Intelligent agricultural robot based on visual positioning

Abstract

The invention relates to the technical field of agricultural robots, and discloses an intelligent agricultural robot based on visual localization, which comprises a main control chip, a data acquisition module, a power supply module, a communication module, an execution mechanism module, an obstacle avoidance module and a man-machine interaction module, the data acquisition module, the power supply module, the communication module, the execution mechanism module, the obstacle avoidance module and the man-machine interaction module are electrically connected with the main control chip; and the main control chip is in signal connection with the GNSS. Through cooperative use of the photoresistor sensor, the soil humidity sensor, the camera and the GNSS, the robot collects illumination intensity in real time through the photoresistor sensor, the camera can identify plants, observe crop health and observe the surrounding environment of the crops, and soil is detected through the soil humidity sensor; the GNSS and the camera are matched for use, so that the equipment can be controlled to move, accurate seeding can be completed, and the functions of weeding, fruit picking and seed planting are achieved.

Description

Technical Field

[0001] The present invention relates to the technical field of agricultural robots, and in particular to an intelligent agricultural robot based on visual positioning. Background Art

[0002] Agricultural robots refer to automated robots or mechanical devices designed specifically for use in the agricultural field. Agricultural robots are changing the way crops are grown, ranging from machines that automatically plant and harvest crops to advanced methods that make agriculture more precise. These robots and technologies improve agricultural production by solving major problems, improving farm operating efficiency, increasing yields, and reducing environmental impact. Agricultural robots have a variety of uses with the goal of making agriculture more efficient, productive, and environmentally friendly.

[0003] With the advancement of agricultural modernization, traditional manual labor methods have become difficult to adapt to the requirements of modern agriculture in terms of efficiency and output. In view of this, it is of great significance to design an integrated automated multifunctional agricultural machinery equipment, which can be used to solve the problems of weeding, fruit picking, and seed planting, thereby increasing crop yields. Summary of the invention

[0004] In view of the deficiencies in the prior art, the present invention provides an intelligent agricultural robot based on visual positioning, which solves the problems raised by the above-mentioned background technology.

[0005] The present invention provides the following technical solution: a smart agricultural robot based on visual positioning, comprising a main control chip, a data acquisition module, a power module, a communication module, an actuator module, an obstacle avoidance module and a human-computer interaction module, wherein the data acquisition module, the power module, the communication module, the actuator module, the obstacle avoidance module and the human-computer interaction module are electrically connected to the main control chip;

[0006] The main control chip signal is connected to the GNSS.

[0007] Preferably, the main control chip adopts an STM32 single-chip microcomputer controller.

[0008] Preferably, the power module includes a solar panel and a lithium battery, and the solar panel is electrically connected to the lithium battery.

[0009] Preferably, the data acquisition module includes a camera, a soil moisture sensor and a photosensor.

[0010] Preferably, the soil moisture sensor is a Decagon Devices 5TE sensor, and the photosensor is of model GL5537.

[0011] Preferably, the actuator module includes a robotic arm, a weeding device, a sowing device and a picking device.

[0012] Preferably, the robotic arm is a six-axis robotic arm, and a camera is installed on the head of the robotic arm.

[0013] Preferably, the picking device adopts one of a clamp and a suction cup, and the obstacle avoidance module combines ultrasound with vision.

[0014] The present invention has the following beneficial effects:

[0015] 1. This smart agricultural robot based on visual positioning is equipped with a photoresistor sensor, a soil moisture sensor, a camera and the coordinated use of GNSS. The robot collects light intensity in real time through the photoresistor sensor. The camera can identify plants, observe the health of crops and the surrounding environment of crops. The soil is detected through the soil moisture sensor. The coordinated use of GNSS and the camera can control the movement of the equipment and complete precise sowing, thereby realizing the functions of weeding, fruit picking and seed planting.

[0016] 2. This smart agricultural robot based on visual positioning uses its own satellite technology to ensure that the agricultural robot can still operate reliably in areas without network connection. At the same time, it uses photovoltaic technology and green nanotechnology to reduce carbon emissions and protect the environment. Through system testing, the design reduces dependence on manual labor, cuts material costs, increases crop yields, and is more environmentally friendly. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 It is the overall functional block diagram of the system of the present invention;

[0018] Figure 2 The hardware circuit diagram of the photoresistor sensor of the present invention;

[0019] Figure 3 The human-computer interaction interface of the present invention;

[0020] Figure 4 This is a diagram of the visual robotic arm system of the present invention;

[0021] Figure 5 This is a diagram of the human-computer interaction system of the present invention;

[0022] Figure 6 This is a diagram of the soil moisture sensor system of the present invention;

[0023] Figure 7 This is a diagram of the navigation and positioning system of the present invention;

[0024] Figure 8 This is a diagram of the solar panel system of the present invention;

[0025] Fig. 9 This is a graph of test results for the present invention;

[0026] Fig.10 This is a diagram of the weed control test results of the present invention. DETAILED DESCRIPTION

[0027] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, 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.

[0028] See also Figure 1 - Fig.10 , a smart agricultural robot based on visual positioning, including a main control chip, a data acquisition module, a power module, a communication module, an actuator module, an obstacle avoidance module and a human-computer interaction module. The data acquisition module, the power module, the communication module, the actuator module, the obstacle avoidance module and the human-computer interaction module are electrically connected to the main control chip. The human-computer interaction function has a vehicle body parameter setting function, covering GPS mode and camera settings, which can meet the user's needs for vehicle positioning and image acquisition. Secondly, it provides a rich setting option of starting display mode, angle mode and speed adjustment, and the display mode and angle mode can be further fine-tuned in the system settings. At the same time, there is also a navigation mode to provide accurate guidance for users' travel. Thirdly, it can monitor the vehicle and operation, display the vehicle speed in real time, and ensure driving safety and operation specifications. Fourthly, it includes data management functions, which is convenient for users to effectively manage and analyze vehicle operation data. In addition, it is also set There is an exit option, which allows users to exit the system at any time, making operation more convenient and flexible. Capacitive touch screens mainly detect touch positions accurately by sensing changes in human body capacitance. The screen surface is covered with a layer of transparent conductive material to form a capacitor layer. When a finger touches the screen, the electric field distribution on the screen will change. The sensor on the screen can detect this electric field change and accurately determine the touch position. The sensors are arranged at the four corners or edges of the screen and accurately calculate the coordinates of the touch point by measuring the capacitance change. Capacitive touch screens are extremely sensitive to touch input and can detect extremely slight touches. They support multi-touch technology, allowing users to use multiple fingers at the same time to operate, thereby providing an extremely rich interactive experience. In addition, capacitive touch screens are usually more durable than resistive touch screens and are not easily damaged by physical damage. Their transparent conductive layer has extremely high transparency and will not affect the display effect of the screen at all.

[0029] The main control chip signal is connected to GNSS. The GNSS antenna and board receive the longitude and latitude information, and send the information to the display terminal after calculation. The display terminal converts the longitude and latitude heading angle information into a rectangular coordinate system with the vehicle body as the origin to calculate the operation planning path. After that, the system will compare the vehicle body position with the planned path, calculate the position deviation, and send this information to the control terminal. After receiving the distance and angle information from the vehicle body to the route, the control terminal will collect the steering wheel angle information and control the motor to drive the steering wheel to turn through the algorithm. Subsequently, the agricultural machinery moves forward and corrects the vehicle body position. The Beidou system refreshes and obtains new position information, and then sends this information to the display terminal.

[0030] In a preferred embodiment, the main control chip adopts an STM32 single-chip microcomputer controller. The STM32 single-chip microcomputer controller plays a vital role in the system. It undertakes the tasks of data transmission, storage, processing and analysis, and is also responsible for controlling the execution module and calculating the control quantity in the control module.

[0031] In a preferred embodiment, the power module includes a solar panel and a lithium battery, which are electrically connected to the lithium battery. When the machine is not working, a dual charging mode is adopted. On the one hand, the solar panel fully absorbs light energy and converts it into electrical energy for storage; on the other hand, the lithium battery is replenished with electricity through contact charging. Monocrystalline silicon solar panels can generate more electricity under the same lighting conditions. The stability of their materials makes the performance of the solar panels change less during long-term use, and they have a service life of 20-30 years. Monocrystalline silicon solar panels have high reliability and can work normally under various harsh environmental conditions. Their power attenuation rate is low, and they can still maintain high power generation efficiency after long-term use, and the maintenance cost is also low.

[0032] In a preferred embodiment, the data acquisition module includes a camera, a soil moisture sensor and a photosensitive sensor. The data acquisition module can not only shoot and identify crops, but also monitor the growth environment of crops. The soil moisture sensor uses the principle of electromagnetic pulses to test the apparent dielectric constant of the soil by measuring the frequency of electromagnetic waves propagating in the soil. Since the dielectric constant of water is much larger than the dielectric constants of other materials and air in the soil matrix, the dielectric constant of the soil mainly depends on the water content of the soil, so that the relative water content of the soil can be derived. The FDR sensor emits high-frequency electromagnetic waves into the soil, usually between 10MHz and 1GHz, and measures the reflection and propagation time of the electromagnetic waves in the soil. The moisture in the soil will affect the propagation speed and reflection characteristics of the electromagnetic waves, thereby changing the dielectric constant of the soil. By measuring the phase and amplitude changes of the reflected signal, the sensor can calculate the dielectric constant of the soil and then deduce the soil humidity.

[0033] In a preferred embodiment, the soil moisture sensor uses a Decagon Devices 5TE sensor. 5TE is a sensor for measuring soil moisture content, conductivity and temperature. It has a simple structure, is easy to operate, has little disturbance to the soil, and is safe and reliable. It takes a short measurement time and is easy to install and use. It can quickly obtain high-precision soil moisture data, provide comprehensive soil environmental information, and meet the needs of most scenarios. It can continuously measure and monitor humidity changes in real time. It is easy to connect to automatic recording systems and computers to realize automatic data collection and processing. The model of the photosensor is GL5537. The GL5537 photoresistor sensor has high sensitivity to changes in light intensity, can respond quickly, and can work stably under different lighting conditions. In addition, the GL5537 photosensor is low in cost and easy to use on a large scale. The maximum tolerable voltage of the GL5537 photoresistor sensor is 150 volts DC (150VDC) and the power is 100 milliwatts. Its rise time and fall time are 20 milliseconds and 30 milliseconds respectively. The operating temperature range is between -30℃ and +70℃. The core material of the GL5537 photosensor is usually cadmium sulfide. When light shines on GL5537, photons interact with electrons in the material, causing the electrons to jump into the conduction band to form free electron-hole pairs. The free electrons and holes increase the conductivity of the material, thereby reducing the resistance value. The stronger the light intensity, the lower the resistance value of GL5537, and the weaker the light intensity, the higher the resistance value.

[0034] In a preferred embodiment, the actuator module includes a robotic arm, a weeding device, a sowing device and a picking device. When the module receives the corresponding instructions, the robotic arm will accurately reach the specified position, and then use the weeding device, sowing device or picking equipment to perform weeding, sowing or picking operations according to different task requirements.

[0035] In a preferred embodiment, the robotic arm adopts a six-axis robotic arm, and a camera is installed on the head of the robotic arm. The robotic arm has six degrees of freedom. This feature gives it the ability to move and rotate in all directions in three-dimensional space. No matter which direction it is facing or what angle it is adjusted to, it can be easily achieved. The six-degree-of-freedom robotic arm has strong adaptability and can work in a variety of different working environments. Each joint is independently controlled and can be accurately positioned during operation. In addition, the robotic arm is also equipped with advanced control algorithms and artificial intelligence technology, so that it has the ability of autonomous learning. It can accumulate experience during continuous operation, continuously optimize its own operating methods, and greatly improve work efficiency. As time goes by, the robotic arm can complete various tasks more and more proficiently.

[0036] In a preferred embodiment, the picking device adopts one of a clamp and a suction cup. The obstacle avoidance module combines ultrasound with vision. The ultrasonic obstacle avoidance technology is based on the principle of ultrasonic ranging. The ultrasonic sensor is composed of a transmitter, a receiver and a control circuit. The transmitter can emit ultrasonic pulses, and the receiver receives the ultrasonic waves reflected by the obstacle. By measuring the time difference between the emission and reception of ultrasonic waves and calculating it according to the speed of sound, which is usually about 340m / s in the air, the distance between the sensor and the obstacle can be determined. Visual obstacle avoidance mainly relies on the image information captured by the camera. After image processing and analysis of computer vision algorithms, the image information can extract key information such as the outline, depth, and position of the obstacle. Based on this information, the system can judge the distance and position of the obstacle, thereby making obstacle avoidance decisions. By combining ultrasonic obstacle avoidance with visual obstacle avoidance, the obstacle avoidance performance of this robot is made stronger.

[0037] It should be noted that, in this article, relational terms such as first and second are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device.

[0038] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A smart agricultural robot based on visual positioning, characterized in that: It includes a main control chip, a data acquisition module, a power module, a communication module, an actuator module, an obstacle avoidance module and a human-computer interaction module, wherein the data acquisition module, the power module, the communication module, the actuator module, the obstacle avoidance module and the human-computer interaction module are electrically connected to the main control chip; The main control chip signal is connected to the GNSS.

2. The intelligent agricultural robot based on visual positioning according to claim 1, characterized in that: The main control chip adopts an STM32 single-chip microcomputer controller.

3. The intelligent agricultural robot based on visual positioning according to claim 1, characterized in that: The power module includes a solar panel and a lithium battery, and the solar panel is electrically connected to the lithium battery.

4. The intelligent agricultural robot based on visual positioning according to claim 1, characterized in that: The data acquisition module includes a camera, a soil moisture sensor and a photosensor.

5. The intelligent agricultural robot based on visual positioning according to claim 4, characterized in that: The soil moisture sensor is a Decagon Devices 5TE sensor, and the photosensor is a GL5537.

6. The intelligent agricultural robot based on visual positioning according to claim 1, characterized in that: The actuator module includes a mechanical arm, a weeding device, a sowing device and a picking device.

7. The intelligent agricultural robot based on visual positioning according to claim 6, characterized in that: The mechanical arm adopts a six-axis mechanical arm, and a camera is installed on the head of the mechanical arm.

8. The intelligent agricultural robot based on visual positioning according to claim 6, characterized in that: The picking device adopts one of a clamp and a suction cup, and the obstacle avoidance module combines ultrasound with vision.

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