Distance adjusting device integrating deep learning and computer vision

Abstract

The utility model provides a distance adjusting device integrating deep learning and computer vision, and belongs to the technical field of distance measurement. The problems that an existing distance adjusting device is low in detection precision and complex in structure, and a device adopting deep learning is poor in flexibility are solved. Comprising a crawler chassis, an electric shell is fixed to the middle of the crawler chassis, a mechanical arm and a central control module are installed on the top of the electric shell, a machine claw is installed at the end of the mechanical arm, a visual induction module is installed on the machine claw, a control electric box is installed at one end of the electric shell, and the visual induction module is electrically connected with the central control module. The central control module is electrically connected with the control electric box, and the control electric box is electrically connected with the driving end of the crawler chassis; an algorithm model for processing data acquired by the visual sensing module is arranged in the central control module; the distance adjusting device is applied to distance adjustment of industrial scenes.

Description

Technical Field

[0001] The utility model provides a distance adjustment device integrating deep learning and computer vision, belonging to the technical field of distance measurement. Background Art

[0002] The main purpose of the distance adjustment device is to accurately control the distance between the object and the equipment. It can be applied to distance detection in the fields of industrial automation, medical imaging equipment, and autonomous driving. In actual application, the accuracy and reliability of the distance adjustment device are crucial in the implementation of the entire system.

[0003] At present, there are three methods for distance measurement of distance adjustment devices: traditional adjustment method, machine vision-based adjustment method and deep learning-based adjustment method. However, in actual application, the above distance adjustment methods all have the following problems: traditional distance adjustment devices mostly rely on manual operation, which is inefficient and difficult to guarantee accuracy; some devices based on machine vision have complex mechanical structures, are prone to failure, and have high maintenance costs. Devices based on deep learning do not have flexible expansion slots, which can easily lead to functional limitations, thus affecting their application effects in complex and changeable scenarios. Utility Model Content

[0004] In order to solve the problems of low detection accuracy, complex structure, and poor flexibility of devices using deep learning in existing distance adjustment devices, the utility model proposes a distance adjustment device that integrates deep learning and computer vision. The purpose is to reduce the complexity of the device structure by combining computer vision with the existing device using deep learning, while improving the flexibility and detection accuracy of the device.

[0005] The technical solution adopted by the utility model is: a distance adjustment device integrating deep learning and computer vision, comprising a crawler chassis, an electric housing is fixed in the middle of the crawler chassis, a mechanical arm and a central control module are installed on the top of the electric housing, a machine claw is installed at the end of the mechanical arm, a visual sensing module is installed on the machine claw, a control electric box is installed at one end of the electric housing, the visual sensing module is electrically connected to the central control module, the central control module is electrically connected to the control electric box, and the control electric box is electrically connected to the driving end of the crawler chassis;

[0006] The central control module has a built-in algorithm model for processing the data collected by the visual sensing module;

[0007] The visual sensing module comprises a pan-tilt base with an adjustable angle installed on the top of the electric housing, a camera is fixed on the pan-tilt base, and a distance sensor is installed on one side of the camera.

[0008] Furthermore, the track chassis includes tracks, transmission rear wheels, track beams, and transmission wheels installed on both sides of the electric housing, wherein toothed transmission rear wheels are respectively installed at both ends of the track beam, and multiple toothed transmission wheels are respectively installed on the upper and lower sides of the track beam. The tracks are meshed with the transmission rear wheels and the transmission wheels, and the transmission rear wheels on both sides are connected by a transmission shaft, and a transmission motor for driving the transmission rear wheels is fixed on one side of the track beam.

[0009] Furthermore, the control box is provided with a visual switch, a laser switch, a transmission switch, an emergency master switch, a storage device, an expansion interface and a display, and a controller is installed inside the control box, and the controller is used to control the above switches and the display.

[0010] Furthermore, the central control module includes a plurality of beams fixed on the top surface of the electric housing, a platform is fixed on the plurality of beams, a central processing unit is fixed on the platform, and the central processing unit is electrically connected to the controller in the control box.

[0011] Furthermore, an obstacle avoidance camera is installed at the other end of the electric housing.

[0012] Furthermore, an alarm is installed on the top of the electric housing.

[0013] Furthermore, the distance sensor adopts a laser rangefinder.

[0014] Furthermore, a wireless communication module is installed in the control electrical box, and the controller communicates with the remote control terminal through the wireless communication module.

[0015] Furthermore, the transmission motor is a linear motor.

[0016] Furthermore, the display is a touch display.

[0017] The beneficial effects of the utility model compared with the prior art are:

[0018] First of all, the utility model can realize accurate measurement of distance. By using mature image segmentation algorithms and deep learning models and integrating them into the central processing unit of the device, it breaks through the limitations of traditional card slot functions, makes data transmission more efficient and stable, and makes the collaboration between devices smoother, thereby significantly improving the accuracy and efficiency of deep learning and computer vision analysis.

[0019] Secondly, the utility model provides multiple expansion interfaces, and users can flexibly add additional computing modules, storage modules or other functional modules according to actual needs, so as to better adapt to the needs of different scenarios and tasks. It effectively solves the problems of single function and poor scalability in the prior art, is no longer limited to fixed configuration, and greatly enhances the versatility and practicality of the device.

[0020] Thirdly, the utility model continuously transmits the distance obtained by the distance sensor back to the central processor, which can realize dynamic detection and control. At the same time, the central processor transmits the processed data to the controller, and the controller transmits the command to the transmission motor, which drives the transmission rear wheel and the transmission small wheel to rotate the gear on the crawler chassis, thereby controlling the operation of the crawler to realize the movement of the device.

[0021] Finally, the design of the utility model improves the overall performance and competitiveness of the device, provides more powerful technical support for the development of related fields, and promotes the widespread application and further development of deep learning and computer vision analysis technology. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] The utility model is further described below in conjunction with the accompanying drawings:

[0023] Figure 1 It is a schematic diagram of the overall structure of the device of the utility model;

[0024] Figure 2 for Figure 1 Left view of

[0025] Figure 3 for Figure 1 Rear view of

[0026] Figure 4 It is a structural diagram of the central control module;

[0027] Figure 5 It is a structural diagram of the visual sensing module;

[0028] In the figure: 1- crawler chassis; 2- electric housing; 3- control box; 4- central control module; 5- alarm; 6- mechanical arm; 7- visual sensing module; 8- obstacle avoidance camera; 9- mechanical claw;

[0029] 101- crawler track; 102- transmission rear wheel; 103- crawler track beam; 104- transmission small wheel; 105- transmission motor;

[0030] 301- visual switch; 302- laser switch; 303- transmission switch; 304- emergency master switch; 305- storage device; 306- expansion interface; 307- display;

[0031] 401- platform; 402- CPU; 403- beam;

[0032] 701- camera; 702- distance sensor; 703- gimbal base. DETAILED DESCRIPTION

[0033] like Figures 1 to 5As shown, the utility model provides a distance adjustment device integrating deep learning and computer vision, which adopts a modular design as a whole, including a crawler chassis 1, an electric housing 2 is fixed in the middle of the crawler chassis 1, a mechanical arm 6, a central control module 4 and an alarm 5 are installed on the top of the electric housing 2, a control box 3 is installed at the rear end of the electric housing 2, and an obstacle avoidance camera 8 is installed at the front end of the electric housing 2; wherein a machine claw 9 is installed at the end of the mechanical arm 6, and a visual sensing module 7 is installed on one side of the machine claw 9, and the visual sensing module 7 includes a camera 701, a distance sensor 702 and a pan-tilt base 703. The pan-tilt base 703 can adjust the angle of 360 degrees, so as to realize the adjustable angle of the camera 701, and the distance information between the device and the observed object is collected in real time through the camera 701 and the distance sensor 702. The setting of the obstacle avoidance camera 8 can realize the avoidance of obstacles and improve the safety of the device.

[0034] The distance sensor 702 may be a laser rangefinder.

[0035] The crawler chassis 1 includes a crawler 101, a transmission rear wheel 102, a crawler crossbeam 103, a transmission small wheel 104 and a transmission motor 105, wherein the two ends of the crawler crossbeam 103 are respectively installed with toothed transmission rear wheels 102, and four toothed transmission small wheels 104 are respectively installed on the upper and lower sides of the crawler crossbeam 103. The crawler 101 is meshed with the transmission rear wheel 102 and the transmission small wheel 104, and the transmission motor 105 is used to drive the transmission rear wheel 102. The transmission motor 105 specifically adopts a high-precision linear motor as a driving component, which can realize the precise adjustment of the moving distance of the device. In addition, a feedback module is added to the control circuit of the linear motor, which can monitor the operating status and output parameters of the linear motor in real time, and dynamically adjust according to the actual situation, further improving the accuracy and stability of the distance adjustment.

[0036] The control box 3 is provided with a visual switch 301, a laser switch 302, a transmission switch 303, an emergency master switch 304, a storage device 305, an expansion interface 306 and a display 307. A controller is installed inside the control box 3, and the controller is used to control the above switches and the display 307; wherein the visual switch 301 is used to control the start and stop of the camera 701, the laser switch 302 is used to control the start and stop of the distance sensor 702, the transmission switch 303 is used to control the start and stop of the transmission motor 105, and the storage device 305 is used to store the image data and sensor data collected by the visual sensing module 7, and the expansion interface 306 can be connected to multiple expansion slots, which meets the requirements of users to add different functional modules according to actual needs. And the expansion slot of the expansion interface 306 is convenient for users to install and remove.

[0037] The central control module 4 includes a plurality of beams 403 fixed on the top surface of the electric housing 2, a circular platform 401 is fixed on the plurality of beams 403, a central processor 402 is fixed on the platform 401, the central processor 402 is electrically connected to the controller in the control box 3, and the central processor 402 is used to process the data collected by the camera 701 and the distance sensor 702. Specifically, the central processor 402 is built with a mature image segmentation algorithm (such as threshold segmentation method, edge segmentation method, region segmentation method and morphological segmentation method, etc.) and a deep learning model (such as a CNN model or an LSTM model, etc.), and the image segmentation algorithm is used to segment the image collected by the camera 701, identify the outline and features of the observed object, and then obtain the feature information of the measured object through the CNN model. Then, combined with the distance data collected by the distance sensor 702, the precise distance between the device and the measured object can be calculated, and the precise distance value is transmitted to the controller. When the distance needs to be adjusted, the controller sends an instruction to the transmission motor 105 of the crawler chassis 1 according to the precise distance value to adjust the distance between the device and the observed object.

[0038] The electric housing 2 in the device is made of high-strength and lightweight materials, which not only improves the protective performance of the device, but also reduces the overall weight, making it easier to move and install the device. At the same time, a special anti-corrosion treatment is performed on the surface of the electric housing 2, so that it can adapt to various harsh working environments and extend the service life of the device.

[0039] The display 307 of this device can adopt a touch display, and the user can set the working parameters and operation mode of each electrical device through the touch screen. It also has a fault alarm function, which can promptly detect and prompt possible problems of each electrical device, making it convenient for users to perform maintenance and repairs.

[0040] The control box 3 of the device is also provided with a wireless communication module, and the controller can communicate with the remote control terminal through the wireless communication module, and set the working parameters and operation mode of each electrical device through the remote control terminal.

[0041] The principle of the utility model is as follows:

[0042] 1. Discovery and measurement of targets

[0043] The angle-adjustable camera 701 first detects the target object, transmits it to the central processor 402, and then measures the distance to the target object through the distance sensor 702.

[0044] 2. Data processing and modification

[0045] The data measured by the distance sensor 702 is transmitted to the central processor 402, and the central processor 402 can process the data and can also be connected to an external microcomputer to modify certain data.

[0046] 3. Mobile

[0047] According to the known distance data, the central processor 402 sends a command to the crawler chassis 1 to move the device toward the target object. Specifically, the central processor 402 transmits the command to the controller, and the controller analyzes the command and sends a command to the transmission motor 105.

[0048] Regarding the specific structure of the utility model, it should be explained that the connection relationship between the various component modules adopted in the utility model is definite and feasible. Except for special instructions in the embodiments, the specific connection relationship can bring corresponding technical effects and solve the technical problems raised by the utility model without relying on the execution of corresponding software programs. The components, modules, models of specific components and the connection methods between each other appearing in the utility model, as well as the conventional use methods and expected technical effects brought about by the above-mentioned technical features, except for specific instructions, all belong to the disclosed contents in patents, journal articles, technical manuals, technical dictionaries, and textbooks that can be obtained by technical personnel in this field before the application date, or belong to the existing technologies such as conventional technologies and common knowledge in this field, and there is no need to elaborate, so that the technical solution provided in this case is clear, complete and feasible, and the corresponding physical products can be reproduced or obtained according to the technical means.

[0049] Finally, it should be noted that the above embodiments are only used to illustrate the technical solution of the utility model, rather than to limit it. Although the utility model has been described in detail with reference to the aforementioned embodiments, ordinary technicians in this field should understand that they can still modify the technical solutions recorded in the aforementioned embodiments, or replace some or all of the technical features therein with equivalents. However, these modifications or replacements do not make the essence of the corresponding technical solution deviate from the scope of the technical solution of the embodiments of the utility model.

Claims

1. A distance adjustment device integrating deep learning and computer vision, characterized in that: The crawler chassis (1) comprises an electric housing (2) fixed in the middle of the crawler chassis (1), a mechanical arm (6) and a central control module (4) are mounted on the top of the electric housing (2), a machine claw (9) is mounted on the end of the mechanical arm (6), a visual sensing module (7) is mounted on the machine claw (9), a control electric box (3) is mounted on one end of the electric housing (2), the visual sensing module (7) is electrically connected to the central control module (4), the central control module (4) is electrically connected to the control electric box (3), and the control electric box (3) is electrically connected to the driving end of the crawler chassis (1); The central control module (4) has a built-in algorithm model for processing the data collected by the visual sensing module (7); The visual sensing module (7) comprises an angle-adjustable pan-tilt base (703) mounted on the top of the electric housing (2), a camera (701) being fixed on the pan-tilt base (703), and a distance sensor (702) being mounted on one side of the camera (701).

2. The distance adjustment device integrating deep learning and computer vision according to claim 1, characterized in that: The crawler chassis (1) comprises crawlers (101) mounted on both sides of an electric housing (2), a transmission rear wheel (102), a crawler crossbeam (103), and a transmission small wheel (104), wherein toothed transmission rear wheels (102) are respectively mounted on both ends of the crawler crossbeam (103), and a plurality of toothed transmission small wheels (104) are respectively mounted on the upper and lower sides of the crawler crossbeam (103), the crawler (101) is meshed with the transmission rear wheel (102) and the transmission small wheel (104), the transmission rear wheels (102) on both sides are connected via a transmission shaft, and a transmission motor (105) for driving the transmission rear wheel (102) is fixed on one side of the crawler crossbeam (103).

3. The distance adjustment device integrating deep learning and computer vision according to claim 2, characterized in that: The control box (3) is provided with a visual switch (301), a laser switch (302), a transmission switch (303), an emergency master switch (304), a storage device (305), an expansion interface (306) and a display (307). A controller is installed inside the control box (3), and the controller is used to control the above switches and the display (307).

4. The distance adjustment device integrating deep learning and computer vision according to claim 3, characterized in that: The central control module (4) comprises a plurality of crossbeams (403) fixed on the top surface of the electric housing (2), a platform (401) being fixed on the plurality of crossbeams (403), a central processing unit (402) being fixed on the platform (401), and the central processing unit (402) being electrically connected to a controller in the control electric box (3).

5. The distance adjustment device integrating deep learning and computer vision according to claim 1, characterized in that: An obstacle avoidance camera (8) is installed at the other end of the electric housing (2).

6. The distance adjustment device integrating deep learning and computer vision according to claim 1, characterized in that: An alarm (5) is also installed on the top of the electric housing (2).

7. The distance adjustment device integrating deep learning and computer vision according to claim 1, characterized in that: The distance sensor (702) is a laser rangefinder.

8. The distance adjustment device integrating deep learning and computer vision according to claim 3, characterized in that: A wireless communication module is also installed in the control electrical box (3), and the controller communicates with the remote control terminal via the wireless communication module.

9. The distance adjustment device integrating deep learning and computer vision according to claim 2, characterized in that: The transmission motor (105) is a linear motor.

10. The distance adjustment device integrating deep learning and computer vision according to claim 8, characterized in that: The display (307) is a touch display.

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