electronicsworkshopsOverview
A self balancing robot with arduino is a type of autonomous robot that is designed to maintain its balance on two wheels or other balancing mechanisms. These robots are able to stand upright and move without falling over, even when subjected to external disturbances. The concept behind a self-balancing robot is often inspired by the way humans and animals maintain their balance.
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https://electronicsworkshops.com/2023/08/26/self-balancing-robot-with-arduino/
Introduction
A self-balancing robot built with Arduino is a captivating project that combines mechanical engineering, electronics, and programming skills. By integrating sensors and motors with an Arduino board, this project aims to create a robot that can maintain its balance on two wheels. The robot uses real-time data from accelerometers and gyroscopes to continuously adjust its motor speeds, preventing it from toppling over even when subjected to external disturbances. This project offers an excellent opportunity to delve into control algorithms like PID (Proportional-Integral-Derivative) and learn about feedback loops. Assembling, programming, and fine-tuning the robot’s behavior provide valuable hands-on experience in robotics and automation, making it an educational and rewarding endeavor for both beginners and experienced enthusiasts alike.
Bill Of Materials
| SN | COMPONENTS NAME | DESCRIPTION | QUANTITY |  |
|---|---|---|---|---|
| 1 | Arduino Board | Arduino nano | 1 | https://amzn.to/3Qe71y5 |
| 2 | Connecting wires | jumper wire | some | https://amzn.to/3fMoSw7 |
| 3 | Breadboard | Normal | 1 | https://amzn.to/3FUQlXe |
| 4 | Motor Driver | HC05 | 1 | https://amzn.to/3Lss0dp |
| 5 | Car Chassis Kit | DIY Robot | 1 | https://amzn.to/3Z6j0A3 |
| 6 | Accelerometer Gyroscope Sensor | MPU-6050 | 1 | https://amzn.to/44udBUp |
Principle of self balancing robot
Self-balancing robot is a robot that balances itself on two wheels, constantly adjusting its position. A gyroscope sensor is used in self-balancing robots, which continuously send the robot’s orientation data to the controller. Based on this data controller commands the motor to run forward or backward to keep the robot’s position upright.
This is the ideal position of the self-balancing robot, with its body perfectly oriented towards the wheel. There is no angle between the Y axis and the robot body.
When the body leans forward, there will be a certain angle between the Y axis and the body. This angle is detected by the gyro sensor MPU6050, then this data is sent to the Arduino. The Arduino now performs the PID calculation and commands the stepper motor to run forward to minimize the tilt angle to 0 degrees.
The same happens if when the robot leans backwards, the motor will reverse and adjust the tilt angle to 0. The robot continues to rotate the motor back and forth more than 400 times per second, which gives us the impression that the robot is stable in its place.
Key Achievements
Balance Control: The core accomplishment of the project is the successful implementation of a balance control algorithm. The robot utilizes sensor data, such as accelerometer and gyroscope readings, to calculate its tilt angle and adjust the motor speeds accordingly to maintain balance.
Motor Control: The integration of motor drivers with Arduino allows precise control of the motors to achieve the desired movement and balance adjustments. The proportional-integral-derivative (PID) control algorithm plays a crucial role in translating sensor data into motor commands.
Sensors Integration: The project demonstrates the effective use of sensors like accelerometers and gyroscopes to gather real-time data about the robot’s orientation. These sensors enable the robot to react quickly and make necessary adjustments to stay upright.
Real-time Processing: The ability of the Arduino to process sensor data and execute control algorithms in real time is a significant achievement. This real-time processing capability is essential for maintaining balance and responding to external disturbances.
Schematic Diagram
PCB Diagram
3D Images
Manufacturing Files
Gerber
Gerber_balancing robot_2023-08-26Download
Position File
PickAndPlace_balancing-robot_2023-08-26Download
Bill Of Materials
BOM_Self-Balancing-robotDownload
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Challenges Faced
Tuning PID Parameters: Achieving optimal balance required tuning the PID parameters, which can be a time-consuming and iterative process. Finding the right values to ensure stability without causing oscillations was a challenge.
Mechanical Design: Designing a stable mechanical structure that allows for smooth movement and balance is crucial. The design of the chassis, wheels, and motor placement affects the robot’s overall performance.
Sensor Accuracy: Sensor calibration and accuracy are essential for reliable performance. Calibrating sensors properly and dealing with noise in sensor data can be challenging.
Power Management: Ensuring a stable power supply and efficient power management is important for consistent and prolonged operation. Battery life and voltage regulation are crucial considerations.
Future Improvements
Enhanced Control Algorithms: Implementing advanced control algorithms, such as model predictive control (MPC), could improve the robot’s ability to respond to dynamic environments and disturbances more effectively.
Wireless Communication: Introducing wireless communication capabilities, such as Bluetooth or Wi-Fi, could allow remote control and real-time monitoring of the robot’s status.
Obstacle Avoidance: Integrating additional sensors like ultrasonic or infrared sensors could enable obstacle detection and avoidance, making the robot more versatile in various environments.
Machine Learning: Utilizing machine learning techniques, such as reinforcement learning, could enable the robot to adapt and learn better balance strategies over time.
Mechanical Upgrades: Improving the mechanical design, using better quality components, and optimizing the weight distribution could enhance stability and overall performance.
Conclusion
In conclusion, the self-balancing robot project with Arduino showcases the successful integration of electronics, programming, and mechanics to achieve an impressive feat of balance and control. While the project’s current state is a significant achievement, there are ample opportunities for further enhancements and innovations, making it an exciting platform for continuous exploration and development in the field of robotics and automation