Composite robot mechanical arm motion path planning method and device and computer equipment

Abstract

The invention relates to a composite robot mechanical arm motion path planning method and device, computer equipment, a storage medium and a computer program product. The method comprises the steps of obtaining real-time chassis positioning data of a moving object, obtaining chassis positioning error data and initial moving path data of a mechanical arm of the moving object under the condition that it is detected that the real-time chassis positioning data has errors relative to preset target chassis positioning data, and determining the moving object according to the chassis positioning error data. And determining motion path compensation data, updating the initial motion path data according to the motion path compensation data to obtain target motion path data of the mechanical arm, and controlling the mechanical arm to move according to a path generated by the target motion path data. By adopting the method, the precision of path planning of the mechanical arm can be improved.

Description

Technical Field

[0001] The present application relates to the field of machine control, and in particular to a method, device, computer equipment, storage medium and computer program product for planning the motion path of a composite robot manipulator. Background Art

[0002] With the development of machine control technology, the application scope of the composite robot system composed of AGV (Automated Guided Vehicle) and robotic arm is becoming wider and wider. AGV is a mobile transportation tool that loads goods or workpieces on the vehicle manually or automatically, automatically walks to the designated location, and then unloads the goods or workpieces. It can be used in many fixed or non-fixed transportation occasions. The robotic arm installed on the AGV can carry various execution systems at the end according to the requirements of the work task to complete various application scenarios such as material handling, assembly processing, patrol inspection, etc.

[0003] In traditional technology, when using AGV composite robot system to transport goods or workpieces, the navigation and positioning function of AGV composite robot system is needed to achieve long-distance trouble-free navigation. Among them, there are many ways of navigation and positioning, such as QR code navigation, laser radar SLAM navigation, inertial navigation, etc.

[0004] However, the current navigation and positioning methods all have some positioning errors to a greater or lesser extent, which makes the movement path of the robotic arm mounted on the AGV inaccurate, resulting in position deviations when the robotic arm performs preset photo taking or grasping tasks, ultimately affecting the operating performance of the composite robot system. Summary of the invention

[0005] Based on this, it is necessary to provide a compound robot manipulator arm motion path planning method, device, computer equipment, computer readable storage medium and computer program product that can improve the accuracy of the compound robot manipulator arm motion path in order to solve the above technical problems.

[0006] In a first aspect, the present application provides a method for planning a motion path of a composite robot manipulator. The method comprises:

[0007] Obtain real-time chassis positioning data of moving objects;

[0008] When it is detected that the real-time chassis positioning data has an error with respect to the preset target chassis positioning data, chassis positioning error data and initial motion path data of the robot arm of the moving object are acquired;

[0009] Determining motion path compensation data according to the chassis positioning error data;

[0010] Update the initial motion path data according to the motion path compensation data to obtain the target motion path data of the robotic arm;

[0011] Control the robotic arm to move along the path generated by the target motion path data.

[0012] In one embodiment, the determining the motion path compensation data according to the chassis positioning error data includes:

[0013] Construct a positioning error pose transformation matrix according to the chassis positioning error data;

[0014] Obtain the motion path compensation data based on the positioning error pose transformation matrix.

[0015] In one embodiment, the chassis positioning error data includes translational error and rotational error;

[0016] The constructing a positioning error pose transformation matrix according to the chassis positioning error data includes:

[0017] Construct a translational error matrix according to the translational error;

[0018] Construct a rotational error matrix according to the rotational error;

[0019] Determine the positioning error pose transformation matrix according to the translational error matrix and the rotational error matrix.

[0020] In one embodiment, the initial motion path data includes the starting and ending pose of the robotic arm, and the updating the initial motion path data according to the motion path compensation data to obtain the target motion path data of the robotic arm includes:

[0021] Perform a spatial matrix transformation on the starting and ending pose according to the positioning error pose transformation matrix to determine the target starting and ending pose of the robotic arm;

[0022] The target motion path data includes the target starting and ending pose;

[0023] Use the target starting and ending pose as the starting position in the target motion path data.

[0024] In one embodiment, the initial motion path data includes an initial pose transformation matrix, and the motion path compensation data includes the positioning error pose transformation matrix;

[0025] The updating the initial motion path data according to the motion path compensation data to obtain the target motion path data of the robotic arm includes:

[0026] Obtain the inverse matrix of the pose transformation matrix of the positioning error;

[0027] According to the inverse matrix, perform pose compensation on the initial pose transformation matrix to obtain a target pose transformation matrix for characterizing the target motion path;

[0028] Based on the target pose transformation matrix, obtain the target motion path data.

[0029] In a second aspect, the present application also provides a device for planning the motion path of a composite robot manipulator. The device includes:

[0030] An initial information acquisition module, configured to acquire real-time chassis positioning data of a moving object;

[0031] An error acquisition module, configured to acquire chassis positioning error data and initial motion path data of the manipulator of the moving object when it is detected that the real-time chassis positioning data has an error relative to preset target chassis positioning data;

[0032] An error compensation module, configured to determine motion path compensation data according to the chassis positioning error data;

[0033] A path update module, configured to update the initial motion path data according to the motion path compensation data to obtain the target motion path data of the manipulator; control the manipulator to move along the path generated by the target motion path data.

[0034] In one embodiment, the error compensation module is further configured to construct a pose transformation matrix of the positioning error according to the chassis positioning error data; and obtain the motion path compensation data based on the pose transformation matrix of the positioning error.

[0035] In a third aspect, the present application also provides a computer device. The computer device includes a memory and a processor. The memory stores a computer program, and when the processor executes the computer program, the steps in the embodiments of the above-mentioned method for planning the motion path of a composite robot manipulator are implemented.

[0036] In a fourth aspect, the present application also provides a computer-readable storage medium. The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps in the embodiments of the above-mentioned method for planning the motion path of a composite robot manipulator are implemented.

[0037] In a fifth aspect, the present application also provides a computer program product. The computer program product includes a computer program, and when the computer program is executed by a processor, the steps in the embodiments of the above-mentioned method for planning the motion path of a composite robot manipulator are implemented.

[0038] The above-mentioned composite robot manipulator motion path planning method, device, computer device, storage medium, and computer program product obtain the real-time chassis positioning data of the moving object. When it is detected that there is an error in the real-time chassis positioning data relative to the preset target chassis positioning data, the chassis positioning error data and the initial motion path data including the starting and ending poses of the manipulator are obtained. Further, according to the chassis positioning error data, the motion path compensation data is determined, and thus the initial motion path data is updated according to the motion path compensation data, and finally the target motion path of the expected manipulator is obtained, so as to control the manipulator to move along the path generated by the target motion path data. The above solution fully considers the positioning error of the moving object, and when the positioning error is found, it can compensate and process the initial motion path data according to the motion error, update the motion path in time to adapt to the change of the chassis position, and obtain the target motion path data that meets the expectations and is more accurate, so that the manipulator can execute tasks as expected. Therefore, adopting the above solution can dynamically plan and adjust the motion path of the manipulator and improve the accuracy of the motion path of the manipulator. Description of the Drawings

[0039] Figure 1 It is an application environment diagram of the composite robot manipulator motion path planning method in an embodiment;

[0040] Figure 2 It is a schematic flowchart of the composite robot manipulator motion path planning method in an embodiment;

[0041] Figure 3 It is a schematic flowchart of the composite robot manipulator motion path planning method in another embodiment;

[0042] Figure 4 It is a schematic flowchart of the composite robot manipulator motion path planning method in yet another embodiment;

[0043] Figure 5 It is a schematic flowchart of the composite robot manipulator motion path planning method in still another embodiment;

[0044] Figure 6 It is a reference schematic diagram of the composite robot manipulator motion path planning method in an embodiment;

[0045] Figure 7 It is a schematic flowchart of the composite robot manipulator motion path planning method in still another embodiment;

[0046] Figure 8 It is a structural block diagram of the composite robot manipulator motion path planning device in an embodiment;

[0047] Figure 9Internal structure diagram of a computer device in an embodiment. Detailed implementation manners

[0048] To make the objectives, technical solutions and advantages of the present application clearer and more understandable, the present application will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0049] The composite robot manipulator motion path planning method provided by the embodiments of the present application can be applied to, for example Figure 1 the application environment shown in the figure. Among them, the moving object can be a robot, a drone, and other moving devices carrying a manipulator, etc. The moving object 102 communicates with the control terminal 104, and the data storage system can store motion path data generated when the control terminal 104 controls the motion path of the moving object. The data storage system can be integrated on the control terminal 104, or placed in the cloud or other servers. Specifically, the moving object 102 can upload real-time chassis positioning data to the control terminal 104. When the control terminal 104 detects an error in the real-time chassis positioning, it obtains the chassis positioning error data and the initial motion path data of the manipulator of the moving object 102. Further, the control terminal 104 determines motion path compensation data according to the chassis positioning error data, and updates the initial motion path data according to the motion path compensation data to obtain the target motion path data of the manipulator. Among them, the moving object 102 can be, but is not limited to, various robots, drones, etc., and the control terminal 104 can be implemented by an independent controller or a controller cluster composed of multiple controllers. It can be understood that the composite robot manipulator motion path planning method provided by the embodiments of the present application can also be applied to the controller built into the moving object body.

[0050] In one embodiment, as Figure 2 shown, a composite robot manipulator motion path planning method is provided. Taking the method applied to Figure 1 the server 104 in the figure as an example, the method includes the following steps:

[0051] S200, obtaining the real-time chassis positioning data of the moving object.

[0052] Among them, the moving object can include, but is not limited to, a robot, a drone, or other moving objects that can carry a manipulator. The real-time chassis positioning data of the moving object refers to the real-time position and attitude data of the moving object body at the current moment. Taking the moving object as a robot as an example, the real-time chassis positioning data includes the spatial position and direction of the center of the robot's own chassis. The real-time chassis positioning data can be obtained through various sensors or sensing units, or can be measured and obtained through lidar, inertial measurement units, etc.

[0053] The initial motion path data refers to the trajectory information of a moving object moving in space. For example, for a composite robot system including a robot body and a robotic arm, the initial motion path data may include the direction, distance, and speed of the robot body moving in a space coordinate system, as well as the angle and position of the robotic arm relative to the robot body. Among them, the starting end pose of the robotic arm describes the position and pose information of the end effector of the robotic arm in the starting stage. For example, the coordinates and rotation state of the end effector of the robotic arm in three-dimensional space. The initial motion path data can be pre-stored in the data storage system of the server to guide the movement of the moving object in space.

[0054] S400, when it is detected that there is an error in the real-time chassis positioning data relative to the preset target chassis positioning data, obtain the chassis positioning error data and the initial motion path data of the robotic arm of the moving object.

[0055] In the actual process of controlling a moving object, the positioning of the moving object may be inaccurate due to measurement errors of the chassis sensors of the moving object, environmental factors, or defects in its own components. For example, the robot does not accurately stop at the preset position but has a positioning error. Therefore, when it is detected that there is an error in the real-time chassis positioning data of the moving object, it is necessary to obtain the chassis positioning error data.

[0056] Exemplarily, taking the AGV composite robot system as an example, when the expected parking position of the robot is point A, but in fact, the actual parking position of the robot is point B, it indicates that there is an error in the chassis positioning data of the robot. At this time, the chassis positioning error data can be obtained through positioning devices such as sensors and gyroscopes installed at the bottom of the robot.

[0057] S600, determine the motion path compensation data according to the chassis positioning error data.

[0058] Among them, the motion path compensation data can be a set of adjustment values used to correct the initial motion path data of the moving object to cope with the chassis positioning error.

[0059] Continuing the above steps, after obtaining the chassis positioning error data, the moving object can timely feedback the chassis positioning error data to the control end. Since there is an error in the positioning at this time, it is no longer possible to control the moving object to reach the target position according to the original initial motion path data. Taking the composite robot system of an AGV plus a robotic arm as an example, the robotic arm is installed on the robot body. Therefore, the end of the robotic arm has a fixed spatial coordinate relative to the center of the robot chassis, and also has a spatial orientation relative to the direction of the robot chassis. When there is an error in the chassis positioning of the robot, the spatial pose of the end of the robotic arm will also deviate, resulting in the robotic arm being unable to perform tasks such as grasping as expected. At this time, the motion path compensation data of the moving object can be analyzed based on the chassis positioning error data, so as to compensate the initial motion path data of the moving object, enabling the moving object to move to the accurate target position. In this embodiment, the motion compensation data includes the position adjustment of the moving object and also includes the direction adjustment of the moving object. In addition, the motion compensation data can also include the adjustment of the motion speed of the moving object to enable it to perform path compensation smoothly.

[0060] S800, according to the motion path compensation data, update the initial motion path data to obtain the target motion path data of the robotic arm, and control the robotic arm to move along the path generated by the target motion path data.

[0061] Among them, the target motion path data refers to the motion path data obtained after compensating and calibrating the initial motion path data. In other words, the target motion path data is the motion path data that enables the robotic arm to perform tasks accurately as expected when the moving object has a chassis positioning error.

[0062] Continuing the above steps, after determining the motion path compensation data, compensate the motion path compensation data into the initial motion path data. The compensation process can include compensating parameters such as position coordinates, motion direction, and motion speed, and generating the target motion path data. Further, apply the target motion path data to the moving object to timely correct the chassis positioning error of the moving object, more accurately plan the motion path of the moving object, and thus control the robotic arm to move along the path generated by the target motion path data.

[0063] The above composite robot manipulator motion path planning method obtains the real-time chassis positioning data of the moving object and the initial motion path data including the starting and ending poses of the manipulator, and obtains the chassis positioning error data when detecting an error in the real-time chassis positioning data. Further, according to the chassis positioning error data, motion path compensation data is determined, and thus the initial motion path data is updated according to the motion path compensation data, and finally the target motion path of the manipulator is obtained, so as to control the manipulator to move along the path generated by the target motion path data. It can be seen that through this solution, the positioning error of the moving object can be fully considered, and the initial motion path is compensated according to the motion error to obtain the target motion path to indicate that the manipulator of the moving object can accurately reach the target position. Therefore, adopting the above solution can improve the accuracy of the manipulator motion path planning.

[0064] In one embodiment, as Figure 3 shown, S600 includes:

[0065] S620, according to the chassis positioning error data, construct a positioning error pose transformation matrix, and based on the positioning error pose transformation matrix, obtain the motion path compensation data.

[0066] Among them, the positioning error pose transformation matrix can be used to describe the pose transformation relationship caused by the chassis positioning error during the task execution of the moving object, that is, to describe the difference between the actual position and pose of the end effector of the manipulator and the expected position and pose. In this embodiment, it can be represented by a 4*4 homogeneous transformation matrix.

[0067] In the process of constructing the positioning error pose transformation matrix, the chassis positioning error data of the moving object can be analyzed first, such as the deviation in position and the deviation in angle, etc., so the constructed positioning error pose transformation matrix can represent the adjustment of the position and angle of the moving object. Further, the motion path compensation data can include the positioning error pose transformation matrix. In practical applications, the positioning error pose transformation matrix contains information on the path adjustment of the moving object, so it can help the moving object adapt to the chassis positioning error and accurately execute the task according to the correct motion path.

[0068] In this embodiment, by constructing a positioning error pose transformation matrix according to the chassis positioning error data, the difference between the actual position and pose of the end effector of the manipulator and the expected position and pose can be accurately described, the size and direction of the positioning error can be precisely quantified and represented, the manipulator positioning error can be comprehensively and accurately described, and strong support can be provided for error analysis, compensation and control, thereby improving the positioning accuracy and performance of the manipulator.

[0069] In one embodiment, the chassis positioning error data includes translational error and rotational error, asFigure 4 As shown in, S620 includes:

[0070] S622, constructing a translation error matrix according to the translation error.

[0071] The chassis positioning error data includes the translation error of the chassis of the moving object, that is, there is an error in the positioning of the chassis in space. Exemplarily, if the forward direction of the moving object is taken as the X direction, the vertical direction of the walking plane is taken as the Z direction, and the Y direction is determined by the right-hand rule, the translation error is denoted as , , , and a translation error matrix is constructed according to this translation error , and the matrix expression is as follows:

[0072]

[0073] Wherein, , and respectively represent the deviations of the moving object in the X, Y, and Z directions, and when the ground is a flat ground, . The translation error matrix represents the translation transformation of the moving object in space.

[0074] S624, constructing a rotation error matrix according to the rotation error.

[0075] In addition to the translation error, the chassis positioning error may also include a rotation error, which in this embodiment represents the rotation error around the Z axis generated when the moving object stops at the parking position, and the rotation angle is denoted as . A rotation error matrix is constructed according to the rotation error , and the matrix expression is as follows:

[0076]

[0077] Wherein, in the above matrix expression is the rotation angle in the clockwise direction. If the rotation angle is in the counterclockwise direction, then is used to replace .

[0078] In addition, if the moving object is a drone, rotation errors around the X axis and Y axis may also be generated. Exemplarily, if the rotation error is generated around the X axis, the rotation angle is denoted as , then the corresponding rotation error matrix can be expressed as:

[0079]

[0080] If the rotation error is generated around the Y axis, the rotation angle is denoted as , the corresponding rotation error matrix can be expressed as:

[0081]

[0082] Similarly, the above rotation angles and are both rotation angles in the clockwise direction. If the rotation angle is in the counterclockwise direction, then , should be used to replace , .

[0083] S626. Determine the positioning error pose transformation matrix according to the translation error matrix and the rotation error matrix.

[0084] After constructing the translation error matrix and the rotation error matrix, the translation error matrix and the rotation error matrix can be integrated to obtain the positioning error pose transformation matrix, where the positioning error pose transformation matrix can be used to describe the translation error and the rotation error of the moving object.

[0085] Following the above steps, after determining the translation error matrix and the rotation error matrix, the positioning error pose transformation matrix can be further determined. The expression of the positioning error pose transformation matrix is:

[0086]

[0087] Taking the rotation error around the Z-axis as an example, the specific expression of the positioning error pose transformation matrix is:

[0088]

[0089] The motion path compensation data includes the positioning error pose transformation matrix, that is, this matrix can be used as part of the subsequent compensation to dynamically adjust the target position and direction of the moving object to compensate for the chassis positioning error.

[0090] In this embodiment, by constructing the translation error matrix and the rotation error matrix according to the translation error and the rotation error in the positioning process of the moving object, and further integrating the translation error matrix and the rotation error matrix into the positioning error pose transformation matrix, and applying this matrix to the compensation adjustment of the initial motion path data of the moving object, real-time pose adjustment of the moving object can be achieved, thereby improving the accuracy of the motion path planning of the robotic arm.

[0091] In one embodiment, the initial motion path data includes the starting and ending poses of the robotic arm, such as Figure 5As shown, S800 includes:

[0092] S810, according to the positioning error pose transformation matrix, performs a spatial matrix transformation on the starting and ending poses to determine the target starting and ending poses of the robotic arm, and takes the target starting and ending poses as the starting positions in the target motion path data.

[0093] The target starting and ending poses are the starting and ending poses obtained after compensating and calibrating the starting and ending poses, and these target starting and ending poses can enable the robotic arm to accurately perform the grasping task as expected.

[0094] In this embodiment, it may be to perform a spatial matrix transformation on the starting and ending poses of the moving object according to the positioning error pose transformation matrix to determine the target starting and ending poses of the robotic arm.

[0095] Exemplarily, referring to the schematic Figure 6 , when there is no positioning error in the chassis positioning of the moving object, the chassis positioning coordinate is point A. Since the robotic arm of the moving object has a specific spatial position relationship relative to the moving object body, and this spatial position relationship is related to the grasping task to be performed by the robotic arm, the ending pose of the robotic arm of the moving object at this time is recorded as the starting and ending poses. However, in reality, due to the chassis positioning error of the moving object, the actual chassis positioning coordinate should be point B, and then the ending pose of the robotic arm of the moving object will also change. The ending pose of the robotic arm at this time is recorded as the target starting and ending poses. Multiply the positioning error pose transformation matrix by the chassis positioning coordinate corresponding to point A to determine the actual chassis positioning coordinate of the moving object, that is, the coordinate of point B. If the coordinate of point A is ( ), then the coordinate of point B can be expressed as:

[0096]

[0097] After determining the actual chassis positioning coordinate of the moving object, the target starting and ending poses of the robotic arm of the moving object can be determined according to the spatial position relationship between the robotic arm of the moving object and the moving object body.

[0098] It can be understood that in the actual process of controlling the moving object, taking a robot as an example, also referring to the schematic Figure 6。When there is no positioning error in the robot chassis, the robot chassis is positioned at point A, and point C is the target chassis position of the robot. At this time, the control terminal sends motion path data to the robot to instruct the robot chassis to move from A to C. Finally, the robot's manipulator can complete the corresponding tasks. However, due to the existence of chassis positioning error, the actual chassis position of the robot is point B. If the robot moves according to the original motion path data, the robot will move to the position of point D, resulting in the end pose of the robot's manipulator not being consistent with the preset one, and finally unable to execute the corresponding tasks. Through the calculation of the above steps, the coordinates of the true chassis position B of the robot can be obtained, so that the control terminal can send motion path data to the robot to instruct the robot chassis to move from B to C, enabling the robot's manipulator to complete the corresponding tasks finally.

[0099] In this embodiment, through the positioning error pose transformation matrix, the starting and ending poses of the moving object in the case of chassis positioning error are corrected to obtain the target starting and ending poses, and the above process can be dynamic and can also dynamically adapt to the chassis positioning error during the movement of the moving object, which helps the moving object to compensate for the chassis positioning error in time and improves the accuracy of the manipulator's planned path.

[0100] In one embodiment, the initial motion path data includes an initial pose transformation matrix, and the motion path compensation data includes a positioning error pose transformation matrix. As Figure 7 shown, S800 includes:

[0101] S820, obtaining the inverse matrix of the positioning error pose transformation matrix.

[0102] S840, according to the inverse matrix, performing pose compensation on the initial pose transformation matrix to obtain a target pose transformation matrix representing the target motion path. The target motion path data includes the target pose transformation matrix. Based on the target pose transformation matrix, the target motion path data is obtained.

[0103] Following the above steps, the initial motion path data includes an initial pose transformation matrix. However, due to the occurrence of chassis positioning error in the moving object, if the moving object moves according to the motion path indicated by the initial pose transformation matrix, the moving object cannot accurately reach the target position, and further the manipulator cannot execute the task as expected. Therefore, in this embodiment, the initial pose transformation matrix is compensated by the positioning error transformation matrix to determine the correct target pose transformation matrix, so as to guide the moving object to move along the accurate motion path and reach the target position.

[0104] Specifically, first obtain the inverse matrix of the positioning error pose transformation matrix. This is because at the starting and ending pose of the robotic arm of the moving object, the existence of the positioning error of the moving object's chassis causes deviation in the starting and ending pose. Therefore, it is necessary to apply the inverse matrix of the positioning error pose transformation matrix for compensation.

[0105] Exemplarily, with reference to the schematic Figure 6 , continuing with the above embodiment, the control terminal can send motion path data to the robot to instruct the robot's chassis to move from B to C, so that the robotic arm of the final robot can complete the corresponding task. Among them, the initial motion path data can include the initial pose transformation matrix , used to instruct the robot's chassis to move from point A to point C. As can be seen from the schematic Figure 6 , the spatial position relationship between point A and point C is the same as that between point B and point D. Therefore, the initial pose transformation matrix can be used to represent the spatial position transformation from point B to point D, which is expressed by the formula:

[0106]

[0107] Furthermore, the spatial transformation matrix from point D to point C can be represented by the inverse matrix of the spatial transformation matrix from point A to point B, which is expressed by the formula:

[0108]

[0109] Among them, represents the inverse matrix of the positioning error pose transformation matrix . Combining the above relational expressions, the spatial transformation relationship between point C and point B can be obtained:

[0110]

[0111] In this embodiment, through the inverse matrix of the positioning error pose transformation matrix and the initial pose transformation matrix for pose compensation, the target pose transformation matrix for characterizing the target motion path is obtained, fully considering the error generated during the positioning of the moving object, and performing pose compensation on the initial pose transformation matrix in the initial motion path data according to the error, thereby improving the accuracy of the robotic arm path planning.

[0112] To make the composite robot robotic arm motion path planning method provided by the present application clearer, the following combines a specific embodiment and the appendix Figure 7 for illustration. This specific embodiment includes the following steps:

[0113] S200, obtain the real-time chassis positioning data of the moving object.

[0114] S400. When it is detected that there is an error in the real-time chassis positioning data relative to the preset target chassis positioning data, obtain the chassis positioning error data and the initial motion path data of the manipulator of the moving object.

[0115] S622. Construct a translation error matrix according to the translation error.

[0116] S624. Construct a rotation error matrix according to the rotation error.

[0117] S626. Determine the positioning error pose transformation matrix according to the translation error matrix and the rotation error matrix.

[0118] S810. Perform a spatial matrix transformation on the starting and ending poses according to the positioning error pose transformation matrix to determine the target starting and ending poses of the manipulator, and use the target starting and ending poses as the starting positions in the target motion path data.

[0119] S820. Obtain the inverse matrix of the positioning error pose transformation matrix;

[0120] S840. Perform pose compensation on the initial pose transformation matrix according to the inverse matrix to obtain the target pose transformation matrix representing the target motion path, and based on the target pose transformation matrix, obtain the target motion path data.

[0121] It should be understood that although the steps in the flowcharts involved in the above-described embodiments are displayed in sequence according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless otherwise clearly stated in this article, the execution of these steps has no strict order limit, and these steps can be executed in other orders. Moreover, at least some of the steps in the flowcharts involved in the above-described embodiments may include multiple steps or multiple stages. These steps or stages are not necessarily executed at the same time, but can be executed at different times, and the execution order of these steps or stages is not necessarily sequential, but can be executed alternately or alternately with at least a part of other steps or steps or stages in other steps.

[0122] Based on the same inventive concept, the embodiments of the present application also provide a composite robot manipulator motion path planning device for implementing the above-mentioned composite robot manipulator motion path planning method. The implementation solutions provided by this device to solve problems are similar to the implementation solutions described in the above method. Therefore, the specific limitations in one or more of the following embodiments of the composite robot manipulator motion path planning device can refer to the limitations on the composite robot manipulator motion path planning method in the above text, and will not be repeated here.

[0123] In one embodiment, as Figure 8As shown, a motion path planning device 800 for a composite robot manipulator is provided, including: an initial information acquisition module 810, an error acquisition module 820, an error compensation module 830, and a path update module 840, where:

[0124] The initial information acquisition module 810 is configured to acquire real-time chassis positioning data of a moving object;

[0125] The error acquisition module 820 is configured to acquire chassis positioning error data and initial motion path data of the manipulator of the moving object when it detects that the real-time chassis positioning data has an error relative to the preset target chassis positioning data;

[0126] The error compensation module 830 is configured to determine motion path compensation data according to the chassis positioning error data;

[0127] The path update module 840 is configured to update the initial motion path data according to the motion path compensation data to obtain the target motion path data of the manipulator, and control the manipulator to move along the path generated by the target motion path data.

[0128] In one embodiment, the error compensation module 830 is further configured to construct a positioning error pose transformation matrix according to the chassis positioning error data, and obtain motion path compensation data based on the positioning error pose transformation matrix.

[0129] In one embodiment, the chassis positioning error data includes a translation error and a rotation error. The error compensation module 830 is further configured to construct a translation error matrix according to the translation error, construct a rotation error matrix according to the rotation error, and determine the positioning error pose transformation matrix according to the translation error matrix and the rotation error matrix.

[0130] In one embodiment, the initial motion path data includes the starting and ending pose of the manipulator. The path update module 840 is further configured to perform a spatial matrix transformation on the starting and ending pose according to the positioning error pose transformation matrix to determine the target starting and ending pose of the manipulator, and use the target starting and ending pose as the starting position in the target motion path data.

[0131] In one embodiment, the initial motion path data includes an initial pose transformation matrix, and the motion path compensation data includes a positioning error pose transformation matrix. The path update module 840 is further configured to obtain the inverse matrix of the positioning error pose transformation matrix, perform pose compensation on the initial pose transformation matrix according to the inverse matrix to obtain a target pose transformation matrix representing the target motion path, and obtain the target motion path data based on the target pose transformation matrix.

[0132] Each module in the above-mentioned composite robot manipulator motion path planning device can be implemented in whole or in part by software, hardware, or a combination thereof. Each of the above modules can be embedded in or independent of a processor in a computer device in the form of hardware, or stored in a memory in the computer device in the form of software, so that the processor can call and execute the operations corresponding to each of the above modules.

[0133] In one embodiment, a computer device is provided. The computer device can be a server, and its internal structure diagram can be as Figure 9 shown. The computer device includes a processor, a memory, an input / output interface (Input / Output, abbreviated as I / O), and a communication interface. Among them, the processor, the memory, and the input / output interface are connected through a system bus, and the communication interface is connected to the system bus through the input / output interface. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program, and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store initial motion path data, positioning error data, etc. The input / output interface of the computer device is used to exchange information between the processor and external devices. The communication interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, it implements a composite robot manipulator motion path planning method.

[0134] Those skilled in the art can understand that Figure 9 the structure shown in

[0135] is only a block diagram of some structures related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine some components, or have different component arrangements.

[0136] In one embodiment, a computer device is provided, including a memory and a processor. A computer program is stored in the memory, and when the processor executes the computer program, it implements the steps in the above-mentioned embodiments of the composite robot manipulator motion path planning method.

[0137] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by the processor, it implements the steps in the above-mentioned embodiments of the composite robot manipulator motion path planning method.

[0138] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use, and processing of relevant data need to comply with the relevant laws, regulations, and standards of relevant countries and regions.

[0139] Those of ordinary skill in the art can understand that all or part of the processes in the methods of the above embodiments can be completed by instructing relevant hardware through a computer program. The computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above methods. Among them, any reference to a memory, database, or other medium used in the embodiments provided in this application can include at least one of non-volatile and volatile memories. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetoresistive random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM), etc. The databases involved in the embodiments provided in this application can include at least one of relational databases and non-relational databases. Non-relational databases can include distributed databases based on blockchain, etc., without limitation. The processors involved in the embodiments provided in this application can be general-purpose processors, central processors, graphics processors, digital signal processors, programmable logic devices, data processing logics based on quantum computing, etc., without limitation.

[0140] The technical features of the above embodiments can be combined arbitrarily. For the sake of brevity of description, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, it should be considered to be within the scope described in this specification.

[0141] The embodiments described above merely represent several implementation manners of the present application. The description thereof is relatively specific and detailed, but it should not be construed as a limitation to the patent scope of the present application. It should be noted that for those of ordinary skill in the art, without departing from the concept of the present application, several modifications and improvements can still be made, and these all fall within the protection scope of the present application. Therefore, the protection scope of the present application shall be subject to the appended claims.

Claims

1. A method for motion path planning of a composite robot manipulator, characterized in that, The method includes: Obtaining real-time chassis positioning data of a moving object; When it is detected that there is an error in the real-time chassis positioning data relative to preset target chassis positioning data, obtaining chassis positioning error data and initial motion path data of the robotic arm of the moving object; Determining motion path compensation data according to the chassis positioning error data; Updating the initial motion path data according to the motion path compensation data to obtain target motion path data of the robotic arm; Controlling the robotic arm to move along the path generated by the target motion path data.

2. The method according to claim 1, characterized in that, The determining motion path compensation data according to the chassis positioning error data includes: Constructing a positioning error pose transformation matrix according to the chassis positioning error data; Obtaining the motion path compensation data based on the positioning error pose transformation matrix.

3. The method according to claim 2, wherein The chassis positioning error data includes translational error and rotational error; The constructing a positioning error pose transformation matrix according to the chassis positioning error data includes: Constructing a translational error matrix according to the translational error; Constructing a rotational error matrix according to the rotational error; Determining a positioning error pose transformation matrix according to the translational error matrix and the rotational error matrix.

4. The method according to claim 2 or 3, characterized in that, The initial motion path data includes the starting and ending poses of the robotic arm; The updating the initial motion path data according to the motion path compensation data to obtain target motion path data of the robotic arm includes: Performing a spatial matrix transformation on the starting and ending poses according to the positioning error pose transformation matrix to determine the target starting and ending poses of the robotic arm; Taking the target starting and ending poses as the starting positions in the target motion path data.

5. The method according to claim 1, wherein The initial motion path data includes an initial pose transformation matrix, and the motion path compensation data includes the positioning error pose transformation matrix; The updating the initial motion path data according to the motion path compensation data to obtain target motion path data of the robotic arm includes: Obtaining the inverse matrix of the positioning error pose transformation matrix; Performing pose compensation on the initial pose transformation matrix according to the inverse matrix to obtain a target pose transformation matrix for characterizing the target motion path; Obtaining the target motion path data based on the target pose transformation matrix.

6. A motion path planning device for a composite robot manipulator, characterized in that, The device includes: An initial information acquisition module, configured to obtain real-time chassis positioning data of a moving object; An error acquisition module, configured to obtain chassis positioning error data and initial motion path data of the robotic arm of the moving object when it is detected that there is an error in the real-time chassis positioning data relative to preset target chassis positioning data; An error compensation module, configured to determine motion path compensation data according to the chassis positioning error data; A path update module, configured to update the initial motion path data according to the motion path compensation data to obtain target motion path data of the robotic arm; controlling the robotic arm to move along the path generated by the target motion path data.

7. The device according to claim 6, characterized in that, The error compensation module is further configured to construct a pose transformation matrix for positioning error based on the chassis positioning error data, and obtain the motion path compensation data based on the pose transformation matrix for positioning error.

8. A computer device, comprising a memory and a processor, the memory storing a computer program, characterized in that, When the processor executes the computer program, the steps of the method according to any one of claims 1 to 5 are implemented.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 5 are implemented.

10. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 5 are implemented.

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