Automatic cleaning equipment and cleaning system

Abstract

The utility model discloses automatic cleaning equipment and a cleaning system.The automatic cleaning equipment comprises an equipment body and a sensing module, the sensing module comprises a TOF sensor and a visual sensor, and the TOF sensor is arranged on the equipment body, faces the advancing direction of the equipment body and is used for obtaining point cloud information in the advancing direction of the equipment body; the visual sensor is arranged on the device body and used for obtaining visual information in the obliquely upward direction of the device body. The point cloud information and the visual information in different directions are acquired through the TOF sensor and the visual sensor, the front area and the oblique upward area of the equipment main body can be covered, the two-dimensional map or the three-dimensional map is constructed by adopting the TOF point cloud information and the visual information in different directions, the surrounding environment information can be determined more accurately, and the user experience is improved. And the obstacle avoidance effect and the operation effect of the automatic cleaning equipment main body are further improved, the positioning precision is guaranteed, and the cost is reduced.

Description

Technical Field

[0001] This application relates to the field of automatic cleaning equipment technology, and more specifically to an automatic cleaning device and cleaning system. Background Technology

[0002] With the development of technology, various automated cleaning robots have become ubiquitous in our lives, such as robotic vacuum cleaners, robotic mops, and vacuum cleaners. These robots can automatically move and clean or remove debris in a specific area without user intervention. Automated cleaning robots typically have a Time-of-Flight (TOF) sensor installed directly in front of the robot, limiting the range of information acquired to the robot's forward direction. Alternatively, TOF sensors may be installed in front of the robot and to its left rear, acquiring information in the forward and left rear directions, respectively. The limited range and variety of environmental information obtained from these two TOF sensors significantly hinders further mapping and localization, impacting the user experience. Utility Model Content

[0003] To overcome at least one of the aforementioned drawbacks, this application provides an automatic cleaning device and a cleaning system. The objective of this application can be achieved by employing the following technical solution:

[0004] A first aspect of this application provides an automatic cleaning device, including a device body and a sensing module, the sensing module comprising:

[0005] A TOF sensor is mounted on the main body of the device and faces the direction of travel of the main body of the device, and is used to acquire point cloud information along the direction of travel of the main body of the device.

[0006] A vision sensor, which is disposed on the main body of the device, is used to acquire visual information in an obliquely upward direction on the main body of the device.

[0007] In one possible implementation, the acquisition direction of the TOF sensor is different from that of the vision sensor;

[0008] The visual sensor is positioned facing the rear of the main body of the device.

[0009] In one possible implementation, the acquisition range of the TOF sensor and the acquisition range of the vision sensor for acquiring environmental information do not overlap; or,

[0010] The acquisition range of the TOF sensor and the acquisition range of the vision sensor for acquiring environmental information partially overlap.

[0011] In one possible implementation, the vision sensor is disposed on the top of the device body.

[0012] In one possible implementation, the visual sensor includes a camera device, the camera device being mounted at an elevation angle ranging from 0° to 90°.

[0013] In one possible implementation, the vision sensor further includes a protective lens for covering the lens of the camera device.

[0014] In one possible implementation, the vision sensor further includes a mounting base connected to the main body of the device, and the camera device is disposed on the mounting base.

[0015] In one possible implementation, the mounting base includes a base plate, and the camera device is disposed on a mounting portion of the base plate, wherein the mounting portion is a protruding structure or a groove structure.

[0016] In one possible implementation, the mounting portion includes a mounting plate, which is obliquely disposed on the substrate, and the camera device is disposed on the mounting plate.

[0017] In one possible implementation, the mounting base and the camera device are movably connected; and / or,

[0018] The mounting base is a movable structure, allowing the orientation angle and / or rotation angle of the visual sensor to be adjusted.

[0019] In one possible implementation, the mounting base further includes a connector, through which the camera device is movably connected to the base plate, and the orientation angle and / or rotation angle of the camera device can be adjusted via the connector.

[0020] In one possible implementation, the fixing base further includes a limiting member disposed on the connecting member and used to limit the camera device in the rotation direction of the camera device.

[0021] In one possible implementation, the sensing module further includes a supplementary light, which is connected to the main body of the device and is used to provide supplementary lighting for the visual sensor.

[0022] A second aspect of this application provides a cleaning system, comprising:

[0023] Any of the automatic cleaning devices mentioned in the first aspect;

[0024] A base station, which is used to provide maintenance for the automatic cleaning equipment.

[0025] In one possible implementation, the automatic cleaning device further includes:

[0026] An inertial sensor is used to acquire motion information of the main body of the device;

[0027] Wheel speed sensor, used to acquire wheel speed information of the main body of the device.

[0028] In one possible implementation, the automatic cleaning device further includes a processor for fusing, locating, and mapping the point cloud information, the visual information, the motion information, and the wheel speed meter information.

[0029] The beneficial technical effects of this application are as follows: According to this disclosure, the automatic cleaning equipment includes a main body and a sensing module. The sensing module includes a TOF sensor and a vision sensor. By setting a TOF sensor facing the direction of movement of the main body and a vision sensor facing diagonally upwards towards the main body, point cloud information and visual information in different directions are acquired. Obstacle avoidance is achieved through a combined obstacle avoidance method in the direction of movement and diagonally upwards in other directions. This can cover the area in front of the main body and the area diagonally upwards. By using TOF point cloud information and visual information in different directions to construct a two-dimensional map or a three-dimensional map, the acquisition direction and types of environmental information are increased, enabling more accurate determination of the surrounding environmental information. This further improves the obstacle avoidance effect and operational efficiency of the automatic cleaning equipment, ensures positioning accuracy, and reduces costs. Attached Figure Description

[0030] The following are given by way of example and without limitation in the accompanying drawings:

[0031] Figure 1 This diagram shows a structural schematic of an existing automatic cleaning device from one angle.

[0032] Figure 2 This shows a structural schematic diagram of an existing automatic cleaning device from another angle;

[0033] Figure 3 This is a schematic diagram of the automatic cleaning device of this application from one angle;

[0034] Figure 4 A schematic diagram of the unfolded structure of the device body and the TOF sensor of this application is shown;

[0035] Figure 5 A schematic diagram of the automatic cleaning device of this application is shown from another angle;

[0036] Figure 6 This paper shows a schematic diagram of the TOF sensor of this application at one angle;

[0037] Figure 7 It shows Figure 6 A magnified schematic diagram of a local structure;

[0038] Figure 8 A flowchart illustrating a positioning method for an automatic cleaning device according to an embodiment of this application is shown;

[0039] Figure 9 A flowchart illustrating a positioning method for an automatic cleaning device according to another embodiment of this application is shown;

[0040] Figure 10 It shows Figure 8 A flowchart illustrating a specific implementation method for step 102;

[0041] Figure 11 A schematic diagram of the positioning device of an automatic cleaning equipment according to an embodiment of this application is shown;

[0042] Figure 12 A schematic diagram of the device structure of a computer device provided in an embodiment of this application is shown.

[0043] In the picture:

[0044] 100. Automatic cleaning equipment; 110. Main body of the equipment;

[0045] 1. Time-of-Flight (TOF) sensor; 2. Vision sensor;

[0046] 21. Camera device; 22. Mounting base; 23. Protective lens;

[0047] 221. Substrate; 222. Mounting part; 2221. Mounting plate. Detailed Implementation

[0048] In the following detailed disclosure, these embodiments are fully described with reference to the accompanying drawings. In order to enable those skilled in the art to understand and clarify the technical solutions of this application more clearly, the implementation methods described below are not limited thereto. The application will be further described in detail below with reference to the embodiments and the accompanying drawings.

[0049] In this application, the terms "first," "second," and "third" are used for descriptive purposes only and should not be construed as indicating or implying relative importance; the term "multiple" refers to two or more unless otherwise expressly defined. The terms "install," "connect," "link," and "fix" should be interpreted broadly. For example, "connect" can mean a fixed connection, a detachable connection, or an integral connection; "link" can mean a direct connection or an indirect connection through an intermediate medium. Those skilled in the art can understand the specific meaning of the above terms in this application based on the specific circumstances.

[0050] In the description of this application, it should be understood that the terms "upper", "lower", "left", "right", "front", "rear", etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. They are only for the convenience of describing this application and simplifying the description, and do not indicate or imply that the device or unit referred to must have a specific orientation or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on this application.

[0051] like Figure 1 and Figure 2 As shown, traditional automated cleaning robots typically have TOF sensors installed in front of the robot and to its left rear, which only acquire point cloud information in the forward direction and to the left rear direction. The direction, range, and types of environmental information acquired are limited, leading to certain errors in further mapping and localization, which affects the user experience.

[0052] The first aspect of this application, as Figures 3-7 As shown, an automatic cleaning device 100 is provided, including a device body 110 and a sensing module. The sensing module includes a TOF sensor 1 and a vision sensor 2. The TOF sensor 1 is disposed on the device body 110 and faces the forward direction of the device body 110, and is used to acquire point cloud information along the forward direction of the device body 110. The vision sensor 2 is disposed on the device body 110 and is used to acquire visual information in the oblique upward direction of the device body 110.

[0053] The automatic cleaning device 100 provided in this embodiment includes a device body 110 and a sensing module. The device body 110 is used to perform service tasks, and the sensing module is installed on the device body 110 to sense the surrounding environment information for the device body 110, that is, to obtain obstacle information.

[0054] The perception module includes a TOF sensor 1 and a vision sensor 2. By setting the TOF sensor 1 facing the forward direction of the device body 110 and the vision sensor 2 facing diagonally upward towards the device body 110, point cloud information and visual information in different directions are acquired. By using a joint obstacle avoidance method in the forward direction and diagonally upward direction, obstacle avoidance can be performed, covering the area in front of the device body 110 and the diagonally upward area in other directions. By using TOF and visual information in different directions to construct a two-dimensional map or a three-dimensional map, the acquisition direction of environmental information is increased, the acquisition range of environmental information is improved, and the distance between the obstacle and the device body 110 can be determined, thus facilitating obstacle avoidance by the device body 100. This setting ensures obstacle avoidance accuracy while reducing obstacle avoidance costs.

[0055] In one feasible implementation, point cloud information is acquired by TOF sensor 1 and visual information is acquired by visual sensor 2. Based on the point cloud information and visual information, obstacle information in two directions is determined. Based on obstacle location information and obstacle type information, the travel path of the main body of the device 110 is determined.

[0056] In one possible implementation, such as Figure 5 As shown, the acquisition direction of TOF sensor 1 is different from that of vision sensor 2, with vision sensor 2 facing the rear of the device body 110.

[0057] It is understandable that the TOF sensor 1 is oriented towards the direction of the device body 110 and is used to acquire environmental information of the area in front of the device body 110 for positioning, mapping, navigation and obstacle avoidance; the visual sensor 2 is used to acquire environmental information in a different direction from the TOF sensor 1, that is, environmental information of the area in front of the device body 110, for positioning, mapping and navigation.

[0058] Among them, the visual sensor 2 can be oriented towards the rear of the device body 110 to obtain environmental information of the area behind the device body 110, forming observations of the front and oblique rear of the device body 110. The combined use of environmental information of the area in front of the device body 110 and the area oblique rear further improves the positioning and mapping effect.

[0059] The vision sensor 2 can face directly behind the main body 110 of the device. The vision sensor 2 and the TOF sensor 1 are set opposite each other, complementing each other in terms of acquisition direction and type of information acquired.

[0060] In one possible implementation, the acquisition range of the TOF sensor 1 and the acquisition range of the vision sensor 2 for acquiring environmental information do not overlap.

[0061] In this embodiment, the acquisition range of the vision sensor 2 can be located outside the acquisition range of the TOF sensor 1. Taking the area directly in front of the device body 110 as an example and the area directly behind the device body 110 as an example, the acquisition range is avoided, which greatly improves the acquisition range and the coverage of the acquired environmental information.

[0062] In one possible implementation, the acquisition range of the TOF sensor 1 and the acquisition range of the vision sensor 2 for acquiring environmental information partially overlap.

[0063] In this embodiment, part of the acquisition range of the vision sensor 2 can be located within the acquisition range of the TOF sensor 1. Taking the area directly in front of the device body 110 of the TOF sensor 1 and the area to the side and rear of the device body 110 of the vision sensor 2 as an example, the acquisition ranges of the two can overlap, which improves the accuracy of environmental information within the overlapping range.

[0064] It is understandable that the acquisition range of the visual sensor 2 can cover at least one of the rear and side areas of the device body 110, and can also cover the front area. The acquisition range of environmental information can be improved by increasing the number of camera devices 21 and adjusting the shooting coverage angle.

[0065] In one possible implementation, the TOF sensor is installed directly in front of the device body 110. It calculates the distance between the device body 110 and the obstacle by measuring the "time of flight" of signals such as ultrasonic waves, microwaves, and light between the transmitter and the reflector. The TOF sensor 1 generates and captures data containing depth information. The device body 110 avoids obstacles by using the point cloud data of the TOF sensor during movement, thereby achieving navigation, self-localization, obstacle avoidance, and map building.

[0066] Understandably, to more accurately acquire obstacle information in the area in front of the device body 110 and the surface to be cleaned, the TOF sensor 1 is typically positioned directly in front of the device body 110, i.e., at the end of the outer periphery of the device body 110 facing the direction of travel. The TOF sensor 1 generally emits a laser beam in the direction of travel of the device body 110, usually horizontally or horizontally downwards. When the laser beam is projected onto the area in front of the device body 110 and the surface to be cleaned, the outline of the laser beam deforms upon impact with an obstacle. This deformation allows the determination of the obstacle's location. However, due to the limitations of the laser emission angle and the obstruction caused by the device body 110, it is difficult to acquire environmental information outside the area in front of the device body 110 using the TOF sensor 1 positioned at the front. The device body 110 needs to turn to acquire environmental information in other areas, affecting mapping efficiency, mapping quality, and self-localization.

[0067] The vision sensor 2 is located on the top of the device body 110 to reduce the obstruction of the field of view of the vision sensor 2 by the device body 110.

[0068] In one possible implementation, such as Figure 5 As shown, the visual sensor 2 includes a camera device 21. The shooting angle of the visual sensor 2 is tilted upward, and the installation elevation angle of the visual sensor 2 is α, where 0° < α < 90°. It is used to acquire environmental information in the area above the main body of the device 110.

[0069] Because the TOF sensor 1 may have light scattering, multiple reflections, and weak resistance to strong ambient light, it is prone to overexposure in strong light environments, which limits its application. It is more suitable for acquiring environmental information of areas close to the surface to be cleaned.

[0070] The visual sensor 2 can be a binocular camera, including an RGB image acquisition module. By analyzing the differences between the images collected by the two image sensors, the distance between the surrounding environment obstacles and the main body of the device 110 is obtained, thereby realizing the measurement of image information of the surrounding environment and completing the recognition of the surrounding environment.

[0071] As the main body of the device 110 moves in one direction, it can acquire environmental information in front through the TOP sensor and visual information from behind and diagonally upward through the vision sensor 2, thus acquiring environmental information from at least two different directions simultaneously. As the main body of the device 110 moves in the opposite direction, it can acquire environmental information in front through the TOP sensor and visual information from behind and diagonally upward through the vision sensor 2. That is, when the main body of the device 110 moves in two opposite directions, it can acquire two kinds of information from the front and rear of the device 110, and the two kinds of information can also be compensated in terms of height, thereby improving the diversity and coverage of the acquired environmental information. The coverage includes the height and width of the acquired area.

[0072] By using the RGB image acquisition module in conjunction with the TOP sensor 1, the main body of the device 110 can more accurately determine the surrounding environmental information, improve the mapping effect and mapping efficiency, and improve the obstacle avoidance effect and operation effect of the main body 110 of the automatic cleaning device 100.

[0073] In one possible implementation, such as Figure 4 As shown, the vision sensor 2 also includes a protective lens 23, which is used to cover the lens of the camera device 21.

[0074] It is understandable that, such as Figure 6 and Figure 7 As shown, the protective lens 23 covers the front of the lens of the camera device 21, which can prevent dust and water, improve the service life of the camera device 21, and improve the imaging accuracy.

[0075] Among them, the protective lens 23 can be a transparent or colored filter, or it can be made from a single lens or multiple lenses stacked together.

[0076] In one possible implementation, such as Figure 6 and Figure 7 As shown, the vision sensor 2 also includes a mounting base 22, which is connected to the main body 110 of the device, and the camera device 21 is mounted on the mounting base 22.

[0077] It is understood that in this example, the camera device 21 and the protective lens 23 are both mounted on the mounting base 22. The mounting base 22 can be detachably connected to the main body 110 of the equipment through one of the following structures: threaded structure, snap-fit ​​structure, and tenon and mortise structure, so that the camera device 21 can be assembled onto the main body 110 of the equipment for easy assembly and maintenance.

[0078] The camera device 21 can be detachably connected to the fixed base 22 via one of the following: threaded structure, snap-fit ​​structure, or tenon and mortise structure.

[0079] In one possible implementation, such as Figure 6 and Figure 7 As shown, the mounting base 22 includes a base plate 221, and the camera device 21 is mounted on the mounting portion 222 of the base plate 221. The mounting portion 222 is a protruding structure or a groove structure.

[0080] Among them, such as Figure 7 As shown, the mounting part 222 may include a mounting plate 2221, which is obliquely disposed on the substrate 221, and the camera device 21 is disposed on the mounting plate 2221.

[0081] In this embodiment, the mounting portion 222 of the substrate 221 is a protruding structure. The mounting plate 2221 protrudes from the upper surface of the device body 110, and the camera device 21 is mounted on the mounting plate 2221 to reduce the obstruction of the field of view of the camera device 21 by the device body 110 and improve the coverage of the acquisition range.

[0082] In this embodiment, the mounting portion 222 of the substrate 221 is a groove structure, that is, the vision sensor 2 is embedded in the device body 110, the mounting plate 2221 is located in the device body 110, and the camera device 21 is mounted on the mounting plate 2221. By adjusting the angle of the mounting elevation of the camera device 21 and the angle and height of the part of the device body 110 or the fixed base 22 that obstructs the field of view of the camera device 21, the obstruction of the field of view of the camera device 21 is reduced, the coverage of the acquisition range is improved, and the overall height of the device can be reduced, the collision of obstacles with the camera device 21 is reduced, the failure rate caused by impact is reduced, and the service life of the camera device 21 is extended.

[0083] In one possible implementation, such as Figure 5 As shown, the shooting angle of the camera device 21 is tilted upward, that is, the field of view of the camera device 21 faces the horizontal plane, that is, the area above the horizontal plane.

[0084] like Figure 7As shown, the mounting plate 2221 in the recessed mounting portion 222 has a certain angle with the horizontal plane. When the substrate 221 is set horizontally, that is, the mounting plate 2221 and the substrate 221 have a certain angle, the angle between the mounting plate 2221 and the horizontal plane is β, and 0°<β<90°.

[0085] In one possible implementation, the fixed base 22 and the camera device 21 are movably connected, which facilitates disassembly and maintenance. The orientation angle and / or rotation angle of the camera device 21 can also be adjusted to change the field of view to suit the usage needs of different scenarios.

[0086] In one possible implementation, the mounting base 22 is a movable structure, so that the orientation angle and / or rotation angle of the vision sensor 2 are adjustable. By adjusting the relative positions of the components of the mounting base 22, the orientation angle and / or rotation angle of the vision sensor 2 can be adjusted to change the field of view and adapt to the usage requirements of different scenarios.

[0087] By adjusting the orientation angle and rotation angle of the camera device 21 in different ways, the needs of different structures of the fixed base 22 and different connection methods between the camera device 21 and the fixed base 22 can be met.

[0088] Furthermore, the mounting base 22 also includes a connector, through which the camera device 21 is movably connected to the base plate 221, and the orientation angle and / or rotation angle of the camera device 21 can be adjusted.

[0089] The connector may have a through hole through which the camera device 21 passes. The camera device 21 is rotatably connected to the connector and can rotate within the through hole to adjust its rotation angle. The connector is rotatably connected to the fixed base 22 and can rotate horizontally relative to the fixed base 22 to adjust the orientation angle of the camera device 21, thereby adjusting its field of view.

[0090] Furthermore, the mounting base 22 also includes a limiting member, which is disposed on the connector and is used to limit the camera device 21 in the rotation direction of the camera device 21.

[0091] Understandably, since the camera device 21 is rotatable relative to the fixed base 22, during the calibration process, the camera device 21 can be rotated to a suitable position and fixed by the limiting component, thereby improving the reliability of the connection between the camera device 21 and the fixed base 22.

[0092] The device may also include a steering drive unit, which is connected to one or more of the fixed base 22, the camera device 21, the connector, and the limiting member. The steering drive unit is used to drive the camera device 21 to rotate and fix it, adjust the orientation angle and / or rotation angle of the camera device 21, and change the field of view.

[0093] The camera device 21 can move according to the direction of the following device body 110; when the device body 110 turns left or is about to turn left, the camera device 21 turns to the left side of the device body 110; when the device body 110 turns right or is about to turn right, the camera device 21 turns to the right side of the device body 110.

[0094] In one possible implementation, the sensing module further includes a supplementary light connected to the device body 110 for providing supplementary lighting to the vision sensor 2.

[0095] In situations where ambient light is low, supplemental lighting can be provided by supplemental lighting, enabling the camera device 21 to obtain visual information with more appropriate brightness and to more accurately determine the type of obstacle.

[0096] The second aspect of this application, as Figures 3-7 As shown, a cleaning system is provided, including any of the automatic cleaning devices 100 in the first aspect and a base station, the base station being used to provide maintenance for the automatic cleaning device 100.

[0097] The cleaning system provided in this application includes the automatic cleaning device 100 of any of the above technical solutions, and therefore has all the beneficial effects of the automatic cleaning device 100 of any of the above technical solutions, which will not be elaborated here.

[0098] The cleaning system provided in this application embodiment allows the automatic cleaning device 100 to perform cleaning tasks remotely from the base station. When the automatic cleaning device completes cleaning or needs maintenance, it can return to the base station, which can then charge the automatic cleaning device 100, clean the mop, collect dust, or replenish water.

[0099] In one possible implementation, the automatic cleaning device 100 further includes an inertial sensor and a wheel speed sensor. The inertial sensor is used to acquire motion information of the device body 110, and the wheel speed sensor is used to acquire wheel speed information of the device body 110.

[0100] The automated cleaning equipment 100 uses a multi-sensor fusion scheme, combining point cloud information and visual information, for positioning and mapping. The fused sensor information includes TOF point cloud information, visual information, IMU information, and wheel speed sensor information, enabling more accurate determination of the surrounding environment. This improves the obstacle avoidance and operational efficiency of the automated cleaning equipment 100 body 110, ensures positioning accuracy, and reduces costs. The fusion positioning algorithm includes several implementation schemes. A loosely coupled scheme fuses visual, IMU, and wheel speed sensor information to achieve a VSLAM solution; a TOF positioning scheme fuses TOF, IMU, and wheel speed sensor information, with the results from the two subsystems undergoing fusion filtering to obtain the final positioning result; and a tightly coupled scheme directly fuses visual, TOF, IMU, and wheel speed sensor information.

[0101] In one possible implementation, the automatic cleaning device 100 further includes a processor for fusing, locating, and mapping point cloud information, visual information, motion information, and wheel speed meter information.

[0102] The automatic cleaning device 100 also includes a processor and a signal processing module. The processor is connected to the TOF sensor 1 and the vision sensor 2, and the signal processing module is connected to the processor to convert light signals into digital signals, which facilitates the identification of obstacle types based on point cloud information and visual information. The processor performs distance calculation based on the received information to determine the location of obstacles and accurately obtain information about the surrounding environment.

[0103] The processor can also be connected to inertial sensors and wheel speed sensors to facilitate the fusion processing of the above-mentioned information.

[0104] Through the above description of the embodiments, those skilled in the art can clearly understand that this application can be implemented by means of software plus necessary general-purpose hardware platform, or it can be implemented by hardware.

[0105] This embodiment provides a positioning method for automatic cleaning equipment, such as... Figure 8 As shown, this method is applied to the server side of an automatic cleaning device and includes the following steps:

[0106] 101. Obtain the positioning and sensing information of the automatic cleaning equipment.

[0107] The positioning and perception information includes environmental information from different acquisition directions. These different acquisition directions can include directions around the automatic cleaning device, such as the direction in front of the automatic cleaning device, the direction to the left of the device, and the direction diagonally above it. The environmental information refers to the information perceived by the automatic cleaning device about its surrounding environment, such as image information, distance information, sound information, and point cloud information. In this embodiment, positioning and perception information can be acquired by setting various sensors on the automatic cleaning device. Specific sensor types can include, but are not limited to, collision sensors, distance sensors, and cameras. Accordingly, collision sensors can detect whether the automatic cleaning device collides with an object, as well as the intensity and direction of the collision; distance sensors can detect the distance between the automatic cleaning device and obstacles; and cameras can collect images of obstacles in the environment.

[0108] In practical applications, a Time-of-Flight (TOF) sensor can be installed on the automatic cleaning equipment. The TOF sensor is oriented in the direction of travel of the automatic cleaning equipment and is used to acquire point cloud information along the direction of travel of the automatic cleaning equipment. A vision sensor can also be installed on the automatic cleaning equipment. The vision sensor is oriented diagonally above the automatic cleaning equipment and is used to acquire visual information along the diagonally above the automatic cleaning equipment.

[0109] The execution subject in this embodiment can be a positioning device or device of an automatic cleaning equipment, which can be configured on the server side of the automatic cleaning equipment. It can acquire the positioning perception information of the automatic cleaning equipment during the cleaning process, and combine it with environmental information from different acquisition directions to locate the automatic cleaning equipment. Furthermore, the location information obtained can be applied to the cleaning task, such as two-dimensional or three-dimensional mapping, obstacle avoidance, etc.

[0110] 102. Based on the positioning and sensing information, the environmental information from different acquisition directions is fused and positioned to perform cleaning tasks using the location information obtained through fused positioning.

[0111] In this embodiment, during the movement of the automatic cleaning equipment, all sensors work simultaneously. Considering the different sensor acquisition methods, the data acquired by different sensors are inconsistent. Therefore, it is necessary to preprocess the environmental information from different acquisition directions. This preprocessing includes at least time synchronization processing, coordinate transformation processing, data filtering, and feature extraction.

[0112] For the time synchronization process, since different sensors have different data acquisition frequencies, time synchronization can be achieved through timestamps. First, the update frequency of the environmental information collected by different sensors is determined, and the timestamp corresponding to each update is recorded according to the update frequency. Then, environmental information with the same or similar timestamps is combined. For example, point cloud information collected by LiDAR is updated every 100ms, image information collected by a vision sensor is updated every 33ms, and motion information collected by an inertial sensor is updated every 10ms. In this case, the motion information and image information can be combined into point cloud information with the same or similar timestamps based on the timestamps recorded for each update.

[0113] For coordinate transformation, since data acquired by different sensors may be in different coordinate systems, a pre-defined body coordinate system can be used to transform the data acquired by different sensors to a preset coordinate system. For example, the point cloud information acquired by LiDAR is in a Cartesian coordinate system centered on itself, while the image information acquired by the vision sensor is in a pixel coordinate system based on the image plane. In this case, the intrinsic and extrinsic parameters of the vision sensor are used to transform the pixel coordinates to the coordinate system corresponding to the device.

[0114] For the data filtering and feature extraction process, since data acquired by different sensors has different data characteristics, environmental information from different acquisition directions can be filtered and feature extracted based on these different data characteristics. For example, Gaussian filtering can be used to remove noise points from point cloud information, and image filtering can be used to reduce image noise from image information.

[0115] The aforementioned fusion positioning algorithm includes several implementation schemes. The loosely coupled scheme treats the visual sensor and the TOF sensor as independent subsystems for processing. On one hand, visual information, motion information, and wheel speed measurement information are fused to achieve a visual positioning system; on the other hand, point cloud information, motion information, and wheel speed measurement information are fused to achieve a point cloud positioning system. The results of the two subsystems are then fused and filtered to obtain the final positioning result of the device. The tightly coupled scheme directly fuses visual information, point cloud information, motion information, and wheel speed measurement information to obtain the final positioning result of the device.

[0116] In the specific localization fusion process, weighted average algorithm, Cartesian filter algorithm, example filter algorithm, Bayesian estimation algorithm, neural network algorithm, etc. can be used, and no specific limitation is made here.

[0117] It is understandable that the location information obtained by fusion positioning is equivalent to the real-time location of the automatic cleaning equipment in the cleaning scene. This real-time location can be used for different cleaning tasks, including but not limited to path planning and area cleaning, two-dimensional or three-dimensional mapping, navigation, and obstacle avoidance.

[0118] The positioning method for automatic cleaning equipment provided in this application differs from existing methods that use two TOF sensors placed at the front and rear of the robot. This application acquires positioning perception information from the automatic cleaning equipment, which includes environmental information from different acquisition directions. This increases the acquisition direction and types of environmental information, enabling more accurate determination of the surrounding environment. Then, the environmental information from different acquisition directions is fused based on the positioning perception information to perform cleaning tasks using the position information obtained from the fused positioning. This improves the accuracy of information acquisition during the positioning process and ensures positioning precision.

[0119] In practical applications, automatic cleaning equipment includes at least a TOF sensor and a vision sensor. The automatic cleaning equipment provided in this embodiment includes a TOF sensor and a vision sensor. The TOF sensor 1 is installed on the automatic cleaning equipment and faces the direction of travel of the automatic cleaning equipment. It is used to acquire point cloud information along the direction of travel of the automatic cleaning equipment. The vision sensor is installed on the automatic cleaning equipment and is used to acquire visual information in the direction diagonally upward of the automatic cleaning equipment.

[0120] Accordingly, step 101 specifically includes the following steps:

[0121] The point cloud information of the automatic cleaning equipment along its direction of travel is acquired through the TOF sensor.

[0122] The visual sensor acquires visual information of the automatic cleaning device along an upward-sloping direction.

[0123] Accordingly, step 102 specifically includes the following steps:

[0124] The point cloud information and the visual information are fused together based on the positioning and perception information to perform cleaning tasks using the location information obtained from the fused positioning.

[0125] In this embodiment, the acquisition direction of the TOF sensor is different from that of the vision sensor. The TOF sensor faces the direction of travel of the automatic cleaning device and is used to acquire environmental information of the area in front of the automatic cleaning device for positioning, mapping, navigation, and obstacle avoidance. The vision sensor is used to acquire environmental information in a different direction from the TOF sensor, that is, environmental information of the area in front of the automatic cleaning device, for positioning, mapping, and navigation.

[0126] In practical applications, the vision sensor can be oriented diagonally above the automatic cleaning equipment to acquire environmental information about the area diagonally above the automatic cleaning equipment. This forms an observation of the area in front of and diagonally above the automatic cleaning equipment. The combined use of environmental information from the area in front of and diagonally above the automatic cleaning equipment further improves the positioning and mapping effect.

[0127] In practical applications, the visual sensor can be directed towards the rear of the automatic cleaning equipment to acquire environmental information about the area behind the equipment, forming observations of the area in front of and diagonally behind the equipment. The combined use of environmental information from the area in front of and diagonally behind the equipment further improves the positioning and mapping effect.

[0128] Of course, the vision sensor can also be positioned directly behind the automatic cleaning device, opposite to the TOF sensor, thus complementing each other in terms of acquisition direction and type of information.

[0129] Furthermore, considering the deployment orientation of the TOF sensor and the vision sensor on the automatic cleaning equipment, in the above embodiments, such as Figure 9 As shown, prior to step 102, the above method further includes the following steps:

[0130] 201. Detect whether there is an overlapping area between the point cloud information and the visual information.

[0131] 202. If there is an overlapping area between the point cloud information and the visual information, the environmental information within the overlapping area is integrated to ensure that there is no duplicate environmental information in the positioning perception information.

[0132] In one possible implementation, if the TOF sensor and the vision sensor have the same placement on the automatic cleaning device, the environmental information acquired by the TOF sensor and the vision sensor will overlap in an area. For example, both the TOF sensor and the vision sensor are placed in front of the automatic cleaning device.

[0133] For environmental information with overlapping areas, the same or similar environmental information can be used to verify each other. For example, both TOF sensors and vision sensors can detect obstacle information within a certain range in front of automatic cleaning equipment. By comparing whether the measurement results of the two sensors on the position, speed and other information of the same obstacle are consistent, the environmental information of the overlapping area can be verified.

[0134] Specifically, in the process of integrating and processing environmental information within overlapping areas, fusion strategies such as weighted averaging can be used to comprehensively utilize redundant data in the environmental information. For example, the distance measurements of the obstacle ahead by the TOF sensor and the vision sensor are A1 and A2, respectively, with accuracies of B1 and B2. The corresponding weights are assigned to the measurements based on their accuracies, and the distance measurements of the obstacle ahead by the automatic cleaning equipment are obtained by weighted summation.

[0135] In one possible implementation, if the TOF sensor and the vision sensor are positioned differently on the automatic cleaning device, then the TOF sensor and the vision sensor will acquire environmental information in areas that do not overlap. For example, the TOF sensor may be positioned in front of the automatic cleaning device, and the vision sensor may be positioned behind the automatic cleaning device.

[0136] It should be noted that the layout and orientation of the TOF sensor and the vision sensor on the automatic cleaning equipment can be changed by adjusting the number, angle, and position. For example, the acquisition orientation can be increased by increasing the number of TOF sensors, the acquisition orientation can be expanded by adjusting the angle of the vision sensor, and the acquisition orientation can be changed by adjusting the position of the TOF sensor and / or the vision sensor.

[0137] Understandably, to more accurately acquire information about obstacles in front of automated cleaning equipment and on the surface to be cleaned, Time-of-Flight (TOF) sensors are typically positioned directly in front of the equipment, i.e., on the outer perimeter facing the direction of travel. TOF sensors generally emit laser light in the direction of travel, usually horizontally or tilted downwards. The laser beam is projected onto the area in front of the equipment and the surface to be cleaned. When the laser beam hits an obstacle, the outline of the projected beam deforms, and this deformation determines the obstacle's position. However, due to the limitations of the laser emission angle and the obstruction caused by the automated cleaning equipment, it is difficult to acquire environmental information beyond the area in front using a TOF sensor positioned at the front of the equipment. The equipment needs to turn to acquire environmental information from other areas, affecting mapping efficiency, mapping quality, and self-localization. Therefore, adding a vision sensor to the automated cleaning equipment allows it to acquire environmental information including the area in front and even more areas, increasing the directions of environmental information acquisition and improving the accuracy of the equipment's localization.

[0138] Furthermore, the visual sensor can be a binocular camera, including an RGB image acquisition module. By analyzing the differences between the images collected by the two image sensors, the distance between the surrounding obstacles and the automatic cleaning equipment can be obtained, thereby realizing the measurement of image information of the surrounding environment and thus completing the recognition of the surrounding environment.

[0139] In one feasible application scenario, as the automatic cleaning device moves in one direction, it can acquire environmental information from the front using a Time-of-Flight (TOF) sensor and visual information from the rear (diagonally upward) using a vision sensor, thus simultaneously acquiring environmental information from at least two different directions. Similarly, as the automatic cleaning device moves in the opposite direction, it can acquire environmental information from the front using a TOF sensor and visual information from the rear (diagonally upward) using a vision sensor. In other words, when the automatic cleaning device moves in two opposite directions, it can acquire both front and rear information, and the two types of information can be compensated for in height, improving the diversity and coverage of the acquired environmental information. The coverage includes both the height and width of the acquired area.

[0140] Correspondingly, by using the RGB image acquisition module in conjunction with the TOF sensor, the automatic cleaning equipment can more accurately determine the surrounding environmental information, improve the mapping effect and mapping efficiency, and enhance the obstacle avoidance and operation effects of the automatic cleaning equipment.

[0141] In practical applications, automatic cleaning equipment also includes inertial sensors and wheel speed sensors. Accordingly, step 101 specifically includes the following steps:

[0142] The motion information of the automatic cleaning equipment during its movement is obtained through the inertial sensor;

[0143] The wheel speed sensor acquires wheel speed information during the movement of the automatic cleaning equipment.

[0144] When fusion localization uses a loosely coupled approach, specifically, in the above embodiments, such as Figure 10 As shown, step 102 includes the following steps:

[0145] 301. Based on the positioning perception information, the visual information, the motion information, and the wheel speed meter information are fused together to obtain visual-inertial fusion information.

[0146] 302. Based on the positioning and perception information, the point cloud information, the motion information, and the wheel speed meter information are fused together to obtain point cloud inertial fusion information.

[0147] 303. Perform a third fusion positioning by combining the visual inertial fusion information with the point cloud inertial fusion information, and use the position information obtained by the fusion positioning to perform the cleaning task.

[0148] When the fusion positioning uses a tightly coupled method, specifically, in the above embodiment, step 102 includes the following steps:

[0149] The visual information, motion information, pose information and wheel speed information are fused based on the positioning and perception information to perform cleaning tasks using the location information obtained from the fused positioning.

[0150] In this embodiment, the automatic cleaning equipment uses point cloud information and visual information together, employing a multi-sensor fusion scheme for positioning and mapping. The fused sensor information includes TOF point cloud information, visual information, motion information, wheel speed measurement information, etc., which can more accurately determine the environmental information around the automatic cleaning equipment, improve the obstacle avoidance effect and operation effect of the automatic cleaning equipment, ensure positioning accuracy, and reduce costs.

[0151] Specifically, in the process of performing the first localization fusion of visual information, motion information, and wheel speed measurement information based on the localization perception information to obtain visual-inertial fusion information, the visual information, motion information, and wheel speed measurement information can be synchronized in time according to the timestamp corresponding to the localization perception information, so that the visual information, motion information, and wheel speed measurement information are in the same time dimension. On the basis of the same time dimension, the motion information and wheel speed measurement information are weighted and fused using the visual pose information of the visual sensor to obtain the pose information after inertial and wheel speed measurement fusion. Here, the visual pose information is obtained by motion estimation of the feature points matched in adjacent image frames in the visual information. Using the pose information after inertial and wheel speed measurement fusion as the predicted value and the visual information as the observed value, the pose estimation is updated through a filtering algorithm to obtain the visual-inertial fusion information.

[0152] Understandably, visual-inertial fusion information combines information from visual sensors and inertial measurement units to estimate the motion state of automated cleaning equipment, such as position, speed, and attitude. Specifically, visual sensors capture environmental images and use feature extraction and matching algorithms to obtain relative motion information between different frames. Inertial sensors and wheel speed sensors measure acceleration using accelerometers and angles using gyroscopes, and estimate the motion state of the automated cleaning equipment based on integration and other calculations.

[0153] In visual positioning systems, inertial sensors, which provide high-frequency motion information, play a crucial role in situations where visual information is obstructed or blurred, thus suppressing the cumulative error of the visual positioning system. Typically, motion information is first used to extract and match feature points to obtain relative position change information based on motion features. Then, visual information is combined to correct and supplement this relative position change information based on motion features.

[0154] Specifically, in the process of performing a second positioning fusion of point cloud information, motion information, and wheel speed measurement information based on positioning and sensing information to obtain point cloud inertial fusion information, the point cloud information, motion information, and wheel speed measurement information can be synchronized in time according to the timestamps corresponding to the positioning and sensing information, so that the point cloud information, motion information, and wheel speed measurement information are in the same time dimension. Based on the same time dimension, the motion information and wheel speed measurement information are weighted and fused using the point cloud pose information of the TOF sensor to obtain the pose information after inertial and wheel speed measurement fusion. Here, the point cloud pose information is obtained by matching the preset coordinate points in the point cloud information with known map information. Using the pose information after inertial and wheel speed measurement fusion as the predicted value and the motion information as the observed value, the pose estimation is updated through a filtering algorithm to obtain the point cloud inertial fusion information.

[0155] Understandably, point cloud inertial fusion information incorporates information from Time-of-Flight (TOF) sensors and inertial measurement units to estimate the distance between the automated cleaning equipment and obstacles. Specifically, TOF calculates the distance to the target object by emitting light pulses and measuring the time it takes for the light pulses to travel from emission to reflection. Inertial sensors and wheel speed sensors measure acceleration using accelerometers and angles using gyroscopes. Based on integration and other calculations, the motion state of the automated cleaning equipment is estimated.

[0156] In a point cloud positioning system, a distance map of the surrounding environment can be constructed using point cloud information measured by multiple TOF sensors or a single TOF sensor at different positions and angles. By continuously acquiring point cloud data and comparing and matching it with previous data, the positional changes of the automatic cleaning equipment and the position and shape of objects in the environment can be estimated, thereby achieving real-time positioning and map construction.

[0157] It should be noted that because TOF sensors can directly provide distance information to surrounding objects, they do not need to indirectly infer distance through complex feature extraction and matching processes like visual sensors, making them more suitable for near-field environmental perception.

[0158] Specifically, in the process of performing third-stage fusion positioning by combining visual-inertial fusion information and point cloud inertial fusion information to execute cleaning tasks based on the location information obtained through fusion positioning, the visual-inertial fusion information and point cloud inertial fusion information can be synchronized in time according to the timestamp corresponding to the positioning perception information, so that the visual-inertial fusion information and point cloud inertial fusion information are in the same time dimension. Based on the same time dimension, the visual fusion information is fused into the point cloud inertial fusion information with the corresponding timestamp according to the visual-inertial pose information of the visual-inertial fusion information, so that the cleaning task can be executed based on the location information obtained through fusion. Here, the visual fusion factor is obtained by motion estimation of adjacent image frames in the visual-inertial fusion information.

[0159] Understandably, by integrating visual positioning systems and point cloud positioning systems, the visual positioning system can accurately estimate the position and pose of automatic cleaning equipment in areas rich in visual features, while the point cloud positioning system can determine the position of the equipment by relying on the distance information of TOF sensors in areas where visual features are missing or unclear, thereby achieving comprehensive and accurate positioning.

[0160] In map building scenarios, by integrating visual positioning systems and point cloud positioning systems, higher quality maps can be generated. By combining the visual positioning system for extracting and matching environmental features with the point cloud system for accurately measuring distance information, more accurate and detailed environmental maps can be constructed.

[0161] Furthermore, as Figures 8-10 In a specific implementation of the method, this application provides a positioning device for an automatic cleaning equipment, such as... Figure 11 As shown, the device includes: an acquisition unit 41 and a positioning unit 42.

[0162] Acquisition unit 41 is used to acquire positioning perception information of automatic cleaning equipment, wherein the positioning perception information includes environmental information in different acquisition directions;

[0163] The positioning unit 42 is used to fuse environmental information from different acquisition directions based on the positioning perception information, so as to perform cleaning tasks using the location information obtained by the fused positioning.

[0164] The positioning device for automatic cleaning equipment provided in this application embodiment differs from the existing method of positioning automatic cleaning equipment using two TOF sensors placed at the front and rear of the robot. This application acquires positioning perception information of the automatic cleaning equipment, which includes environmental information from different acquisition directions. This increases the acquisition direction and types of environmental information, enabling more accurate determination of the surrounding environment. Then, the environmental information from different acquisition directions is fused and positioned based on the positioning perception information. The cleaning task is then performed using the position information obtained from the fused positioning, improving the accuracy of information acquisition during the positioning process of the automatic cleaning equipment and ensuring positioning precision.

[0165] In specific application scenarios, the automatic cleaning device includes at least a TOF sensor and a vision sensor, and the acquisition unit is specifically used for:

[0166] The point cloud information of the automatic cleaning equipment along the direction of travel is obtained through the TOF sensor;

[0167] The visual sensor acquires visual information of the automatic cleaning equipment along an upward-sloping direction;

[0168] Accordingly, the positioning unit is specifically used for:

[0169] The point cloud information of the automatic cleaning equipment along the direction of travel is obtained through the TOF sensor;

[0170] The visual sensor acquires visual information of the automatic cleaning device along an upward-sloping direction.

[0171] In specific application scenarios, the device further includes:

[0172] The detection unit is used to detect whether there is an overlapping area between the point cloud information and the visual information before fusing the point cloud information and the visual information according to the positioning perception information to perform the cleaning task based on the location information obtained by the fused positioning.

[0173] An integration unit is used to integrate environmental information within the overlapping area if the point cloud information and the visual information overlap, so that there is no duplicate environmental information in the positioning perception information.

[0174] In specific application scenarios, the automatic cleaning equipment further includes an inertial sensor and a wheel speed sensor, and the acquisition unit is specifically used for:

[0175] The motion information of the automatic cleaning equipment during its movement is obtained through the inertial sensor;

[0176] The wheel speed sensor acquires wheel speed information during the movement of the automatic cleaning equipment.

[0177] In specific application scenarios, when fusion positioning uses a loosely coupled approach, the positioning unit is specifically used for:

[0178] Based on the positioning and perception information, the visual information, the motion information, and the wheel speed meter information are fused together to obtain visual-inertial fusion information;

[0179] The point cloud information, motion information, and wheel speed meter information are fused together using the positioning and sensing information to obtain point cloud inertial fusion information.

[0180] The visual-inertial fusion information and the point cloud inertial fusion information are combined for a third fusion positioning, and the cleaning task is performed using the position information obtained from the fusion positioning.

[0181] In specific application scenarios, the positioning unit is further used for:

[0182] The visual information, motion information and wheel speed meter information are synchronized in time according to the timestamp corresponding to the positioning and sensing information, so that the visual information, motion information and wheel speed meter information are in the same time dimension;

[0183] Based on the same time dimension, the motion information and the wheel speed measurement information are weighted and fused using the visual pose information of the visual sensor to obtain the pose information after the inertial and wheel speed measurement are fused. The visual pose information is obtained by motion estimation of the feature points matched in adjacent image frames in the visual information.

[0184] Using the pose information fused from the inertial and wheel speed measurements as the predicted value and the visual information as the observed value, the pose estimation is updated through a filtering algorithm to obtain visual-inertial fusion information.

[0185] In specific application scenarios, the positioning unit is further used for:

[0186] The point cloud information, motion information and wheel speed meter information are synchronized in time according to the timestamp corresponding to the positioning and sensing information, so that the point cloud information, motion information and wheel speed meter information are in the same time dimension;

[0187] Based on the same time dimension, the motion information and wheel speed measurement information are weighted and fused using the point cloud pose information of the TOF sensor to obtain the pose information after the inertial and wheel speed measurement are fused. The point cloud pose information is obtained by matching the preset coordinate points in the point cloud information with known map information.

[0188] Using the pose information fused from the inertial and wheel speed sensors as the predicted value and the point cloud information as the observed value, the pose estimation is updated through a filtering algorithm to obtain the point cloud inertial fusion information.

[0189] In specific application scenarios, the positioning unit is further used for:

[0190] The visual-inertial fusion information and the point cloud inertial fusion information are synchronized in time according to the timestamp corresponding to the positioning and sensing information, so that the visual-inertial fusion information and the point cloud inertial fusion information are in the same time dimension.

[0191] Based on the same time dimension, the visual fusion information is fused into the point cloud inertial fusion information with the corresponding timestamp according to the visual inertial pose information of the visual inertial fusion information, so as to perform a cleaning task through the position information obtained by fusion. The visual fusion factor is obtained by motion estimation of adjacent image frames in the visual inertial fusion information.

[0192] In specific application scenarios, when fusion positioning uses a tightly coupled approach, the positioning unit is specifically used for:

[0193] The visual information, motion information, pose information and wheel speed information are fused based on the positioning and perception information to perform cleaning tasks using the location information obtained from the fused positioning.

[0194] It should be noted that other corresponding descriptions of the functional units involved in the positioning device of the automatic cleaning equipment provided in this embodiment can be found in [reference]. Figures 1-7 The corresponding description in [the document] will not be repeated here.

[0195] Based on the above, Figures 8-10 Accordingly, this application embodiment also provides a storage medium storing a computer program thereon, which, when executed by a processor, implements the above-described method. Figures 8-10 The positioning method of the automatic cleaning equipment shown.

[0196] Based on this understanding, the technical solution of this application can be embodied in the form of a software product. This software product can be stored in a non-volatile storage medium (such as a CD-ROM, USB flash drive, or portable hard drive), and includes several instructions to cause a computer device (such as a personal computer, server, or network device) to execute the methods described in the various implementation scenarios of this application.

[0197] Based on the above, Figures 8-10 The method shown, and Figure 11 To achieve the above objectives, this application also provides a physical device for locating an automatic cleaning device, as illustrated in the virtual device embodiment. Specifically, this physical device can be a computer, smartphone, tablet, smartwatch, server, or network device, etc. The physical device includes a storage medium and a processor; the storage medium stores a computer program; the processor executes the computer program to achieve the above-described objectives. Figures 8-10 The positioning method of the automatic cleaning equipment shown.

[0198] Optionally, the physical device may also include a user interface, a network interface, a camera, radio frequency (RF) circuitry, sensors, audio circuitry, a Wi-Fi module, etc. The user interface may include a display screen, input units such as a keyboard, etc., and optional user interfaces may also include USB interfaces, card reader interfaces, etc. The network interface may optionally include standard wired interfaces, wireless interfaces (such as Wi-Fi interfaces), etc.

[0199] In an exemplary embodiment, see Figure 12The aforementioned physical device includes a communication bus, a processor, a memory, and a communication interface. It may also include input / output interfaces and a display device. The various functional units can communicate with each other via the bus. The memory stores computer programs, and the processor executes the programs stored in the memory to perform the painting mounting method described in the above embodiments.

[0200] Those skilled in the art will understand that the physical device structure for positioning an automatic cleaning device provided in this embodiment does not constitute a limitation on the physical device, and may include more or fewer components, or combine certain components, or have different component arrangements.

[0201] The storage medium may also include an operating system and a network communication module. The operating system is a program that manages the hardware and software resources of the physical device for processing store search information, supporting the operation of the information processing program and other software and / or programs. The network communication module is used to enable communication between the various components within the storage medium, as well as communication with other hardware and software within the information processing physical device.

[0202] In the description of this specification, the terms "one embodiment," "some embodiments," "specific embodiment," etc., refer to a specific feature, structure, material, or characteristic described in connection with that embodiment or example, which is included in at least one embodiment or example of this application. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples.

[0203] The above are merely preferred embodiments of this application and are not intended to limit this application. Various modifications and variations can be made to this application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the protection scope of this application.

[0204] In view of the detailed description above, these and other changes can be made to these embodiments, and this written description includes embodiments of the best mode disclosed in this application. The patent scope of this application is defined by the claims, which are not limited by this disclosure, and the protection scope of this application is not limited thereto. Any equivalent substitutions or modifications made by those skilled in the art within the scope disclosed in this application, based on the technical solutions and concepts of this application, shall fall within the protection scope of this application.

Claims

1. An automatic cleaning device, characterized in that, It includes a main body of the device and a sensing module, wherein the sensing module includes: A TOF sensor is mounted on the main body of the device and faces the direction of travel of the main body of the device, and is used to acquire point cloud information along the direction of travel of the main body of the device. A vision sensor, which is disposed on the main body of the device, is used to acquire visual information in an obliquely upward direction on the main body of the device.

2. The automatic cleaning equipment according to claim 1, characterized in that, The acquisition direction of the TOF sensor is different from that of the vision sensor; The visual sensor is positioned facing the rear of the main body of the device.

3. The automatic cleaning equipment according to claim 1, characterized in that, The acquisition range of the TOF sensor and the acquisition range of the vision sensor for acquiring environmental information have no overlapping area; or, The acquisition range of the TOF sensor and the acquisition range of the vision sensor for acquiring environmental information partially overlap.

4. The automatic cleaning equipment according to any one of claims 1-3, characterized in that, The visual sensor is located inside the top of the main body of the device.

5. The automatic cleaning equipment according to claim 4, characterized in that, The visual sensor includes: A camera device, wherein the installation elevation angle of the camera device is in the range of 0° to 90°.

6. The automatic cleaning equipment according to claim 5, characterized in that, The vision sensor also includes: A protective lens, used to cover the lens of the camera device.

7. The automatic cleaning equipment according to claim 5 or 6, characterized in that, The visual sensor also includes a mounting base, which is connected to the main body of the device, and the camera device is mounted on the mounting base.

8. The automatic cleaning equipment according to claim 7, characterized in that, The fixing base includes: The substrate, wherein the camera device is mounted on the mounting portion of the substrate, the mounting portion being a raised structure or a groove structure.

9. The automatic cleaning equipment according to claim 8, characterized in that, The mounting unit includes: Mounting plate, which is inclinedly disposed on the base plate, and camera device is disposed on the mounting plate.

10. The automatic cleaning equipment according to claim 8, characterized in that, The fixed base and the camera device are movably connected.

11. The automatic cleaning equipment according to claim 8, characterized in that, The mounting base is a movable structure, allowing the orientation angle and / or rotation angle of the visual sensor to be adjusted.

12. The automatic cleaning equipment according to claim 8, characterized in that, The mounting base also includes: A connector is provided, through which the camera device is movably connected to the substrate, and the orientation angle and / or rotation angle of the camera device can be adjusted via the connector.

13. A cleaning system, characterized in that, include: The automatic cleaning equipment as described in any one of claims 1-12; A base station, which is used to provide maintenance for the automatic cleaning equipment.

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