WO2023274339A1

WO2023274339A1 - Self-propelled working system

Info

Publication number: WO2023274339A1
Application number: PCT/CN2022/102601
Authority: WO
Inventors: 伊曼纽尔康蒂; 兰彬财; 何爱俊; 汪应龙
Original assignee: 苏州宝时得电动工具有限公司
Priority date: 2021-06-30
Filing date: 2022-06-30
Publication date: 2023-01-05
Also published as: CN116917826A

Abstract

The present application provides a self-propelled working system, comprising: a self-moving device, the self-moving device moving and/or working on a working surface defined by a working boundary; the self-moving device comprising a surface identifying apparatus, configured to directly identify material information of the working surface; a location collecting apparatus, configured to collect location information of the self-moving device and/or location information between the self-moving device and at least part of the working boundary; a control apparatus, configured to control the self-moving device to move and/or work on the working surface; and a determination apparatus, configured to determine whether the self-moving device has reached the working boundary. When a determination module determines, according to the material information identified by the surface identifying apparatus, that the self-moving device has not reached the working boundary, then, if it is determined according to the location information collected by the location acquisition apparatus and at least part of the working boundary that the self-moving device has reached the working boundary, the control apparatus controls the self-moving device to walk along the working boundary, or to turn to the working surface.

Description

automatic work system

technical field

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

Background technique

Self-moving equipment can move and/or work on the work surface defined by the work boundary without manual operation. At present, there is a method of identifying the working boundary through a surface recognition device. For example, the surface recognition device can determine whether the mobile device has reached the working boundary by recognizing the material information of the working surface. However, for areas where the material information inside and outside the working boundary does not change significantly, the surface recognition device may not be able to identify the working boundary.

Contents of the invention

In view of this, the present application provides an automatic working system, which can improve the accuracy of boundary recognition from mobile devices.

In a first aspect, an automatic working system is provided, the automatic working system includes: self-moving equipment, the self-moving equipment moves and/or works on the working surface defined by the working boundary, and the self-moving equipment is configured with : surface recognition device, configured to directly identify the material information of the working surface; position acquisition device, configured to collect the position information of the self-moving device and/or the position information between the self-moving device and at least part of the working boundary a control device, connected to the surface recognition device and the position acquisition device, the control device is configured to control the self-moving device to move and/or work on the working surface defined by the working boundary, the self-moving device The mobile device is also equipped with: a judging device configured to judge whether the self-mobile device has reached the working boundary, and the judging module judges that the self-mobile device has not reached the working boundary according to the material information recognized by the surface recognition device. In the case of the above working boundary, if it is judged that the self-moving device reaches the working boundary according to the position information collected by the position acquisition device and the at least part of the working boundary, the control device controls the self-moving device to move along the The working boundary walks, or turns, into the working surface.

Optionally, as an implementation manner, the at least part of the working boundary is an open working boundary.

Optionally, as an implementation manner, at least part of the working boundary is provided with a boundary device to form the working boundary, and the mobile device includes: a signal detection sensor that detects that the boundary device sends and judging whether the self-mobile device has reached the working boundary according to the virtual signal.

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

Optionally, as an implementation manner, when the surface recognition device is an image acquisition module, the surface recognition device is configured to identify the material information of the working surface in the following manner: use the image acquisition module to photograph the self A current image of the location of the mobile device; inputting the current image into an artificial intelligence model to identify material information of the working surface.

Optionally, as an implementation, the location acquisition device includes at least one of the following: ultrasonic sensors, radar sensors, optical sensors, ultra-wideband UWB sensors, inertial navigation sensors, satellite positioning modules, and image acquisition modules.

Optionally, as an implementation manner, the at least part of the working boundary includes a boundary map, and correspondingly, the location collection device is configured to collect the location information between the self-mobile device and at least a part of the working boundary, including: collecting relative position information between the current location of the self-mobile device and the boundary map; the judging module is configured to judge the relative position information between the current position of the self-mobile device and the boundary map The working boundary is reached from the mobile device.

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 mobile device, and correspondingly, the satellite positioning module configures In order to obtain the boundary map as follows: use the satellite positioning module to collect position information of multiple position points in the at least part of the working boundary, and obtain the boundary map according to the position information of the multiple 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: a smart device with a location collection function, and correspondingly, the smart device is configured to acquire the boundary map as follows: using the smart The device collects location information of multiple location points in the at least part of the working boundary, and obtains the boundary map according to the location information of the multiple location points.

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

Optionally, as an implementation manner, the judging that the self-mobile device reaches the working boundary according to the location information collected by the location collection device and the at least part of the working boundary includes: extending the boundary map to obtain Extending the boundary: judging that the self-mobile device has reached the working boundary according to the location information collected by the location acquisition device and the extending boundary.

Optionally, as an implementation manner, if the boundary map is obtained by using 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 , which is equal to twice the positioning error of the position acquisition device.

Optionally, as an implementation manner, if the boundary map is obtained using a smart device, the distance between the extended boundary and the boundary map is equal to the positioning error of the position collection device, or equal to the The device positioning error of the smart device, or equal to the 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 judging that the self-mobile device reaches the working boundary according to the location information collected by the location collection device and the at least part of the working boundary includes: shrinking the boundary map to obtain Shrinking boundary: judging that the self-mobile device reaches the working boundary according to the position information collected by the position acquisition device and the shrinking boundary.

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

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

Based on the above technical solution, the embodiment of the present application may first use a surface recognition device to perform boundary recognition. In the case where the surface recognition device does not recognize the boundary, for example, for the areas on both sides of the boundary, when the material information does not change significantly, or when the surface recognition device fails, the position acquisition device can be used for boundary recognition. The surface recognition device and the position acquisition device cooperate with each other to improve the accuracy of boundary recognition of the mobile device.

Description of drawings

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

Fig. 2 is a schematic structural diagram of an intelligent lawn mower provided by an embodiment of the present application.

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

Fig. 4 is a schematic structural diagram of an autonomous mobile device provided by an embodiment of the present application.

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

detailed description

The following will clearly and completely describe the technical solutions in the embodiments of the application with reference to the drawings in the embodiments of the application. Apparently, the described embodiments are only some, not all, embodiments of the application.

The self-moving device in the embodiment of the present application may be an outdoor robot, such as a smart lawn mower, a smart snow plow, a smart sweeper, a smart scrubber, and other smart devices with automatic walking functions.

Taking an intelligent lawn mower as an example, the automatic working system 100 shown in FIG. 1 may include an intelligent lawn mower 1 and a boundary 6 , which may be used to define the working area (or work surface) of the intelligent lawn mower 1 . Wherein, the boundary line 6 may be the boundary line between the lawn area and the non-lawn area. The intelligent lawn mower 1 can work in the area defined by the boundary 6, such as automatically completing the mowing work, and the boundary 6 can separate the working area 7 from the non-working area.

In the working area of the intelligent lawn mower 1, there are also some obstacle areas that affect the work of the intelligent lawn mower. The obstacle area may include, for example, the area 3 where the house is located, the area 4 where the pit is located, and the area 5 where the trees are located. During the working process, the intelligent lawnmower 1 can bypass these areas to work.

The automatic working system 100 may also include a charging station 2 for replenishing electric energy for the intelligent lawnmower 1 . The smart lawn mower 1 can automatically perform work tasks without human supervision, and when the power is insufficient, it can automatically return to the charging station 2 for charging.

The charging station 2 can be located on the boundary line 6, that is, a part of the charging station 2 is located in the working area 7, and a part is located in the non-working area; or the charging station 2 can be completely located in the working area 7; or, the charging station 2 can also be completely in a non-working area.

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

The mobile module is used to drive the intelligent mower to walk in the working area 7 . The mobile module usually includes a wheel set installed on the intelligent lawn mower and a walking motor that drives the wheel set to walk and turn. The wheel set includes a drive wheel 14 connected to the traveling motor and an auxiliary wheel 15 mainly serving as an auxiliary support. The auxiliary wheel 15 can also be called a driven wheel, and the auxiliary wheel 15 can be a universal wheel. The number of driving wheels 14 can be two, which are respectively located on both sides of the housing 16 . The quantity of traveling motor can be 2, is connected with two driving wheels respectively. The number of training wheels can be one or two. When there are 2 auxiliary wheels 15, these 2 auxiliary wheels 15 can be positioned at both sides of the front portion of the intelligent mower. Auxiliary wheel 15 is not connected with travel motor, but can be driven to roll and walk when supporting intelligent mower to walk. Through the setting of the above structure, the intelligent mower can flexibly walk and turn in the working area under the control of the control device.

The task performance module can include a cutting assembly that can be used to perform mowing work. The cutting assembly can be arranged on the chassis of the intelligent mower, and its position can be located between the driving wheel 14 and the auxiliary wheel 15 .

The energy module may include a battery pack for providing electric energy for the movement and work of the intelligent lawnmower 1 . For example, the energy module can provide electric energy for the motor, so that the motor can drive the cutting assembly to work.

The control device can be electrically connected with the mobile module, the task execution module and the energy module, so as to control the mobile module to drive the smart lawn mower 1 to move, and control the task execution module to perform work tasks.

The control device can be used to control the intelligent lawn mower to automatically walk, work, replenish energy, etc., and is the core component of the intelligent lawn 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 mobile module to walk along the path, judging the power of the energy module and instructing the intelligent lawn mower to return to the docking station in time and automatically docking and charging, When it is detected that the intelligent lawn mower is in a boundary position or a non-working area, the lawn mower is controlled to return to the working area, etc.

Continuing to refer to FIG. 1 , the boundary 6 in FIG. 1 can be understood as a working boundary. There is now a way to identify working boundaries with visual sensors. The visual sensor can judge whether the mobile device has reached the working boundary by identifying the material information of the working surface. For example, taking an automatic lawn mower as an example, the surface recognition device can recognize grass information to determine whether the mobile device has reached the working boundary.

However, for areas where material information does not change significantly within and outside the working boundary, the surface recognition device cannot accurately identify the working boundary, thereby affecting the work of the mobile device. Taking a smart lawn mower as an example, when there is grass 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 working boundaries from mobile devices.

As shown in FIG. 3 and FIG. 4 , the automatic working system 300 may include a self-moving device 310 that can move and/or work on a working surface defined by a working boundary. The autonomous mobile device 310 may be any self-mobile device described above.

The self-moving device 310 may be configured with a surface recognition device 311 , a location collection device 312 , a control device 313 and a judging module 314 .

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

Radar sensors and ultrasonic sensors can emit wave signals and identify material information by receiving 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, and the like.

For capacitive sensors, capacitive sensors can be installed on mobile devices. The capacitive sensor can sense the capacitance between the mobile device and the ground. In the process of moving from the mobile device, if the material information changes, the capacitance value will also change. Taking a smart lawn mower as an example, it is assumed that the working surface of the smart lawn mower includes grass, and the non-working surface does not include grass, or the non-working surface includes roads, obstacles, and the like. Due to the presence of grass on the working surface, the capacitance value sensed by the capacitive sensor on the working surface is different from the capacitance value sensed on the non-working surface. The self-moving device can judge whether the smart lawn mower has reached the working boundary according to the difference of the capacitance value.

For the image acquisition module, the image acquisition module can be configured to identify the material information of the work surface in the following manner: utilize the image acquisition module to capture the current image from the location of the mobile device; input the current image into the artificial intelligence (Artificial Intelligence, AI) module , to identify the material information of the work surface.

The artificial intelligence model may be trained based on sample images. Before working from the mobile device, the AI model can be trained through sample images, 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; inputting the sample image into a 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 the training is completed, the mobile device can use the second AI model to recognize the current image.

Taking a smart lawn mower as an example, the key features can include grass features, and the image acquisition module can use the AI model to identify grass areas and non-grass areas. For example, if the image acquisition module recognizes that the current image includes grass features, it can be determined that the smart lawn mower is in the working area; if the vision module recognizes that the current image does not include grass features, or includes road or obstacle features , it can be determined that the smart mower is in the non-working area, or has reached the working boundary.

The embodiment of the present application does not specifically limit the manner in which the AI model identifies material information. For example, the AI model can identify material information through semantic segmentation. Semantic segmentation can refer to classifying each pixel in the current image, determining the category of each pixel, and performing regional division to identify each object in the current image.

The location collecting unit 312 may be configured to collect location information from the mobile device, and/or, location information between the mobile device and at least part of the working boundary. Here, the position information between the self-mobile device and at least part of the working boundary may refer to relative position information between the self-mobile device and at least part of the working boundary. At least part of the working boundary may be a closed working boundary or an open working boundary. For example, for an area where the boundary between the working area and the non-working area is relatively obvious, no working boundary may be set in this area, and the working boundary may be set only in the area where the boundary is not obvious, so as to form a non-closed working boundary. For another example, regardless of whether the boundary between the working area and the non-working area is obvious, a closed working boundary can be set.

Optionally, in addition to acquiring the location information during the operation of the mobile device, the location acquisition device may also construct a boundary map of the mobile device before the mobile device works. In this way, the self-mobile device can use the boundary map to identify boundaries during work.

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

The ultrasonic sensor can detect relative position information between the mobile device and at least part of the working boundary by emitting ultrasonic signals. Obstacles can be set on the working boundary, and the ultrasonic sensor can move along the working boundary and emit ultrasonic waves outward. Further, the ultrasonic sensor can construct a map according to the received ultrasonic signal reflected by obstacles. During the working process of the self-mobile device, the ultrasonic sensor can identify the current position of the self-mobile device according to the received reflected ultrasonic signal.

Radar sensors, optical sensors, and UWB sensors work similarly to ultrasonic sensors. For convenience of description, radar sensors, optical sensors and UWB sensors are collectively referred to as sensors. Obstacles can be set on the working boundary, and the sensor can move along the working boundary and emit light signals outward. Further, the sensor can construct a map according to the received light signal reflected by the obstacle. During the working process of the self-mobile device, the sensor can identify the current position of the self-mobile device according to the received reflected light signal.

The inertial navigation sensor may include, for example, an odometer (odometry, ODO), and/or an inertial measurement unit (inertial measurement unit, IMU) and the like. The inertial navigation sensor can establish a reference coordinate system, and measure the relative position relationship between the current position and the coordinate origin of the reference coordinate system, so as to determine the relative position information between the mobile device and at least part of the boundary. The relative positional relationship between the current position and the coordinate origin may include, for example, the distance between the current position and the coordinate origin and/or phase information in the reference coordinate system. The reference coordinate system may take the charging station as an initial point, that is, the charging station may serve as the coordinate origin of the reference coordinate system.

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

Taking FIG. 4 as an example, the satellite positioning module 312 shown in FIG. 4 may be disposed above the mobile device, and determine the current position of the mobile device by receiving signals transmitted by satellites.

The image acquisition module can capture the current image from the location of the mobile device. In one embodiment of the present application, markers may be provided on at least part of the working boundary, and the markers may be at least one of ropes, signs, fences, and fences, for example. The image acquisition module can determine the relative position between the mobile device and at least part of the working boundary according to the position of the marker in the current image. The image acquisition module can identify markers in the current image through AI recognition. During the mapping process, the image acquisition module can move along the working boundary and take images of multiple locations, and construct a boundary map based on the positions of the markers in the multiple images. During the working process of the self-mobile device, the image acquisition module can capture the current image of the position of the self-mobile device, and determine the position information of the self-mobile device 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 Simultaneous Localization and Mapping (SLAM for short) to establish a map and determine the current location of the mobile device. During the mapping process, the image acquisition module is controlled to move along the working boundary, and images of multiple positions are taken, and the transformation relationship between two consecutive frames of images is determined according to the transformation relationship. In the process of working from the mobile device, the image acquisition module can capture the current image of the location of the mobile device, and determine the current location information of the mobile device according to the slam algorithm. When the machine cannot recognize the working boundary between grass and non-grass only by using the visual sensor or the combination of the visual sensor and AI, the working boundary between the grass and the non-grass can be determined by recognizing the visual sensor combined with slam.

Taking FIG. 4 as an example, the image acquisition module 313 may also be called a vision sensor. The image collection module 313 can collect images from the moving direction of the mobile device for image recognition. The image acquisition module 313 can be set at a position close to the front of the self-moving device, or can be set at a middle position of the casing of the self-moving device. The shooting direction of the image acquisition module 313 can be fixed or rotated. For example, the image acquisition module 313 may include a camera, and the camera may rotate driven by a motor. The rotation direction of the camera can be left and right, or up and down.

The control device 313 may be signally connected with the surface recognition device and the position acquisition device. The embodiment of the present application does not specifically limit the connection manner between devices. For example, the control device may be electrically connected with the surface recognition device and the location acquisition device. For another example, the control device may be wirelessly connected with the surface recognition device and the location acquisition device. The wireless connection manner may include a Bluetooth connection, and/or a wireless fidelity (Wireless Fidelity, WIFI) connection, and the like. The control device can control the self-mobile device to move and/or work on the work surface defined by the work boundary.

The judging module 314 may be configured to judge whether the self-mobile device has reached the working boundary. The judging module 314 may first judge whether the self-mobile device 310 has reached the working boundary according to the material information recognized by the surface recognition device 311 . If it is judged according to the material information that the self-mobile device 310 has reached the working boundary, the control device 313 may control the self-mobile device 310 to walk along the working boundary, or turn to the inside of the working surface. If it is judged according to the material information that the self-mobile device has not reached the working boundary, the judging module 314 may further judge whether the self-mobile device 310 has reached the working boundary according to the position information collected by the location acquisition device 312 and at least part of the working boundary. If it is judged according to the location information that the mobile device has reached the working boundary, the control device 313 may control the self-mobile device to walk along the working boundary, or turn to the inside of the working surface. If it is judged according to both the material information and the location information that the self-mobile device has not reached the working boundary, the control device 313 may control the self-mobile device to continue working.

The positioning error of the position acquisition device in the embodiment of the present application may be greater than or equal to the recognition error of the surface recognition device. Since the recognition accuracy of the surface recognition device is high, the embodiment of the present application may first use the surface recognition device to perform boundary recognition, so as to improve the accuracy of boundary recognition. In the case where the surface recognition device does not recognize the boundary, such as for the areas on both sides of the boundary, when the material information does not change significantly, or when the surface recognition device fails, the position acquisition device can be used for boundary recognition to avoid missed cuts. phenomenon, or avoid moving from a mobile device to a location that is too far away from the work area, causing a safety hazard. The surface recognition device and the location acquisition device in the embodiment of the present application cooperate with each other and work together to improve the accuracy of the boundary recognition of the self-mobile device.

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

As an example, at least part of the working boundary may be provided with a magnetic device (eg, a magnetic strip), which 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 device. If the magnetic field strength detected by the mobile device exceeds a preset threshold, it may indicate that the mobile device has reached the working boundary. If the magnetic field strength detected by the mobile device does not exceed the preset threshold, it may indicate that the mobile device has not reached the working boundary.

As another example, a virtual wall may be set on at least part of the working boundary, and the self-moving device may include a virtual wall detection device to detect the virtual wall. The virtual wall can be established by setting an infrared sensor on the boundary, and the infrared distance emitted by the infrared sensor is the length of at least part of the working boundary. The virtual wall is a virtual wall used to block the mobile device from entering the area, and only allows the mobile device to work on one side of the virtual wall, and does not allow the mobile device to move to the other side of the virtual wall. When the self-mobile device detects the virtual wall, it means that the self-mobile device has reached the working boundary.

At least part of the working boundary in this embodiment of the present application may include a boundary map. Correspondingly, the location collecting device can be configured to collect from the relative position relationship between the mobile device and the boundary map. The position collection device may be configured to judge whether the self-mobile device has reached the working boundary according to the collected relative position information between the current position of the self-mobile device and the boundary map. For example, when the distance between the mobile device and the boundary map is less than or equal to the preset value, it can be determined that the mobile device has reached the working boundary; when the distance between the mobile device and the boundary is greater than the preset value, it can be determined that the mobile device has reached the working boundary; The mobile device does not reach the work boundary.

The embodiment of the present application does not specifically limit the manner of acquiring the boundary map (that is, the mapping process). In order to distinguish it from the process of obtaining location information during the working process, the process of obtaining the boundary map is called the mapping process, and the process of obtaining location information during the working process is called the working 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 obtained using information collected by a position collection device. It should be noted that the position acquisition device during the mapping process may be the same as or different from the position acquisition device during the working process, which is not specifically limited in this embodiment of the present application. For example, in this embodiment of the present application, an inertial navigation sensor may be used to obtain a boundary map, and a satellite positioning module may be used to obtain position information or relative position information of an automatic device. For another example, in the embodiment of the present application, the first satellite positioning module may be used to obtain a border map, and the second satellite positioning module may be used to obtain position information or relative position information of automatic equipment. The first satellite positioning module and the second satellite positioning module may be the same satellite positioning module, or different satellite positioning modules, and different satellite positioning modules may have different positioning accuracy.

In the following, the device for obtaining the boundary map is the same as the device for obtaining the location information (using the same satellite positioning module to construct the map and control the work of the mobile device) as an example to describe.

Taking the location acquisition device as an example for illustration, the satellite positioning module (GPS or GPS-RTK, etc.) is detachably or fixedly installed on the mobile device. Correspondingly, the satellite positioning module may be configured to obtain the boundary map as follows: use the satellite positioning module to collect position information of multiple position points in at least part of the working boundary, and obtain the boundary map according to the position information of the multiple position points.

For example, in the embodiment of the present application, the satellite positioning module can be used to move one or more circles along the working boundary to obtain the location information of multiple location points; and obtain the boundary map according to the location information of the multiple location points. If the satellite positioning module is detachably connected to the self-mobile device, the satellite positioning module can be disassembled from the self-mobile device, and the satellite positioning module can be directly used to obtain the position information of multiple location points and the boundary map; After the map, the satellite positioning installation module can be installed on the self-mobile device for positioning and navigation. If the satellite positioning module is fixedly connected with the self-mobile device, the self-mobile device can be manipulated (such as remotely controlled) to move along the working boundary, so as to obtain the position information of multiple position points, and obtain the boundary map; after obtaining the boundary map, you can control The self-mobile device carrying the satellite positioning module performs positioning and navigation.

In the embodiment of the present application, the boundary map can be directly used as the working boundary, and the judging module can determine whether the self-mobile device has reached 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 the positioning error is small and can be ignored. Therefore, if the satellite positioning module is used to collect a boundary map, the collected boundary map is close to the working boundary, and the boundary map can be directly used for boundary recognition.

However, for other satellite positioning modules, such as low-precision satellite positioning modules or sub-meter satellite positioning modules, when using the satellite positioning module to obtain the boundary map, because the satellite positioning module has satellite positioning errors, the obtained boundary map is different from the real one. Errors exist between working boundaries. There are two cases of this error. The first is that the boundary map shrinks relative to the working boundary. The working boundary here refers to the real working boundary. As shown in Figure 5, the boundary map 1 is indented relative to the real working boundary. The second is that the boundary map is extended relative to the real working boundary. As shown in Figure 5, the boundary map 2 is expanded relative to the real working boundary. If the boundary map 1 is used to determine whether the self-mobile device has reached the working boundary, it will cause the self-mobile device to mistakenly recognize the working area as the boundary, and some working areas cannot be processed (such as missing grass). If the border map 2 is used to determine whether the mobile device has reached the working boundary, it will cause the mobile device to recognize the non-working area as the boundary, and the mobile device will work in an area outside the working boundary.

Based on this, the embodiment of the present application may not directly use the boundary map as the working boundary, but process the boundary map to obtain the processed working boundary, and determine whether the mobile device reaches the working boundary according to the processed working boundary.

The embodiment of the present application does not specifically limit the manner of processing the boundary map to obtain the processed working boundary. For example, the boundary map can be expanded outward to obtain the working boundary. For another example, the boundary map can be shrunk inward to obtain the working boundary. The specific expansion mode or contraction mode can be determined according to the actual situation. For example, in order to improve the work efficiency of the self-mobile device, the boundary map can be extended outward to obtain the working boundary, so that the self-mobile device can complete the processing of the work area as much as possible. Taking the smart lawn mower as an example, the smart lawn mower can avoid missing cuts by extending the boundary map. For another example, in order to ensure the safety of working from the mobile device, the boundary map may be shrunk inward to obtain the working boundary, so as to prevent the mobile device from moving outside the working boundary.

In this embodiment of the present application, the extended boundary can be obtained by extending the boundary map. It is understandable that the expansion boundary is not a real working boundary, but a boundary for boundary identification. Further, the judging module can judge whether the self-mobile device has reached the working boundary according to the location information collected by the location collecting device and the extended boundary. When the judging module judges that the self-mobile device has reached the working boundary according to the position information collected by the position acquisition device and the extended boundary, the control device can control the self-mobile device to walk along the working boundary, or turn to the working surface to control the self-moving Return the equipment to the work area.

In this embodiment of the present application, the shrinking boundary can be obtained by shrinking the boundary map. It can be understood that the shrinkage boundary is not a real working boundary, but a boundary for boundary identification. Further, the judging module can judge whether the self-mobile device has reached the working boundary according to the location information collected by the location collection device and the contraction boundary. When the judging module judges that the self-mobile device reaches the working boundary according to the position information collected by the position acquisition device and the shrinkage boundary, the control device can control the self-mobile device to walk along the working boundary, or turn to the working surface to control Return to the work area from the mobile device.

Expanding the boundary map may refer to moving multiple location points on the boundary map away from the working area, and shrinking the boundary map may refer to moving multiple location points on the boundary map closer to the working area.

For the convenience of description, the boundary map acquired by the location acquisition device is referred to as the boundary before processing below. The processed boundary can be an expanding boundary or a shrinking boundary.

The embodiment of the present application does not specifically limit the distance between the boundary before processing and the boundary after processing.

As an example, 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 the working process. For example, if the accuracy of the location acquisition device during the mapping process is relatively high, and there is basically no error between the boundary map collected by it and the real working boundary, then the distance between the boundary before processing and the boundary after processing can be equal to that during the working process. The positioning error of the position acquisition device.

As another example, 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 the mapping process. For example, if the accuracy of the location acquisition device in the working process is relatively high, and there is basically no error between the location information obtained from the mobile device and the real location information, the distance between the boundary before processing and the boundary after processing can be equal to The positioning error of the position acquisition device during the mapping process.

As another example, the distance between the pre-processed boundary and the processed boundary may be equal to the sum of the positioning error of the position acquisition device during the mapping process and the positioning error of the position acquisition device during the working process. If there are positioning errors in both position acquisition devices, the distance between the boundary before processing and the boundary after processing 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 obtain the border map and location information, the distance between the pre-processed border and the processed border can be equal to twice the positioning error of the satellite positioning module. For example, in order to improve the working efficiency of the mobile device, the boundary before processing can be expanded outward by twice the satellite positioning error to obtain the boundary after processing. For another example, in order to ensure the safety of the mobile device, the boundary before processing can be shrunk inward by twice the satellite positioning error to obtain the boundary after processing.

The following describes the difference between the position acquisition device in the mapping process and the position acquisition device in the working process as an example. Of course, the following conditions are also applicable to the same position acquisition device during the mapping process as the position acquisition device during the work process.

In order to distinguish, the embodiment of the present application refers to the location acquisition device in the mapping process as a smart device. The smart device may be a mobile phone with a location collection function, or may be an independent device with only a location collection function. The automatic working system may include the smart device, which has a position collection function. The smart device may include at least one of the following: an ultrasonic sensor, a radar sensor, an optical sensor, a UWB sensor, an inertial navigation sensor, a satellite positioning module, and an image acquisition module.

The smart device may be configured to obtain the boundary map in the following manner: the smart device is used to collect position information of multiple position points in at least part of the working boundary, and the boundary map is obtained according to the position information of the multiple position points. The smart device can obtain the boundary map in any of the ways described above. For example, in the case that the smart device includes a satellite positioning module, the smart device can acquire the longitude information and/or latitude information of multiple location points to obtain a border map. For another example, when the smart device includes an inertial navigation sensor, the smart device may acquire distance and/or phase information of multiple location points relative to the coordinate origin to obtain a boundary map.

Similar to the method described above, the embodiment of the present application can directly use the boundary map acquired by the smart device to identify the boundary. Or, because the smart device has a device positioning error, the embodiment of the present application may process the boundary map acquired by the smart device, and use the processed boundary to identify the boundary. Wherein, the device positioning error of the smart device is greater than or equal to the positioning error of the surface recognition device.

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

There is a device positioning error in the process of using the smart device to obtain the boundary map, and there is a device positioning error in the process of using the location acquisition device to collect the location information from the mobile device. In order to compensate for the positioning errors of the two devices, the embodiment of the present application can The border map is processed so that the distance between the processed border and the pre-processed border is equal to the sum of the equipment positioning error and the device positioning error.

After the smart device obtains the boundary map, it can send the boundary map to the self-mobile device, so that the self-mobile device can identify the boundary. After receiving the boundary map, the mobile device may perform the above processing on the boundary map to obtain a processed boundary map. The judging module can judge whether the mobile device has reached the working boundary according to the location information of the mobile device and the processed boundary map.

The solution of the embodiment of the present application will be described in detail below by taking two different satellite positioning modules as an example with reference to FIG. 5 .

In the embodiment of the present application, the first satellite positioning module can be used to move along the real working boundary to obtain the location information of multiple location points, and obtain the boundary map according to the location information of the multiple location points. Due to the positioning error of the first satellite positioning module, such as the positioning error d1, the obtained boundary map is located between the boundary map 1 and the boundary map 2 . Boundary map 1 is the boundary map obtained by indenting the real boundary by d1, and boundary map 2 is the boundary map obtained by expanding the real boundary outward by d1.

In this embodiment of the present application, the second satellite positioning module may be used to obtain the location information from the mobile device. The judging module can determine whether the mobile device has reached the border according to the location information of the mobile device and the border map. Due to the positioning error of the second satellite positioning module, such as the positioning error d2, when performing boundary recognition, the self-mobile device may recognize the boundary map 3 as the boundary, and may also recognize the boundary map 4 as the boundary. In other words, the boundary finally recognized from the mobile device is between the boundary map 3 and the boundary map 4 .

If in order to improve the working efficiency of the self-mobile device and avoid the self-mobile device from identifying the border map 3 as a border, the embodiment of the present application can extend the border map obtained by the first satellite positioning module outward by a distance of (d1+d2). This ensures that the working area defined by the real working boundary can be processed.

If in order to ensure that the self-mobile device does not move to the non-working area under any circumstances and avoid the self-mobile device from identifying the boundary map 4 as a boundary, the embodiment of the present application can indent the boundary map obtained by the first satellite positioning module (d1 +d2) distance.

Taking the boundary map obtained by the satellite positioning module as an example, due to the satellite positioning error of the satellite positioning module, there is an error between the obtained boundary map and the real working boundary. In order to offset the error, the embodiment of the present application can eliminate the error by taking an intermediate value through multiple mappings. To illustrate, the embodiment of the present application can control the satellite positioning module to move multiple circles along the working boundary to obtain multiple boundary maps. Further, the position information of the same position point on the multiple boundary maps can be averaged to obtain the boundary map. The error between the boundary map obtained after mean value processing and the real working boundary has been greatly reduced, so that the boundary map can basically coincide with the real working boundary.

In this case, the errors in the process of building the boundary map have been basically eliminated, and this embodiment of the present application may only consider the errors in the work process. In order to compensate for this error, the embodiment of the present application may process the boundary map so that the distance between the processed boundary and the pre-processed boundary is equal to the positioning error of the position acquisition device during the working process.

The above is only a preferred embodiment of the application, and is not intended to limit the application. Any modifications, equivalent replacements, etc. made within the spirit and principles of the application shall be included in the protection scope of the application. within.

Claims

An automatic working system, characterized in that the automatic working system includes: self-moving equipment, which moves and/or works on the working surface defined by the working boundary, and is configured with:

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

A location collection device configured to collect location information of the self-mobile device and/or location information between the self-mobile device and at least part of the working boundary;

a control device, signal-connected to the surface recognition device and the position acquisition device, the control device is configured to control the self-moving device to move and/or work on the work surface defined by the work boundary,

The self-moving device is also equipped with: a judging device configured to judge whether the self-moving device has reached the working boundary, and the judging module judges whether the self-moving device has reached the working boundary according to the material information identified by the surface recognition device. If the working boundary is not reached, if it is judged that the self-mobile device has reached the working boundary according to the position information collected by the position acquisition device and the at least part of the working boundary, the control device controls the self-moving device to reach the working boundary. A mobile device walks along the work boundary, or turns into the work surface.
The automatic working system according to claim 1, wherein the at least part of the working boundary is an open working boundary.
The automatic working system according to claim 1, wherein at least part of the working boundary is provided with a boundary device to form the working boundary, and the self-moving device includes: a signal detection sensor, which is detected by the signal detection sensor The virtual signal sent by the boundary device is used to determine whether the mobile device has reached the working boundary according to the virtual signal.
The automatic working system according to claim 1, wherein the surface recognition device comprises at least one of the following: a radar sensor, an ultrasonic sensor, a capacitive sensor, and an image acquisition module.
The automatic working system according to claim 4, wherein when the surface recognition device is an image acquisition module, the surface recognition device is configured to recognize the material information of the work surface in the following manner:

Using the image acquisition module to capture the current image of the location of the self-mobile device;

The current image is input into an artificial intelligence model to identify material information of the working surface.
The automatic working system according to claim 1, wherein the position acquisition device comprises at least one of the following: ultrasonic sensors, radar sensors, optical sensors, ultra-wideband UWB sensors, inertial navigation sensors, satellite positioning modules, image acquisition module.
The automated working system of claim 1, wherein said at least part of the working boundary comprises a boundary map,

Correspondingly, the location collection device is configured to collect location information between the self-mobile device and at least part of the working boundary, including:

collecting 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 has reached the working boundary according to the relative position information between the current position of the self-mobile device and the boundary map.
The automatic working system according to claim 7, wherein when the position acquisition device is a satellite positioning module, the satellite positioning module is detachable or fixedly installed on the self-moving device, correspondingly,

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

The satellite positioning module is used to collect the position information of a plurality of position points in the at least part of the working boundary, and the boundary map is obtained according to the position information of the plurality of position points.
The automatic working system according to claim 8, wherein the satellite positioning module has a satellite positioning error, and the satellite positioning error is greater than or equal to the recognition error of the surface recognition device.
The automatic working system according to claim 7, characterized in that, the automatic working system also includes: an intelligent device with a position acquisition function, correspondingly,

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

The smart device is used to collect position information of multiple position points in the at least part of the working boundary, and the boundary map is obtained according to the position information of the multiple position points.
The automatic working system according to claim 10, wherein the smart device has a device positioning error, and the device positioning error is greater than or equal to the positioning error of the surface recognition device.
The automatic working system according to claim 7, wherein the judging that the self-mobile device reaches the working boundary according to the position information collected by the position collecting device and the at least part of the working boundary comprises:

extending the boundary map to obtain an extended boundary;

Judging that the self-mobile device has reached the working boundary according to the location information collected by the location collecting device and the extended boundary.
The automatic working system according to claim 12, wherein if the boundary map is obtained by using the position acquisition device, the distance between the extended boundary and the boundary map is equal to that of the position acquisition device The positioning error, or, is equal to twice the positioning error of the position acquisition device.
The automatic working system according to claim 12, wherein if the boundary map is obtained by using an intelligent device, the distance between the extended boundary and the boundary map is equal to the positioning error of the position acquisition device , or equal to the device positioning error of the smart device, or equal to the sum of the positioning error of the position acquisition device and the device positioning error of the smart device.
The automatic working system according to claim 7, wherein the judging that the self-mobile device reaches the working boundary according to the position information collected by the position collecting device and the at least part of the working boundary comprises:

shrinking the border map yields a shrunk border;

It is judged that the self-mobile device reaches the working boundary according to the location information collected by the location collecting device and the contraction boundary.
The automatic working system according to claim 15, wherein if the boundary map is obtained by using the position acquisition device, the distance between the shrinking boundary and the boundary map is equal to that of the position acquisition device The positioning error, or, is equal to twice the positioning error of the position acquisition device.
The automatic working system according to claim 15, wherein if the boundary map is obtained by using an intelligent device, the distance between the shrinking boundary and the boundary map is equal to the positioning error of the position acquisition device , or equal to the device positioning error of the smart device, or equal to the sum of the positioning error of the position acquisition device and the device positioning error of the smart device.