Method for path adjustment of mobile robot, mobile robot and storage medium

Abstract

The application discloses a kind of path adjustment method of mobile robot, mobile robot and storage medium, its method includes: based on the acceleration vibration signal of acquisition running process being set on mobile robot based on acceleration sensor;Acceleration vibration signal is preprocessed to generate wavelet packet energy spectrum entropy value;Determine whether the wavelet packet energy spectrum entropy value is greater than preset sample entropy threshold;If it is determined that the wavelet packet energy spectrum entropy value is greater than the preset sample entropy threshold, then based on the current speed of the current position record of the robot;Identify the scene around mobile robot;Based on speed regulation instruction and current speed drive mobile robot in the 3D virtual space generation path adjustment direction;Based on path adjustment direction, carry out mobile operation.The application adjusts the path direction of robot by collecting the acceleration vibration signal on mobile robot, so that it can reduce the hardware damage of mobile robot in the process of moving, reduce the failure rate of mobile robot.

Description

Technical Field

[0001] This invention relates to the field of mobile robot technology, and in particular to a method for adjusting the path of a mobile robot, the mobile robot, and a storage medium. Background Technology

[0002] As mobile robot technology matures, it is increasingly being applied to various industrial production processes and hazardous environments to replace manual labor, thereby reducing operating costs. Current technologies demonstrate high efficiency for tasks with fixed locations or fixed movement trends. However, mobile robots are subject to various road condition interferences during movement, necessitating path adjustments. Road conditions need to be optimized in conjunction with the robot's operating scenario. Existing technologies use energy quotient spectra to collect vibration data in real time. These vibrations can damage the mobile robot's hardware and affect its lifespan. Therefore, combining energy quotient spectra from vibration signals for path adjustment becomes crucial. Summary of the Invention

[0003] The purpose of this invention is to overcome the shortcomings of the prior art. This invention provides a method for adjusting the path of a mobile robot, a mobile robot, and a storage medium. It adjusts the path direction of the robot by collecting acceleration vibration signals on the mobile robot, thereby reducing hardware damage to the mobile robot during movement and reducing the failure rate of the mobile robot.

[0004] To address the aforementioned problems, this invention proposes a method for adjusting the path of a mobile robot, the method comprising:

[0005] Acceleration vibration signals during operation are collected using accelerometers installed on the mobile robot.

[0006] Preprocessing of the acceleration vibration signal generates wavelet packet energy spectrum entropy values;

[0007] Determine whether the wavelet packet energy spectrum entropy value is greater than a preset sample entropy threshold;

[0008] If the wavelet packet energy spectrum entropy value is determined to be greater than the preset sample entropy threshold, the current speed is recorded based on the robot's current position, and a speed adjustment command is generated.

[0009] Identify the scene around the mobile robot, collect the spatial shape of the scene, and present the 3D virtual space of the scene in the virtual brain of the mobile robot.

[0010] Based on the speed adjustment command and the current speed, the mobile robot generates a path adjustment direction in the 3D virtual space;

[0011] Movement operations are performed based on path adjustment direction.

[0012] The acceleration vibration signals collected during operation by the acceleration sensor installed on the mobile robot include:

[0013] Simulated acceleration vibration signals are acquired based on an accelerometer;

[0014] The simulated acceleration vibration signal is filtered to remove high-frequency vibration signals;

[0015] The analog acceleration vibration signal after filtering out high-frequency vibration signals is processed by analog-to-digital conversion to generate a digital acceleration vibration signal.

[0016] The preprocessing of the acceleration vibration signal to generate wavelet packet energy spectrum entropy values ​​includes:

[0017] The acceleration vibration signal is decomposed into wavelet packets using the wavelet packet decomposition principle.

[0018] The wavelet packet coefficients are reconstructed, and the proportion of energy contained in each frequency band component to the total signal energy is calculated.

[0019] The energy distribution of each wavelet packet coefficient of the acceleration vibration signal is obtained by calculating the energy spectral entropy of each frequency band, and the wavelet packet energy spectral entropy is used as a characteristic parameter of the acceleration vibration signal.

[0020] The process of reconstructing the wavelet packet coefficients and determining the proportion of energy contained in each frequency band component to the total signal energy includes:

[0021] Different frequency band components of the signal are obtained by wavelet packet decomposition. Based on the distribution of the frequency bands of the acceleration vibration signal, the characteristic information of each frequency band is obtained. The wavelet packet energy spectrum is used to analyze different acceleration vibration signals.

[0022] After determining whether the wavelet packet energy spectrum entropy value is greater than a preset sample entropy threshold, the process further includes:

[0023] If the wavelet packet energy spectrum entropy value is determined to be no greater than the preset sample entropy threshold, then a movement operation is performed based on the current speed and current path planning.

[0024] The process of identifying the scene surrounding the mobile robot, acquiring the spatial shape of the surrounding scene, and presenting the 3D virtual space of the surrounding scene in the virtual brain of the mobile robot includes:

[0025] Multiple monocular panoramic images of the surrounding scene are captured using a monocular camera on a mobile robot.

[0026] Data processing is performed on each monocular panoramic image, specific boundary line detection is performed on each monocular panoramic image, and the ground region in each monocular panoramic image is segmented based on the detected specific boundary line.

[0027] Based on the 2D feature points contained in the ground region of each monocular panoramic image, obtain the 3D point cloud corresponding to the ground region in the camera coordinate system;

[0028] Based on the coordinate information of each 3D point in the 3D point cloud in the camera coordinate system, calculate the first height information between the monocular camera and the ground area in the camera coordinate system;

[0029] Based on the first height information and the second height information of the monocular camera in world coordinates when capturing each monocular panoramic image, the scale information of each monocular panoramic image is determined.

[0030] A 3D virtual space is presented by fusing multiple monocular panoramic images to depict the surrounding scene.

[0031] The path adjustment direction generated by the mobile robot in the 3D virtual space based on the speed adjustment command and the current speed includes:

[0032] The current position of the mobile robot in the 3D virtual space is obtained, and an avoidance route for the mobile robot is formulated based on the current position. The adjustment path of the robot is determined during the movement of the avoidance route.

[0033] The actual driving range of the mobile robot is determined based on the adjusted path and driving route, and its moving speed is adjusted according to its orientation and ground environment.

[0034] Accordingly, the present invention also provides a mobile robot, wherein the mobile robot is provided with a memory and a processor, the memory is used to store a computer program, and the processor is used to be coupled to the memory to execute the computer program in order to implement the method described above.

[0035] Accordingly, the present invention also provides a computer-readable storage medium, wherein when the computer program is executed by a processor, the processor causes the processor to perform the steps in the above-described method.

[0036] The method, mobile robot, and storage medium involved in this invention adjust the robot's path direction by collecting acceleration vibration signals from the mobile robot, thereby reducing hardware damage and failure rate during movement. The method combines wavelet packet decomposition and energy spectral entropy to extract feature information from the acceleration vibration signals at the robot's location. This feature extraction allows for location-based path changes. By integrating with 3D virtual space, adaptive path planning can be quickly performed to adjust the path during mobile operations, reducing interference and damage from uneven surfaces and ultimately extending the robot's hardware lifespan. Attached Figure Description

[0037] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0038] Figure 1 This is a schematic diagram of the mobile robot structure in an embodiment of the present invention;

[0039] Figure 2 This is a flowchart of a method for adjusting the path of a mobile robot according to an embodiment of the present invention;

[0040] Figure 3 This is a flowchart of a method for identifying the scene around a mobile robot according to an embodiment of the present invention. Detailed Implementation

[0041] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0042] Figure 1 A schematic diagram of the structure of a mobile robot according to an embodiment of the present invention is shown. The mobile robot includes:

[0043] The data acquisition module is used to collect acceleration vibration signals during operation based on the acceleration sensors installed on the mobile robot;

[0044] The preprocessing module is used to preprocess the acceleration vibration signal to generate wavelet packet energy spectrum entropy values;

[0045] The judgment and processing module is used to determine whether the wavelet packet energy spectrum entropy value is greater than a preset sample entropy threshold.

[0046] The adjustment processing module is used to record the current speed based on the robot's current position and generate a speed adjustment command when it is determined that the wavelet packet energy spectrum entropy value is greater than the preset sample entropy threshold.

[0047] The scene recognition module is used to identify the scene around the mobile robot, collect the spatial shape of the surrounding scene, and present the 3D virtual space of the surrounding scene in the virtual brain of the mobile robot.

[0048] The path adjustment module is used to drive the mobile robot to generate a path adjustment direction in the 3D virtual space based on the speed adjustment command and the current speed.

[0049] The job processing module is used to perform moving jobs based on path adjustment direction.

[0050] This mobile robot adjusts its path direction by collecting acceleration vibration signals, reducing hardware damage during movement and lowering the failure rate. The method combines wavelet packet decomposition and energy spectral entropy to extract characteristic information from the robot's acceleration vibration signals. This feature extraction allows for location-based path changes. By integrating with 3D virtual space, adaptive path planning can be quickly performed to adjust the path during mobile operations, reducing interference and damage from uneven surfaces and ultimately extending the robot's hardware lifespan.

[0051] Specifically, Figure 2 The flowchart of a method for adjusting the path of a mobile robot according to an embodiment of the present invention is shown, which specifically includes:

[0052] S201. Acceleration vibration signals during operation are collected based on the acceleration sensor installed on the mobile robot;

[0053] Specifically, the mobile robot here is equipped with an accelerometer. This accelerometer can collect acceleration vibration signals at its location during the robot's movement, thereby enabling the final path adjustment process to be completed based on these acceleration vibration signals.

[0054] The acquisition of acceleration vibration signals during operation based on the acceleration sensor installed on the mobile robot includes: acquiring simulated acceleration vibration signals based on the acceleration sensor; filtering the simulated acceleration vibration signals to remove high-frequency vibration signals; and performing analog-to-digital conversion on the simulated acceleration vibration signals with the high-frequency vibration signals removed to generate digital acceleration vibration signals.

[0055] In this embodiment of the invention, a MEMS accelerometer can be selected to collect signals. The MEMS accelerometer has the advantages of small size, low price, strong output signal, and simple subsequent circuitry.

[0056] In this embodiment of the invention, an anti-aliasing filter circuit can be used for filtering, which can effectively filter out high-frequency vibration signals in the simulated acceleration vibration signal.

[0057] In this embodiment of the invention, the data is converted into digital quantities using an analog-to-digital converter (ADC). The sampling frequency of the ADC is set to above 5kHz. The sampled data is then output to the corresponding processor via a serial port according to a predefined format to extract the acceleration vibration signal.

[0058] S202. Preprocess the acceleration vibration signal to generate wavelet packet energy spectrum entropy value;

[0059] The preprocessing of the acceleration vibration signal to generate wavelet packet energy spectrum entropy values ​​includes: decomposing the acceleration vibration signal into wavelet packets using the wavelet packet decomposition principle; reconstructing the wavelet packet coefficients and calculating the proportion of energy contained in each frequency band component to the total signal energy; obtaining the energy distribution of each wavelet packet coefficient of the acceleration vibration signal by calculating the energy spectrum entropy of each frequency band, and using the wavelet packet energy spectrum entropy as a characteristic parameter of the acceleration vibration signal.

[0060] The reconstruction of wavelet packet coefficients and the determination of the proportion of energy contained in each frequency band component to the total signal energy include: obtaining different frequency band components of the signal through wavelet packet decomposition, obtaining the characteristic information of each frequency band based on the distribution of the acceleration vibration signal frequency bands, and analyzing the acceleration vibration signal using the wavelet packet energy spectrum.

[0061] It should be noted that wavelet packet decomposition of acceleration vibration signals is commonly used in the identification and judgment of fault vibrations under mechanical principles. The collected acceleration vibration signal forms a random variable with several probability distribution values. Each random variable has an overall feature entropy value. The larger the probability distribution value of the random variable, the larger its corresponding overall feature entropy value; the smaller the probability distribution value of the random variable, the smaller its corresponding overall feature entropy value.

[0062] For a random time series under random variables, there is a relationship between the energy of each frequency band under the random time series, and the energy spectral entropy under the random time series can reflect the distribution of energy of the time series signal in the frequency domain.

[0063] Wavelet packet decomposition can decompose the decomposition space into the sum of different sub-decomposition spaces according to different scales. If a higher resolution is required, each sub-decomposition space can be further decomposed, which unifies the multi-resolution subspace and each sub-decomposition space through the new space.

[0064] Here, wavelet packet decomposition is used to obtain different frequency band components of the signal. Based on the distribution of the acceleration vibration signal's frequency bands, the characteristic information of each frequency band is obtained. The wavelet packet energy spectrum is then used to analyze different acceleration vibration signals. Wavelet packet transform has good processing capabilities for non-stationary signals, and its application to the analysis of acceleration vibration signals yields good results. Wavelet packet decomposition can obtain different frequency band components of the signal, and the information distribution of these components differs. Based on the distribution of the acceleration vibration signal, the characteristic information of each frequency band can be obtained.

[0065] The energy of each frequency band component of the wavelet packet of an acceleration vibration signal can be calculated using Passerwale's theorem. The wavelet packet coefficients are used to analyze the energy of different frequency bands of the acceleration vibration signal. The energy corresponding to the wavelet packet coefficients is different for different acceleration vibration signals. Here, the wavelet packet energy spectrum can be used to analyze different acceleration vibration signals.

[0066] Energy spectral entropy is a quantitative description of the complexity of the energy distribution of an accelerated vibration signal in the frequency domain. It reflects the amount of information across the entire frequency range of the accelerated vibration signal, characterizing the information entropy at all frequencies without considering the detailed components of the spectrum. Here, wavelet packet transform is used to process the accelerated vibration signal. It has a wideband response for non-stationary signals, high frequency resolution at low frequencies, and high time resolution at high frequencies, making it suitable for analyzing non-stationary signals.

[0067] S203. Determine whether the wavelet packet energy spectrum entropy value is greater than the preset sample entropy threshold. If it is greater than the preset sample entropy threshold, proceed to S204; otherwise, proceed to S208.

[0068] The preset sample entropy threshold represents the degree of damage to the mobile robot caused by the energy spectrum. Exceeding the preset sample entropy value indicates that there is significant damage to the operation of the mobile robot, and changes need to be made to the operation process of the mobile robot. The preset sample entropy threshold can be set according to the application environment.

[0069] S204. If the wavelet packet energy spectrum entropy value is determined to be greater than the preset sample entropy threshold, the current speed is recorded based on the robot's current position, and a speed adjustment command is generated.

[0070] S205. Identify the scene around the mobile robot, collect the spatial shape of the scene, and present the 3D virtual space of the scene in the virtual brain of the mobile robot.

[0071] Here, the surrounding scene of the mobile robot is identified and its spatial shape is collected. The 3D virtual space of the surrounding scene is presented in the virtual brain of the mobile robot, which can be achieved by a monocular camera. This can determine the scale information of the monocular panoramic image, improve the effect of use in practical applications, reduce hardware investment, and save hardware costs.

[0072] Specifically, Figure 3 A flowchart of a method for identifying the scene surrounding a mobile robot according to an embodiment of the present invention is shown, which specifically includes:

[0073] S301. Multiple monocular panoramic images of the surrounding scene are captured using a monocular camera on a mobile robot.

[0074] S302. Perform data processing on each monocular panoramic image, detect specific boundary lines on each monocular panoramic image, and segment the ground region in each monocular panoramic image based on the detected specific boundary lines.

[0075] S303. Based on the 2D feature points contained in the ground region of each monocular panoramic image, obtain the 3D point cloud corresponding to the ground region in the camera coordinate system.

[0076] In the specific implementation process, feature extraction is performed on the monocular panoramic image to obtain the 2D feature points contained in the monocular panoramic image; from the 2D feature points contained in the monocular panoramic image, 2D feature points in the ground area are obtained; based on the depth change information between the monocular panoramic image captured by the monocular camera and the previous monocular panoramic image, the 2D feature points in the ground area are spatially mapped to obtain the 3D point cloud corresponding to the ground area in the camera coordinate system.

[0077] S304. Based on the coordinate information of each 3D point in the 3D point cloud in the camera coordinate system, calculate the first height information between the monocular camera and the ground area in the camera coordinate system.

[0078] In the specific implementation process, the mean value of the height information of each 3D point in the 3D point cloud in the camera coordinate system is calculated as the Gaussian filter mean value. Based on the Gaussian filter mean value, the height information of each 3D point in the camera coordinate system is subjected to Gaussian filtering to obtain multiple target 3D points. According to the height information of the multiple target 3D points in the camera coordinate system, the first height information between the monocular camera and the ground area in the camera coordinate system is calculated.

[0079] S305. Based on the first height information and the second height information of the monocular camera in world coordinates when capturing each monocular panoramic image, determine the scale information of each monocular panoramic image.

[0080] S306. A 3D virtual space that presents the surrounding scene by fusing data from multiple monocular panoramic images.

[0081] Here, the relative positional relationship of the monocular camera when capturing the two adjacent monocular panoramic images is calculated; based on the relative positional relationship, the scale information of multiple monocular panoramic images, and the specific boundary lines contained in the multiple monocular panoramic images, a 3D virtual space of the surrounding scene is generated.

[0082] In the specific implementation process, a first monocular panoramic image is obtained from the monocular panoramic images that have not yet been generated. The scale information of the first monocular panoramic image is used as the first scale information, and the current corresponding scale information is used as the second scale information. The image adjacent to the first monocular panoramic image in the monocular panoramic images that have participated in the generation operation is called the second monocular panoramic image. Using the first scale information and the second scale information respectively, combined with the specific boundary lines contained in the first monocular panoramic image and the second monocular panoramic image, and the relative positional relationship of the monocular camera when capturing the first monocular panoramic image and the second monocular panoramic image, the first 3D virtual space and the second 3D virtual space corresponding to the first scale information and the second scale information are obtained respectively. According to the quality parameters of the first 3D virtual space and the second 3D virtual space, the 3D virtual space with better quality is selected as the new current 3D virtual space, and the operation of obtaining the first monocular panoramic image from the monocular panoramic images that have not yet participated in the generation operation continues until all monocular panoramic images participate in the 3D virtual space generation operation, thus obtaining the 3D virtual space of the surrounding scene.

[0083] S206. Based on the speed adjustment command and the current speed, drive the mobile robot to generate a path adjustment direction in the 3D virtual space;

[0084] The method of driving the mobile robot to generate path adjustment direction in the 3D virtual space based on speed adjustment commands and current speed includes: obtaining the current position point of the mobile robot in the 3D virtual space, formulating an avoidance route for the mobile robot based on the current position point, and determining the adjustment path of the robot during the travel of the avoidance route; determining the actual travel range of the mobile robot based on the adjustment path and travel route, and adjusting its own movement speed according to its own orientation and ground environment.

[0085] S207. Moving operations based on path adjustment direction;

[0086] S208. If it is determined that the wavelet packet energy spectrum entropy value is not greater than the preset sample entropy threshold, then a movement operation is performed based on the current speed and the current path planning.

[0087] Since each acceleration vibration signal has a different energy spectrum, it needs to be analyzed and compared with the corresponding energy spectrum to obtain the path adjustment for each energy spectrum. If the energy spectrum does not harm the operation of the mobile robot, the operation can be carried out with the current speed and the current path planning. If the energy spectrum harms the operation of the mobile robot, the path adjustment direction needs to be generated to adjust the mobile robot's operation.

[0088] The method in this embodiment of the invention adjusts the path direction of a mobile robot by collecting acceleration vibration signals, thereby reducing hardware damage and failure rate during movement. The method combines wavelet packet decomposition and energy spectral entropy to extract feature information from the acceleration vibration signals at the robot's location. This feature extraction allows for location-based path changes. By integrating with 3D virtual space, adaptive path planning can be quickly performed to adjust the path during mobile operations, reducing interference and damage from uneven surfaces and ultimately extending the robot's hardware lifespan.

[0089] This invention also provides a mobile robot, which includes a memory and a processor. The memory stores a computer program, and the processor is coupled to the memory to execute the computer program to implement the methods described above.

[0090] This invention also provides a computer-readable storage medium, wherein when the computer program is executed by a processor, the processor causes the processor to perform the steps in the above-described method.

[0091] The embodiments of the present invention have been described in detail above. Specific examples have been used to illustrate the principles and implementation methods of the present invention. The description of the above embodiments is only for the purpose of helping to understand the method and core ideas of the present invention. At the same time, for those skilled in the art, there will be changes in the specific implementation methods and application scope based on the ideas of the present invention. Therefore, the content of this specification should not be construed as a limitation of the present invention.

Claims

1. A method for adjusting the path of a mobile robot, characterized in that, The method includes: Acceleration vibration signals are collected by the accelerometer installed on the mobile robot during operation. The collected acceleration vibration signals form a random variable, which has several probability distribution values. Each random variable has an overall characteristic entropy value. Preprocessing of the acceleration vibration signal generates wavelet packet energy spectrum entropy values; Determine whether the wavelet packet energy spectrum entropy value is greater than a preset sample entropy threshold; If the wavelet packet energy spectrum entropy value is determined to be greater than the preset sample entropy threshold, the current speed is recorded based on the robot's current position, and a speed adjustment command is generated. Identify the scene around the mobile robot, collect the spatial shape of the scene, and present the 3D virtual space of the scene in the virtual brain of the mobile robot. Based on the speed adjustment command and the current speed, the mobile robot generates a path adjustment direction in the 3D virtual space; Movement operations are performed based on path adjustment direction; The preprocessing of the acceleration vibration signal to generate wavelet packet energy spectrum entropy values ​​includes: The acceleration vibration signal is decomposed into wavelet packets using the wavelet packet decomposition principle. The wavelet packet coefficients are reconstructed, and the proportion of energy contained in each frequency band component to the total signal energy is calculated. The energy distribution of each wavelet packet coefficient of the acceleration vibration signal is obtained by calculating the energy spectrum entropy of each frequency band, and the wavelet packet energy spectrum entropy is used as a characteristic parameter of the acceleration vibration signal. The process of reconstructing the wavelet packet coefficients and determining the proportion of energy contained in each frequency band component to the total signal energy includes: Different frequency band components of the signal are obtained by wavelet packet decomposition. Based on the distribution of the frequency bands of the acceleration vibration signal, the characteristic information of each frequency band is obtained. The wavelet packet energy spectrum is used to analyze different acceleration vibration signals.

2. The method for adjusting the path of a mobile robot as described in claim 1, characterized in that, The acceleration vibration signals collected during operation by the acceleration sensor installed on the mobile robot include: Simulated acceleration vibration signals are acquired based on an accelerometer; The simulated acceleration vibration signal is filtered to remove high-frequency vibration signals; The analog acceleration vibration signal after filtering out high-frequency vibration signals is processed by analog-to-digital conversion to generate a digital acceleration vibration signal.

3. The method for adjusting the path of a mobile robot as described in claim 1, characterized in that, After determining whether the wavelet packet energy spectrum entropy value is greater than a preset sample entropy threshold, the process further includes: If the wavelet packet energy spectrum entropy value is determined to be no greater than the preset sample entropy threshold, then a movement operation is performed based on the current speed and current path planning.

4. The method for adjusting the path of a mobile robot as described in claim 3, characterized in that, The process of identifying the scene surrounding the mobile robot, acquiring the spatial shape of the surrounding scene, and presenting the 3D virtual space of the surrounding scene in the virtual brain of the mobile robot includes: Multiple monocular panoramic images of the surrounding scene are captured using a monocular camera on a mobile robot. Data processing is performed on each monocular panoramic image, specific boundary line detection is performed on each monocular panoramic image, and the ground region in each monocular panoramic image is segmented based on the detected specific boundary line. Based on the 2D feature points contained in the ground region of each monocular panoramic image, obtain the 3D point cloud corresponding to the ground region in the camera coordinate system; Based on the coordinate information of each 3D point in the 3D point cloud in the camera coordinate system, calculate the first height information between the monocular camera and the ground area in the camera coordinate system; Based on the first height information and the second height information of the monocular camera in world coordinates when capturing each monocular panoramic image, the scale information of each monocular panoramic image is determined. A 3D virtual space is presented by fusing multiple monocular panoramic images to depict the surrounding scene.

5. The method for adjusting the path of a mobile robot as described in claim 1, characterized in that, The path adjustment direction generated by the mobile robot in the 3D virtual space based on the speed adjustment command and the current speed includes: The current position of the mobile robot in the 3D virtual space is obtained, and an avoidance route for the mobile robot is formulated based on the current position. The adjustment path of the robot is determined during the movement of the avoidance route. The actual driving range of the mobile robot is determined based on the adjusted path and driving route, and its moving speed is adjusted according to its orientation and ground environment.

6. A mobile robot, characterized in that, The mobile robot is provided with a memory and a processor. The memory is used to store computer programs, and the processor is used to couple with the memory to execute the computer programs in order to implement the method according to any one of claims 1 to 5.

7. A computer-readable storage medium, characterized in that, When the computer program is executed by the processor, it causes the processor to perform the steps of the method according to any one of claims 1-5.

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