CN116917826A

CN116917826A - automatic working system

Info

Publication number: CN116917826A
Application number: CN202280015461.9A
Authority: CN
Inventors: 伊曼纽尔·康蒂; 兰彬财; 何爱俊; 汪应龙
Original assignee: Positec Power Tools Suzhou Co Ltd
Current assignee: Positec Power Tools Suzhou Co Ltd
Priority date: 2021-06-30
Filing date: 2022-06-30
Publication date: 2023-10-20
Also published as: WO2023274339A1

Abstract

The application provides an automatic working system, comprising: a self-moving device that moves and/or works on a work surface defined by a work boundary; the self-mobile device comprises a surface identification device configured to directly identify material information of a working surface; a position acquisition device configured to acquire position information from the mobile device and/or position information between the mobile device and at least part of the working boundary; control means configured to control the movement and/or operation of the self-moving device on the work surface; and the judging device is configured to judge whether the self-mobile equipment reaches the working boundary, and the control device controls the self-mobile equipment to walk along the working boundary or turn into the working surface if the self-mobile equipment is judged to reach the working boundary according to the position information acquired by the position acquisition device and at least part of the working boundary under the condition that the self-mobile equipment is judged to not reach the working boundary according to the material information identified by the surface identification device.

Description

Automatic working system

Technical Field

The application relates to the technical field, in particular to an automatic working system.

Background

The self-moving device can move and/or work on a work surface defined by a work boundary without manual manipulation. At present, a manner of identifying a working boundary by a surface identifying device that can determine whether a self-mobile device reaches the working boundary by identifying material information of a working surface, for example, has appeared. However, the surface recognition device has a problem that the working boundary cannot be recognized in a region where the material information inside and outside the working boundary is not significantly changed.

Disclosure of Invention

In view of the above, the present application provides an automatic working system capable of improving the accuracy of boundary recognition of a self-mobile device.

In a first aspect, an automated work system is provided, the automated work system comprising: a self-moving device that moves and/or works on a work surface defined by a work boundary, the self-moving device being configured with: a surface recognition device configured to directly recognize material information of the working surface; a position acquisition device configured to acquire position information of the self-moving device and/or position information between the self-moving device and at least part of the working boundary; control device, with surface recognition device and position collection device signal link, control device is configured to control from mobile device to move and/or work on the work surface that the working boundary prescribes, still be configured with on the mobile device: and the judging device is configured to judge whether the self-moving equipment reaches the working boundary, and the control device controls the self-moving equipment to walk along the working boundary or turn into the working surface if the self-moving equipment is judged to reach the working boundary according to the position information acquired by the position acquisition device and the at least partial working boundary under the condition that the self-moving equipment is judged not to reach the working boundary according to the material information identified by the surface identification device.

Optionally, as an implementation, the at least part of the working boundary is a non-closed working boundary.

Optionally, as an implementation manner, the at least part of the working boundary is provided with a boundary device to form the working boundary, and the self-mobile device includes: and the signal detection sensor is used for detecting a virtual signal sent by the boundary device and judging whether the self-mobile equipment reaches the working boundary according to the virtual signal.

Optionally, as an implementation manner, the surface recognition device includes at least one of the following: radar sensor, ultrasonic sensor, capacitive sensor, image acquisition module.

Optionally, as an implementation manner, when the surface identifying device is an image acquisition module, the surface identifying device is configured to identify material information of the working surface according to the following manner: shooting a current image of the position of the self-mobile device by using the image acquisition module; and inputting the current image into an artificial intelligent model to identify the material information of the working surface.

Optionally, as an implementation manner, the position acquisition device includes at least one of the following: ultrasonic sensor, radar sensor, optical sensor, ultra-wideband UWB sensor, inertial navigation sensor, satellite positioning module, image acquisition module.

Optionally, as an implementation manner, the at least part of working boundary includes a boundary map, and correspondingly, the position acquisition device is configured to acquire position information between the self-mobile device and the at least part of working boundary, including: acquiring relative position information between the current position of the self-mobile device and the boundary map; the judging module is configured to judge that the self-mobile device reaches the working boundary according to the relative position information between the current position of the self-mobile device and the boundary map.

Optionally, as an implementation manner, when the position acquisition device is a satellite positioning module, the satellite positioning module is detachably or fixedly installed on the self-mobile device, and accordingly, the satellite positioning module is configured to acquire the boundary map according to the following manner: and acquiring the position information of a plurality of position points in the at least partial working boundary by utilizing the satellite positioning module, and obtaining the boundary map according to the position information of the plurality of position points.

Optionally, as an implementation manner, the satellite positioning module has a satellite positioning error, and the satellite positioning error is greater than or equal to an identification error of the surface identification device.

Optionally, as an implementation manner, the automatic working system further includes: an intelligent device having a location acquisition function, the intelligent device being configured to acquire the boundary map as follows: and acquiring the position information of a plurality of position points in the at least partial working boundary by using the intelligent equipment, and obtaining the boundary map according to the position information of the plurality of position points.

Optionally, as an implementation manner, the smart device has a device positioning error, where the device positioning error is greater than or equal to a positioning error of the surface recognition device.

Optionally, as an implementation manner, the determining that the self-mobile device reaches the working boundary according to the location information acquired by the location acquisition device and the at least part of the working boundary includes: expanding the boundary map to obtain an expanded boundary; and judging that the self-mobile equipment reaches the working boundary according to the position information acquired by the position acquisition device and the expansion boundary.

Optionally, as an implementation, if the boundary map is obtained by the position acquisition device, the distance between the extended boundary and the boundary map is equal to the positioning error of the position acquisition device or is equal to twice the positioning error of the position acquisition device.

Optionally, as an implementation manner, if the boundary map is obtained by using a smart device, the distance between the extended boundary and the boundary map is equal to a positioning error of the position acquisition device, or is equal to a device positioning error of the smart device, or is equal to a sum of the positioning error of the position acquisition device and the device positioning error of the smart device.

Optionally, as an implementation manner, the determining that the self-mobile device reaches the working boundary according to the location information acquired by the location acquisition device and the at least part of the working boundary includes: contracting the boundary map to obtain a contracted boundary; and judging that the self-mobile equipment reaches the working boundary according to the position information acquired by the position acquisition device and the contraction boundary.

Optionally, as an implementation, if the boundary map is obtained by the position acquisition device, the distance between the contracted boundary and the boundary map is equal to the positioning error of the position acquisition device or is equal to twice the positioning error of the position acquisition device.

Optionally, as an implementation manner, if the boundary map is obtained by using an intelligent device, the distance between the contracted boundary and the boundary map is equal to the positioning error of the position acquisition device, or is equal to the device positioning error of the intelligent device, or is equal to the sum of the positioning error of the position acquisition device and the device positioning error of the intelligent device.

Based on the technical scheme, the boundary recognition can be performed by using the surface recognition device. In the case where the boundary is not recognized by the surface recognition device, for example, when the material information changes in the regions on both sides of the boundary are not obvious, or when the surface recognition device fails, the boundary recognition may be performed by using the position acquisition device. The surface recognition device and the position acquisition device are matched with each other and act together, so that the boundary recognition accuracy of the self-moving equipment is improved.

Drawings

Fig. 1 is a schematic diagram of an automatic working system according to an embodiment of the present application.

Fig. 2 is a schematic structural diagram of an intelligent mower according to an embodiment of the present application.

Fig. 3 is a schematic block diagram of another automatic working system provided by an embodiment of the present application.

Fig. 4 is a schematic structural diagram of a self-mobile device according to an embodiment of the present application.

Fig. 5 is a schematic diagram of several possible locations of a boundary map provided by an embodiment of the present application.

Detailed Description

The following description of the embodiments of the present application will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present application, but not all embodiments.

The self-moving equipment in the embodiment of the application can be an outdoor robot, for example, can be intelligent equipment with an automatic walking function such as an intelligent mower, an intelligent snow sweeper, an intelligent floor cleaning vehicle and the like.

Taking a smart mower as an example, the robotic work system 100 shown in fig. 1 may include a smart mower 1, and a boundary 6, the boundary 6 may be used to define a work area (or work surface) of the smart mower 1. The boundary line 6 may be a boundary line between a lawn area and a non-lawn area. The intelligent mower 1 may operate within an area defined by a boundary 6, such as automatically performing mowing operations, and the boundary 6 may separate an operating area 7 from a non-operating area.

In the working area of the intelligent mower 1, there may also be some obstacle areas affecting the operation of the intelligent mower, which may include, for example, an area 3 where a house is located, a pit area 4, an area 5 where a tree is located, etc. The intelligent mower 1 can bypass the areas to work in the working process.

The automatic working system 100 may further comprise a charging station 2 for recharging the intelligent mower 1. The intelligent mower 1 can automatically execute work tasks without supervision, and can automatically return to the charging station 2 for charging when the electric energy is insufficient.

The charging station 2 may be located on the boundary line 6, i.e. a part of the charging station 2 is located in the working area 7 and a part in the non-working area; or the charging station 2 may be located entirely in the working area 7; still alternatively, the charging station 2 may also be located entirely in the non-operating area.

Fig. 2 shows a schematic structural diagram of an intelligent mower. The robotic lawnmower may include a housing 16, a movement module, a task execution module, an energy module, a control device, and the like.

The mobile module is used for driving the intelligent mower to walk in the working area 7. The mobile module generally comprises a wheel set mounted on the intelligent mower and a travel motor for driving the wheel set to travel and steer. The wheel set comprises a driving wheel 14 connected to the travelling motor and an auxiliary wheel 15 mainly acting as an auxiliary support. The auxiliary wheel 15 may also be referred to as driven wheel, and the auxiliary wheel 15 may be a universal wheel. The number of driving wheels 14 may be 2, one on each side of the housing 16. The number of the walking motors can be 2, and the walking motors are respectively connected with the two driving wheels. The number of auxiliary wheels may be one or two. When the number of auxiliary wheels 15 is 2, the 2 auxiliary wheels 15 may be located at both sides of the front of the intelligent mower. The auxiliary wheel 15 is not connected with a walking motor, but can be driven to roll and walk when the intelligent mower is supported to walk. Through the arrangement of the structure, the intelligent mower can flexibly walk and turn in a working area under the control of the control device.

The task execution module may include a cutting assembly that may be used to perform mowing work. The cutting assembly may be provided on the chassis of the intelligent mower, which may be positioned between the drive wheel 14 and the auxiliary wheel 15.

The energy module may include a battery pack for providing electrical energy for movement and operation of the intelligent mower 1. For example, the energy module may provide electrical energy to the motor to enable the motor to drive the cutting assembly to operate.

The control device can be electrically connected with the mobile module, the task execution module and the energy module to control the mobile module to drive the intelligent mower 1 to move and control the task execution module to execute a work task.

The control device can be used for controlling the intelligent mower to automatically walk, work, supplement energy and the like, and is a core component of the intelligent mower. The functions performed by the control device may include controlling the task execution module to start or stop working, generating a walking path and controlling the movement module to walk according to the path, determining the power of the energy module and timely indicating the intelligent mower to return to the docking station and automatically docking and charging, controlling the mower to return to the working area when detecting that the intelligent mower is at a boundary position or a non-working area, and the like.

With continued reference to fig. 1, boundary 6 in fig. 1 may be understood as a working boundary. There is currently a way to identify the working boundary by a visual sensor. The vision sensor can judge whether the self-mobile device reaches the working boundary or not by identifying the material information of the working surface. For example, using a robotic lawnmower as an example, the surface recognition device may identify grass information to determine whether the self-moving device has reached a working boundary.

However, for the areas with insignificant material information changes inside and outside the working boundary, the surface recognition device cannot accurately recognize the working boundary, thereby affecting the operation of the self-mobile device. Taking an intelligent mower as an example, when grass is on both sides of the boundary, the surface recognition device cannot recognize the working boundary.

Based on this, the embodiment of the present application provides an automatic working system 300, which can improve the accuracy of identifying the working boundary from the mobile device.

As shown in fig. 3 and 4, the automated work system 300 may include a self-moving device 310, where the self-moving device 310 may move and/or work on a work surface defined by a work boundary. The self-mobile device 310 may be any of the self-mobile devices described above.

The self-mobile device 310 may be provided with a surface recognition device 311, a position acquisition device 312, a control device 313 and a judgment module 314.

The surface recognition device 311 may be the surface recognition device described above. The surface recognition device 311 can recognize material information of the work surface. For example, the surface recognition device can recognize a change between the material information of the working surface and the material information of the non-working surface. The surface identification means may be at least one of: radar sensor, ultrasonic sensor, capacitive sensor, image acquisition module.

The radar sensor and the ultrasonic sensor may transmit wave signals outward and identify material information by receiving the reflected wave signals. The wave signal may be an optical signal or an ultrasonic signal, and the reflected wave signal may include a reflected ultrasonic signal, a reflected optical signal, a refracted optical signal, or the like.

For capacitive sensors, the capacitive sensor may be mounted on the self-moving device. The capacitive sensor may sense a capacitance value between the self-mobile device and ground. During the movement from the mobile device, the capacitance value will also change if the material information changes. Taking the example of a smart mower, it is assumed that the working surface of the smart mower includes grass, the non-working surface does not include grass, or the non-working surface includes a road surface, an obstacle, or the like. The capacitance sensed by the capacitive sensor at the working surface is different from the capacitance sensed at the non-working surface due to the presence of grass on the working surface. The self-mobile device can judge whether the intelligent mower reaches the working boundary according to the difference of the capacitance values.

For an image acquisition module, the image acquisition module may be configured to identify texture information of the work surface as follows: shooting a current image of the position of the mobile equipment by using an image acquisition module; the current image is input into an artificial intelligence (Artificial Intelligence, AI) module to identify material information of the work surface.

The artificial intelligence model may be trained from sample images. Before the self-mobile device works, the AI model can be trained by the sample image, so that the trained model can accurately identify the characteristics of each object in the image. The training process may include, for example: acquiring a sample image, which may include an image of a working area and/or an image of a non-working area; and inputting the sample image into the first AI model for training to obtain a second AI model. The first AI model may be an initial AI model and the second AI model may be a target AI model after training. After training is completed, the self-mobile device may identify the current image using the second AI model.

Taking an intelligent mower as an example, the key features may include features of grass, and the image acquisition module may identify a grass area and a non-grass area using the AI model. For example, if the image acquisition module identifies a feature of the current image that includes grass, it may be determined that the intelligent mower is within the work area; if the vision module identifies a feature in the current image that does not include grass, or that includes a road surface or obstacle, it may be determined that the intelligent mower is within a non-operational area, or that an operational boundary is reached.

The manner in which the AI model identifies the material information is not particularly limited in the embodiment of the present application. For example, the AI model may identify material information by way of semantic segmentation. Semantic segmentation may refer to classifying each pixel in the current image, determining the class of each pixel, and thus performing region division to identify individual objects in the current image.

The location acquisition device 312 may be configured to acquire location information from the mobile device and/or from location information between the mobile device and at least a portion of the working boundary. The location information between the self-mobile device and at least part of the working boundary may here refer to relative location information between the self-mobile device and at least part of the working boundary. At least a portion of the working boundary may be a closed working boundary or a non-closed working boundary. For example, for an area where the boundary between the working area and the non-working area is relatively clear, the working boundary may not be set in the area, but only in an area where the boundary is not clear, thereby forming a non-closed working boundary. For another example, a closed working boundary may be provided regardless of whether the boundary between the working area and the non-working area is apparent.

Alternatively, the position acquisition device may construct a boundary map of the self-mobile device before the self-mobile device works, in addition to acquiring position information during the self-mobile device works. In this way, the self-mobile device can use the boundary map for boundary identification during operation.

The position acquisition device 312 may include at least one of the following: ultrasonic sensor, radar sensor, optical sensor, ultra Wide Band (UWB) sensor, inertial navigation sensor, satellite positioning module, image acquisition module.

The ultrasonic sensor may detect relative positional information between the self-moving device and at least a portion of the working boundary by transmitting ultrasonic signals. An obstacle may be provided on the working boundary, and the ultrasonic sensor may move along the working boundary and emit ultrasonic waves outwardly. Further, the ultrasonic sensor may map based on the received ultrasonic signal reflected back from the obstacle. During operation of the self-mobile device, the ultrasonic sensor may identify a current location of the self-mobile device based on the received reflected ultrasonic signal.

The radar sensor, the optical sensor and the UWB sensor operate in a similar manner to the ultrasonic sensor. For convenience of description, the radar sensor, the optical sensor, and the UWB sensor are collectively referred to as a sensor. An obstacle may be provided on the working boundary, and the sensor may move along the working boundary and emit an optical signal to the outside. Further, the sensor may map based on the received light signal reflected back from the obstacle. During operation of the self-mobile device, the sensor may identify the current location of the self-mobile device from the received reflected light signal.

Inertial navigation sensors may include, for example, odometers (ODO), and/or inertial measurement units (inertial measurement unit, IMU), etc. The inertial navigation sensor can establish a reference coordinate system and measure a relative positional relationship between the current location and a coordinate origin of the reference coordinate system to determine relative positional information between the self-mobile device and at least a portion of the boundary. The relative positional relationship between the current position and the origin of coordinates may comprise, for example, a distance between the current position and the origin of coordinates and/or phase information in a reference coordinate system. The reference coordinate system may serve as an initial point of the charging station, that is, the charging station may serve as a coordinate origin of the reference coordinate system.

The satellite positioning module may be, for example, one or more of a global positioning system (global positioning system, GPS), GPS real-time kinematic (Real time kinematic, RTK), beidou satellite navigation system (BeiDou navigation satellite system, BDS), galileo satellite navigation system, and GLONASS. The satellite positioning module may obtain location information from the mobile device, which may include, for example, longitude information and/or latitude information. The satellite positioning module in the embodiment of the application can be a high-precision satellite positioning module, a low-precision satellite positioning module or a sub-meter satellite positioning module.

Taking fig. 4 as an example, the satellite positioning module 312 shown in fig. 4 may be disposed above the self-mobile device to determine the current location of the self-mobile device by receiving signals transmitted by satellites.

The image acquisition module may take a current image from the location of the mobile device. An embodiment of the present application may provide a marker on at least a portion of the working boundary, the marker may be, for example, at least one of a rope, sign, fence, or fence. The image acquisition module may determine a relative position between the self-moving device and at least a portion of the working boundary based on the position of the marker in the current image. The image acquisition module can identify the marker in the current image by means of AI identification. In the construction process, the image acquisition module can move along the working boundary, images of a plurality of position points are shot, and a boundary map is constructed according to the positions of the markers in the images. In the working process of the self-mobile device, the image acquisition module can shoot a current image of the position of the self-mobile device, and the position information of the self-mobile device is determined according to the position of the marker in the current image. In another embodiment of the present application, the image acquisition module may also use a method of visual instant positioning and map creation (Simultaneous Localization and Mapping, abbreviated as SLAM) to build a map and determine the current position of the self-mobile device. In the process of mapping, an image acquisition module is controlled to move along a working boundary, images of a plurality of position points are shot, a transformation relation between two continuous frames of images is determined, and a boundary map track is determined according to the transformation relation. In the working process of the self-mobile device, the image acquisition module can shoot a current image of the position of the self-mobile device, and determine the current position information of the self-mobile device according to a slam algorithm. When the machine cannot identify the working boundary of grass and non-grass only by adopting a visual sensor or a mode of combining the visual sensor with AI, the working boundary of grass and non-grass can be determined by adopting the mode of combining the visual sensor with slam.

Taking fig. 4 as an example, the image acquisition module 313 may also be referred to as a vision sensor. The image acquisition module 313 may acquire images from the forward direction of the mobile device for image recognition. The image acquisition module 313 may be disposed at a position close to the vehicle head of the self-moving device, or may be disposed at an intermediate position of the housing of the self-moving device. The shooting direction of the image acquisition module 313 may be fixed or may be rotated. For example, the image acquisition module 313 may include a camera, and the camera may be driven by a motor to rotate. The rotation direction of the camera may be left-right rotation or up-down rotation.

The control device 313 may be in signal connection with the surface identification device and the position acquisition device. The connection mode between the devices is not particularly limited in the embodiment of the application. For example, the control device may be electrically connected to the surface identification device and the position acquisition device. For another example, the control device may be wirelessly connected with the surface identification device and the position acquisition device. The manner of wireless connection may include a bluetooth connection, and/or a wireless fidelity (Wireless Fidelity, WIFI) connection, etc. The control means may control the movement and/or operation of the self-moving device on a work surface defined by the work boundary.

The determination module 314 may be configured to determine whether the self-mobile device has reached a working boundary. The determining module 314 may determine whether the self-mobile device 310 reaches the working boundary according to the material information identified by the surface identifying device 311. If it is determined from the material information that the mobile device 310 has reached the working boundary, the control unit 313 may control the mobile device 310 to walk along the working boundary or turn into the working surface. If it is determined that the self-mobile device does not reach the working boundary according to the material information, the determining module 314 may further determine whether the self-mobile device 310 reaches the working boundary according to the location information acquired by the location acquisition device 312 and at least part of the working boundary. If it is determined from the position information that the mobile device has reached the working boundary, the control means 313 may control the mobile device to walk along the working boundary or to turn into the working surface. The control device 313 may control the self-mobile device to continue to operate if it is determined that the self-mobile device has not reached the operation boundary according to both the material information and the location information.

The positioning error of the position acquisition device in the embodiment of the application can be larger than or equal to the identification error of the surface identification device. Because the surface recognition device has higher recognition precision, the boundary recognition can be performed by using the surface recognition device firstly, so that the accuracy of boundary recognition is improved. Under the condition that the boundary is not recognized by the surface recognition device, if the material information changes obviously to the areas on two sides of the boundary, or the surface recognition device fails, the boundary recognition can be performed by using the position acquisition device so as to avoid the phenomenon of missed cutting, or the potential safety hazard caused by moving the mobile equipment to a position far away from the working area is avoided. The surface recognition device and the position acquisition device in the embodiment of the application are mutually matched and act together, so that the accuracy of boundary recognition of the self-mobile equipment is improved.

At least some of the working boundaries in embodiments of the present application may include physical boundaries and/or virtual boundaries. The physical boundary may include, for example, a marker, which may be, for example, at least one of a rope, a sign, a fence, or a fence. The virtual boundary may be, for example, a magnetic device, and/or a virtual wall, etc.

As one example, at least a portion of the working boundary may be provided with a magnetic device (e.g., a magnetic stripe) that may be used to form the working boundary. The self-moving device may include a magnetic field detection sensor to detect a magnetic field in the magnetic means. If the strength of the magnetic field detected from the mobile device exceeds a preset threshold, it may be indicative of reaching a working boundary from the mobile device. If the strength of the magnetic field detected from the mobile device does not exceed the preset threshold, it may be indicated that the working boundary has not been reached from the mobile device.

As another example, a virtual wall may be provided on at least part of the working boundary, and the self-moving device may include virtual wall detection means to detect the virtual wall. The virtual wall can be established by arranging an infrared sensor on the boundary, and the infrared distance emitted by the infrared sensor is at least the length of part of the working boundary. A virtual wall is a virtual wall that blocks access to an area from a mobile device, allowing the mobile device to operate on only one side of the virtual wall, and not allowing the mobile device to move to the other side of the virtual wall. The self-mobile device, upon detecting the virtual wall, indicates that the self-mobile device has reached a working boundary.

At least some of the working boundaries in embodiments of the present application may include boundary maps. Accordingly, the position acquisition means may be configured to acquire a relative positional relationship between the mobile device and the boundary map. The position acquisition means may be configured to determine whether the self-mobile device reaches the working boundary based on the acquired relative position information between the current position of the self-mobile device and the boundary map. For example, when the distance between the self-mobile device and the boundary map is less than or equal to a preset value, it may be determined that the self-mobile device reaches the working boundary; when the distance between the self-mobile device and the boundary is greater than a preset value, it may be determined that the self-mobile device has not reached the working boundary.

The manner of acquiring the boundary map (i.e., the mapping process) is not particularly limited in the embodiment of the present application. In order to distinguish from a process of acquiring position information during operation, a process of acquiring a boundary map will be hereinafter referred to as a mapping process, and a process of acquiring position information during operation will be hereinafter referred to as an operation process.

For example, the boundary map may be obtained by the user by delineating an area on the map. For another example, the boundary map may be derived using information collected by the location acquisition device. It should be noted that the position acquisition device in the mapping process and the position acquisition device in the working process may be the same or different, which is not particularly limited in the embodiment of the present application. For example, the embodiment of the application can acquire the boundary map by using an inertial navigation sensor, and acquire the position information or the relative position information of the automatic equipment through a satellite positioning module. For another example, the embodiment of the present application may acquire the boundary map using a first satellite positioning module and acquire the position information or the relative position information of the automatic device using a second satellite positioning module. The first satellite positioning module and the second satellite positioning module can be the same satellite positioning module, can also be different satellite positioning modules, and can have different positioning accuracy.

The following description will be given by taking the same device for acquiring the boundary map as the device for acquiring the position information (the same satellite positioning module is used for mapping and controlling the self-mobile device to work) as an example.

The position acquisition device is exemplified as a satellite positioning module (GPS or GPS-RTK, etc.) that is removably or fixedly mounted on the self-mobile device. Accordingly, the satellite positioning module may be configured to obtain the boundary map as follows: and acquiring the position information of a plurality of position points in at least part of the working boundary by utilizing a satellite positioning module, and obtaining the boundary map according to the position information of the plurality of position points.

By way of example, the embodiment of the application can utilize the satellite positioning module to move one or more circles along the working boundary to obtain the position information of a plurality of position points; and obtaining a boundary map according to the position information of the plurality of position points. If the satellite positioning module is detachably connected with the self-mobile equipment, the satellite positioning module can be detached from the self-mobile equipment, and the satellite positioning module is directly used for acquiring the position information of a plurality of position points and acquiring a boundary map; after the boundary map is obtained, the satellite positioning installation module can be installed on the self-mobile device to perform positioning navigation. If the satellite positioning module is fixedly connected with the self-mobile equipment, the self-mobile equipment can be controlled (such as remote control) to move along a working boundary, so that the position information of a plurality of position points is acquired, and a boundary map is acquired; after the boundary map is obtained, the self-mobile device carrying the satellite positioning module can be controlled to perform positioning navigation.

According to the embodiment of the application, the boundary map can be directly used as a working boundary, and the judging module can determine whether the self-mobile device reaches the boundary according to the relative position between the current position of the self-mobile device and the boundary map. For example, taking a satellite positioning module as an example, if the satellite positioning module is a high-precision satellite positioning module, the satellite positioning module has no positioning error or has a small positioning error, which can be ignored. Therefore, if the satellite positioning module is used for collecting the boundary map, the collected boundary map is close to the working boundary, and the boundary map can be directly used for boundary identification.

However, for other satellite positioning modules, such as a low-precision satellite positioning module or a sub-meter satellite positioning module, when the satellite positioning module is used to acquire a boundary map, an error exists between the acquired boundary map and a real working boundary due to satellite positioning errors of the satellite positioning module. There are two cases of this error, the first is that the boundary map is scaled inward relative to the working boundary. The working boundary here refers to a true working boundary. As shown in fig. 5, the boundary map 1 is contracted relative to the true working boundary. Second, the boundary map is flared with respect to the real working boundary. As shown in fig. 5, the boundary map 2 is expanded with respect to the real working boundary. If the boundary map 1 is used to determine whether the self-mobile device reaches the working boundary, the self-mobile device may mistakenly identify the working area as the boundary, and a problem arises that a part of the working area cannot be processed (such as mowing missing). If the boundary map 2 is used to determine whether the self-mobile device reaches the working boundary, this causes the self-mobile device to recognize the non-working area as the boundary, and a problem arises in that the self-mobile device works in an area outside the working boundary.

Based on this, the embodiment of the application can process the boundary map instead of directly using the boundary map as the working boundary, obtain the processed working boundary, and determine whether the self-mobile device reaches the working boundary according to the processed working boundary.

The method for processing the boundary map and obtaining the processed working boundary is not particularly limited. For example, the boundary map may be expanded outward to obtain the working boundary. For another example, the boundary map may be contracted inwards to obtain the working boundary. The specific expansion mode or the contraction mode can be determined according to actual conditions. For example, if the boundary map is extended outwards to improve the working efficiency of the self-mobile device, a working boundary is obtained, so that the self-mobile device finishes the processing of the working area as much as possible. Taking an intelligent mower as an example, the intelligent mower can be prevented from being missed by expanding the boundary map. For another example, to ensure the safety of the operation of the self-mobile device, the boundary map may be contracted inwards to obtain the operation boundary, so as to avoid the self-mobile device from moving outside the operation boundary.

The embodiment of the application can obtain the expanded boundary by expanding the boundary map. It will be appreciated that the production expansion boundary is not a true working boundary, but a boundary for boundary identification. Further, the judging module can judge whether the self-mobile device reaches the working boundary according to the position information acquired by the position acquisition device and the expansion boundary. Under the condition that the judging module judges that the self-moving equipment reaches the working boundary according to the position information acquired by the position acquisition device and the expansion boundary, the control device can control the self-moving equipment to walk along the working boundary or turn into the working surface so as to control the self-moving equipment to return into the working area.

The embodiment of the application can obtain the contracted boundary by contracting the boundary map. It will be appreciated that the shrink boundary is not a true working boundary, but a boundary for boundary identification. Further, the judging module can judge whether the self-mobile device reaches the working boundary according to the position information acquired by the position acquisition device and the contraction boundary. Under the condition that the judging module judges that the self-moving equipment reaches the working boundary according to the position information and the contraction boundary acquired by the position acquisition device, the control device can control the self-moving equipment to walk along the working boundary or turn into the working surface so as to control the self-moving equipment to return into the working area.

Expanding the boundary map may refer to moving a plurality of location points on the boundary map in a direction away from the work area, and contracting the boundary map may refer to moving a plurality of location points on the boundary map in a direction toward the work area.

For convenience of description, the boundary map acquired by the position acquisition device will be hereinafter referred to as a pre-processing boundary. The processed boundary may be an expanded boundary or a contracted boundary.

The distance between the boundary before processing and the boundary after processing is not particularly limited in the embodiment of the application.

As an example, the distance between the pre-processing boundary and the post-processing boundary may be equal to the positioning error of the position acquisition device during operation. For example, if the accuracy of the position acquisition device during mapping is relatively high, and there is substantially no error between the acquired boundary map and the actual working boundary, the distance between the pre-processing boundary and the post-processing boundary may be equal to the positioning error of the position acquisition device during working.

As another example, the distance between the pre-processing boundary and the post-processing boundary may be equal to the positioning error of the position acquisition device during mapping. For example, if the accuracy of the position acquisition device during operation is relatively high, and there is substantially no error between the acquired position information of the self-mobile device and the actual position information, the distance between the boundary before processing and the boundary after processing may be equal to the positioning error of the position acquisition device during mapping.

As yet another example, the distance between the pre-processing boundary and the post-processing boundary may be equal to the sum of the positioning error of the position acquisition device during mapping and the positioning error of the position acquisition device during operation. If there is a positioning error in both position acquisition devices, the distance between the pre-processing boundary and the post-processing boundary may be equal to the sum of the two positioning errors. Taking the satellite positioning module as an example, if the same satellite positioning module is used to acquire the boundary map and the position information, the distance between the boundary before processing and the boundary after processing may be equal to twice the positioning error of the satellite positioning module. For example, to increase the efficiency of operation of the self-mobile device, the pre-processing boundary may be extended outward by twice the satellite positioning error, resulting in a processed boundary. For another example, to ensure the safety of operation of the self-mobile device, the pre-processing boundary may be scaled inward by twice the satellite positioning error, resulting in a processed boundary.

The following description will be made by taking the difference between the position acquisition device in the drawing process and the position acquisition device in the working process as an example. Of course, the following applies equally to the position detection device in the mapping process and the position detection device in the working process.

For distinguishing, the position acquisition device in the mapping process is called intelligent equipment in the embodiment of the application. The intelligent device can be a mobile phone with a position acquisition function or can be a stand-alone device with only the position acquisition function. The automated work system may include the smart device having a location acquisition function. The smart device may include at least one of: ultrasonic sensor, radar sensor, optical sensor, UWB sensor, inertial navigation sensor, satellite positioning module, image acquisition module.

The smart device may be configured to obtain the boundary map as follows: and acquiring the position information of a plurality of position points in at least part of the working boundary by using the intelligent equipment, and obtaining the boundary map according to the position information of the plurality of position points. The smart device may obtain the boundary map in any of the ways described above. For example, in the case where the smart device includes a satellite positioning module, the smart device may obtain the boundary map by acquiring longitude information and/or latitude information of a plurality of location points. For another example, where the smart device includes an inertial navigation sensor, the smart device may obtain distance and/or phase information of a plurality of location points relative to an origin of coordinates, resulting in a boundary map.

Similar to the above-described manner, the embodiment of the present application may directly use the boundary map acquired by the intelligent device to perform boundary recognition. Or, because the intelligent device has device positioning errors, the embodiment of the application can process the boundary map acquired by the intelligent device and use the processed boundary to carry out boundary identification. Wherein, the equipment positioning error of the intelligent equipment is greater than or equal to the positioning error of the surface recognition device.

Due to the positioning error of the intelligent device, an error exists between the boundary map acquired by the intelligent device and the real working boundary. For example, the distance between the boundary map acquired by the smart device and the real working boundary may be equal to the device positioning error.

In order to compensate the positioning errors of the two devices, the boundary map can be processed, so that the distance between the processed boundary and the boundary before processing is equal to the sum of the equipment positioning errors and the device positioning errors.

After obtaining the boundary map, the intelligent device can send the boundary map to the self-mobile device for boundary identification by the self-mobile device. After receiving the boundary map from the mobile device, the boundary map may be processed as described above, to obtain a processed boundary map. The judging module can judge whether the self-mobile device reaches the working boundary according to the position information of the self-mobile device and the processed boundary map.

The following describes in detail the scheme of the embodiment of the present application, taking two different satellite positioning modules as an example, with reference to fig. 5.

The embodiment of the application can utilize the first satellite positioning module to move along the real working boundary to obtain the position information of a plurality of position points, and obtain the boundary map according to the position information of the plurality of position points. Since the first satellite positioning module has a positioning error, such as the positioning error d1, the obtained boundary map is located between the boundary map 1 and the boundary map 2. The boundary map 1 is a boundary map obtained by retracting the real boundary inward by d1, and the boundary map 2 is a boundary map obtained by expanding the real boundary outward by d 1.

The embodiment of the application can use the second satellite positioning module to acquire the position information of the mobile equipment. The determination module may determine whether the self-mobile device reaches the boundary based on the location information of the self-mobile device and the boundary map. Since the second satellite positioning module has a positioning error, such as the positioning error d2, the self-mobile device may recognize the boundary map 3 as a boundary and may recognize the boundary map 4 as a boundary when performing boundary recognition. In other words, the boundary finally identified from the mobile device is between the boundary map 3 and the boundary map 4.

If the boundary map 3 is prevented from being identified as a boundary by the self-mobile device in order to improve the working efficiency of the self-mobile device, the embodiment of the present application may obtain the distance of the outward expansion (d1+d2) of the boundary map by the first satellite positioning module. This ensures that the working area defined by the true working boundary can be processed.

If the boundary map 4 is avoided being identified as a boundary by the self-mobile device in order to ensure that the self-mobile device does not move to the non-operating area in any case, embodiments of the present application may retract the boundary map obtained by the first satellite positioning module inward by a distance of (d1+d2).

Taking the example of obtaining the boundary map through the satellite positioning module, the satellite positioning module has satellite positioning errors, so that errors exist between the obtained boundary map and the real working boundary. To counteract this error, embodiments of the present application may eliminate the error by plotting multiple times to take intermediate values. For example, the embodiment of the application can control the satellite positioning module to move for a plurality of circles along the working boundary to obtain a plurality of boundary maps. Further, the position information of the same position point on the plurality of boundary maps can be subjected to mean value processing to obtain the boundary map. The error between the boundary map obtained after mean value processing and the real working boundary is greatly reduced, so that the boundary map can be basically overlapped with the real working boundary.

In this case, the errors in constructing the boundary map are substantially eliminated, and the embodiment of the present application may consider only the errors in the working process. To compensate for this error, embodiments of the present application may process the boundary map such that the distance between the processed boundary and the boundary before processing is equal to the positioning error of the position acquisition device during operation.

The foregoing description of the preferred embodiments of the application is not intended to be limiting, but rather is to be construed as including any modifications, equivalents, and alternatives falling within the spirit and principles of the application.

Claims

An automated working system, the automated working system comprising: a self-moving device that moves and/or works on a work surface defined by a work boundary, the self-moving device being configured with:

a surface recognition device configured to directly recognize material information of the working surface;

a position acquisition device configured to acquire position information of the self-moving device and/or position information between the self-moving device and at least part of the working boundary;

control means in signal communication with said surface identification means and said position acquisition means, said control means being configured to control movement and/or operation of said self-moving device on a work surface defined by said work boundary,

The self-mobile device is also provided with: and the judging device is configured to judge whether the self-moving equipment reaches the working boundary, and the control device controls the self-moving equipment to walk along the working boundary or turn into the working surface if the self-moving equipment is judged to reach the working boundary according to the position information acquired by the position acquisition device and the at least partial working boundary under the condition that the self-moving equipment is judged not to reach the working boundary according to the material information identified by the surface identification device.
The automated working system of claim 1, wherein the at least partial working boundary is a non-closed working boundary.
The automated working system of claim 1, wherein the at least a portion of the working boundary is provided with boundary means to form the working boundary, the self-mobile device comprising: and the signal detection sensor is used for detecting a virtual signal sent by the boundary device and judging whether the self-mobile equipment reaches the working boundary according to the virtual signal.
The automated working system of claim 1, wherein the surface identification means comprises at least one of: radar sensor, ultrasonic sensor, capacitive sensor, image acquisition module.
The automated working system of claim 4, wherein when the surface identification device is an image acquisition module, the surface identification device is configured to identify texture information of the working surface as follows:

shooting a current image of the position of the self-mobile device by using the image acquisition module;

and inputting the current image into an artificial intelligent model to identify the material information of the working surface.
The automated working system of claim 1, wherein the position acquisition device comprises at least one of: ultrasonic sensor, radar sensor, optical sensor, ultra-wideband UWB sensor, inertial navigation sensor, satellite positioning module, image acquisition module.
The automated working system of claim 1, wherein the at least a portion of the working boundary comprises a boundary map,

accordingly, the position acquisition device is configured to acquire position information between the self-mobile device and at least part of the working boundary, and includes:

acquiring relative position information between the current position of the self-mobile device and the boundary map;

the judging module is configured to judge that the self-mobile device reaches the working boundary according to the relative position information between the current position of the self-mobile device and the boundary map.
The automated work system of claim 7, wherein when the position acquisition device is a satellite positioning module, the satellite positioning module is removably or fixedly mounted on the self-moving device and, correspondingly,

the satellite positioning module is configured to obtain the boundary map as follows:

and acquiring the position information of a plurality of position points in the at least partial working boundary by utilizing the satellite positioning module, and obtaining the boundary map according to the position information of the plurality of position points.
The automated working system of claim 8, wherein the satellite positioning module has a satellite positioning error that is greater than or equal to an identification error of the surface identification device.
The automated working system of claim 7, further comprising: an intelligent device with a position acquisition function, correspondingly,

the smart device is configured to obtain the boundary map as follows:

and acquiring the position information of a plurality of position points in the at least partial working boundary by using the intelligent equipment, and obtaining the boundary map according to the position information of the plurality of position points.
The automated working system of claim 10, wherein the smart device has a device positioning error that is greater than or equal to a positioning error of the surface identification device.
The automated working system of claim 7, wherein the determining that the self-mobile device reaches the working boundary based on the location information acquired by the location acquisition device and the at least partial working boundary comprises:

expanding the boundary map to obtain an expanded boundary;

and judging that the self-mobile equipment reaches the working boundary according to the position information acquired by the position acquisition device and the expansion boundary.
The automated working system of claim 12, wherein if the boundary map is obtained with the position acquisition device, the distance between the extended boundary and the boundary map is equal to the position error of the position acquisition device or equal to twice the position error of the position acquisition device.
The automated working system of claim 12, wherein if the boundary map is obtained with a smart device, the distance between the extended boundary and the boundary map is equal to a positioning error of the position acquisition device, or equal to a device positioning error of the smart device, or equal to a sum of a positioning error of the position acquisition device and a device positioning error of the smart device.
The automated working system of claim 7, wherein the determining that the self-mobile device reaches the working boundary based on the location information acquired by the location acquisition device and the at least partial working boundary comprises:

contracting the boundary map to obtain a contracted boundary;

and judging that the self-mobile equipment reaches the working boundary according to the position information acquired by the position acquisition device and the contraction boundary.
The automated working system of claim 15, wherein if the boundary map is obtained with the position acquisition device, the distance between the contracted boundary and the boundary map is equal to the position error of the position acquisition device or is equal to twice the position error of the position acquisition device.
The automated working system of claim 15, wherein if the boundary map is obtained using a smart device, the distance between the contracted boundary and the boundary map is equal to a positioning error of the position acquisition device, or equal to a device positioning error of the smart device, or equal to a sum of a positioning error of the position acquisition device and a device positioning error of the smart device.