Methods, devices, systems, electronic equipment, and storage media for picking up and putting down components.

Abstract

This invention provides a method, device, system, electronic device, and storage medium for controlling the retrieval and placement of chess pieces. The method includes: performing tilt detection based on the retrieval and placement stroke data of multiple chess positions on the chessboard and a preset robot state model to obtain the tilt parameters of the chess-playing robot; updating the corresponding state model based on the tilt parameters; determining the target height value corresponding to the current chess position to be retrieved or placed based on the updated state model; and controlling the chess-playing robot to retrieve or place the piece at the current chess position according to the target height value. By updating and optimizing the retrieval and placement stroke data obtained from daily chess playing, precise retrieval and placement of chess pieces can be achieved without affecting the user's daily use. This not only improves the operational accuracy and efficiency of the chess-playing robot but also avoids damage to the equipment, enhances the stability and durability of the chess-playing robot, and provides support for a higher level of intelligence and precision in chess-playing robots.

Description

Technical Field

[0001] This invention relates to the field of robot control technology, and in particular to a method, apparatus, system, electronic device, and storage medium for picking up and placing items. Background Technology

[0002] In the field of automation in chess games, chess-playing robots serve as an important vehicle for intelligent entertainment and competition, and their performance and accuracy directly impact user experience and competitive fairness. However, chess-playing robots still face a series of technical challenges in achieving high-precision and high-stability chess-playing actions, especially in the control of picking up and placing pieces.

[0003] Currently, the precise positioning and verticality of the robotic arm are crucial for the successful handling of chess pieces in chess-playing robots. However, unavoidable deviations occur during the production and assembly stages of chess-playing robots, causing the end effector of the robotic arm to sag. Furthermore, errors may also occur in the robot's body during production and long-term use, preventing it from maintaining an ideal vertical position and exacerbating the sag problem. This sag affects operational accuracy, making it highly susceptible to collisions with the chessboard and inaccurate piece handling during pick-up and placement. Summary of the Invention

[0004] This invention provides a method, device, system, electronic device, and storage medium for controlling the picking and placing of pieces, in order to solve the problem in the prior art where the end of the piece droops due to deviation, making it difficult to accurately control the picking and placing process and easily resulting in collisions with the chessboard or failure to pick up pieces.

[0005] This invention provides a method for controlling the picking and placing of pieces, applied to a chess-playing robot, comprising:

[0006] The robot acquires piece-picking and placing journey data for multiple chessboard positions, including the height value of the chess-playing robot when picking up or placing pieces at the corresponding chessboard positions; the piece-picking and placing journey data is collected from the historical chess-playing process of the chess-playing robot.

[0007] Based on the piece-picking and-placing travel data at each chess-playing point and a preset robot state model, tilt detection is performed to obtain the tilt parameters of the chess-playing robot. The robot state model includes the state models of the chess-playing robot under various types of problems. The state model is used to reflect the correlation between the robot parameters and the height value when picking up and placing pieces under the corresponding type of problem.

[0008] The corresponding state model is updated based on the tilt parameters, and the target height value corresponding to the current move point is determined based on the updated state model. The chess-playing robot is then controlled to pick up and place pieces at the current move point according to the target height value.

[0009] According to a piece-picking and placing control method provided by the present invention, the tilt detection is performed based on the piece-picking and placing stroke data at each playing point and a preset robot state model to obtain the tilt parameters of the chess-playing robot, including:

[0010] Based on the piece-picking and placing travel data of each chess-playing point, fuselage tilt detection is performed to obtain tilt detection results;

[0011] Based on the tilt detection results and the preset robot state model, tilt detection is performed to obtain the tilt parameters of the chess-playing robot.

[0012] According to a piece-picking and placing control method provided by the present invention, the preset robot state model includes a state model under the tilt problem of the robot body and the robotic arm. The tilt detection is performed based on the tilt detection result and the preset robot state model to obtain the tilt parameters of the chess-playing robot, including:

[0013] When the tilt detection result indicates that the body of the chess-playing robot is tilted, the piece-picking and placing travel data of each chess-playing point are grouped to obtain multiple first data groups;

[0014] Based on the pick-and-place sub-stroke data in each first data group, and the state model under the tilt problem of the body and robotic arm, the robot parameters corresponding to each first data group are determined.

[0015] Based on the robot parameters corresponding to each of the first data groups, mean filtering is performed to obtain the tilt parameters of the chess-playing robot under the tilt problem of the body and robotic arm.

[0016] According to a piece-picking and placing control method provided by the present invention, the preset robot state model includes a state model under the problem of robot arm tilting. The tilt detection, based on the tilt detection result and the preset robot state model, obtains the tilt parameters of the chess-playing robot, including:

[0017] When the tilt detection result indicates that the body of the chess-playing robot is not tilted, the piece-picking and placing travel data of each chess-playing point are grouped to obtain multiple second data groups;

[0018] Based on the pick-and-place sub-stroke data in each second data group and the state model under the robotic arm tilt problem, the robot parameters corresponding to each second data group are determined.

[0019] Based on the robot parameters corresponding to each of the second data groups, mean filtering is performed to obtain the tilt parameters of the chess-playing robot under the problem of robot arm tilt.

[0020] According to the present invention, a method for controlling the picking and placing of pieces, wherein the tilt detection of the fuselage is performed based on the piece picking and placing stroke data of each playing point to obtain the tilt detection result includes:

[0021] Determine the theoretical height value, which is the height value when the chess-playing robot picks up and places pieces at each chess position under the condition that there are no problems;

[0022] Based on the theoretical height value and the piece placement and retrieval travel data of each chess-playing point, the height difference corresponding to each chess-playing point is determined. Based on the height difference corresponding to each chess-playing point, the fuselage tilt is detected to obtain the tilt detection result.

[0023] According to the present invention, a method for controlling the picking and placing of pieces, wherein acquiring the picking and placing stroke data of multiple playing points on the chessboard includes:

[0024] Acquire initial travel data for multiple chess-playing points, the initial travel data including encoder angle and height values ​​when the chess-playing robot picks up and places pieces at the corresponding chess-playing points;

[0025] Based on the encoder angle values ​​in the initial travel data and the theoretical encoder angle values ​​of the corresponding chess move points, valid travel data is obtained by filtering from the initial travel data; the theoretical encoder angle values ​​are determined based on the coordinates of the corresponding chess move points on the chessboard.

[0026] The effective travel data of each chess position in the multiple chess positions is averaged to obtain the chess piece placement and take-up travel data of multiple chess positions.

[0027] The present invention also provides a piece-picking and placing control device for a chess-playing robot, comprising:

[0028] The acquisition unit is used to acquire piece retrieval and placement travel data for multiple chessboard positions on the chessboard. The piece retrieval and placement travel data includes the height value of the chess-playing robot when retrieving or placing pieces at the corresponding chessboard positions. The piece retrieval and placement travel data is collected from the historical chess-playing process of the chess-playing robot.

[0029] The detection unit is used to perform tilt detection based on the piece picking and placing stroke data at each chess position and a preset robot state model to obtain the tilt parameters of the chess-playing robot; the robot state model includes the state model of the chess-playing robot under various types of problems, and the state model is used to reflect the correlation between the robot parameters and the height value when picking and placing pieces under the corresponding type of problem;

[0030] The control unit is used to update the corresponding state model based on the tilt parameters, and based on the updated state model, determine the target height value corresponding to the current move point to be picked up or placed, and control the chess-playing robot to pick up or place pieces at the current move point according to the target height value.

[0031] This invention also provides a piece-picking and placing control system for a chess-playing robot, comprising a processor, a lifting motor, a lifting encoder, a robotic arm motor, a robotic arm encoder, an air pump, and an air pressure sensor. The processor acquires piece-picking and placing stroke data for multiple playing points on the chessboard. Based on the piece-picking and placing stroke data for each playing point and a preset robot state model, it performs tilt detection to obtain the tilt parameters of the chess-playing robot. Based on the tilt parameters, it updates the corresponding state model and, based on the updated state model, determines the target height value corresponding to the current playing point to be picked up or placed, controlling the chess-playing robot to pick up or place pieces at the current playing point according to the target height value.

[0032] The robot state model includes the state models of the chess-playing robot under various types of problems. The state model is used to reflect the correlation between the robot parameters and the height values ​​when picking up and placing pieces under the corresponding type of problem. The piece picking and placing travel data includes the height values ​​of the chess-playing robot when picking up and placing pieces at the corresponding chess position. The piece picking and placing travel data is collected from the historical chess-playing process of the chess-playing robot.

[0033] The processor is also used to control the lifting motor, the robotic arm motor, and the air pump to perform piece retrieval and placement at corresponding chess-playing points. The lifting motor is used to drive the piece retrieval and placement structure connected to the front end of the robotic arm of the chess-playing robot to rise and fall. The lifting encoder is used to feed back the encoder angle value of the lifting motor to the processor. The robotic arm motor is used to drive the robotic arm to rotate. The robotic arm encoder is used to feed back the encoder angle value of the robotic arm to the processor. The air pump is used to provide air pressure during piece retrieval and placement. The air pressure sensor is used to detect the air pressure value at the piece retrieval and placement structure and feed back the air pressure value to the processor so that the processor can determine the success or failure of piece retrieval and placement.

[0034] The present invention also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the pick-and-place control method as described above.

[0035] The present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the pick-and-place subcontrol method as described above.

[0036] The present invention provides a piece-picking and placing control method, device, system, electronic device, and storage medium. Based on piece-picking and placing stroke data from multiple playing points on the chessboard and a preset robot state model, tilt detection is performed to obtain the tilt parameters of the chess-playing robot. The corresponding state model is then updated accordingly. Based on the updated state model, the target height value corresponding to the current playing point to be picked up or placed is determined. The chess-playing robot is then controlled to pick up or place pieces at the current playing point according to the target height value. The robot state model includes state models of the chess-playing robot under various problem conditions, reflecting the correlation between robot parameters and the height value during piece picking and placing under the corresponding problem type. By updating and optimizing the piece-picking and placing stroke data obtained from daily chess playing, precise piece picking and placing can be achieved without affecting the user's daily use. This not only improves the operational accuracy and efficiency of the chess-playing robot but also avoids damage to the equipment, enhancing the stability and durability of the chess-playing robot and providing support for a higher level of intelligence and precision in chess-playing robots. Attached Figure Description

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

[0038] Figure 1 This is a flowchart illustrating the pick-and-place control method provided by the present invention;

[0039] Figure 2 This is a schematic diagram of the chess-playing robot provided by the present invention;

[0040] Figure 3 This is an example diagram showing the tilting state of the chess-playing robot provided by the present invention;

[0041] Figure 4 This is a schematic diagram of the state model under ideal conditions provided by the present invention;

[0042] Figure 5 This is a schematic diagram of the state model of the robotic arm tilting problem provided by the present invention;

[0043] Figure 6 This is a schematic diagram of the state model under the fuselage tilt problem provided by the present invention;

[0044] Figure 7 This is a schematic diagram of the state model of the fuselage and robotic arm tilting problem provided by the present invention;

[0045] Figure 8 This is an overall flowchart of the tilt detection results provided by the present invention;

[0046] Figure 9 This is one of the flowcharts illustrating the pick-and-place control process provided by the present invention;

[0047] Figure 10 This is a schematic diagram of the robotic arm control loop provided by the present invention;

[0048] Figure 11 This is the second flowchart illustrating the pick-and-place control process provided by the present invention;

[0049] Figure 12 This is the third flowchart illustrating the pick-and-place control process provided by the present invention;

[0050] Figure 13 This is a schematic diagram of the structure of the pick-and-place control device provided by the present invention;

[0051] Figure 14 This is a schematic diagram of the structure of the pick-and-place sub-control system provided by the present invention;

[0052] Figure 15 This is a schematic diagram of the structure of the electronic device provided by the present invention.

[0053] Figure label:

[0054] 1410: Processor; 1420: Lifting motor; 1430: Lifting encoder; 1440: Robotic arm motor; 1450: Robotic arm encoder; 1460: Air pump; 1470: Air pressure sensor. Detailed Implementation

[0055] To make the objectives, technical solutions, and advantages of this invention clearer, the technical solutions of this invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of this invention. All other embodiments obtained by those skilled in the art based on the embodiments of this invention without creative effort are within the scope of protection of this invention.

[0056] Currently, the precise positioning and verticality of the robotic arm are crucial for the successful handling of chess pieces in chess-playing robots. However, unavoidable deviations occur during the production and assembly stages of the robot, such as the clearance of the bearings in the main and auxiliary arms, and the bending deformation of the arms under stress. These factors collectively cause the end effector of the chess-playing robot's piece-picking and placing mechanism to sag during actual operation. Furthermore, errors may also occur in the robot's body during production and long-term use, preventing it from maintaining an ideal vertical position and exacerbating the end effector sag.

[0057] Furthermore, this end-cap drooping affects the operational accuracy of the chess-playing robot, especially during piece handling. It makes it difficult for the robot to accurately judge and adjust to the optimal operating height, leading to collisions with the board or inaccurate piece grabbing or placement. In short, current chess-playing robots with end-cap drooping not only struggle with precise piece handling, reducing operational efficiency and accuracy, but may also suffer damage, shortening the robot's lifespan.

[0058] To address this issue, the present invention provides a piece-picking and placing control method. This method collects piece-picking and placing stroke data from multiple points on the chessboard during daily chess games. Based on this data, and combined with a pre-analyzed and established state model reflecting the correlation between robot parameters and the height values ​​during piece picking and placing under various conditions, the method performs tilt detection on the chess-playing robot to determine its tilt parameters. The state model is then updated based on this, allowing the application of a state model that fits the current state of the chess-playing robot in subsequent games to determine the optimal operating height. This enables precise piece picking and placing, solving the problems of difficulty in accurately controlling the height during piece picking and placing due to various deviations, high difficulty in picking and placing pieces, and easy damage to the equipment, without affecting the user's daily use. This significantly improves the efficiency of piece picking and placing.

[0059] Figure 1 This is a flowchart illustrating the pick-and-place control method provided by the present invention, as shown below. Figure 1 As shown, this method is applied to a chess-playing robot, and the method includes:

[0060] Step 110: Obtain piece retrieval and placement travel data for multiple playing points on the chessboard. The piece retrieval and placement travel data includes the height value of the chess-playing robot when retrieving or placing pieces at the corresponding playing points. The piece retrieval and placement travel data is collected from the chess-playing robot's historical playing process.

[0061] Step 120: Based on the piece-picking and-placing travel data at each chess-playing point and the preset robot state model, tilt detection is performed to obtain the tilt parameters of the chess-playing robot; the robot state model includes the state model of the chess-playing robot under various types of problems, and the state model is used to reflect the correlation between the robot parameters and the height value when picking up and placing pieces under the corresponding type of problem.

[0062] Step 130: Update the corresponding state model based on the tilt parameters, and based on the updated state model, determine the target height value corresponding to the current move point to be picked up or placed, and control the chess-playing robot to pick up or place pieces at the current move point according to the target height value.

[0063] Specifically, considering that current chess-playing robots may experience deviations during production, assembly, and use, resulting in a drooping phenomenon in the piece-picking and placing structure at the end of the robotic arm, this drooping can cause the chess-playing robot to collide with the chessboard, fail to pick up pieces, or place pieces in the wrong position when picking up or placing pieces. In other words, it is difficult to achieve accurate piece picking and placing and it is easy to damage the equipment.

[0064] In view of this, in this embodiment of the invention, it is proposed to optimize the height when picking up and placing pieces, so as to achieve precise control of the height value when picking up and placing pieces. This allows the chess robot to accurately pick up and place pieces even when the end of the chess robot droops due to various reasons. This not only improves the operation accuracy and efficiency of the chess robot, but also avoids damage to the equipment, improves the stability and durability of the chess robot, and thus optimizes the user experience and chess playing experience.

[0065] It is understandable that during the update and optimization process of programs, devices, etc., it often affects the normal use of users. Even if the user is currently using the device, they will be forced to exit the process to complete the update, which will interrupt normal use and easily lead to a poor user experience. In view of this, this invention proposes to collect the data required for update and optimization during daily use, and trigger the optimization and update process when the data accumulates to a certain amount. In this way, the optimization and update can be completed "silently" without affecting the normal use of users.

[0066] Specifically, this could be during the daily operation of the chess-playing robot, i.e., during the robot's historical chess-playing process, collecting data on the movement of pieces at multiple points on the chessboard. This data represents the height value of the chess-playing robot when it picks up or places a piece at the corresponding point. This height value could be the height of the piece-picking / placing structure at the end of the robot's robotic arm, the height of its descent, or a height relative to an ideal situation. This embodiment of the invention does not impose specific limitations on this.

[0067] It should be noted that the collected move data corresponding to the moves does not need to cover the entire chessboard; a certain amount is sufficient, such as 90%, 80%, or 75% of the entire chessboard. Specific values ​​can be set according to actual circumstances and are not specifically limited here. Furthermore, the historical move process can be the move process before the current moment in the current move, or it can be the move process from previous moves. This embodiment of the invention does not specifically limit this.

[0068] After obtaining the piece-picking and placing stroke data for multiple chess-playing points that can trigger optimization updates, this embodiment of the invention can perform optimization updates to achieve precise control over the piece-picking and placing height. Specifically, tilt detection can be performed based on the collected piece-picking and placing stroke data for each chess-playing point to detect whether the chess-playing robot has any deviation. Since deviation manifests as tilt, deviation detection can also be called tilt detection. The result obtained is whether the chess-playing robot is tilted, and the tilt parameters under tilt conditions. Considering that deviations inevitably occur in the production, assembly, and use of the various components of the chess-playing robot, and that the long, narrow structure of the robotic arm is prone to deformation, this embodiment of the invention assumes that the chess-playing robot is tilted. What needs to be solved is the tilt parameters of the chess-playing robot under tilt conditions.

[0069] Specifically, this involves using the piece-picking and-placing stroke data at each move point, combined with a pre-defined robot state model that reflects the relationship between the robot's status (robot parameters) and the height values ​​during piece picking and placing under various tilting conditions, to perform tilt detection on the robot and obtain its tilt parameters. It's important to note that this approach doesn't directly input the piece-picking and placing stroke data for each move point into the model and use the model's output robot parameters as the tilt parameters to be solved. Instead, it analyzes the piece-picking and placing stroke data from multiple move points to determine the type and state of the tilting problem. Based on this, further analysis and judgment are performed using the robot state model. By combining the analyzed tilt conditions and types with the correspondence between the robot's status and height values ​​under various problems reflected in the robot state model, a comprehensive analysis is conducted to obtain the tilt parameters.

[0070] Before performing tilt detection, it was considered that the tilt caused by the deviation faced by the chess-playing robot could have various causes. Figure 2 This is a schematic diagram of the chess-playing robot provided by the present invention. Figure 3 This is an example diagram showing the tilting state of the chess-playing robot provided by the present invention, such as... Figure 2 and Figure 3 As shown, ideally, the body and robotic arm of a chess-playing robot should remain vertical. However, in actual use, it is almost impossible for a chess-playing robot to maintain an ideal state; tilting is common, including tilting of the robotic arm (both the upper and lower arms) and tilting of the body and robotic arm. To better measure tilting, this embodiment of the invention can pre-analyze various tilting problems to establish a system state model of the chess-playing robot under these conditions, i.e., a robot state model. Specifically, this involves analyzing the factors affecting the height value when picking up and placing pieces under various tilting problems, locating the corresponding robot parameters, and establishing the correspondence between these robot parameters and the height value, thereby obtaining the robot state model.

[0071] It should be noted that the robot state model in this embodiment of the invention is not a single model, but rather a collective term for multiple state models. The state model corresponding to each type of problem can be obtained by analyzing the factors affecting the height value during the picking and placing of the robot under that type of problem. In this embodiment of the invention, state models for three types of tilting problems, as well as a state model under ideal conditions, are pre-analyzed and pre-defined. Figure 4 This is a schematic diagram of the ideal state model provided by the present invention. Figure 5 This is a schematic diagram of the state model for the tilting problem of the robotic arm provided by the present invention. Figure 6 This is a schematic diagram of the state model under the fuselage tilt problem provided by the present invention. Figure 7 This is a schematic diagram of the state model of the fuselage and robotic arm tilting problem provided by the present invention, as shown below. Figure 4 As shown, in an ideal situation, i.e., when the chess-playing robot does not have a tilting problem, the height value (theoretical height value) is taken when placing the piece. It is stable and unaffected by other influencing factors; while... Figure 5 , Figure 6 and Figure 7 As shown, the height value when the chess-playing robot picks up and places pieces is [not specified] when the robot has a tilting problem. , and The accuracy of the model is affected by robot parameters (arm length, tilt angle, etc.), and different types of problems have different robot parameters, which ensures the accuracy of the model.

[0072] After this, the robot's state model can be updated based on the obtained tilt parameters. Specifically, the tilt parameters are used to update a class of state models corresponding to the tilt problem of the chess-playing robot. This can be achieved by updating the robot parameters in the state model to the obtained tilt parameters, thus enabling the unknown parameters (robot parameters) to move towards known parameters (tilt parameters). In subsequent chess games, the optimal height value for picking up and placing pieces can be calculated based on this updated state model. That is, the optimal height value for the chess-playing robot to pick up and place pieces at the current position can be determined through the updated state model. This is called the target height value. The chess-playing robot can then be controlled to pick up and place pieces according to this target height value, thus achieving precise picking up and placing of pieces.

[0073] In this embodiment of the invention, to address the problem that chess-playing robots tilt during the process of picking up and placing pieces due to deviations, making it difficult to accurately control the height of picking up and placing pieces, and easily leading to situations such as board collisions, failure to pick up pieces, and incorrect placement of pieces, the invention utilizes piece-picking and placing journey data collected from multiple points on the chessboard during daily chess games, along with a pre-established robot state model that reflects robot parameters and height values ​​during piece picking and placing under various problems. Tilt detection is performed, and the model is updated based on the detected tilt parameters of the chess-playing robot. This allows the updated model, which fits the current state of the chess-playing robot, to be applied in subsequent chess games to solve for the optimal height value, and to pick up and place pieces accordingly. This solves the aforementioned problems and achieves accurate piece picking and placing under various conditions.

[0074] The piece-picking and placing control method provided by this invention performs tilt detection based on the piece-picking and placing stroke data of multiple playing points on the chessboard and a preset robot state model to obtain the tilt parameters of the chess-playing robot, and updates the corresponding state model accordingly. Based on the updated state model, the target height value corresponding to the current playing point to be picked up or placed is determined, and the chess-playing robot is controlled to pick up or place the piece at the current playing point according to the target height value. By updating and optimizing the piece-picking and placing stroke data obtained from daily chess playing, the method can achieve precise piece picking and placing without affecting the user's daily use. This not only improves the operational accuracy and efficiency of the chess-playing robot, but also avoids damage to the equipment, enhances the stability and durability of the chess-playing robot, and provides support for a higher level of intelligence and precision in chess-playing robots.

[0075] Based on the above embodiments, the state models for the robotic arm tilt problem, the fuselage tilt problem, and the fuselage and robotic arm tilt problems can be represented by the following formulas:

[0076] The state model for the robotic arm tilt problem can be represented as follows:

[0077]

[0078] In the formula, This represents the height value of the chess-playing robot when picking up and placing pieces under the problem of robot arm tilt. That is, after the end of the robot arm (upper arm and lower arm) droops due to tilt, the height of the piece picking and placing structure at the end of the robot arm relative to the upper surface of the chessboard when picking up and placing pieces. This represents the height value of the chess-playing robot when it picks up and places pieces under ideal conditions. That is, when the chess-playing robot does not have a tilt problem, the height value of the piece-picking and placing structure at the end of the robotic arm relative to the upper surface of the chessboard when it picks up and places pieces. and These represent the tilt angles of the robotic arm's upper and lower arms relative to the horizontal plane, respectively. and These represent the lengths of the upper arm and lower arm of the robotic arm, respectively.

[0079] The state model for the fuselage tilt problem can be represented as follows:

[0080]

[0081] In the formula, This indicates the height value of the chess-playing robot when picking up and placing pieces under the problem of body tilt. That is, after the end of the robot arm droops due to body tilt, the height of the piece picking and placing structure at the end of the robot arm relative to the upper surface of the chessboard when picking up and placing pieces. Indicates the tilt angle of the fuselage; This represents the equivalent length of the coordinates of a piece on the chessboard relative to the center of the machine.

[0082] The state model for the tilting problem of the fuselage and robotic arm can be represented as follows:

[0083]

[0084] In the formula, This indicates the height value of the chess-playing robot when picking up and placing pieces under the problem of tilting of the body and robotic arm. That is, after the end of the robotic arm droops due to the tilt of the body and robotic arm, the height of the piece picking and placing structure at the end of the robotic arm relative to the upper surface of the chessboard when picking up and placing pieces.

[0085] Based on the above embodiments, step 120 includes:

[0086] Based on the piece handling data at each chess-playing point, fuselage tilt detection is performed to obtain tilt detection results;

[0087] Based on the tilt detection results and the preset robot state model, tilt detection is performed to obtain the tilt parameters of the chess-playing robot.

[0088] Specifically, the process of obtaining the tilt parameters of the chess-playing robot by performing tilt detection based on the piece-picking and placing travel data at each chess-playing point and the robot's state model includes:

[0089] Firstly, considering the potential for deviations in the production, assembly, and use of the various components of the chess-playing robot, and the ease with which the elongated structure of the robotic arm can deform, this embodiment of the invention assumes that the robotic arm of the chess-playing robot is tilted. To achieve more precise piece-picking and placing control, a more accurate assessment of the robot's tilt is required. Specifically, tilt detection can be performed based on the piece-picking and placing stroke data at each playing point to detect any deviations in the robot's body, thus obtaining the tilt detection result. In this embodiment, based on the piece-picking and placing stroke data at each playing point, data comparison is performed to determine whether the robot's body is tilted by comparing the height values ​​during piece picking and placing.

[0090] Next, tilt detection can be performed based on the tilt detection results of the robot body and the preset robot state model to obtain the tilt parameters of the chess-playing robot. That is, using the tilt detection results of the robot body as a benchmark, and based on the piece-picking and-placing stroke data at each chess-playing point, as well as the robot state model that reflects the correlation between robot parameters and the height values ​​during piece picking and placing under various tilt problems, the tilt detection of the chess-playing robot is performed to obtain its tilt parameters. Specifically, the tilt detection results of the robot body can be used as a guide to determine the state model corresponding to the tilt problem of the chess-playing robot from the robot state model. For example, the state model for the robotic arm tilt problem, the state model for the robot body and robotic arm tilt problems, etc., so that the tilt parameters of the chess-playing robot can be solved by combining the piece-picking and placing stroke data at each chess-playing point with the corresponding state model.

[0091] Based on the above embodiments, the preset robot state model includes a state model under the problem of body and robotic arm tilting;

[0092] Based on the tilt detection results and the preset robot state model, tilt detection is performed to obtain the tilt parameters of the chess-playing robot, including:

[0093] When the tilt detection results indicate that the robot body is tilted, the piece picking and placing travel data at each playing point are grouped to obtain multiple first data groups;

[0094] Based on the pick-and-place sub-stroke data in each first data group, and the state model under the tilt problem of the robot body and robotic arm, the robot parameters corresponding to each first data group are determined.

[0095] Based on the robot parameters corresponding to each first data group, mean filtering is performed to obtain the tilt parameters of the chess-playing robot under the problem of body and robotic arm tilt.

[0096] Specifically, the process of performing tilt detection based on the tilt detection results and a preset robot state model to obtain the tilt parameters of the chess-playing robot can include:

[0097] Figure 8 This is an overall flowchart of the tilt detection results provided by the present invention, as follows: Figure 8 As shown, after performing body tilt detection based on the piece pick-up and put-down stroke data of each chess position, if the tilt detection result indicates that the chess-playing robot has a tilt problem, that is, when the body is tilted, tilt detection can be performed based on the piece pick-up and put-down stroke data of each chess position and the state model corresponding to the tilt detection result, thereby obtaining the tilt parameters of the chess-playing robot.

[0098] However, considering the tilt of the robot body, the chess-playing robot faces the problem of tilting of the body and robotic arm. The state model under this tilt problem contains three unknown parameters, namely the tilt angle of the upper and lower arms of the robotic arm and the tilt angle of the body. Therefore, in this embodiment of the invention, when using the pick-up and put-down stroke data of each chess position for calculation, the pick-up and put-down stroke data can be grouped to obtain multiple first data groups. Each first data group contains a multiple of three (such as 3, 6, 9, etc.) of pick-up and put-down stroke data.

[0099] Furthermore, after obtaining multiple first data groups, in this embodiment of the invention, calculations can be performed based on the pick-and-place sub-stroke data in each first data group and the state model under the tilt problem of the robot body and robotic arm in the robot state model. Specifically, the three pick-and-place sub-stroke data in each first data group can be substituted into the state model for calculation, and the system of three identical unknown parameters (robot parameters) can be simultaneously established. , and The three equations can be solved to obtain the values ​​of the three unknown parameters, thus yielding the robot parameters corresponding to each first data set. It should be noted that when the first data set contains only three pick-and-place sub-stroke data points, it corresponds to only one set of robot parameters; however, when it contains more than three (6, 9, etc.) pick-and-place sub-stroke data points, it corresponds to multiple sets of robot parameters.

[0100] After obtaining the robot parameters corresponding to each first data group, in this embodiment of the invention, these multiple sets of robot parameters can be fused to determine the final tilt parameters of the chess-playing robot. Specifically, this can be achieved by averaging the robot parameters of each group, i.e., averaging all the solved parameters... , and Average value filtering is performed to obtain the final tilt parameters, that is, the tilt parameters of the chess-playing robot under the tilt problem of the body and robotic arm.

[0101] Furthermore, after obtaining the tilt parameters under the tilt problem of the fuselage and robotic arm, in this embodiment of the invention, the state model under the tilt problem of the fuselage and robotic arm can be updated according to these tilt parameters so that the optimal height value for picking up and placing the device can be solved based on the updated state model, and the picking up and placing of the device can be performed accordingly. Figure 9 This is one of the flowcharts illustrating the pick-and-place control process provided by the present invention, such as... Figure 9As shown, after updating the corresponding state model based on the solved tilt parameters, when it is necessary to pick up or place a piece at a certain point on the chessboard, the optimal height value for the chess-playing robot to pick up or place a piece at that point can be calculated using the updated state model based on the coordinates of that point (the current point where the piece needs to be picked up or placed). This is the target height value corresponding to that point. Then, the chess-playing robot can be controlled to pick up or place pieces according to this target height value. Here, when controlling the robotic arm of the chess-playing robot to pick up and place pieces, the control system of the robotic arm has four main control loops. Figure 10 This is a schematic diagram of the robotic arm control loop provided by the present invention, as shown below. Figure 10 As shown, the main control loops are pneumatic closed-loop control, pick-and-place piece closed-loop control, boom rotation closed-loop control, and forearm rotation closed-loop control. The combined action of all components (processor, air pump, air pressure sensor, lifting motor, lifting encoder, boom motor, boom encoder, etc.) and control loops enables the robotic arm to accurately pick up and place chess pieces through the pick-and-place piece structure at its end under the control of the control system.

[0102] Based on the above embodiments, the preset robot state model includes a state model under the problem of robot arm tilting;

[0103] Based on the tilt detection results and the preset robot state model, tilt detection is performed to obtain the tilt parameters of the chess-playing robot, including:

[0104] If the tilt detection results indicate that the robot body is not tilted, the piece picking and placing travel data at each chess position are grouped to obtain multiple second data groups;

[0105] Based on the pick-and-place sub-stroke data in each second data group and the state model under the robot arm tilt problem, the robot parameters corresponding to each second data group are determined.

[0106] Based on the robot parameters corresponding to each second data group, mean filtering is performed to obtain the tilt parameters of the chess-playing robot under the problem of robot arm tilt.

[0107] Specifically, the process of performing tilt detection based on the tilt detection results and a preset robot state model to obtain the tilt parameters of the chess-playing robot can include:

[0108] See Figure 8 It can be seen that when the tilt detection result shows that the body of the chess-playing robot is not tilted, the tilt detection can be performed based on the piece picking and placing stroke data of each chess position and the state model corresponding to the tilt detection result of the body, so as to obtain the tilt parameters of the chess-playing robot.

[0109] Considering that when the robot body is not tilted, the chess-playing robot only faces the problem of the mechanical arm tilting, and the state model under the mechanical arm tilting problem only contains two unknown parameters, namely, the tilt angle of the upper arm and the lower arm of the mechanical arm, in this embodiment of the invention, the pick-up and put-down stroke data can be grouped to obtain multiple second data groups, and each second data group can contain a multiple of two (such as 2, 4, 6, etc.) of pick-up and put-down stroke data.

[0110] After obtaining multiple second data sets, in this embodiment of the invention, the tilt parameters of the chess-playing robot can be calculated based on the pick-and-place sub-stroke data in each second data set and the state model under the robot arm tilt problem in the robot state model. Specifically, this can be achieved by substituting two pick-and-place sub-stroke data sets from each second data set into the state model for calculation, and simultaneously solving the system of equations containing the same unknown parameters (robot parameters). and The two equations can be solved to obtain the values ​​of the two unknown parameters, thus yielding the robot parameters corresponding to each second data set. It should be noted that when the second data set contains only two pick-and-place sub-stroke data points, it corresponds to only one set of robot parameters; however, when it contains two or more pick-and-place sub-stroke data points (4, 8, etc.), it corresponds to multiple sets of robot parameters.

[0111] Furthermore, after obtaining the robot parameters corresponding to each second data group, in this embodiment of the invention, these multiple sets of robot parameters can be fused. Specifically, this can be done by performing mean filtering on each set of robot parameters, that is, filtering all the solved parameters... and Average value filtering is performed to obtain the final tilt parameters, which are the tilt parameters of the chess-playing robot under the problem of robotic arm tilt.

[0112] After that, the state model of the robotic arm tilt problem can be updated according to the tilt parameters. Then, based on the updated state model, the optimal height value for picking up and placing pieces can be obtained, that is, the target height value corresponding to the current piece placement point. The robot can be controlled to pick up and place pieces according to this target height value.

[0113] Based on the above embodiments, the aircraft tilt is detected based on the piece handling travel data at each chess-playing point, and the tilt detection results are obtained, including:

[0114] Determine the theoretical height value, which is the height value when the chess-playing robot picks up and places pieces at each chess position, assuming there are no problems with the chess-playing robot;

[0115] Based on the theoretical height value and the piece placement and retrieval travel data at each chess-playing point, the height difference corresponding to each chess-playing point is determined. Based on the height difference corresponding to each chess-playing point, the fuselage tilt is detected, and the tilt detection result is obtained.

[0116] Specifically, in the above process, when performing body tilt detection based on the piece picking and placing stroke data of each chess position, the theoretical height value can be determined first. This height value refers to the height value when picking and placing pieces at chess positions on the chessboard under ideal conditions, that is, when the chess-playing robot does not have a tilt problem. This value is fixed. Next, based on the theoretical height value and the piece-picking / placing travel data at each chess-playing point, the height difference can be calculated to determine the height of the end-point piece-picking / placing structure (relative to the upper surface of the chessboard) when the chess-playing robot picks up and places pieces at each chess-playing point, and the difference between this and the theoretical height value. This difference is the height difference value corresponding to each chess-playing point. Then, the robot's tilt can be detected based on the height difference values ​​corresponding to each chess-playing point to obtain the tilt detection results. The height difference values ​​corresponding to each chess-playing point can be compared to see if the height difference values ​​of all chess-playing points are basically consistent. Specifically, a curve can be drawn, and the ratio of points on the curve to points outside the curve can be used to determine whether they are basically consistent. Alternatively, the height difference values ​​can be grouped in pairs, and each group can be compared to determine whether they are consistent. Based on the comparison results of each group, it can be determined whether they are basically consistent. If the consistency exceeds 90% or 95%, it is considered basically consistent, and if they are basically consistent, it can be determined that there is no tilt problem in the robot. Conversely, if they are not basically consistent, it can be determined that there is a tilt problem in the robot, that is, the robot is tilted.

[0117] Based on the above embodiments, step 110 includes:

[0118] Acquire initial travel data for multiple chess-playing points. The initial travel data includes the encoder angle and height values ​​when the chess-playing robot picks up and places pieces at the corresponding chess-playing points.

[0119] Based on the encoder angle values ​​in the initial travel data and the theoretical encoder angle values ​​for the corresponding chess move positions, valid travel data is obtained by filtering from the initial travel data; the theoretical encoder angle values ​​are determined based on the coordinates of the corresponding chess move positions on the chessboard.

[0120] The effective travel data of each chess position in the multiple chess positions is averaged to obtain the chess piece placement and take-up travel data of multiple chess positions.

[0121] Specifically, the process of obtaining the move data for picking up and placing pieces at multiple points on the chessboard may include the following steps:

[0122] Without knowing the tilt parameters of the chess-playing robot, the lifting motor will be controlled to descend according to the maximum distance, thereby realizing the picking and placing of pieces. Figure 11This is the second flowchart illustrating the pick-and-place control process provided by the present invention, as shown below. Figure 11 As shown, during daily chess games, when retrieving or placing a piece at a certain playing point, the lifting motor descends according to the maximum distance. During the retrieval or placement process, the air pressure value at the retrieval or placement structure fed back by the air pressure sensor determines whether the retrieval or placement is successful. The air pressure required for retrieval or placement is provided by an air pump. When the air pressure value reaches the set command value, the height value of the retrieval or placement structure at this time can be recorded as the initial travel data for that playing point, and the retrieval or placement is judged to be successful. Conversely, when the air pressure value does not reach the command value, but the lifting motor has descended the maximum distance, the retrieval or placement is judged to have failed.

[0123] Figure 12 This is the third flowchart illustrating the pick-and-place control process provided by the present invention, as shown below. Figure 12 As shown, when collecting initial travel data for multiple chess-playing points, since pieces may be retrieved and placed multiple times at the same chess-playing point during daily operations, this embodiment of the invention includes data on multiple retrievals and placements at the same chess-playing point in the collected initial travel data. In addition to recording the height value during piece retrieval and placement, the encoder angle values ​​fed back by the encoders can also be recorded, such as the upper arm encoder angle value fed back by the upper arm encoder and the lower arm encoder angle value fed back by the lower arm encoder. Based on these encoder angle values, data validity can be filtered; that is, the validity of the recorded initial travel data can be determined based on the upper arm encoder angle value, the lower arm encoder angle value, and the theoretical encoder angle value.

[0124] When the combined angle values ​​of the upper arm encoder and the lower arm encoder have a small error compared to the theoretical encoder angle value (e.g., less than 0.5 degrees), the corresponding initial travel data can be considered valid. Conversely, if the error is large, the corresponding initial travel data is considered invalid. Based on this, valid travel data can be filtered from the initial travel data of all recorded chess-playing points. The theoretical encoder angle value can be calculated based on the coordinates of the corresponding chess-playing point, specifically through inverse kinematics operations on the coordinates. The theoretical encoder angle value includes the encoder angle values ​​corresponding to both the upper arm and the lower arm.

[0125] After obtaining the valid travel data, in this embodiment of the invention, the valid travel data of each chess position can be fused to obtain the final piece-taking and placing travel data; that is, the valid travel data of each chess position can be averaged to take the average height value of the recorded multiple piece-taking and placing times as the final height value, thereby obtaining the piece-taking and placing travel data of each chess position.

[0126] The pick-and-place control device provided by the present invention is described below. The pick-and-place control device described below can be referred to in correspondence with the pick-and-place control method described above.

[0127] Figure 13 This is a schematic diagram of the structure of the pick-and-place control device provided by the present invention, as shown below. Figure 13 As shown, this device is used in a chess-playing robot, and the device includes:

[0128] The acquisition unit 1310 is used to acquire piece retrieval and placement travel data of multiple chessboard positions on the chessboard. The piece retrieval and placement travel data includes the height value of the chess-playing robot when retrieving or placing pieces at the corresponding chessboard positions. The piece retrieval and placement travel data is collected from the historical chess-playing process of the chess-playing robot.

[0129] The detection unit 1320 is used to perform tilt detection based on the piece picking and placing stroke data of each chess position and the preset robot state model to obtain the tilt parameters of the chess-playing robot; the robot state model includes the state model of the chess-playing robot under various types of problems, and the state model is used to reflect the correlation between the robot parameters and the height value when picking and placing pieces under the corresponding type of problem.

[0130] The control unit 1330 is used to update the corresponding state model based on the tilt parameters, and based on the updated state model, determine the target height value corresponding to the current move point to be picked up or placed, and control the chess-playing robot to pick up or place pieces at the current move point to be picked up or placed according to the target height value.

[0131] The piece-picking and-placing control device provided by this invention performs tilt detection based on the piece-picking and-placing stroke data of multiple playing points on the chessboard and a preset robot state model to obtain the tilt parameters of the chess-playing robot. It then updates the corresponding state model accordingly. Based on the updated state model, it determines the target height value corresponding to the current playing point to be picked up or placed, and controls the chess-playing robot to pick up or place pieces at the current playing point according to the target height value. By updating and optimizing the piece-picking and-placing stroke data obtained from daily chess playing, it can achieve precise piece picking and placing without affecting the user's daily use. This not only improves the operational accuracy and efficiency of the chess-playing robot but also avoids damage to the equipment, enhances the stability and durability of the chess-playing robot, and provides support for a higher level of intelligence and precision in chess-playing robots.

[0132] Based on the above embodiments, the detection unit 1320 is used for:

[0133] Based on the piece-picking and placing travel data of each chess-playing point, fuselage tilt detection is performed to obtain tilt detection results;

[0134] Based on the tilt detection results and the preset robot state model, tilt detection is performed to obtain the tilt parameters of the chess-playing robot.

[0135] Based on the above embodiments, the preset robot state model includes a state model under the problem of body and robotic arm tilting, and the detection unit 1320 is used for:

[0136] When the tilt detection result indicates that the body of the chess-playing robot is tilted, the piece-picking and placing travel data of each chess-playing point are grouped to obtain multiple first data groups;

[0137] Based on the pick-and-place sub-stroke data in each first data group, and the state model under the tilt problem of the body and robotic arm, the robot parameters corresponding to each first data group are determined.

[0138] Based on the robot parameters corresponding to each of the first data groups, mean filtering is performed to obtain the tilt parameters of the chess-playing robot under the tilt problem of the body and robotic arm.

[0139] Based on the above embodiments, the preset robot state model includes a state model under the robotic arm tilt problem, and the detection unit 1320 is used for:

[0140] When the tilt detection result indicates that the body of the chess-playing robot is not tilted, the piece-picking and placing travel data of each chess-playing point are grouped to obtain multiple second data groups;

[0141] Based on the pick-and-place sub-stroke data in each second data group and the state model under the robotic arm tilt problem, the robot parameters corresponding to each second data group are determined.

[0142] Based on the robot parameters corresponding to each of the second data groups, mean filtering is performed to obtain the tilt parameters of the chess-playing robot under the problem of robot arm tilt.

[0143] Based on the above embodiments, the detection unit 1320 is used for:

[0144] Determine the theoretical height value, which is the height value when the chess-playing robot picks up and places pieces at each chess position under the condition that there are no problems;

[0145] Based on the theoretical height value and the piece placement and retrieval travel data of each chess-playing point, the height difference corresponding to each chess-playing point is determined. Based on the height difference corresponding to each chess-playing point, the fuselage tilt is detected to obtain the tilt detection result.

[0146] Based on the above embodiments, the acquisition unit 1310 is used for:

[0147] Acquire initial travel data for multiple chess-playing points, the initial travel data including encoder angle and height values ​​when the chess-playing robot picks up and places pieces at the corresponding chess-playing points;

[0148] Based on the encoder angle values ​​in the initial travel data and the theoretical encoder angle values ​​of the corresponding chess move points, valid travel data is obtained by filtering from the initial travel data; the theoretical encoder angle values ​​are determined based on the coordinates of the corresponding chess move points on the chessboard.

[0149] The effective travel data of each chess position in the multiple chess positions is averaged to obtain the chess piece placement and take-up travel data of multiple chess positions.

[0150] Figure 14 This is a schematic diagram of the structure of the pick-and-place sub-control system provided by the present invention, as shown below. Figure 14 As shown, the system is applied to a chess-playing robot. The system includes a processor 1410, a lifting motor 1420, a lifting encoder 1430, a robotic arm motor 1440, a robotic arm encoder 1450, an air pump 1460, and an air pressure sensor 1470.

[0151] The processor 1410 is used to acquire piece-picking and-placing travel data for multiple playing points on the chessboard, and based on the piece-picking and-placing travel data for each playing point and a preset robot state model, to perform tilt detection and obtain the tilt parameters of the chess-playing robot; based on the tilt parameters, to update the corresponding state model, and based on the updated state model, to determine the target height value corresponding to the current playing point to be picked up or placed, and to control the chess-playing robot to pick up or place pieces at the current playing point to be picked up or placed according to the target height value;

[0152] The robot state model includes the state models of the chess-playing robot under various types of problems. The state model is used to reflect the correlation between the robot parameters and the height values ​​when picking up and placing pieces under the corresponding type of problem. The piece picking and placing travel data includes the height values ​​of the chess-playing robot when picking up and placing pieces at the corresponding chess position. The piece picking and placing travel data is collected from the historical chess-playing process of the chess-playing robot.

[0153] The processor 1410 is also used to control the lifting motor 1420, the robotic arm motor 1440, and the air pump 1460 to realize the retrieval and placement of pieces at the corresponding chess-playing points; the lifting motor 1420 is used to drive the retrieval and placement structure connected to the front end of the robotic arm of the chess-playing robot to rise and fall; the lifting encoder 1430 is used to feed back the encoder angle value of the lifting motor to the processor 1410; the robotic arm motor 1440 is used to drive the robotic arm to rotate; the robotic arm encoder 1450 is used to feed back the encoder angle value of the robotic arm to the processor 1410; the air pump 1460 is used to provide air pressure during the retrieval and placement of pieces; the air pressure sensor 1470 is used to detect the air pressure value at the retrieval and placement structure and feed back the air pressure value to the processor 1410 so that the processor 1410 can determine the success or failure of the retrieval and placement of pieces.

[0154] The piece-picking and placing control system provided by this invention performs tilt detection based on the piece-picking and placing stroke data of multiple playing points on the chessboard and a preset robot state model to obtain the tilt parameters of the chess-playing robot. The corresponding state model is then updated accordingly. Based on the updated state model, the target height value corresponding to the current playing point to be picked up or placed is determined. The chess-playing robot is then controlled to pick up or place pieces at the current playing point according to the target height value. By updating and optimizing the piece-picking and placing stroke data obtained from daily chess playing, precise piece picking and placing can be achieved without affecting the user's daily use. This not only improves the operational accuracy and efficiency of the chess-playing robot but also avoids damage to the equipment, enhances the stability and durability of the chess-playing robot, and provides support for a higher level of intelligence and precision in chess-playing robots.

[0155] Figure 15 An example is a schematic diagram of the physical structure of an electronic device, such as... Figure 15As shown, the electronic device may include: a processor 1510, a communications interface 1520, a memory 1530, and a communications bus 1540, wherein the processor 1510, the communications interface 1520, and the memory 1530 communicate with each other through the communications bus 1540. The processor 1510 can call logic instructions in the memory 1530 to execute a piece-picking and placing control method. This method is applied to a chess-playing robot and includes: acquiring piece-picking and placing journey data for multiple playing points on the chessboard, the piece-picking and placing journey data including the height value of the chess-playing robot when picking up or placing a piece at the corresponding playing point; the piece-picking and placing journey data being collected from the historical playing process of the chess-playing robot; performing tilt detection based on the piece-picking and placing journey data for each playing point and a preset robot state model to obtain the tilt parameters of the chess-playing robot; the robot state model including the state models of the chess-playing robot under various types of problems, the state models being used to reflect the correlation between the robot parameters and the height values ​​when picking up or placing pieces under the corresponding type of problem; updating the corresponding state model based on the tilt parameters, and determining the target height value corresponding to the current playing point to be picked up or placed based on the updated state model, and controlling the chess-playing robot to pick up or place a piece at the current playing point to be picked up or placed according to the target height value.

[0156] Furthermore, the logical instructions in the aforementioned memory 1530 can be implemented as software functional units and, when sold or used as independent products, can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, essentially, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0157] On the other hand, the present invention also provides a computer program product, the computer program product comprising a computer program stored on a non-transitory computer-readable storage medium, the computer program comprising program instructions, which, when executed by a computer, enable the computer to execute the piece-picking and placing control method provided by the above methods. This method is applied to a chess-playing robot, and includes: acquiring piece-picking and placing travel data for multiple playing points on the chessboard, the piece-picking and placing travel data including the height value of the chess-playing robot when picking up or placing a piece at the corresponding playing point; the piece-picking and placing travel data is collected from the historical chess-playing process of the chess-playing robot. Based on the piece-picking and-placing travel data at each chess-playing point and a preset robot state model, tilt detection is performed to obtain the tilt parameters of the chess-playing robot. The robot state model includes the state models of the chess-playing robot under various types of problems. The state model is used to reflect the correlation between the robot parameters and the height value when picking up and placing pieces under the corresponding type of problem. The corresponding state model is updated based on the tilt parameters, and based on the updated state model, the target height value corresponding to the current chess-playing point to be picked up and placed is determined. The chess-playing robot is then controlled to pick up and place pieces at the current chess-playing point according to the target height value.

[0158] In another aspect, the present invention also provides a non-transitory computer-readable storage medium storing a computer program thereon. When executed by a processor, the computer program implements the piece-picking and placing control method provided by the above-described methods. This method is applied to a chess-playing robot and includes: acquiring piece-picking and placing journey data for multiple playing points on the chessboard, the piece-picking and placing journey data including the height value of the chess-playing robot when picking up or placing a piece at the corresponding playing point; the piece-picking and placing journey data being collected from the historical playing process of the chess-playing robot; performing tilt detection based on the piece-picking and placing journey data for each playing point and a preset robot state model to obtain the tilt parameters of the chess-playing robot; the robot state model including the state models of the chess-playing robot under various types of problems, the state models being used to reflect the correlation between the robot parameters and the height values ​​when picking up or placing a piece under the corresponding type of problem; updating the corresponding state model based on the tilt parameters, and determining the target height value corresponding to the current playing point to be picked up or placed based on the updated state model, and controlling the chess-playing robot to pick up or place a piece at the current playing point to be picked up or placed according to the target height value.

[0159] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Those skilled in the art can understand and implement this without any creative effort.

[0160] Through the above description of the embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus necessary general-purpose hardware platforms, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solutions, in essence or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods described in the various embodiments or some parts of the embodiments.

[0161] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for controlling the picking and placing of a component, characterized in that, Applications in chess-playing robots include: The robot acquires piece-picking and placing journey data for multiple chessboard positions, including the height value of the chess-playing robot when picking up or placing pieces at the corresponding chessboard positions; the piece-picking and placing journey data is collected from the historical chess-playing process of the chess-playing robot. Based on the piece-picking and-placing travel data at each chess-playing point and a preset robot state model, tilt detection is performed to obtain the tilt parameters of the chess-playing robot. The robot state model includes the state models of the chess-playing robot under various types of problems. The state model is used to reflect the correlation between the robot parameters and the height value when picking up and placing pieces under the corresponding type of problem. The corresponding state model is updated based on the tilt parameters, and the target height value corresponding to the current move point is determined based on the updated state model. The chess-playing robot is then controlled to pick up and place pieces at the current move point according to the target height value.

2. The pick-and-place control method according to claim 1, characterized in that, The tilt detection is performed based on the piece-picking and placing travel data at each chess-playing point and a preset robot state model to obtain the tilt parameters of the chess-playing robot, including: Based on the piece-picking and placing travel data of each chess-playing point, fuselage tilt detection is performed to obtain tilt detection results; Based on the tilt detection results and the preset robot state model, tilt detection is performed to obtain the tilt parameters of the chess-playing robot.

3. The pick-and-place control method according to claim 2, characterized in that, The preset robot state model includes state models for the tilting of the robot body and robotic arm. Based on the tilt detection results and the preset robot state model, tilt detection is performed to obtain the tilt parameters of the chess-playing robot, including: When the tilt detection result indicates that the body of the chess-playing robot is tilted, the piece-picking and placing travel data of each chess-playing point are grouped to obtain multiple first data groups; Based on the pick-and-place sub-stroke data in each first data group, and the state model under the tilt problem of the body and robotic arm, the robot parameters corresponding to each first data group are determined. Based on the robot parameters corresponding to each of the first data groups, mean filtering is performed to obtain the tilt parameters of the chess-playing robot under the tilt problem of the body and robotic arm.

4. The pick-and-place control method according to claim 2, characterized in that, The preset robot state model includes a state model under the robotic arm tilt problem. Based on the tilt detection results and the preset robot state model, tilt detection is performed to obtain the tilt parameters of the chess-playing robot, including: When the tilt detection result indicates that the body of the chess-playing robot is not tilted, the piece-picking and placing travel data of each chess-playing point are grouped to obtain multiple second data groups; Based on the pick-and-place sub-stroke data in each second data group and the state model under the robotic arm tilt problem, the robot parameters corresponding to each second data group are determined. Based on the robot parameters corresponding to each of the second data groups, mean filtering is performed to obtain the tilt parameters of the chess-playing robot under the problem of robot arm tilt.

5. The method for controlling the pick-up and put-down of a device according to any one of claims 2 to 4, characterized in that, The aircraft tilt detection is performed based on the piece retrieval and placement travel data at each chess-playing point to obtain tilt detection results, including: Determine the theoretical height value, which is the height value when the chess-playing robot picks up and places pieces at each chess position under the condition that there are no problems; Based on the theoretical height value and the piece placement and retrieval travel data of each chess-playing point, the height difference corresponding to each chess-playing point is determined. Based on the height difference corresponding to each chess-playing point, the fuselage tilt is detected to obtain the tilt detection result.

6. The method for controlling the pick-up and put-down of a device according to any one of claims 1 to 4, characterized in that, The process of acquiring piece placement and removal data at multiple points on the chessboard includes: Acquire initial travel data for multiple chess-playing points, the initial travel data including encoder angle and height values ​​when the chess-playing robot picks up and places pieces at the corresponding chess-playing points; Based on the encoder angle values ​​in the initial travel data and the theoretical encoder angle values ​​of the corresponding chess move points, valid travel data is obtained by filtering from the initial travel data; the theoretical encoder angle values ​​are determined based on the coordinates of the corresponding chess move points on the chessboard. The effective travel data of each chess position in the multiple chess positions is averaged to obtain the chess piece placement and take-up travel data of multiple chess positions.

7. A device for controlling the picking and placing of a component, characterized in that, Applications in chess-playing robots include: The acquisition unit is used to acquire piece retrieval and placement travel data for multiple chessboard positions on the chessboard. The piece retrieval and placement travel data includes the height value of the chess-playing robot when retrieving or placing pieces at the corresponding chessboard positions. The piece retrieval and placement travel data is collected from the historical chess-playing process of the chess-playing robot. The detection unit is used to perform tilt detection based on the piece picking and placing stroke data at each chess position and a preset robot state model to obtain the tilt parameters of the chess-playing robot; the robot state model includes the state model of the chess-playing robot under various types of problems, and the state model is used to reflect the correlation between the robot parameters and the height value when picking and placing pieces under the corresponding type of problem; The control unit is used to update the corresponding state model based on the tilt parameters, and based on the updated state model, determine the target height value corresponding to the current move point to be picked up or placed, and control the chess-playing robot to pick up or place pieces at the current move point according to the target height value.

8. A pick-and-place control system, characterized in that, This system, applied to a chess-playing robot, includes a processor, a lifting motor, a lifting encoder, a robotic arm motor, a robotic arm encoder, an air pump, and an air pressure sensor. The processor acquires piece-picking and-placing stroke data for multiple chessboard positions. Based on this data and a pre-defined robot state model, it performs tilt detection to obtain the robot's tilt parameters. The processor updates the corresponding state model based on these tilt parameters and determines the target height value for the current piece-picking / placing position. It then controls the robot to pick up and place pieces at the target height value at the current piece-picking / placing position. The robot state model includes the state models of the chess-playing robot under various types of problems. The state model is used to reflect the correlation between the robot parameters and the height values ​​when picking up and placing pieces under the corresponding type of problem. The piece picking and placing travel data includes the height values ​​of the chess-playing robot when picking up and placing pieces at the corresponding chess position. The piece picking and placing travel data is collected from the historical chess-playing process of the chess-playing robot. The processor is also used to control the lifting motor, the robotic arm motor, and the air pump to perform piece retrieval and placement at corresponding chess-playing points. The lifting motor is used to drive the piece retrieval and placement structure connected to the front end of the robotic arm of the chess-playing robot to rise and fall. The lifting encoder is used to feed back the encoder angle value of the lifting motor to the processor. The robotic arm motor is used to drive the robotic arm to rotate. The robotic arm encoder is used to feed back the encoder angle value of the robotic arm to the processor. The air pump is used to provide air pressure during piece retrieval and placement. The air pressure sensor is used to detect the air pressure value at the piece retrieval and placement structure and feed back the air pressure value to the processor so that the processor can determine the success or failure of piece retrieval and placement.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the pick-and-place sub-control method as described in any one of claims 1 to 6.

10. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the pick-and-place sub-control method as described in any one of claims 1 to 6.

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