Self Balancing Robot
An integration of mechanical design, electronics, and control systems programming for real-time stability control.
Project Overview
This project involved the complete design and development of a two-wheeled self-balancing robot from concept to implementation. The project required integration of mechanical design principles, embedded electronics, and advanced control systems programming to achieve real-time orientation tracking and dynamic stability.
The robot utilizes an inverted pendulum control strategy, where continuous sensor feedback and real-time corrections maintain balance while allowing for controlled movement.
Technical Challenge
Creating a stable two-wheeled robot presents several engineering challenges:
- Dynamic Stability: Unlike statically stable systems, the robot must continuously adjust to maintain balance
- Real-time Control: Response times must be under 50ms to prevent the system from becoming unstable
- Sensor Fusion: Combining accelerometer and gyroscope data to accurately determine orientation
- Mechanical Optimization: Minimizing center of mass deviations while maintaining structural integrity
Design & Implementation
Mechanical Design
The chassis was designed in SOLIDWORKS with several key considerations:
- Lightweight construction using 3D-printed PLA components to reduce inertia
- Optimized weight distribution to minimize center-of-mass deviations by 30%
- Modular design allowing for component mounting and easy maintenance
- Integrated cable management to prevent interference with moving parts
Control System Development
The control algorithm development followed a systematic approach:
- Mathematical Modeling: Derived the inverted pendulum equations of motion
- MATLAB/Simulink Simulation: Modeled the system dynamics and tuned PID parameters
- Parameter Optimization: Achieved steady-state error below 2% through iterative tuning
- Real-time Implementation: Translated control algorithm to C++ for STM32 microcontroller
Electronics Integration
The electronic system includes:
- STM32 microcontroller for real-time control processing
- MPU6050 IMU for orientation sensing (accelerometer + gyroscope)
- Dual DC motors with encoders for precise movement control
- Motor driver circuit for PWM speed control
- Battery management system for safe operation
Tools & Technologies
CAD Design
SOLIDWORKS for 3D modeling, assembly design, and mechanical optimization
Control Systems
MATLAB/Simulink for system modeling, simulation, and PID tuning
Embedded Programming
C++ development for STM32 microcontroller with real-time constraints
Rapid Prototyping
3D printing for chassis fabrication and component integration
Key Achievements
- Balance Performance: Achieved dynamic stability with correction response time under 50ms
- Control Accuracy: Maintained steady-state error below 2% through optimized PID tuning
- Weight Optimization: Reduced center-of-mass deviations by 30% through strategic design
- System Integration: Successfully integrated mechanical, electrical, and software components
- Real-time Performance: Implemented efficient sensor fusion and control algorithms
Results & Impact
The completed self-balancing robot successfully demonstrated stable operation under various conditions, including disturbances and controlled movement commands. The project validated the effectiveness of the integrated design approach and provided valuable experience in:
- Multidisciplinary system design and integration
- Real-time embedded systems programming
- Control theory application to physical systems
- Iterative design and testing methodologies
This project serves as a foundation for more complex autonomous systems and demonstrates proficiency in the complete product development cycle from concept through implementation.