Local docking method based on two-dimensional code navigation

Abstract

The invention provides a working method of a detection device applied to a relay assembly, and the method specifically comprises the steps: (1) conveying a relay placement jig to a position above a probe assembly through a conveying belt, and enabling a movable spring part to be located between a push rod assembly and the probe assembly; (2) the push rod assembly moves downwards and makes contact with the movable spring piece; (3) the probe driving part drives the probe to move upwards and make contact with the connecting terminal of the movable spring piece; (4) the probe driving part continues to drive the probe to move upwards by a certain distance; (5) carrying out resistance detection on the connecting terminal of the movable spring piece through a probe; according to the method, it is guaranteed that the probe can make full contact with the connecting terminal of the movable spring piece, and meanwhile the problem that rigid collision does not occur between the probe and the connecting terminal of the movable spring piece is solved.

Description

Technical Field

[0001] The present invention relates to the technical field of robot navigation, and in particular to a local docking method based on two-dimensional code navigation. Background Art

[0002] In recent years, with the continuous improvement of production technology, most modern intelligent manufacturing workshops are equipped with AGV carts (Automated Guided Vehicle, referred to as AGV). AGV carts have the advantages of high degree of automation, high level of intelligence, and small footprint. Products are transported by AGV carts equipped with transmission mechanisms, and can automatically interface with other logistics equipment to realize the automation of the entire process of loading and unloading and handling of goods and materials.

[0003] For example, the patent document with Chinese patent application number 202210109495.6 and publication date 2022.07.26 discloses an AGV high-precision positioning device and a precise docking method, including a positioning plate, an automated production line, a Mecanum wheel AGV and an intelligent tower warehouse. A positioning plate is provided at the bottom of one side of the intelligent tower warehouse and both sides of the automated production line. The positioning plate includes a positioning bushing, a fixing hole, and a navigation QR code. The positioning bushing is conical, with two diagonal holes and six fixing holes, four of which are connected to the ground by bolts, and the other two are connected to the automated production line. Transport hoists are provided at both ends of the inlet and outlet of the automated production line.

[0004] The above-mentioned document achieves high-precision positioning within 0.5mm through conical positioning pins and positioning bushings after the Mecanum wheel AGV scans the QR code for preliminary navigation. It cannot solve the technical problem of accurate docking of AGV and machine. In the process of using AGV to transport materials in the workshop, the AGV is often required to determine the starting point of the driving path and then drive to the end point of the machine along the path to dock with the machine to realize functions such as charging or transportation. Especially for long-distance straight paths, the AGV may have an angle deviation during the rotation process of confirming the starting point. For example, if the angle is rotated a little larger, the center of the AGV will not be at the starting point. In this way, it will subsequently walk according to the non-starting point, and it will not be able to achieve accurate docking with the machine to complete the material transportation. Summary of the invention

[0005] The purpose of the present invention is to provide a local docking method based on QR code navigation, which can solve the problem of high-precision docking of logistics robots indoors, so that the logistics robots can accurately reach the destination and realize material handling.

[0006] To achieve the above object, the present invention provides a local docking method based on QR code navigation, which is used for a logistics robot. A camera is provided at the bottom of the logistics robot, and a QR code is set on the ground of a preset path, comprising the following steps: S1. Set a starting QR code in the scanning area at the starting point of the preset path, and set an end QR code in the scanning area at the end point of the preset path. The preset logistics robot can successfully scan the QR code within the maximum deviation range [-x, x]. The preset logistics robot adjusts the angle to a at the maximum deviation, and the preset docking error range of the logistics robot at the end point. S2, the logistics robot enters the scanning area at the starting point of the preset path along the direction from the starting QR code to the end QR code, scans the starting QR code through the camera, and then recognizes the starting QR code information; S3. The logistics robot establishes a coordinate system with the center point of the starting QR code as the origin, and then calculates the deviation between the actual position coordinates of the logistics robot and the origin coordinates. S4, correct the deviation between the actual position coordinates of the logistics robot and the origin coordinates, S4.1. Determine the angle a0 at which the logistics robot deviates from the preset path using formula (1). (1), is the deviation between the horizontal coordinate of the actual position coordinate of the logistics robot and the origin coordinate; S4.2. Determine the distance s that the logistics robot travels along the deviation angle a0 to the preset path using formula (2). (2), S4.3, control the logistics robot to travel at a preset speed v along the deviation angle a0 and a distance s to stop, and then control the logistics robot to rotate (90- a0)° in the direction of the preset path, so that the logistics robot corrects the deviation and returns to the preset path; S5. Control the logistics robot to continue driving along the preset path to the end point scanning area, and then scan the end point QR code again through the camera and read the information to determine whether the logistics robot is within the docking error range.

[0007] The above setting, by setting a QR code in the code scanning area, and making the logistics robot enter the code scanning area along the direction from the starting QR code to the end QR code, ensures that the logistics robot can complete the code scanning and obtain the QR code information when it drives into the code scanning area; because after the logistics robot enters the code scanning area along the direction from the starting QR code to the end QR code and completes the code scanning, there may be a deviation between the center of the logistics robot and the center point of the starting QR code, and then by calculating the deviation between the horizontal coordinate of the actual position of the logistics robot and the horizontal coordinate of the origin coordinate, the actual deviation position of the logistics robot and the origin coordinate can be determined; then the angle a0 required to adjust the actual deviation of the logistics robot is calculated, and the distance s from the actual deviation position to the preset path is determined, so that the logistics robot can be controlled to drive to the preset path according to the calculated distance s, and then the logistics robot is rotated counterclockwise (90- a0)°, so that the logistics robot corrects the angle deviation and returns to the preset path; finally, the logistics robot is controlled to continue driving along the preset path to the end point scanning area, and then it can scan the QR code again and read the information. In this way, it can drive to the end point according to the preset path to eliminate the starting point deviation, and it can determine whether the logistics robot is within the docking error range and complete the docking, ensuring high-precision docking.

[0008] Further, step S3 includes: S3.1. Calculate the deviation between the horizontal coordinate of the actual position coordinate of the logistics robot and the origin coordinate, and then determine the positional relationship between the logistics robot and the origin coordinate. S3.1.1. If there is a deviation between the horizontal coordinate of the actual position coordinate of the logistics robot and the origin coordinate If the value is within the range of [-x, 0], the logistics robot is judged to be on the left side of the starting QR code. S3.1.2. If there is a deviation between the horizontal coordinate of the actual position coordinate of the logistics robot and the origin coordinate If the value is within the range of [0, x], it is judged that the logistics robot has deviated to the right side of the starting point QR code.

[0009] The above settings are based on the deviation between the horizontal coordinates of the actual position coordinates of the logistics robot and the origin coordinates. Compare with the preset logistics robot within the maximum deviation range to determine whether the deviation is on the left or right side, so as to preliminarily determine the deviation position.

[0010] Furthermore, the preset path is set as the straight-line distance from the starting QR code to the ending QR code.

[0011] The above settings make it easier for the logistics robot to arrive along a straight path and achieve precise docking.

[0012] Furthermore, the step S2 also includes the following steps S2.1-S2.2: S2.1. If the QR code information of the starting point cannot be read, the logistics robot exits the scanning area of ​​the preset path starting point and then re-enters; S2.2: If the starting point QR code information is read successfully, the logistics robot recognizes it as the starting point of the preset path and then proceeds to step S3.

[0013] The above settings make it easy to verify whether the logistics robot can scan the starting point QR code information through the camera and successfully read the starting point QR code information.

[0014] Furthermore, the step S4.2 also includes: The distance l0 from the origin of the coordinate system to the intersection of the path along the deviation angle a0 and the preset path is determined by formula (3). (3), Then, the distance L between the logistics robot and the end point of the preset path after the deviation is corrected is determined by formula (4): L=l-l0(4) Where l is the distance of the preset path.

[0015] The above settings make it easy for the logistics robot to drive in a straight line according to the distance from the terminal scanning area after correcting the deviation, so that it can reach the terminal scanning area to scan the code again and achieve docking.

[0016] Furthermore, step S5 also includes: The logistics robot is controlled to continue driving a distance L along the preset path to the end point scanning area. After the logistics robot successfully scans the end point QR code, the information read in the end point QR code overwrites the information read in the starting point QR code. The information read in the end point QR code is then used as a reference standard. If the logistics robot is within the preset docking error range of the logistics robot at the end point, the docking is completed; otherwise, step S2 is entered to re-dock.

[0017] The above settings can prevent the distance L calculated by the logistics robot after correcting the deviation from being inconsistent with the information data in the destination QR code, so that the logistics robot continues to travel according to the distance L calculated after correcting the deviation after scanning the destination QR code. This will cause the logistics robot to exceed the docking error range of the preset path endpoint, and thus make the logistics robot unable to complete the docking. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1 It is a flow chart of the working method of the present invention.

[0019] Figure 2 It is a geometric diagram of the calculation in the process of correcting the deviation in the present invention.

[0020] Figure 3It is a schematic diagram of entering the starting point scanning area in the present invention.

[0021] Figure 4 This is a schematic diagram of the logistics robot of the present invention after adjusting the body angle.

[0022] Figure 5 This is a schematic diagram of the logistics robot in the present invention rotating to a preset path. DETAILED DESCRIPTION

[0023] The present invention is further described in detail below with reference to the accompanying drawings and specific embodiments.

[0024] like Figure 1-5 As shown, a local docking method based on QR code navigation is provided. A camera is provided at the bottom of the logistics robot. The camera is used to identify QR code information. The QR code is set on the ground of a preset path. In this embodiment, the starting QR code 1 is set in the scanning area of ​​the starting point of the preset path, and the end point QR code 2 is set in the scanning area of ​​the end point of the preset path. The preset path is set as the straight-line distance from the starting QR code to the end point QR code.

[0025] The specific method includes the following steps: S1. The logistics robot is preset to be able to successfully scan the QR code within the maximum deviation range [-x, x]. The adjustment angle of the logistics robot is a at the maximum deviation. The docking error range of the logistics robot at the end point is preset to b. In this embodiment, x is set to 300 mm, a is set to 30°, and b is 5 mm.

[0026] S2, the logistics robot enters the scanning area at the starting point of the preset path along the direction from the starting QR code to the end QR code, scans the starting QR code through the camera, and then recognizes the starting QR code information; S2.1. If the QR code information of the starting point cannot be read, the logistics robot exits the scanning area of ​​the preset path starting point and then re-enters; S2.2: If the starting point QR code information is read successfully, the logistics robot recognizes it as the starting point of the preset path and then proceeds to step S3.

[0027] S3, calculate the deviation between the horizontal coordinate of the actual position coordinate of the logistics robot (i.e. the horizontal coordinate of the center point 3 of the logistics robot) and the origin coordinate, and then determine the positional relationship between the logistics robot and the origin coordinate. S3.1.1. If the deviation x0 between the abscissa of the actual position coordinates of the logistics robot (i.e. the abscissa of the center point 3 of the logistics robot) and the origin coordinates is within the range of [-x, 0], then it is determined that the logistics robot is deviated to the left of the starting point QR code. S3.1.2. If the deviation x0 between the horizontal coordinate of the actual position coordinate of the logistics robot and the origin coordinate is within the range of [0, x], it is judged that the logistics robot deviates to the right side of the starting QR code. In this embodiment, x0 is set to 100 mm.

[0028] S4, correct the deviation between the actual position coordinates of the logistics robot and the origin coordinates, S4.1. Determine the angle a0 at which the logistics robot deviates from the preset path using the following formula (1): (1); S4.2. Use formula (2) to determine the distance s that the logistics robot travels along the deviation angle a0 to the preset path. (2), The distance l0 from the origin of the coordinate system to the intersection of the distance s and the preset path is determined by formula (3). (3), Then formula (4) determines the distance L between the logistics robot and the end point of the preset path after the deviation is corrected. L=l-l0(4) Where l is the distance of the preset path.

[0029] S4.3. Control the logistics robot to travel a distance s at a speed v along a deviation angle a0 and stop, and then control the logistics robot to rotate (90-a0)° to the preset path. In this embodiment, the rotation is counterclockwise in the plane where the XY axis is located, so that the logistics robot returns to the preset path after correcting the deviation.

[0030] S5. Control the logistics robot to continue driving a distance L along the preset path to the end point scanning area, and then scan the end point QR code again through the camera. After the logistics robot successfully scans the end point QR code, the information read in the end point QR code overwrites the information read in the starting point QR code, and uses the information read in the end point QR code as a reference standard. If the logistics robot is within the docking error range, the docking is completed; otherwise, enter step S2 to re-dock.

[0031] like Figure 3-5 As shown, at the beginning, the distance between the midpoint 3 of the logistics robot and the starting point QR code 1 , control the logistics robot body to travel a distance s along the deviation angle a0, so that the midpoint of the logistics robot body moves to the preset path, and then continues to travel a distance L along the preset path, and confirms whether it returns to the key QR code, thereby ensuring the reliability of docking.

[0032] The working principle of the present invention is as follows: the logistics robot is controlled to enter the scanning area at the starting point of the preset path along the direction from the starting point QR code to the end point QR code to scan the code and read the QR code information, and then a coordinate system is established with the center point of the QR code as the coordinate origin, and the deviation between the actual position of the logistics robot and the origin coordinate is judged, and then the deviation, the angle corresponding to the corrected deviation and the distance from the actual deviation position to the preset path are calculated, so that the logistics robot returns to the preset path after adjusting the angle, and continues to drive along the preset path to the end point scanning area to scan the code again, and read the QR code information at the same time, and then stops driving with the information read by the end point scanning as a reference standard, and finally judges whether the logistics robot is within the docking error range and completes the docking.

Claims

1. A local docking method based on QR code navigation, used for a logistics robot, a camera is provided at the bottom of the logistics robot, and a QR code is set on the ground of a preset path, characterized in that: The following steps are involved: S1. Set a starting QR code in the scanning area at the starting point of the preset path, and set an end QR code in the scanning area at the end point of the preset path. The preset logistics robot can successfully scan the QR code within the maximum deviation range [-x, x]. The preset logistics robot adjusts the angle to a at the maximum deviation, and the preset docking error range of the logistics robot at the end point. S2, the logistics robot enters the scanning area at the starting point of the preset path along the direction from the starting QR code to the end QR code, scans the starting QR code through the camera, and then recognizes the starting QR code information; S3. The logistics robot establishes a coordinate system with the center point of the starting QR code as the origin, and then calculates the deviation between the actual position coordinates of the logistics robot and the origin coordinates. S4. Correct the deviation between the actual position coordinates of the logistics robot and the origin coordinates. S4.

1. Determine the angle a0 of the logistics robot deviating from the preset path by formula (1). (1), is the deviation between the horizontal coordinate of the actual position coordinate of the logistics robot and the origin coordinate; S4.

2. Determine the distance s that the logistics robot travels along the deviation angle a0 to the preset path by using formula (2). （2）， S4.3, control the logistics robot to travel at a preset speed v along the deviation angle a0 and a distance s to stop, and then control the logistics robot to rotate (90- a0)° in the direction of the preset path, so that the logistics robot corrects the deviation and returns to the preset path; S5. Control the logistics robot to continue driving along the preset path to the end point scanning area, and then scan the end point QR code again through the camera and read the information to determine whether the logistics robot is within the docking error range.

2. A local docking method based on two-dimensional code navigation according to claim 1, characterized in that: Step S3 includes: S3.1, calculating the deviation between the horizontal coordinate of the actual position coordinate of the logistics robot and the origin coordinate, and then determining the positional relationship between the logistics robot and the origin coordinate, S3.1.

1. If there is a deviation between the horizontal coordinate of the actual position coordinate of the logistics robot and the origin coordinate If the value is within the range of [-x, 0], the logistics robot is judged to be on the left side of the starting QR code. S3.1.

2. If the deviation x0 between the horizontal coordinate of the actual position coordinate of the logistics robot and the origin coordinate is within the range of [0, x], it is judged that the logistics robot deviates to the right side of the starting point QR code.

3. The local docking method based on two-dimensional code navigation according to claim 1, characterized in that: The preset path is set as the straight-line distance from the starting QR code to the ending QR code.

4. The local docking method based on two-dimensional code navigation according to claim 1, characterized in that: The step S2 also includes the following steps S2.1-S2.2: S2.

1. If the QR code information at the starting point cannot be read, the logistics robot exits the code scanning area at the starting point of the preset path and then re-enters; S2.2: If the starting point QR code information is read successfully, the logistics robot recognizes it as the starting point of the preset path and then proceeds to step S3.

5. The local docking method based on two-dimensional code navigation according to claim 1, characterized in that: The step S4.2 also includes: The distance l0 from the origin of the coordinate system to the intersection of the path along the deviation angle a0 and the preset path is determined by formula (3). （3）， Then, the distance L between the logistics robot and the end point of the preset path after the deviation is corrected is determined by formula (4): L=l-l0（4）， Where l is the distance of the preset path.

6. A local docking method based on two-dimensional code navigation according to claim 5, characterized in that: Step S5 also includes: After the logistics robot successfully scans the destination QR code, the information read in the destination QR code overwrites the information read in the starting QR code, and then uses the information read in the destination QR code as a reference standard. If the logistics robot is within the docking error range, the docking is completed; otherwise, enter step S2 to re-dock.

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