Self-moving device track accumulation detection method, self-moving device, and medium

Abstract

The present application discloses a self-moving device track accumulation detection method, a self-moving device, and a medium. The method comprises: when it is determined, by means of a level detection sensor in a self-moving device, that the self-moving device is located in a region of a first type, detecting a current in track wheels in the self-moving device; when the current is greater than a first preset current for a preset duration, determining that objects are accumulated on a track in the self-moving device; and when it is determined, by means of the level detection sensor in the self-moving device, that the self-moving device is located in a region of a second type, after the self-moving device is controlled to move to the region of the first type, determining, by detecting the current in the track wheels in the self-moving device, whether objects are accumulated on the track in the self-moving device. Whether objects are accumulated on the track in the self-moving device can be detected in both the region of the first type and the region of the second type, thereby not only avoiding affecting the working efficiency of the self-moving device, but also avoiding damage to mechanical components of the self-moving device.

Description

Methods for detecting track stacking in self-moving equipment, self-moving equipment and media Technical Field

[0001] This application relates to the field of self-moving equipment detection technology, and in particular to a method for detecting track stacking of self-moving equipment, self-moving equipment and medium. Background Technology

[0002] This self-moving robot, designed specifically for gardens, is equipped with tracks to traverse complex terrain. Wheels are cleverly integrated within the tracks to enhance stability and efficiency. However, it's worth noting that the tiny gaps between the tracks and wheels pose a potential problem; during operation, small objects in the garden, such as fallen leaves and pebbles, can easily enter the robot through these gaps.

[0003] If users fail to detect and remove these small objects from the self-moving device in a timely manner, they may gradually accumulate and place an additional burden on the robot's walking mechanism. This could not only reduce the working efficiency of the self-moving device but also cause wear and tear on its mechanical parts, or even lead to malfunctions.

[0004] Therefore, the inventors realized that there was an urgent need to find a new technical solution to solve the above-mentioned technical problems. Technical issues

[0005] Therefore, it is necessary to provide a method for detecting track stacking on self-moving equipment, a self-moving equipment, and a medium to address the aforementioned technical problems, in order to solve the technical problems in the prior art where the accumulation of objects on the tracks of self-moving equipment affects work efficiency and increases the risk of failure. Technical solutions

[0006] To achieve the above objectives, a method for detecting track stacking on a self-moving device is provided, the method comprising:

[0007] When the self-moving device is determined to be located in a first type of area by a level detection sensor in the self-moving device, the current in the track wheels of the self-moving device is detected;

[0008] When the current is greater than the first preset current for a preset duration, it is determined that the track in the self-moving device is piled up with objects.

[0009] When the self-moving device is determined to be located in a second type of area by the horizontal detection sensor in the self-moving device, it is controlled to move to a first type of area. Then, the current in the track wheels of the self-moving device is detected to determine whether the track of the self-moving device is piled up with objects.

[0010] To achieve the above objectives, a self-moving device is also provided, including a horizontal detection sensor and a controller. The horizontal detection sensor and the controller are communicatively connected, and the controller controls the self-moving device's track stacking detection program to perform the following steps:

[0011] When the self-moving device is determined to be located in a first type of area by a level detection sensor in the self-moving device, the current in the track wheels of the self-moving device is detected;

[0012] When the current is greater than the first preset current for a preset duration, it is determined that the track in the self-moving device is piled up with objects.

[0013] When the self-moving device is determined to be located in a second type of area by the horizontal detection sensor in the self-moving device, it is controlled to move to a first type of area. Then, the current in the track wheels of the self-moving device is detected to determine whether the track of the self-moving device is piled up with objects.

[0014] To achieve the above objectives, a computer-readable storage medium is also provided, which stores a computer program that, when executed by a processor, performs the following steps:

[0015] When the self-moving device is determined to be located in a first type of area by a level detection sensor in the self-moving device, the current in the track wheels of the self-moving device is detected;

[0016] When the current is greater than the first preset current for a preset duration, it is determined that the track in the self-moving device is piled up with objects.

[0017] When the self-moving device is determined to be located in a second type of area by the horizontal detection sensor in the self-moving device, it is controlled to move to a first type of area. Then, the current in the track wheels of the self-moving device is detected to determine whether the track of the self-moving device is piled up with objects. Beneficial effects

[0018] The method for detecting track accumulation on a self-moving device provided in this application includes: when the self-moving device is determined to be located in a first type of area by a horizontal detection sensor in the self-moving device, detecting the current in the track wheels of the self-moving device; when the current is greater than a first preset current for a preset duration, determining that the track of the self-moving device is piled up with objects; when the self-moving device is determined to be located in a second type of area by a horizontal detection sensor in the self-moving device, controlling the self-moving device to move to the first type of area, and continuing to determine whether the track of the self-moving device is piled up with objects by detecting the current in the track wheels of the self-moving device. This technical solution performs current detection in the first type of area to determine whether the track of the self-moving device is piled up with objects, and controls the self-moving device to move to the first type of area for detection in the second type of area. Thus, detection of track accumulation on the self-moving device can be achieved in both the first and second type of areas. When track accumulation is found, it can be detected in a timely manner and the corresponding user can be notified for cleanup, which not only avoids affecting the working efficiency of the self-moving device but also avoids damage to the mechanical components of the self-moving device.

[0019] Details of one or more embodiments of this application are set forth in the following drawings and description, and other features and advantages of this application will become apparent from the specification, drawings and claims. Attached Figure Description

[0020] To more clearly illustrate the technical solutions of the embodiments of this application, the drawings used in the description of the embodiments of this application will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0021] Figure 1 is a flowchart illustrating an embodiment of the method for detecting track stacking of a self-moving device according to this application.

[0022] Figure 2 is a schematic block diagram of an embodiment of the mobile device of this application;

[0023] Figure 3 is a schematic diagram of the vehicle tracks in the self-moving device of this application. The best embodiment of the present invention

[0024] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0025] As shown in Figure 1, an embodiment of this application provides a method for detecting track stacking in a self-moving device. This method can be applied to the controller in the self-moving device, where the controller can also be understood as an MCU (Microcontroller Unit) or other devices with the same function. The method includes the following steps:

[0026] S10, when the self-moving device is determined to be located in a first type of area by the horizontal detection sensor in the self-moving device, the current in the track wheels of the self-moving device is detected.

[0027] Understandably, the horizontal detection sensor can be an IMU sensor, or Inertial Measurement Unit, which measures the angle, velocity, and acceleration of an object. It typically consists of an accelerometer and a gyroscope. The accelerometer works by sensing the acceleration of an object and converting it into an electrical signal. By analyzing these signals, the acceleration values ​​along the X, Y, and Z axes can be obtained. Similarly, the gyroscope senses the change in angular velocity when an object rotates and converts it into an electrical signal. By analyzing these signals, the angular velocity values ​​along the X, Y, and Z axes can be obtained. The self-moving device is a garden robot with functional modules. The functional modules can be leaf blowing modules and weeding modules, etc. The garden robot in this embodiment is preferably suitable for garden robots in weeding scenarios (in weeding scenarios, grass clippings and stones are more likely to get stuck in the tracks of the self-moving device); the first type of area refers to a flat area in the working area of ​​the self-moving device, such as the area in the garden area where the body of the self-moving device is less than 10 degrees relative to the ground; the tracks are set on both sides of the self-moving device (as shown in Figure 3), and corresponding walking wheels can be set in the tracks. There can be two walking wheels, and a walking motor can be set between the walking wheels. The current in the track wheels of the self-moving device can be detected by the feedback circuit set in the motor, or by the preset current sensor.

[0028] S20, when the current is greater than the first preset current for a preset duration, it is determined that the track in the self-moving device is piled up with objects.

[0029] Understandably, the current is a track motor current detected in real time. This current can be a value at a point in time or an average value over a certain time range. The first preset current is a value obtained in advance through experimental measurement (that is, the value obtained by measuring different stacking conditions of the self-moving equipment track in the first type of area - planar area, such as continuously placing corresponding stacking objects inside the track).

[0030] S30, after determining that the self-moving device is located in a second type of area by the horizontal detection sensor in the self-moving device, the self-moving device is controlled to move to a first type of area, and then the track in the self-moving device is further determined by detecting the current in the track wheels of the self-moving device to determine whether the track in the self-moving device is piled up with objects.

[0031] Understandably, the second type of area refers to a portion of the non-flat area in the working area of ​​the self-moving device, such as an area in the courtyard where the self-moving device body is at an angle of 10 degrees or more relative to the ground. The detection of the second type of area can be carried out in the first type of area instead of the first type of area. The specific reason is that in the courtyard area, the area of ​​the first type of flat area is likely to be larger than the area of ​​the second type of non-flat area. In addition, on the second type of non-flat area, the self-moving device is not conducive to detection at different slopes.

[0032] In the embodiments of steps S10 to S30, current detection is performed in the first type of area to determine whether the track in the self-moving device is piled up with objects. In the second type of area, the self-moving device is controlled to move to the first type of area for detection. In this way, whether the track in the self-moving device is piled up with objects can be detected in both the first type of area and the second type of area. When there is a pile of objects on the track, it can be detected in time and the corresponding user can be notified to clean it up. This not only avoids affecting the working efficiency of the self-moving device, but also avoids damage to the mechanical parts of the self-moving device.

[0033] Further, determining that the self-moving device is located in a first type of area via a horizontal detection sensor in the self-moving device includes:

[0034] The tilt angle of the self-moving device's body relative to the horizontal plane of the area is determined by a horizontal detection sensor in the self-moving device.

[0035] When the tilt angle is a preset target tilt angle, the self-moving device is determined to be located in the area of ​​the first type.

[0036] Understandably, the tilt angle identified by the horizontal detection sensor in the self-moving device is matched with the stored preset target tilt angle. Tilting angles less than 10 degrees can be preset as target tilt angles, such as setting the target tilt angle starting from 1 degree.

[0037] Specifically, the acceleration values ​​(ax, ay, az) in the x, y, and z directions are obtained from the accelerometer of the horizontal detection sensor; the tilt angles are calculated: the roll angle (Roll, θx) about the x-axis is calculated using the formula θx = arctan(ay / √(ax² + az²)), and the pitch angle (Pitch, θy) about the y-axis is calculated using the formula θy = arctan(-ax / √(ay² + az²)).

[0038] The self-moving device in this embodiment can accurately identify the type of area it is in using a horizontal detection sensor, and perform corresponding operations as needed, which helps to improve the autonomy and safety of the self-moving device, enabling it to more effectively complete the task of detecting the accumulation of tracks on the self-moving device.

[0039] Further, detecting the current in the track wheels of the self-moving device includes:

[0040] Determine the signal transmitted by the walking motor corresponding to the track of the self-moving device;

[0041] Determine whether data conversion processing is required based on the signal type of the signal;

[0042] After determining that data conversion processing is required, the signal data is converted and processed, and the current in the track wheels of the self-moving device is obtained by analyzing the converted signal.

[0043] After determining that no data conversion processing is required, the current in the track wheels of the self-moving device is obtained by analyzing the signal.

[0044] Understandably, the power for the tracks of an automated mobile device comes from the drive of a walking motor. Thus, the current passing through the tracks and wheels of the mobile device can be determined by detecting the signal generated by the walking motor. Data conversion refers to converting analog signals into digital signals using an analog-to-digital converter (ADC). In the corresponding detection device, current sensors that can output digital signals are used for detection, eliminating the need for data conversion processing. The analysis process processes and analyzes the collected current signals to extract information such as the current's trend, peak value, and average value.

[0045] This embodiment determines whether data conversion is needed to minimize data loss and distortion, thereby preserving key information in the signal and providing a reliable data foundation for subsequent analysis; it can directly analyze the signal and accurately obtain the current value of the track wheels in the self-moving device.

[0046] Further, determining that the track in the self-moving device is piled up with objects when the current is greater than the first preset current for a preset duration includes:

[0047] A changing current is determined on the current change curve based on the value of the current.

[0048] [Correction 13.11.2025 according to Rule 91] When the changing current is greater than the first preset current and less than the second preset current, it is determined that the track in the self-moving device is piled up with objects.

[0049] Understandably, the current of the travel motor may be at different values ​​under different operating conditions. In order to determine a stable comparison value, a variable current can be determined from the current change curve corresponding to the current. This variable current can be the peak value, minimum value, mean value, or mode value of the curve. The value of the second preset current is greater than the value of the first preset current. The purpose of setting the second preset current is to avoid the current value being too high due to abnormal operation of the travel motor. In this way, setting the second preset current can determine whether there is an abnormality in the current travel motor, so as to avoid misjudging the condition of the track accumulation.

[0050] Furthermore, before controlling the self-moving device to move to the first type of area after determining by the horizontal detection sensor in the self-moving device that the self-moving device is located in the second type of area, the method further includes:

[0051] Centered on the region of the second type, at least one region of the first type is determined from the preset map corresponding to the self-mobile device, which is at least a preset distance threshold from the region of the second type.

[0052] Understandably, the second type of area is a non-planar area, and there will be planar areas around the non-planar area; the preset map can be a map created by the self-moving device after it has walked through its yard area once, wherein, based on the preset map, the first type of area closest to the second type of area can be determined in any direction, so as to control the self-moving device to continue to detect the track stacking situation in the first type of area;

[0053] In this embodiment, the self-moving device can determine the target detection area when it is not in the detection area, reducing unnecessary waiting and stagnation time, thereby improving the efficiency of detection task execution and avoiding misjudgment of detection in non-detection areas.

[0054] Furthermore, before detecting the current in the track wheels of the self-moving device, the method further includes:

[0055] The obstacle detection sensor in the self-moving device identifies whether an obstacle exists in the area of ​​the first type.

[0056] When there are no obstacles, the process of detecting the current in the tracks and wheels of the self-moving device is initiated.

[0057] Understandably, obstacle recognition sensors include, but are not limited to, one or more of the following sensors: lidar, radar, camera, ultrasonic radar, and infrared sensor. Lidar works by emitting a laser beam and measuring the time difference between emission and reception to calculate the distance to the obstacle. Radar works by emitting radio waves and receiving their reflected signals to detect objects in the surrounding environment. Cameras work by capturing video images to identify and understand the surrounding environment. Ultrasonic radar works by emitting ultrasonic waves and receiving their reflected signals to measure the distance to objects. Infrared sensors work by measuring distance based on the principle of triangulation.

[0058] In this embodiment, when the area is in the first type of area, it is determined whether the area is an obstacle to eliminate the possibility that the obstacle will block the self-moving device and cause the current of the walking motor to increase. In this way, it can be ensured that the track accumulation can be detected in the first type of area.

[0059] In another embodiment, when an obstacle is present, if it is determined that the current in the walking motor is rising and the current position of the self-moving device has not changed significantly, the user is reminded that the self-moving device is blocked by an obstacle, and the process of detecting the current in the track wheels of the self-moving device is not initiated.

[0060] Furthermore, before determining that the self-moving device is located in the second type of area by the horizontal detection sensor in the self-moving device, the method further includes:

[0061] The height recognition sensor in the self-moving device determines whether the body of the self-moving device was lifted by a person.

[0062] When not manually moved, the process proceeds to determine that the self-moving device is located in a second type of area using a horizontal detection sensor in the self-moving device.

[0063] Understandably, the height recognition sensor can be installed on the bottom of the self-moving device to determine whether the self-moving device has been artificially lifted by measuring the distance between it and the ground. This can be done through principles such as acoustic ranging, laser ranging, and ultrasonic ranging. Specifically, the height recognition sensor can first identify the first vertical distance between the self-moving device and the ground before it is lifted. Then, after determining that the self-moving device is not moving, the height recognition sensor can identify the second vertical distance between the self-moving device and the ground under the current condition. Finally, after comparing the second vertical distance with the first vertical distance, it can be determined that the self-moving device has been artificially lifted.

[0064] This embodiment determines whether the self-moving device's body was lifted by a person, thus eliminating the possibility that the self-moving device was placed in the first type of area due to being lifted by a person. This ensures that the second type of area can be detected subsequently.

[0065] In another embodiment, when the device is manually lifted, the process of determining that the self-moving device is located in a second type of region using the horizontal detection sensor in the self-moving device is not initiated. In this embodiment, when the device is manually lifted, the area where the self-moving device is located may also belong to a first type of region; therefore, the process of detecting the second type of region is not initiated, saving resources.

[0066] Furthermore, after controlling the self-moving device to move to the first type of area, and further determining whether the tracks of the self-moving device are piled up with objects by detecting the current in the tracks and wheels of the self-moving device, the method further includes:

[0067] Determine whether the second type of region in the self-moving device is in a fixed state;

[0068] When in the fixed state, the location corresponding to the second type of area is marked in the preset map corresponding to the self-mobile device, so as to directly control the self-mobile device to move to the first type of area after it moves to the second type of area;

[0069] When not in the fixed state, the area recognition sensor in the self-moving device determines in advance whether the first type of area still exists. If it does not exist, the self-moving device moves to the first type of area and directly enters the process of detecting the current in the track wheels of the self-moving device.

[0070] Understandably, a fixed state refers to whether the second type of area continues to exist. The second type of area is an area with a certain tilt angle, formed by piles of materials, stones, etc., and may be cleared away. Thus, the fixed state of the second type of area is the state of not continuing to exist. The area recognition sensor includes, but is not limited to, one or more sensors such as LiDAR, radar, camera, ultrasonic radar, and infrared sensor, which mainly identify whether the second type of area still has a tilt angle. Any area that the self-moving device has walked through can be marked in the preset map, and the corresponding position of the second type of area can also be marked. When the self-moving device walks and works in the courtyard area, it can walk through the courtyard area multiple times at different times.

[0071] [Corrected according to Rule 91, 13.11.2025] This embodiment can determine whether the second type of area is in a fixed state. When it is in a fixed state, the location of the fixed area is marked on a preset map. The self-moving device can go directly to the first type of area after moving to the area without additional judgment, which improves the working efficiency of the self-moving device. When it is not in a fixed state, the existence of the first type of area can be detected in advance by the area recognition sensor, which can avoid the situation that the tilt angle of the area does not exist only after the device arrives, thereby reducing invalid movement and possible resource waste, and thus improving the working efficiency of the self-moving device.

[0072] This application provides a method for detecting track accumulation on a self-moving device, belonging to the field of self-moving device detection technology. When the self-moving device is determined to be located in a first-type area by a horizontal detection sensor, the current in the track wheels is detected. When the current exceeds a first preset current for a preset duration, it is determined that the track on the self-moving device is piled up with objects. When the self-moving device is determined to be located in a second-type area by the horizontal detection sensor, the self-moving device is controlled to move to the first-type area, and the current in the track wheels is detected again to further determine whether the track on the self-moving device is piled up with objects. Current detection is performed in the first-type area to determine whether the track on the self-moving device is piled up with objects; in the second-type area, the self-moving device is controlled... The equipment is moved to the first type of area for detection. In this way, in both the first and second type of areas, it is possible to detect whether the tracks of the self-moving equipment are piled up with objects. When there are piled-up objects on the tracks, they can be detected in time and the corresponding user can be notified to clean them up. This not only avoids affecting the working efficiency of the self-moving equipment (reducing the burden on the machine's movement and power consumption), but also avoids damage to the mechanical components of the self-moving equipment (reducing the impact of piled-up objects on the normal operation of the walking motor and walking wheels). Detecting track pile-up in the first type of area - flat ground - can improve detection efficiency and reduce the workload before detection or the time cost of detection. If detection is carried out in the second type of area - non-flat ground - it is necessary to measure the data of the area at different tilt angles in advance to determine the corresponding preset current.

[0073] It should be understood that the sequence number of each step in the above embodiments does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of this application.

[0074] As shown in Figure 2, a self-moving device is also provided, comprising a horizontal detection sensor and a controller. The horizontal detection sensor and controller are communicatively connected. The controller controls the motors in the motor control system to implement the steps of the self-moving device track stacking detection method. The self-moving device is equipped with a working motor for operation and a walking motor for movement. The controller can control the start and stop of the walking motor. Various sensors are installed on the body and front of the device, and the controller can also control the start and stop of these sensors and receive signals transmitted from them.

[0075] The controller's execution functions correspond one-to-one with the self-moving device track stacking detection method described in the above embodiments. Specific limitations of the controller can be found in the limitations of the self-moving device track stacking detection method described above, and will not be repeated here. The execution process of each sub-module in the controller can be found in the limitations of the self-moving device track stacking detection method described above, and will not be repeated here. It can be implemented entirely or partially through software, hardware, or a combination thereof. Each sub-module can be embedded in the controller in hardware form or independent of the controller, or it can be stored in the controller's memory in software form, so that the controller can call and execute the operations corresponding to each of the above sub-modules.

[0076] In one embodiment, this application also provides one or more readable storage media storing computer-readable instructions. The readable storage media provided in this embodiment include non-volatile readable storage media and volatile readable storage media. The readable storage media stores computer-readable instructions, which, when executed by one or more processors, cause one or more processors to implement the steps of the self-moving device track stacking detection method described in the above embodiment.

[0077] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by instructing related hardware with computer-readable instructions. These computer-readable instructions can be stored in a non-volatile readable storage medium or a volatile readable storage medium. When executed, these computer-readable instructions can include the processes of the embodiments of the above methods. Any references to memory, storage, databases, or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory may include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), dual data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), RAMbus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc.

[0078] Those skilled in the art will clearly understand that, in practical applications, the above functions can be assigned to different functional units or modules as needed, that is, the internal structure of the self-moving device can be divided into different functional units or modules to complete all or part of the functions described above.

[0079] The above-described embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application, and should all be included within the protection scope of this application.

Claims

1. A self-moving device track accumulation condition detection method, wherein, The method includes: When the self-moving device is determined to be located in a first type of area by a level detection sensor in the self-moving device, the current in the track wheels of the self-moving device is detected; When the current is greater than the first preset current for a preset duration, it is determined that the track in the self-moving device is piled up with objects. When the self-moving device is determined to be in a second type of area by the horizontal detection sensor in the self-moving device, it is controlled to move to a first type of area. Then, the current in the track wheels of the self-moving device is detected to determine whether the track of the self-moving device is piled up with objects.

2. The self-moving apparatus track accumulation condition detection method according to claim 1, wherein, The step of determining that the self-moving device is located in a first type of area using a horizontal detection sensor in the self-moving device includes: The tilt angle of the self-moving device's body relative to the horizontal plane of the area is determined by a horizontal detection sensor in the self-moving device. When the tilt angle is a preset target tilt angle, the self-moving device is determined to be located in the area of ​​the first type.

3. The self-moving apparatus track accumulation condition detection method according to claim 1, wherein, The detection of the current in the track wheels of the self-moving device includes: Determine the signal transmitted by the walking motor corresponding to the track of the self-moving device; Determine whether data conversion processing is required based on the signal type of the signal; After determining that data conversion processing is required, the signal data is converted and processed, and the current in the track wheels of the self-moving device is obtained by analyzing the converted signal. After determining that no data conversion processing is required, the current in the track wheels of the self-moving device is obtained by analyzing the signal.

4. The self-moving apparatus track accumulation condition detection method according to claim 1, wherein, The step of determining that the track in the self-moving device is piled up with objects when the current is greater than the first preset current for a preset duration includes: A changing current is determined on the current change curve based on the value of the current. When the changing current is greater than a first preset current and less than a second preset current, it is determined that the track in the self-moving device is piled up with objects.

5. The self-moving apparatus track accumulation condition detection method according to claim 1, wherein, Before controlling the self-moving device to move to the first type of area after determining that the self-moving device is located in the second type of area by the horizontal detection sensor in the self-moving device, the method further includes: Centered on the region of the second type, at least one region of the first type is determined from the preset map corresponding to the self-mobile device, which is at least a preset distance threshold from the region of the second type.

6. The self-moving apparatus track accumulation condition detection method according to claim 1, wherein Before detecting the current in the track wheels of the self-moving device, the method further includes: The obstacle detection sensor in the self-moving device identifies whether an obstacle exists in the area of ​​the first type. When there are no obstacles, the process of detecting the current in the tracks and wheels of the self-moving device is initiated.

7. The self-moving apparatus track accumulation condition detection method according to claim 1, wherein, Before determining that the self-moving device is located in the second type of area by using a horizontal detection sensor in the self-moving device, the method further includes: The height recognition sensor in the self-moving device determines whether the body of the self-moving device was lifted by a person. When not manually moved, the process proceeds to determine that the self-moving device is located in a second type of area using a horizontal detection sensor in the self-moving device.

8. The self-moving apparatus track accumulation condition detection method according to any one of claims 1 to 7, wherein, After controlling the self-moving device to move to the first type of area, and further determining whether the tracks of the self-moving device are piled up with objects by detecting the current in the tracks and wheels of the self-moving device, the method further includes: Determine whether the second type of region in the self-moving device is in a fixed state; When in the fixed state, the location corresponding to the second type of area is marked in the preset map corresponding to the self-mobile device, so as to directly control the self-mobile device to move to the first type of area after it moves to the second type of area; When not in the fixed state, the area recognition sensor in the self-moving device determines in advance whether the first type of area still exists. If it does not exist, the self-moving device moves to the first type of area and directly enters the process of detecting the current in the track wheels of the self-moving device.

9. A self-moving device, wherein, The system includes a horizontal detection sensor and a controller for a self-moving device, which are connected in communication. The controller controls the self-moving device's track stacking detection program to implement the following steps. When the self-moving device is determined to be located in a first type of area by a level detection sensor in the self-moving device, the current in the track wheels of the self-moving device is detected; When the current is greater than the first preset current for a preset duration, it is determined that the track in the self-moving device is piled up with objects. When the self-moving device is determined to be located in a second type of area by the horizontal detection sensor in the self-moving device, it is controlled to move to a first type of area. Then, the current in the track wheels of the self-moving device is detected to determine whether the track of the self-moving device is piled up with objects.

10. The self-moving device of claim 9, wherein, The self-moving device is located in a first type of area by a horizontal detection sensor in the self-moving device, and the controller controls the self-moving device track stacking detection program to implement the following steps; The tilt angle of the self-moving device's body relative to the horizontal plane of the area is determined by a horizontal detection sensor in the self-moving device. When the tilt angle is a preset target tilt angle, the self-moving device is determined to be located in the area of ​​the first type.

11. The self-moving device of claim 9, wherein, The detection of current in the track wheels of the self-moving device, and the controller controlling the self-moving device track stacking detection program to implement the following steps; Determine the signal transmitted by the walking motor corresponding to the track of the self-moving device; Determine whether data conversion processing is required based on the signal type of the signal; After determining that data conversion processing is required, the signal data is converted and processed, and the current in the track wheels of the self-moving device is obtained by analyzing the converted signal. After determining that no data conversion processing is required, the current in the track wheels of the self-moving device is obtained by analyzing the signal.

12. The self-mobility device of claim 9, wherein, When the current is greater than the first preset current for a preset duration, it is determined that the track in the self-moving device is piled up with objects. The controller controls the self-moving device track pile-up detection program to implement the following steps. A changing current is determined on the current change curve based on the value of the current. When the changing current is greater than a first preset current and less than a second preset current, it is determined that the track in the self-moving device is piled up with objects.

13. The self-mobility device of claim 9, wherein, Before controlling the self-moving device to move to the first type of area after determining that the self-moving device is located in the second type of area by the horizontal detection sensor in the self-moving device, the controller controls the self-moving device track stacking detection program to also perform the following steps; Centered on the region of the second type, at least one region of the first type is determined from the preset map corresponding to the self-mobile device, which is at least a preset distance threshold from the region of the second type.

14. The self-mobbling device of claim 9, wherein, Before detecting the current in the track wheels of the self-moving device, the controller controls the self-moving device track stacking detection program to further implement the following steps; The obstacle detection sensor in the self-moving device identifies whether an obstacle exists in the area of ​​the first type. When there are no obstacles, the process of detecting the current in the tracks and wheels of the self-moving device is initiated.

15. A computer-readable storage medium storing a computer program, wherein, When the computer program is executed by the processor, it performs the following steps; When the self-moving device is determined to be located in a first type of area by a level detection sensor in the self-moving device, the current in the track wheels of the self-moving device is detected; When the current is greater than the first preset current for a preset duration, it is determined that the track in the self-moving device is piled up with objects. When the self-moving device is determined to be in a second type of area by the horizontal detection sensor in the self-moving device, it is controlled to move to a first type of area. Then, the current in the track wheels of the self-moving device is detected to determine whether the track of the self-moving device is piled up with objects.

16. The computer-readable storage medium of claim 15, wherein, The step of determining that the self-moving device is located in a first type of area using a horizontal detection sensor in the self-moving device, when the computer program is executed by the processor, implements the following steps: The tilt angle of the self-moving device's body relative to the horizontal plane of the area is determined by a horizontal detection sensor in the self-moving device. When the tilt angle is a preset target tilt angle, the self-moving device is determined to be located in the area of ​​the first type.

17. The computer-readable storage medium of claim 15, wherein, The step of determining that the self-moving device is located in a first type of area using a horizontal detection sensor in the self-moving device, when the computer program is executed by the processor, implements the following steps: The tilt angle of the self-moving device's body relative to the horizontal plane of the area is determined by a horizontal detection sensor in the self-moving device. When the tilt angle is a preset target tilt angle, the self-moving device is determined to be located in the area of ​​the first type.

18. The computer-readable storage medium of claim 15, wherein, The detection of current in the track wheels of the self-moving device, when executed by the processor, involves the following steps: Determine the signal transmitted by the walking motor corresponding to the track of the self-moving device; Determine whether data conversion processing is required based on the signal type of the signal; After determining that data conversion processing is required, the signal data is converted and processed, and the current in the track wheels of the self-moving device is obtained by analyzing the converted signal. After determining that no data conversion processing is required, the current in the track wheels of the self-moving device is obtained by analyzing the signal.

19. The computer-readable storage medium of claim 15, wherein, When the current is greater than the first preset current for a preset duration, it is determined that the track in the self-moving device is piled up with objects. When the computer program is executed by the processor, the following steps are implemented: A changing current is determined on the current change curve based on the value of the current. When the changing current is greater than a first preset current and less than a second preset current, it is determined that the track in the self-moving device is piled up with objects.

20. The computer-readable storage medium of claim 15, wherein, Before controlling the self-moving device to move to the first type of area after determining that the self-moving device is located in the second type of area by the horizontal detection sensor in the self-moving device, the computer program, when executed by the processor, also performs the following steps: Centered on the region of the second type, at least one region of the first type is determined from the preset map corresponding to the self-mobile device, which is at least a preset distance threshold from the region of the second type.

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