Hardware Components

  • Microcontroller: Arduino Uno
  • Sensors: MPU6050 Sensor (for tilt measurement)
  • Actuators: DC Motors
  • Communication: Bluetooth Module

Key Challenges

  • Tuning PD control parameters to achieve stable balance was challenging due to sensor noise and environmental variations.
  • Implemented a reinforcement learning algorithm to adjust the PD values dynamically, improving the robot’s stability.
  • Analyzed sensor data and experimented with different control strategies to optimize performance.

Results

  • Successfully built a robot that maintains balance autonomously using reinforcement learning.
  • Enhanced stability through real-time PD tuning, significantly reducing the robot’s tendency to tip over.
  • Demonstrated the integration of AI techniques in constrained hardware environments.

Usage

  • The robot can operate in manual and balance modes.
  • Use Bluetooth commands to control the robot remotely.

GitHub Repository

View Full Project on GitHub