Multi-dimensional data fusion sweeping robot motion control system and method

Abstract

The invention relates to the technical field of sweeping robots, in particular to a multi-dimensional data fusion sweeping robot motion control system and method. The method comprises the following steps: acquiring environment perception information, analyzing the environment perception information, and determining a temporary obstacle information set and a normal obstacle information set; acquiring a robot parameter set, and determining a cleaning dead zone of the sweeping robot under the obstacle avoidance condition based on the robot parameter set according to the temporary obstacle information set and the normal obstacle information set; based on the robot parameter set, the environment perception information and the temporary obstacle information set, analyzing a cleaning dead zone, and determining a dead zone elimination strategy; and according to the dead zone elimination strategy, the sweeping robot is controlled to perform corresponding sweeping motion, and a temporary obstacle target area is determined and output. The sweeping effect of the sweeping robot under the dual influence of the ground obstacle object characteristics and the space environment characteristics in the low and narrow space can be guaranteed.

Description

Technical Field

[0001] The present application relates to the technical field of sweeping robots, and in particular to a sweeping robot motion control system and method with multi-dimensional data fusion. Background Art

[0002] In recent years, sweeping robots, as an important part of smart homes, have received widespread attention. With the development of technology, the navigation and obstacle avoidance capabilities of sweeping robots have been continuously improved. Existing high-end sweeping robots combine lidar navigation with visual navigation to improve their obstacle avoidance and scene adaptability.

[0003] However, when the sweeping robot is located in a low and narrow space, under the dual influence of the characteristics of ground obstacles and the characteristics of the spatial environment, the existing technology still cannot guarantee the cleaning effect of the sweeping robot when avoiding obstacles, resulting in the continuous retention of obstacles and dirt in the low and narrow space. Summary of the invention

[0004] The present application provides a sweeping robot motion control system and method with multi-dimensional data fusion to solve the above-mentioned technical problems.

[0005] In a first aspect, the present application provides a sweeping robot motion control method with multi-dimensional data fusion, the method comprising: Acquire environmental perception information, analyze the environmental perception information, and determine a temporary obstacle information set and a normal obstacle information set; acquire a robot parameter set, and determine a cleaning dead zone of the sweeping robot in an obstacle avoidance situation based on the robot parameter set, the temporary obstacle information set and the normal obstacle information set; analyze the cleaning dead zone based on the robot parameter set, the environmental perception information and the temporary obstacle information set, and determine a dead zone elimination strategy; according to the dead zone elimination strategy, control the sweeping robot to perform a corresponding cleaning movement, and determine and output a temporary obstacle target area.

[0006] Through this solution, environmental perception information is analyzed to determine the temporary obstacle information set and normal obstacle information set that reflect the characteristics of temporary obstacles and normal obstacles in the area to be cleaned. On this basis, combined with the robot parameter set, the cleaning dead zone faced by the sweeping robot under the dual influence of temporary obstacles and normal obstacles is determined. For the cleaning dead zone, a dead zone elimination strategy for eliminating the cleaning dead zone is formulated. According to the dead zone elimination strategy, the sweeping robot is controlled to perform corresponding cleaning movements, and the temporary obstacle target area is determined and output. This ensures the cleaning effect of the sweeping robot under the dual influence of the characteristics of ground obstacles and the characteristics of the spatial environment when the sweeping robot is in a low and narrow space, prevents temporary obstacles and dirt from continuing to stay in the low and narrow space, and significantly improves the adaptability and cleaning coverage of the sweeping robot.

[0007] Optionally, the environmental perception information includes map data, real-time robot position data, real-time point cloud data, and real-time visual data, and the analyzing the environmental perception information to determine the temporary obstacle information set and the normal obstacle information set includes: Based on the map data and the real-time position data of the robot, the real-time visual data is analyzed to determine the edge features of normal obstacles; based on the edge features of the normal obstacles, the real-time point cloud data is analyzed to determine the coordinates of the center point of the normal obstacles and the interference radius of the normal obstacles, and the normal obstacle information set is determined according to the edge features of the normal obstacles and the interference radius of the normal obstacles; the real-time point cloud data and the real-time visual data are analyzed to determine the key analysis area of ​​temporary obstacles; according to the key analysis area of ​​temporary obstacles, the laser radar scanning strategy is adjusted, and according to the adjusted laser radar scanning strategy, the temporary obstacle point cloud information is determined; according to the temporary obstacle point cloud information and the real-time visual data, the temporary obstacle type, the coordinates of the center point of the temporary obstacle, the interference radius of the temporary obstacle and the edge features of the temporary obstacle are determined, so as to determine the temporary obstacle information set.

[0008] Through this solution, based on map data and real-time robot position data, real-time visual data is analyzed, and on this basis, combined with real-time point cloud data, the coordinates of the center point of normal obstacles and the interference radius of normal obstacles are obtained, so as to construct a normal obstacle information set, and provide a clear absolute boundary for the subsequent analysis process of cleaning dead zones. By analyzing real-time point cloud data and real-time visual data, the key analysis area of ​​temporary obstacles is determined, and through the corresponding lidar scanning strategy, the point cloud information of temporary obstacles is analyzed to determine the type of temporary obstacles, the coordinates of the center point of temporary obstacles, the interference radius of temporary obstacles and the edge features of temporary obstacles, so as to construct a temporary obstacle information set, realize accurate identification of temporary obstacles, and provide a clear relative boundary for the subsequent analysis process of cleaning dead zones.

[0009] Optionally, the analyzing the real-time point cloud data and the real-time visual data to determine the key analysis area of ​​the temporary obstacle includes: analyzing the real-time visual data to determine the local color features and the local edge features of the temporary obstacle; analyzing the real-time point cloud data to determine the local geometric features of the temporary obstacle, and performing feature fusion on the local color features of the temporary obstacle, the local edge features of the temporary obstacle and the local geometric features of the temporary obstacle to determine the comprehensive features of the temporary obstacle; clustering the comprehensive features of the temporary obstacle according to a preset clustering algorithm to determine the fuzzy area of ​​the temporary obstacle; analyzing the fuzzy area of ​​the temporary obstacle to determine the coordinates of the center point of the fuzzy area, and determining the key analysis area of ​​the temporary obstacle according to the preset scanning radius and the coordinates of the center point of the fuzzy area, which is specifically the following formula: ; in, Focus analysis area for the temporary obstacle, is the coordinate of the scanning point to be selected, is the horizontal coordinate of the center point of the fuzzy area, is the ordinate of the center point of the fuzzy area, is the preset scanning radius.

[0010] Through this solution, real-time visual data is analyzed to obtain local color features and local edge features of temporary obstacles. At the same time, local geometric features of temporary obstacles are obtained by analyzing real-time point cloud data. The preset clustering algorithm is used to cluster the comprehensive features of temporary obstacles after the fusion of the above features to determine the fuzzy area of ​​temporary obstacles. On this basis, combined with the preset scanning radius and the coordinates of the center point of the fuzzy area, the key analysis area of ​​temporary obstacles is scientifically quantified through clear mathematical formulas to improve the accuracy of temporary obstacle recognition. At the same time, scientific data reference is provided for the targeted adjustment of lidar scanning strategies.

[0011] Optionally, the robot parameter set includes a working width and a safe collision distance, and the analyzing the cleaning dead zone based on the robot parameter set, the environmental perception information and the temporary obstacle information set, and determining the dead zone elimination strategy and the temporary obstacle target area includes: According to the normal obstacle edge features and the temporary obstacle edge features, the area to be analyzed and the obstacle area are determined; based on the preset analysis point division rules, the area to be analyzed is divided into analysis points to determine the analysis point coordinate set; based on the working width and the safe collision distance, according to the normal obstacle edge features, the temporary obstacle edge features and the analysis point coordinate set, the obstacle radiation area is determined; according to the obstacle area and the obstacle radiation area, the cleaning dead zone is determined.

[0012] Through this scheme, the area to be analyzed and the obstacle area are divided according to the edge characteristics of normal obstacles and temporary obstacles, and the analysis points of the area to be analyzed are divided to determine the coordinate set of the analysis points. On this basis, combined with the corresponding working width and safe collision distance of the sweeping robot, the obstacle radiation area is analyzed and obtained. The obstacle area and the obstacle radiation area are comprehensively analyzed to determine the cleaning dead zone, thereby improving the analysis efficiency and accuracy of the cleaning dead zone, thereby improving the scientificity and comprehensiveness of the subsequent motion strategy analysis process for the cleaning dead zone.

[0013] Optionally, the obstacle radiation area is determined based on the working width and the safe collision distance according to the normal obstacle edge features, the temporary obstacle edge features and the analysis point coordinate set, specifically by the following formula: ; in, is the barrier radiation area, is the coordinate of the current analysis point, For the The edge of a temporary obstacle, is the coordinate distance function, For the The edge of a normal obstacle, is the working width, is the safe collision distance; the cleaning dead zone is determined according to the obstacle area and the obstacle radiation area, specifically the following formula: in, To clean up the dead zone, is the barrier radiation area, is the obstacle area.

[0014] Through this scheme, based on the working width and safe collision distance, according to the normal obstacle edge characteristics, temporary obstacle edge characteristics and analysis point coordinate set, through clear mathematical processing means, all analysis points belonging to the obstacle radiation area are automatically screened, and then the obstacle radiation area is clarified. On this basis, through mathematical processing means, the union between the obstacle radiation area and the obstacle area is used as the cleaning dead zone to accurately describe the scope of the cleaning dead zone, thereby improving the accuracy and calculation efficiency of the cleaning dead zone determination process.

[0015] Optionally, the robot parameter set also includes a robot radius, and the cleaning dead zone is analyzed based on the robot parameter set and the temporary obstacle information set to determine a dead zone elimination strategy, including: based on the temporary obstacle type, analyzing the edge features of the temporary obstacle to determine the coordinates of the movable endpoint of the temporary obstacle; determining the robot travel path according to the real-time position data of the robot and the coordinates of the movable endpoint of the temporary obstacle; determining the movement offset and movement direction according to the robot travel path, and determining the coordinates of the active endpoint after the movement; determining the safety area based on the robot radius and the normal obstacle interference radius and the coordinates of the temporary obstacle center point and the normal obstacle edge features; integrating the robot travel path, the coordinates of the active endpoint after the movement and the safety area to determine the dead zone elimination strategy.

[0016] Through this scheme, the coordinates of the movable endpoints of temporary obstacles are determined according to the types of temporary obstacles and the edge features of temporary obstacles, and the robot's travel path is planned in combination with the real-time position data of the robot, taking full account of the different movable conditions of temporary obstacles. On this basis, the movement offset and movement direction are determined according to the robot's travel path, and the coordinates of the active endpoints after the movement are obtained. At the same time, the safety area is delineated based on the robot radius and the normal obstacle interference radius, and the dead zone elimination strategy is determined by integrating the robot's travel path, the coordinates of the active endpoints after the movement and the safety area. The dead zone elimination strategy can avoid the collision between the sweeping robot and the normal obstacles while eliminating the cleaning dead zone through the targeted movement of temporary obstacles, thereby significantly improving the cleaning effect and adaptability of the sweeping robot.

[0017] Optionally, the integration of the robot's travel path, the coordinates of the active endpoint after movement, and the safety area to determine the dead zone elimination strategy is specifically the following formula: ; in, is the robot’s travel path, is the real-time position data of the robot, For the The coordinates of the temporary obstacle center point of the normal obstacle, is the robot radius, For the The normal obstacle interference radius of the normal obstacle, For the The normal obstacle edge features of the normal obstacles, is the normal obstacle information set, is the coordinate of the active endpoint after the movement, is the temporary obstacle interference radius, is the safe area.

[0018] Through this solution, the robot's travel path, the coordinates of the active endpoint after movement, and the safe area are integrated, the limiting conditions of each stage in the process of the sweeping robot moving temporary obstacles are clarified, and a dead zone elimination strategy is constructed, so that the sweeping robot can eliminate the current cleaning dead zone while avoiding collisions between the sweeping robot and normal obstacles, and can effectively avoid the emergence of new cleaning dead zones.

[0019] Optionally, the integration of the robot's travel path, the coordinates of the active endpoint after movement, and the safety area is specifically the following formula: ; in, is the robot’s travel path, is the real-time position data of the robot, are the coordinates of the movable endpoints of the temporary obstacle, For the The coordinates of the temporary obstacle center point of the normal obstacle, To make progress for the unit, is the preset maximum step size, is the robot radius, For the The normal obstacle interference radius of the normal obstacle, For the The normal obstacle edge features of the normal obstacles, is the coordinate of the active endpoint after the movement, is the safe area, is the shift offset, is the moving direction.

[0020] Through this scheme, mathematical analysis methods are used to describe the planning process of the robot's travel path, the determination process of the active endpoint coordinates after movement, and the demarcation process of the safe area, respectively, to clarify the mathematical relationship between the robot's travel path, the coordinates of the active endpoint after movement, and the safe area and their respective influencing factors, to improve the scientificity, accuracy and comprehensiveness of the robot's travel path, the coordinates of the active endpoint after movement, and the safe area determination process, thereby improving the effectiveness of the dead zone elimination strategy formulated based on this.

[0021] Optionally, according to the dead zone elimination strategy, the sweeping robot is controlled to perform corresponding cleaning movements, and a temporary obstacle target area is determined and output, including: according to the dead zone elimination strategy, the sweeping robot is controlled to move along the robot's travel path to move the temporary obstacle; when the sweeping robot moves the temporary obstacle, the cleaning structure of the sweeping robot is controlled to stop working, and according to the normal obstacle edge features, the area outside the normal obstacle coverage range closest to the temporary obstacle is determined as a temporary obstacle target area, and the sweeping robot is controlled to move the temporary obstacle into the temporary obstacle target area; after the sweeping robot moves the temporary obstacle into the temporary obstacle target area, the sweeping robot is controlled to clean the cleaning dead zone, and record and output the temporary obstacle target area.

[0022] Through this solution, according to the dead zone elimination strategy, the sweeping robot is controlled to move the temporary obstacle, and in this process, the cleaning structure of the sweeping robot is controlled to stop working to avoid the sweeping robot being affected by the temporary obstacle during the movement and causing malfunction. At the same time, the sweeping robot is controlled to move the temporary obstacle to the temporary obstacle target area, and after the sweeping robot completes the cleaning work of the original cleaning dead zone, the temporary obstacle target area is provided to the user, so that the user can know the location of the temporary obstacle in time, so that the user can quickly deal with the temporary obstacle, and effectively avoid the temporary obstacle from continuing to stay in the current area.

[0023] In a second aspect, the present application provides a multi-dimensional data fusion sweeping robot motion control system, the system comprising: An obstacle analysis module is used to obtain environmental perception information, analyze the environmental perception information, and determine a temporary obstacle information set and a normal obstacle information set; an area analysis module is used to obtain a robot parameter set, and based on the robot parameter set, determine the cleaning dead zone of the sweeping robot in the obstacle avoidance situation according to the temporary obstacle information set and the normal obstacle information set; a motion analysis module is used to analyze the cleaning dead zone based on the robot parameter set, the environmental perception information and the temporary obstacle information set, and determine a dead zone elimination strategy; a motion control module is used to control the sweeping robot to perform corresponding cleaning motion according to the dead zone elimination strategy, and determine and output a temporary obstacle target area. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, a brief introduction will be given below to the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative labor.

[0025] Figure 1 A schematic diagram of an application scenario provided for an embodiment of the present application; Figure 2 A flowchart of a sweeping robot motion control method with multi-dimensional data fusion provided in one embodiment of the present application; Figure 3 A schematic diagram of the structure of a sweeping robot motion control system with multi-dimensional data fusion provided in one embodiment of the present application. DETAILED DESCRIPTION

[0026] 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. Obviously, the described embodiments are part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0027] In addition, the term "and / or" in this article is only a description of the association relationship of associated objects, indicating that there can be three relationships. For example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone. In addition, the character " / " in this article, unless otherwise specified, generally means that the associated objects before and after are in an "or" relationship.

[0028] The embodiments of the present application are further described in detail below in conjunction with the drawings in the specification.

[0029] However, when the sweeping robot is located in a low and narrow space, under the dual influence of the characteristics of ground obstacles and the characteristics of the spatial environment, the existing technology still cannot guarantee the cleaning effect of the sweeping robot when avoiding obstacles, resulting in the continuous retention of obstacles and dirt in the low and narrow space.

[0030] Based on this, the present application provides a sweeping robot motion control system and method with multi-dimensional data fusion. Analyze environmental perception information, determine temporary obstacle information sets and normal obstacle information sets that reflect the characteristics of temporary obstacles and normal obstacles in the area to be cleaned, and on this basis, combine the robot parameter set to determine the cleaning dead zone faced by the sweeping robot under the dual influence of temporary obstacles and normal obstacles, formulate a dead zone elimination strategy for eliminating the cleaning dead zone, and control the sweeping robot to perform corresponding cleaning movements according to the dead zone elimination strategy, determine and output the temporary obstacle target area, ensure the sweeping robot is in a low and narrow space, and the cleaning effect under the dual influence of the characteristics of ground obstacles and space environment characteristics, prevent temporary obstacles and dirt from being continuously retained in the low and narrow space, and significantly improve the adaptability and cleaning coverage of the sweeping robot.

[0031] Figure 1 A schematic diagram of an application scenario provided by the present application. During the operation of the sweeping robot, the method provided by the present application is applied to ensure the sweeping effect of the sweeping robot in a low and narrow space under the dual influence of the characteristics of ground obstacles and the characteristics of the space environment.

[0032] Specifically, the method of the present application is applied to any server, which can be mounted inside a sweeping robot. The server obtains and analyzes the environmental perception information provided by the sweeping robot, determines the temporary obstacle information set and the normal obstacle information set reflecting the characteristics of temporary obstacles and normal obstacles in the area to be cleaned, and on this basis, combined with the robot parameter set, determines the cleaning dead zone faced by the sweeping robot under the dual influence of temporary obstacles and normal obstacles, formulates a dead zone elimination strategy for eliminating the cleaning dead zone, and controls the sweeping robot to perform corresponding cleaning movements according to the dead zone elimination strategy, determines and outputs the temporary obstacle target area, ensures the sweeping robot is in a low and narrow space, and is subject to the dual influence of the characteristics of ground obstacles and the characteristics of the space environment. The cleaning effect is prevented, temporary obstacles and dirt are prevented from being continuously retained in the low and narrow space, and the adaptability and cleaning coverage of the sweeping robot are significantly improved. The specific implementation method can refer to the following embodiments.

[0033] Figure 2 This is a flow chart of a method for controlling the motion of a sweeping robot using multi-dimensional data fusion provided by an embodiment of the present application. The method of this embodiment can be applied to the server in the above scenario. Figure 2 As shown, the method includes: S201. Acquire environmental perception information, analyze the environmental perception information, and determine a temporary obstacle information set and a normal obstacle information set.

[0034] Environmental perception information may be information about the home environment perceived by the sweeping robot, and the environmental perception information may be obtained through the cooperation of the built-in laser radar sensor and visual sensor of the sweeping robot. A temporary obstacle information set may be an information set corresponding to the features of temporary obstacles existing in the current area to be cleaned by the sweeping robot. A temporary obstacle may be an obstacle that temporarily appears in the area and can be moved, such as a small toy or data cable. A normal obstacle information set may be an information set corresponding to the features of normal obstacles existing in the current area to be cleaned by the sweeping robot. A normal obstacle information set may be an obstacle that normally exists in the area and cannot be moved, such as furniture or walls.

[0035] Specifically, when a sweeping robot is cleaning a low and narrow area, such as the bottom of a sofa, if there are temporary obstacles on the ground, the accuracy of the sweeping robot's obstacle recognition is easily affected by both the surface characteristics of the object and environmental factors. The surface characteristics of the object mainly affect the lidar's recognition of obstacles. Obstacles with weak surface reflection characteristics, such as data cables with rubber insulating materials, have weak echo signals on their surfaces for laser pulses, making it difficult for the lidar to fully and accurately recognize them. Environmental factors mainly affect the visual sensor's recognition of obstacles. The light conditions in low and narrow areas are poor, and the sweeping robot's own light source range is limited and easily affected by other objects with high light reflectivity in the surrounding area. Therefore, the recognition of obstacles in low and narrow areas requires complementary scheduling of the lidar sensor and the visual sensor to effectively analyze environmental perception information and correctly identify temporary obstacles and normal obstacles.

[0036] After identifying temporary obstacles and normal obstacles, existing sweeping robots will avoid them through their built-in obstacle avoidance algorithms. However, this method is likely to cause inadequate cleaning in low and narrow areas, because in low and narrow areas, temporary obstacles are likely to form a cleaning dead zone together with normal obstacles. The cleaning dead zone does not require the temporary obstacles and normal obstacles to form a closed area, but only requires the interval between the temporary obstacles and the normal obstacles to be smaller than the width through which the sweeping robot can pass. Especially in low and narrow areas, since the space available for the sweeping robot to adjust its movement is relatively small, Small, temporary obstacles of small size can form a large cleaning dead zone with the surrounding normal obstacles, and low and narrow areas are usually easily ignored by users, which causes temporary obstacles to remain in the area for a long time, resulting in the dirt in the corresponding cleaning dead zone cannot be cleaned for a long time, which in turn has a negative impact on the user's home environment. Therefore, after identifying temporary obstacles and normal obstacles in low and narrow areas, the characteristics of temporary obstacles and normal obstacles reflected in the environmental perception information are extracted to form temporary obstacle information sets and normal obstacle information sets, which provide a data basis for the subsequent analysis of cleaning dead zones and the formulation of corresponding cleaning strategies.

[0037] S202: Obtain a robot parameter set, and determine a cleaning dead zone of the sweeping robot in an obstacle avoidance situation based on the robot parameter set, a temporary obstacle information set, and a normal obstacle information set.

[0038] The robot parameter set may be a set of device parameters corresponding to the sweeping robot, such as volume, radius, etc., and the robot parameter set may be provided by the sweeping robot. The cleaning dead zone may be an area formed by temporary obstacles and normal obstacles in a low and narrow area that is difficult to be directly cleaned by the sweeping robot.

[0039] Specifically, the concept of cleaning dead zone is not only related to the temporary obstacles and normal obstacles that directly constitute the cleaning dead zone, but also related to the specific parameters of the sweeping robot. For the same area composed of temporary obstacles and normal obstacles, the size and shape of the cleaning dead zone faced by sweeping robots of different volumes and passability will be different. It is necessary to conduct a comprehensive analysis of the temporary obstacle information set and the normal obstacle information set based on the robot parameter set through mathematical analysis methods, so as to quantify the cleaning dead zone that will be formed by the current sweeping robot taking obstacle avoidance measures under the dual influence of the current temporary obstacles and normal obstacles, so as to provide scientific data support for the subsequent analysis process of eliminating cleaning dead zones.

[0040] S203: Analyze the cleaning dead zone based on the robot parameter set, the environmental perception information and the temporary obstacle information set, and determine the dead zone elimination strategy.

[0041] The dead zone elimination strategy may be a control strategy for controlling the cleaning robot to perform corresponding movements with the purpose of eliminating the cleaning dead zone.

[0042] Specifically, after determining the cleaning dead zone currently faced by the sweeping robot, it is necessary to plan the subsequent motion trajectory of the sweeping robot to clear the cleaning dead zone. Since the position of normal obstacles cannot change, in order to allow the sweeping robot to enter the cleaning area for cleaning, the position of temporary obstacles must be changed. Through mathematical analysis, based on the robot parameter set, environmental perception information and temporary obstacle information set, the cleaning dead zone is analyzed, and the motion strategy of the sweeping robot to move temporary obstacles is planned, so that the temporary obstacles after the change of position can no longer form an inaccessible cleaning dead zone with the corresponding normal obstacles. At the same time, avoid the temporary obstacles after the move from forming a new cleaning dead zone with other normal obstacles, so as to eliminate the cleaning dead zone and improve the cleaning effect of the sweeping robot.

[0043] S204: According to the dead zone elimination strategy, the sweeping robot is controlled to perform corresponding cleaning movements, and a temporary obstacle target area is determined and output.

[0044] The temporary obstacle target area may be the final area to which the corresponding temporary obstacle needs to be moved after the sweeping robot completes the corresponding cleaning work.

[0045] Specifically, after determining the dead zone elimination strategy, the sweeping robot is controlled to move the temporary obstacles according to the corresponding travel route in the dead zone elimination strategy, and after eliminating the cleaning dead zone, the cleaning area that was originally inaccessible is cleaned. After the cleaning is completed, the temporary obstacle is further moved outside the current low and narrow area, and the final area where the temporary obstacle is located is marked as the temporary obstacle target area, and the area is provided to the user, so that the user can clear the temporary obstacle in time to avoid the temporary obstacle affecting the subsequent cleaning work of the sweeping robot. At the same time, it can also help the user find small items lost in the corner.

[0046] Through this solution, environmental perception information is analyzed to determine the temporary obstacle information set and normal obstacle information set that reflect the characteristics of temporary obstacles and normal obstacles in the area to be cleaned. On this basis, combined with the robot parameter set, the cleaning dead zone faced by the sweeping robot under the dual influence of temporary obstacles and normal obstacles is determined. For the cleaning dead zone, a dead zone elimination strategy for eliminating the cleaning dead zone is formulated. According to the dead zone elimination strategy, the sweeping robot is controlled to perform corresponding cleaning movements, and the temporary obstacle target area is determined and output. This ensures the cleaning effect of the sweeping robot under the dual influence of the characteristics of ground obstacles and the characteristics of the spatial environment when the sweeping robot is in a low and narrow space, prevents temporary obstacles and dirt from continuing to stay in the low and narrow space, and significantly improves the adaptability and cleaning coverage of the sweeping robot.

[0047] In some embodiments, based on map data and real-time position data of the robot, real-time visual data is analyzed to determine edge features of normal obstacles; based on the edge features of normal obstacles, real-time point cloud data is analyzed to determine the coordinates of the center point of the normal obstacles and the interference radius of the normal obstacles, and a normal obstacle information set is determined based on the edge features of the normal obstacles and the interference radius of the normal obstacles; real-time point cloud data and real-time visual data are analyzed to determine a key analysis area for temporary obstacles; based on the key analysis area for temporary obstacles, a lidar scanning strategy is adjusted, and based on the adjusted lidar scanning strategy, temporary obstacle point cloud information is determined; based on the temporary obstacle point cloud information and real-time visual data, the type of temporary obstacles, the coordinates of the center point of the temporary obstacles, the interference radius of the temporary obstacles and the edge features of the temporary obstacles are determined to determine the temporary obstacle information set.

[0048] The environmental perception information includes map data, robot real-time position data, real-time point cloud data, and real-time visual data. The map data may be map information of the user's home constructed by the built-in laser radar sensor of the sweeping robot. The real-time position data of the robot may be the position coordinates of the sweeping machine in the user's home during operation. The real-time point cloud data may be local three-dimensional spatial data of the environment in which the sweeping robot is located, collected by the built-in laser radar of the sweeping robot. The real-time visual data may be local visual data of the environment in which the sweeping robot is located, collected by the built-in visual sensor of the sweeping robot. The edge features of normal obstacles may be information representing the local edge features corresponding to the normal obstacles that affect the current sweeping robot. The coordinates of the center point of the normal obstacles may be the coordinates of the local center point of the normal obstacles that affect the current sweeping robot. The interference radius of the normal obstacles may be the local influence radius of the normal obstacles that affect the current sweeping robot. The key analysis area of ​​temporary obstacles may be the area where the temporary obstacles are located. The laser radar scanning strategy may be the operation strategy of the built-in laser radar of the sweeping robot, which may include scanning angle, scanning frequency, scanning area, etc. The point cloud information of temporary obstacles may be point cloud information used to represent the shape features of temporary obstacles. The temporary obstacle type may be the type of item to which the temporary obstacle belongs. The temporary obstacle center point coordinates may be the center point coordinates of the temporary obstacle in the current state. The temporary obstacle interference radius may be the radius of influence of the temporary obstacle on the sweeping robot. The temporary obstacle edge feature may be information used to characterize the edge feature of the current temporary obstacle.

[0049] Specifically, in the process of analyzing normal obstacles, since normal obstacles are usually larger in size than sweeping robots, the cleaning dead zone formed by temporary obstacles is usually not the entire normal obstacle, but a local part of the normal obstacle. The distribution position of the normal obstacle in the home can be reflected from the map data collected in advance by the sweeping robot. Combined with the real-time position data of the robot, it can be obtained that the current sweeping robot is located at which relative position of which normal obstacles, and then through the edge recognition technology in the image analysis technology, the real-time visual data is analyzed to extract the edge features of the normal obstacles in the area to be cleaned faced by the current sweeping robot. The edge features of the normal obstacles can provide a clear absolute boundary for the subsequent analysis process of the cleaning dead zone. Based on the edge features of the normal obstacles, point cloud data located within the edge of the normal obstacles are screened from the real-time point cloud data. These point cloud data can jointly reflect the geometric features of the normal obstacles. Based on this, the coordinates of the center point of the normal obstacle and the interference radius of the normal obstacle are obtained to reflect the maximum influence range of the normal obstacle. The normal obstacle information set thus constructed can provide scientific guidance data for the subsequent analysis of the sweeping robot motion strategy.

[0050] After analyzing and obtaining the normal obstacle information set, it is necessary to analyze the temporary obstacles. It can be seen from the description of the above embodiments that accurate analysis of temporary obstacles requires good cooperation between the laser radar and the visual sensor. Through mathematical analysis, according to the real-time point cloud data and real-time visual data, the temporary obstacle key analysis area is delineated. This area provides guidance for further data collection of the laser radar. According to the relative angle, relative distance between the temporary obstacle key analysis area and the current position of the sweeping robot and the size of the temporary obstacle key analysis area, the scanning angle, scanning frequency and scanning range of the laser radar are adjusted respectively, so that the laser radar can be changed from the original default with wide adaptability to the original default. The circular scanning strategy is transformed into a special scanning strategy for temporary obstacles to improve the recognition accuracy of temporary obstacles. The key scanning area is determined by visual sensors and targeted scanning is performed by lidar. The lidar and visual sensors work well together to obtain temporary obstacle point cloud information that can accurately reflect the characteristics of temporary obstacles. On this basis, the temporary obstacle type is obtained through the entity recognition algorithm, and the obstacle center coordinates, temporary obstacle interference radius and temporary obstacle edge features are screened from the obstacle point cloud information to construct a temporary obstacle information set, which provides a clear relative boundary for the subsequent analysis process of cleaning dead zones.

[0051] Through this solution, based on map data and real-time robot position data, real-time visual data is analyzed, and on this basis, combined with real-time point cloud data, the coordinates of the center point of normal obstacles and the interference radius of normal obstacles are obtained, so as to construct a normal obstacle information set, and provide a clear absolute boundary for the subsequent analysis process of cleaning dead zones. By analyzing real-time point cloud data and real-time visual data, the key analysis area of ​​temporary obstacles is determined, and through the corresponding lidar scanning strategy, the point cloud information of temporary obstacles is analyzed to determine the type of temporary obstacles, the coordinates of the center point of temporary obstacles, the interference radius of temporary obstacles and the edge features of temporary obstacles, so as to construct a temporary obstacle information set, realize accurate identification of temporary obstacles, and provide a clear relative boundary for the subsequent analysis process of cleaning dead zones.

[0052] In some embodiments, the real-time visual data is analyzed to determine the local color features and the local edge features of the temporary obstacle; the real-time point cloud data is analyzed to determine the local geometric features of the temporary obstacle, and the local color features, the local edge features and the local geometric features of the temporary obstacle are feature fused to determine the comprehensive features of the temporary obstacle; the comprehensive features of the temporary obstacle are clustered according to a preset clustering algorithm to determine the fuzzy area of ​​the temporary obstacle; the fuzzy area of ​​the temporary obstacle is analyzed to determine the coordinates of the center point of the fuzzy area, and the key analysis area of ​​the temporary obstacle is determined according to the preset scanning radius and the coordinates of the center point of the fuzzy area, which is specifically the following formula (1): (1) in, Focus analysis areas for temporary obstacles, is the coordinate of the scanning point to be selected, is the horizontal coordinate of the center point of the fuzzy area, is the ordinate of the center point of the fuzzy area, The preset scanning radius.

[0053] The local color feature of the temporary obstacle may be information used to characterize the local color feature of the temporary obstacle. The local edge feature of the temporary obstacle may be information used to characterize the local edge feature of the temporary obstacle. The local geometric feature of the temporary obstacle may be information used to characterize the local geometric feature of the temporary obstacle. The comprehensive feature of the temporary obstacle may be data used to characterize the comprehensive feature of the temporary obstacle obtained by splicing the local color feature, local edge feature and local geometric feature corresponding to the temporary obstacle through a feature splicing algorithm. The preset clustering algorithm may be a preset algorithm for classifying and distinguishing the comprehensive feature of the temporary obstacle from other features in the area. The preset clustering algorithm may adopt an existing mature clustering algorithm such as the K-means algorithm and the DBSCAN algorithm. The fuzzy area of ​​the temporary obstacle may be the area where the temporary obstacle is located, which is preliminarily determined. The coordinates of the center point of the fuzzy area may be the coordinates of the center point corresponding to the fuzzy area of ​​the temporary obstacle. The preset scanning radius may be the maximum scanning radius supported by the built-in laser radar of the sweeping robot.

[0054] Specifically, since the real-time visual data collected by the sweeping robot through the visual sensor is affected by problems such as limited viewing angle and insufficient light, it is difficult to reflect the complete characteristics of temporary obstacles. The color histogram analysis algorithm and edge detection algorithm in the image analysis technology are used to extract the local color features and local edge features of the temporary obstacles reflected in the real-time visual data respectively. The local color features and local edge features of the temporary obstacles can jointly reflect the boundary between the temporary obstacle and the surrounding objects and areas. Similarly, since the real-time point cloud data collected by the sweeping robot through the lidar is affected by problems such as the default scanning strategy and the surface characteristics of the object, it is also difficult to reflect the complete characteristics of the temporary obstacles. The real-time point cloud data can mainly reflect the temporary obstacles. The local geometric structure features of the temporary obstacle can provide guidance for the judgment of the type of temporary obstacle, and then deduce the impact area of ​​the current temporary obstacle. The local color features, local edge features and local geometric features of the temporary obstacle are fused through the feature vector splicing algorithm to determine the comprehensive features of the temporary obstacle. The comprehensive features of the temporary obstacle are clustered through the preset clustering algorithm to preliminarily distinguish the boundaries of the area where the temporary obstacle is located to determine the fuzzy area of ​​the temporary obstacle. Then, the key analysis area of ​​the temporary obstacle is scientifically quantified through formula (1), which improves the recognition accuracy of the temporary obstacle and provides scientific data reference for the targeted adjustment of the lidar scanning strategy.

[0055] Through this solution, real-time visual data is analyzed to obtain local color features and local edge features of temporary obstacles. At the same time, local geometric features of temporary obstacles are obtained by analyzing real-time point cloud data. The preset clustering algorithm is used to cluster the comprehensive features of temporary obstacles after the fusion of the above features to determine the fuzzy area of ​​temporary obstacles. On this basis, combined with the preset scanning radius and the coordinates of the center point of the fuzzy area, the key analysis area of ​​temporary obstacles is scientifically quantified through clear mathematical formulas to improve the accuracy of temporary obstacle recognition. At the same time, scientific data reference is provided for the targeted adjustment of lidar scanning strategies.

[0056] In some embodiments, the area to be analyzed and the obstacle area are determined based on normal obstacle edge features and temporary obstacle edge features; the area to be analyzed is divided into analysis points based on preset analysis point division rules to determine the analysis point coordinate set; based on the working width and safe collision distance, the obstacle radiation area is determined based on normal obstacle edge features, temporary obstacle edge features and the analysis point coordinate set; and the cleaning dead zone is determined based on the obstacle area and the obstacle radiation area.

[0057] The robot parameter set includes working width and safe collision distance. The working width may be the maximum width of the sweeping robot in the working state. The safe collision distance may be the preset collision warning distance inside the sweeping robot. The area to be analyzed may be the corresponding area where there may be a cleaning dead zone under the influence of the current temporary obstacles and normal obstacles. The obstacle area may be the area occupied by the temporary obstacles and normal obstacles that have been identified. The preset analysis point division rule may be a preset rule for dividing the analysis points of the area to be analyzed, which may include parameters such as analysis point density, and the preset analysis point division rule may be set according to specific needs. The analysis point coordinate set may be a set of all analysis point coordinate positions obtained by division. The obstacle radiation area may be an area that the sweeping robot cannot pass through under the combined influence of temporary obstacles and normal obstacles.

[0058] Specifically, the area formed by the normal obstacle edge features and the temporary obstacle edge features is extracted, wherein the area occupied by the normal obstacle edge and the temporary obstacle edge is the obstacle area, and the sweeping robot cannot touch this area, otherwise it will directly collide with the normal obstacle or the temporary obstacle, and the area outside the area occupied by the normal obstacle edge and the temporary obstacle edge is the area to be analyzed, and there may be a cleaning dead zone in this area, which requires further analysis. Since the area to be analyzed is composed of countless points, in order to balance the analysis accuracy and analysis efficiency, the analysis point division is performed on the area to be analyzed according to the preset analysis point division rule, and the analysis point coordinate set is extracted to control the calculation scale. On this basis, since the judgment of the cleaning dead zone is mainly based on whether the sweeping robot can enter the area without colliding with temporary obstacles or normal obstacles, if it can enter, the area is not a cleaning dead zone, if it cannot enter, the area is a cleaning dead zone, the passability of the sweeping robot mainly depends on its corresponding working width and safe collision distance. The working width determines whether the sweeping robot can pass through the designated area smoothly, and the safe collision distance determines whether the sweeping robot has motion adjustment space. Through mathematical analysis, based on the working width and safe collision distance, according to the normal obstacle edge characteristics, temporary obstacle edge characteristics and analysis point coordinate set, the obstacle radiation area is calculated, and the obstacle area and obstacle radiation area are combined to determine the cleaning dead zone.

[0059] Through this scheme, the area to be analyzed and the obstacle area are divided according to the edge characteristics of normal obstacles and temporary obstacles, and the analysis points of the area to be analyzed are divided to determine the coordinate set of the analysis points. On this basis, combined with the corresponding working width and safe collision distance of the sweeping robot, the obstacle radiation area is analyzed and obtained. The obstacle area and the obstacle radiation area are comprehensively analyzed to determine the cleaning dead zone, thereby improving the analysis efficiency and accuracy of the cleaning dead zone, thereby improving the scientificity and comprehensiveness of the subsequent motion strategy analysis process for the cleaning dead zone.

[0060] In some embodiments, based on the working width and the safe collision distance, the obstacle radiation area is determined according to the normal obstacle edge characteristics, the temporary obstacle edge characteristics and the analysis point coordinate set, specifically, the following formula (2): (2) in, For the barrier radiation area, is the coordinate of the current analysis point, For the The edge of a temporary obstacle, is the coordinate distance function, For the The edge of a normal obstacle, is the working width, is the safe collision distance; the cleaning dead zone is determined according to the obstacle area and the obstacle radiation area, which is specifically the following formula (3): (3) Among them, To clean up the dead zone, For the barrier radiation area, The coordinate distance function may be a mathematical function used to calculate the relative distance between different coordinate points.

[0061] Specifically, the obstacle radiation area is defined by formula (2), where the condition The meaning is: if there is an analysis point whose relative distance to a temporary obstacle or a normal obstacle is less than the working width of the sweeping robot, then the analysis point belongs to the obstacle radiation area, and the condition The meaning is: if there is an analysis point whose relative distance to a temporary obstacle or a normal obstacle is less than the safe collision distance of the sweeping robot, then the analysis point belongs to the obstacle radiation area. Formula (2) is used to automatically screen all analysis points belonging to the obstacle radiation area, and then the obstacle radiation area is clarified. On this basis, formula (3) is used to take the union of the obstacle radiation area and the obstacle area as the cleaning dead zone, so as to accurately describe the range of the cleaning dead zone.

[0062] Through this scheme, based on the working width and safe collision distance, according to the normal obstacle edge characteristics, temporary obstacle edge characteristics and analysis point coordinate set, through clear mathematical processing means, all analysis points belonging to the obstacle radiation area are automatically screened, and then the obstacle radiation area is clarified. On this basis, through mathematical processing means, the union between the obstacle radiation area and the obstacle area is used as the cleaning dead zone to accurately describe the scope of the cleaning dead zone, thereby improving the accuracy and calculation efficiency of the cleaning dead zone determination process.

[0063] In some embodiments, based on the type of temporary obstacle, the edge features of the temporary obstacle are analyzed to determine the coordinates of the movable endpoint of the temporary obstacle; the robot's travel path is determined based on the robot's real-time position data and the coordinates of the movable endpoint of the temporary obstacle; based on the robot's travel path, the movement offset and movement direction are determined, and the coordinates of the movable endpoint after the movement are determined accordingly; based on the robot radius and the normal obstacle interference radius, the safe area is determined according to the coordinates of the center point of the temporary obstacle and the edge features of the normal obstacle; the robot's travel path, the coordinates of the movable endpoint after the movement, and the safe area are integrated to determine the dead zone elimination strategy.

[0064] The robot parameter set also includes the robot radius, which may be the radius size of the robot body. The coordinates of the movable endpoint of the temporary obstacle may be the coordinates of the endpoint of the current temporary obstacle that can be moved. The robot travel path may be the route that the sweeping robot needs to move to move the temporary obstacle. The movement offset may be the distance that the sweeping robot moves the temporary obstacle. The movement direction may be the direction in which the sweeping robot moves the temporary obstacle. The coordinates of the movable endpoint after movement may be the coordinates of the position of the movable endpoint of the temporary obstacle after it is moved by the sweeping robot according to the current corresponding robot travel path. The safe area may be a safe area in which the sweeping robot can perform dynamic path planning without being affected by other factors.

[0065] Specifically, after determining the cleaning dead zone, it is necessary to control the sweeping robot to move the temporary obstacle to break the establishment conditions of the cleaning dead zone in the aforementioned embodiment, and then eliminate the cleaning dead zone. In this process, it is first necessary to clarify how to move the temporary obstacle. Here, it is considered that there are two situations of temporary obstacles: freely movable and non-freely movable. Freely movable means that the temporary obstacle is not connected to other objects and can be moved freely and independently, while non-freely movable means that the temporary obstacle is connected to other objects, such as a charging cable or socket wire hanging on the ground, one end of which is connected to other objects, with a limited range of movement and only the end without connection can be moved. Therefore, the concept of the coordinates of the movable endpoint of the temporary obstacle is introduced to provide a position reference for the moving point of the temporary obstacle during the moving process of the sweeping robot. The coordinates of the movable endpoint of the temporary obstacle are directly related to the type of temporary obstacle and the edge characteristics of the temporary obstacle. The type of temporary obstacle determines whether the temporary obstacle is an object that cannot be moved freely. The edge features of temporary obstacles determine the position of the movable endpoint corresponding to the temporary obstacle. Through comprehensive analysis of the temporary obstacle type and the edge features of temporary obstacles, the coordinates of the movable endpoints of temporary obstacles are extracted. Through mathematical analysis, the robot's travel path required for the sweeping robot to move the temporary obstacle is planned according to the robot's real-time position data and the coordinates of the movable endpoints of temporary obstacles. The movement offset and movement direction are used to determine the coordinates of the movable endpoint after the movement, and then the coordinates of the movable endpoint after the movement are extracted. If the coordinates of the movable endpoint after the movement still form a cleaning dead zone with other obstacles, further planned movement paths are required. At this time, the sweeping robot needs to be in a safe area to ensure the accuracy of the new route. Through mathematical analysis, based on the robot radius and the normal obstacle interference radius, according to the coordinates of the temporary obstacle center point and the normal obstacle edge features, the corresponding range of the safe area is quantified. By integrating the above robot travel path, the coordinates of the movable endpoint after the movement and the safe area, a dead zone elimination strategy is obtained.

[0066] Through this scheme, the coordinates of the movable endpoints of temporary obstacles are determined according to the types of temporary obstacles and the edge features of temporary obstacles, and the robot's travel path is planned in combination with the real-time position data of the robot, taking full account of the different movable conditions of temporary obstacles. On this basis, the movement offset and movement direction are determined according to the robot's travel path, and the coordinates of the active endpoints after the movement are obtained. At the same time, the safety area is delineated based on the robot radius and the normal obstacle interference radius, and the dead zone elimination strategy is determined by integrating the robot's travel path, the coordinates of the active endpoints after the movement and the safety area. The dead zone elimination strategy can avoid the collision between the sweeping robot and the normal obstacles while eliminating the cleaning dead zone through the targeted movement of temporary obstacles, thereby significantly improving the cleaning effect and adaptability of the sweeping robot.

[0067] In some embodiments, the robot's travel path, the coordinates of the active endpoint after movement, and the safety area are integrated to determine the dead zone elimination strategy, which is specifically the following formula (4): (4) in, is the robot's travel path, The real-time position data of the robot. For the The coordinates of the temporary obstacle center point of a normal obstacle, is the robot radius, For the The normal obstacle interference radius of a normal obstacle, For the The normal obstacle edge features of a normal obstacle, is the normal obstacle information set, is the coordinates of the active endpoint after moving, is the temporary obstacle interference radius, For safe area.

[0068] Specifically, when the sweeping robot moves according to the robot's travel route to move the temporary obstacle, it is necessary to ensure that the sweeping robot does not collide with other normal obstacles. The relative distance between the sweeping robot and normal obstacles is limited to be greater than the sum of the corresponding interference radii of the two. That is, the sweeping robot always maintains a safe distance from each normal obstacle during movement. After moving the temporary obstacle, it is also necessary to prevent new interference between the temporary obstacle and the normal obstacle. The relationship between temporary obstacles and normal obstacles after movement is limited. If the above conditions cannot be met, it means that the travel path needs to be updated. By limiting the sweeping robot to re-plan the path in the safe area, the sweeping robot is prevented from being interfered with during the path planning process. Combining the above three steps, a dead zone elimination strategy is constructed.

[0069] Through this solution, the robot's travel path, the coordinates of the active endpoint after movement, and the safe area are integrated, the limiting conditions of each stage in the process of the sweeping robot moving temporary obstacles are clarified, and a dead zone elimination strategy is constructed, so that the sweeping robot can eliminate the current cleaning dead zone while avoiding collisions between the sweeping robot and normal obstacles, and can effectively avoid the emergence of new cleaning dead zones.

[0070] In some embodiments, the robot's travel path, the coordinates of the active endpoint after movement, and the safety area are integrated, specifically as follows: (5) in, is the robot's travel path, The real-time position data of the robot. are the coordinates of the movable endpoints of the temporary obstacle, For the The coordinates of the temporary obstacle center point of a normal obstacle, To make progress for the unit, is the preset maximum step size, is the robot radius, For the The normal obstacle interference radius of a normal obstacle, For the The normal obstacle edge features of a normal obstacle, is the coordinates of the active endpoint after moving, For safe areas, To move the offset, To move the direction.

[0071] The unit travel step length may be the step length of each travel of the cleaning robot in the current robot travel path.

[0072] The preset maximum step length may be the maximum step length that the sweeping robot can directly move in the current environment. The preset maximum step length is directly related to the number of obstacles around the sweeping robot. The preset maximum step length may be derived from the linear relationship between the moving step length and the number of obstacles.

[0073] Specifically, through formula (5) Describes the direction vector from the robot's real-time position to the coordinates of the movable end point of the temporary obstacle, and uses Describe the unit direction vector, combined with the unit step length, and plan the robot's route based on the current robot's real-time position data. , calculate the position of the movable endpoint coordinates of the temporary obstacle after the movement offset in the corresponding movement direction is applied, and obtain the coordinates of the movable endpoint after movement. The limited safety area consists of everything that can maintain a safe distance from the sweeping robot to prevent the sweeping robot from colliding with normal obstacles.

[0074] Through this scheme, mathematical analysis methods are used to describe the planning process of the robot's travel path, the determination process of the active endpoint coordinates after movement, and the demarcation process of the safe area, respectively, to clarify the mathematical relationship between the robot's travel path, the coordinates of the active endpoint after movement, and the safe area and their respective influencing factors, to improve the scientificity, accuracy and comprehensiveness of the robot's travel path, the coordinates of the active endpoint after movement, and the safe area determination process, thereby improving the effectiveness of the dead zone elimination strategy formulated based on this.

[0075] In some embodiments, according to the dead zone elimination strategy, the sweeping robot is controlled to move along the robot's travel path to move the temporary obstacle; when the sweeping robot moves the temporary obstacle, the cleaning structure of the sweeping robot is controlled to stop working, and according to the edge characteristics of the normal obstacle, the area outside the coverage range of the normal obstacle closest to the temporary obstacle is determined as the temporary obstacle target area, and the sweeping robot is controlled to move the temporary obstacle into the temporary obstacle target area; after the sweeping robot moves the temporary obstacle into the temporary obstacle target area, the sweeping robot is controlled to clean the cleaning dead zone, and the temporary obstacle target area is recorded and output.

[0076] Specifically, according to the dead zone elimination strategy, the built-in microcontroller of the sweeping robot is used to control the sweeping robot to move along the robot's travel path to achieve the removal of temporary obstacles. During the movement process, the cleaning structure on the sweeping robot, such as the side brush and the roller brush assembly, is prone to part of the structure of the temporary obstacle being drawn into the cleaning structure when dealing with some special types of temporary obstacles, such as data cables, causing the sweeping robot to malfunction. Therefore, during the movement process, the cleaning structure is controlled to stop working, and the structural components of the sweeping robot that can fit tightly with the ground, such as the mop structure, are in direct contact with the temporary obstacle, and the temporary obstacle is moved through the movement of the sweeping robot to avoid the occurrence of a malfunction. Avoid the negative impact of temporary obstacles on the sweeping robot. At the same time, determine the area outside the coverage of the normal obstacle closest to the temporary obstacle as the temporary obstacle target area, and control the sweeping robot to move the temporary obstacle into the temporary obstacle target area to avoid the temporary obstacle being continuously blocked by the normal obstacle, which makes it difficult for the user to deal with the temporary obstacle in time. After the temporary obstacle is moved to the temporary obstacle target area, control the sweeping robot to restart the cleaning structure to clean the original cleaning dead zone, and provide the temporary obstacle target area to the user by means of information push, so that the user can know the location of the temporary obstacle in time, so that the user can quickly deal with the temporary obstacle.

[0077] Through this solution, according to the dead zone elimination strategy, the sweeping robot is controlled to move the temporary obstacle, and in this process, the cleaning structure of the sweeping robot is controlled to stop working to avoid the sweeping robot being affected by the temporary obstacle during the movement and causing malfunction. At the same time, the sweeping robot is controlled to move the temporary obstacle to the temporary obstacle target area, and after the sweeping robot completes the cleaning work of the original cleaning dead zone, the temporary obstacle target area is provided to the user, so that the user can know the location of the temporary obstacle in time, so that the user can quickly deal with the temporary obstacle, and effectively avoid the temporary obstacle from continuing to stay in the current area.

[0078] Figure 3 A schematic diagram of a multi-dimensional data fusion sweeping robot motion control system provided in an embodiment of the present application is shown in FIG. Figure 3 As shown, a multi-dimensional data fusion sweeping robot motion control system 300 of this embodiment includes: an obstacle analysis module 301 , a region analysis module 302 , a motion analysis module 303 and a motion control module 304 .

[0079] The obstacle analysis module 301 is used to obtain environmental perception information, analyze the environmental perception information, and determine a temporary obstacle information set and a normal obstacle information set; the area analysis module 302 is used to obtain a robot parameter set, and based on the robot parameter set, determine the cleaning dead zone of the sweeping robot in the obstacle avoidance situation according to the temporary obstacle information set and the normal obstacle information set; the motion analysis module 303 is used to analyze the cleaning dead zone based on the robot parameter set, the environmental perception information and the temporary obstacle information set, and determine the dead zone elimination strategy; the motion control module 304 is used to control the sweeping robot to perform corresponding cleaning motion according to the dead zone elimination strategy, and determine and output the temporary obstacle target area.

[0080] Optionally, the obstacle analysis module 301 is specifically used to: analyze the real-time visual data based on the map data and the real-time position data of the robot to determine the edge features of normal obstacles; analyze the real-time point cloud data based on the normal obstacle edge features to determine the coordinates of the center point of the normal obstacle and the normal obstacle interference radius, and determine the normal obstacle information set according to the normal obstacle edge features and the normal obstacle interference radius; analyze the real-time point cloud data and the real-time visual data to determine the key analysis area of ​​temporary obstacles; adjust the lidar scanning strategy according to the temporary obstacle key analysis area, and determine the temporary obstacle point cloud information according to the adjusted lidar scanning strategy; determine the temporary obstacle type, the temporary obstacle center point coordinates, the temporary obstacle interference radius and the temporary obstacle edge features according to the temporary obstacle point cloud information and the real-time visual data, so as to determine the temporary obstacle information set.

[0081] Optionally, when analyzing the real-time point cloud data and the real-time visual data to determine the key analysis area of ​​the temporary obstacle, the regional analysis module 302 is specifically used to: analyze the real-time visual data to determine the local color features and local edge features of the temporary obstacle; analyze the real-time point cloud data to determine the local geometric features of the temporary obstacle, and perform feature fusion on the local color features of the temporary obstacle, the local edge features of the temporary obstacle and the local geometric features of the temporary obstacle to determine the comprehensive features of the temporary obstacle; perform clustering processing on the comprehensive features of the temporary obstacle according to a preset clustering algorithm to determine the fuzzy area of ​​the temporary obstacle; analyze the fuzzy area of ​​the temporary obstacle to determine the coordinates of the center point of the fuzzy area, and determine the key analysis area of ​​the temporary obstacle according to the preset scanning radius and the coordinates of the center point of the fuzzy area, which is specifically the following formula: ;in, Focus analysis area for the temporary obstacle, is the coordinate of the scanning point to be selected, is the horizontal coordinate of the center point of the fuzzy area, is the ordinate of the center point of the fuzzy area, is the preset scanning radius.

[0082] Optionally, the area analysis module 302 includes a working width and a safe collision distance in the robot parameter set, and analyzes the cleaning dead zone based on the robot parameter set, the environmental perception information and the temporary obstacle information set, and determines the dead zone elimination strategy and the temporary obstacle target area, specifically for: determining the area to be analyzed and the obstacle area according to the normal obstacle edge characteristics and the temporary obstacle edge characteristics; dividing the area to be analyzed into analysis points based on preset analysis point division rules to determine the analysis point coordinate set; determining the obstacle radiation area based on the working width and the safe collision distance according to the normal obstacle edge characteristics, the temporary obstacle edge characteristics and the analysis point coordinate set; determining the cleaning dead zone according to the obstacle area and the obstacle radiation area.

[0083] Optionally, when the area analysis module 302 determines the obstacle radiation area based on the working width and the safe collision distance, according to the normal obstacle edge feature, the temporary obstacle edge feature and the analysis point coordinate set, it is specifically the following formula: ; in, is the barrier radiation area, is the coordinate of the current analysis point, For the The edge of a temporary obstacle, is the coordinate distance function, For the The edge of a normal obstacle, is the working width, is the safe collision distance; the cleaning dead zone is determined according to the obstacle area and the obstacle radiation area, specifically the following formula: in, To clean up the dead zone, is the barrier radiation area, is the obstacle area.

[0084] Optionally, the motion analysis module 303 is specifically used to: analyze the edge features of the temporary obstacle based on the temporary obstacle type, and determine the coordinates of the movable endpoint of the temporary obstacle; determine the robot's travel path based on the robot's real-time position data and the coordinates of the movable endpoint of the temporary obstacle; determine the movement offset and movement direction based on the robot's travel path, and determine the coordinates of the active endpoint after the movement; determine the safety area based on the robot radius and the normal obstacle interference radius, according to the coordinates of the temporary obstacle center point and the normal obstacle edge features; integrate the robot's travel path, the coordinates of the active endpoint after the movement, and the safety area to determine the dead zone elimination strategy.

[0085] Optionally, the motion analysis module 303 integrates the robot's travel path, the coordinates of the active endpoint after movement, and the safety area to determine the dead zone elimination strategy, specifically the following formula: ; in, is the robot’s travel path, is the real-time position data of the robot, For the The coordinates of the temporary obstacle center point of the normal obstacle, is the robot radius, For the The normal obstacle interference radius of the normal obstacle, For the The normal obstacle edge features of the normal obstacles, is the normal obstacle information set, is the coordinate of the active endpoint after the movement, is the temporary obstacle interference radius, is the safe area.

[0086] Optionally, the motion analysis module 303 integrates the robot's travel path, the coordinates of the activity endpoint after movement, and the safety area using the following formula: ; Wherein, E is the robot's travel path, is the real-time position data of the robot, are the coordinates of the movable endpoints of the temporary obstacle, For the The coordinates of the temporary obstacle center point of the normal obstacle, To make progress for the unit, is the preset maximum step size, is the robot radius, For the The normal obstacle interference radius of the normal obstacle, For the The normal obstacle edge features of the normal obstacles, is the coordinate of the active endpoint after the movement, is the safe area, is the shift offset, is the moving direction.

[0087] Optionally, the motion control module 304 is specifically used to: control the sweeping robot to move along the robot's travel path to move the temporary obstacle according to the dead zone elimination strategy; when the sweeping robot moves the temporary obstacle, control the cleaning structure of the sweeping robot to stop working, and according to the normal obstacle edge characteristics, determine the area outside the normal obstacle coverage range closest to the temporary obstacle as a temporary obstacle target area, and control the sweeping robot to move the temporary obstacle into the temporary obstacle target area; after the sweeping robot moves the temporary obstacle into the temporary obstacle target area, control the sweeping robot to clean the cleaning dead zone, and record and output the temporary obstacle target area.

[0088] The system of this embodiment can be used to execute the method of any of the above embodiments. The implementation principles and technical effects are similar and will not be described in detail here.

Claims

1. A sweeping robot motion control method based on multi-dimensional data fusion, characterized in that: include: Acquire environmental perception information, analyze the environmental perception information, and determine a temporary obstacle information set and a normal obstacle information set; Acquire a robot parameter set, and determine a cleaning dead zone of the sweeping robot in an obstacle avoidance situation based on the robot parameter set and the temporary obstacle information set and the normal obstacle information set; Analyzing the cleaning dead zone based on the robot parameter set, the environmental perception information and the temporary obstacle information set, and determining a dead zone elimination strategy; According to the dead zone elimination strategy, the cleaning robot is controlled to perform corresponding cleaning movements, and a temporary obstacle target area is determined and output; The environmental perception information includes real-time position data of the robot, the robot parameter set also includes a robot radius, and the cleaning dead zone is analyzed based on the robot parameter set and the temporary obstacle information set to determine a dead zone elimination strategy, including: based on the type of temporary obstacles, analyzing the edge features of the temporary obstacles to determine the coordinates of the movable endpoints of the temporary obstacles; The robot's travel path is determined according to the robot's real-time position data and the coordinates of the movable endpoints of the temporary obstacle; the movement offset and movement direction are determined according to the robot's travel path, and the coordinates of the movable endpoint after the movement are determined accordingly; based on the robot radius and the normal obstacle interference radius, the safety area is determined according to the coordinates of the temporary obstacle center point and the normal obstacle edge features; the robot's travel path, the coordinates of the movable endpoint after the movement and the safety area are integrated to determine the dead zone elimination strategy.

2. The method according to claim 1, characterized in that The environmental perception information includes map data, real-time point cloud data, and real-time visual data. The analyzing the environmental perception information to determine the temporary obstacle information set and the normal obstacle information set includes: Analyzing the real-time visual data based on the map data and the real-time position data of the robot to determine the edge features of normal obstacles; Based on the normal obstacle edge features, the real-time point cloud data is analyzed to determine the normal obstacle center point coordinates and the normal obstacle interference radius, and the normal obstacle information set is determined according to the normal obstacle edge features and the normal obstacle interference radius; Analyze the real-time point cloud data and the real-time visual data to determine a key analysis area for temporary obstacles; According to the temporary obstacle key analysis area, adjusting the laser radar scanning strategy, and determining the temporary obstacle point cloud information according to the adjusted laser radar scanning strategy; According to the temporary obstacle point cloud information and the real-time visual data, the temporary obstacle type, the temporary obstacle center point coordinates, the temporary obstacle interference radius and the temporary obstacle edge features are determined to determine the temporary obstacle information set.

3. The method according to claim 2, characterized in that The analyzing the real-time point cloud data and the real-time visual data to determine a temporary obstacle key analysis area includes: Analyze the real-time visual data to determine local color features and local edge features of the temporary obstacle; Analyze the real-time point cloud data to determine the local geometric features of the temporary obstacle, and perform feature fusion on the local color features of the temporary obstacle, the local edge features of the temporary obstacle, and the local geometric features of the temporary obstacle to determine the comprehensive features of the temporary obstacle; According to a preset clustering algorithm, clustering processing is performed on the comprehensive features of the temporary obstacle to determine the fuzzy area of ​​the temporary obstacle; Analyze the temporary obstacle fuzzy area, determine the coordinates of the center point of the fuzzy area, and determine the temporary obstacle key analysis area according to the preset scanning radius and the coordinates of the center point of the fuzzy area, specifically the following formula: ； in, Focus analysis area for the temporary obstacle, is the coordinate of the scanning point to be selected, is the horizontal coordinate of the center point of the fuzzy area, is the ordinate of the center point of the fuzzy area, is the preset scanning radius.

4. The method according to claim 3, characterized in that: The robot parameter set includes a working width and a safe collision distance. The cleaning dead zone is analyzed based on the robot parameter set, the environmental perception information and the temporary obstacle information set to determine a dead zone elimination strategy and a temporary obstacle target area, including: Determining the area to be analyzed and the obstacle area according to the normal obstacle edge features and the temporary obstacle edge features; Based on a preset analysis point division rule, the area to be analyzed is divided into analysis points to determine an analysis point coordinate set; Based on the working width and the safe collision distance, determining the obstacle radiation area according to the normal obstacle edge characteristics, the temporary obstacle edge characteristics and the analysis point coordinate set; The cleaning dead zone is determined according to the obstacle area and the obstacle radiation area.

5. The method according to claim 4, characterized in that Based on the working width and the safe collision distance, the obstacle radiation area is determined according to the normal obstacle edge features, the temporary obstacle edge features and the analysis point coordinate set, specifically the following formula: ； in, is the barrier radiation area, is the coordinate of the current analysis point, For the The edge of a temporary obstacle, is the coordinate distance function, For the The edge of a normal obstacle, is the working width, is the safe collision distance; The cleaning dead zone is determined according to the obstacle area and the obstacle radiation area, specifically, the following formula: ； in, To clean up the dead zone, is the barrier radiation area, is the obstacle area.

6. The method according to claim 5, characterized in that The dead zone elimination strategy is determined by integrating the robot's travel path, the coordinates of the active endpoint after the movement, and the safety area, which is specifically the following formula: ； in, is the robot’s travel path, is the real-time position data of the robot, For the The coordinates of the temporary obstacle center point of the normal obstacle, is the robot radius, For the The normal obstacle interference radius of the normal obstacle, For the The normal obstacle edge features of the normal obstacles, is the normal obstacle information set, is the coordinate of the active endpoint after the movement, is the temporary obstacle interference radius, is the safe area.

7. The method according to claim 6, characterized in that The integration of the robot's travel path, the coordinates of the active endpoint after movement, and the safety area is specifically the following formula: ； in, is the robot’s travel path, is the real-time position data of the robot, are the coordinates of the movable endpoints of the temporary obstacle, For the The coordinates of the temporary obstacle center point of the normal obstacle, To make progress for the unit, is the preset maximum step size, is the robot radius, For the The normal obstacle interference radius of the normal obstacle, For the The normal obstacle edge features of the normal obstacles, is the coordinate of the active endpoint after the movement, is the safe area, is the shift offset, is the moving direction.

8. The method according to claim 7, characterized in that According to the dead zone elimination strategy, controlling the cleaning robot to perform corresponding cleaning motion, determining and outputting a temporary obstacle target area, includes: According to the dead zone elimination strategy, the cleaning robot is controlled to move along the robot's travel path to move the temporary obstacle; When the cleaning robot moves the temporary obstacle, the cleaning structure of the cleaning robot is controlled to stop working, and according to the edge characteristics of the normal obstacle, an area outside the coverage range of the normal obstacle closest to the temporary obstacle is determined as a temporary obstacle target area, and the cleaning robot is controlled to move the temporary obstacle into the temporary obstacle target area; After the cleaning robot moves the temporary obstacle into the temporary obstacle target area, the cleaning robot is controlled to clean the cleaning dead zone, and the temporary obstacle target area is recorded and output.

9. A multi-dimensional data fusion sweeping robot motion control system, characterized in that: The method as claimed in any one of claims 1 to 8 comprises: An obstacle analysis module, used to obtain environmental perception information, analyze the environmental perception information, and determine a temporary obstacle information set and a normal obstacle information set; A region analysis module, used for obtaining a robot parameter set, and determining a cleaning dead zone of the sweeping robot in an obstacle avoidance situation based on the robot parameter set, the temporary obstacle information set and the normal obstacle information set; A motion analysis module, configured to analyze the cleaning dead zone and determine a dead zone elimination strategy based on the robot parameter set, the environmental perception information and the temporary obstacle information set; The motion control module is used to control the cleaning robot to perform corresponding cleaning motion according to the dead zone elimination strategy, and determine and output the temporary obstacle target area.

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