter among the multiple initial distance parameters, determining the target side where the distance detection device corresponding to the out-of-range distance parameter is located, wherein the out-of-range distance parameter is an initial distance parameter greater than a preset distance parameter threshold; The initial distance parameters detected by the distance detection device on the side of the target are removed from the multiple initial distance parameters to obtain multiple target distance parameters.

9. The control method according to claim 1, characterized in that: The control method further comprises: Respectively obtaining the vertical distance between the working robot and each of the walls; Determining whether any of the vertical distances is less than a preset anti-collision distance; When the arbitrary vertical distance is smaller than the preset anti-collision distance, the working robot is controlled to stop moving.

10. A processor, characterized in that: The method is configured to execute the control method for a working robot according to any one of claims 1 to 9.

11. A working robot, characterized in that: include: Robot body; Point cloud acquisition device; as well as A processor according to claim 10.

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