Spatial point location motion collaborative planning method based on multi-axis time sequence optimization

Abstract

The invention belongs to the technical field of motion planning of industrial robots, multi-axis mechanical arms and other multi-degree-of-freedom motion equipment, and discloses a spatial point location motion collaborative planning method based on multi-axis time sequence optimization. The method comprises the following steps: firstly, constructing a dynamic and static space model of the patch equipment based on an external rectangle, and effectively describing a working space of the equipment; secondly, planning a non-interference moving track by considering the boundary constraint of taking the chip to the chip mounting position, and analyzing a critical moving track of chip mounting equipment in a safe space; secondly, optimizing a spatial multi-axis motion time sequence by considering a critical trajectory of operation; and finally, planning a multi-axis cooperative motion track, realizing maximization of motion efficiency, and ensuring safety and stability of equipment. According to the method provided by the invention, conflicts and waiting time among multiple axes can be reduced, theoretical and practical support is provided for efficient application of multi-axis motion equipment, and the method has important engineering value and application prospect.

Description

Technical Field

[0001] The present invention belongs to the technical field of motion planning for industrial robots, multi-axis manipulators and other multi-degree-of-freedom motion equipment, and relates to a spatial point motion collaborative planning method based on multi-axis timing optimization. Background Art

[0002] With the development of intelligent manufacturing and industrial informatization, the demand for chips is becoming more and more extensive, and there is an urgent need to improve the chip packaging efficiency. Chip packaging equipment often performs high-precision and high-efficiency complex movements through multi-axis coupling. Multi-axis collaborative motion is the key to improving chip handling and assembly efficiency. However, the existing multi-axis motion planning method has shortcomings in actual use. It only considers the motion path of a single axis and fails to effectively coordinate the motion timing and coordination between multiple axes, resulting in the difficulty in improving the overall efficiency of chip packaging equipment when performing high-speed tasks. In addition, the spatial structure of chip packaging equipment is complex. If spatial obstacles and equipment motion range are not fully considered during motion planning, it will make it difficult to ensure the safety of equipment operation and the feasibility of trajectory in complex environments. Therefore, there is an urgent need for a method that can achieve multi-axis timing optimization and collaborative planning. Research on spatial point motion collaborative planning methods based on multi-axis timing optimization is of great significance to improving the packaging efficiency of chip packaging equipment and reducing packaging costs.

[0003] Han Fuzhu et al.'s patent "Multi-axis linkage laser processing machine tool", announcement number ZL115488496B, proposes a multi-axis linkage laser processing machine tool. By fixing the laser and combining it with the multi-axis linkage processing machine tool, the proposed multi-axis linkage laser processing machine tool has the advantages of good stability and simple optical path protection structure. Xiao Kedong et al.'s patent "A fully automatic multi-axis linkage conveyor printing and packaging equipment", announcement number ZL209700072U, proposes a fully automatic multi-axis linkage conveyor printing and packaging equipment, which realizes fast printing and packaging, saves working time and improves working efficiency. However, the above technologies do not elaborate on how to achieve multi-axis linkage, and lack the theoretical basis of multi-axis linkage. Summary of the invention

[0004] In view of the shortcomings of the prior art, the present invention invents a method for collaborative planning of spatial point motion based on multi-axis timing optimization. This method significantly improves the motion efficiency and safety of multi-axis equipment in the execution of complex tasks by constructing a motion space model, analyzing critical trajectories, optimizing motion timing, and planning multi-axis collaborative trajectories. The proposed method is suitable for high-efficiency motion processes in chip packaging, plays an important role in improving the efficiency of patch motion, and provides theoretical and technical support for high-speed and high-efficiency motion control in semiconductor packaging.

[0005] The technical solution of the present invention:

[0006] A spatial point motion collaborative planning method based on multi-axis timing optimization significantly improves the motion efficiency and safety of multi-axis equipment in the execution of complex tasks by constructing a motion space model, analyzing critical trajectories, optimizing motion timing, and planning multi-axis collaborative trajectories; the steps are as follows:

[0007] Step 1: Construction of global motion space model based on bounding box;

[0008] Chip placement is a process in which surface mounted components or bare chips are quickly and accurately placed on the preset position of the circuit substrate by a high-speed placement machine while ensuring safe movement. However, the high-speed placement machine has a compact spatial structure, and the unreasonable spatial trajectory planning of high-speed short-stroke placement is prone to collision and interference between the pick-up arm and the placement machine. Realizing multi-axis linkage of the placement process in the safe space of the pick-up arm can shorten the running time of the chip transfer stage based on the existing motion parameters, and is an effective method to improve the efficiency of placement while ensuring the stability of the placement. Planning a safe path between the chip picking component and the working structure of the placement machine during the pick-up arm placement process is the first step to achieve multi-axis linkage and improve the efficiency of placement.

[0009] In order to simplify motion planning in complex environments, the motion space of multi-axis devices is modeled based on bounding box theory. The OBB external rectangular bounding box can better fit the object, reduce the blank area, and accurately describe the effective reach of the device. By constructing an external rectangular bounding box, it is possible to quickly determine whether the device is within the safe motion range, thereby avoiding the computational burden brought by complex geometric analysis.

[0010] The motion space of the multi-axis device is modeled based on the bounding box theory, and an circumscribed rectangular bounding box is constructed to determine whether the multi-axis device is within the safe motion range; the placement machine includes a placement machine body and a placement machine moving component, and the placement machine moving component is a pick-up arm; first, based on the contour boundary vertices of the pick-up arm, the convex hull algorithm is used to construct the minimum convex polygon composed of the pick-up arm to ensure that all points of the pick-up arm are within the boundary and interior of the minimum convex polygon; then, the principal component analysis method is used to find the optimal rotation direction of the contour boundary vertices of the pick-up arm, and the boundary of the circumscribed rectangular bounding box is determined according to the optimal rotation direction obtained by the principal component analysis method;

[0011] The optimal rotation direction is obtained by covariance calculation, and the coordinates of a series of contour boundary vertices of the pickup arm are defined as (x i ,y i ), according to the covariance calculation formula, the covariance is calculated as follows:

[0012] C ij = Cov(x i ,y i )=E[(x i -u i )(yi -u j )] i,j=1,2,…,n (1)

[0013] Where E[x] and E[y] are the coordinates x and y respectively. i and i The expected value of C ij Represents the covariance matrix, which is calculated and solved by the following formula:

[0014]

[0015] Then, the coordinates of the contour boundary vertices are projected onto the direction vector, and the maximum and minimum values ​​of the x and y components in each direction are recorded as v k min 、v k max , k = 0, 1; the center of the circumscribed rectangular bounding box is obtained by the following formula:

[0016]

[0017] In the formula, O represents the center point of the outer rectangular bounding box, P 0 Indicates the direction between two points;

[0018] The half length of the bounding box is calculated as follows:

[0019]

[0020] According to the mechanical structure and motion constraints of the multi-axis device, the motion range of each degree of freedom of the multi-axis device is abstracted as an independent external rectangular bounding box; after completing the modeling of the external rectangular bounding box, the external rectangular bounding boxes of each single axis are further combined into the global motion space model of the multi-axis device through joint analysis to limit the effective activity range of the multi-axis device in the entire working environment; according to the structural characteristics of the placement machine, in order to avoid the collision between the pick-up arm and the placement machine body in the multi-axis linkage, the external rectangular bounding boxes of the placement machine body and the pick-up arm are respectively constructed through the bounding box theory, so as to establish a spatial relationship model from the chip picking point to the placement point constrained by boundary obstacles; during the chip picking-placing movement, the boundary of the global motion space model is used as a constraint, and the running trajectory of the end of the pick-up arm should be limited to the safety domain of the global motion space model to avoid collision interference;

[0021] Step 2: Analysis of critical motion trajectories taking into account the safety space;

[0022] Based on the global motion space model, in order to ensure the operational safety of the equipment, it is necessary to analyze the critical motion trajectory during task execution. By defining the safe space, the dangerous areas where the equipment may collide or cross the boundary are eliminated to determine the feasible trajectory range of the equipment.

[0023] In the chip placement process, the safe space is a restriction on the motion range of the multi-axis equipment. Multi-axis linkage is conducive to reducing the running time from the chip picking point to the patch point, but it is necessary to ensure that the position boundary constraints from the chip picking point to the patch point do not interfere with the running trajectory; the feasible space boundary is constructed through the shortest safe distance between the pick-up arm and the patch machine body; on this basis, combined with the dynamic performance of the equipment, such as speed and acceleration constraints, to ensure the smoothness and continuity of the trajectory, the geometric analysis and dynamic simulation methods are used to generate the critical motion trajectory of the multi-axis motion components of the patch machine in the safe space; the chip picking-patch process includes three typical multi-axis linkage space motion trajectories: critical trajectory curve, safe and feasible trajectory, and collision interference trajectory. In order to balance the operating efficiency and safety, the critical running trajectory needs to be accurately solved. The analyzed critical motion trajectory provides the motion boundary information of the equipment, laying a safe guarantee for motion planning in complex environments.

[0024] The YOZ coordinate system is constructed with the chip picking point as the origin, the direction from the chip picking point to the patch point as the Y axis, and the direction perpendicular to the chip picking plane as the Z axis. The generation process of the motion trajectory is ensured to ensure that there is no interference in the chip picking-placing process. In order to avoid lateral scratches of the chip at the moment of picking and position errors in the patch process, when picking, the Z axis must first move to the set safety height, and then the Y axis is linked. When patching, it is necessary to ensure that the Y axis first crosses the constraint area of ​​the patch machine carrier track to reach a safe position, and then the Z axis reaches the patch position height and completes the patch instruction. In the safe space, the key to reducing the unnecessary running time of the chip picking-patch space linkage motion process is to reasonably plan the multi-axis linkage trajectory and determine the multi-axis linkage motion sequence. The obstacle-constrained chip picking-patch space linkage motion process is carried out through the following process:

[0025] ①Boundary interference check at the chip picking position. The constraint boundary is constructed by bounding box theory. The key vertex coordinates of the placement machine are marked as (R, 0) and (R, H 1 ), and the straight line formed by the key vertices is the boundary; when the Y and Z axes are running in linkage, for a given Y axis motion parameter (J y ,a y ,v y ,x y ), calculate the Y axis to reach x y = time t at R's location 1 ; Given the Z-axis motion parameters (J z ,a z ,v z ,x z ), calculation time t 1 Height x of the lower Z axis z (t 1 );

[0026] ②Judge xz (t 1 ) and H 1 When x z (t 1 ) > H 1 , there is no interference in the biaxial linkage at the chip-taking position, go to step ④; when x z (t 1 ) < H 1 , there will be interference in the biaxial linkage, and it is necessary to update the calculation of the Z-axis advance running time, go to step ③;

[0027] ③ Calculate the time t 1 required for the Z-axis to run to the H 2 plane, and determine the advance amount Δt = t 2 - t 1 ;

[0028] ④ Check the boundary interference at the chip-placement position and determine the constraint boundary; calculate the time T z when the Z-axis reaches the highest point. At this time, the running distance x y (T z ) of the Y-axis; the length of the obstacle boundary in the Y direction is denoted as L. If x y (T z ) > R + L, the Z-axis can directly return; if x y (T z ) < R + L, it is necessary to further calculate the time T 1 for the Z-axis to return to the H z,place plane, that is, the time to run in the reverse direction by height h. At this time, the total running time of the corresponding Y-axis is t_y = T z + T z,place , and the running position of the Y-axis is dis_y;

[0029] ⑤ Judge the relationship between dis_y and R + L: If dis_y > R + L, the Z-axis can directly return to meet the constraint conditions and end; if dis_y < R + L, the Z-axis needs to return with a delay, and it is necessary to determine the delay time, go to step ⑥;

[0030] ⑥ Calculate the time t 3 when Y reaches R + L, that is, when leaving the constraint, and then according to the time T z,place when the Z-axis descends to the constraint height h, the time delay is Δt_r = t 3 - T z,place - T_z;

[0031] According to the above chip-taking - chip-placement space linkage movement process, the total time calculation of the chip-taking - chip-placement linkage process considering obstacle constraints is:

[0032] T = 2(Δt + T y + Tz,place +Δt_r)+T place +T pick (5)

[0033] Where, T y Indicates the time of Y-axis operation, T place and T pick The time required for removing and applying the patch is respectively;

[0034] Step 3: Multi-axis motion timing optimization considering critical trajectory space for safe operation;

[0035] During the patch process, in order to prevent lateral displacement between the chip and the wafer and to avoid collision between the pickup arm and the workbench, the Z axis moves in advance and then the Y axis starts to move in conjunction. In the return process to pick up the wafer, in order to avoid collision, the Y axis needs to reach the set safety point in space, and then the Z axis starts to move in conjunction to the specified position and complete the wafer picking. However, the amount of time the Z axis moves in advance during the patch process and the position of the spatial safety point during the wafer picking process are both set based on the experience of the engineer, and the safety threshold is set too high to fully ensure safety, resulting in process timing redundancy, which restricts the improvement of patch efficiency and makes it difficult to reduce packaging costs.

[0036] On the basis of determining the safe trajectory, the goal of the patch process is to improve the patch efficiency based on ensuring the chip patch accuracy. In order to maximize the efficiency of chip picking and patching, it is necessary to optimize the multi-axis motion timing of the chip transmission process. Through the optimization of the patch process timing, the patch operation time can be shortened on the basis of the existing motion process parameters, and the patch efficiency can be improved. Based on the multi-axis linkage analysis, the interference judgment and avoidance strategy between the pick-up arm and the patch machine structure during the chip picking and patching process is analyzed. By building a multi-axis timing optimization model, the start-up time, movement speed and acceleration of each axis are coordinated to eliminate conflicts and invalid waiting between multiple axes. Therefore, on the basis of considering the obstacle constraints, the patch process timing is comprehensively considered, the process beat is optimized to shorten the unnecessary process time of the chip picking and patching movement, and the patch efficiency is improved.

[0037] Analyze the key points and paths of each axis in the chip picking and patching process to determine their impact on the overall task progress. Secondly, based on the task requirements and the motion characteristics of the equipment, a mathematical optimization model is established, with motion time as the objective function and speed, acceleration and path continuity as constraints. Finally, an optimization algorithm (such as genetic algorithm, particle swarm optimization algorithm, etc.) is used to calculate the optimal motion timing allocation of multiple axes to ensure that the motion of all axes reaches the optimal coordination state in time. The optimized timing planning can significantly reduce the task execution time, avoid motion conflicts or long waiting times caused by the incoordination between multiple axes, and thus improve the overall system efficiency.

[0038] On the basis of determining the critical motion trajectory within the safety space, the goal of the chip mounting process is to improve the mounting efficiency based on ensuring the chip mounting accuracy. The precise Z-axis motion advance amount and the position setting of the spatial safety point during mounting are the key to the multi-axis motion timing optimization. Based on the results of step 2, the multi-axis timing model is constructed to optimize the process timing between multiple axes.

[0039] Step 1 is used to analyze the key points and smooth path of the end of the picking arm in the pick-up-patch motion. The key points include the pick-up point, the spatial safety point and the patch point. Step 2 is used to analyze the impact of multi-axis motion on the efficiency of the patch task. Based on the patch task requirements and the motion characteristics of the multi-axis equipment, a mathematical optimization model of multi-axis linkage efficiency is established. With the goal of improving the multi-axis linkage efficiency, an objective function of minimizing time is constructed. With speed, acceleration and path continuity as constraints, the patch motion process is ensured to be efficient and stable. The mathematical optimization model is shown below:

[0040]

[0041] Where, T represents the total time of the chip removal-chip placement linkage process; v i 、a i , Δp i Respectively represent the speed, acceleration and trajectory continuity of each axis; v max 、a max They represent the maximum value constraints of velocity and acceleration, Δp max represents the continuity constraint of the trajectory; t i Indicates the time of each process in multi-axis coordinated motion;

[0042] Step 4: Multi-axis collaborative trajectory planning based on timing optimization

[0043] Based on the process timing between multiple axes and combined with the dynamic constraints of the multi-axis equipment, the multi-axis collaborative trajectory is further planned, and the speed curve of each axis is adjusted to synchronize its motion trajectory in time and space to ensure that the actual motion trajectory of the multi-axis equipment meets the task requirements; the multi-axis linkage trajectory is planned based on the key points in the multi-axis motion trajectory to ensure the smoothness and controllability of the trajectory; the collaborative motion trajectory of each axis is converted into executable instructions for the control system to realize the multi-axis linkage operation of the patch equipment.

[0044] Through the above steps, the placement machine can achieve efficient modeling of motion space, dynamic timing optimization and collaborative trajectory planning when multiple axes collaborate to perform complex pick-up and placement tasks, reducing conflicts and unnecessary waiting time between multiple axes, thereby improving the efficiency of pick-up and placement work while ensuring the safe operation of the equipment.

[0045] Furthermore, genetic algorithm or particle swarm algorithm is used to effectively solve the objective function through initialization of random solution, iterative optimization and convergence judgment, calculate the optimal motion timing allocation of multiple axes, find the optimal allocation plan of the motion time of each axis, and ensure that each axis reaches the optimal coordination state in time.

[0046] Beneficial effects of the present invention: The spatial point motion collaborative planning method based on multi-axis timing optimization of the present invention effectively solves the problems of low motion efficiency, timing conflicts and safety hazards of multi-axis equipment through bounding box modeling, safe space constraints, timing optimization and multi-axis collaborative trajectory planning. First, a dynamic and static spatial model of the patch equipment is constructed based on the circumscribed rectangle to effectively describe the working space of the equipment; secondly, the interference-free operation trajectory is planned considering the boundary constraints from the patch to the patch position, and the critical motion trajectory of the patch equipment in the safe space is analyzed; then, the spatial multi-axis motion timing is optimized considering the critical trajectory of the operation; finally, the multi-axis collaborative motion trajectory is planned to maximize the motion efficiency and ensure the safety and stability of the equipment. The proposed method significantly improves the task execution efficiency, reduces the conflicts and waiting time between multiple axes, provides theoretical and practical support for the efficient application of multi-axis motion equipment, and has important engineering value and application prospects. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] Figure 1 This is the overall flow chart of the spatial point motion collaborative planning method based on multi-axis timing optimization.

[0048] Figure 2 This is a patch model diagram under the safe space constraint based on the bounding box theory.

[0049] Figure 3 It represents the typical spatial motion trajectory during the film-taking process, where the horizontal axis represents the actual running Y axis and the vertical axis represents the actual running Z axis;

[0050] Figure 4 It represents the typical spatial motion trajectory during the patch process, where the horizontal axis represents the actual running Y axis and the vertical axis represents the actual running Z axis.

[0051] Figure 5 It indicates that the collision interference occurs at the film taking position under the current parameters, where the horizontal axis represents the displacement of the Y axis, in mm, and the vertical axis represents the displacement of the Z axis, in mm;

[0052] Figure 6 It indicates the avoidance of collision interference of the film taking position under the current parameters, where the horizontal axis represents the displacement of the Y axis, in mm, and the vertical axis represents the displacement of the Z axis, in mm.

[0053] Figure 7It is a displacement-time curve of the optimized pick-up-and-placement process, where the horizontal axis represents time in seconds and the vertical axis represents displacement in mm.

[0054] Figure 8 It represents the total time of a single row pick-and-place process before process timing optimization, where the horizontal axis represents time in seconds and the vertical axis represents displacement in mm;

[0055] Fig. 9 It represents the total time of a single-row pick-and-place process after process timing optimization, where the horizontal axis represents time in seconds and the vertical axis represents displacement in mm. DETAILED DESCRIPTION

[0056] The specific implementation of the present invention is described in detail below in combination with the technical scheme and the accompanying drawings.

[0057] During the chip packaging process, multi-axis coupling performs high-precision and high-efficiency chip picking and mounting tasks. Improving the efficiency of chip mounting is the goal of chip packaging, and multi-axis collaborative motion is the key to improving chip handling and assembly efficiency. Compared with conventional multi-axis linkage, chip mounting requires not only considering the multi-axis linkage motion path, but also coordinating the motion timing and coordination between multiple axes. Therefore, designing a method that can achieve multi-axis timing optimization and collaborative planning is of great significance to improving the packaging efficiency of chip packaging equipment and reducing packaging costs. To this end, a spatial point motion collaborative planning method based on multi-axis timing optimization is invented. The process of the method is as follows: Figure 1 shown.

[0058] The present invention aims at the problem of safe and efficient multi-axis timing optimization in the chip mounting process, and describes the specific implementation process of the present invention in detail through examples.

[0059] First, based on the bounding box theory, the motion space of the multi-axis device is modeled with an external rectangular bounding box. According to the characteristics of the external rectangular model of the high-speed placement machine, the chip picking point and the placement point have different Z-direction heights. In order to avoid the collision between the picking arm and the placement machine structure in the multi-axis linkage, a spatial relationship model from the chip picking point to the placement point with boundary obstacle constraints is constructed, such as Figure 2 As shown in the figure. The gray part is the physical structure, and the red line represents the physical boundary constraint. When the chip is picked up and placed, the running trajectory of the end of the pick-up arm should avoid the boundary constraint to avoid collision interference.

[0060] Secondly, based on the constructed model, during the chip bonding process, multi-axis linkage needs to consider the boundary constraints from chip picking to chip bonding position to plan the non-interference running trajectory. Figure 3 , 4The spatial motion trajectories of several typical multi-axis linkage situations in the process of picking up and placing chips are shown, including the critical curve of the trajectory, the safe and feasible trajectory, and the collision and interference between the pick-up arm and the packaging equipment during the picking up and placing process. Based on the critical trajectory in step 2, the spatial linkage trajectory in the placement journey from the pick-up point to the placement point can be planned. Assuming the structural parameters of the placement machine are R = 30mm, L = 70mm, H 1 =30mm, H 2 =5mm, h=10mm as an example, set the Y-axis motion parameter J according to engineering experience y =4800m / s 3 、a y =120m / s 2 、v y =2.5m / s, Z-axis motion parameter J z =3600m / s 3 、a z =120m / s 2 、v z =2m / s. Under the current motion parameters, if the Z axis reaches the film-taking height and the Y axis moves with it, the YZ axis spatial motion trajectory at the film-taking position is as follows: Figure 5 As shown in the figure, the pick-up arm collides with the placement machine structure. To avoid collision and reduce the waiting time, the Z-axis priority running time needs to be accurately calculated. According to the above method, the Z-axis runs 10.5ms in advance, and rounding up to 11ms can avoid collision. The critical motion trajectory is as follows Figure 6 shown.

[0061] Finally, reducing invalid empty timing can improve the operation efficiency. To this end, the safety threshold is accurately calculated with the non-interference of the chip position boundary as a constraint. According to the structure size of the placement machine, the given spatial position relationship is R = 35mm, L = 25mm, H 1 =23.5mm, H 2 =0.8mm, h=3mm, the entire Y-direction movement distance can be expressed as dis_y=R+L+0.0055×(k-1), k represents the number of patch points on the PCB board, and the Y-axis movement distance is a function of the patch position; the entire Z-direction movement distance is dis_z=H 1 +h. Three direction motion parameter selection, J = 8000m / s 3 , a=120m / s 2 , v=2m / s.

[0062] According to the non-interference judgment criterion, the advance running time of the Z axis in the first fetching process is Δt = 1.5ms (rounded up to 2ms), and the minimum time for the positive movement of the Y axis is T y =62.9ms, the Z-axis rise time when taking the slice is T z=47.3ms, the Z-axis running time during patch placement is T z,place =24.8ms. Determine T z +T z,place -Δt vs. T y The relationship between z +T z,place -Δt <T y It is always true, that is, no interference will occur during patch placement. Therefore, the entire process time can be calculated by formula (5).

[0063] Based on the above timing optimization method, the optimized timing of multi-axis linkage in the chip safe pick-up and placement process can be obtained, such as Figure 7 To verify the correctness of the proposed algorithm, the number of rows of the lead substrate is k = 12, and the total running time of the whole row pick-and-place process under different process sequences is analyzed. The time used in the single row pick-and-place process before optimizing the process sequence is compared. Figure 8 As shown in the figure, after optimizing the process sequence, the time comparison of the single row pick-and-place process is as follows: Fig. 9 As shown. Figure 8 , 9 The results show that the efficiency of the pick-and-place movement is improved after the process timing is optimized compared with the original working condition. The time taken by the optimized method for the single-row pick-and-place movement of the lead frame board is 3.1s, while the original method takes 3.4s. It can be seen that the process timing optimization can reduce the running time of the pick-and-place process without changing the motion parameters, and improve the spatial operation efficiency by 9.6%, providing a guarantee for improving the placement efficiency.

[0064] After comprehensive analysis of the algorithm, it can be seen that this method can achieve timing optimization of multi-axis linkage on the basis of ensuring safe operation. It shows that the spatial point motion collaborative planning method based on multi-axis timing optimization of the present invention can effectively improve the efficiency of multi-axis linkage, provide technical support for high-speed patch of IC packaging in engineering practice, and play an important guiding role in realizing low-cost chip packaging.

Claims

1. A spatial point motion collaborative planning method based on multi-axis timing optimization, characterized in that: Here are the steps: Step 1: Construction of global motion space model based on bounding box; The motion space of the multi-axis device is modeled based on the bounding box theory, and an circumscribed rectangular bounding box is constructed to determine whether the multi-axis device is within the safe motion range; the placement machine includes a placement machine body and a placement machine moving component, and the placement machine moving component is a pick-up arm; first, based on the contour boundary vertices of the pick-up arm, the convex hull algorithm is used to construct the minimum convex polygon composed of the pick-up arm to ensure that all points of the pick-up arm are within the boundary and interior of the minimum convex polygon; then, the principal component analysis method is used to find the optimal rotation direction of the contour boundary vertices of the pick-up arm, and the boundary of the circumscribed rectangular bounding box is determined according to the optimal rotation direction obtained by the principal component analysis method; According to the mechanical structure and motion constraints of the multi-axis device, the motion range of each degree of freedom of the multi-axis device is abstracted as an independent external rectangular bounding box; after completing the modeling of the external rectangular bounding box, the external rectangular bounding boxes of each single axis are further combined into the global motion space model of the multi-axis device through joint analysis to limit the effective activity range of the multi-axis device in the entire working environment; according to the structural characteristics of the placement machine, in order to avoid the collision between the pick-up arm and the placement machine body in the multi-axis linkage, the external rectangular bounding boxes of the placement machine body and the pick-up arm are respectively constructed through the bounding box theory, so as to establish a spatial relationship model from the chip picking point to the placement point constrained by boundary obstacles; during the chip picking-placing movement, the boundary of the global motion space model is used as a constraint, and the running trajectory of the end of the pick-up arm should be limited to the safety domain of the global motion space model to avoid collision interference; Step 2: Analysis of critical motion trajectories taking into account the safety space; In the chip placement process, the safety space is a restriction on the motion range of the multi-axis equipment. Multi-axis linkage is conducive to reducing the running time from the chip picking point to the chip placement point, but it is necessary to ensure that the position boundary constraints from the chip picking point to the chip placement point do not interfere with the running trajectory; the feasible space boundary is constructed through the shortest safe distance between the pick-up arm and the chip placement machine body; the critical motion trajectory of the multi-axis motion components of the chip placement machine in the safety space is generated by using geometric analysis and dynamic simulation methods; Step 3: Multi-axis motion timing optimization considering critical trajectory space for safe operation; On the basis of determining the critical motion trajectory within the safety space, the goal of the chip mounting process is to improve the mounting efficiency based on ensuring the chip mounting accuracy. The precise Z-axis motion advance amount and the position setting of the spatial safety point during mounting are the key to the multi-axis motion timing optimization. Based on the results of step 2, the multi-axis timing model is constructed to optimize the process timing between multiple axes. Step 4: Multi-axis collaborative trajectory planning based on timing optimization Based on the process timing between multiple axes and combined with the dynamic constraints of the multi-axis equipment, the multi-axis collaborative trajectory is further planned, and the speed curve of each axis is adjusted to synchronize its motion trajectory in time and space to ensure that the actual motion trajectory of the multi-axis equipment meets the task requirements; the multi-axis linkage trajectory is planned based on the key points in the multi-axis motion trajectory to ensure the smoothness and controllability of the trajectory; the collaborative motion trajectory of each axis is converted into executable instructions for the control system to realize the multi-axis linkage operation of the patch equipment.

2. The method for collaborative planning of spatial point motion based on multi-axis timing optimization according to claim 1 is characterized in that: In step 1, the specific implementation process of "using the principal component analysis method to find the best rotation direction of the boundary vertices and determining the boundary of the circumscribed rectangular bounding box according to the rotation direction" is as follows: the best rotation direction is obtained by covariance calculation, and the coordinates of a series of contour boundary vertices of the pickup arm are defined as (x i ,y i ), according to the covariance calculation formula, the covariance is calculated as follows: C ij =Cov(x i ,y i )=E[(x i -u i )(y i -u j )] i,j=1,2,…,n (1) Where E[x] and E[y] are the coordinates x and y respectively. i and i The expected value of C ij Represents the covariance matrix, which is calculated and solved by the following formula: Then, the coordinates of the contour boundary vertices are projected onto the direction vector, and the maximum and minimum values ​​of the x and y components in each direction are recorded as v k min 、v k max , k = 0, 1; the center of the circumscribed rectangular bounding box is obtained by the following formula: In the formula, O represents the center point of the outer rectangular bounding box, P 0 Indicates the direction between two points; The semi-length of the circumscribed rectangular bounding box is calculated as follows:

3. The method for collaborative planning of spatial point motion based on multi-axis timing optimization according to claim 1 is characterized in that: The specific implementation process of Step 2 is as follows: Taking the chip picking point as the origin, the direction from the picking point to the placement point as the Y-axis, and the direction perpendicular to the picking plane as the Z-axis, a YOZ coordinate system is constructed; Ensure that the chip picking and placement process does not interfere with the generation process of the motion trajectory. To avoid the lateral scratching of the chip during picking and the position error during the placement process, during picking, the Z-axis needs to move to the set safety height first, and then the Y-axis moves in联动; During placement, it is necessary to ensure that the Y-axis first crosses the constrained area of the placement machine carrier track to reach a safe position, and then the Z-axis reaches the placement position height and completes the placement instruction; In the safe space, reasonably planning the multi-axis linkage trajectory and determining the motion timing of the multi-axis linkage is the key to reducing the unnecessary running time during the picking and placement space linkage motion process; Ensure that the picking and placement space linkage motion process with obstacle constraints is carried out through the following process: ①Boundary interference check at the chip picking position. The constraint boundary is constructed by the bounding box theory. The key vertex coordinates of the placement machine are marked as (R, 0) and (R, H1), and the straight line formed by the key vertices is used as the boundary; when the Y and Z axes are running in linkage, for a given Y axis motion parameter (J y ,a y ,v y ,x y ), calculate the Y axis to reach x y = time t1 at the position of R; given Z axis motion parameters (J z ,a z ,v z ,x z ), calculate the height x of the Z axis at time t1 z (t1); ②Judge x z (t1) and the relationship with H1. When x z (t1) > H1, there is no interference in the biaxial linkage at the film taking position, go to ④; when x z (t1) < H1, there will be interference in the biaxial linkage, and it is necessary to update and calculate the Z-axis advance running time, go to ③; ③ Calculate the time t2 required for the Z-axis to move to the H1 plane, and determine the advance amount Δt = t2 - t1 of the Z-axis movement; ④ Interference check of the boundary at the patch position to determine the constraint boundary; calculate the time T when the Z-axis reaches the highest point z , at this time, the running distance x of the Y-axis y (T z ); The length of the obstacle boundary in the Y direction is denoted as L. If x y (T z ) > R + L, the Z-axis can directly return; if x y (T z ) < R + L, it is necessary to further calculate the time T z,place when the Z-axis returns to the H1 plane, that is, the time for reverse running of height h. At this time, the total running time of the corresponding Y-axis is t_y = T z + T z,place , and the running position of the Y-axis is dis_y; ⑤ Judge the relationship between dis_y and R + L: If dis_y > R + L, the Z-axis can directly return to meet the constraint conditions and end; If dis_y < R + L, the Z-axis needs to return with a delay, and the delay time needs to be determined, go to ⑥; ⑥ Calculate the time t3 when Y reaches R+L, that is, when it leaves the constraint, and then calculate the time T when the Z axis drops to the constraint height h z,place , the time delay is Δt_r=t3-T z,place -T_z; According to the above picking and placement space linkage motion process, considering the total time of the picking and placement linkage process with obstacle constraints is calculated as: T=2(Δt +T y +T z,place +Δt_r)+T place +T pick (5) Where, T y Indicates the time of Y-axis operation, T place and T pick The time required for taking and applying the patch is respectively.

4. The method for collaborative planning of spatial point motion based on multi-axis timing optimization according to claim 1 is characterized in that: In Step 3, use Step 1 to analyze the key points and smooth paths at the end of the picking arm during the picking and placement motion. The key points include the picking point, the space safety point, and the placement point, and use Step 2 to analyze the impact of multi-axis motion on the placement task efficiency; Based on the placement task requirements and the motion characteristics of multi-axis equipment, establish a mathematical optimization model for multi-axis linkage efficiency. With the goal of improving multi-axis linkage efficiency, construct an objective function for minimizing time, and use speed, acceleration, and path continuity as constraint conditions to ensure the high efficiency and stability of the placement motion process. The mathematical optimization model is as follows: Where, T represents the total time of the chip removal-chip placement linkage process; v i 、a i , Δp i Respectively represent the speed, acceleration and trajectory continuity of each axis; v max 、a max They represent the maximum value constraints of velocity and acceleration, Δp max represents the continuity constraint of the trajectory; t i Indicates the time of each process in multi-axis coordinated motion.

5. The method for collaborative planning of spatial point motion based on multi-axis timing optimization according to claim 3 is characterized in that: Use the genetic algorithm or particle swarm algorithm to effectively solve the objective function through initializing random solutions, iterative optimization, and convergence judgment, calculate the optimal motion timing allocation of multiple axes, find the optimal allocation scheme for the motion time of each axis, and ensure that each axis reaches the optimal coordination state in time.

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