How to Make Self Balancing Robot using Arduino UNO, MPU6050 and L298N Motor Driver

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⚡ Project Level: Advanced

⏱ Time Required: 2–3 Hours

💰 Budget: Medium

🤖 Function: Self Balancing Robot

INTRODUCTION

Want to build a robot that balances itself like a Segway? 🤖 In this project, you will learn how to make a Self Balancing Robot using Arduino UNO, MPU6050 sensor, and L298N motor driver.

This robot uses PID control algorithm to maintain balance automatically by adjusting motor speed continuously.

WATCH YOUTUBE VIDEO

COMPONENTS REQUIRED

Image	Name	Qty	Buy
	Arduino UNO	1	{getButton} $text={Buy Now} $icon={cart} $color={#007bff}
	MPU6050 Sensor	1	{getButton} $text={Buy Now} $icon={cart} $color={#007bff}
	L298N Motor Driver	1	{getButton} $text={Buy Now} $icon={cart} $color={#007bff}
	DC Motors	2	{getButton} $text={Buy Now} $icon={cart} $color={#007bff}
	Battery Pack	1	{getButton} $text={Buy Now} $icon={cart} $color={#007bff}
	Jumper Wires	-	{getButton} $text={Buy Now} $icon={cart} $color={#007bff}

TOOLS REQUIRED

Image	Tool	Qty	Buy
	Screwdriver	1	{getButton} $text={Buy Tool} $icon={cart} $color={#007bff}
	Wire Cutter	1	{getButton} $text={Buy Tool} $icon={cart} $color={#007bff}

APPS AND ONLINE SERVICES

Logo	App	Access
	Arduino IDE	{getButton} $text={Download} $icon={download} $color={#007bff}

CIRCUIT DIAGRAM

Add your circuit diagram image here

WIRING CONNECTIONS

MPU6050 ↔ Arduino UNO

VCC	5V
GND	GND
SCL	A5
SDA	A4

L298N ↔ Arduino UNO

IN1	7
IN2	6
IN3	5
IN4	4
ENA	11
ENB	10

ARDUINO CODE

//Self Balancing Robot #include <PID_v1.h> #include <LMotorController.h> #include "I2Cdev.h" #include "MPU6050_6Axis_MotionApps20.h" #if I2CDEV_IMPLEMENTATION == I2CDEV_ARDUINO_WIRE #include "Wire.h" #endif #define MIN_ABS_SPEED 30 MPU6050 mpu; // MPU control/status vars bool dmpReady = false; // set true if DMP init was successful uint8_t mpuIntStatus; // holds actual interrupt status byte from MPU uint8_t devStatus; // return status after each device operation (0 = success, !0 = error) uint16_t packetSize; // expected DMP packet size (default is 42 bytes) uint16_t fifoCount; // count of all bytes currently in FIFO uint8_t fifoBuffer[64]; // FIFO storage buffer // orientation/motion vars Quaternion q; // [w, x, y, z] quaternion container VectorFloat gravity; // [x, y, z] gravity vector float ypr[3]; // [yaw, pitch, roll] yaw/pitch/roll container and gravity vector //PID double originalSetpoint = 181.0; double setpoint = originalSetpoint; double movingAngleOffset = 0.1; double input, output; //adjust these values to fit your own design double Kp = 60; double Kd = 2.2; double Ki = 270; PID pid(&input, &output, &setpoint, Kp, Ki, Kd, DIRECT); double motorSpeedFactorLeft = 0.9; double motorSpeedFactorRight = 0.9; //MOTOR CONTROLLER int ENA = 11; int IN1 = 7; int IN2 = 6; int IN3 = 5; int IN4 = 4; int ENB = 10; LMotorController motorController(ENA, IN1, IN2, ENB, IN3, IN4, motorSpeedFactorLeft, motorSpeedFactorRight); volatile bool mpuInterrupt = false; // indicates whether MPU interrupt pin has gone high void dmpDataReady() { mpuInterrupt = true; } void setup() { // join I2C bus (I2Cdev library doesn't do this automatically) #if I2CDEV_IMPLEMENTATION == I2CDEV_ARDUINO_WIRE Wire.begin(); TWBR = 24; // 400kHz I2C clock (200kHz if CPU is 8MHz) #elif I2CDEV_IMPLEMENTATION == I2CDEV_BUILTIN_FASTWIRE Fastwire::setup(400, true); #endif mpu.initialize(); devStatus = mpu.dmpInitialize(); // supply your own gyro offsets here, scaled for min sensitivity mpu.setXGyroOffset(0); mpu.setYGyroOffset(0); mpu.setZGyroOffset(0); mpu.setZAccelOffset(0); // 1688 factory default for my test chip // make sure it worked (returns 0 if so) if (devStatus == 0) { // turn on the DMP, now that it's ready mpu.setDMPEnabled(true); // enable Arduino interrupt detection attachInterrupt(0, dmpDataReady, RISING); mpuIntStatus = mpu.getIntStatus(); // set our DMP Ready flag so the main loop() function knows it's okay to use it dmpReady = true; // get expected DMP packet size for later comparison packetSize = mpu.dmpGetFIFOPacketSize(); //setup PID pid.SetMode(AUTOMATIC); pid.SetSampleTime(10); pid.SetOutputLimits(-255, 255); } else { // ERROR! // 1 = initial memory load failed // 2 = DMP configuration updates failed // (if it's going to break, usually the code will be 1) Serial.print(F("DMP Initialization failed (code ")); Serial.print(devStatus); Serial.println(F(")")); } } void loop() { // if programming failed, don't try to do anything if (!dmpReady) return; // wait for MPU interrupt or extra packet(s) available while (!mpuInterrupt && fifoCount < packetSize) { //no mpu data - performing PID calculations and output to motors pid.Compute(); motorController.move(output, MIN_ABS_SPEED); } // reset interrupt flag and get INT_STATUS byte mpuInterrupt = false; mpuIntStatus = mpu.getIntStatus(); // get current FIFO count fifoCount = mpu.getFIFOCount(); // check for overflow (this should never happen unless our code is too inefficient) if ((mpuIntStatus & 0x10) || fifoCount == 1024) { // reset so we can continue cleanly mpu.resetFIFO(); Serial.println(F("FIFO overflow!")); // otherwise, check for DMP data ready interrupt (this should happen frequently) } else if (mpuIntStatus & 0x02) { // wait for correct available data length, should be a VERY short wait while (fifoCount < packetSize) fifoCount = mpu.getFIFOCount(); // read a packet from FIFO mpu.getFIFOBytes(fifoBuffer, packetSize); // track FIFO count here in case there is > 1 packet available // (this lets us immediately read more without waiting for an interrupt) fifoCount -= packetSize; mpu.dmpGetQuaternion(&q, fifoBuffer); mpu.dmpGetGravity(&gravity, &q); mpu.dmpGetYawPitchRoll(ypr, &q, &gravity); input = ypr[1] * 180/M_PI + 180; } }

WORKING PRINCIPLE

The MPU6050 sensor measures tilt angle of the robot continuously.

Arduino processes this data using PID algorithm and adjusts motor speed to maintain balance.

If robot tilts forward or backward, motors move accordingly to keep it upright.

STEPS

1. Connect MPU6050 and motor driver
2. Upload the code
3. Power the robot
4. Tune PID values
5. Test balancing

TIPS

• PID tuning is very important
• Use good battery
• Balance weight properly

CONCLUSION

This self balancing robot is a great advanced robotics project using control systems and sensors.