Vehicle window height positioning method and lifting exit robot

Abstract

The invention relates to the technical field of intelligent card recovery equipment, and particularly provides a method for positioning the height of a car window and a lifting exit robot. The method comprises the steps of obtaining the state of a vehicle arriving at a toll station island head, and judging whether the vehicle arrives at the toll station island head; if it is judged that the vehicle arrives at the toll station island head, a camera identifies a license plate, and a vehicle model database is matched at the same time; when a vehicle type is matched in the vehicle type database, the vehicle window height of the corresponding vehicle type is obtained, the lifting exit robot is moved to the corresponding height, the tipping bucket is opened, algorithm recognition is started, and card recycling is carried out; and when the vehicle model is not matched in the vehicle model database, the lifting exit robot is directly moved to the corresponding height, the tipping bucket is opened, algorithm recognition is started for card recovery, and the method realizes accurate positioning of the upper and lower positions, improves the operation convenience of a driver, and improves the passing efficiency.

Description

Technical Field

[0001] The present invention relates to the technical field of intelligent card recycling equipment, and in particular to a method for positioning the height of a vehicle window and a lifting exit robot. Background Art

[0002] The highway card recycling machine is an intelligent card recycling device used on highways. Through this device, drivers can easily obtain pass card recycling and payment, so as to pass through highway toll stations more efficiently. Compared with manual card recycling, it improves traffic efficiency and reduces congestion.

[0003] In the existing technology, some card recovery machines can only retrieve cards through double-station card insertion. However, this card recovery method also has certain disadvantages. The driver needs to judge the position and stay at a fixed position accurately. Sometimes, if the distance is far, he needs to get off the car to insert the card for recovery. When retrieving the card, the driver needs to manually operate it, which greatly reduces the traffic efficiency. Summary of the invention

[0004] In view of this, the present invention provides a method for positioning the height of a vehicle window and a lifting exit robot, so as to achieve accurate positioning of the upper and lower positions, improve the convenience of the driver's operation, and improve the traffic efficiency.

[0005] In a first aspect, the present invention provides a method for positioning a vehicle window height, the method comprising: Step 1: Get the vehicle arrival status at the toll station island, and determine whether the vehicle has reached the toll station island; Step 2: If it is determined that the vehicle has arrived at the toll station island, the camera will recognize the license plate and match it with the vehicle model database; if it is determined that the vehicle has not arrived at the toll station island, continue to step 1; Step 3. When a vehicle model is matched in the vehicle model database, the window height of the corresponding vehicle model is obtained, and the lifting exit robot is moved to the corresponding height, the dump bucket is opened, and the algorithm recognition is started to recover the card; when the vehicle model database does not match the vehicle model, the lifting exit robot is directly moved to the corresponding height, the dump bucket is opened, and the algorithm recognition is started to recover the card.

[0006] Optionally, in step 3, moving the lifting exit robot to a corresponding height includes: The window height is sent to the control end of the lifting exit robot, and the control end drives the servo motor to drive the lifting slide to move up and down.

[0007] Optionally, in step 3, the dump bucket is opened and algorithm recognition is started to recover the card, including: The dump box opens, and the camera is started to perform face and window recognition, and simultaneously determine whether a card is put into the dump box; if it is determined that no card is put into the dump box, when the algorithm returns, the height needs to be adjusted, and the dump box is closed at the same time, and the control end drives the servo motor to drive the lifting slide to make fine adjustments up and down to achieve positioning; then the dump box opens again, waiting for the card to be put into the dump box; when the algorithm does not return and the height needs to be adjusted, the car is in the leaving state, the dump box is closed, and the state of the car arriving at the toll station island head continues to be obtained.

[0008] Optionally, it also includes: If it is determined that a card has been put into the dump truck, the card insertion message is reported and the card collection or return instruction is waited for; when the card return instruction is received, wait for the card to be taken away, and after the card is taken away, the card removal message is reported to obtain the vehicle departure status. When the vehicle leaves, the dump truck is closed, and the vehicle arrival status at the toll station island head is continued to be obtained; when the card collection instruction is received, the dump truck is closed and the card is collected; the card recovery message is reported, the dump truck is closed, and the vehicle arrival status at the toll station island head is continued to be obtained; when no card collection instruction is received, continue to wait for the card collection or return instruction.

[0009] Optionally, when the card is put into the tipping bucket, the card is read successfully and the payment is successful, the tipping bucket action will collect the card into the temporary storage mechanism.

[0010] Optionally, the algorithm identification includes: Step 31: image preprocessing; (1) Image capture: Capturing the image of the front of the vehicle through a camera; (2) Image enhancement: Enhance the captured image, including denoising, sharpening, and contrast adjustment, to obtain an enhanced image; (3) Image cropping: crop the enhanced image according to the preset region of interest (ROI); Step 32: Window positioning; (1) Feature extraction: Use image processing technology to extract features of the window area, including edges, colors, and textures; (2) Window recognition: A deep learning model is used to classify the extracted features and identify the position and shape of the driver’s window. (3) Window boundary determination: Determine the precise boundary of the window based on the recognition results; Step 33: face positioning; (1) Face detection: A deep learning face detection algorithm is used to detect the driver’s face in the window area. (2) Face position determination: Based on the position of the feature points, the precise position of the face is determined, and the offset of the face relative to the lifting exit robot is calculated; Step 34: Position adjustment; (1) Calculation of the position of the lifting exit robot: Based on the positioning results of the car window and the human face, combined with the algorithm logic preset by the device, the optimal position of the lifting exit robot is calculated; (2) Position adjustment command: Send a position adjustment command to the lifting exit robot to move it to the calculated optimal position; Step 35: Result feedback; (1) Positioning success / failure feedback: The algorithm determines whether the window and face positioning is successful and provides feedback to the system; (2) Error handling: If positioning fails, the algorithm will try to recapture the image or perform error handling to ensure the stability and reliability of the system.

[0011] In a second aspect, an embodiment of the present invention provides a lifting exit robot for vehicle window height positioning, the lifting exit robot is used to implement the first aspect or any one of the methods for vehicle window height positioning of the first aspect, the lifting exit robot comprises: a recovery panel, a lifting mechanism and a temporary storage mechanism; The recycling panel includes a tipping bucket, a camera, a payment module, and a display screen; the lifting mechanism includes a lifting slide, a servo motor, an in-position sensor, and a panel bracket; The recycling panel is fixed on the panel bracket, the panel bracket is connected to the lifting mechanism, the distance between the highest position of the panel bracket and the in-place sensor is driven by the servo motor to drive the lifting slide; the payment module and the display screen are fixed to the rear of the recycling panel by threads, and the payment module is used to scan the QR code; the display screen is used to display the amount and license plate; the license plate is recognized by the camera and matched with the vehicle model database to determine the vehicle model and move at different heights; when the card is put into the tipping bucket, the card is read successfully and the payment is successful, the tipping bucket will collect the card into the temporary storage mechanism; when the number of recycled cards in the temporary storage mechanism reaches the preset value, the lifting mechanism will drop to the lowest point and recycle the card into the recycling box.

[0012] In the technical solution provided by the present invention, the method includes obtaining the status of the vehicle arriving at the toll station island head and judging whether the vehicle has reached the toll station island head; if it is judged that the vehicle has arrived at the toll station island head, the camera recognizes the license plate and matches the vehicle model database at the same time; if it is judged that the vehicle has not arrived at the toll station island head, the status of the vehicle arriving at the toll station island head continues to be obtained; when the vehicle model is matched in the vehicle model database, the window height of the corresponding vehicle model is obtained, and the lifting exit robot is moved to the corresponding height, the dump bucket is opened, and the algorithm recognition is started to recover the card; when the vehicle model is not matched in the vehicle model database, the lifting exit robot is directly moved to the corresponding height, the dump bucket is opened, and the algorithm recognition is started to recover the card. The method realizes precise positioning of the upper and lower positions, improves the convenience of the driver's operation, and improves the traffic efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0013] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0014] Figure 1 A flow chart of a method for locating vehicle window height provided by an embodiment of the present invention; Figure 2 A schematic diagram of the three-dimensional structure of a lifting exit robot provided in an embodiment of the present invention; Figure 3 Another schematic diagram of the three-dimensional structure of the lifting exit robot provided by an embodiment of the present invention; Figure 4 A schematic diagram of the side structure of a recycling panel provided by an embodiment of the present invention; Figure 5 A schematic diagram of the rear structure of a recycling panel provided in an embodiment of the present invention; Figure 6 A schematic structural diagram of a lifting mechanism provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0015] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0016] It should be clear that the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0017] The terms used in the embodiments of the present invention are only for the purpose of describing specific embodiments, and are not intended to limit the present invention. The singular forms "a", "said" and "the" used in the embodiments of the present invention are also intended to include plural forms, unless the context clearly indicates other meanings.

[0018] It should be understood that the term "and / or" used in this article is only a description of the association relationship of associated objects, indicating that there can be three relationships. For example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone. In addition, the character " / " in this article generally indicates that the associated objects before and after are in an "or" relationship.

[0019] The word "if" as used herein may be interpreted as "at the time of" or "when" or "in response to determining" or "in response to detecting", depending on the context. Similarly, the phrases "if it is determined" or "if (stated condition or event) is detected" may be interpreted as "when it is determined" or "in response to determining" or "when detecting (stated condition or event)" or "in response to detecting (stated condition or event)", depending on the context.

[0020] Figure 1 A flow chart of a method for locating vehicle window height provided by an embodiment of the present invention, such as Figure 1 As shown, the method includes: Step 1: Get the vehicle arrival status at the toll station island, and determine whether the vehicle has reached the toll station island; Step 2: If it is determined that the vehicle has arrived at the toll station island, the camera 102 recognizes the license plate and matches the vehicle model database; if it is determined that the vehicle has not arrived at the toll station island, continue to execute step 1; Step 3. When a vehicle model is matched in the vehicle model database, the window height of the corresponding vehicle model is obtained, and the lifting exit robot is moved to the corresponding height, the dump bucket 101 is opened, and the algorithm recognition is started to recover the card; when a vehicle model is not matched in the vehicle model database, the lifting exit robot is directly moved to the corresponding height, the dump bucket 101 is opened, and the algorithm recognition is started to recover the card.

[0021] In the embodiment of the present invention, in step 3, moving the lifting exit robot to a corresponding height includes: The window height is sent to the control end of the lifting exit robot, and the control end drives the servo motor 202 to drive the lifting slide 201 to move up and down.

[0022] In the embodiment of the present invention, in step 3, the dump bucket is opened and the algorithm recognition is started to recover the card, which includes: The dump box 101 is opened, and the camera 102 is started to perform face and window recognition, and simultaneously determine whether a card is put into the dump box 101; if it is determined that no card is put into the dump box 101, when the algorithm returns that the height needs to be adjusted, the dump box 101 is closed at the same time, and the control end drives the servo motor 202 to drive the lifting slide 201 to make fine adjustments in the up and down positions to achieve positioning; then the dump box 101 is opened again, waiting for the card to be put into the dump box 101; when the algorithm does not return that the height needs to be adjusted, at this time the car is in the leaving state, the dump box 101 is closed, and the state of the car arriving at the toll station island head continues to be obtained.

[0023] In the embodiment of the present invention, it also includes: If it is determined that a card has been put into the dump box 101, the card insertion message is reported and the card collection or return instruction is waited; when the card return instruction is received, wait for the card to be taken away, and after the card is taken away, report the card removal message and obtain the vehicle departure status. When the vehicle leaves, the dump box 101 is closed and the vehicle arrival status at the toll station island head is continued to be obtained; when the card collection instruction is received, the dump box 101 is closed and the card is collected; the card recovery message is reported, the dump box 101 is closed and the vehicle arrival status at the toll station island head is continued to be obtained; when no card collection instruction is received, continue to wait for the card collection or return instruction.

[0024] In the embodiment of the present invention, when the card is put into the tipping bucket 101 , the card is read successfully and the payment is successful, then the tipping bucket 101 moves to collect the card into the temporary storage mechanism 300 .

[0025] The face and window recognition algorithm is an image recognition technology integrated into the highway robot. It aims to capture the image of the front of the vehicle, automatically locate the window area and the driver's face, and accurately adjust the position of the exit robot to ensure that the ETC card can be smoothly issued to the driver. This algorithm combines image processing, machine learning, and deep learning technologies to achieve efficient and accurate window and face positioning. It has the characteristics of high precision, real-time, robustness, and scalability, and provides strong support for the intelligent and personalized services of the automatic card issuing machine.

[0026] In the embodiment of the present invention, algorithm identification includes: Step 31: image preprocessing; (1) Image capture: capturing an image of the front of the vehicle through the camera 102; (2) Image enhancement: The captured image is enhanced, including denoising, sharpening, and contrast adjustment, to improve image quality and obtain an enhanced image; (3) Image cropping: Crop the enhanced image according to the preset region of interest (ROI) to reduce the computational complexity of subsequent processing; Step 32: Window positioning; (1) Feature extraction: Use image processing technology to extract features of the window area, including edges, colors, and textures; (2) Window recognition: A deep learning model is used to classify the extracted features and identify the position and shape of the driver’s window. (3) Window boundary determination: Based on the recognition results, the precise boundary of the window is determined to provide a reference for subsequent face positioning; Step 33: face positioning; (1) Face detection: A deep learning face detection algorithm is used to detect the driver’s face in the window area. (2) Face position determination: Based on the position of the feature points, the precise position of the face is determined, and the offset of the face relative to the lifting exit robot is calculated; Step 34: Position adjustment; (1) Calculation of the position of the lifting exit robot: Based on the positioning results of the car window and the human face, combined with the algorithm logic preset by the device, the optimal position of the lifting exit robot is calculated; (2) Position adjustment command: Send a position adjustment command to the lifting exit robot to move it to the calculated optimal position; Step 35: Result feedback; (1) Positioning success / failure feedback: The algorithm determines whether the window and face positioning is successful and provides feedback to the system; (2) Error handling: If positioning fails, the algorithm will try to recapture the image or perform error handling to ensure the stability and reliability of the system.

[0027] The face window recognition algorithm has the following beneficial effects: High Precision: Advanced image processing technology and deep learning models are used to achieve high-precision positioning of vehicle windows and faces.

[0028] Real-time: The algorithm has fast processing speed and can quickly complete positioning and adjustment operations after the vehicle stops.

[0029] Robustness: Ability to cope with complex scenarios such as different lighting conditions, vehicle types, and driver postures to ensure positioning accuracy and stability.

[0030] Scalability: The algorithm can be customized and optimized according to actual needs to meet the needs of different application scenarios.

[0031] The present invention provides a lifting exit robot for window height positioning, such as Figures 2 to 6 As shown, the lifting export robot includes: a recovery panel 100, a lifting mechanism 200 and a temporary storage mechanism 300; The recycling panel 100 includes a tipping bucket 101, a camera 102, a payment module 103, and a display screen 104; the lifting mechanism 200 includes a lifting slide 201, a servo motor 202, an in-position sensor 203, and a panel bracket 204; The recycling panel 100 is fixed on the panel bracket 204, and the panel bracket 204 is connected to the lifting mechanism 200. The highest position of the panel bracket 204 is to the in-place sensor 203, and the distance between them is driven by the servo motor 202 to drive the lifting slide 201; the payment module 103 and the display screen 104 are fixed to the rear of the recycling panel 100 by threads, and the payment module 103 is used to scan the QR code; the display screen 104 is used to display the amount and license plate; the license plate is identified according to the camera 102, and the vehicle model database is matched at the same time to determine the vehicle model and move at different heights; when the card is put into the tipping bucket 101, the card reading is successful, and the payment is successful, then the tipping bucket 101 moves to collect the card into the temporary storage mechanism 300; when the number of recycled cards in the temporary storage mechanism 300 reaches the preset value, the lifting mechanism 200 will drop to the lowest point and recycle the card into the recycling box.

[0032] The present invention adopts traditional license plate recognition matching + independent camera secondary positioning to achieve precise positioning. An independent camera is set on the lifting panel to shoot and algorithm to identify the window position. According to the recognition result, a servo motor + screw lifting mechanism is used to achieve precise upper and lower position positioning, which greatly facilitates the driver's operation and improves traffic efficiency.

[0033] In the technical solution provided by the present invention, the method includes obtaining the status of the vehicle arriving at the toll station island head and judging whether the vehicle has reached the toll station island head; if it is judged that the vehicle has arrived at the toll station island head, the camera recognizes the license plate and matches the vehicle model database at the same time; if it is judged that the vehicle has not arrived at the toll station island head, the status of the vehicle arriving at the toll station island head continues to be obtained; when the vehicle model is matched in the vehicle model database, the window height of the corresponding vehicle model is obtained, and the lifting exit robot is moved to the corresponding height, the dump bucket is opened, and the algorithm recognition is started to recover the card; when the vehicle model is not matched in the vehicle model database, the lifting exit robot is directly moved to the corresponding height, the dump bucket is opened, and the algorithm recognition is started to recover the card. The method realizes precise positioning of the upper and lower positions, improves the convenience of the driver's operation, and improves the traffic efficiency.

[0034] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A method for locating vehicle window height, characterized in that: The method comprises: Step 1: Get the vehicle arrival status at the toll station island, and determine whether the vehicle has reached the toll station island; Step 2: If it is determined that the vehicle has arrived at the toll station island, the camera (102) recognizes the license plate and matches the vehicle model database; if it is determined that the vehicle has not arrived at the toll station island, continue to execute step 1; Step 3: When a vehicle model is matched in the vehicle model database, the window height of the corresponding vehicle model is obtained, and the lifting exit robot is moved to the corresponding height, the dump bucket (101) is opened, and the algorithm recognition is started to recover the card; when a vehicle model is not matched in the vehicle model database, the lifting exit robot is directly moved to the corresponding height, the dump bucket (101) is opened, and the algorithm recognition is started to recover the card.

2. The method according to claim 1, characterized in that In step 3, moving the lifting exit robot to a corresponding height includes: The height of the vehicle window is sent to the control end of the lifting exit robot, and the control end drives the servo motor (202) to drive the lifting slide (201) to move up and down.

3. The method according to claim 1, characterized in that In step 3, the dump bucket is opened and algorithm recognition is started to recover the card, including: The dump box (101) is opened, and the camera (102) is started to perform face and window recognition, and simultaneously determine whether a card is put into the dump box (101); if it is determined that no card is put into the dump box (101), when the algorithm returns that the height needs to be adjusted, the dump box (101) is closed at the same time, and the control end drives the servo motor (202) to drive the lifting slide (201) to perform fine adjustment of the upper and lower positions to achieve positioning; then the dump box (101) is opened again, waiting for the card to be put into the dump box (101); when the algorithm does not return that the height needs to be adjusted, and the vehicle is in a leaving state, the dump box (101) is closed, and the vehicle continues to obtain the state of arriving at the toll station island.

4. The method according to claim 3, characterized in that Also includes: If it is determined that a card has been put into the dump box (101), a card insertion message is reported, and the card collection or card return instruction is waited for; when a card return instruction is received, the card is waited for to be taken away, and after the card is taken away, a card removal message is reported, and the vehicle departure status is obtained. When the vehicle leaves, the dump box (101) is closed, and the vehicle arrival status at the toll station island head is continued to be obtained; when a card collection instruction is received, the dump box (101) is closed, and the card is collected; a card recovery message is reported, the dump box (101) is closed, and the vehicle arrival status at the toll station island head is continued to be obtained; when no card collection instruction is received, the card collection or card return instruction is continued to be waited for.

5. The method according to claim 4, characterized in that When the card is put into the tipping bucket (101), the card reading is successful and the payment is successful, then the tipping bucket (101) moves to collect the card into the temporary storage mechanism (300).

6. The method according to claim 1, characterized in that The algorithm identification includes: Step 31, image preprocessing; (1) Image capture: capturing an image of the front of the vehicle through a camera (102); (2) Image enhancement: Enhance the captured image, including denoising, sharpening, and contrast adjustment, to obtain an enhanced image; (3) Image cropping: crop the enhanced image according to the preset region of interest (ROI); Step 32: Window positioning; (1) Feature extraction: Use image processing technology to extract features of the window area, including edges, colors, and textures; (2) Window recognition: A deep learning model is used to classify the extracted features and identify the position and shape of the driver’s window. (3) Window boundary determination: Determine the precise boundary of the window based on the recognition results; Step 33: face positioning; (1) Face detection: A deep learning face detection algorithm is used to detect the driver’s face in the window area. (2) Face position determination: Based on the position of the feature points, the precise position of the face is determined, and the offset of the face relative to the lifting exit robot is calculated; Step 34: Position adjustment; (1) Calculation of the position of the lifting exit robot: Based on the positioning results of the car window and the human face, combined with the algorithm logic preset by the device, the optimal position of the lifting exit robot is calculated; (2) Position adjustment command: Send a position adjustment command to the lifting exit robot to move it to the calculated optimal position; Step 35: Result feedback; (1) Positioning success / failure feedback: The algorithm determines whether the window and face positioning is successful and provides feedback to the system; (2) Error handling: If positioning fails, the algorithm will try to recapture the image or perform error handling to ensure the stability and reliability of the system.

7. A lifting exit robot for window height positioning, characterized in that: The lifting exit robot is used to implement any one of the methods for window height positioning according to claims 1 to 6, and the lifting exit robot comprises: a recovery panel (100), a lifting mechanism (200) and a temporary storage mechanism (300); The recycling panel (100) comprises a tipping bucket (101), a camera (102), a payment module (103), and a display screen (104); the lifting mechanism (200) comprises a lifting slide (201), a servo motor (202), an in-position sensor (203), and a panel bracket (204); The recycling panel (100) is fixed on the panel bracket (204), the panel bracket (204) is connected to the lifting mechanism (200), the panel bracket (204) is at the highest position to the in-place sensor (203), and the distance between them is driven by the servo motor (202) to drive the lifting slide (201); the payment module (103) and the display screen (104) are fixed to the rear of the recycling panel (100) by screw threads, and the payment module (103) is used to scan the QR code; the display screen (104) is used to display the amount and the license plate; the license plate is identified according to the camera (102), and the vehicle model database is matched at the same time to determine the vehicle model and move at different heights; when the card is put into the tipping bucket (101), the card reading is successful, and the payment is successful, then the tipping bucket 101 moves to collect the card into the temporary storage mechanism (300); when the number of recycled cards in the temporary storage mechanism (300) reaches a preset value, the lifting mechanism (200) will drop to the lowest point and recycle the card into the recycling box.

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