Self-balancing single-wheel robot based on RTK and IMU

Abstract

The self-balancing single-wheel robot based on the RTK and the IMU comprises a vehicle body, a controller is arranged on the top of the vehicle body, three RTK modules are installed on the top of the vehicle body in a triangular distribution mode, two brushless motors are symmetrically arranged on the left side and the right side of the vehicle body, and the two brushless motors are respectively connected with a momentum wheel. A traveling wheel is arranged at the bottom of the vehicle body, a driver and a brush motor are arranged in the middle of the vehicle body, the driver is connected with the brush motor, the traveling wheel is connected with the brush motor through a belt transmission structure, and the encoder is connected with the traveling wheel; the controller is connected with the brushless motor, the driver, the encoder and the RTK module. According to the utility model, the RTK module is adopted for positioning, centimeter-level accurate position data can be obtained through a real-time dynamic difference technology, and the outdoor environment positioning precision is high.

Description

Technical Field

[0001] This utility model relates to a self-balancing unicycle robot based on RTK and IMU. Background Technology

[0002] A unicycle is a small, simple, and unstable mobile unicycle characterized by multivariability, high nonlinearity, and strong coupling. Because its design involves mechanical structure design, embedded system development, and complex control algorithm verification, the unicycle is not only an ideal platform for conducting related experiments but also possesses significant scientific research value and broad application prospects. Currently, research on unicycles in areas such as balance control and path planning has attracted considerable attention and has become a research hotspot for researchers and educators.

[0003] Currently, research on unicycles mainly focuses on balance control, and most experiments are conducted in relatively stable indoor environments. For example, previous researchers have achieved precise posture control of unicycles through a combination of sensor technology and control algorithms, but these studies are mostly limited to indoor applications and experimental scenarios with fewer external environmental disturbances. Significant progress has been made in applying unicycles to complex outdoor environments, primarily because the greater uncertainty and disturbances in outdoor environments make it difficult for unicycles to maintain balance and stable movement. Summary of the Invention

[0004] To address the aforementioned technical problems, this utility model provides a simple, self-balancing unicycle robot based on RTK and IMU, suitable for outdoor scenarios.

[0005] The technical solution of this utility model to solve the above-mentioned technical problems is as follows: a self-balancing unicycle robot based on RTK and IMU, including a vehicle body, a controller on the top of the vehicle body for information processing and motion control of the entire vehicle, three RTK modules for acquiring the current position information of the unicycle robot and displaying the current running status of the unicycle robot are installed in a triangular arrangement on the top of the vehicle body, two brushless motors are symmetrically arranged on the left and right sides of the vehicle body, and the two brushless motors are respectively connected to a momentum wheel for realizing the self-balancing function of the self-balancing unicycle robot; a travel wheel is provided at the bottom of the vehicle body, a driver and a brushed motor are provided in the middle of the vehicle body, the driver is connected to the brushed motor, the travel wheel is connected to the brushed motor through a belt drive structure, an encoder is connected to the travel wheel, and the encoder detects the travel speed of the self-balancing unicycle robot; the controller is connected to the brushless motor, driver, encoder and RTK modules respectively.

[0006] The aforementioned self-balancing unicycle robot based on RTK and IMU includes a controller comprising a microcontroller, an IMU module, and a TFT screen. The microcontroller is connected to a brushless motor, a driver, an encoder, an RTK module, an IMU module, and a TFT screen, respectively.

[0007] The aforementioned self-balancing unicycle robot based on RTK and IMU also includes a wireless Bluetooth module in its controller. The controller is connected to the wireless Bluetooth module and, through the wireless Bluetooth module, to the remote controller.

[0008] The aforementioned self-balancing unicycle robot based on RTK and IMU has a power supply and power management module located in the middle of the vehicle body. The power supply and power management module are connected to provide working power to the entire self-balancing unicycle robot.

[0009] The aforementioned self-balancing unicycle robot based on RTK and IMU has its IMU module and wireless Bluetooth module connected to the controller via a busbar.

[0010] The aforementioned self-balancing unicycle robot based on RTK and IMU has its RTK module connected to the controller via a ribbon cable.

[0011] The aforementioned self-balancing unicycle robot based on RTK and IMU has a momentum wheel on the left side with an angle of 135° to the horizontal plane, and a momentum wheel on the right side with an angle of 45° to the horizontal plane.

[0012] The self-balancing unicycle robot based on RTK and IMU mentioned above uses the TC297TX microcontroller.

[0013] The self-balancing unicycle robot based on RTK and IMU mentioned above uses the MPU6050 as the main chip of the IMU module.

[0014] The aforementioned self-balancing unicycle robot based on RTK and IMU uses the DRV8701E as its main driver chip.

[0015] The beneficial effects of this utility model are as follows:

[0016] 1. This utility model uses an RTK module for positioning, which can obtain centimeter-level accurate position data through real-time dynamic differential technology, and has the advantage of high positioning accuracy in outdoor environments.

[0017] 2. This utility model realizes the pose detection of the unicycle robot through the IMU module. Combined with the brushless motors and momentum wheels distributed on the left and right sides of the vehicle body, it can realize the real-time posture detection and motion control of the unicycle robot, and has high robustness.

[0018] 3. This utility model is based on a belt drive structure that drives the travel wheel with a brushed motor, which can ensure the stability of the unicycle robot's forward and backward movement. Combined with the speed feedback of the encoder, it can improve the accuracy of motion control. Attached Figure Description

[0019] Figure 1 This is a schematic diagram of the overall structure of this utility model.

[0020] Figure 2 for Figure 1 The front view.

[0021] Figure 3 for Figure 1 The right view.

[0022] Figure 4 for Figure 1 Top view.

[0023] Figure 5 This is a circuit structure block diagram of the present invention.

[0024] Figure 6 This is a schematic diagram of the controller.

[0025] Figure 7 This is the circuit diagram of a microcontroller.

[0026] Figure 8 This is a circuit diagram for the IMU module, serial port, encoder, and brushed motor interface.

[0027] Figure 9 This is a circuit diagram of the power management module and the brushless motor interface.

[0028] Figure 10 This is a circuit diagram for a TFT screen.

[0029] Figure 11 This is a circuit diagram of the H-bridge drive circuit for the driver.

[0030] Figure 12 The circuit diagram is for the DRV8701E chip used as the driver. Detailed Implementation

[0031] like Figures 1-5As shown, a self-balancing unicycle robot based on RTK and IMU includes a vehicle body 1. A controller 2, responsible for information processing and motion control of the entire vehicle, is located on the top of the vehicle body 1. Three RTK modules 3, arranged in a triangular pattern on the top of the vehicle body 1, are used to acquire the current position information of the unicycle robot and display its current operating status. Two brushless motors 4, namely brushless motor A and brushless motor B, are symmetrically arranged on the left and right sides of the vehicle body 1. Brushless motor A and brushless motor B are each connected to a momentum wheel 5 for achieving the self-balancing function of the unicycle robot. A travel wheel 10 is located at the bottom of the vehicle body 1. A driver 8 and a brushed motor 7 are located in the middle of the vehicle body 1. The driver 8 is connected to the brushed motor 7, and the travel wheel 10 is connected to the brushed motor 7 via a belt drive structure 11. An encoder 9 is connected to the travel wheel 10 and detects the travel speed of the self-balancing unicycle robot. The controller 2 is connected to the brushless motor 4, the driver 8, the encoder 9, and the RTK modules 3. The momentum wheel 5 on the left makes an angle of 135° with the horizontal plane, while the momentum wheel 5 on the right makes an angle of 45° with the horizontal plane.

[0032] The vehicle body 1 is equipped with a power supply 6 and a power management module in the middle. The power supply 6 is connected to the power management module to provide working power to the entire self-balancing unicycle robot.

[0033] like Figure 6 As shown, the controller 2 includes a microcontroller 12, an IMU module 13, a TFT screen 14, a brushless motor A interface 15, a brushless motor B interface 16, a driver interface 17, an encoder interface 18, and a wireless Bluetooth module. The microcontroller 12 is connected to brushless motor A via brushless motor A interface 15, to brushless motor B via brushless motor B interface 16, to a driver via driver interface 17, and to encoder 9 via encoder interface 18. The microcontroller 12 is also connected to the RTK module 3, IMU module 13, and TFT screen 14. The controller 2 is connected to the wireless Bluetooth module and, through the wireless Bluetooth module, to a remote control. The IMU module 13 and the wireless Bluetooth module are connected to the controller 2 via a header. The RTK module 3 is connected to the controller 2 via a ribbon cable.

[0034] like Figures 7-10As shown, the microcontroller selected is the TC297TX. This microcontroller belongs to Infineon's first-generation Aurix TC29xTX series and is equipped with up to three independent 32-bit TriCore CPUs, up to 8MB of Flash, 2.7MB of SRAM, and a powerful general-purpose timer module (GTM). It supports multiple communication protocols, including CAN, CAN FD, LIN, FlexRay, and Ethernet, which can meet the communication needs of the unicycle robot. It has rich I / O interfaces and can fully support the design of the unicycle robot.

[0035] IMU module 13 uses a gyroscope, and its main chip is MPU6050. The MPU6050 has eight pins: GND, 3V3, SCL, SDA, AD0, NC1, INT, and NC2. The GND pin is connected to GND, the 3V3 pin is connected to the 3.3V power supply, the SCL pin is connected to the P11.6 pin of the microcontroller, the SDA pin is connected to the P11.9 pin of the microcontroller, the AD0 pin is connected to the P11.3 pin of the microcontroller, the NC1 pin is connected to the P11.11 pin of the microcontroller, and the INT and NC2 pins are left floating.

[0036] The TFT screen has seven pins: GND, VCC, CS, SCK, SDI, DC, and RST. The GND pin is connected to GND, the VCC pin is connected to the 3.3V power supply, the CS pin is connected to the P20.13 pin of the microcontroller, the SCK pin (i.e., the D0 pin) is connected to the P20.11 pin of the microcontroller, the SDI pin (i.e., the D1 pin) is connected to the P20.14 pin of the microcontroller, the DC pin is connected to the P20.12 pin of the microcontroller, and the RST pin is connected to the P20.10 pin of the microcontroller.

[0037] like Figure 9 As shown, the brushless motor A interface 15 has 8 pins: BAT, GND, MT2N, MT3P, MT3N, V3.3, ENcoder2A, and ENcoder2B. The BAT pin is connected to the 24V power input, the GND pin is grounded, the MT2N pin is connected to the P22.3 pin of the microcontroller, the MT3P pin is connected to the P21.4 pin of the microcontroller, the MT3N pin is connected to the P21.3 pin of the microcontroller, the V3.3 pin is connected to the 3.3V power supply, the Encoder2A pin is connected to the P02.8 pin of the microcontroller, and the Encoder2B pin is connected to the P33.5 pin of the microcontroller.

[0038] like Figure 9As shown, the brushless motor B interface 16 has 8 pins: BAT, GND, MT2N, MT4P, MT4N, V3.3, ENcoder3A, and ENcoder3B. The BAT pin is connected to the 24V power input, the GND pin is grounded, the MT2N pin is connected to the P22.3 pin of the microcontroller, the MT4P pin is connected to the P20.8 pin of the microcontroller, the MT4N pin is connected to the P21.5 pin of the microcontroller, the V3.3 pin is connected to the 3.3V power supply, the Encoder3A pin is connected to the P10.3 pin of the microcontroller, and the Encoder3B pin is connected to the P10.1 pin of the microcontroller.

[0039] The brushed motor has four pins: 3V3, PWM, DIR, and GND. The 3V3 pin is connected to a 3.3V power supply, the PWM pin is connected to the P23.1 pin of the microcontroller, the DIR pin is connected to the P32.4 pin of the microcontroller, and the GND pin is connected to GND.

[0040] The RTK module has four pins: 5V, GND, TX, and RX. The 5V pin is connected to the 5V power supply, the GND pin is connected to GND, the TX pin is connected to the P00.0 pin of the microcontroller, and the RX pin is connected to the P00.1 pin of the microcontroller.

[0041] The wireless Bluetooth module has a total of 6 pins: STATE, EN, RXD, TXD, GND, and VCC. The STATE and EN pins are left floating, the RXD pin is connected to the P14.0 pin of the microcontroller, the TXD pin is connected to the P14.1 pin of the microcontroller, the GND pin is connected to GND, and the VCC pin is connected to the 5V power supply.

[0042] The encoder is connected to the controller via a 2*3 6-pin ribbon cable, with the effective pins being 3V3, GND, EncoderA, and EncoderB. The 3V3 pin is connected to the 3.3V power supply, the GND pin is connected to GND, EncoderA is connected to the P20.3 pin of the microcontroller, and EncoderB is connected to the P20.0 pin of the microcontroller.

[0043] like Figure 11 , Figure 12As shown, the DRV8701E is selected as the driver chip. The DRV8701E is an H-bridge gate driver that supports power input from 5.9V to 45V. It has high gate driving capability, achieves low conduction loss, and has high motor driving efficiency. By controlling external MOSFETs, it can drive high-power motors and is capable of handling the motor driving tasks of this robot system. At the same time, the DRV8701E has a flexible control interface, and the speed and direction of the motor can be controlled through the PH and EN pins. The MOSFET selected is TPH1R403NL. The main factors considered when selecting a MOSFET are: voltage rating, on-resistance, and package. The input voltage for the drive is 24V. Considering that the brushed motor 7 may generate regenerative power during operation, a voltage rating with a margin of 1.25 times is selected for the motor drive, so a voltage rating of 30V is chosen. The lower the on-resistance, the better. At the same time, good heat dissipation performance should also be taken into account. After comprehensive consideration, TPH1R403NL is selected as the MOSFET for the drive section. Its voltage rating is as high as 30V, which can withstand a large current of 150A. It also has an extremely low on-resistance of only 1.7mΩ and good heat dissipation performance.

[0044] Figure 11 In the circuit, capacitors C4, C3, C11, and C9 act as filters to prevent power supply noise interference. Two KF301-2P sockets are used to connect the input power supply and the brushed motor 7, respectively. Diode SK1010C provides reverse connection protection to prevent damage to the system due to reverse input power connection. A 74HC125PW buffer handles the direction selection signal from the microcontroller's GPIO and the speed control signal from the microcontroller's PWM. The driver section uses four TPH1R403NL N-channel MOSFETs to form an H-bridge circuit to control the motor's forward and reverse rotation and start / stop. GH1, GL1, GH2, and GL2 are control signals provided by the DRV8701E driver chip. By controlling these pins, the MOSFETs are switched on / off states, thus driving the motor. The 4-pin interface of the XH2.54-4P is used to connect to the microcontroller's motor control pins.

[0045] like Figure 9As shown, due to the needs of the two brushless motors 4 and the brushed motor 7, a 24V model aircraft battery is selected for power supply. However, the microcontroller, TFT screen, wireless Bluetooth module, and other modules require 5V or 3.3V voltage input. Therefore, the 24V power input needs to be stepped down to 5V and 3.3V for use by these modules. For the 5V step-down section, the LM2596CS-V5 power converter is selected. The LM2596 has an input voltage range of up to 40V, a switching frequency of up to 150kHz, and an output voltage range of 1.2V to 37V, with an output load current of 3A. Since the robot system's power input is 24V, the target output is 5V, the switching frequency is relatively low, and the output current requirement is below 3A, the LM2596CS-V5 chip from the LM2596 series is selected to complete the task of a fixed 5V output. In the peripheral circuit of LM2596, the 1N5824 Schottky diode is used to provide a path for the inductor to release current when the switch is off; the 1000μF C14 and 100nF C6 are input capacitors, connected in parallel at the input terminal to filter and stabilize the output voltage, preventing input voltage fluctuations and ripple interference from affecting the operation of LM2596. The 1000μF C14 is used to filter out low-frequency ripple and the 100nF C6 is used to filter out high-frequency ripple; the 33μH inductor L2 is used to store energy when the switch is on and release energy when the switch is off, forming a stable output current. In addition to the 5V voltage, the system also requires a 3.3V voltage supply. Therefore, a 3.3V step-down section is immediately following the 5V output. The 3.3V step-down section uses the LM1084RS-3.3V regulator. The LM1084RS-3.3V chip has a maximum input voltage of 15V, a fixed output voltage of 3.3V, an output load current of 5A, and a power supply ripple rejection ratio of 65dB at a switching frequency of 120Hz. This fully meets the system's requirement of generating a 3.3V output from a 5V input. Therefore, this chip was chosen to construct the 3.3V step-down section. The 100μF capacitor C3 in the circuit mainly serves to filter and stabilize the output voltage, effectively reducing low-frequency ripple in the output and providing a stable 3.3V output. The 10μF capacitor at the output terminal is used to filter out high-frequency noise.

[0046] The working process of this utility model is as follows: Turn on the power switch to power on the entire unicycle robot system. After powering on, wait for the RTK module, MPU6050 gyroscope, and other peripheral modules to initialize. After the module initialization is complete, the system parameters and status can be observed through the TFT screen. The system working mode can be switched using the buttons on the controller. First, enter the path point setting mode. In this mode, the robot can be manually moved to the desired target point, and then the button can be pressed to save the path point. Then, move to the next target point and repeat the above process until all path points are saved. After the path points are set and saved, return to the starting point and press the button to switch the unicycle robot to the balance mode. In this mode, the unicycle robot maintains self-balancing at the current position. After the unicycle robot stabilizes in self-balancing mode, press the button again to switch to the working mode. The unicycle robot will start from the starting point and travel along the path planned by the microcontroller through the path points, passing through the set path points to complete the work task.

Claims

1. A self-balancing unicycle robot based on RTK and IMU, characterized in that: The system includes a vehicle body, with a controller on top for information processing and motion control of the entire vehicle. Three RTK modules, arranged in a triangular pattern on the top of the vehicle body, are used to acquire the current position information and display the current operating status of the unicycle. Two brushless motors are symmetrically arranged on the left and right sides of the vehicle body, each connected to a momentum wheel for self-balancing. A travel wheel is located at the bottom of the vehicle body. A driver and a brushed motor are located in the middle of the vehicle body. The driver is connected to the brushed motor, and the travel wheel is connected to the brushed motor via a belt drive. An encoder is connected to the travel wheel to detect the travel speed of the self-balancing unicycle. The controller is connected to the brushless motor, driver, encoder, and RTK modules.

2. The self-balancing unicycle robot based on RTK and IMU according to claim 1, characterized in that: The controller includes a microcontroller, an IMU module, and a TFT screen. The microcontroller is connected to the brushless motor, driver, encoder, RTK module, IMU module, and TFT screen, respectively.

3. The self-balancing unicycle robot based on RTK and IMU according to claim 2, characterized in that: The controller also includes a wireless Bluetooth module, which is connected to the controller and the remote control via the wireless Bluetooth module.

4. The self-balancing unicycle robot based on RTK and IMU according to claim 1, characterized in that: The vehicle body is equipped with a power supply and a power management module in the middle. The power supply and the power management module are connected to provide working power to the entire self-balancing unicycle robot.

5. The self-balancing unicycle robot based on RTK and IMU according to claim 3, characterized in that: The IMU module and the wireless Bluetooth module are connected to the controller via a busbar.

6. The self-balancing unicycle robot based on RTK and IMU according to claim 3, characterized in that: The RTK module is connected to the controller via a ribbon cable.

7. The self-balancing unicycle robot based on RTK and IMU according to claim 1, characterized in that: The momentum wheel on the left makes an angle of 135° with the horizontal plane, while the momentum wheel on the right makes an angle of 45° with the horizontal plane.

8. The self-balancing unicycle robot based on RTK and IMU according to claim 2, characterized in that: The microcontroller used is TC297TX.

9. The self-balancing unicycle robot based on RTK and IMU according to claim 2, characterized in that: The main chip of the IMU module is the MPU6050.

10. The self-balancing unicycle robot based on RTK and IMU according to claim 2, characterized in that: The driver's main chip is DRV8701E.

Images