Method for realizing automatic planning of measurement points

Abstract

The invention provides a method for realizing automatic planning of a measurement point. The method comprises the following steps: converting CAD drawing data into picture data and preprocessing the picture data; all house type doors are closed through a robot automatic door closing algorithm; any pixel point in the house type is clicked; automatically traversing point locations around the clicked coordinates by using a robot house type detection algorithm to obtain all RGB same point locations, extracting all traversed point locations, redrawing an internal space, and creating a new measurement point stack; based on a robot measurement point generation algorithm, all contours in a picture are automatically recognized, the number of current contours is recorded, contour areas are sorted, the center coordinates of the minimum contour are obtained, RGB numerical modification is conducted on all point positions of the minimum contour, then all contours in the picture are automatically recognized, the number of the current contours is recorded, and the contour areas are sorted. According to the invention, the measurement robot can be helped to realize automatic planning of the measurement point, manual participation is not needed, and the operation efficiency of individual household acceptance measurement is effectively improved.

Description

Technical Field

[0001] The invention belongs to the technical field of intelligent household acceptance, and in particular relates to a method for realizing automatic planning of measurement points. Background Art

[0002] With the acceleration of urbanization and the rapid development of the real estate market, the construction industry has ushered in unprecedented development opportunities. However, competition in the construction industry is also increasingly fierce. How to improve construction efficiency and reduce costs while ensuring the quality of buildings has become the focus of the industry. In this context, the application of intelligent technologies such as measurement robots and line-laying robots has received widespread attention. These technologies achieve accurate measurement and rapid analysis of various indicators of buildings through automation and intelligence, providing strong support for the improvement of building quality. At the same time, these technologies can also improve the efficiency and accuracy of acceptance, reduce labor costs and error rates, and provide new impetus for the development of the construction industry.

[0003] However, the workload of household acceptance measurement is increasing day by day, and the traditional manual measurement method can no longer meet the requirements of efficient and accurate acceptance. Moreover, the measuring robot is still in the research and development stage. Various products on the market cannot completely get rid of manpower and are cumbersome to operate. The existing intelligent household acceptance technology still requires a large amount of manpower to operate. For example, the actual measurement robot still needs to be carried by manpower in each room. Although some measuring robots have integrated chassis, the measuring points in the household type to be measured need to be manually set on the operating software, which greatly affects the operating efficiency. In order to solve the above problems, the present invention designs a method for realizing automatic planning of measuring points, which can help the measuring robot realize automatic planning of measuring points without manual participation, thereby greatly improving the measurement efficiency. Summary of the invention

[0004] In view of the deficiencies in the prior art, the present invention provides a method for realizing automatic planning of measurement points, which effectively improves the operational efficiency of household acceptance measurement.

[0005] The present invention achieves the above technical objectives through the following technical means.

[0006] A method for realizing automatic planning of measurement points includes the following process: Step 1: Export the CAD drawing data for measuring point planning into image format data; Step 2: Use the preprocessing algorithm in the openCV tool to automatically preprocess the converted image; Step 3: Use the robot automatic door closing algorithm in the openCV tool to close the doors of all the apartments in the apartment drawings; Step 4: Manually click on any pixel point within the house type on the screen where measurement points need to be planned; Step 5: The robot house type detection algorithm automatically traverses the points around the clicked coordinate, obtaining all points with the same RGB until the boundary is encountered; Step 6: Based on the robot house type detection algorithm, automatically extract all the traversed points, redraw the internal space on a newly created blank image, and create a measurement point stack; Step 7: Based on the robot measurement point generation algorithm, automatically identify all the contours in the image, record the current number of contours as state1, and sort the areas of the contours; Step 8: Based on the robot measurement point generation algorithm, automatically obtain the center coordinate of the smallest contour and name it point; Step 9: Based on the robot measurement point generation algorithm, automatically modify the RGB values of all points of the smallest contour to the background color of the image; Step 10: Based on the robot measurement point generation algorithm, automatically identify all the contours in the image, record the current number of contours as state2, and sort the contour areas; When state1 = state2, no operation is performed; When state1 < state2, pop the top coordinate point from the measurement point stack and set state1 = state2; When state1 > state2, push point onto the top of the measurement point stack; When there are still contours in the image, repeat steps 8 to 10, otherwise end the operation; all the points existing in the measurement point stack are the final measurement point results after automatic planning, and mark the results on the drawing.

[0007] Furthermore, the specific method of the preprocessing in step 2 is as follows: Step 2.1: Scan and filter all pixel points in the image, perform binarization operation to ensure that there are only black and white colors in the image; Step 2.2: Identify the contours in the image, and then redraw all the contours to ensure the closure of the house type diagram.

[0008] Furthermore, the specific process of step 3 is as follows: Step 3.1: Manually click on any image coordinate point within the house type; Step 3.2: Scan around in a circular manner with the clicked coordinate point as the center; Step 3.3: Automatically scan to the two closest points where two walls are horizontal; Step 3.4: Connect the two points with a black line segment to close the internal space.

[0009] Furthermore, the specific process of step 5 is as follows: Step 5.1: Create a new apartment space point stack, obtain the clicked image coordinate point, and push it into the apartment space point stack; Step 5.2: Pop up the coordinates of the top of the apartment space point stack, turn it red, and store the coordinates. Check whether the points around it are white. If so, push them into the apartment space point stack; Step 5.3: Repeat step 5.2 until the apartment space point stack is empty.

[0010] The present invention has the following beneficial effects: The automatic planning method for measuring points provided by the present invention can plan a measuring point at the midpoint of each room in the apartment through simple operations on the software, and can help the measuring robot to realize automatic planning of measuring points without human intervention, thus saving the operator's time in setting measuring points in each room and effectively improving the operational efficiency of household acceptance measurement. BRIEF DESCRIPTION OF THE DRAWINGS

[0011] Figure 1 is a schematic diagram of the CAD drawing conversion.

[0012] Figure 2 is a schematic diagram of the results after image preprocessing.

[0013] FIG3 is a schematic diagram showing the result of closing the image and traversing all coordinates of its internal space.

[0014] FIG4 is a schematic diagram showing the presentation effect of all extracted traversal coordinates in a new background.

[0015] FIG. 5 is a schematic diagram showing the effect of modifying the RGB values ​​of the image contour coordinates.

[0016] Figure 6 is a schematic diagram of the measurement point results generated after automatic planning is completed.

[0017] FIG7 is a flow chart of the method for realizing automatic planning of measurement points. DETAILED DESCRIPTION

[0018] The present invention is further described below in conjunction with the accompanying drawings and specific embodiments, but the protection scope of the present invention is not limited thereto.

[0019] Reference Figure 7 The method for realizing automatic planning of measurement points described in the present invention includes the following process: Step 1: First, export the CAD drawing data that needs to be planned for measurement points into image format data. The converted image format data is as follows: Figure 1 As shown; Step 2: Use the preprocessing algorithm in the openCV (open source computer vision library) tool on the computer to automatically preprocess the converted image to facilitate subsequent operations. The preprocessed result is as follows: Figure 2 As shown; the preprocessing method is as follows: Step 2.1: Scan and filter all pixels in the image and perform binarization to ensure that only black and white are present in the image; Step 2.2: Identify the contours in the image, and then redraw all contours to ensure the closedness of the floor plan.

[0020] Step 3: Use the robot automatic door closing algorithm in the openCV tool to close the doors of all the apartments in the apartment drawings. The specific method is as follows: Step 3.1: Manually click any image coordinate point in the house type; Step 3.2: Scan in a circular manner around the clicked coordinate point; Step 3.3: Automatically scan to the two points that are closest and where the two walls are horizontal; Step 3.4: Connect the two points with a black line segment to close the internal space.

[0021] Step 4: Manually click on any pixel point on the screen within the apartment where the measurement point needs to be planned.

[0022] Step 5: Figure 3 As shown in the figure, the robot apartment detection algorithm automatically traverses the points around the clicked coordinates and obtains all points with the same RGB until it encounters a boundary. The specific method is as follows: Step 5.1: Create a new apartment space point stack, obtain the clicked image coordinate point, and push it into the apartment space point stack; Step 5.2: Pop up the coordinates of the top of the apartment space point stack, turn it red, and store the coordinates. Check whether the points around it are white. If so, push them into the apartment space point stack; Step 5.3: Repeat step 5.2 until the apartment space point stack is empty.

[0023] Step 6: Figure 4 As shown, based on the robot apartment type detection algorithm, all traversed points are automatically extracted, the internal space is redrawn on the newly created blank picture, and a new measurement point stack is created.

[0024] Step 7: Automatically identify all contours in the image based on the robot measurement point generation algorithm, record the current number of contours as state1, and sort the areas of the contours.

[0025] Step 8: Automatically obtain the coordinates of the center of the smallest contour based on the robot measurement point generation algorithm, and name it point; Step 9: As Figure 5 shown, automatically modify the RGB values of all points of the smallest contour based on the robot measurement point generation algorithm, and modify RGB (a color standard in the industrial field) to the background color of the picture.

[0026] Step 10: Automatically identify all the contours in the picture based on the robot measurement point generation algorithm, record the current number of contours as state2, and sort the contour areas; If state1 = state2, do not perform any operation; If state1 < state2, pop the top coordinate point from the measurement point stack, and set state1 = state2; If state1 > state2, push point onto the top of the measurement point stack; If there are still contours in the picture, repeat Steps 8 to 10; otherwise, end the operation. All the points existing in the measurement point stack are the final measurement point results generated after automatic planning. Mark the results on the drawing, as Figure 6 shown.

[0027] The explanations of the professional terms involved in the above process are as follows: Stack: A stack, also known as a pushdown list, is a restricted linear list where insertions and deletions are limited to one end, called the top of the stack. The other end is called the bottom of the stack. Inserting a new element into a stack is also called pushing, which places the new element on top of the top element of the stack, making it the new top element. Deleting an element from a stack is also called popping, which removes the top element of the stack, making the adjacent element the new top element.

[0028] The described embodiments are the preferred embodiments of the present invention, but the present invention is not limited to the above embodiments. Without departing from the essence of the present invention, any obvious improvements, substitutions, or variations that those skilled in the art can make fall within the protection scope of the present invention.

Claims

1. A method for realizing automatic planning of measurement points, characterized in that: It includes the following processes: Step 1: Export the CAD drawing data to be measured point planned into picture format data; Step 2: Automatically preprocess the converted picture by using the preprocessing algorithm in the openCV tool; Step 3: Use the robot automatic door closing algorithm in the openCV tool to close all the doors of the house types in the house type drawing; Step 4: Manually click on any pixel point in the house type on the screen where the measurement points need to be planned; Step 5: The robot house type detection algorithm automatically traverses the points around the clicked coordinates, and obtains all the points with the same RGB until the boundary is encountered; Step 6: Based on the robot house type detection algorithm, automatically extract all the traversed points, redraw the internal space on a newly created blank picture, and create a measurement point stack; Step 7: Based on the robot measurement point generation algorithm, automatically identify all the contours in the picture, record the current number of contours as state1, and sort the areas of the contours; Step 8: Based on the robot measurement point generation algorithm, automatically obtain the center coordinates of the smallest contour, and name it point; Step 9: Based on the robot measurement point generation algorithm, automatically modify the RGB values of all the points of the smallest contour, and change the RGB to the background color of the picture; Step 10: Based on the robot measurement point generation algorithm, automatically identify all the contours in the picture, record the current number of contours as state2, and sort the contour areas; When state1 = state2, no operation is performed; When state1 < state2, pop the top coordinate point in the measurement point stack, and set state1 = state2; When state1 > state2, push point onto the top of the measurement point stack; When there are still contours in the picture, repeat steps 8 to 10, otherwise end the operation; all the points existing in the measurement point stack are the final measurement point results generated after automatic planning, and mark the results on the drawing.

2. The method for realizing automatic planning of measuring points according to claim 1, characterized in that: The specific method of the preprocessing in step 2 is as follows: Step 2.1: Scan and filter all the pixel points in the picture, and perform binarization operation to ensure that there are only black and white colors in the image; Step 2.2: Identify the contours in the picture, and then redraw all the contours to ensure the closure of the house type drawing.

3. The method for realizing automatic planning of measurement points according to claim 1, characterized in that: The specific process of step 3 is as follows: Step 3.1: Manually click on any image coordinate point in the house type; Step 3.2: Scan around in a circular manner with the clicked coordinate point as the center; Step 3.3: Automatically scan to the two points that are the closest and where two walls are horizontal; Step 3.4: Connect the two points with a black line segment to close the internal space.

4. The method for realizing automatic planning of measurement points according to claim 1, characterized in that: The specific process of step 5 is as follows: Step 5.1: Create a house type space point stack, obtain the clicked image coordinate point, and push it into the house type space point stack; Step 5.2: Pop the coordinate at the top of the house type space point stack, change it to red, and store the coordinate. Detect whether the points around it are white. If so, push them into the house type space point stack; Step 5.3: Repeat step 5.2 until the house type space point stack is empty and end.

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