Control method of mechanical arm, desktop robot and electronic equipment

Abstract

The embodiment of the invention provides a mechanical arm control method, a desktop robot and electronic device.The method comprises the steps that a panoramic image of an operable area of the desktop robot is obtained based on a visual sensor located on a head assembly of the desktop robot, and a to-be-operated position of the desktop robot is determined according to the panoramic image; wherein the to-be-operated position is used for indicating the to-be-executed game action position of the desktop robot; determining a target rotation angle of a mechanical arm of the desktop robot moving to the to-be-operated position; and controlling the mechanical arm to move to the to-be-operated position according to the target rotation angle.

Description

Technical Field

[0001] The present application relates to the field of automatic control, and in particular to a control method for a robotic arm, a desktop robot, and an electronic device. Background Art

[0002] With the continuous advancement of science and technology, especially the maturity of artificial intelligence technology, home desktop robots have moved from science fiction to reality and gradually become assistants and partners in modern family life. In this field, desktop robots, as a device that combines mechanical arm operation and intelligent decision-making, provide game enthusiasts with a new way of entertainment.

[0003] However, existing desktop robots are usually designed for one-on-one desktop gaming, and can only play the same game with one user at a time, which limits the diversity of usage scenarios and the sharing of entertainment. For example, when multiple family members want to play different desktop games at the same time, traditional desktop robots cannot meet this demand and must play games with each user in turn, reducing the continuity and interactivity of entertainment.

[0004] Therefore, in the prior art, desktop robots only support one-on-one desktop games and cannot meet the needs of multiple users to play different desktop games at the same time, resulting in obvious limitations in function expansion and user experience.

[0005] In the existing technology, traditional desktop robots can only play games with one person, which has certain limitations. No effective solution has been proposed yet.

[0006] Therefore, it is necessary to improve the related technology to overcome the above-mentioned defects in the related technology. Summary of the invention

[0007] The embodiments of the present application provide a control method for a robotic arm, a desktop robot, and an electronic device to at least solve the problem in the prior art that a traditional desktop robot can only play games with one person and has certain limitations.

[0008] According to one embodiment of the present application, a method for controlling a robotic arm is provided, comprising: acquiring a panoramic image of an operable area of ​​the desktop robot based on a visual sensor located at a head assembly of the desktop robot, and determining a position to be operated of the desktop robot according to the panoramic image, wherein the position to be operated is used to indicate a position at which the desktop robot is to perform a game action; determining a target rotation angle for the robotic arm of the desktop robot to move to the position to be operated; and controlling the robotic arm to move to the position to be operated according to the target rotation angle.

[0009] In an exemplary embodiment, a panoramic image of the operable area of ​​the desktop robot is obtained based on a visual sensor located in a head component of the desktop robot, including: obtaining local images respectively captured by the visual sensor at different rotation angles, wherein a common field of view exists between two adjacent local images; performing a stitching step: extracting feature points in each local image, and matching feature points in the Nth local image with feature points in the N+1th local image; calculating a homography transformation moment of the Nth local image and the N+1th local image based on the matched feature points; matrix; performing homography transformation on the N+1th local image according to the homography transformation matrix of the Nth local image and the N+1th local image, and splicing the N+1th local image after the homography transformation with the Nth local image, wherein N is a positive integer; looping the splicing step until the Mth local image after the homography transformation is spliced ​​with the M-1th local image to obtain the panoramic image, wherein the Mth local image is the last local image acquired by the visual sensor within the target period, and M is a positive integer greater than 1.

[0010] In an exemplary embodiment, determining the operating position of the desktop robot according to the panoramic image includes: determining the operating position of the desktop robot according to a first feature vector of each area in the panoramic image and a second feature vector of each area in a historical panoramic image, wherein the historical panoramic image is a previous image of the panoramic image and each area corresponds to a desktop game of a different process; determining whether a game state in each area has changed according to the first feature vector and the second feature vector of each area; in a case where it is determined that there is a target area where the game state has changed, determining whether the desktop robot is required to perform a game operation according to the game rules of the desktop game in the target area; in a case where it is determined that the desktop robot is required to perform a game operation, determining the position corresponding to the target area as the operating position of the desktop robot.

[0011] In an exemplary embodiment, determining a target rotation angle for the robotic arm of the desktop robot to move to the position to be operated includes: determining a first rotation angle of a head component corresponding to a first absolute encoder when the visual sensor captures a target local image, wherein the first absolute encoder is used to obtain the rotation angle of the head component, and the target area exists in the target local image; determining the first rotation angle to be the target rotation angle.

[0012] In an exemplary embodiment, controlling the robotic arm to move to the position to be operated according to the target rotation angle includes: determining a second rotation angle of a second absolute encoder corresponding to the robotic arm; determining whether the second rotation angle is consistent with the target rotation angle; when the second rotation angle is consistent with the target rotation angle, determining that the robotic arm moves to the position to be operated; when the second rotation angle is inconsistent with the target rotation angle, controlling the robotic arm to move to the position to be operated according to the target rotation angle.

[0013] In an exemplary embodiment, after controlling the robotic arm to move to the position to be operated according to the target rotation angle, the method further includes: determining a tabletop game corresponding to the position to be operated; determining a target position of a picking component of the robotic arm according to the rules of the tabletop game and a current state of the tabletop game; controlling the picking component to grab a target object at the target position, and / or controlling the picking component to move the target object to the target position, wherein the picking component is used to grasp or release the target object.

[0014] In an exemplary embodiment, a panoramic image of the operable area of ​​the desktop robot is acquired based on a visual sensor located at a head component of the desktop robot, including: determining whether there are multiple rounds of desktop games simultaneously in the operable area; if there are no multiple rounds of desktop games simultaneously in the operation area, determining a target operation area for the desktop games, and acquiring an image of the target operation area of ​​the desktop robot based on the visual sensor of the head component of the desktop robot; if there are multiple rounds of desktop games simultaneously in the operation area, acquiring a panoramic image of the operable area of ​​the desktop robot based on the visual sensor located at the head component of the desktop robot.

[0015] According to another embodiment of the present application, a desktop robot is provided, comprising: a visual sensor for acquiring a panoramic image of an operable area of ​​the desktop robot; a driving module for determining a position to be operated of the desktop robot according to the panoramic image; determining a target rotation angle for a mechanical arm of the desktop robot to move to the position to be operated; and controlling the mechanical arm to move to the position to be operated according to the target rotation angle, wherein the position to be operated is used to indicate a position of the desktop robot to perform a game action;

[0016] In an exemplary embodiment, the desktop robot comprises: a head assembly and a body spring sheet, wherein the rotating contact spring sheet of the head assembly contacts the body spring sheet seat through elastic force.

[0017] According to another embodiment of the present application, a computer-readable storage medium is provided, in which a computer program is stored, wherein the computer program is configured to execute the steps of any of the above method embodiments when run.

[0018] According to another embodiment of the present application, an electronic device is provided, including a memory and a processor, wherein the memory stores a computer program, and the processor is configured to run the computer program to execute the steps in any one of the above method embodiments.

[0019] According to another embodiment of the present application, a computer program product is provided, including a computer program, and when the computer program is executed by a processor, the steps in any of the above method embodiments are implemented.

[0020] Through this application, a panoramic image of the operable area of ​​the desktop robot is obtained based on a visual sensor located in the head component of the desktop robot, and the position to be operated of the desktop robot is determined according to the panoramic image, wherein the position to be operated is used to indicate the position of the desktop robot to perform a game action; the target rotation angle of the mechanical arm of the desktop robot to move to the position to be operated is determined; and the mechanical arm is controlled to move to the position to be operated according to the target rotation angle. In the embodiment of the present application, the desktop robot captures images from multiple angles using a visual sensor by continuously rotating the head component, and then fuses these images into a panoramic image (i.e., a 360° image) through image stitching technology; based on the panoramic image, the desktop robot can determine the position to be operated through image analysis and pattern recognition technology, and then control the desktop robot to play games with multiple people within a 360° range. Therefore, the problem that traditional desktop robots can only play games with one person and have certain limitations can be solved. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and, together with the description, serve to explain the principles of the present application.

[0022] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, for ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative labor.

[0023] Figure 1 It is a hardware structure block diagram of a desktop robot of a method for controlling a mechanical arm according to an embodiment of the present application;

[0024] Figure 2is a flow chart of a method for controlling a robotic arm according to an embodiment of the present application;

[0025] Figure 3 is a schematic diagram of a desktop robot according to an embodiment of the present application (I);

[0026] Figure 4 is a schematic diagram of a desktop robot according to an embodiment of the present application (II);

[0027] Figure 5 is a schematic diagram of a desktop robot according to an embodiment of the present application (III);

[0028] Figure 6 It is a structural block diagram of a desktop robot according to an embodiment of the present application. DETAILED DESCRIPTION

[0029] The embodiments of the present application will be described in detail below with reference to the accompanying drawings and in combination with the embodiments.

[0030] It should be noted that the terms "first", "second", etc. in the specification and claims of this application and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence.

[0031] The method embodiments provided in the embodiments of the present application can be executed in a desktop robot or a similar computing device. Taking running on a desktop robot as an example, Figure 1 1 is a hardware structure diagram of a desktop robot of a control method of a mechanical arm in an embodiment of the present application. Figure 1 As shown, the desktop robot may include one or more ( Figure 1 Only one is shown in the figure) a processor 102 (the processor 102 may include but is not limited to a processing device such as a microprocessor MPU or a programmable logic device FPGA) and a memory 104 for storing data, wherein the above-mentioned desktop robot may also include a transmission device 106 for communication functions and an input and output device 108. It can be understood by those skilled in the art that Figure 1 The structure shown is only for illustration and does not limit the structure of the above desktop robot. Figure 1 More or fewer components as shown, or with Figure 1 Different configurations shown.

[0032] The memory 104 can be used to store computer programs, for example, software programs and modules of application software, such as the computer program corresponding to the control method of the robot arm in the embodiment of the present application. The processor 102 executes various functional applications and data processing by running the computer program stored in the memory 104, that is, to implement the above method. The memory 104 may include a high-speed random access memory, and may also include a non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some examples, the memory 104 may further include a memory remotely arranged relative to the processor 102, and these remote memories can be connected to the desktop robot via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0033] The transmission device 106 is used to receive or send data via a network. The specific example of the above network may include a wireless network provided by the communication provider of the desktop robot. In one example, the transmission device 106 includes a network adapter (Network Interface Controller, referred to as NIC), which can be connected to other network devices through a base station so as to communicate with the Internet. In one example, the transmission device 106 can be a radio frequency (Radio Frequency, referred to as RF) module, which is used to communicate with the Internet wirelessly.

[0034] In this embodiment, a control method for a robotic arm is provided, which is applied to the above-mentioned desktop robot. Figure 2 is a flow chart of a control method of a robotic arm according to an embodiment of the present application, such as Figure 2 As shown, the process includes the following steps:

[0035] Step S202, obtaining a panoramic image of the operable area of ​​the desktop robot based on a visual sensor located at a head component of the desktop robot, and determining a position to be operated of the desktop robot according to the panoramic image, wherein the position to be operated is used to indicate a position of the desktop robot to perform a game action;

[0036] In step S202, the desktop robot can obtain a panoramic image of the operating area using the visual sensor on the head assembly of the desktop robot. This is very different from the traditional desktop robot that can only obtain images directly in front of it or at a fixed perspective. Obtaining a panoramic image means that the desktop robot can observe the entire desktop without blind spots, including the game status in all directions, such as the distribution of the chessboard and chess pieces. Based on the panoramic image, the desktop robot can quickly identify different game states and determine the position to be operated, that is, the precise position where the game action needs to be performed.

[0037] It should be noted that in order to ensure stable signal transmission between the visual system and the body of the desktop robot head assembly during the infinite cycle rotation, a spring contact design is adopted. The rotating contact spring contacts the body spring seat through elastic force, and can maintain electrical connection even during 360° rotation, ensuring continuous data transmission. This solves the signal interruption or winding problem that traditional desktop robots may encounter when the head rotates.

[0038] Step S204, determining a target rotation angle for the mechanical arm of the desktop robot to move to the position to be operated;

[0039] It should be noted that the desktop robot monitors the rotation angle of the head through the first absolute encoder on the head assembly. After the position to be operated is determined, the desktop robot calculates the angle (target rotation angle) that the robotic arm needs to rotate to accurately align with the position. Based on the control of the target rotation angle, the robotic arm can flexibly move to any required position and perform game actions, without being limited to fixed-direction operations like traditional desktop robots. This time-sharing control and synchronous scheduling mechanism ensures that the desktop robot can flexibly perform tasks within a 360° range, serve more users and perform more types of desktop games.

[0040] Step S206: controlling the robot arm to move to the waiting operation position according to the target rotation angle.

[0041] Through the above steps, a panoramic image of the operable area of ​​the desktop robot is obtained based on the visual sensor located in the head component of the desktop robot, and the position to be operated of the desktop robot is determined according to the panoramic image, wherein the position to be operated is used to indicate the position of the desktop robot to perform the game action; the target rotation angle of the mechanical arm of the desktop robot to move to the position to be operated is determined; and the mechanical arm is controlled to move to the position to be operated according to the target rotation angle. In the embodiment of the present application, the desktop robot captures images from multiple angles using a visual sensor by continuously rotating the head component, and then fuses these images into a panoramic image (i.e., a 360° image) through image stitching technology; based on the panoramic image, the desktop robot can determine the position to be operated through image analysis and pattern recognition technology, and then control the desktop robot to play games with multiple people within a 360° range. Therefore, the problem that traditional desktop robots can only play chess with one person and have certain limitations can be solved.

[0042] Optionally, the above step S202 can be implemented in the following manner: obtaining local images respectively captured by the visual sensor at different rotation angles, wherein there is a common field of view between two adjacent local images; performing a stitching step: extracting feature points in each local image, and matching feature points in the Nth local image with feature points in the N+1th local image; calculating the homography transformation matrix of the Nth local image and the N+1th local image based on the matched feature points; performing a homography transformation on the N+1th local image according to the homography transformation matrix of the Nth local image and the N+1th local image, and stitching the N+1th local image after the homography transformation with the Nth local image, wherein N is a positive integer; looping the stitching step until the Mth local image after the homography transformation is stitched with the M-1th local image to obtain the panoramic image, wherein the Mth local image is the last local image acquired by the visual sensor within the target period, and M is a positive integer greater than 1.

[0043] First, the head assembly of the desktop robot uses its visual sensor to collect multiple local images at different rotation angles, and these local images together cover the entire operating area. For example, assuming that the field of view of the desktop robot is 90°, in order to cover a 360° area, it needs to collect images in four directions: 0°, 90°, 180°, and 270°. Each image is taken from a specific angle and can capture information about part of the chessboard and chess pieces in that direction.

[0044] After acquiring partial images, the desktop robot vision system automatically extracts feature points in each image. Feature points are points with unique properties in the image, such as corner points, edge points, etc. They serve as anchor points in the image stitching process to help identify the correspondence between images. For example, suppose the Nth image (N=1) captures a corner of the chessboard and part of the chess pieces, while the N+1th image (N+1=2) covers the other side of the chessboard. The vision system will identify the feature points of the chessboard corners and chess pieces in the two images, and then match them to find the same feature point pairs.

[0045] When the feature point matching is completed, the homography transformation matrix between the Nth image and the N+1th image will be calculated based on the matched feature point pairs. It should be noted that homography transformation is an image transformation technology used to describe the geometric relationship between corresponding points in two images, especially used to adjust the image perspective in image stitching so that the two images can be aligned. In this embodiment, the calculated homography transformation matrix will be used for subsequent image alignment and stitching.

[0046] When the homography transformation matrix is ​​calculated, the calculated homography transformation matrix is ​​used to adjust the perspective of the N+1th image to align with the Nth image. The adjusted image is stitched with the Nth image to form a larger image. This process is repeated until all local images are stitched together to form a panoramic image covering the entire operating area.

[0047] For example, assuming the target cycle is 120° rotation, the desktop robot will start rotating from 0° and obtain three partial images of 120°, 240°, and 360° (back to 0°) in sequence. First, the feature points of the first image (0°) and the second image (120°) are matched, the corresponding homography transformation matrix is ​​calculated, and then the second image is transformed and spliced ​​to the first image. Next, the second and third images (240°) repeat this process until all images are spliced ​​together to form a panoramic image covering a 360° viewing angle.

[0048] After acquiring the panoramic image, the desktop robot can observe and analyze the entire operating area, and support desktop games with multiple users in different directions. For example, the desktop robot can simultaneously identify the chess board in front, the Gobang board on the right, and the mahjong board on the left, and then play games with users in different directions according to the game rules and strategies.

[0049] Through the above steps, the 360° rotating multi-tasking desktop robot can overcome the limitations of traditional desktop robots in terms of viewing angle and achieve all-round visual perception of the operating area, thereby supporting simultaneous, multi-tasking desktop games with multiple users, greatly enhancing the interactivity and entertainment of the desktop robot.

[0050] Optionally, the "determining the operating position of the desktop robot according to the panoramic image" in the above step S202 can be achieved in the following way: according to the first feature vector of each area in the panoramic image, and the second feature vector of each area in the historical panoramic image, wherein the historical panoramic image is the previous image of the panoramic image, and each area corresponds to a desktop game of a different process; determining whether the game status in each area has changed according to the first feature vector and the second feature vector of each area; in the case of determining that there is a target area where the game status has changed, determining whether the desktop robot is required to perform a game operation according to the game rules of the desktop game in the target area; in the case of determining that the desktop robot is required to perform a game operation, determining the position corresponding to the target area as the operating position of the desktop robot.

[0051] In the embodiment of the present application, the first feature vector of each area is extracted from the current panoramic image, and the second feature vector of each area is extracted from the historical panoramic image (i.e., the previous frame image). The feature vector may contain information such as color distribution, texture pattern, and arrangement of chess pieces or cards in the area, which is the basis for the system to judge the change of game status.

[0052] By comparing the first and second eigenvectors of each region, the robot can determine whether the game state has changed. For example, if the position of a chess piece or card in a region changes between two frames of images, the game state of that region is considered to have changed.

[0053] When the robot determines that there is a target area where the game state has changed, it will further analyze the specific tabletop game (such as chess, cards, etc.) corresponding to this area and determine whether a game action needs to be performed to cope with the change. For example, if a deck of playing poker cards is identified in the target area and the game state has changed, the robot will determine whether it needs to play or shuffle the cards.

[0054] If it is determined that a game operation needs to be performed, the robot will decide the specific action based on the game rules of the table game in the target area. In chess game scenarios, the robot needs to decide whether to pick up, move or put down chess pieces based on the rules of the game. In card games such as poker, the robot needs to determine whether to shuffle, deal or collect cards based on the rules of the game.

[0055] After determining a specific game action, the robot will determine the position corresponding to the target area as its waiting position, that is, the precise desktop coordinates required for the game operation. For example, after determining that the cards need to be dealt in a poker game, the robot will calculate the desktop coordinates required for dealing the cards and determine them as the waiting position.

[0056] It should be noted that when the above-mentioned desktop robot cannot accurately determine whether the desktop robot is required to perform game operations, the desktop robot will also send question information to the target object through voice question and answer, and perform the game operation when receiving response information from the target object indicating that the desktop robot is required to perform game operations.

[0057] Suppose at a family gathering, a chess game is going on on one side of the table, while several users are playing a poker game on the other side. The robot continuously collects panoramic images of the table through the visual sensor of its head assembly.

[0058] When the robot detects that the feature vector of a chessboard area has changed, it may be because the user has moved a chess piece. The robot identifies this area as the target area for the game state change, and determines whether it needs to perform operations such as picking up chess pieces or moving chess pieces according to the rules of chess. If necessary, the robot will calculate the new position of the chess piece, determine it as the position to be operated, and dispatch the robot arm to perform the corresponding chess piece movement action.

[0059] At the same time, if the robot detects a change in the feature vector in the poker game area, such as a change in the position or number of cards, this may mean that the user has played or shuffled the cards. The robot also identifies this area as the target area for the game state change, and then determines whether to shuffle, deal, or collect cards based on the rules of the poker game. If necessary, the robot will determine the exact position of the card as the position to be operated, and dispatch the robot arm to perform operations such as shuffling or dealing.

[0060] This method of analyzing the feature vectors of continuous panoramic images and making intelligent decisions based on game rules enables the robot to efficiently respond to various actions in tabletop games, whether it is chess games or card games, and can achieve precise operations and intelligent game interactions, greatly enriching the application scenarios of the robot and the user's gaming experience.

[0061] Optionally, the above step S204 can be implemented in the following way: determine the first rotation angle of the head component corresponding to the first absolute value encoder when the visual sensor captures the target local image, wherein the first absolute value encoder is used to obtain the rotation angle of the head component, and the target area exists in the target local image; determine that the first rotation angle is the target rotation angle.

[0062] When the desktop robot head assembly rotates to a certain angle, its visual sensor will capture a partial image. If this partial image contains the target area that needs to be operated, then this image is called the target partial image. For example, if the desktop robot rotates to 240° and the visual sensor captures the movement of chess pieces on the chessboard, then the image captured at the 240° angle is the target partial image.

[0063] An absolute encoder is a sensor that can output the current position or angle. Unlike traditional incremental encoders, it can maintain the current position information after power failure without repositioning. The first absolute encoder equipped on the head assembly of the desktop robot can monitor and record the rotation angle of the head assembly in real time, providing the desktop robot with accurate information of the current viewing angle.

[0064] When the visual sensor captures a partial image of the target, the first absolute encoder records the current rotation angle of the head assembly, which is the first rotation angle. This rotation angle is directly related to the position where the robotic arm needs to move to. If the current position of the robotic arm is inconsistent with the target operation position (target area position), the desktop robot needs to calculate and determine a target rotation angle so that the robotic arm can accurately move to the target position to perform game actions.

[0065] If the first rotation angle recorded by the first absolute encoder is exactly the angle that the desktop robot needs to reach the position to be operated, then this first rotation angle itself is directly determined as the target rotation angle. This means that the robot arm does not need to rotate additionally and can directly perform game actions.

[0066] Once the target rotation angle is determined, the desktop robot will control the robotic arm to rotate appropriately until the robotic arm is aligned with the target area.

[0067] Through the embodiments of the present application, the desktop robot can realize efficient linkage between the rotation of the head assembly and the control of the mechanical arm, ensuring that the mechanical arm can aim at the target area at the correct time and angle to perform game actions. The embodiments of the present application greatly improve the operational flexibility and accuracy of the desktop robot, enabling it to accurately respond to users' desktop game requests in different directions, support multiple users to interact at the same time, and increase the fun and participation of the game.

[0068] For example, in a family game, when the desktop robot detects that the chess pieces on the chessboard in front of it have changed, the visual sensor on its head assembly will capture this change, and the first absolute encoder will record the current rotation angle, which is 270°. If the current orientation of the robotic arm is consistent with this angle, then 270° is directly determined as the target rotation angle, and the robotic arm can directly perform operations such as picking up or moving chess pieces to respond to the user's game actions without further adjustment. If the robotic arm is not at the 270° position, the desktop robot will control the robotic arm to rotate according to the target rotation angle until it is aligned with the target area to complete the game action. This precise control mechanism ensures that the desktop robot can flexibly and efficiently interact with users in desktop games within a 360° range.

[0069] Optionally, controlling the robotic arm to move to the position to be operated according to the target rotation angle includes: determining a second rotation angle of a second absolute encoder corresponding to the robotic arm; determining whether the second rotation angle is consistent with the target rotation angle; when the second rotation angle is consistent with the target rotation angle, determining that the robotic arm moves to the position to be operated; when the second rotation angle is inconsistent with the target rotation angle, controlling the robotic arm to move to the position to be operated according to the target rotation angle.

[0070] Before the desktop robot is ready to move the robotic arm, it first checks the rotation angle of the current position of the robotic arm, which is provided by the second absolute encoder corresponding to the robotic arm. The absolute encoder can provide direct information about the current position of the robotic arm without the need to accumulate relative displacement.

[0071] After obtaining the second rotation angle, the desktop robot compares it with the target rotation angle, which is the ideal angle calculated by the desktop robot in order to move to the position to be operated.

[0072] If the second rotation angle is consistent with the target rotation angle, the robotic arm is currently aligned with the target position and no further rotation is required. In this case, the desktop robot can directly control the robotic arm to perform game actions.

[0073] If the second rotation angle is inconsistent with the target rotation angle, the desktop robot will control the robotic arm to make corresponding adjustments based on the target rotation angle to ensure that the robotic arm can accurately align with the position to be operated. This usually involves calculating the difference angle that the robotic arm needs to rotate and controlling the robotic arm drive motor (such as a stepper motor) to achieve this rotation. The desktop robot will continue to monitor the second absolute encoder until the robotic arm reaches the target rotation angle and aligns with the position to be operated.

[0074] Through the embodiments of the present application, it is ensured that the robotic arm can accurately respond to the operational requirements of the desktop robot, and can quickly and accurately locate specific positions on each chessboard, whether in the initial position or during movement. Through real-time monitoring of the second absolute encoder, the desktop robot can achieve closed-loop control of the robotic arm, that is, adjust the control signal according to the actual position feedback, which greatly improves the accuracy and stability of the robotic arm movement.

[0075] In an exemplary embodiment, after controlling the robotic arm to move to the position to be operated according to the target rotation angle, it also includes: determining a tabletop game corresponding to the position to be operated; determining the target position of the picking component of the robotic arm according to the rules of the tabletop game and the current state of the tabletop game; controlling the picking component to grab the target object at the target position, and / or controlling the picking component to move the target object to the target position, wherein the picking component is used to grasp or release the target object.

[0076] When the robot reaches the position to be operated, the desktop robot's vision system will further analyze the characteristics of the target area to determine the tabletop game being played on the board. This is because different tabletop games have different rules and ways of playing. For example, the desktop robot needs to identify the layout of the board, the style of the chess pieces, etc., to determine whether the game on the board is chess, go, chess or gobang, etc.; in poker games, the robot needs to understand the rounds of the game, the status of the player's hand cards, and the timing of playing or shuffling cards.

[0077] After the tabletop game is determined, the tabletop robot will calculate the target position of the robotic arm to pick up the component according to the rules of the tabletop game and the current state of the target area. In other words, the tabletop robot can analyze the current state of the game and evaluate the best operation strategy.

[0078] When the target location is determined, the desktop robot will control the pickup component on its robotic arm to pick up the target object (for example, a chess piece, a card) and move it to the target location. The pickup component usually has the ability to grasp and release the target object, allowing the desktop robot to flexibly handle target objects such as chess pieces, cards, and mahjong, and move them from the current location to another. For example, if the desktop robot recognizes that a Go game is being played in the target area, it will determine the best position for the next move based on the Go rules and the current game, and then control the pickup component to pick up a Go piece and place it accurately on the calculated position for the move.

[0079] Through the embodiments of the present application, the desktop robot can autonomously identify desktop games, analyze the current game status, and execute game actions according to game rules and strategies.

[0080] For example, during a family gathering, the desktop robot detected that a user had moved a chess piece on the left chessboard. The desktop robot first used the visual sensor and absolute encoder system of its head assembly to determine the position of the board where the robotic arm should move to. After reaching the target position, the desktop robot analyzed the characteristics of the chessboard and determined that the tabletop game being played was chess. Then, based on the rules of chess and the current state of the game, the desktop robot calculated the best position on the board to which its robotic arm pickup assembly should move a chess piece in response to the user's previous move. Finally, the desktop robot controlled the pickup assembly to accurately pick up a chess piece and move it to the calculated chess position, completing a successful chess move.

[0081] When the robot detects the need to shuffle the cards in the poker game area (perhaps due to the end of the previous round of the game), it will calculate the pickup component to grab the cards from the shuffle area and move them to the target position in the shuffle area according to the rules of the poker game. The robot then controls the pickup component to perform the shuffle action, mix the cards evenly, and then distribute the shuffled cards to each player according to the rules of the game to ensure the fairness and smoothness of the game.

[0082] Optionally, a panoramic image of the operable area of ​​the desktop robot is acquired based on a visual sensor located at a head component of the desktop robot, including: determining whether there are multiple rounds of desktop games simultaneously in the operable area; if there are no multiple rounds of desktop games simultaneously in the operation area, determining a target operation area for the desktop games, and acquiring an image of the target operation area of ​​the desktop robot based on the visual sensor of the head component of the desktop robot; if there are multiple rounds of desktop games simultaneously in the operation area, acquiring a panoramic image of the operable area of ​​the desktop robot based on the visual sensor located at the head component of the desktop robot.

[0083] In an embodiment of the present application, the desktop robot checks whether there are multiple rounds of desktop games in its operating area (usually a desktop or a game area) at the same time. Optionally, the distribution of different chessboards in the area is determined by analyzing the image information currently acquired by the visual sensor and identifying and counting them. For example, the desktop robot vision system can identify the existence of objects on the desktop, thereby determining whether there are multiple rounds of desktop games in progress at the same time.

[0084] If the desktop robot determines that there are no multiple rounds of desktop games in the operation area at the same time, that is, the desktop robot only needs to focus on and process the games in a single area. In this case, the desktop robot will determine the target operation area for the desktop game. Then, the desktop robot will only obtain the image of the target operation area based on the visual sensor of the head component to save computing resources and improve processing efficiency.

[0085] If the desktop robot detects that there are multiple rounds of desktop games in the operating area at the same time, the desktop robot will obtain a panoramic image of the entire operating area based on the visual sensor of its head component. The panoramic image can cover the information of all areas, that is, the desktop robot can handle games in multiple areas at the same time, identify the layout changes of games in each area, and calculate the response strategies respectively.

[0086] Through the embodiments of the present application, the desktop robot can intelligently adjust the image acquisition range of its visual sensor, and efficiently perform game state analysis and game action calculation according to the actual situation of the desktop game in the operation area. The desktop robot's ability to intelligently adjust the image acquisition range not only improves the processing efficiency of the desktop robot, but also ensures that it can accurately and timely respond to the user's game actions in a complex game environment, and supports playing games with multiple users on different chessboards at the same time.

[0087] In order to better understand the process of the control method of the above-mentioned robotic arm, the implementation method flow of the control of the above-mentioned robotic arm is described below in combination with an optional embodiment, but it is not used to limit the technical solution of the embodiment of the present application.

[0088] The present application embodiment provides a desktop robot, such as Figure 3 , Figure 4 and Figure 5 As shown,

[0089] Figure 3 1-1 is the head assembly of the desktop robot (including the visual sensor); 1-2 is the robotic arm of the desktop robot; 1-3 is the center of the head assembly / rotation center of the robotic arm of the desktop robot.

[0090] Figure 4 2-1 is the robot arm drive stepper motor module; 2-2 is the motor mounting bracket; 2-3 is the upper arm drive shaft support bearing; 2-4 is the robot arm frame; 2-5 is the motor motion limit frame; 2-6 is the robot arm frame shaft support bearing; 2-7 is the robot arm housing; 2-8 is the motor upper damping plate; 2-9 is the motor lower damping plate; 2-10 is the machine housing.

[0091] Figure 5 3-1 is the head assembly driving stepper motor module; 3-2 is the head driving gear (17 teeth); 3-3 is the head driven gear (51 teeth); 3-4 is the body shell; 3-5 is the head rotating bearing; 3-6 is the head rotating contact spring; 3-7 is the body spring seat.

[0092] like Figure 3 and Figure 4As shown, the robot arm driving stepper motor module (2-1) drives the robot arm (1-2) to rotate around the robot arm rotation center (1-3): the robot arm driving stepper motor module (2-1) is installed on the motor mounting bracket (2-2), and the motor shaft is directly connected to the robot arm frame (2-4) to realize the driving of the robot arm, and the transmission ratio of the motor to the robot arm is 1:1.

[0093] like Figure 5 As shown, the head assembly drives the stepper motor module (3-1) to drive the head assembly (1-1) to rotate around the center of the head assembly (1-3): the head assembly drives the stepper motor module (3-1) is installed on the head assembly (1-1), and the motor shaft is connected to the head driving gear (3-2) to drive the head driven gear (3-3) to realize the rotation of the head assembly, and the transmission ratio of the head gear is 1:3. The head rotating contact spring (3-6) and the fuselage spring seat (3-7) can always maintain reliable contact and transmit signals during the 360° rotation process of the head.

[0094] In the embodiment of the present application, in order to solve the problem of the risk of breakage caused by the traditional cable winding problem when the desktop robot head rotates 360°, the spring contact technology is adopted, such as Figure 5 As shown, through the elastic connection between the rotating contact spring (3-6) on the head assembly and the spring seat (3-7) on the fuselage, the continuous stability of signal transmission can be ensured even in an endless rotation cycle, effectively avoiding the hidden danger of cable breakage, thereby achieving unlimited rotation capability beyond 360°.

[0095] In order to ensure that the rotation of the head vision sensor is synchronized with the position of the robot arm, a multi-encoder system is used, especially the combination of absolute encoders. Each encoder monitors and records the precise angle of rotation of the robot arm to ensure that it can accurately match the visual sensor's perspective after rotation in any direction. This design not only improves the overall flexibility of the system, but also ensures the consistency and accuracy between visual inspection and robot execution.

[0096] During the task execution phase, through the angle information provided by multiple encoders, when the visual system identifies and locates the area to be operated, it can immediately dispatch the robotic arm to the target position, even if the visual sensor and the robotic arm are in different rotation states, it can ensure the smooth completion of the task. In the scenario where it is necessary to simulate a one-on-many round-robin battle between humans, a synchronous control strategy is adopted to keep the robotic arm and the head visual system in the same rotation direction, ensuring that the desktop robot can seamlessly switch to different games and play continuous desktop games with multiple users.

[0097] In order to overcome the limitation of the limited field of view of the camera, in the embodiment of the present application, during the rotation process, the camera automatically takes pictures when it reaches a specific angle to capture the image on the current area. By continuously shooting K images, each image shares a part of the field of view with its adjacent images, and using image processing technology, key feature points are extracted, such as the specific identification of SI FT feature points. These feature points serve as anchor points for image stitching, and through the calculation of the homography transformation matrix, K images can be accurately aligned to finally synthesize a complete 360° panoramic image. This method not only solves the problem of field of view limitation, but also provides a full range of game detection capabilities for desktop robots, enhancing the system's adaptability to complex game environments.

[0098] Through the embodiments of the present application, not only the problem of synchronization between the rotation of the robotic arm and the visual system in the traditional design is solved, but also the overall efficiency and flexibility of the system are further improved. The tasks are subdivided into visual perception, intelligent decision-making and robotic arm execution. Through the decoupling of the visual system and the robotic arm control, the desktop robot can perform continuous positioning and real-time detection within a 360° range. When the task requirements are clear, the system can quickly locate and adjust the robotic arm to the required position, respond quickly and execute operations. In the embodiments of the present application, not only the application scope of the desktop robot in a multi-tasking environment is expanded, but also its interactive experience and intelligent performance in the desktop game scene are significantly improved. Through a complex multi-angle task time-sharing scheduling algorithm, the task processing process is optimized, and the double improvement of efficiency and accuracy is achieved, thereby bringing users a smoother and smarter desktop game experience.

[0099] Through the description of the above implementation methods, those skilled in the art can clearly understand that the method according to the above embodiment can be implemented by means of software plus a necessary general hardware platform, and of course by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art, can be embodied in the form of a software product, which is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk), and includes a number of instructions for a terminal device (which can be a mobile phone, computer, server, or network device, etc.) to execute the methods described in each embodiment of the present application.

[0100] In this embodiment, a desktop robot is also provided, which is used to implement the above-mentioned embodiments and preferred implementation modes, and the descriptions that have been made will not be repeated. As used below, the term "module" can implement a combination of software and / or hardware for a predetermined function. Although the desktop robot described in the following embodiments is preferably implemented in software, the implementation of hardware, or a combination of software and hardware, is also possible and conceivable.

[0101] Figure 6is a structural block diagram of a desktop robot according to an embodiment of the present application, such as Figure 6 As shown, the desktop robot includes:

[0102] A visual sensor 62, used to obtain a panoramic image of the operable area of ​​the desktop robot;

[0103] The driving module 64 is used to determine the operating position of the desktop robot according to the panoramic image; determine the target rotation angle of the mechanical arm of the desktop robot to move to the operating position; and control the mechanical arm to move to the operating position according to the target rotation angle, wherein the operating position is used to indicate the position of the desktop robot to perform a game action.

[0104] Through the above-mentioned desktop robot, a panoramic image of the operable area of ​​the desktop robot is obtained based on the visual sensor located in the head component of the desktop robot, and the driving module determines the position to be operated of the desktop robot according to the panoramic image, wherein the position to be operated is used to indicate the position of the desktop robot to perform the game action; determines the target rotation angle of the mechanical arm of the desktop robot to move to the position to be operated; and controls the mechanical arm to move to the position to be operated according to the target rotation angle. In the embodiment of the present application, the desktop robot captures images from multiple angles by continuously rotating the head component using a visual sensor, and then fuses these images into a panoramic image (i.e., a 360° image) through image stitching technology; based on the panoramic image, the desktop robot can determine the position to be operated through image analysis and pattern recognition technology, and then control the desktop robot to play chess with multiple people within a 360° range. Therefore, the problem that traditional desktop robots can only play chess with one person and have certain limitations can be solved.

[0105] In an exemplary embodiment, the desktop robot comprises: a head assembly and a body spring sheet, wherein the rotating contact spring sheet of the head assembly contacts the body spring sheet seat through elastic force.

[0106] In an exemplary embodiment, the visual sensor 62 is used to obtain local images collected by the visual sensor at different rotation angles, wherein there is a common field of view between two adjacent local images; perform a stitching step: extract feature points in each local image, and match feature points in the Nth local image with feature points in the N+1th local image; calculate the homography transformation matrix of the Nth local image and the N+1th local image based on the matched feature points; perform a homography transformation on the N+1th local image according to the homography transformation matrix of the Nth local image and the N+1th local image, and stitch the N+1th local image after the homography transformation with the Nth local image, wherein N is a positive integer; and loop through the stitching step until the Mth local image after the homography transformation is stitched with the M-1th local image to obtain the panoramic image, wherein the Mth local image is the last local image acquired by the visual sensor within the target period, and M is a positive integer greater than 1.

[0107] In an exemplary embodiment, the driving module 64 is used to determine whether the game status of each area has changed based on a first feature vector of each area in the panoramic image and a second feature vector of each area in a historical panoramic image, wherein the historical panoramic image is a previous image of the panoramic image and each area corresponds to a desktop game of a different process; when it is determined that there is a target area where the game status has changed, determine whether the desktop robot is required to perform a game operation based on the game rules of the desktop game in the target area; when it is determined that the desktop robot is required to perform a game operation, determine the position corresponding to the target area as the position to be operated by the desktop robot.

[0108] In an exemplary embodiment, the driving module 64 is used to determine a first rotation angle of a head component corresponding to a first absolute encoder when the visual sensor captures a target local image, wherein the first absolute encoder is used to obtain the rotation angle of the head component, and the target area exists in the target local image; and determine that the first rotation angle is the target rotation angle.

[0109] In an exemplary embodiment, the driving module 64 is used to determine the second rotation angle of the second absolute encoder corresponding to the robotic arm; determine whether the second rotation angle is consistent with the target rotation angle; when the second rotation angle is consistent with the target rotation angle, determine that the robotic arm moves to the operating position; when the second rotation angle is inconsistent with the target rotation angle, control the robotic arm to move to the operating position according to the target rotation angle.

[0110] In an exemplary embodiment, the driving module 64 is used to determine the tabletop game corresponding to the position to be operated; determine the target position of the picking component of the robotic arm according to the rules of the tabletop game and the current state of the tabletop game; control the picking component to grab the target object at the target position, and / or control the picking component to move the target object to the target position, wherein the picking component is used to grasp or release the target object.

[0111] In an exemplary embodiment, the driving module 64 is used to determine whether there are multiple rounds of tabletop games simultaneously in the operable area; if there are no multiple rounds of tabletop games simultaneously in the operating area, determine the target operating area for conducting the tabletop games; the visual sensor 62 is used to obtain an image of the target operating area of ​​the desktop robot; if there are multiple rounds of tabletop games simultaneously in the operating area, obtain a panoramic image of the operable area of ​​the desktop robot.

[0112] It should be noted that the above modules can be implemented by software or hardware. For the latter, it can be implemented in the following ways, but not limited to: the above modules are all located in the same processor; or the above modules are located in different processors in any combination.

[0113] An embodiment of the present application further provides a computer-readable storage medium, in which a computer program is stored, wherein the computer program is configured to execute the steps of any of the above method embodiments when running.

[0114] Optionally, in this embodiment, the storage medium may be configured to store program codes for executing the following steps:

[0115] S1, acquiring a panoramic image of the operable area of ​​the desktop robot based on a visual sensor located at a head component of the desktop robot, and determining a position to be operated of the desktop robot according to the panoramic image, wherein the position to be operated is used to indicate a position of the desktop robot to perform a game action;

[0116] S2, determining a target rotation angle for the mechanical arm of the desktop robot to move to the position to be operated;

[0117] S3, controlling the robot arm to move to the waiting operation position according to the target rotation angle.

[0118] In an exemplary embodiment, the computer-readable storage medium may include, but is not limited to, various media that can store computer programs, such as a USB flash drive, a read-only memory (ROM), a random access memory (RAM), a mobile hard disk, a magnetic disk or an optical disk.

[0119] An embodiment of the present application further provides an electronic device, including a memory and a processor, wherein a computer program is stored in the memory, and the processor is configured to run the computer program to execute the steps in any one of the above method embodiments.

[0120] In an exemplary embodiment, the electronic device may further include a transmission device and an input / output device, wherein the transmission device is connected to the processor, and the input / output device is connected to the processor.

[0121] Optionally, in this embodiment, the processor may be configured to perform the following steps through a computer program:

[0122] S1, acquiring a panoramic image of the operable area of ​​the desktop robot based on a visual sensor located at a head component of the desktop robot, and determining a position to be operated of the desktop robot according to the panoramic image, wherein the position to be operated is used to indicate a position of the desktop robot to perform a game action;

[0123] S2, determining a target rotation angle for the mechanical arm of the desktop robot to move to the position to be operated;

[0124] S3, controlling the robot arm to move to the waiting operation position according to the target rotation angle.

[0125] An embodiment of the present application further provides a computer program product, which includes a computer program. When the computer program is executed by a processor, the steps in any one of the above method embodiments are implemented.

[0126] An embodiment of the present application further provides another computer program product, including a non-volatile computer-readable storage medium, wherein the non-volatile computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps in any of the above method embodiments are implemented.

[0127] An embodiment of the present application also provides a computer program, which includes computer instructions, which are stored in a computer-readable storage medium; a processor of a computer device reads the computer instructions from the computer-readable storage medium, and the processor executes the computer instructions, so that the computer device performs the steps in any one of the above method embodiments.

[0128] Optionally, in this embodiment, the processor may be configured to perform the following steps through a computer program:

[0129] S1, acquiring a panoramic image of the operable area of ​​the desktop robot based on a visual sensor located at a head component of the desktop robot, and determining a position to be operated of the desktop robot according to the panoramic image, wherein the position to be operated is used to indicate a position of the desktop robot to perform a game action;

[0130] S2, determining a target rotation angle for the mechanical arm of the desktop robot to move to the position to be operated;

[0131] S3, controlling the robot arm to move to the waiting operation position according to the target rotation angle.

[0132] For specific examples in this embodiment, reference may be made to the examples described in the above embodiments and exemplary implementation modes, and this embodiment will not be described in detail herein.

[0133] Obviously, those skilled in the art should understand that the above modules or steps of the present application can be implemented by a general computing device, they can be concentrated on a single computing device, or distributed on a network composed of multiple computing devices, they can be implemented by a program code executable by a computing device, so that they can be stored in a storage device and executed by the computing device, and in some cases, the steps shown or described can be executed in a different order from that herein, or they can be made into individual integrated circuit modules, or multiple modules or steps therein can be made into a single integrated circuit module for implementation. Thus, the present application is not limited to any specific combination of hardware and software.

[0134] The above description is only the preferred embodiment of the present application and is not intended to limit the present application. For those skilled in the art, the present application may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the principles of the present application shall be included in the protection scope of the present application.

Claims

1. A method for controlling a robotic arm, characterized in that: include: Acquire a panoramic image of the operable area of ​​the desktop robot based on a visual sensor located at a head component of the desktop robot, and determine a position of the desktop robot to be operated according to the panoramic image, wherein the position to be operated is used to indicate a position of the desktop robot to perform a game action; Determine a target rotation angle for the mechanical arm of the desktop robot to move to the position to be operated; The robot arm is controlled to move to the position to be operated according to the target rotation angle.

2. The method according to claim 1, characterized in that Acquiring a panoramic image of an operable area of ​​the desktop robot based on a visual sensor located at a head component of the desktop robot includes: Acquire partial images respectively collected by the visual sensor at different rotation angles, wherein there is a common field of view between two adjacent partial images; Execute the stitching step: extract feature points from each partial image, and match the feature points in the Nth partial image with the feature points in the N+1th partial image; calculate the homography transformation matrix of the Nth partial image and the N+1th partial image based on the matched feature points; Performing homography transformation on the N+1th partial image according to the homography transformation matrix of the Nth partial image and the N+1th partial image, and splicing the N+1th partial image after the homography transformation with the Nth partial image, wherein N is a positive integer; The stitching step is executed in a loop until the Mth local image after the homography transformation is stitched with the M-1th local image to obtain the panoramic image, wherein the Mth local image is the last local image acquired by the visual sensor within the target period, and M is a positive integer greater than 1.

3. The method according to claim 1, characterized in that Determining a position of the desktop robot to be operated according to the panoramic image includes: According to a first feature vector of each area in the panoramic image and a second feature vector of each area in a historical panoramic image, wherein the historical panoramic image is a previous image of the panoramic image, each area corresponds to a tabletop game of a different process; Determining whether the game state in each area has changed according to the first feature vector and the second feature vector of each area; In the case where it is determined that there is a target area where the game state has changed, determining whether the desktop robot is required to perform a game operation according to the game rules of the desktop game in the target area; When it is determined that the desktop robot is required to perform a game operation, the position corresponding to the target area is determined as the position of the desktop robot to be operated.

4. The method according to claim 3, characterized in that Determining a target rotation angle of the mechanical arm of the desktop robot when it moves to the position to be operated includes: Determine a first rotation angle of the head component corresponding to the first absolute encoder when the visual sensor captures a target partial image, wherein the first absolute encoder is used to obtain the rotation angle of the head component, and the target area exists in the target partial image; The first rotation angle is determined as the target rotation angle.

5. The method according to claim 1, characterized in that: Controlling the robot arm to move to the position to be operated according to the target rotation angle includes: Determine a second rotation angle of a second absolute encoder corresponding to the robotic arm; determining whether the second rotation angle is consistent with the target rotation angle; When the second rotation angle is consistent with the target rotation angle, determining that the robot arm moves to the waiting operation position; When the second rotation angle is inconsistent with the target rotation angle, the robot arm is controlled to move to the waiting position according to the target rotation angle.

6. The method according to claim 1, characterized in that After controlling the mechanical arm to move to the position to be operated according to the target rotation angle, the method further includes: Determine the table game corresponding to the position to be operated; Determining a target position of the picking component of the robotic arm according to the rules of the tabletop game and the current state of the tabletop game; The picking component is controlled to grab the target object at the target position, and / or the picking component is controlled to move the target object to the target position, wherein the picking component is used to grasp or release the target object.

7. The method according to claim 1, characterized in that Acquiring a panoramic image of an operable area of ​​the desktop robot based on a visual sensor located at a head component of the desktop robot includes: Determine whether there are multiple rounds of tabletop games in the operable area at the same time; In the case where there are no multiple rounds of tabletop games in the operation area at the same time, determining a target operation area for the tabletop game, and acquiring an image of the target operation area of ​​the tabletop robot based on a visual sensor of a head assembly of the tabletop robot; In the case where there are multiple rounds of tabletop games simultaneously in the operating area, a panoramic image of the operable area of ​​the tabletop robot is acquired based on a visual sensor located at the head component of the tabletop robot.

8. A desktop robot, characterized in that: include: A visual sensor, used to obtain a panoramic image of the operable area of ​​the desktop robot; A driving module, used for determining a position of the desktop robot to be operated according to the panoramic image; Determine a target rotation angle for the mechanical arm of the desktop robot to move to the position to be operated; control the mechanical arm to move to the position to be operated according to the target rotation angle, wherein the position to be operated is used to indicate the position of the desktop robot to perform a game action.

9. The desktop robot according to claim 8, characterized in that: include: A head assembly and a fuselage shrapnel, wherein the rotating contact shrapnel of the head assembly contacts the fuselage shrapnel seat through elastic force.

10. An electronic device comprising a memory and a processor, characterized in that: A computer program is stored in the memory, and the processor is configured to execute the method according to any one of claims 1 to 7 through the computer program.

Images