TWI524162B - Spatial Machining Path Trajectory Smoothing Algorithm - Google Patents

Description

Spatial processing path trajectory smoothing algorithm

The invention relates to an algorithm for processing a workpiece, in particular to an algorithm which can improve the similarity of adjacent machining paths, avoid uneven machining marks on the workpiece, or reduce the surface smoothness of the workpiece.

The competitiveness of modern industry is becoming more and more fierce. How to improve production efficiency has become the focus of attention of all enterprises. With the advancement of technology, the performance of computer hardware is becoming more diversified and the price is decreasing, so various industries gradually use computers. Auxiliary design (CAD) is a process of computer software production and simulation of physical design, showing the appearance, structure, color, texture and other characteristics of newly developed products.

The designed product, computer-aided design (CAD) and computer-aided manufacturing (CAM), generates a CNC machining program for the computer numerical control (CNC) machine tool according to the contour curve of the product, thereby shortening Write the time of the CNC machining code and increase the output of the product.

Although computer-aided design (CAD) and computer-aided manufacturing (CAM) can quickly generate CNC machining code, on the finished product, there will be obvious knife marks on the surface, making the surface smoothness of the finished product not in line with the market. The demand, therefore, often requires more time and cost to process the surface, so that the surface of the product meets market demand, causing inconvenience to the manufacturer.

In view of this, the traditional CNC machining programs generated by computer-aided design (CAD) and computer-aided manufacturing (CAM) still have shortcomings in the processed products. It is necessary to improve and innovate an algorithm to target The processing program is smoothed to improve the smoothness of the surface of the product.

The main purpose of the present invention is to smooth the tool path of the machining program generated by computer-aided design (CAD) and computer-aided manufacturing (CAM), improve the similarity of adjacent processing paths, and avoid the surface of the product after processing. Inhomogeneous tool marks or insufficient smoothness of the product surface.

To achieve the above objective, the spatial processing path trajectory smoothing algorithm of the present invention comprises the steps of: providing a spatial filter to read a processing code, and removing a processing path in the processing code that is not cut; the spatial filtering Calculating an average width between the processing paths; the spatial filter finding a peripheral contour of the processing path; wherein the spatial filter calculates a length and a width of the peripheral contour, and the processing path is determined by a length and a width of the peripheral contour The average width calculates a mesh model composed of a plurality of mesh nodes, and the one-axis X-axis coordinate value of the mesh node and the Y-axis coordinate value of the other point cooperate with the average width and the plurality of mesh nodes. Calculating the X-axis coordinate value and the Y-axis coordinate value of all the above-mentioned mesh nodes; the spatial filter calculates the arc portion in the above-mentioned processing path and represents it by a plurality of short straight lines; the above spatial filtering The above average width is used to segment the length of the single block instruction in the above processing code, and the point is increased. The amount of information. The spatial filter calculates a Z-axis coordinate value of the mesh node by using an X-axis coordinate value and a Y-axis coordinate value of the mesh node; and the spatial filter performs a first smoothing on a Z-axis coordinate value of the mesh node. And obtaining a Z-axis coordinate smoothing value; and the spatial filter performs a second smoothing process on the coordinate data of the processing path by using the smoothed value of the Z-axis coordinate to obtain the smoothed processing program code.

The spatial filter converts the arc portion of the machining path into the plurality of short straight lines by the interpolation principle. In addition, in the process of the equal length segmentation described above, if the length of the single block command is less than the average width, no segmentation is required.

Furthermore, the spatial filter described above uses the convex hull concept to find the peripheral contour of the processing path. The convex hull concept includes the following steps: (a) the spatial filter uses the convex hull concept to find the left end point and the right end point of the processing path point coordinate, and divide all the coordinates of the processing path into the upper part and The lower half; (b) the spatial filter establishes a convex sag coordinate register, and the embossed coordinate coordinate register has a point coordinate data of one of the left end or the right end; (c) according to the contour The direction sequentially finds the unprocessed point coordinate data. If there is only one point coordinate data inside the convex sag coordinate register, the found coordinate data is directly stored in the stacking point coordinate register, and finally Repeating step (c); (d) calculating a first vector from the point coordinate data found in step (c) and the last stacked second coordinate point data in the convex sag coordinate register, and then The second vector is calculated by the last-numbered coordinate data of the last stack and the second-point coordinate data of the last stack in the convex sag coordinate register, and the second vector is subjected to an outer product operation with the first vector to obtain an outer product value. If the value is equal to or less than zero, the coordinate data of the above point is stored in the stacking manner in the convex point coordinate register, and finally returns to step (c); if the outer product value is less than zero, the convex point coordinate register will be the last one. The coordinate data of the point coordinate is removed. After the removal, the convex point coordinate register has only one coordinate data, and the found coordinate data is stored in the stack at the end of the convex point coordinate register, and then returned. Step (c), and vice versa, if the convex hull coordinate register has more than two coordinate coordinates, then return to step (d); (e) finally the convex sag coordinate register If the last coordinate point data is the coordinate point data of one of the left end point and the right end point, the convex contour of the upper half or the lower half is searched for completion.

The invention is characterized in that the spatial filter is provided to read the processing code, the uncut machining path in the machining code is removed, and the average width, the peripheral contour and the width and length of the peripheral contour between the machining paths are calculated, and then the outer periphery is passed. The width and length of the contour and the average width of the machining path are calculated as a mesh model composed of a plurality of mesh nodes, and the X-axis coordinate value of the mesh node is further obtained. The coordinate value of the axis and the coordinate value of the Z axis. Finally, the Z-axis coordinate value is smoothed for the first time, and the smooth value of the Z-axis coordinate is obtained, and the coordinate data of the machining path is used for the second time by the Z-axis coordinate smoothing value. Smoothing process can be used to obtain the smoothed machining code. Thereby, the similarity of the processing paths is improved, and after processing, unevenness of the tool marks on the surface of the product or insufficient smoothness of the surface of the product is avoided.

10‧‧‧ Spatial Filter

11‧‧‧Convex point coordinate register

20‧‧‧Processing code

21‧‧‧Processing path

22‧‧‧Outer contour

30‧‧‧ mesh model

31‧‧‧ mesh nodes

1 is a flow chart of the steps of the spatial processing path trajectory smoothing algorithm of the present invention; FIG. 2 is a schematic diagram of the spatial filter reading processing code of the present invention; FIG. 3 is a schematic diagram of the processing path of the present invention; 5 is a schematic diagram of the concept of a convex hull according to the present invention; FIG. 6 is a schematic diagram of a mesh model calculated by the spatial filter of the present invention; FIG. 7 is a schematic diagram showing a circular arc represented by a straight line in the spatial filter of the present invention; The present invention calculates a schematic diagram of an angular increment; FIG. 9 is a schematic diagram of a mesh node and a processing coordinate of the present invention; FIG. 10 is a mesh node with a mask constant set to 1 according to the present invention; and FIG. 11 is a spatial filtering of the present invention. The schematic diagram of the smoothed processing code is obtained.

In order to further clarify and understand the structure, the use and the features of the present invention, the preferred embodiment is described in detail with reference to the following drawings:

Referring to FIG. 1 , the spatial processing path trajectory smoothing algorithm of the present invention provides a spatial filter 10 to complete smoothing of a processing code 20, including the following steps:

a. providing the above spatial filter 10 to read the above processing code 20, as shown in the figure, The machining program code 20 includes a plurality of program line numbers (N00 to N10), machining commands (G01, G02, G03), and point coordinate data (Xa0 Yb0 Zc0) of the machining path 21.

Referring to FIGS. 2 and 3, after the spatial filter 10 is read, the spatial filter 10 removes the processing path 21 of the processing code 20 that is not cut, in the preferred embodiment of the drawing. The spatial filter 10 removes the above program line numbers N00 and N10, and retains the above program line numbers N01 to N09.

b. The spatial filter 10 calculates the width of the two adjacent processing paths 21, and adds the widths of all the two adjacent processing paths 21 together, and divides the total number of the two adjacent processing paths 21 to obtain the above. The average width between the processing paths 21.

c. The spatial filter 10 described above finds the peripheral contour 22 of the processing path 21 via calculation. In the preferred embodiment, the spatial filter 10 finds the peripheral contour 22 of the processing path 21 by using the convex hull concept. Referring to FIG. 4 and FIG. 5, the following steps are included:

(a) The spatial filter 10 finds the left end point and the right end point of the coordinate point 21 of the processing path 21, as shown in the figure, point A and point G, and then connects the left end point to the right end point to make the processing path 21 All point coordinates are divided into the upper half and the lower half. In this embodiment, the peripheral contour 22 of the lower half is first sought.

(b) Before the spatial filter 10 finds the peripheral contour 22 of the lower half, a convex point coordinate register 11 is first established, wherein the convex point coordinate register 11 has the left end (point A) Point coordinates information.

(c) The spatial filter 10 sequentially finds unprocessed point coordinate data (point B to point G) according to the contour direction, wherein if the convex sag coordinate register 11 has only one point coordinate data inside, The next found coordinate data is stored in the stack in the above convex point coordinate register. 11, repeat step (c).

(d) The spatial filter 10 calculates the point coordinate data (point C) found in the step (c) and the last penultimate point coordinate data (point A) in the innermost stacking of the convex point coordinate register 11 a vector And the vector direction of the first vector is pointed to the found point coordinate data (point C) by the last penultimate point coordinate data (point A) of the last stacking inside the convex cryptographic coordinate register 11; The second point vector (the point B) and the second point coordinate data (point A) of the last stack of the last stack in the coordinate point register 11 calculate the second vector ( And the vector direction of the second vector is pointed to by the last penultimate coordinate data (point A) of the last stack of the convex point coordinate register 11 to point to the first point coordinate data (point B), and then The spatial filter 10 performs an outer product operation on the second vector and the first vector.

If the obtained outer product value is greater than zero or equal to zero, the point coordinate data (point C) found by the spatial filter 10 is stored in the stacking manner in the convex sag coordinate register 11 and then returns to step (c).

If the obtained outer product value is less than zero, the spatial filter 10 removes the last point coordinate data (point B) in the convex sag coordinate register 11 and removes the spatial filter 10 after the spatial filter 10 is removed. The point coordinate data (point C) is stored in a stacked manner in the convex sag coordinate register 11 and returns to step (c). On the other hand, after the point coordinate data (point B) is removed, if there are two point coordinate data in the convex burr coordinate register 11 or more, the process returns to step (d).

(e) when the spatial filter 10 continuously searches for unprocessed point coordinate data until the convex sag coordinate register 11 accesses the point coordinate data of the right end point (point G), the spatial filter 10 stops. Find the point coordinates of the lower half contour 22 of the lower half. Therefore, after the spatial filter 10 stops searching for the point coordinates of the lower half contour 22, the convex point coordinate register 11 sequentially connects the accessed coordinate data to complete the lower half. Peripheral contour 22.

In accordance with the same steps, the peripheral contour 22 of the upper half is found. Finally, the spatial filter 10 will combine the lower peripheral contour 22 and the upper peripheral contour 22 to form the complete peripheral contour 22.

d. Referring to FIG. 6, the spatial filter 10 calculates the width of the peripheral contour 22 from the upper end point and the lower end point of the peripheral contour 22, and calculates the outer contour from the right end point and the left end point of the peripheral contour 22. The length of 22, and select a maximum from the length and width, and this value is defined as the maximum value of the contour.

The length and width of a mesh model 30 can be obtained by multiplying the contour maximum value by a double boundary ratio by the spatial filter 10 and adding the length and width of the peripheral contour 22, respectively. In this embodiment, the boundary ratio is set to 0.05. However, the boundary ratio is set to 0.05 for convenience of explanation, and the boundary ratio may be set to a different value by different use conditions.

The spatial filter 10 divides the length and the width of the mesh model 30 by the average width, and adds 1 to the unconditional carry program, so that the mesh model 30 generates a plurality of mesh nodes 31, and then the network The length and width of the lattice model 30 are respectively divided by the number of horizontal nodes of the mesh node 31 minus 1 and the number of longitudinal nodes is decreased by 1, so that the X-axis direction and the Y-axis direction between the plurality of mesh nodes 31 can be obtained. Long width. Then, the X-axis coordinate value and Y of all the above-mentioned mesh nodes 31 are calculated by the pitch length of one of the X-axis coordinate values of the mesh node 31 and the Y-axis coordinate value of the other point in cooperation with the pitch length between the plurality of mesh nodes 31. Shaft coordinate value.

In this embodiment, the length (or width) of the mesh model 30 and the average width of the adjacent processing path 21 are 1 mm and 0.3 mm, respectively, and the length (or width) of the mesh model 30 is divided by the average. Width, after adding 1 to the unconditional carry program, the above-mentioned mesh node 31 of 5×5 can be obtained, and the distance between the plurality of mesh nodes is 0.25 mm, and then the above spatial filtering is performed. 10 subtracts the X-axis coordinate value of the left end point of the peripheral contour 22 from the Y-axis coordinate value of the lower end point of the peripheral contour 22, respectively, and subtracts the contour maximum value of the peripheral contour 22 by the boundary ratio, and the obtained values are respectively The X-axis coordinate value of the left endpoint of the lattice model 30 and the Y-axis coordinate value of the lower endpoint. The other adjacent mesh nodes 31 differ in the X-axis and Y-axis directions by the pitch length between the plurality of mesh nodes 31. Therefore, the X-axis coordinate value of the left end point of the mesh model 30 and the Y of the lower end point are The X-axis coordinate value and the Y-axis coordinate value of all the mesh nodes 31 can be calculated by matching the axis coordinate value with the pitch length between the plurality of mesh nodes 31.

e. Referring to FIGS. 7 and 8 , for the convenience of calculation of smoothing, the spatial filter 10 converts the arc portion of the machining path 21 into a complex number by using the angular increment after the calculation. The short straight lines indicate that, in a preferred embodiment, the spatial filter 10 converts the arc portion of the machining path 21 into the plurality of short straight lines by interpolation with the angular increment.

The above interpolation principle is in accordance with the relational expression of the angle increment; as follows (DX _i , DY _i )=f(α, θ, X _i , Y _i )

Endpoint short pitch line; α:: wherein, DXi, DYi angular increments; S, E: starting and ending points of the arc (see FIG section 7); θ: angle of the arc Xi, Yi: short The starting endpoint coordinate of the line.

The spatial filter 10 is matched with the angle increment ( α ) from the starting point of the arc by the interpolation principle described above, and the discrete point data of the arc portion of the machining path 21 is calculated. In the preferred embodiment, the angle increment is determined by the set value ( ε ) of the chord error and the radius of the arc, and the relationship between the angle increment, the set value of the chord error, and the radius of the arc exists. , as shown below: α=f(ε,R)

Where α : angle increment; ε : set value of string error; R: arc radius.

After the angle increment ( α ) is obtained by the above calculation formula, the spatial filter 10 divides the arc angle ( θ ) by the angle increment to obtain a multiple value, and if the multiple value has a decimal point, the spatial filter 10 will the decimal value is rounded down multiple, incremental angle ([alpha]) after the arc angle ([theta]) is divided by a multiple of the adjustment worth of the angle increment ([alpha]) after the adjustment is approximately linear short arc Number of. For example, when the arc angle is 33 degrees, and the angle increment obtained by setting the string error calculation is 10 degrees, the value obtained by dividing the arc angle by the angle increment is unconditionally discarded. Times, then divide the arc angle by the multiple value to get the adjusted angle increment by 11 degrees, and then divide the arc angle by the adjusted angle increment. Therefore, the number of short straight lines that approximate the arc is 3 segments.

f. In order to make the mesh model 30 more similar to the actual machining contour, a large amount of point coordinate data is required, and the spatial filter 10 uses the average width to equally divide the length of the single block command in the processing code 20 Segment, increase the number of coordinates of the point. In the process of equal segmentation, if the length of the block instruction is less than the average width, no segmentation is required; otherwise, the length of the block instruction is equally divided by the average width, if the length of the block instruction is not the above If the multiple is the multiple of the average width, the length of the last segment will be smaller than the average width. For example, the length and average width of the single-segment command are 10.5mm and 1mm. After equal segmentation, 11 segments will be generated, and the first 10 segments will be generated. The length is 1mm, and the last segment is 0.5mm. Therefore, the point coordinate data of the single length will change from 2 to 12 points.

g. The spatial filter 10 is represented by the X-axis coordinate value and the Y-axis of the mesh node 31 described above. The coordinate value calculates the Z-axis coordinate value of the above-described mesh node 31. Referring to FIG. 9, the X-axis coordinate value and the Y-axis coordinate value of the mesh node 31 are obtained by the step d, and the spatial filter 10 uses the coordinates of the mesh node 31 (circle of FIG. 9). The value data finds the three-point coordinate data (the triangle of FIG. 9) closest to the above-mentioned mesh node 31 on the above-mentioned processing path 21 (the thick solid line of FIG. 9), and is calculated from the three-point coordinate data. a plane equation (z=f(x, y)), assuming that the grid node 31 is on the plane, the X-axis coordinate value and the Y-axis coordinate value of the grid node 31 are input into the plane equation, and the above-mentioned equation can be obtained. The Z-axis coordinate value of the mesh node 31.

For example, assume that the coordinates of the three point coordinates closest to the mesh node 31 are (x, y, z) = (-1, 0, 0.5), (x, y, z) = (1, 1, 1) and (x, y, z) = (1, -1, 1), using the coordinate data of the three points to calculate the plane equation The X-axis coordinate value of the mesh node 31 and the Y-axis coordinate value "(x, y) = (0, 0)" are input to the plane equation, and the Z-axis coordinate value of the mesh node 31 is obtained. Therefore, the coordinate point data of the above-mentioned mesh node 31 is .

h. Referring to FIG. 10, the spatial filter 10 performs a first smoothing process on the Z-axis coordinate value of the mesh node 31, and obtains a smoothed value of a Z-axis coordinate. Referring to FIG. 10, in the preferred embodiment, the spatial filter 10 sets a mask constant for performing a first smoothing process on the Z-axis coordinate value of the mesh node 31. In this embodiment, the mask constant is set to 1, and the process of the first smoothing process is started. The spatial filter 10 first centers on one mesh node 31 (M5 shown in FIG. 10). And the Z-axis coordinate average of the eight mesh nodes 31 (M1~M4 and M6~M9 shown in FIG. 10) is obtained, and the mesh node 31 (M5 shown in FIG. 10) is in the After one smoothing process, it is known that the smoothed value of the Z-axis coordinate, the average value of the Z-axis coordinate, and the mesh node 31 (M5 shown in Fig. 10) have the following relationship, as follows: Z ' _M5 = f(Z _avg , Z _M5 , β)

Where Z'M5: the smoothed value of the Z-axis coordinate of the center of the mesh node 31; Zavg: the average value of the Z-axis coordinates of the surrounding eight mesh nodes 31; ZM5: the Z-axis coordinate value of the center of the mesh node 31; And β is a proportional coefficient.

As shown in the figure, it is assumed that the Z-axis coordinate value (Z _M5 ) of the central mesh node 31 is 0.9 mm, and the Z-axis coordinate values of the adjacent eight mesh nodes 31 (M1 to M4 and M6 to M9) are 0.7. Mm, after calculation, the Z-axis coordinate average (Zavg) is 0.7mm, then the proportional coefficient ( β ) is set to 0.8. According to the above formula, the central mesh node 31 (M5) can be calculated after the first smoothing process. The smoothed value (Z'M5) of the latter Z-axis coordinate is 0.86 mm. It can be seen from the results that the Z-axis coordinate smoothing value (Z'M5) obtained by the center mesh node 31 (M5) after the first smoothing process is close to the Z-axis coordinate average value of the surrounding mesh node 31 (Zavg ), the z-axis coordinate values of the nine mesh nodes 31 are relatively similar to achieve the smoothing effect. Therefore, the Z-axis coordinate smoothing values of all the mesh nodes 31 after the first smoothing process can be obtained by sequentially calculating in the order of the mesh nodes 31 described above.

As shown in the figure, since the five mesh nodes 31 (M1 to M4 and M7) in the mesh model 30 are located at the outermost edge of the mesh model 30, and the number of adjacent nodes is less than 1, the processing is not affected. As a result of the smoothing of the path 21, the five mesh nodes 31 (M1 to M4 and M7) in the mesh model 30 are not subjected to the first smoothing process.

i. In order to perform the first smoothing process of all the mesh nodes 31 described above without changing the original X-axis and Y-axis machining paths 21 and achieving the smoothing of the above-described machining path 21, the spatial filter 10 performs the above-described processing. The point coordinate data of the path 21 is subjected to the second smoothing process in accordance with the Z-axis coordinate smoothing value, and the Z-axis coordinate value of the machining path 21 is sequentially smoothed, and the smoothed processing code 20 is obtained. Referring to Fig. 11, the X-axis coordinate value and the Y-axis coordinate value ((X, Y) = (0.3, 0.2)) of the point coordinate data (the triangle of Fig. 11) of the above-described processing path 21 are used to find the neighborhood. The four mesh nodes 31 (circles M1 to M4 in Fig. 11) can be used to obtain the Z-axis coordinate value (Z1234) of the above-mentioned processing path 21 after the second smoothing process in accordance with the following relationship.

Wherein, Z1234 is a Z-axis coordinate value obtained by the second smoothing process; , , versus The Z-axis coordinate values of M1, M2, M3, and M4 in the mesh node 31 are respectively; Lx and Ly are the maximum X-axis and Y-axis distances of the four mesh nodes 31 in the figure respectively; Δx and △ y is the X-axis distance and the Y-axis distance of the point coordinate data of the above-mentioned processing path 21 from the mesh node 31 (M1).

For example, assume that the point coordinates (X, Y, Z) of the mesh nodes 31 (M1 to M4) are M1 (0.0, 0.0, 0.8), M2 (0.5, 0.0, 0.7), and M3 (0.0, respectively). 0.5, 0.7) and M4 (0.5, 0.5, 0.8), brought into the above formula, calculated and obtained versus And then will find it again versus Bring into the above formula and find Z1234=0.748. Z1234 is the Z-axis coordinate value obtained by the second smoothing process. Therefore, the smoothed processing code 20 can be obtained in accordance with steps a to i.

In summary, the present invention reads a machining program code by providing a spatial filter, removes an uncut machining path in the machining code, and calculates an average width, a peripheral contour, and a peripheral contour width between the machining paths. Length, and then calculate the mesh model composed of a plurality of mesh nodes through the width, length and average width of the peripheral contour, and further obtain the X-axis coordinate value, the Y-axis coordinate value and the Z-axis of the mesh node. Coordinate value, finally smoothing the Z-axis coordinate value for the first time, and obtaining the smoothed value of the Z-axis coordinate value, and then smoothing the coordinate data of the processing path for the second smoothing process, The smoothed processing code. Thereby, the similarity of the processing paths is improved, and after processing, unevenness of the tool marks on the surface of the product or insufficient smoothness of the surface of the product is avoided.

The above embodiments are intended to be illustrative only, and are not intended to limit the scope of the present invention. It is included in the scope of the following patent application.

Claims (7)

A spatial processing path trajectory smoothing algorithm includes the following steps: providing a spatial filter to read a processing code, and removing a processing path in the processing code that is not cut; the spatial filter calculating the processing path The average width between the two; the spatial filter finds a peripheral contour of the processing path; the spatial filter calculates the length and width of the peripheral contour, and calculates the length and width of the peripheral contour and the average width of the processing path a mesh model consisting of a plurality of mesh nodes, wherein the one-axis X-axis coordinate value of the mesh node and the Y-axis coordinate value of the other point cooperate with the average width and the length of the space between the plurality of mesh nodes Calculating an X-axis coordinate value and a Y-axis coordinate value of all the mesh nodes; the spatial filter calculates a Z-axis coordinate value of the mesh node by using an X-axis coordinate value and a Y-axis coordinate value of the mesh node; The spatial filter performs a first smoothing process on the Z-axis coordinate value of the mesh node, and obtains a Z-axis coordinate smoothing value; And said second spatial filter for smoothing process coordinate data of the machining path by the Z-axis coordinate value smoothing, the machining obtain smoothed code. The spatial processing path trajectory smoothing algorithm according to claim 1, wherein the spatial filter calculates a Z-axis coordinate value of the mesh node by using an X-axis coordinate value and a Y-axis coordinate value of the mesh node. Previously, the above spatial filter calculates the arc portion in the above-described machining path and represents it by a plurality of short straight lines. The spatial processing path trajectory smoothing algorithm according to claim 2, wherein the spatial filter converts the arc portion of the processing path into the plurality of short straight lines by an interpolation method. The spatial processing path trajectory smoothing algorithm according to claim 2, wherein the spatial filter uses the average width after the arc portion of the processing path is calculated and represented by a straight line. The length of the single block instruction in the above processing code is equally divided to increase the number of point coordinates. The space processing path trajectory smoothing algorithm according to claim 4, wherein in the process of the length equal segmentation, if the length of the single block command is less than the average width, no segmentation is needed. The space processing path trajectory smoothing algorithm according to claim 1, wherein the spatial filter finds a peripheral contour of the processing path by using a convex hull concept. The spatial processing path trajectory smoothing algorithm according to claim 6, wherein the convex hull concept comprises the following steps: (a) the spatial filter uses the convex hull concept to find the left end point of the processing path point coordinate And the right end point, and all the coordinates of the above processing path are divided into an upper half and a lower half; (b) the spatial filter establishes a convex point coordinate register, and the convex point coordinate register has an internal Point coordinate data of one point of the left end point or the right end point; (c) sequentially find the unprocessed point coordinate data according to the contour direction, and if there is only one point coordinate data inside the convex point point coordinate register, the found point coordinate The data is directly stored in the stacking point coordinate register in the above-mentioned convex point, and finally the step (c) is repeated; (d) calculating a first vector from the point coordinate data found in step (c) and the last stacked second coordinate point data in the convex sag coordinate register, and then using the convex sag coordinate register Calculating a second vector from the last-numbered coordinate data of the last stack and the second-point coordinate data of the last stack, and the second vector is subjected to an outer product operation with the first vector, and the obtained outer product value is greater than or equal to zero, then the coordinate data of the point coordinates Stored in the stacking point coordinate register in the above manner, and finally returned to step (c); if the outer product value is less than zero, the convex point coordinate register temporarily removes the last point coordinate data, and after removing If the embossed point coordinate register has only one point coordinate data, the found coordinate data is stored in a stack manner at the end of the convex sag coordinate register, and then returns to step (c), otherwise, the removal is performed. After the embossed point coordinate register has more than two coordinate data, it returns to step (d); (e) finally, the last coordinate point information in the convex sag coordinate register is the left end The coordinates of one point of the point and the right end point Data, then the convex hull profile to find top or bottom half of the end.