JPH0778425B2 - Three-dimensional data interpolation method - Google Patents

Description

Description: TECHNICAL FIELD The present invention relates to a three-dimensional data interpolation method for point cloud data in a three-dimensional space obtained by a three-dimensional position measuring machine or the like.

(Prior Art) A contact point of a model shape can be obtained by bringing a probe such as a three-dimensional position measuring machine into contact with the model surface with one axis fixed and scanning the model surface a plurality of times at predetermined intervals. it can. For example, as shown in FIG. 5, the X-axis is fixed, the scanning (measuring) direction is the Y-axis direction, the probe is scanned 7 times at the measurement interval a, and predetermined interpolation is performed to obtain the point cloud data of the black circles in the figure. Can be obtained. In this point cloud data, each point is connected as a series of fine straight line sections in the measurement direction (S ₁ , S ₂ , ..., S _{7 in the} figure), whereas there is no connection in the direction orthogonal to the measurement direction. No information given. Therefore, when the inclination in the direction orthogonal to the measurement direction is small (θ ₁ , θ ₂ , θ ₄ , θ ₅ , θ _{6 in the} drawing), sufficient shape accuracy can be obtained, but when the inclination is large (in the illustration, θ ₃ ) has a problem that the point cloud data density is relatively lowered (between S ₃ and S _{4 in the} figure), and the shape accuracy is deteriorated. Therefore, in order to improve the shape accuracy of the portion where the point cloud data density is reduced, a method has been adopted in which the measurement interval is narrowed to b to obtain the point cloud data, as shown in FIG. 6, for example.

(Problem to be Solved by the Invention) In the above-described method, there is a sufficient effect in a portion where the point cloud data density is reduced, but there is a disadvantage that the amount of point cloud data is unnecessarily increased in other portions. was there. In addition, there is also a problem that the measurement time is too long because the measurement distance is increased.

The present invention has been made under the circumstances as described above, and an object of the present invention is to provide a three-dimensional data interpolation method capable of rapidly obtaining point group data representing sufficient shape accuracy for various model shapes. To provide.

(Means for Solving the Problem) The present invention relates to a three-dimensional data interpolation method for point group data in a three-dimensional space obtained by a three-dimensional position measuring machine or the like. 3 obtained by scanning the model surface multiple times at a predetermined interval
The point cloud data of the dimensional space is input, and connecting lines with points on the line connecting each point of one point cloud data of one point scan data of one adjacent scan to each point of the other point cloud data, respectively. This is achieved by obtaining and creating virtual interpolation point group data on each obtained connecting line.

(Operation) Since the three-dimensional data interpolation method of the present invention creates virtual point group data within the measurement interval, even if there is a portion having a large inclination in the direction orthogonal to the measurement direction, the point of that portion It is possible to prevent a decrease in the group data density and perform the measurement in a short time.

(Embodiment) FIG. 1 is a block diagram showing an example of an apparatus that realizes the three-dimensional data interpolation method of the present invention. Point cloud data measured by a three-dimensional position measuring machine or the like according to a command from the operation panel 1. Is input to sequentially store the point cloud data S _i (i = 1, 2, ...) For one scan in the point cloud data memory 3, and the point cloud data S _i-1 , for adjacent one scan are stored. The point on the straight line group having the shortest distance from each point of the one point cloud data of S _i to the straight line group connecting two adjacent points of the other point cloud data is obtained, and the point having the shortest distance is obtained. Each bond line C _ik (k = 1,2, ...)
The connection information CT _m (m = 1, 2, ...) _{Composed of} is obtained and sequentially stored in the connection information memory 4, and virtual interpolation point group data DP _ijk ”(j = 1, on the obtained connection line C _ik . 2, ...; k = 1,2, ...) is created and sequentially stored in the interpolation point cloud data memory 5, and numerical control data is created and output based on the created interpolation point cloud data DP _ijk. It is configured by the processing device 2.

In such a configuration, its operation will be described with reference to the flowchart of FIG. 2 and the example of the point cloud data of FIG. 3. The operation device 1 measures the operation device 2 with a three-dimensional position measuring machine or the like in accordance with a command. The point cloud data for one scan is read from the point cloud data and stored in the point cloud data memory 3 (step S1),
It is confirmed whether or not the point cloud data is the first line (step S2). If the point cloud data is the first line, the process returns to step S1 and the above-described operation is repeated. On the other hand, in the decision step S2, if the data point group I read is not the first run, the front Kaidoku elaborate point cloud data S _i-1 and now Kaidoku elaborate point cloud data S _i of one of the point group data, For example S _i-1
From point Q ₃ (P ₃ ) on (S _i ) to the other point cloud data S _i (S _i-1 )
For all points, the operation of finding the connecting line C _i3 (C _i4 ) by finding the point P ₃ ′ (Q ₃ ′) on the other point cloud data S _i (S _i-1 ) with the shortest distance to The connection information CT _m composed of the obtained connection lines C _ik is sequentially stored in the connection information memory 4 (step S3). It should be noted that at points that are clearly recognized as corners of the shape (for example, P ₂ and Q ₂ ), at start points (for example, P ₁ and Q ₁ ) and end points (for example, P ₄ and Q ₄ ) of the point cloud data. The connecting lines are C _i1 , C _i2 , and C _{i5 in} which the points are connected without obtaining the shortest distance. Then, virtual interpolation point group data DP _ijk is created on the obtained connecting line C _ik and sequentially stored in the interpolation point group data memory 5 (step S4). Then, it is confirmed whether or not all the point cloud data is finished (step S5). If all the point cloud data is not finished, the procedure returns to step S1 and the above-mentioned operation is repeated, and the all point cloud data is finished. In this case, the numerical control data is generated and output based on the created interpolation point group data DP _ijk , and all the processes are ended.

FIG. 4 is point cloud data showing the case where the method of the present invention is applied to the point cloud data shown in FIG. 5, and the broken line connecting the black circles and the black circles and the broken line connecting the black circles and the X marks are the connecting lines. The white circles on each connecting line indicate the newly interpolated point group data.
As described above, it is possible to obtain the point cloud data with high shape accuracy, although the point cloud data is obtained by the same measurement.

As described above, according to the three-dimensional data interpolation method of the present invention,
Since it is possible to quickly obtain point cloud data with high shape accuracy for various model shapes, it is possible to improve productivity and supply products with high processing accuracy at low cost.

[Brief description of drawings]

FIG. 1 is a block diagram showing an example of an apparatus for realizing the three-dimensional data interpolation method of the present invention, FIG. 2 is a flow chart for explaining its operation, and FIG. 3 is point cloud data for explaining the interpolation method of the present invention. FIG. 4 is a perspective view showing an example of point cloud data to which the interpolation method of the present invention is applied, and FIGS. 5 and 6 show an example of point cloud data by the conventional interpolation method. It is a perspective view. 1 ... Operation panel, 2 ... Processing device, 3 ... Point cloud data memory, 4 ... Combined information memory, 5 ... Interpolation point cloud data memory.

Claims (1)

[Claims] 1. Point cloud data of a three-dimensional space obtained by scanning a probe on a model surface a plurality of times at predetermined intervals, and inputting one point cloud of the point cloud data for one adjacent scan. It is characterized in that a connection line with each point of the data and a point on the line connecting each point of the other point cloud data is obtained, and virtual interpolation point cloud data is created on each obtained connection line. Three-dimensional data interpolation method.