Methods, devices, computer equipment and media for motion control of gripperless robotic arms

Abstract

This application relates to a motion control method, apparatus, computer device, storage medium, and computer program product for a gripperless robotic arm, belonging to the field of robotics. The method includes: acquiring an initial control point sequence of the robotic arm, wherein the initial control point sequence characterizes the motion trajectory of the robotic arm when carrying an object; acquiring target interpolation parameters; smoothing the initial control point sequence according to the target interpolation parameters to obtain a target control point sequence of the robotic arm; generating pose change control information for a carrying component disposed on the robotic arm based on the target control point sequence; controlling the robotic arm to perform trajectory movement through the target control point sequence, and controlling the pose change of the carrying component to perform pose changes through the pose change control information, thereby controlling the robotic arm to carry an object. This method can improve the stability of motion control for gripperless robotic arms.

Description

Technical Field

[0001] This application relates to the field of robot control technology, and in particular to a motion control method, device, computer equipment, storage medium and computer program product for a gripperless robotic arm. Background Technology

[0002] With the rapid development of artificial intelligence, robotic arms are gradually being applied to fields such as transportation, loading and unloading, packaging, distribution processing, and delivery. As the application fields continue to expand, the types of objects that are moved and transported by robotic arms are also becoming more diverse.

[0003] Especially for the handling of certain special objects (such as objects with a high center of gravity or fragile objects), the current common method is to use grippers adapted to these special objects. However, this method often requires the development of specific adaptation programs to control the grippers and additional debugging, resulting in high costs for object handling using grippers. Therefore, how to control a robotic arm to handle objects without gripping has become an urgent problem to be solved. Furthermore, considering that objects are prone to tipping over or sliding due to centrifugal force when not gripped, the motion control stability of a gripperless robotic arm is relatively low. Summary of the Invention

[0004] Therefore, it is necessary to provide a method, apparatus, computer equipment, computer-readable storage medium, and computer program product for motion control of gripperless robotic arms that can improve the stability of motion control of gripperless robotic arms, in response to the above-mentioned technical problems.

[0005] Firstly, this application provides a motion control method for a gripperless robotic arm. The method includes:

[0006] Obtain the initial control point sequence of the robotic arm, wherein the initial control point sequence is used to characterize the motion trajectory of the robotic arm when it is carrying an object;

[0007] Obtain the target interpolation parameters, and perform smooth interpolation on the initial control point sequence based on the target interpolation parameters to obtain the target control point sequence of the robotic arm;

[0008] Based on the target control point sequence, pose change control information of the handling components set on the robotic arm is generated;

[0009] The robotic arm is controlled to perform trajectory movement by the target control point sequence, and the pose change control information is used to control the pose change of the transport component, thereby controlling the robotic arm to transport objects.

[0010] In one embodiment, the target control point sequence includes at least one target control point, and the step of generating pose change control information for the transport component disposed on the robotic arm based on the target control point sequence includes:

[0011] Based on the displacement information and displacement time between adjacent target control points, the desired acceleration information of the robotic arm is determined; the gravitational acceleration information and the desired acceleration information are preset to generate the target acceleration information of the transport component; the target acceleration information is normalized to obtain the pose change control information in the first direction.

[0012] In one embodiment, after the step of normalizing the target acceleration information to obtain pose change control information in the first direction, the method further includes:

[0013] The pose change control information in the first direction is projected onto the second direction to obtain the projection information in the second direction; the projection information in the second direction is normalized to obtain the pose change control information in the second direction; based on the pose change control information in the first direction and the pose change control information in the second direction, pose change control information in the third direction is generated.

[0014] In one embodiment, the smooth interpolation includes position interpolation and rotation interpolation. The step of smoothing the initial control point sequence according to the target interpolation parameters to obtain the target control point sequence of the robotic arm includes:

[0015] Based on the target interpolation parameters, position interpolation is performed on the initial control point sequence to obtain position interpolation results, and rotation interpolation is performed on the initial control point sequence based on the target interpolation parameters to obtain rotation interpolation results; the target control point sequence is generated based on the position interpolation results and the rotation interpolation results.

[0016] In one embodiment, before the steps of controlling the robotic arm to perform trajectory movement through the target control point sequence and controlling the transport component to perform pose changes through the pose change control information, and controlling the robotic arm to transport objects, the method further includes:

[0017] The target control point sequence is mapped to the joint space to obtain the mapping result; based on the mapping result, the motion capability of the robotic arm is detected to obtain the motion capability detection result; if the motion capability detection result is passed, the following steps are executed: controlling the robotic arm to perform trajectory movement through the target control point sequence, and controlling the transport component to perform pose change through the pose change control information, thereby controlling the robotic arm to transport objects.

[0018] In one embodiment, prior to the step of obtaining the initial control point sequence of the robotic arm, the method further includes:

[0019] Obtain a preset motion time range, and determine an interpolation range based on the motion pose constraint information of the robotic arm and the preset motion time range; select uniformly distributed target interpolation parameters within the interpolation range.

[0020] Secondly, this application also provides a motion control device for a gripperless robotic arm. The device includes:

[0021] A control point acquisition module is used to acquire an initial control point sequence of the robotic arm, wherein the initial control point sequence is used to characterize the motion trajectory of the robotic arm when it is carrying an object.

[0022] A smooth interpolation module is used to obtain target interpolation parameters and perform smooth interpolation on the initial control point sequence based on the target interpolation parameters to obtain the target control point sequence of the robotic arm.

[0023] A pose change control information generation module is used to generate pose change control information for the transport components set on the robotic arm based on the target control point sequence.

[0024] The trajectory sending module is used to control the robotic arm to perform trajectory movement through the target control point sequence, and to control the position change control information to control the position change of the transport component, thereby controlling the robotic arm to transport objects.

[0025] Thirdly, this application also provides a computer device. The computer device includes a memory and a processor, the memory storing a computer program, and the processor executing the computer program to perform the following steps:

[0026] An initial control point sequence of a robotic arm is obtained, wherein the initial control point sequence is used to characterize the motion trajectory of the robotic arm when carrying an object; a target interpolation parameter is obtained, and the initial control point sequence is smoothly interpolated according to the target interpolation parameter to obtain a target control point sequence of the robotic arm; based on the target control point sequence, pose change control information of the carrying component set on the robotic arm is generated; the robotic arm is controlled to perform trajectory movement through the target control point sequence, and the pose change control information is used to control the pose change of the carrying component, thereby controlling the robotic arm to carry an object.

[0027] Fourthly, this application also provides a computer-readable storage medium. The computer-readable storage medium stores a computer program thereon, which, when executed by a processor, performs the following steps:

[0028] An initial control point sequence of a robotic arm is obtained, wherein the initial control point sequence is used to characterize the motion trajectory of the robotic arm when carrying an object; a target interpolation parameter is obtained, and the initial control point sequence is smoothly interpolated according to the target interpolation parameter to obtain a target control point sequence of the robotic arm; based on the target control point sequence, pose change control information of the carrying component set on the robotic arm is generated; the robotic arm is controlled to perform trajectory movement through the target control point sequence, and the pose change control information is used to control the pose change of the carrying component, thereby controlling the robotic arm to carry an object.

[0029] Fifthly, this application also provides a computer program product. The computer program product includes a computer program that, when executed by a processor, performs the following steps:

[0030] An initial control point sequence of a robotic arm is obtained, wherein the initial control point sequence is used to characterize the motion trajectory of the robotic arm when carrying an object; a target interpolation parameter is obtained, and the initial control point sequence is smoothly interpolated according to the target interpolation parameter to obtain a target control point sequence of the robotic arm; based on the target control point sequence, pose change control information of the carrying component set on the robotic arm is generated; the robotic arm is controlled to perform trajectory movement through the target control point sequence, and the pose change control information is used to control the pose change of the carrying component, thereby controlling the robotic arm to carry an object.

[0031] The above-mentioned motion control methods, devices, computer equipment, storage media, and computer program products for gripperless robotic arms. Compared to traditional robotic arms that use grippers for object handling, this application employs a gripperless robotic arm method, saving on object handling costs. First, this application obtains an initial control point sequence for the robotic arm, which characterizes the motion trajectory of the robotic arm during object handling. Then, it obtains target interpolation parameters and smooths the initial control point sequence based on these parameters to obtain a target control point sequence for the robotic arm. Based on this target control point sequence, it generates pose change control information for the handling components mounted on the robotic arm, achieving adaptation between the pose change control information and the target control point sequence. This allows the robotic arm to move along a trajectory using the target control point sequence and the handling components to change pose using the pose change control information. When the robotic arm handles objects, the handling components and the robotic arm move in tandem. This tandem movement generates a reaction force that counteracts centrifugal force, preventing the object from tipping over or sliding due to centrifugal force during gripperless object handling. Therefore, it can improve the stability of motion control of gripperless robotic arms. Attached Figure Description

[0032] Figure 1 This is a schematic diagram illustrating an application scenario of a motion control method for a gripperless robotic arm in one embodiment.

[0033] Figure 2 This is a flowchart illustrating a motion control method for a gripperless robotic arm in one embodiment;

[0034] Figure 3 This is a schematic diagram of the process for generating target acceleration in one embodiment;

[0035] Figure 4 This is a schematic diagram of the process for generating pose change control information in one embodiment;

[0036] Figure 5 This is a schematic diagram of the smooth interpolation process in one embodiment;

[0037] Figure 6 This is a schematic diagram of the motion ability detection process in one embodiment;

[0038] Figure 7 This is a schematic diagram illustrating the selection process of the target interpolation parameters in one embodiment;

[0039] Figure 8 This is a structural block diagram of a motion control device for a gripperless robotic arm in one embodiment;

[0040] Figure 9 This is an internal structural diagram of a computer device in one embodiment. Detailed Implementation

[0041] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0042] With the rapid development of artificial intelligence, robotic arms are increasingly being applied in transportation, loading and unloading, packaging, distribution processing, and delivery. As these applications expand, the types of objects handled by robotic arms have also diversified. Especially for handling certain special objects, such as unassembled stacked objects like building blocks, objects with a high center of gravity like goblets, or cups containing liquids, the current common practice is to use grippers adapted to these objects. However, this method often requires developing specific adaptation programs to control the grippers and additional debugging, resulting in high costs for object handling using grippers. Therefore, how to control robotic arms to handle objects without grippers has become a pressing problem. Furthermore, considering that these objects all have a high center of gravity, the centrifugal force is also greater. Therefore, objects handled without grippers are prone to tipping over or sliding, meaning that the stability of the motion control of a gripperless robotic arm is relatively low.

[0043] The motion control method for a gripperless robotic arm provided in this disclosure can be applied to, for example... Figure 1 In the application environment shown, the robotic arm 102 of this application can be a gripperless robotic arm. The robotic arm 102 is communicatively connected to the control server 104. A transport component 106 is provided on the robotic arm 102. The transport component 106 can be integrated with the robotic arm 102 or detachable. The control server 104 can be used to control the robotic arm 102 to perform trajectory movement and to control the transport component 106 to perform pose changes, thereby controlling the robotic arm 102 to transport objects. Specifically, the control server 104 first obtains the initial control point sequence and target interpolation parameters of the robotic arm 102, and then performs smooth interpolation on the initial control point sequence according to the target interpolation parameters to obtain the target control point sequence of the robotic arm 102. Then, based on the target control point sequence, it generates pose change control information for the transport component 106. Finally, the control server 104 controls the robotic arm 102 to perform trajectory movement according to the target control point sequence and controls the transport component 106 to perform pose changes according to the pose change control information, thereby controlling the robotic arm 102 to transport objects. By achieving coordinated movement between the handling component 106 and the robotic arm 102, a reaction force that counteracts centrifugal force is generated, ensuring that the robotic arm 102 will not cause the object to tip over or slide due to centrifugal force when handling objects without gripping. This improves the stability of the motion control of the gripping-free robotic arm.

[0044] The robotic arm 102 may be, but is not limited to, an actuator capable of six degrees of freedom of motion at the end, including common gripperless industrial robots, gripperless industrial robots with external axes, and multi-joint robots (bipedal and quadrupedal) humanoid robots with actuators; the control server 104 may be implemented by a standalone server or a server cluster composed of multiple servers.

[0045] In one embodiment, such as Figure 2 As shown, a motion control method for a gripperless robotic arm is provided. In this embodiment, the method includes the following steps:

[0046] Step S202: Obtain the initial control point sequence of the robotic arm.

[0047] The initial control point sequence is used to characterize the motion trajectory of the robotic arm when carrying an object. The initial control point sequence contains at least one initial control point i, and the expression for the initial control point can be:

[0048] P i =[x i ,y i ,z i ,R xi ,R yi ,R zi ]

[0049] Where, x i Represents the x-axis distance of the initial control point i, y i Z represents the y-axis distance of the initial control point i. i R represents the z-axis distance of the initial control point i. xi R represents the rotation angle between the initial control point i and the x-axis. yi R represents the rotation angle between the initial control point i and the y-axis. zi This represents the rotation angle between the initial control point i and the z-axis. xyz can represent the position vector of the initial control point, and R can represent the rotation vector of the initial control point. That is, each initial control point can have six degrees of freedom.

[0050] As an example, the initial control point can be configured with input conditions. For instance, the start and end times of the initial control point can be set so that the transported component is in a horizontal position; that is, at the first and last initial control points, the transported component is placed horizontally. The input conditions for the initial control point can be set manually based on experience or the actual application scenario.

[0051] Specifically, the control server can first construct a task coordinate system, which can be set at the object's center of gravity or on the plane of the transported component. In response to the user's input signals regarding each initial control point, it generates the pose coordinates (P) of each initial control point. i This yields the initial control point sequence, which is then used for subsequent smooth interpolation.

[0052] Step S204: Obtain the target interpolation parameters, and perform smooth interpolation on the initial control point sequence according to the target interpolation parameters to obtain the target control point sequence of the robotic arm.

[0053] The target interpolation parameter refers to the interpolation time parameter, that is, the time range of interpolation; the target control point sequence refers to the control point sequence obtained after smoothing the initial control point sequence; the smooth interpolation can include position interpolation and rotation interpolation.

[0054] As an example, the target interpolation parameters can be generated based on the robot arm's motion pose constraints and a preset motion time range.

[0055] Specifically, the interpolation time parameters are obtained and input into the interpolation function to perform smooth interpolation on each initial control point, thereby outputting the target control point sequence of the robotic arm. The interpolation function can satisfy two conditions: first, the interpolation function is C3-smooth and continuous; second, the initial and final accelerations of the interpolation function are both zero. C3-smooth means that the function obtained by differentiating the interpolation time is bounded.

[0056] As an example, the interpolation function is a B-spline basis function. A B-spline basis function is a polynomial function that can represent sine functions, elliptical arcs, circular arcs, and other complex curves. Its advantages include high accuracy in generating curves and ease of expansion and modification of curve shapes, laying the foundation for subsequent smooth interpolation. The expression for the B-spline basis function is:

[0057]

[0058] Where u represents the target interpolation parameter, i.e., the interpolation time parameter, n represents the number of initial control points, and N i (u) represents the basis function.

[0059] Step S206: Generate pose change control information for the handling components set on the robotic arm based on the target control point sequence.

[0060] The transport component can refer to a component that carries an object for movement, such as a pallet. The transport component can be located at the end of a robotic arm, and its connection with the robotic arm can be either an integrated connection or a detachable connection. The pose change control information refers to the information on the pose change of the transport component.

[0061] As an example, the pose change control information may include pose change control information of the transport component in a first direction, pose change control information in a second direction, and pose change control information in a third direction.

[0062] As an example, with the center of the transport component as the origin, the first direction can refer to the direction perpendicular to the transport component, the second direction can refer to the horizontal direction of the transport component, and the third direction can refer to the horizontal direction of the transport component.

[0063] Specifically, based on the target control point sequence of the robotic arm, the desired acceleration information of the robotic arm when transporting objects is generated, and the target acceleration information of the transport component is calculated based on the desired acceleration. Then, based on the target acceleration information, the pose change control information of the transport component in the first direction, the pose change control information in the second direction, and the pose change control information in the third direction are calculated.

[0064] Step S208: Control the robotic arm to perform trajectory movement through the target control point sequence, and control the transport component to perform pose change through the pose change control information, thereby controlling the robotic arm to transport objects.

[0065] Specifically, after the control server obtains the target control point sequence, it also obtains the object transport trajectory that meets the user's needs. It controls the robotic arm to move along the trajectory according to the target control point sequence, and controls the position change of the transport component to adapt to the movement trajectory of the robotic arm based on the position change information of the transport component. This allows the robotic arm to transport the object. Through the coordinated movement of the robotic arm and the transport component, the transport component can match well with the object transport trajectory, whether the acceleration or the trajectory amplitude is too large, thus ensuring the smooth transport of the object and improving the stability of the motion control of the gripperless robotic arm.

[0066] In this embodiment, an initial control point sequence of the robotic arm is obtained, which characterizes the motion trajectory of the robotic arm when transporting objects. Then, target interpolation parameters are obtained, and the initial control point sequence is smoothed using these parameters to obtain the target control point sequence of the robotic arm. Based on this target control point sequence, pose change control information for the transport component mounted on the robotic arm is generated, achieving adaptation between the pose change control information and the target control point sequence. This allows the robotic arm to perform trajectory movement controlled by the target control point sequence, and the transport component to perform pose changes controlled by the pose change control information, enabling coordinated movement between the transport component and the robotic arm when transporting objects. This coordinated movement generates a reaction force that counteracts centrifugal force, preventing the object from tipping over or sliding due to centrifugal force during un-gripped object transport. Therefore, the stability of the motion control of the un-gripped robotic arm can be improved.

[0067] In one embodiment, since acceleration is a crucial parameter of motion, this embodiment calculates the target acceleration of the transport component based on the desired acceleration of the robotic arm. This facilitates the subsequent adaptation of the motion trajectories of the two components. Furthermore, considering that the robotic arm cannot maintain the balance of an object during transport due to the influence of the object's gravity, the sum of the acceleration of the transport component and the object's gravity may not equal the acceleration of the robotic arm, leading to relative motion and instability. Therefore, as... Figure 3 As shown, the step of generating pose change control information for the transport component set on the robotic arm based on the target control point sequence includes:

[0068] Step S302: Based on the displacement information and displacement time between adjacent target control points, determine the desired acceleration information of the robotic arm.

[0069] The target control point sequence includes at least one target control point; the displacement information may refer to the displacement change between adjacent target control points; the displacement time may refer to the displacement time difference between adjacent target control points; and the expected acceleration information may refer to the expected acceleration vector.

[0070] Specifically, the displacement change and displacement-time difference between adjacent target control points are obtained, and these values ​​are input into a preset desired acceleration function to calculate the desired acceleration vector of the robotic arm. In one example, the expression for the preset desired acceleration function can be:

[0071]

[0072] Among them, a linear P represents the desired acceleration vector, t represents displacement time, and P represents the displacement vector. interp (t i ) represents the displacement information of the target control point i at time t.

[0073] Step S304: Generate target acceleration information for the transport component based on preset gravitational acceleration information and the desired acceleration information.

[0074] The preset gravity acceleration information can refer to the gravity acceleration vector, which can be [0,0,-9.8], representing the gravity acceleration vector in the task coordinate system. Since the direction of gravity is downward, the direction of the gravity acceleration vector is negative. The target acceleration information can refer to the target acceleration vector of the transport component, which can be used to calculate the pose transformation control information of the transport component.

[0075] Specifically, the obtained gravitational acceleration vector and the desired acceleration vector of the robotic arm are input into a preset acceleration function to calculate the target acceleration vector of the transported component. In one example, the expression for the preset acceleration function can be:

[0076] a tray =a linear -g

[0077] Among them, a tray denoted by , g represents the target acceleration vector, and g represents the gravitational acceleration vector.

[0078] Step S306: Normalize the target acceleration information to obtain pose change control information in the first direction.

[0079] The pose change control information in the first direction refers to the pose change information of the transport component in the vertical direction.

[0080] Specifically, since the target acceleration direction of the transported component is in the same direction as the z-axis of the task coordinate system and is a normalized vector, the target acceleration vector can be input into a preset first direction function for normalization, thereby obtaining the pose change information of the transported component in the vertical direction. In one example, the expression of the preset first direction function can be:

[0081]

[0082] Among them, ||a tray || represents the norm of the target acceleration vector.

[0083] In this embodiment, considering that acceleration is a crucial parameter affecting operation, and to ensure better coordinated movement between the robotic arm and the transport component, the target acceleration of the transport component is calculated based on the desired acceleration of the robotic arm. Furthermore, considering that the robotic arm's inability to maintain object balance during transport is also due to the influence of gravity, the acceleration of the transport component plus the object's gravity may not equal the acceleration of the robotic arm, leading to relative motion and instability. Therefore, this embodiment utilizes the desired acceleration of the robotic arm and gravitational acceleration to generate the target acceleration of the transport component, and generates its pose change control information based on the target acceleration. This improves the accuracy of the pose change control information, thereby enhancing the stability of the gripperless robotic arm's motion control.

[0084] In one embodiment, such as Figure 4 As shown, after the step of normalizing the target acceleration information to obtain pose change control information in the first direction, the method further includes:

[0085] Step S402: Project the pose change control information in the first direction to the second direction to obtain the projection information in the second direction;

[0086] Step S404: Normalize the projection information in the second direction to obtain pose change control information in the second direction.

[0087] Wherein, the projection information in the second direction can refer to the projection vector of the pose change control information of the transport component in the vertical direction onto the horizontal direction; the pose change control information in the second direction can refer to the pose change information of the transport component in the horizontal transverse direction.

[0088] Specifically, the pose change control information in the first direction is input into a preset projection function to project the z-axis. normalized Perform a horizontal projection to obtain the projection vector. In one example, the expression for the preset projection function can be:

[0089] p = x interp -(x interp ·z normalized )z normalized

[0090] Where p represents the projection vector, x interp This refers to the target control point P. interp (t i The x-axis direction is x interp .

[0091] Then, the projection vector p is normalized using a preset second direction function to obtain pose change control information in the second direction. In one example, the expression for the preset second direction function can be:

[0092]

[0093] Where ||p|| represents the norm of the projection vector.

[0094] Step S406: Based on the pose change control information in the first direction and the pose change control information in the second direction, generate pose change control information in the third direction.

[0095] The third-party pose change control information can refer to the pose change information of the transport component in the horizontal and vertical directions.

[0096] Specifically, the pose change information of the transported component in the horizontal and vertical directions can be calculated using the right-hand screw rule. According to the right-hand screw rule, the pose change information of the transported component in the horizontal and vertical directions can be obtained by multiplying its pose change information in the vertical direction and its pose change information in the horizontal direction. Therefore, a preset third-direction function is constructed, and the pose change control information in the vertical direction and the horizontal direction is input into the preset third-direction function to obtain the pose change control information in the horizontal and vertical directions. In one example, the expression of the preset third-direction function can be:

[0097] y = z normalized ×x normalized

[0098] In one embodiment, since the initial control point has a position vector and a rotation vector, to ensure the accuracy of smooth interpolation, this embodiment selects spline interpolation to interpolate the position vector of the initial control point and linear interpolation to interpolate the rotation vector of the initial control point. For example... Figure 5 As shown, the step of smoothly interpolating the initial control point sequence according to the target interpolation parameters to obtain the target control point sequence of the robotic arm includes:

[0099] Step S502: Based on the target interpolation parameters, perform position interpolation on the initial control point sequence to obtain position interpolation results; and based on the target interpolation parameters, perform rotation interpolation on the initial control point sequence to obtain rotation interpolation results.

[0100] The position interpolation refers to interpolating the position vectors of each initial control point; the rotation interpolation refers to interpolating the rotation vectors of each initial control point.

[0101] Specifically, the target interpolation parameters are directly input into the B-spline basis function to perform position interpolation on each initial control point, obtaining the position interpolation result. The position interpolation result can be expressed as the interpolation result in three-dimensional coordinates, and its expression can be:

[0102]

[0103]

[0104] Where, x interp (u) represents the interpolation result of the initial control point in the x-coordinate, y interp (u) represents the interpolation result of the initial control point in the y-coordinate, z interp (u) represents the interpolation result of the initial control point in the z-coordinate.

[0105] For linear interpolation of rotations at each initial control point, the Slerp (Spherical linear interpolation) method using quaternions can be chosen. This is a linear interpolation operation of quaternions, primarily used for smooth interpolation between two quaternions representing rotations. A quaternion consists of four parts representing rotations around an axis. Compared to Euler angles, quaternions do not have gimbal lock and can easily perform incremental rotations around the axis of rotation, with less computational overhead. In one example, the quaternion expression for each initial control point can be Q. i =[q xi ,q yi ,q zi ,q wi ], where q xi q yi q zi These represent the initial control point i on the x-axis, y-axis, and z-axis, respectively, and q wi This represents the rotation angle of the initial control point i.

[0106] In one example, the expression for the Slerp interpolation function can be:

[0107]

[0108] Where θ is the included angle, defined as θ = cos -1 (Q a ·Q b ), where Q a and Q b Let Q represent the quaternion representation of any two initial control points respectively. interp (u) represents the quaternion obtained by Slerp interpolation.

[0109] Step S504: Generate the target control point sequence based on the position interpolation result and the rotation interpolation result.

[0110] Specifically, after obtaining the position interpolation results and the rotation interpolation results, the position interpolation results and the rotation interpolation results are combined to obtain the target control point sequence. The expression for the target control point sequence can be:

[0111] P interp (u)=[x interp (u),y interp (u),z interp (u),R xinterp (u),R yinterp (u),R zinterp (u)]

[0112] In this embodiment, considering that the initial control points have both position and rotation vectors, to ensure the accuracy of smooth interpolation, spline interpolation (B-spline basis function) is used to interpolate the position vectors of each initial control point, yielding position interpolation results. Linear interpolation (quaternion Slerp interpolation) is used to interpolate the selected vectors of each initial control point, yielding rotation interpolation results. B-spline basis function is characterized by accuracy and stability, and can effectively interpolate multiple position points, thereby reducing computational load. It also makes the curve shape as smooth as possible, eliminating jitter. Quaternion Slerp interpolation provides smooth interpolation in rotational space. The combination of these two methods significantly improves interpolation accuracy, resulting in a smoother motion trajectory formed by the interpolated target control point sequence, thus enhancing the stability of the gripperless robotic arm's motion control.

[0113] In one embodiment, before controlling the robotic arm to transport objects, to ensure accurate movement of the robotic arm, motion capability testing can be performed to determine whether the robotic arm possesses the motion capabilities set by the user. For example... Figure 6 As shown, before the steps of controlling the robotic arm to perform trajectory movement through the target control point sequence and controlling the transport component to perform pose changes through the pose change control information, and controlling the robotic arm to transport objects, the method further includes:

[0114] Step S602: Map the target control point sequence to the joint space to obtain the mapping result.

[0115] The joint space refers to the space composed of all joint vectors of the robotic arm. Since the above series of operations are performed in Cartesian space, i.e., the task coordinate system, the robotic arm's motion capability can be mapped to the joint space for testing in order to better verify its motion capability. The joint space and Cartesian space are mutually convertible.

[0116] Specifically, the target control point P can be... interp (t i The pose change control information in the first direction, the second direction, and the third direction is concatenated with the pose change control information in the third direction to form a new homogeneous transformation matrix. The matrix expression can be:

[0117]

[0118] Here, the homogeneous transformation matrix represents the corrected t iThe pose of the target control point at any given time, which is also the pose of the robotic arm, is used to generate new Cartesian space control points using the homogeneous transformation matrix. The new Cartesian space control points are then inversely transformed to convert the control points from Cartesian space to joint space. The resulting mapping can be used to characterize whether the target control point sequence has been successfully converted from Cartesian space to joint space.

[0119] In one example, the inverse transformation of the joint space can be achieved by calculating the Jacobian matrix of the target control sequence.

[0120] Step S604: Based on the mapping result, perform motion capability detection on the robotic arm to obtain motion capability detection results.

[0121] The motion capability detection can include reduced motion capability detection, following motion capability detection, and singular motion capability detection. Reduced motion capability detection refers to whether reduced motion is triggered at the joint position boundary. Following motion capability detection refers to whether the speed and acceleration of the robotic arm joint are exceeded. Singular motion capability detection refers to whether the movement occurs at a singular boundary, causing the robotic arm to lose acceleration capability in a specific direction. The motion capability detection results can include reduced motion capability detection results, following motion capability detection results, and singular motion capability detection results.

[0122] Specifically, if the target control point sequence is successfully mapped from Cartesian space to joint space, a new joint control point sequence is obtained. The new joint control point sequence includes at least one joint control point, and each joint control point corresponds to a joint position. Reduced mobility testing refers to checking the new joint position for each joint j. Is it close to the joint position boundary? or If so, the joint is determined to have triggered a reduction motion. In one example, the test equation for the reduction motion capability detection can be expressed as:

[0123]

[0124] Following motion capability detection refers to calculating the new joint velocity for each joint j. and acceleration and link it to the speed limit and acceleration limit The comparison is performed, and if the limits are exceeded, it indicates that the speed and acceleration exceed the following capability. In one example, the test equation for the following motion capability detection can be expressed as:

[0125]

[0126] Singularity capability detection involves checking whether the singularity value of each joint j is close to zero. A small singularity value indicates the presence of a singular boundary near that position, potentially leading to a loss of acceleration capability in a specific direction. In one example, the test equation for singularity capability detection can be expressed as:

[0127]

[0128] in It is the new Jacobian matrix of the target control sequence, and ∩ represents the limit value.

[0129] Step S606: If the motion capability detection result is passed, then the following steps are executed: control the robotic arm to perform trajectory movement through the target control point sequence, and control the transport component to perform pose change through the pose change control information, thereby controlling the robotic arm to transport objects.

[0130] Specifically, if the reduction motion capability detection result is that each joint does not trigger reduction motion at the joint position boundary, the following motion capability detection result is that the new joint velocity and acceleration of each joint do not exceed the velocity limit and acceleration limit, and the singular motion capability detection result is that the robotic arm does not lose the acceleration capability in a specific direction, it means that the robotic arm's motion capability meets the user's requirements. The control server then sends the target control point sequence and pose change control information to the joint servo interface so that the joint servo interface can drive the robotic arm to carry out object handling.

[0131] In this embodiment, before controlling the robotic arm to transport objects, the target control point sequence of the robotic arm is converted from Cartesian space to joint space for motion capability detection, thereby ensuring that the motion capability of the robotic arm meets the user's requirements.

[0132] In one embodiment, to improve the accuracy of smooth interpolation, the target interpolation parameters are optimized, such as... Figure 7 As shown, prior to the step of obtaining the initial control point sequence of the robotic arm, the method further includes:

[0133] Step S702: Obtain the preset motion time range, and determine the interpolation range based on the motion pose constraint information of the robotic arm and the preset motion time range.

[0134] Step S704: Select a uniformly distributed target interpolation parameter within the interpolation range.

[0135] The preset motion time range can refer to the time range of uniform interpolation; the motion pose constraint information can refer to the velocity constraint conditions when the robotic arm is handling an object. The velocity constraint conditions can refer to the mapping relationship between time and velocity satisfying the jerk-minimizing law. The meaning of the jerk-minimizing law is to solve the coefficients of each trajectory segment to minimize the total time, while also satisfying the velocity constraint conditions. The velocity constraint conditions can be that the velocity and acceleration at the start and end times are zero; the interpolation range refers to the range of values ​​for the target interpolation parameters.

[0136] Specifically, the coefficients of the velocity constraint are solved, and then substituted into the interpolation polynomial constructed based on the uniform interpolation time range to obtain the interpolation range. Within this range, the target interpolation parameters are selected based on a uniform distribution. In one example, the expression for the interpolation polynomial can be:

[0137] u(t) = a0 + a1t + a2t 2 +a3t 3 +a4t 4 +a5t 5

[0138] Where t is the time range of uniform interpolation, i.e. the preset motion time range, t∈[0,1], and a is the coefficient of the velocity constraint condition.

[0139] The expression for the velocity constraint can be:

[0140] u(0)=a0=0

[0141] u(1)=a0+a1+a2+a3+a4+a5=1

[0142] u ′ (0)=a1=0

[0143] u ′ (1)=a1+2a2+3a3+4a4+5a5=0

[0144] u″(0)=2a2=0

[0145] u″(1)=2a2+6a3+12a4+20a5=0

[0146] By solving the above constraints, the values ​​of coefficients a0, a1, a2, a3, a4, and a5 can be obtained. Substituting these coefficient values ​​into the interpolation polynomial yields the range of values ​​for the target interpolation parameters.

[0147] In this embodiment, by imposing a speed constraint on the time range of uniform interpolation, the smoothness of the obtained target interpolation parameters is ensured, thereby improving the smoothness of subsequent interpolation based on the target interpolation parameters, and thus improving the stability of motion control of the gripperless robotic arm.

[0148] In one embodiment, the robotic arm can be a gripperless industrial robot, the object can be a wine glass, and the handling component can be a flange disposed at the end of the axis joint of the gripperless industrial robot. Specifically, a preset motion time range of the gripperless industrial robot is first obtained. Based on the motion pose constraint information of the gripperless industrial robot and the preset motion time range, an interpolation range is determined. Within the interpolation range, uniformly distributed target interpolation parameters are selected.

[0149] Next, an initial control point sequence of the gripperless industrial robot is obtained, wherein the initial control point sequence is used to characterize the motion trajectory of the gripperless industrial robot when carrying a stemmed glass; target interpolation parameters are obtained, and position interpolation and rotation interpolation are performed on the initial control point sequence according to the target interpolation parameters to obtain the target control point sequence of the gripperless industrial robot; pose change control information of the flange is generated according to the target control point sequence; the gripperless industrial robot is controlled to perform trajectory movement through the target control point sequence, and the pose change control information is used to control the pose change of the flange, thereby controlling the gripperless industrial robot to carry the stemmed glass.

[0150] As an example, based on the displacement information and displacement time between adjacent target control points, the desired acceleration information of the gripperless industrial robot is determined; according to the preset gravitational acceleration information and the desired acceleration information, the target acceleration information of the flange is generated; the target acceleration information is normalized to obtain pose change control information in a first direction; the pose change control information in the first direction is projected onto a second direction to obtain projection information in the second direction; the projection information in the second direction is normalized to obtain pose change control information in the second direction; based on the pose change control information in the first direction and the pose change control information in the second direction, pose change control information in a third direction is generated.

[0151] As an example, before controlling the gripperless industrial robot to perform trajectory movement via the target control point sequence and controlling the flange to perform pose changes via the pose change control information to control the gripperless industrial robot to transport a goblet, the target control point sequence is mapped to the joint space of the gripperless industrial robot to obtain a mapping result; based on the mapping result, the motion capability of the gripperless industrial robot is detected to obtain a motion capability detection result; if the motion capability detection result is passed, then the following steps are executed: controlling the robotic arm to perform trajectory movement via the target control point sequence and controlling the transport component to perform pose changes via the pose change control information to control the robotic arm to transport an object.

[0152] By adapting the target point sequence of the gripperless industrial robot to the pose change control information of the flange, the robot and flange can move in tandem when the robot is controlled to perform trajectory motion via the target control point sequence and when the flange is controlled to perform pose changes via the pose change control information. This coordinated movement generates a reaction force that counteracts centrifugal force, preventing the object from tipping over or sliding due to centrifugal force during object handling. Therefore, the stability of the motion control of the gripperless industrial robot can be improved.

[0153] It should be understood that although the steps in the flowcharts of the embodiments described above are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowcharts of the embodiments described above may include multiple steps or multiple stages. These steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these steps or stages is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the steps or stages of other steps.

[0154] Based on the same inventive concept, this application also provides a gripperless robotic arm motion control device for implementing the aforementioned gripperless robotic arm motion control method. The solution provided by this device is similar to the solution described in the above method; therefore, the specific limitations in one or more gripperless robotic arm motion control device embodiments provided below can be found in the limitations of the gripperless robotic arm motion control method described above, and will not be repeated here.

[0155] In one embodiment, such as Figure 8 As shown, a motion control device for a gripperless robotic arm is provided, comprising: a control point acquisition module 802, a smooth interpolation module 804, a pose change control information generation module 806, and a trajectory transmission module 808, wherein:

[0156] The control point acquisition module 802 is used to acquire the initial control point sequence of the robotic arm, wherein the initial control point sequence is used to characterize the motion trajectory of the robotic arm when it is carrying an object.

[0157] The smooth interpolation module 804 is used to obtain target interpolation parameters and perform smooth interpolation on the initial control point sequence according to the target interpolation parameters to obtain the target control point sequence of the robotic arm.

[0158] The pose change control information generation module 806 is used to generate pose change control information of the transport component set on the robotic arm according to the target control point sequence.

[0159] The trajectory sending module 808 is used to control the robotic arm to perform trajectory movement through the target control point sequence, and to control the transport component to perform pose change through the pose change control information, thereby controlling the robotic arm to transport objects.

[0160] In one embodiment, the pose change control information generation module 806 is further configured to:

[0161] Based on the displacement information and displacement time between adjacent target control points, the desired acceleration information of the robotic arm is determined; according to the preset gravitational acceleration information and the desired acceleration information, the target acceleration information of the transport component is generated; the target acceleration information is normalized to obtain the pose change control information in the first direction.

[0162] In one embodiment, the pose change control information generation module 806 is further configured to:

[0163] The pose change control information in the first direction is projected onto the second direction to obtain the projection information in the second direction; the projection information in the second direction is normalized to obtain the pose change control information in the second direction; based on the pose change control information in the first direction and the pose change control information in the second direction, pose change control information in the third direction is generated.

[0164] In one embodiment, the smooth interpolation module 804 is further configured to:

[0165] Based on the target interpolation parameters, position interpolation is performed on the initial control point sequence to obtain position interpolation results, and rotation interpolation is performed on the initial control point sequence based on the target interpolation parameters to obtain rotation interpolation results; the target control point sequence is generated based on the position interpolation results and the rotation interpolation results.

[0166] In one embodiment, prior to the trajectory sending module 808, the following is also included:

[0167] The target control point sequence is mapped to the joint space to obtain the mapping result; based on the mapping result, the motion capability of the robotic arm is detected to obtain the motion capability detection result; if the motion capability detection result is passed, the following steps are executed: controlling the robotic arm to perform trajectory movement through the target control point sequence, and controlling the transport component to perform pose change through the pose change control information, thereby controlling the robotic arm to transport objects.

[0168] In one embodiment, prior to the control point acquisition module 802, the following is also included:

[0169] Obtain a preset motion time range, and determine an interpolation range based on the motion pose constraint information of the robotic arm and the preset motion time range; select uniformly distributed target interpolation parameters within the interpolation range.

[0170] Each module in the aforementioned gripperless robotic arm motion control device can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in or independent of the processor in a computer device, or stored in the computer device's memory as software, so that the processor can call and execute the operations corresponding to each module.

[0171] In one embodiment, a computer device is provided, which may be a server, and its internal structure diagram may be as follows: Figure 9 As shown, the computer device includes a processor, memory, and a network interface connected via a system bus. The processor provides computing and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system, computer programs, and a database. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage media. The database stores item recommendation data. The network interface communicates with external terminals via a network connection. When the computer program is executed by the processor, it implements a motion control method for a gripperless robotic arm.

[0172] Those skilled in the art will understand that Figure 9The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0173] In one embodiment, a computer device is provided, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to perform the following steps:

[0174] An initial control point sequence of a robotic arm is obtained, wherein the initial control point sequence is used to characterize the motion trajectory of the robotic arm when carrying an object; a target interpolation parameter is obtained, and the initial control point sequence is smoothly interpolated according to the target interpolation parameter to obtain a target control point sequence of the robotic arm; based on the target control point sequence, pose change control information of the carrying component set on the robotic arm is generated; the robotic arm is controlled to perform trajectory movement through the target control point sequence, and the pose change control information is used to control the pose change of the carrying component, thereby controlling the robotic arm to carry an object.

[0175] In one embodiment, the processor, when executing a computer program, also performs the following steps:

[0176] Based on the displacement information and displacement time between adjacent target control points, the desired acceleration information of the robotic arm is determined; according to the preset gravitational acceleration information and the desired acceleration information, the target acceleration information of the transport component is generated; the target acceleration information is normalized to obtain the pose change control information in the first direction.

[0177] In one embodiment, the processor, when executing a computer program, also performs the following steps:

[0178] The pose change control information in the first direction is projected onto the second direction to obtain the projection information in the second direction; the projection information in the second direction is normalized to obtain the pose change control information in the second direction; based on the pose change control information in the first direction and the pose change control information in the second direction, pose change control information in the third direction is generated.

[0179] In one embodiment, the processor, when executing a computer program, also performs the following steps:

[0180] Based on the target interpolation parameters, position interpolation is performed on the initial control point sequence to obtain position interpolation results, and rotation interpolation is performed on the initial control point sequence based on the target interpolation parameters to obtain rotation interpolation results; the target control point sequence is generated based on the position interpolation results and the rotation interpolation results.

[0181] In one embodiment, the processor, when executing a computer program, also performs the following steps:

[0182] The target control point sequence is mapped to the joint space to obtain the mapping result; based on the mapping result, the motion capability of the robotic arm is detected to obtain the motion capability detection result; if the motion capability detection result is passed, the following steps are executed: controlling the robotic arm to perform trajectory movement through the target control point sequence, and controlling the transport component to perform pose change through the pose change control information, thereby controlling the robotic arm to transport objects.

[0183] In one embodiment, the processor, when executing a computer program, also performs the following steps:

[0184] Obtain a preset motion time range, and determine an interpolation range based on the motion pose constraint information of the robotic arm and the preset motion time range; select uniformly distributed target interpolation parameters within the interpolation range.

[0185] In one embodiment, a computer-readable storage medium is provided having a computer program stored thereon, the computer program performing the following steps when executed by a processor:

[0186] An initial control point sequence of a robotic arm is obtained, wherein the initial control point sequence is used to characterize the motion trajectory of the robotic arm when carrying an object; a target interpolation parameter is obtained, and the initial control point sequence is smoothly interpolated according to the target interpolation parameter to obtain a target control point sequence of the robotic arm; based on the target control point sequence, pose change control information of the carrying component set on the robotic arm is generated; the robotic arm is controlled to perform trajectory movement through the target control point sequence, and the pose change control information is used to control the pose change of the carrying component, thereby controlling the robotic arm to carry an object.

[0187] In one embodiment, when the computer program is executed by a processor, it also performs the following steps:

[0188] Based on the displacement information and displacement time between adjacent target control points, the desired acceleration information of the robotic arm is determined; according to the preset gravitational acceleration information and the desired acceleration information, the target acceleration information of the transport component is generated; the target acceleration information is normalized to obtain the pose change control information in the first direction.

[0189] In one embodiment, when the computer program is executed by a processor, it also performs the following steps:

[0190] The pose change control information in the first direction is projected onto the second direction to obtain the projection information in the second direction; the projection information in the second direction is normalized to obtain the pose change control information in the second direction; based on the pose change control information in the first direction and the pose change control information in the second direction, pose change control information in the third direction is generated.

[0191] In one embodiment, when the computer program is executed by a processor, it also performs the following steps:

[0192] Based on the target interpolation parameters, position interpolation is performed on the initial control point sequence to obtain position interpolation results, and rotation interpolation is performed on the initial control point sequence based on the target interpolation parameters to obtain rotation interpolation results; the target control point sequence is generated based on the position interpolation results and the rotation interpolation results.

[0193] In one embodiment, when the computer program is executed by a processor, it also performs the following steps:

[0194] The target control point sequence is mapped to the joint space to obtain the mapping result; based on the mapping result, the motion capability of the robotic arm is detected to obtain the motion capability detection result; if the motion capability detection result is passed, the following steps are executed: controlling the robotic arm to perform trajectory movement through the target control point sequence, and controlling the transport component to perform pose change through the pose change control information, thereby controlling the robotic arm to transport objects.

[0195] In one embodiment, when the computer program is executed by a processor, it also performs the following steps:

[0196] Obtain a preset motion time range, and determine an interpolation range based on the motion pose constraint information of the robotic arm and the preset motion time range; select uniformly distributed target interpolation parameters within the interpolation range.

[0197] In one embodiment, a computer program product is provided, including a computer program that, when executed by a processor, performs the following steps:

[0198] An initial control point sequence of a robotic arm is obtained, wherein the initial control point sequence is used to characterize the motion trajectory of the robotic arm when carrying an object; a target interpolation parameter is obtained, and the initial control point sequence is smoothly interpolated according to the target interpolation parameter to obtain a target control point sequence of the robotic arm; based on the target control point sequence, pose change control information of the carrying component set on the robotic arm is generated; the robotic arm is controlled to perform trajectory movement through the target control point sequence, and the pose change control information is used to control the pose change of the carrying component, thereby controlling the robotic arm to carry an object.

[0199] In one embodiment, when the computer program is executed by a processor, it also performs the following steps:

[0200] Based on the displacement information and displacement time between adjacent target control points, the desired acceleration information of the robotic arm is determined; according to the preset gravitational acceleration information and the desired acceleration information, the target acceleration information of the transport component is generated; the target acceleration information is normalized to obtain the pose change control information in the first direction.

[0201] In one embodiment, when the computer program is executed by a processor, it also performs the following steps:

[0202] The pose change control information in the first direction is projected onto the second direction to obtain the projection information in the second direction; the projection information in the second direction is normalized to obtain the pose change control information in the second direction; based on the pose change control information in the first direction and the pose change control information in the second direction, pose change control information in the third direction is generated.

[0203] In one embodiment, when the computer program is executed by a processor, it also performs the following steps:

[0204] Based on the target interpolation parameters, position interpolation is performed on the initial control point sequence to obtain position interpolation results, and rotation interpolation is performed on the initial control point sequence based on the target interpolation parameters to obtain rotation interpolation results; the target control point sequence is generated based on the position interpolation results and the rotation interpolation results.

[0205] In one embodiment, when the computer program is executed by a processor, it also performs the following steps:

[0206] The target control point sequence is mapped to the joint space to obtain the mapping result; based on the mapping result, the motion capability of the robotic arm is detected to obtain the motion capability detection result; if the motion capability detection result is passed, the following steps are executed: controlling the robotic arm to perform trajectory movement through the target control point sequence, and controlling the transport component to perform pose change through the pose change control information, thereby controlling the robotic arm to transport objects.

[0207] In one embodiment, when the computer program is executed by a processor, it also performs the following steps:

[0208] Obtain a preset motion time range, and determine an interpolation range based on the motion pose constraint information of the robotic arm and the preset motion time range; select uniformly distributed target interpolation parameters within the interpolation range.

[0209] 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 used for analysis, data stored, data displayed, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties.

[0210] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. Any references to memory, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. 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), magnetic 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 take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM). The databases involved in the embodiments provided in this application may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the embodiments provided in this application may be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, etc., and are not limited to these.

[0211] The technical features of the above embodiments can be combined in any way. For the sake of brevity, 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, they should be considered to be within the scope of this specification.

[0212] The embodiments described above are merely illustrative of several implementation methods of this application, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of this patent application. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this application should be determined by the appended claims.

Claims

1. A motion control method for a gripperless robotic arm, characterized in that, The method includes: Obtain the initial control point sequence of the robotic arm, wherein the initial control point sequence is used to characterize the motion trajectory of the robotic arm when it is carrying an object; Obtain the target interpolation parameters, and perform smooth interpolation on the initial control point sequence based on the target interpolation parameters to obtain the target control point sequence of the robotic arm; the target control point sequence includes at least one target control point; Based on the displacement information and displacement time between adjacent target control points, the desired acceleration information of the robotic arm is determined; Based on the preset gravitational acceleration information and the desired acceleration information, target acceleration information of the transport component set on the robotic arm is generated; The target acceleration information is normalized to obtain pose change control information in the first direction; The pose change control information in the first direction is projected onto the second direction to obtain the projection information in the second direction; The projection information in the second direction is normalized to obtain the pose change control information in the second direction; Based on the pose change control information in the first direction and the pose change control information in the second direction, pose change control information in the third direction is generated. The robotic arm is controlled to perform trajectory movement by the target control point sequence, and the pose change control information is used to control the pose change of the transport component, thereby controlling the robotic arm to transport objects.

2. The method as described in claim 1, characterized in that, The smooth interpolation includes position interpolation and rotation interpolation. The step of smoothing the initial control point sequence according to the target interpolation parameters to obtain the target control point sequence of the robotic arm includes: Based on the target interpolation parameters, position interpolation is performed on the initial control point sequence to obtain position interpolation results; and based on the target interpolation parameters, rotation interpolation is performed on the initial control point sequence to obtain rotation interpolation results. The target control point sequence is generated based on the position interpolation result and the rotation interpolation result.

3. The method as described in claim 1, characterized in that, Before the steps of controlling the robotic arm to perform trajectory movement through the target control point sequence and controlling the transport component to perform pose changes through the pose change control information, thereby controlling the robotic arm to transport objects, the method further includes: The target control point sequence is mapped to the joint space to obtain the mapping result; Based on the mapping result, the motion capability of the robotic arm is detected to obtain the motion capability detection result; If the motion capability detection result is passed, then the following steps are executed: control the robotic arm to perform trajectory movement through the target control point sequence, and control the transport component to perform pose change through the pose change control information, thereby controlling the robotic arm to transport objects.

4. The method as described in claim 1, characterized in that, Prior to the step of obtaining the initial control point sequence of the robotic arm, the method further includes: Obtain a preset motion time range, and determine the interpolation range based on the motion pose constraint information of the robotic arm and the preset motion time range; Select target interpolation parameters that are uniformly distributed within the interpolation range.

5. A motion control device for a gripperless robotic arm, characterized in that, The device includes: A control point acquisition module is used to acquire an initial control point sequence of the robotic arm, wherein the initial control point sequence is used to characterize the motion trajectory of the robotic arm when it is carrying an object. A smooth interpolation module is used to obtain target interpolation parameters, and to perform smooth interpolation on the initial control point sequence based on the target interpolation parameters to obtain the target control point sequence of the robotic arm; the target control point sequence includes at least one target control point; A pose change control information generation module is used to determine the desired acceleration information of the robotic arm based on the displacement information and displacement time between adjacent target control points; generate target acceleration information of the transport component set on the robotic arm according to preset gravitational acceleration information and the desired acceleration information; normalize the target acceleration information to obtain pose change control information in a first direction; project the pose change control information in the first direction to a second direction to obtain projection information in the second direction; normalize the projection information in the second direction to obtain pose change control information in the second direction; and generate pose change control information in a third direction based on the pose change control information in the first direction and the pose change control information in the second direction. The trajectory sending module is used to control the robotic arm to perform trajectory movement through the target control point sequence, and to control the position change control information to control the position change of the transport component, thereby controlling the robotic arm to transport objects.

6. The apparatus according to claim 5, characterized in that, The smooth interpolation includes positional interpolation and rotational interpolation, and the smooth interpolation module is further used for: Based on the target interpolation parameters, position interpolation is performed on the initial control point sequence to obtain position interpolation results; and based on the target interpolation parameters, rotation interpolation is performed on the initial control point sequence to obtain rotation interpolation results. The target control point sequence is generated based on the position interpolation result and the rotation interpolation result.

7. The apparatus according to claim 5, characterized in that, The device is also used for: The target control point sequence is mapped to the joint space to obtain the mapping result; Based on the mapping result, the motion capability of the robotic arm is detected to obtain the motion capability detection result; If the motion capability detection result is passed, then the following steps are executed: control the robotic arm to perform trajectory movement through the target control point sequence, and control the transport component to perform pose change through the pose change control information, thereby controlling the robotic arm to transport objects.

8. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the method according to any one of claims 1 to 4.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 4.

10. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 4.

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