TWI715353B - Robot balance determination device and robot balance determination method - Google Patents

Abstract

A robot balance determination device includes a photographing device and a processor. The processor is coupled to the photographing device. The processor is configured to: receive a set of images from the photographing device; obtain the coordinates of each initial image; arrange and stitch a plurality of the initial images according to the coordinates to generate an image model; set a balance threshold of the image model; receive a determination image from the photographing device instantly; compare the determination image with the image model to obtain a difference value; determine whether the difference value exceeds the balance threshold to determine the balance state of the robot. The invention also provides a robot balance determination method.

Description

Robot balance determination device and robot balance determination method

The invention relates to the field of robots, in particular to a robot balance determination device and a robot balance determination method.

During the movement of the robot, the center of gravity of the robot will change due to various actions, which will easily cause the robot to enter an unbalanced state. If it cannot be adjusted in time, it will easily cause the robot to fall and cause damage to the robot.

In view of this, the present invention provides a robot balance determination device and a robot balance determination method to solve the above-mentioned problems.

The first aspect of the application provides a robot balance determination device, including a photographing device; a processor, coupled to the photographing device, and configured to: receive an image set from the photographing device, the image set including the robot holding Multiple initial images taken by the photographing device during balance; acquiring the coordinates of each initial image; arranging and stitching multiple initial images according to the coordinates to generate an image model; setting the image The balance threshold of the image model; instantaneously receive the judgment image from the photographing device; compare the judgment image with the image model to obtain a difference value; determine whether the difference value exceeds the balance threshold, to Determine the balance state of the robot.

Further, the processor is further configured to: if the robot maintains a balance, adjust the image model according to the judgment image.

Further, wherein the difference value is: the difference between the coordinates of the judgment image and the coordinates of the same image area in the image model, or the difference between the coordinates of the judgment image and the image model The degree of difference between images in the same coordinate area.

Further, the processor is further configured to: determine the judgment coordinates according to the model characteristics of the image model; the photographing device is further configured to: obtain the judgment image according to the judgment coordinates.

Further, the robot balance determination device further includes a first sensing unit and a second sensing unit, the first sensor is used for sensing the speed and displacement of the robot to form first sensing information, and the second sensor is used for sensing The azimuth angle of the robot to obtain second sensing information, wherein the processor is further configured to: obtain the first sensing information and the second sensing information; according to the first sensing information and the second sensing information Forming status information; adjusting the reconstruction period of the image model according to the status information.

A second aspect of the present invention provides a robot balance determination method, including: acquiring an image set, the image set including a plurality of initial images acquired when the robot is in balance; acquiring the coordinates of each of the initial images; Arranging the coordinates and splicing a plurality of the initial images to generate an image model; setting the balance threshold of the image model; obtaining the judgment image immediately; comparing the judgment image with the image model to Get the difference value; It is determined whether the difference value exceeds the balance threshold to determine the balance state of the robot.

Further, the method further includes the step of: if the robot maintains a balance, adjusting the image model according to the judgment image.

Further, wherein the difference value is: the difference between the coordinates of the judgment image and the coordinates of the same image area in the image model, or the difference between the coordinates of the judgment image and the image model The degree of difference between images in the same coordinate area.

Further, “receiving the judgment image from the photographing device immediately” specifically includes the steps of: determining the judgment coordinates according to the model characteristics of the image model; and obtaining the judgment image according to the judgment coordinates.

Further, the method further includes the step of acquiring first sensing information and second sensing information, wherein the first sensing information includes speed and displacement information of the robot, and the second sensing information includes the orientation of the robot Angle information; forming state information based on the first sensing information and the second sensing information; adjusting the reconstruction period of the image model based on the state information.

The present invention establishes an image model when the robot maintains balance, sets the balance threshold of the image model, and instantly compares the judgment image and the image model to obtain the difference value, and judges the balance state of the robot according to the difference value and the balance threshold. In order to control the robot to adjust the state in time.

100: Robot balance determination device

10: Camera equipment

20: processor

30: memory

40: The first induction unit

50: second sensing unit

60: The third induction unit

200: Robot balance determination system

201: receiving module

202: Judgment Module

203: Control Module

204: Get Module

205: Model Creation Module

206: Setting Module

207: Comparison module

208: Update module

FIG. 1 is a schematic diagram of the hardware architecture of a robot balance determination device in an embodiment of the present invention.

2 is a schematic diagram of functional modules of the robot balance determination system in an embodiment of the present invention Figure.

Fig. 3 is a method flowchart of a robot balance determination method in an embodiment of the present invention.

Fig. 4 is a schematic diagram of an image model in an embodiment of the present invention.

In order to be able to understand the above-mentioned objectives, features and advantages of the present invention more clearly, the present invention will be described in detail below in conjunction with the accompanying drawings and specific embodiments. It should be noted that the embodiments of the application and the features in the embodiments can be combined with each other if there is no conflict.

In the following description, many specific details are explained in order to fully understand the present invention. The described embodiments are only a part of the embodiments of the present invention, rather than all of them. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative work shall fall within the protection scope of the present invention.

Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those skilled in the technical field of the present invention. The terminology used in the specification of the present invention herein is only for the purpose of describing specific embodiments, and is not intended to limit the present invention.

The term "and/or" as used herein includes any and all combinations of one or plural related listed items.

Please refer to FIG. 1, which is a schematic diagram of a robot balance determination device provided in an implementation of the present invention.

In this embodiment, the robot balance determination device 100 includes a photographing device 10, a processor 20, a memory 30, a first sensing unit 40, a second sensing unit 50, and a third sensing unit 60.

The photographing device 10 is used to photograph images around the robot.

In this embodiment, when the robot is in balance, the multiple images around the robot taken by the photographing device 10 are the initial images, and an image set is formed based on the multiple initial images.

In one embodiment, one or more photographing devices 10 are used to sequentially photograph multiple initial images according to the axis of the robot and according to different shooting angles. The multiple initial images can be used to obtain the surroundings of the robot while maintaining balance. Environmental conditions, such as whether it contains a landmark object, the relative position of the landmark object and the robot. It is understandable that the number of pictures taken can be selected according to environmental conditions.

Further, the initial images can be partially overlapped, so as to ensure the image continuity of the image model obtained from the multiple initial images.

Further, according to the photographing device 10, only a plurality of initial images directly in front of the robot can be captured to obtain the environmental conditions in front of the robot.

It can be understood that when the robot is in balance, the robot can be stationary or in motion.

In an embodiment, the photographing device 10 is also used to shoot an image corresponding to the coordinate area according to the judgment coordinates to obtain the judgment image.

In an embodiment, the photographing device 10 may be a CCD camera, a binocular camera, or the like.

The processor 20 may be a central processing unit (CPU, Central Processing Unit), and may also include other general-purpose processors, digital signal processors (Digital Signal Processors, DSPs), and dedicated integrated circuits (Application Specific Integrated Circuits, ASICs). , Ready-made programmable gate array (Field-Programmable Gate Array, FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor can be a microprocessor or the processor can also be any conventional processor. The processor 20 is the control center of the robot balance determination device 100, which uses various interfaces and lines to connect the entire robot balance determination device 100. Various parts.

The memory 30 is used to store various data in the robot balance determination device 100, such as image collections, image models, and so on. In this embodiment, the memory 30 may include, but is not limited to, read-only memory (Read-Only Memory, ROM), random access memory (Random Access Memory, RAM), and programmable read-only memory (Programmable Read-Only Memory, RAM). -Only Memory, PROM), Erasable Programmable Read-Only Memory (EPROM), One-time Programmable Read-Only Memory (OTPROM), Electronic Erasable Programmable Read-Only Memory (OTPROM) Memory (Electrically-Erasable Programmable Read-Only Memory, EEPROM), CD-ROM (Compact Disc Read-Only Memory, CD-ROM) or other optical disk memory, magnetic disk memory, tape memory, or can be used to carry Or any other computer-readable medium for storing data.

The first sensing unit 40 is used for sensing the speed and displacement of the robot to obtain first sensing information.

In this embodiment, the first sensing unit 40 includes a gravity sensor, and the first sensing information is information on the speed and displacement of the robot. It can be understood that the first sensing unit 40 may also include an acceleration sensor and the like, but is not limited thereto.

The second sensing unit 50 is used for sensing the azimuth angle of the robot to obtain second sensing information.

In this embodiment, the second sensing unit 50 includes a gyroscope, and the second sensing information is information about the azimuth angle of the robot. It can be understood that the second sensing unit 50 may also include a magnetometer, etc., but is not limited thereto.

In another embodiment, the first sensing unit 40 obtains the first sensing information when the robot is in balance, and forms a first information set based on a plurality of first sensing information; the second sensing unit 50 obtains the second information when the robot is in balance Sensing information, and forming a second information set based on a plurality of second sensing information.

The third sensing unit 60 is used for sensing the distance between the robot and surrounding objects to obtain third sensing information.

In this embodiment, the third sensing unit 60 includes an ultrasonic sensor, and the third sensing information is distance information between the robot and surrounding objects. It can be understood that the third sensing unit 60 may also include an infrared sensor and the like, but is not limited thereto.

Please refer to FIG. 2, which is a schematic diagram of functional modules of the robot balance determination system 200 in an embodiment of the present invention.

In this embodiment, the robot balance determination system 200 includes one or more computer instructions in the form of a program, and the one or more computer instructions in the form of a program are stored in the memory 30 and executed by the processor 20. Execute to realize the functions provided by the present invention.

In this embodiment, the robot balance determination system 200 can be divided into a receiving module 201, a determination module 202, a control module 203, an acquisition module 204, a model creation module 205, and a setting module 206. Group 207 and update module 208. The functions of each functional module will be described in detail in the following embodiments.

The receiving module 201 is configured to receive an image set sent by the photographing device 10, where the image set includes a plurality of initial images obtained by the photographing device 10 while photographing the periphery of the robot while maintaining balance.

In this embodiment, the receiving module 201 is also used to receive the judgment image sent by the photographing device 10.

Furthermore, the receiving module 201 is also used for receiving the first sensing information sent by the first sensing unit 40 and the second sensing information sent by the second sensing unit 50.

In another embodiment, the receiving module 201 is also used to receive a first information set and a second information set, wherein the first information set is a plurality of first sensors acquired by the first sensor unit 40 when the robot is in balance. A collection of information, the second information set is a collection of multiple second sensing information acquired by the second sensing unit 50 when the robot is in balance.

Furthermore, the receiving module 201 is also used for receiving the third sensing information sent by the third sensing unit 60.

The judging module 202 is used to judge the balance state of the robot.

In one embodiment, the receiving module 201 receives the first sensing information sent by the first sensing unit 40 and the second sensing information sent by the second sensing unit 50, and the determining module 202 sets the determination threshold value according to According to the first sensing information, the second sensing information, and the balance threshold, the robot's balance state is determined. The balance state includes maintaining balance and losing balance.

The determination module 202 is also used to determine the determination area according to the model characteristics of the image model, and then determine the determination coordinates of the determination area.

Among them, the characteristics of the model include the similarity, coherence, and whether it contains obvious features in each area of the image model. For example, the image similarity of multiple regions in the image model is relatively high. If the region is used as the judgment region, it is easy to cause judgment errors; if the adjacent region images in the image model are continuous and repetitive, it is difficult to find the similarity. The distinguishing point of the neighboring area is not suitable for the judgment area; if the image model has prominent features, for example, an area contains animal patterns that are clearly different from the surrounding environment, the area can be used as the judgment area.

The determination module 202 is also used to determine whether the difference value exceeds the balance threshold, so as to determine the balance state of the robot.

In another embodiment, the determination module 202 is further configured to compare the first sensing information, the second sensing information, and the auxiliary balance threshold respectively to determine the balance state of the robot.

The control module 203 is configured to send a photographing instruction to enable the photographing device 10 to photograph an image.

Further, the photographing instruction includes a first photographing instruction and a second photographing instruction. The control module 203 sends the first photographing instruction to enable the photographing device 10 to photograph multiple initial images forming the image set; the control module 203 sends the second photographing instruction. The photographing instruction is used to make the photographing device 10 photograph the judgment image.

The control module 203 is also used to send an adjustment instruction to the robot to make the robot self-adjust and balance.

The acquiring module 204 is used to acquire the coordinates of each initial image in the image set.

In one embodiment, the coordinate system established by the module 204 is acquired, and the corresponding coordinates are set according to the relative position of each initial image and the robot. The coordinate system may be a rectangular coordinate system or a three-dimensional coordinate system.

The model building module 205 is used for arranging and stitching a plurality of initial images in the image set according to coordinates to generate an image model.

In an embodiment, the image model is a panoramic image that is arranged and stitched according to coordinates.

In another embodiment, the image model is shown in Figure 4. The image model is composed of 25 initial images arranged in a 5*5 matrix, and each initial image is provided with corresponding coordinates, which are 1 ~25. It can be understood that the coordinates and arrangement of each initial image can be adjusted according to actual application scenarios.

In another embodiment, the model building module 205 is further used to update the three-dimensional coordinates of each image area in the image model according to the third information.

The setting module 206 is used to set the balance threshold of the image model.

In an embodiment, the balance threshold is the degree of difference in a specific image region of the image model. For example, the degree of difference between the image acquired according to the specified coordinates and the image of the same coordinate region in the image model.

In another embodiment, the balance threshold is the coordinate offset, for example, the coordinate difference between the image acquired according to the specified coordinates and the coordinates of the same image area in the image model is the coordinate offset.

In another embodiment, the setting module 206 is further configured to set the auxiliary balance threshold according to the first information set and the second information set. The auxiliary balance threshold can be an angle or azimuth range.

The comparison module 207 is used to compare the judgment image with the image model to obtain the difference value.

In one embodiment, the comparison module 207 compares and determines the degree of difference between the image and the image area of the same coordinate in the image model, and the degree of difference is the difference value.

In another embodiment, the comparison module 207 compares the coordinates of the judged image with the coordinates of the same image area in the image model to obtain the coordinate difference, which is the difference value.

The update module 208 is used for forming state information according to the first sensing information and the second sensing information, and adjusting the reconstruction period of the image model according to the state information. State information includes movement speed, acceleration, direction change, angle change, etc. Among them, the movement speed and acceleration are the speed of the robot movement Changes, direction changes and angle changes are the frequency of turning and changing the direction of movement of the robot during movement. For example, if the surrounding environment of the robot changes more or the robot moves faster, the reconstruction period of the image model needs to be shortened to ensure the accuracy of the image model. If the robot speed is slow and the environment changes less, the reconstruction period of the image model needs to be increased.

The model building module 205 is also used to rebuild a new image model according to the reconstruction period to replace the old image model.

The reconstruction period is the length of time the image model is rebuilt to ensure that the image model is consistent with the environment around the robot.

Please refer to FIG. 3, which is a flowchart of robot balance determination provided by an embodiment of the present invention. According to different needs, the order of the steps in the flowchart can be changed, and some steps can be omitted. For ease of description, only parts related to the embodiment of the present invention are shown.

As shown in Figure 3, the robot balance determination method includes the following steps.

Step S1: Obtain an image set.

Specifically, the receiving module 201 receives an image set sent by the photographing device 10, where the image set includes a plurality of initial images obtained by the photographing device 10 while photographing the periphery of the robot while maintaining balance.

Step S1 specifically includes the steps of: determining the balance state of the robot; if the balance is maintained, acquiring multiple initial images; forming an image set based on the multiple initial images.

If you lose balance, send an adjustment command to make the robot self-adjust.

Specifically, the judging module 202 judges the balance state of the robot; if the balance is maintained, the control module 203 sends a photographing instruction to the photographing device 10 so that the photographing device 10 takes multiple initial images, and forms the image according to the multiple initial images. Like set. If the balance is lost, the control module 203 sends an adjustment instruction to the robot so that the robot can adjust its balance.

Step S2: Obtain the coordinates of each initial image in the image set.

Specifically, the acquisition module 204 acquires the coordinates of each initial image in the image set.

In one embodiment, the coordinate system established by the module 204 is acquired, and the corresponding coordinates are set according to the relative position of each initial image and the robot. The coordinate system may be a rectangular coordinate system or a three-dimensional coordinate system.

Step S3: Arranging and splicing a plurality of the initial images according to the coordinates to generate an image model.

Specifically, the model building module 205 arranges and stitches a plurality of initial images in the image set according to coordinates to generate an image model.

In an embodiment, the image model is a panoramic image stitched together according to coordinate arrangement.

In another embodiment, the image model is shown in FIG. 4, which is composed of 25 initial images arranged in a 5*5 matrix, and each initial image is provided with corresponding coordinates, which are 1-25, respectively. It can be understood that the coordinates and arrangement of each initial image can be adjusted according to actual application scenarios.

In another embodiment, further, after step S3, the method further includes the steps of: acquiring third sensing information; and adjusting the image model according to the third sensing information.

Specifically, the receiving module 201 receives the third sensing information sent by the third sensing unit 60, the third sensing information includes the distance of things around the robot displayed in the image model, and the model building module 205 updates the map according to the third sensing information. The three-dimensional coordinates of each image area in the image model.

Step S4: Set the balance threshold of the image model.

Specifically, the setting module 206 sets the balance threshold of the image model.

In an embodiment, the balance threshold is the degree of difference in a specific image region of the image model. For example, the degree of difference between the image acquired according to the specified coordinates and the image of the same coordinate region in the image model.

In another embodiment, the balance threshold is the coordinate offset, for example, the coordinate difference between the image acquired according to the specified coordinates and the coordinates of the same image area in the image model is the coordinate offset.

In one embodiment, the balance threshold is set according to the robot's self-adjustment ability. For example, when the robot moves, the tilt caused by its own shaking can be adjusted according to its own gravity, then the tilt belongs to the normal range and is within the balance threshold range ; The robot tilts more than a certain angle and cannot be adjusted by the robot's own gravity. If the robot does not adjust the state, the robot will be unbalanced or even fall, and the state will exceed the balance threshold range.

Step S5: Obtain the judgment image immediately.

Specifically, the receiving module 201 immediately receives the determined image from the photographing device 10.

In one embodiment, step S5 specifically includes the steps of: determining the judgment coordinates according to the model characteristics of the image model; and obtaining the judgment image according to the judgment coordinates.

Specifically, the determination module 202 determines the determination area according to the model characteristics of the image model, and then determines the determination coordinates, and the photographing device 10 captures the determination image of the determination coordinates according to the determination coordinates.

The characteristics of the model include the similarity, coherence, and whether it contains obvious features in the image model. For example, the similarity of multiple regions in the image model is relatively high. If the region is used as the judgment region, it is easy to cause judgment errors; if the adjacent regions in the image model are continuous and repetitive, it is difficult to find the difference between adjacent regions If the image model has a prominent feature, for example, an area contains animal patterns that are clearly different from the surrounding environment, then this area can be used as a judgment area.

Step S6: Compare the judgment image with the image model to obtain a difference value.

Specifically, the comparison module 207 compares the determined image with the image model to obtain the difference value.

In one embodiment, the comparison module 207 compares and determines the degree of difference between the image and the image area of the same coordinate in the image model, and the degree of difference is the difference value.

In another embodiment, the comparison module 207 compares the coordinates of the judged image with the coordinates of the same image area in the image model to obtain the coordinate difference, which is the difference value.

Step S7: Determine whether the difference value exceeds the balance threshold to determine the balance state of the robot.

If yes, perform step S8: determine that the robot is out of balance and control the robot to adjust; if not, perform step S9: determine that the robot is in balance, and adjust the image model according to the determined image.

For example, as shown in Figure 4, if the coordinate of the judged image is 8, but the judged image with the coordinate of 8 is located in the image area with the coordinate of 24 in the image model, it exceeds the balance threshold range 3, 7, 8, 9 And 13, it is determined that the robot is out of balance.

Specifically, the determination module 202 determines whether the difference value exceeds the balance threshold value to determine the balance state of the robot. If the robot loses balance, the control module 203 sends an adjustment instruction to the robot to adjust the balance of the robot. If the robot maintains balance, the model building module 205 replaces the pattern of the corresponding area in the image model according to the determined image.

Further, the method further includes the steps of: acquiring first sensing information and second sensing information in real time; forming state information based on the first sensing information and first sensing information; adjusting the image model based on the state information Rebuild cycle.

The status information includes movement speed, acceleration, direction change, angle change, etc. The movement speed and acceleration are the speed change of the robot movement, and the direction change and angle change are the frequency of turning and changing the moving direction during the movement of the robot.

Specifically, the receiving module 201 receives the first sensing information and the second sensing information; the update module 208 forms state information according to the first sensing information and the second sensing information, and adjusts the reconstruction of the image model according to the state information cycle. For example, if the environment around the robot changes more, or the robot If the moving speed is faster, the reconstruction period of the image model needs to be shortened to ensure the accuracy of the image model. If the robot speed is slow and the environment changes less, the reconstruction period of the image model needs to be increased.

In one embodiment, according to the reconstruction period, step S1 to step S3 are periodically executed to rebuild the image model to replace the old image model.

In another embodiment, the method further includes the step of: obtaining a first information set and a second information set, wherein the first information set is a plurality of first sensors acquired by the first sensor unit 40 when the robot is in balance. A collection of information, the second information set is a collection of a plurality of second sensing information acquired by the second sensing unit 50 when the robot is in balance; the auxiliary balance threshold is set according to the first information set and the second information set; Obtain the first sensor information and the second sensor information; compare the first sensor information, the second sensor information and the auxiliary balance threshold respectively to determine the balance state of the robot.

When the robot maintains balance, it acquires the image set, the first information set and the second information set through the first sensing unit 40, the second sensing unit 50 and the photographing device 10, and sets the balance threshold and the auxiliary balance threshold to obtain the judgment image in real time , The first sensor information and the second sensor information determine the balance state of the robot according to the balance threshold, the auxiliary balance threshold, the judgment image, the first sensor information and the second sensor information. By combining multiple judgment methods, the accuracy of balance judgment and the adaptability of balance judgment are enhanced.

The above robot balance determination method establishes an image model when the robot maintains balance, sets the balance threshold of the image model, and instantly compares the image and the image model to obtain the difference value, and determines the robot’s performance based on the difference value and the balance threshold. Balance state, so as to control the robot to adjust the state in time.

The robot balance determination method described above periodically reconstructs the image model according to the state information to ensure the accuracy of the image model, thereby improving the accuracy of the robot's balance state determination.

Further, the aforementioned robot balance determination method can be combined with other balance determination methods, such as determination based on a gravity sensor and a gyroscope, to improve the accuracy of the robot balance determination and enhance the adaptability.

For those skilled in the art, it is obvious that the present invention is not limited to the details of the above exemplary embodiments, and the present invention can be implemented in other specific forms without departing from the spirit or basic characteristics of the present invention. Therefore, no matter from which point of view, the embodiments should be regarded as exemplary and non-limiting. The scope of the present invention is defined by the appended claims rather than the above description, and therefore it is intended to fall within the claims. All changes within the meaning and scope of the equivalent elements of are included in the present invention. Any reference signs in the request shall not be regarded as the request item involved in the restriction. In addition, it is obvious that the word "include" does not exclude other means or steps, and the singular does not exclude the plural.

The above are only preferred embodiments of the present invention, and are not intended to limit the present invention in any form. In addition, those skilled in the art can also make other changes within the spirit of the present invention. Of course, these changes made according to the spirit of the present invention should all be included in the scope of protection of the present invention.

Claims (10)

A robot balance determination device, which is improved in that it includes: a photographing device; a processor, coupled to the photographing device, and configured to: receive an image set from the photographing device, the image set including the time when the robot is in balance Multiple initial images taken by the photographing device; acquiring the coordinates of each of the initial images; arranging and stitching multiple initial images according to the coordinates to generate an image model; setting the image model The balance threshold; receive the judgment image from the photographing device immediately; compare the judgment image with the image model to obtain the difference value; determine whether the difference value exceeds the balance threshold to determine the State the equilibrium state of the robot. The robot balance determination device according to claim 1, wherein the processor is further configured to: if the robot maintains balance, adjust the image model according to the determination image. The robot balance determination device according to claim 1, wherein the difference value is: the difference between the coordinates of the determination image and the coordinates of the same image area in the image model, or the determination The degree of difference between the image and the image in the same coordinate region in the image model. The robot balance determination device according to claim 1, wherein the processor is further configured to: determine the determination coordinates according to the model characteristics of the image model; the photographing device is further configured to: obtain the determination coordinates according to the determination coordinates The judgment image. The robot balance determination device according to claim 1, wherein the robot balance determination device further includes a first sensing unit and a second sensing unit, and the first sensing unit is used to sense the speed and displacement of the robot to form The first sensing information, the second sensing unit is used for sensing the azimuth angle of the robot to form second sensing information, wherein the processor is further used for: acquiring the first sensing information and the second sensing information; Forming state information according to the first sensing information and the second sensing information; adjusting the reconstruction period of the image model based on the state information. A method for determining the balance of a robot, which is improved in that it includes: acquiring an image set, the image set including a plurality of initial images acquired when the robot is in balance; acquiring the coordinates of each of the initial images; and according to the coordinates Arrange and stitch a plurality of the initial images to generate an image model; set the balance threshold of the image model; obtain the judgment image instantly; compare the judgment image with the image model to obtain the difference Value; determine whether the difference value exceeds the balance threshold to determine the balance state of the robot. The robot balance determination method according to claim 6, wherein the method further includes the step of: if the robot maintains a balance, adjusting the image model according to the determination image. The robot balance determination method according to claim 6, wherein the difference value is: the difference between the coordinates of the determination image and the coordinates of the same image area in the image model, or the determination The degree of difference between the image and the image in the same coordinate region in the image model. The robot balance determination method described in claim 6, in which "getting the determination immediately The "image" specifically includes the steps of: determining the judgment coordinates according to the model characteristics of the image model; acquiring the judgment image according to the judgment coordinates. The robot balance determination method according to claim 6, wherein the method further includes the step of: acquiring first sensing information and second sensing information, wherein the first sensing information includes speed and displacement information of the robot, and The second sensing information includes the azimuth angle information of the robot; the state information is formed according to the first sensing information and the second sensing information; the reconstruction period of the image model is adjusted according to the state information.

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