Traversing machine AI guidance system

Abstract

The utility model discloses an AI guidance system of a traversing machine, which belongs to the technical field of traversing machine navigation and comprises a microcontroller, a 9-degree-of-freedom inertial navigation sensing measurement module, a visual monitoring module, a double-frequency positioning module, a driving module and a power supply module. The method has the characteristics of high efficiency, reliability and flexibility, is suitable for various complex application scenes, and has a wide market prospect.

Description

Technical Field

[0001] The utility model relates to the technical field of drone navigation, and more particularly to an AI guidance system for a drone. Background Art

[0002] With the advancement of drone technology, traditional manual control methods are no longer sufficient for operating in complex environments. Especially in areas like security surveillance and emergency rescue, the demand for drones to be more intelligent and automated is increasing. Existing drones often rely on the pilot's skill, which limits their efficiency and flexibility in specific situations. With the continuous advancement of drone technology, drones have become a major highlight in the drone industry with their superior flight performance and flexible maneuvers. However, existing drone guidance methods are unable to meet the needs of more diverse application scenarios.

[0003] Therefore, how to provide an AI guidance system for a FPV is an urgent problem that needs to be solved by those skilled in the art. Utility Model Content

[0004] In view of this, the utility model provides an AI guidance system for a FPV drone, which meets the needs of more application scenarios through modules such as a microcontroller, a 9-degree-of-freedom inertial navigation sensor measurement module, a visual monitoring module, a dual-frequency positioning module, a drive module, and a power supply module.

[0005] In order to achieve the above purpose, the utility model adopts the following technical solutions:

[0006] A drone AI guidance system, comprising:

[0007] Microcontroller, 9-DOF inertial navigation sensor measurement module, visual monitoring module, dual-frequency positioning module, drive module and power module;

[0008] The microcontroller exchanges data with the 9-DOF inertial navigation sensor measurement module, the visual monitoring module, the dual-frequency positioning module and the driving module respectively through the SPI bus;

[0009] The 9-DOF inertial navigation sensor measurement module is used to obtain information on the attitude, angular velocity and linear acceleration of the FPV;

[0010] The visual monitoring module is used to obtain information on environmental perception, target recognition, and tracking;

[0011] The dual-frequency positioning module is used to obtain real-time positioning information;

[0012] The driving module is connected to the four motors of the FPV machine to realize the control of the FPV machine;

[0013] The power supply module supplies power to the microcontroller, the 9-DOF inertial navigation sensor measurement module, the visual monitoring module, the dual-frequency positioning module, and the driving module respectively.

[0014] Furthermore, the 9-DOF inertial navigation sensor measurement module includes: a digital compass, an HMC5883L three-axis magnetic induction sensor, an ADXL345 three-axis acceleration sensor and an ITG3200 three-axis gyroscope, which are respectively connected to the microcontroller.

[0015] Furthermore, the visual monitoring module includes: a multispectral / hyperspectral camera, a binocular camera and a thermal imaging camera, which are respectively connected to the microcontroller.

[0016] Furthermore, the dual-frequency positioning module includes: a positioning antenna, a signal transmitting antenna, a positioning unit and a navigation satellite system receiver;

[0017] The positioning unit is connected to the signal transmitting antenna, and both the signal transmitting antenna and the positioning antenna are connected to the navigation satellite system receiver. The navigation satellite system receiver is used to store satellite positions and signal arrival time information.

[0018] Furthermore, the model of the microcontroller is STM32.

[0019] Furthermore, the driving module includes: an electronic speed regulator and an optocoupler isolation circuit;

[0020] The electronic speed regulator is connected to an optocoupler isolation circuit, and the optocoupler isolation circuit is connected to the microcontroller.

[0021] Furthermore, the electronic speed controller is any one of the following models: Hobbywing Xerun 50A, T-Motor F40 Pro II 50A, DJI E500 50A, Hobbywing XRotor 4-in-1 50A, or T-Motor F40 Pro II 4-in-1 50A.

[0022] Furthermore, it also includes: indicator lights and buttons;

[0023] The indicator light and the button are connected to the microcontroller respectively.

[0024] Furthermore, it also includes: a communication module;

[0025] The communication module is connected to the microcontroller.

[0026] Furthermore, the communication module includes:

[0027] 4GHz wireless communication unit, 8GHz image transmission unit, 433MHz / 915MHz wireless communication unit, Wi-Fi module, 4G / 5G LTE module, LoRa module and Zigbee module.

[0028] It can be seen from the above technical solutions that compared with the existing technology, the present invention discloses an AI guidance system for a FPV, which, through integrated navigation, positioning, perception and communication modules, has the characteristics of high efficiency, reliability and flexibility, is suitable for a variety of complex application scenarios, and has broad market prospects. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are merely embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on the provided drawings without paying any creative work.

[0030] Figure 1 It is a structural diagram of the utility model;

[0031] Figure 2 The power module circuit diagram provided by the utility model;

[0032] Figure 3 This is a schematic diagram of the optocoupler isolation circuit provided by the utility model. DETAILED DESCRIPTION

[0033] 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 embodiments described 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 making creative efforts are within the scope of protection of the present invention.

[0034] See also Figure 1 The present invention discloses an AI guidance system for a drone, including:

[0035] Microcontroller, 9-DOF inertial navigation sensor measurement module, visual monitoring module, dual-frequency positioning module, drive module and power module;

[0036] The microcontroller exchanges data with the 9-DOF inertial navigation sensor measurement module, visual monitoring module, dual-frequency positioning module and drive module through the SPI bus.

[0037] The 9-DOF inertial navigation sensor measurement module is used to obtain the attitude, angular velocity, and linear acceleration information of the FPV;

[0038] The visual monitoring module is used to obtain information on environmental perception, target recognition, and tracking;

[0039] The dual-frequency positioning module is used to obtain real-time positioning information;

[0040] The driver module is connected to the four motors of the drone to control it.

[0041] The power modules respectively provide power for the microcontroller, 9-DOF inertial navigation sensor measurement module, visual monitoring module, dual-frequency positioning module, and drive module.

[0042] Specifically, the microcontroller exchanges data with each module through the SPI bus to form an efficient control system that can quickly respond to various inputs and improve the control performance and reaction speed of the FPV.

[0043] In one embodiment, see Figure 2 The figure shows the schematic diagram of the power module circuit provided by the present invention, which includes: a boost controller, a MOSFET power switch tube Q, an inductor L, a diode D, an output filter capacitor C, a short-circuit protection, a battery sampling and feedback loop;

[0044] Specifically, the core of the boost controller circuit is responsible for controlling the switching of the MOSFET to achieve the boost function. It includes several pins: CS1 and CS2 are current sense pins; EN / SYNC is the enable / synchronization pin; VIN is the input voltage pin; SS is the soft-start pin; FB is the feedback pin; and GND is the ground pin.

[0045] Specifically, the MOSFET power switch Q switches on and off according to the PWM signal from the boost controller. When the MOSFET power switch Q turns on, the inductor L begins to store energy. When the MOSFET power switch Q turns off, the inductor releases energy and supplies power to the load through the diode D.

[0046] Specifically, the inductor L stores energy during the on-time of the MOSFET power switch tube Q and releases the energy during the off-time of the MOSFET, thereby achieving a boost effect.

[0047] Specifically, the diode D prevents the reverse electromotive force generated by the inductor during the discharge process from damaging the MOSFET and ensures that the current can only flow in one direction from the inductor to the load.

[0048] Specifically, the output filter capacitor C is used to smooth the output voltage and reduce ripple.

[0049] Specifically, the short-circuit protection part monitors the output current and immediately cuts off the MOSFET once it exceeds the set threshold to prevent overcurrent from damaging the device.

[0050] Specifically, BAT1 and BAT2 are input and output power supplies, which feed back a portion of the output voltage to the FB pin of the boost controller through a resistor divider network to adjust the PWM duty cycle, maintain output voltage stability, and amplify the output current for short-circuit protection.

[0051] More specifically, the power module operates as follows: when the MOSFET is on, the inductor charges, increasing the current. When the MOSFET is off, the inductor discharges to the load through the diode while continuing to charge the inductor, achieving a voltage boost. A feedback loop monitors the output voltage. If the output voltage falls below the target value, the PWM duty cycle is increased; otherwise, the PWM duty cycle is reduced to maintain a stable output voltage. The output current is monitored, and if it exceeds a safe range, the MOSFET is immediately turned off to prevent overcurrent damage. This power module provides stable power to all system components, ensuring the reliability and safety of the drone during extended flight.

[0052] In a specific embodiment, the 9-DOF inertial navigation sensor measurement module includes: a digital compass, an HMC5883L three-axis magnetic induction sensor, an ADXL345 three-axis acceleration sensor, and an ITG3200 three-axis gyroscope, which are respectively connected to a microcontroller.

[0053] Specifically, the use of a 9-degree-of-freedom inertial navigation sensor measurement module combined with a dual-frequency positioning module can achieve high-precision attitude, angular velocity and linear acceleration measurements, ensuring the stable flight and precise positioning of the FPV in complex environments.

[0054] In a specific embodiment, the visual monitoring module includes: a multispectral / hyperspectral camera, a binocular camera, and a thermal imaging camera, which are respectively connected to a microcontroller.

[0055] Specifically, the visual monitoring module integrates multispectral / hyperspectral cameras, binocular cameras and thermal imaging cameras, which can perform environmental perception, target recognition and tracking under different lighting and weather conditions, enhancing the intelligence and adaptability of the FPV.

[0056] In a specific embodiment, the dual-frequency positioning module includes: a positioning antenna, a signal transmitting antenna, a positioning unit and a navigation satellite system receiver; the positioning unit is connected to a microcontroller.

[0057] The positioning unit is connected to the signal transmitting antenna, and both the signal transmitting antenna and the positioning antenna are connected to a navigation satellite system receiver. The navigation satellite system receiver is used to store satellite positions and signal arrival time information.

[0058] In a specific embodiment, the microcontroller is a STM32.

[0059] In a specific embodiment, the driving module includes: an electronic speed regulator and an optocoupler isolation circuit;

[0060] The electronic speed regulator is connected to the optocoupler isolation circuit, and the optocoupler isolation circuit is connected to the microcontroller.

[0061] For details, see Figure 3 , which is a schematic diagram of the optocoupler isolation circuit provided by the utility model, including: input side, output side and photoelectric isolation;

[0062] Specifically, the input signals (PWM1, PWM2, PWM3, and PWM4) are connected to the TLP521-4 input terminals (IN1+, IN1-, IN2+, IN2-, IN3+, IN3-, IN4+, and IN4-) through four 1kΩ resistors. These input signals come from the microcontroller's pulse-width modulation (PWM) signals.

[0063] Specifically, the output terminals (OUT1+, OUT1-, OUT2+, OUT2-, OUT3+, OUT3-, OUT4+, and OUT4-) of the four-channel optocoupler TLP521-4 are connected to a 7V power supply and ground via four 1kΩ resistors. After optical isolation, the output signals are transmitted to the next-stage circuit (the electronic speed regulator).

[0064] Specifically, the four-channel optocoupler TLP521-4 contains a light-emitting diode (LED) and a phototransistor. When the input receives a PWM signal, the LED illuminates, turning on the phototransistor and transmitting the input signal to the output. Optical isolation effectively prevents high voltage or current from flowing from one side to the other, protecting electronic components on both sides from damage. By introducing an optocoupler isolation circuit, this utility model improves the electrical safety of the FPV drone, reduces the risk of failure, and ensures stable system operation.

[0065] In a specific embodiment, the electronic speed controller is any one of the following models: Hobbywing Xerun 50A, T-Motor F40 Pro II 50A, DJI E500 50A, Hobbywing XRotor 4-in-1 50A, or T-Motor F40 Pro II 4-in-1 50A.

[0066] In a specific embodiment, it further includes: an indicator light and a button;

[0067] The indicator lights and buttons are connected to the microcontroller respectively.

[0068] Specifically, the design of indicator lights and buttons enhances the user interaction experience, making operation easier and more intuitive, and facilitating real-time monitoring and control of the drone's status.

[0069] Specifically, the one-button lock function can be achieved through the button: the operation is simple, just place the target in the middle of the image, flick the switch to lock the target and start tracking.

[0070] In a specific embodiment, it further includes: a communication module;

[0071] The communication module is connected to the microcontroller.

[0072] In a specific embodiment, the communication module includes:

[0073] 4GHz wireless communication unit, 8GHz image transmission unit, 433MHz / 915MHz wireless communication unit, Wi-Fi module, 4G / 5G LTE module, LoRa module and Zigbee module.

[0074] Specifically, the communication module supports multiple wireless communications (such as Wi-Fi, 4G / 5G LTE, LoRa, etc.), enabling remote control and data transmission, expanding the application scenarios of the FPV drone, such as monitoring, mapping, and rescue. At the same time, even if the remote control signal is poor or lost, or the image return signal is interfered with or lost, the utility model will take over the FPV drone to ensure the mission is completed.

[0075] Specifically, the independent design of each module (such as drive module, positioning module, communication module, etc.) makes the system easy to maintain and upgrade, and convenient for customization according to different application requirements.

[0076] In a specific embodiment, the present invention can be used on a GD-7 drone, which has a 7-inch frame, a 324mm wheelbase, dimensions of 246*337*65mm, a weight of 685g, a 2807-1300KV motor, 3 7537*3 propellers, a 50A 4-in-1 electronic control system, an F405V3 flight controller, a 5.8G 2.5 video transmission system, an ELRS915MHZ receiver, a 1200TVL480P camera, a 5.8GHz high-gain antenna for long-distance navigation, and a 6S4200mAh battery. The drone has a payload of 1.5kg (10 minutes of flight time), a flight speed of 150km / h, a flight time of 20 minutes, and a remote control distance of 8km.

[0077] Specifically, the microcontroller in this utility model stores an existing AI guidance algorithm. This vision-based AI guidance algorithm can use people, vehicles, and objects as guidance factors. Based on visible light recognition of target features, it can lock onto the target's position and guide the drone to track it. The specific operation of the drone is the same as that of a standard drone. The difference is that after switching to AI guidance mode, the drone will autonomously fly based on the selected target, aiming to achieve its attack objective. It also has the ability to recognize multiple targets, accurately distinguishing and tracking multiple targets even in complex environments.

[0078] In a specific embodiment, the present invention is also equipped with a high-speed flight platform that can accommodate a variety of sizes of drone bodies (5 inches to 15 inches), with a maximum speed of up to 150 km / h, ensuring rapid response and execution of tasks.

[0079] In a specific embodiment, the present invention is also equipped with a remote monitoring and command system, which transmits real-time images back to the command center through built-in audio and video transmission equipment, supports intranet broadcast sharing, and facilitates collaborative work among multiple departments.

[0080] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on the differences from other embodiments. Reference can be made to the common and similar parts between the various embodiments. For the devices disclosed in the embodiments, since they correspond to the methods disclosed in the embodiments, the description is relatively simple, and the relevant parts can be referred to the method description.

[0081] The above description of the disclosed embodiments will enable one skilled in the art to implement or use the present invention. Various modifications to these embodiments will be readily apparent to one skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention is not limited to the embodiments shown herein but is intended to conform to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A drone AI guidance system, characterized by: include: Microcontroller, 9-DOF inertial navigation sensor measurement module, visual monitoring module, dual-frequency positioning module, drive module and power module; The microcontroller exchanges data with the 9-DOF inertial navigation sensor measurement module, the visual monitoring module, the dual-frequency positioning module and the driving module respectively through the SPI bus; The 9-DOF inertial navigation sensor measurement module is used to obtain information on the attitude, angular velocity and linear acceleration of the FPV; The visual monitoring module is used to obtain information on environmental perception, target recognition, and tracking; The dual-frequency positioning module is used to obtain real-time positioning information; The driving module is connected to the four motors of the FPV machine to realize the control of the FPV machine; The power supply module supplies power to the microcontroller, the 9-DOF inertial navigation sensor measurement module, the visual monitoring module, the dual-frequency positioning module, and the driving module respectively; The power module circuit includes: boost controller, MOSFET power switch tube Q, inductor L, diode D, output filter capacitor C, short-circuit protection, battery sampling and feedback loop; The boost controller controls the switching action of the MOSFET to achieve the boost function; The MOSFET power switch tube Q performs switching operations according to the PWM signal of the boost controller. When the MOSFET power switch tube Q is turned on, the inductor L begins to store energy. When the MOSFET power switch tube Q is turned off, the inductor releases energy and supplies power to the load through the diode D. The inductor L stores energy during the on-time of the MOSFET power switch Q and releases the energy during the off-time of the MOSFET to achieve voltage boost. Diode D prevents the reverse electromotive force generated by the inductor during discharge from damaging the MOSFET and ensures that current can only flow in one direction from the inductor to the load; The output filter capacitor C is used to smooth the output voltage; The short-circuit protection monitors the output current and immediately cuts off the MOSFET once it exceeds the set threshold; The model of the microcontroller is STM32; The driving module includes: an electronic speed regulator and an optocoupler isolation circuit; The electronic speed regulator is connected to an optocoupler isolation circuit, and the optocoupler isolation circuit is connected to the microcontroller.

2. The AI ​​guidance system for a FPV drone according to claim 1, characterized in that: The 9-DOF inertial navigation sensor measurement module includes: a digital compass, an HMC5883L three-axis magnetic induction sensor, an ADXL345 three-axis acceleration sensor and an ITG3200 three-axis gyroscope, which are respectively connected to the microcontroller.

3. The AI ​​guidance system for a FPV drone according to claim 1, characterized in that: The visual monitoring module includes: a multispectral / hyperspectral camera, a binocular camera and a thermal imaging camera, which are respectively connected to the microcontroller.

4. The AI ​​guidance system for a FPV drone according to claim 1, characterized in that: The dual-frequency positioning module includes: a positioning antenna, a signal transmitting antenna, a positioning unit and a navigation satellite system receiver; The positioning unit is connected to the signal transmitting antenna, and both the signal transmitting antenna and the positioning antenna are connected to the navigation satellite system receiver. The navigation satellite system receiver is used to store satellite positions and signal arrival time information.

5. The AI ​​guidance system for a FPV drone according to claim 1, characterized in that: The electronic speed controller is any one of the following models: Hobbywing Xerun 50A, T-Motor F40 Pro II 50A, DJI E500 50A, Hobbywing XRotor 4-in-1 50A, or T-Motor F40 Pro II 4-in-1 50A.

6. The AI ​​guidance system for a FPV drone according to claim 1, characterized in that: Also includes: Indicator lights and buttons; The indicator light and the button are connected to the microcontroller respectively.

7. The AI ​​guidance system for a FPV drone according to claim 1, characterized in that: Also includes: Communication module; The communication module is connected to the microcontroller.

8. The AI ​​guidance system for a FPV drone according to claim 7, characterized in that: The communication module includes: 4GHz wireless communication unit, 8GHz image transmission unit, 433MHz / 915MHz wireless communication unit, Wi-Fi module, 4G / 5GLTE module, LoRa module and Zigbee module.

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