Cylindrical crossed roller bearing automatic assembly mechanical arm and trajectory planning method thereof

Abstract

The application discloses a cylindrical crossed roller bearing automatic assembly mechanical arm and a trajectory planning method thereof, the mechanical arm directly drives each required motion mechanism through a plurality of driving mechanisms; the trajectory planning method firstly divides the motion trajectory of the mechanical arm into three interval segments, uses different order polynomial interpolation functions for trajectory planning on the interval segmentation, calculates the shortest motion trajectory of the mechanical arm through an improved grey wolf algorithm with an exploration step length, and obtains the shortest motion time of the three intervals; then, the longest joint motion time in the calculated shortest motion time is selected as the total motion time, so that the joints are synchronously moved. The mechanical arm has high transmission efficiency, can install cylindrical rollers in different directions, the trajectory planning method calculates the shortest motion trajectory, so that the motion process time is the shortest, the mechanical arm efficiently completes the installation of the cylindrical crossed roller bearing, and the working efficiency of the mechanical arm is improved.

Description

Technical Field

[0001] This invention belongs to the field of robotic arm technology, and relates to an automatic assembly robotic arm for cylindrical crossed roller bearings and its trajectory planning method. Background Technology

[0002] Cylindrical crossed roller bearings are an important slewing bearing component, widely used in CNC rotary tables of precision machine tools and joints of industrial robots. However, due to the different directions of adjacent rollers, it is difficult to achieve automatic assembly of cylindrical crossed roller bearings. Controlling the robotic arm to run smoothly along the preset path to successfully grasp the cylindrical crossed roller bearing is also a challenge. Usually, algorithms with large computational loads are slow and cumbersome, while those with small computational loads lack accuracy.

[0003] Therefore, there is a need for a robotic arm that can be used for gripping and assembling cylindrical crossed roller bearings with high efficiency. Summary of the Invention

[0004] In view of this, in order to overcome the shortcomings of the prior art, the purpose of this invention is to provide an automatic assembly robot arm for cylindrical crossed roller bearings and its trajectory planning method. The robot arm directly drives each joint through a drive mechanism, resulting in high transmission efficiency. Its trajectory planning method, through improvements to the robot arm motion planning and the Grey Wolf algorithm, calculates the trajectory with the shortest motion time, thus solving the problem of low installation efficiency.

[0005] To achieve the above objectives, the technical solution adopted by the present invention is as follows:

[0006] A method for trajectory planning of an automated assembly robot for cylindrical crossed roller bearings, comprising the following steps:

[0007] Step 1: Divide the movement trajectory of the robotic arm into three intervals.

[0008] Among them, the starting position and the ending position obtained from the forward kinematics equation divide the path trajectory into three intervals, obtain the Cartesian space coordinates of the four path points, and obtain the solution of the four joint path points from the inverse kinematics of the robotic arm.

[0009] Step 2: Perform trajectory planning by segmenting the interval using polynomial interpolation functions of different orders;

[0010] The motion in the first interval is planned using cubic polynomial interpolation, the motion in the second interval is planned using seventh polynomial interpolation, and the motion in the third interval is planned using cubic polynomial interpolation. This makes the motion trajectory smoother and more continuous, avoids mechanical shock, and reduces damage to the motor's lifespan. The trajectory is divided into three segments, and the shortest time for each segment is calculated, which gives the time for each joint to reach the target position.

[0011] Among them, the shortest motion trajectory of the robotic arm was calculated by incorporating the exploration step size, and the shortest motion time of the three intervals was obtained.

[0012] Step 3: Select the longest joint movement time from the calculated shortest movement time as the total movement time, so that the joints move synchronously.

[0013] To further optimize this process, step 2, the calculation of the shortest motion trajectory for the robotic arm, includes the following steps:

[0014] Step 2.1: First, initialize the gray wolf population parameters;

[0015] Step 2.2: Calculate the fitness value of individual gray wolves and save the three gray wolves with the best fitness values;

[0016] Step 2.3: Update each individual gray wolf using the encirclement formula;

[0017] Step 2.4: Update the gray wolf population parameters;

[0018] Step 2.5: Recalculate the fitness values ​​of individual gray wolves and save the three gray wolves with the best fitness values;

[0019] Step 2.6: Repeat steps 2.2 to 2.5 until the maximum number of iterations is reached. Output the optimal solution and use the three gray wolves with the best fitness values ​​as the shortest movement time for the three intervals of the movement trajectory.

[0020] Furthermore, the maximum number of iterations for the enclosing formula is one hundred.

[0021] Alternatively, the improved gray wolf algorithm can be initialized with a tent chaotic map.

[0022] Furthermore, the improved gray wolf algorithm employs nonlinear control parameters, the expression for which is:

[0023]

[0024] Where k is the current iteration number, K is the total number of iterations, tan is the sine function, and arctan is the arctangent function.

[0025] Furthermore, the improved gray wolf algorithm combines the gray wolf hunting prey with the longhorn beetle whisker algorithm, incorporating the exploration step size for calculation. The expression for prey encirclement is:

[0026] X(k+1)=(0.5·X1(k)+0.3·X2(k)+0.2·X3(k))+ο k ·r·sign(X best -X(k))

[0027] Where X1 is the α wolf, X2 is the β wolf, X3 is the σ wolf, k is the current iteration number, and o k =0.95·o k -1; o0 = 0.5; r is a random number; sign is the sign function, X best Let X(k) be the optimal gray wolf position in the previous generation's fitness, and X(k) be the current gray wolf position. The improved gray wolf algorithm incorporates the search step size of the beetle whisker search, which allows the computational results to escape local optima.

[0028] Further optimization involves step 3, where the α-wolf, β-wolf, and σ-wolf values ​​obtained from the improved gray wolf algorithm are assigned to parameters Ki, Kp, and Kd, respectively, as control parameters input to the PID controller. The PID controller then tracks and controls the calculated desired motion trajectory. Ki, Kp, and Kd are proportional, integral, and derivative parameters, respectively. The improved gray wolf algorithm is used to optimize the calculation of these three parameters, tune the PID parameters, and control the movement of the robotic arm.

[0029] An automatic assembly robot arm for cylindrical crossed roller bearings includes a base, a linear guide mechanism mounted on the base, and a robot arm body. The linear guide mechanism includes a turntable, a column guide rail, and a lead screw. The upper and lower ends of the linear guide mechanism are respectively provided with a first drive mechanism for driving the lead screw to move up and down and a second drive mechanism for driving the turntable to rotate.

[0030] The robotic arm body includes a first joint arm, a second joint arm, and a robotic claw connected in sequence. One end of the first joint arm is sleeved on the column guide rail and the lead screw, and the other end is rotatably connected to the second joint arm. The lead screw drives the first joint arm to move up and down along the column guide rail, and the robotic claw is rotatably connected to the second joint arm.

[0031] A third drive mechanism for driving the movement of the second joint arm is provided at the connection between the first joint arm and the second joint arm, and a fourth drive mechanism and a fifth drive mechanism for driving the rotation of the mechanical claw are provided at the connection between the second joint arm and the mechanical claw.

[0032] Further optimization involves providing a disc at one end of the first articulated arm near the column guide rail, with multiple circular perforations on the disc. The number and position distribution of the circular perforations correspond one-to-one with the sum and position distribution of the column guide rail and the lead screw.

[0033] Further optimization includes a turntable upper cover and a turntable lower cover with the same axial direction. The turntable includes a turntable upper cover and a turntable lower cover with the same axial direction. Both the turntable upper cover and the turntable lower cover are provided with a circular hole. The outer edge of the circular hole is fixedly connected to the outer ring of a rotating bearing. The two ends of the lead screw are fixedly connected to the inner ring of the rotating bearing of the turntable lower cover and the turntable upper cover, respectively.

[0034] All of the above-mentioned drive mechanisms include a motor and a planetary gear reducer. The output shaft of the planetary gear reducer of the first drive mechanism passes through the turntable cover and is fixedly connected to the lead screw.

[0035] The beneficial effects of this invention are:

[0036] First, the robotic arm of the present invention directly drives the articulated arm through a motor, which improves the transmission efficiency and enables the installation of cylindrical rollers in different horizontal and vertical directions, thereby improving the working efficiency of the robotic arm.

[0037] Secondly, the trajectory planning method of this invention, through the improved gray wolf algorithm, calculates a PID controller with Kp, Ki, and Kd, which can effectively control the movement of the robotic arm to achieve the purpose of automatic assembly of cylindrical crossed roller bearings; furthermore, it minimizes the assembly process time, enabling the robotic arm to efficiently complete the installation of cylindrical crossed roller bearings, reducing the impact of mechanical shock and motor life.

[0038] Third, through the trajectory planning method of this invention, the angle, angular velocity and angular acceleration of the robotic arm are continuous, smooth and without abrupt changes during movement, avoiding mechanical impact on the robotic arm during movement and reducing the impact on motor life. Attached Figure Description

[0039] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0040] Figure 1 This is a comparison diagram of the nonlinear control factor and linear control factor functions in Embodiment 1 of the present invention;

[0041] Figure 2 This is a schematic diagram of the calculation process of the improved gray wolf algorithm in Embodiment 1 of the present invention;

[0042] Figure 3 This is a schematic diagram of the control strategy parameter calculation process in Embodiment 1 of the present invention;

[0043] Figure 4This refers to the robotic arm control strategy in Embodiment 1 of the present invention;

[0044] Figure 5 This is a schematic diagram of the robotic arm in Embodiment 2 of the present invention;

[0045] Figure 6 This is a schematic diagram of the base structure in Embodiment 2 of the present invention;

[0046] Figure 7 This is a schematic diagram of the structure of the first articulated arm in Embodiment 2 of the present invention;

[0047] The reference numerals in the attached drawings are as follows: 1. Base; 2. First drive mechanism; 201. First planetary gear reducer; 3. Turntable; 301. Turntable lower cover; 302. Column guide rail; 303. Lead screw; 304. Turntable upper cover; 4. Second drive mechanism; 5. First articulated arm; 501. Disc; 5011. Linear motion bearing; 5012. Lead screw nut; 502. First mounting hole; 6. Third drive mechanism; 7. Second articulated arm; 701. Second mounting hole; 702. Third mounting hole; 8. Fourth drive mechanism; 9. Mechanical claw; 10. Fifth drive mechanism. Detailed Implementation

[0048] Specific embodiments are given below to further clarify, completely, and in detail the technical solution of the present invention. These embodiments are the preferred embodiments based on the technical solution of the present invention, but the scope of protection of the present invention is not limited to the following embodiments.

[0049] Example 1

[0050] A method for trajectory planning of an automated assembly robot for cylindrical crossed roller bearings, comprising the following steps:

[0051] Step 1: Divide the movement trajectory of the robotic arm into segments;

[0052] The starting and ending positions obtained from the forward kinematics equations divide the path into three intervals, yielding the Cartesian coordinates of four path points. The inverse kinematics of the robotic arm provides the solution for the four joint path points.

[0053] Further optimization, step 1 includes the following steps:

[0054] Step 1-1: Solve the forward kinematics equations and inverse kinematics of the robotic arm using the standard DH method, and establish a mathematical model of the robotic arm in three-dimensional space using the MATLAB Robotics Toolbox.

[0055] Steps 1-2: Determine the spatial coordinates of the robotic arm, including the starting point, ending point, and necessary intermediate path nodes during the movement process;

[0056] Steps 1-3: Divide all spatial coordinate points into segments;

[0057] Steps 1-4: Based on the above spatial coordinate points, solve for the joint angle values ​​corresponding to the spatial coordinate points.

[0058] Step 2: Apply polynomial interpolation functions of different orders to the segmented intervals for path trajectory planning;

[0059] The motion in the first interval is planned using cubic polynomial interpolation, the motion in the second interval is planned using seventh polynomial interpolation, and the motion in the third interval is planned using cubic polynomial interpolation. The "3-7-3" polynomial interpolation planning makes the motion trajectory smoother and more continuous, avoids mechanical impact, and reduces damage to the motor life. Dividing the trajectory into three segments and calculating the shortest time for each segment will give the time for each joint to reach the target position.

[0060] Further optimization involves step 2, where the shortest continuous smooth motion trajectory of the robotic arm is calculated using an improved gray wolf algorithm, including the following steps:

[0061] Step 2-1: First, initialize the gray wolf population parameters;

[0062] Step 2-2: Calculate the fitness value of individual gray wolves and save the three gray wolves with the best fitness values;

[0063] Steps 2-3: Update each individual gray wolf using the encirclement formula;

[0064] Steps 2-4: Update the gray wolf population parameters;

[0065] Steps 2-5: Recalculate the fitness values ​​of individual gray wolves and save the three gray wolves with the best fitness values;

[0066] Step 2-6: Repeat steps 2-2 to 2-5 until the maximum number of iterations is reached. Output the optimal solution and use the three gray wolves with the best fitness values ​​as the shortest movement time for the three intervals of the movement trajectory.

[0067] Furthermore, the maximum number of iterations for the enclosing formula is one hundred.

[0068] Alternatively, the improved gray wolf algorithm can be initialized with a tent chaotic map.

[0069] Furthermore, the improved gray wolf algorithm employs nonlinear control parameters, the expression for which is:

[0070]

[0071] Where k is the current iteration number, K is the total number of iterations, tan is the sine function, and arctan is the arctangent function.

[0072] When the absolute value of the control factor is greater than 1, the global search capability of the improved gray wolf algorithm is better. By adopting the above nonlinear control parameters, the absolute value of the gray wolf's encirclement step size is more than 1, thus enhancing the global search capability.

[0073] In the coefficients for the gray wolves surrounding their prey, A represents the simulated attack behavior of gray wolves on their prey; a is a control factor, which is a nonlinear decreasing function from 2 to 0; and C is a coefficient expressing the distance between the α, β, δ layer wolf packs and the ω layer wolf pack.

[0074] The parameter A plays a crucial role in the search capability of the GWO algorithm. When |A| > 1, the population expands its search range, finding better candidate solutions and thus enhancing global search capability. When |A| < 1, the population's search capability decreases, meaning the GWO algorithm is prone to getting trapped in local optima. During optimization, the value of A changes with the control parameter a, meaning the GWO algorithm's search capability depends on the change in the control parameter a, and the value of a decreases as the number of iterations increases. This improvement slows down the convergence speed of the algorithm during the search for the optimal value, but it allows it to find the global optimum more effectively.

[0075] Furthermore, the improved gray wolf algorithm combines the gray wolf hunting prey with the longhorn beetle whisker algorithm, incorporating the exploration step size for calculation. The expression for prey encirclement is:

[0076] X(k+1)=(0.5·X1(k)+0.3·X2(k)+0.2·X3(k))+ο k ·r·sign(X best -X(k))

[0077] Where X1 is the α wolf, X2 is the β wolf, X3 is the σ wolf, k is the current iteration number, and o k =0.95·o k -1; o0 = 0.5; r is a random number; sign is the sign function, X best Let X(k) be the optimal gray wolf position in the previous generation's fitness, and X(k) be the current gray wolf position. The improved gray wolf algorithm incorporates the search step size of the beetle whisker search, which allows the computational results to escape local optima.

[0078] r is a random number between 0 and 1, when X(k) is greater than X best time o k ×r×sign(X best A negative value for -X(k) indicates that the gray wolf is far from the prey, allowing it to approach the optimal position more quickly. When X(k) equals X... best time ok ×r×sign(X best -X(k) is 0, and the gray wolf position is updated by assigning weights to α wolf, β wolf, and σ wolf. This speeds up the convergence of the algorithm during the optimization process, and combined with point 3, it can find the global optimum better and faster.

[0079] Step 3: Select the longest joint movement time from the calculated shortest movement time as the total movement time, so that the joints move synchronously.

[0080] In further optimization, in step 3, the α wolf, β wolf, and σ wolf obtained by the improved gray wolf algorithm are assigned to parameters Ki, Kp, and Kd respectively as control parameters input to the PID controller, and then the PID controller tracks and controls the calculated desired motion trajectory.

[0081] In this embodiment, a link coordinate system is established, and the forward kinematic equations of the robotic arm are solved using the standard DH method to obtain the position and orientation of the robotic arm in the base coordinate system. The motion angles of each joint of the robotic arm are obtained through inverse kinematics. The forward kinematic equations include:

[0082]

[0083] In the formula, n x =c 23 c4;o x =-c 23 s4; q x =s 23 ;q z =0; p x =L4c 23 c4+L3c 23 +L2c2;n y =s 23 c4;o y =-s 23 s4;p y =L4s 23 c4+L3s 23 +L2s2;q y =-c 23 ;n z =s4;o z =c4;p z =L4s4+d1;

[0084] Among them, s4=sinθ4; s2=sinθ2; c4=cosθ4; c2=cosθ2; c 23 =cos(θ2+θ4); s 23= sin(θ2+θ3); L2 is the length of the first joint arm 5, L3 is the length of the second joint arm 7, L4 is the length of the third joint arm (mechanical claw 9), d1 is the distance the first joint arm 5 moves up and down; θ2 is the joint angle of the first joint arm 5, θ3 is the joint angle of the second joint arm 7, and θ4 is the joint angle of the third joint arm (mechanical claw 9).

[0085] The robotic arm calculates its motion trajectory using an improved gray wolf algorithm, with the arm's velocity and acceleration as constraints, and the objective function being to minimize the time taken for the robotic arm's motion trajectory. The objective function includes:

[0086] f(t)=min(t1+t2+t3)

[0087] The constraints include:

[0088] max(|v ij |)≤v ijmax

[0089] max(|a ij |)≤a ijmax

[0090] The advantages of the robotic arm are that the motor directly drives the articulated arm, improving transmission efficiency. It can install cylindrical rollers in different horizontal and vertical directions, with the shortest assembly time, thus improving the working efficiency of the robotic arm. Furthermore, the angle, angular velocity, and angular acceleration are continuous, smooth, and without abrupt changes, avoiding mechanical impact during the movement of the robotic arm and reducing the impact on the lifespan of the motor.

[0091] Example 2

[0092] An automatic assembly robot arm for cylindrical crossed roller bearings includes a base 1, a linear guide mechanism mounted on the base 1, and a robot arm body. The linear guide mechanism includes a turntable 3, a column guide rail 302, and a lead screw 303. The upper and lower ends of the linear guide mechanism are respectively provided with a first drive mechanism 2 for driving the lead screw 303 to move up and down and a second drive mechanism 4 for driving the turntable 3 to rotate.

[0093] The robotic arm body includes a first joint arm 5, a second joint arm 7, and a robotic claw 9 connected in sequence. One end of the first joint arm 5 is sleeved on the column guide rail 302 and the lead screw 303, and the other end is rotatably connected to the second joint arm 7. The lead screw 303 drives the first joint arm 5 to move up and down along the column guide rail 302, and the second joint arm 7 is rotatably connected to the robotic claw 9.

[0094] The first articulated arm 5 and the second articulated arm 7 are connected by a third drive mechanism 6 for driving the movement of the second articulated arm 7. The second articulated arm 7 and the mechanical claw 9 are connected by a fourth drive mechanism 8 and a fifth drive mechanism 10 for driving the mechanical claw 9 to turn and grasp, respectively.

[0095] According to an embodiment of the present invention, the joints of the automatic assembly robot arm for cylindrical crossed roller bearings are driven by motors, which reduces energy loss during the driving process. The gripping surface of the mechanical claw 9 for gripping the cylindrical rollers is made of flexible material. The robot arm can assemble cylindrical rollers in both the horizontal and vertical directions with stable gripping. The mechanical claw 9 will not cause damage to the cylindrical rollers, and the movement of the robot arm has the advantages of short time and good stability.

[0096] All of the above-mentioned drive mechanisms include a motor and a planetary gear reducer. The output shaft of the motor and the planetary gear reducer are directly connected. The output shaft of the first planetary gear reducer 201 of the first drive mechanism 2 passes through the turntable cover 304 and the lead screw 303 and is fixedly connected.

[0097] Specifically, the turntable upper cover 304 and the turntable lower cover 301 are discs 501 of the same shape and size. One end of the plurality of column guide rails 302 is fixedly connected to the turntable lower cover 301, and the other end of the plurality of column guide rails 302 is fixedly connected to the turntable upper cover 304.

[0098] Further optimization is achieved by the turntable 3 comprising a turntable upper cover 304 and a turntable lower cover 301 with the same axial direction. The turntable 3 comprises a turntable upper cover 304 and a turntable lower cover 301 with the same axial direction. Both the turntable upper cover 304 and the turntable lower cover 301 are provided with a circular hole. The outer edge of the circular hole is fixedly connected to the outer ring of a rotating bearing. The two ends of the lead screw 303 are fixedly connected to the inner rings of the rotating bearings of the turntable lower cover 301 and the turntable upper cover 304, respectively.

[0099] Further optimization involves providing a disc 501 at one end of the first articulated arm 5 near the column guide rail 302 and a first mounting hole 502 at the other end. The disc 501 has multiple circular through holes, and the number and position distribution of the circular through holes correspond one-to-one with the total number and position distribution of the column guide rail 302 and the lead screw 303.

[0100] Optionally, a linear motion bearing 5011 or a lead screw nut 5012 is installed inside the circular through hole. The outer ring of the linear motion bearing 5011 is fixedly installed in the circular through hole, and the inner ring of the linear motion bearing 5011 is sleeved on the column guide rail 302, allowing the linear motion bearing 5011 to slide on the column guide rail 302. The inner ring of the lead screw nut 5012 is sleeved on the lead screw 303. The output shaft of the planetary gear reducer of the first drive mechanism 2 drives the lead screw 303, causing the lead screw nut 5012 to move the first articulated arm 5 up and down. Each end of the second articulated arm 7 near the first articulated arm 5 has a second mounting hole 701. The output shaft of the planetary gear reducer of the third drive mechanism 6 passes through the first mounting hole 502 and the second mounting hole 701 and is fixedly connected to the second articulated arm 7, driving the second articulated arm 7 to move.

[0101] Specifically, the second joint arm 7 has a third mounting hole 702 at one end near the mechanical claw 9, and the mechanical claw 9 has a fourth mounting hole at one end near the second joint arm 7. The output shaft of the planetary gear reducer of the fourth drive mechanism 8 is fixedly connected to the fourth mounting hole through the third and fourth mounting holes, driving the mechanical claw 9 to rotate. The fifth drive mechanism 10 is arranged opposite to the output shaft of the fourth drive mechanism 8, and the output shaft of the planetary gear reducer of the fifth drive mechanism 10 is connected to the mechanical claw 9 to control the gripping of the mechanical claw 9.

[0102] Further optimization involves the robotic arm employing fixed-point gripping and fixed-point installation. Specifically:

[0103] The robotic arm performs a fixed-point gripping action. After the robotic arm grips a cylindrical roller at a fixed position, the conveying device transports the next cylindrical roller to the position where the robotic arm grips the roller.

[0104] The robotic arm is installed at a fixed point. After the cylindrical rollers are installed on the robotic arm, the rotating platform where the bearing is located will rotate the next installation position to the fixed installation position.

[0105] Further optimization involves a hollow structure inside the base 1, with the second drive mechanism 4 housed within the base 1, and the output shaft of its star gear reducer fixedly mounted on the turntable 3.

[0106] In the trajectory tracking method described in this invention, a mathematical model of the robotic arm in three-dimensional space is established using the MATLAB Robotics Toolbox. The coordinates of the robotic arm's grasping and mounting positions are obtained using the MATLAB Robotics Toolbox. These coordinates are then converted into joint motion angles for each joint through inverse kinematics. The motion trajectory is calculated using an improved Grey Wolf algorithm, with the robotic arm's velocity and acceleration as constraints, and the objective function being the shortest possible motion time. The angular velocity at each point along the path is continuously and smoothly measured to obtain the angular velocity, and the desired sliding distance is also output. Specifically:

[0107] The shortest time for the robotic arm is calculated using an improved Grey Wolf algorithm based on 3-7-3 polynomial interpolation. Simultaneously, the polynomial coefficients for the shortest motion time are also obtained. The values ​​of the robotic arm's angular velocity and angular acceleration are the first and second derivatives of the 3-7-3 polynomial. By calculating the coefficients and time, the values ​​of angular velocity and angular acceleration can be obtained, and the output is a two-dimensional curve. The smoothness of the curve represents the desired angular velocity and angular acceleration of the robotic arm.

[0108] Furthermore, the robotic arm also includes a PID controller. Based on the desired joint angle (rad) and joint angular velocity (rad / s) of the turntable 3 calculated by the improved gray wolf algorithm in the method of the present invention, the control signal sent by the PID controller adjusts the motor speed of the second drive mechanism 4, converts this into joint angular velocity, and achieves motion control of each joint of the robotic arm.

[0109] The desired sliding distance is converted into the rotation angle of the lead screw 303. The control signal sent by the PID controller adjusts the motor speed of the first drive mechanism 2, which is then converted into the joint angular velocity to achieve motion control of the first joint arm 5 of the robotic arm.

[0110] According to the improved gray wolf algorithm of the present invention, the expected joint angle (rad) and joint angular velocity (rad / s) of the second joint arm 7 are calculated. The control signal sent by the PID controller adjusts the motor speed of the third drive mechanism 6, which is then converted into joint angular velocity to achieve motion control of the second joint arm 7.

[0111] According to the method of the present invention, the expected joint angle (rad) and joint angular velocity (rad / s) of the mechanical claw 9 are calculated by the improved gray wolf algorithm. The control signal sent by the PID controller adjusts the motor speed of the fourth drive mechanism 8, and converts it into joint angular velocity to achieve motion control of the mechanical claw 9.

[0112] Furthermore, the mechanical gripper 9 is equipped with a torque sensor. After the robotic arm grasps the cylindrical roller, it sends a control signal to the PID controller to adjust the motor speed of the fourth drive mechanism 8, thereby achieving gripping control of the mechanical gripper 9.

[0113] The PID controller controls the movement of each joint of the robotic arm. Manually adjusting the control parameters is quite complicated, while the improved Grey Wolf algorithm calculates the control parameters more accurately and simply.

[0114] Specific work process:

[0115] When the mechanical claw 9 is installing the cylindrical roller, the cylindrical roller is placed horizontally and vertically on the conveying device. For the horizontal shaft hole, the mechanical claw 9 grips the cylindrical surface for installation, and for the vertical shaft hole, the mechanical arm grips both ends of the cylindrical roller for installation.

[0116] When the mechanical claw 9 grips the cylindrical roller, the coordinates of the center of gravity of the cylindrical roller are the initial point of motion. The distance that the mechanical claw 9 opens before gripping is greater than the height of the cylindrical roller. When the robotic arm installs the cylindrical roller, the coordinates of the center position of the shaft hole are the placement and installation point.

[0117] The robotic arm grasps a cylindrical roller at a fixed point. After grasping the cylindrical roller at the fixed position, the conveying device will transport the next cylindrical roller to the fixed grasping position of the robotic arm.

[0118] The robotic arm installs cylindrical rollers at a fixed point. After installation at the fixed position, the rotating platform where the bearing is located rotates the next installation position to the fixed installation position.

[0119] In summary, the present invention directly drives the joints of the robotic arm with a motor, improving transmission efficiency and enabling the installation of cylindrical rollers in different horizontal and vertical directions. The assembly process is completed in the shortest possible time, allowing the robotic arm to efficiently install the cylindrical crossed roller bearings, reducing mechanical impact and extending motor lifespan. The control method of this invention calculates Kp, Ki, and Kd, which are then output to a PID controller to effectively control the movement of the robotic arm, achieving the goal of automatic assembly of the cylindrical crossed roller bearings.

[0120] The foregoing has shown and described the main features, basic principles, and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The embodiments and descriptions in the specification are merely illustrative of the principles of the invention. Various changes and modifications can be made to the invention based on actual circumstances without departing from its spirit and scope, and all such changes and modifications fall within the scope of the present invention as claimed. The scope of protection of this invention is defined by the appended claims and their equivalents.

Claims

1. A trajectory planning method for an automated assembly robot arm for cylindrical crossed roller bearings, comprising trajectory planning and control of the automated assembly robot arm for cylindrical crossed roller bearings, characterized in that, The method includes the following steps: Step 1: Divide the movement trajectory of the robotic arm into three intervals. Step 2: Perform trajectory planning by segmenting the interval using polynomial interpolation functions of different orders; The motion in the first interval is planned using cubic polynomial interpolation, the motion in the second interval is planned using seventh polynomial interpolation, and the motion in the third interval is planned using cubic polynomial interpolation. The shortest motion trajectory of the robotic arm was calculated by incorporating an improved gray wolf algorithm with an exploration step size, and the shortest motion time for the three intervals was obtained. The calculation of the shortest motion trajectory for a robotic arm includes the following steps: Step 2.1: First, initialize the gray wolf population parameters; Step 2.2: Calculate the fitness value of individual gray wolves and save the three gray wolves with the best fitness values; Step 2.3: Update each individual gray wolf using the encirclement formula; Step 2.4: Update the gray wolf population parameters; Step 2.5: Recalculate the fitness values ​​of individual gray wolves and save the three gray wolves with the best fitness values; Step 2.6: Repeat steps 2.2 to 2.5 until the maximum number of iterations is reached, output the optimal solution, and use the three gray wolves with the best fitness values ​​as the shortest movement time for the three intervals of the movement trajectory. The improved gray wolf algorithm combines the longhorn beetle whisker algorithm with the gray wolf hunting prey, incorporating the exploration step size for calculation. The expression for prey encirclement is as follows: Where X1 is the position of wolf α, X2 is the position of wolf β, and X3 is the position of wolf σ; k =0.95·o k-1 k is the current iteration number, o0 = 0.5; r is a random number; sign is the sign function, X best X(k) represents the optimal gray wolf position in the previous generation, and X(k) represents the current gray wolf position. Step 3: Select the longest joint movement time from the calculated shortest movement time as the total movement time, so that the joints move synchronously.

2. The trajectory planning method for an automatic assembly robot arm of a cylindrical crossed roller bearing according to claim 1, characterized in that, The maximum number of iterations for the enclosing formula is one hundred.

3. The trajectory planning method for an automatic assembly robot arm of cylindrical crossed roller bearings according to claim 1, characterized in that, The improved gray wolf algorithm uses a tent chaotic map to initialize the population.

4. The trajectory planning method for an automatic assembly robot arm of cylindrical crossed roller bearings according to claim 1, characterized in that, The improved gray wolf algorithm uses nonlinear control parameters, and the expression for the control factor is: Where k is the current iteration number, K is the total number of iterations, tan is the tangent function, and arctan is the arctangent function.

5. The trajectory planning method for an automatic assembly robot arm of cylindrical crossed roller bearings according to claim 1, characterized in that, In step 3, the shortest motion times αwolf, βwolf, and σwolf obtained by the improved gray wolf algorithm are assigned to parameters Ki, Kp, and Kd respectively as control parameters and input to the PID controller. Then, the PID controller tracks and controls the calculated desired motion trajectory, where Ki, Kp, and Kd are proportional, integral, and derivative parameters, respectively.

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