Topics to Learn for Building a Small Autonomous Car

1. Basic Electronics and Circuit Design

  • Voltage, current, resistance, Ohm’s law
  • Soldering techniques
  • Components:
    • Resistors, capacitors, diodes, transistors, ICs
    • Microcontrollers (Arduino, Raspberry Pi, ESP32)
    • Motor drivers, H-bridge, relays
  • Power supply systems (battery management, voltage regulation)
  • Power distribution design for components

2. Mechanical Engineering Fundamentals

  • Vehicle design and chassis (basic principles)
  • Motor types (brushless vs brushed DC motors)
  • Wheels, suspension, and tire selection
  • Steering mechanism (servo motors, Ackermann steering)
  • Gears and transmission design (gear ratios, motor alignment)
  • Actuators (motors, servos, linear actuators)

3. Embedded Systems Programming

  • Microcontrollers/Development boards: Arduino, Raspberry Pi, ESP32
  • Programming in C/C++/Python for hardware control
  • PWM (Pulse Width Modulation) for motor control
  • Sensor integration (reading data from various sensors)
  • Serial communication (debugging and data transfer)

4. Sensors for Autonomous Driving

  • LIDAR (Light Detection and Ranging)
  • Ultrasonic sensors for obstacle detection
  • IMU (Inertial Measurement Unit) for orientation
  • Wheel encoders for measuring wheel rotation
  • Infrared sensors for proximity sensing
  • GPS for outdoor navigation
  • Computer Vision: Cameras for object and lane recognition

5. Control Systems

  • PID Control (Proportional-Integral-Derivative)
  • State machine design for decision-making logic
  • Path planning algorithms (A*, Dijkstra, etc.)
  • Obstacle avoidance algorithms
  • Vehicle dynamics modeling (acceleration, braking, turning)
  • Implementing safety mechanisms and fail-safes

6. Artificial Intelligence & Machine Learning (optional)

  • Computer vision with OpenCV
    • Image preprocessing, object detection
  • Machine learning:
    • Neural Networks, Convolutional Neural Networks (CNNs)
    • Training models for obstacle recognition
  • Reinforcement learning for autonomous behavior (optional)
  • SLAM (Simultaneous Localization and Mapping) for dynamic environments
  • AI frameworks (TensorFlow, PyTorch)

7. Networking and Communication

  • Bluetooth/Wi-Fi communication for remote control
  • Radio frequency (RF) communication for remote control
  • IoT (Internet of Things) for connectivity with cloud or devices
  • Telemetry systems for real-time data transmission

8. Battery and Power Systems

  • Understanding battery technologies (Li-ion, Li-Po)
  • Battery management systems (BMS)
  • Power conversion systems (DC-DC converters, voltage regulators)
  • Power consumption optimization for longer runtime
  • Charging circuits for safe battery charging

9. Data Logging and Telemetry

  • Storing sensor, GPS, and camera data
  • Real-time data logging for performance analysis
  • Data transmission for remote monitoring and control

10. User Interface and Remote Control

  • Developing a mobile application for remote control (Bluetooth/Wi-Fi)
  • Web interface for monitoring and control (if applicable)
  • Manual override systems for emergency control

11. Testing and Debugging

  • Simulating car behavior using software (Gazebo, V-REP)
  • Testing real-world performance and troubleshooting
  • Iterative design process and testing for improvements

12. Safety Considerations

  • Implementing emergency stop mechanisms
  • System redundancy for backup in case of failure
  • Understanding legal regulations for autonomous vehicles (even small ones)

13. Advanced Topics (Optional)

  • Swarm robotics (using multiple autonomous cars)
  • Sim2Real transfer (adapting simulated results to real-world scenarios)
  • Advanced sensor fusion algorithms

14. Tools and Software

  • PCB design software (Eagle, KiCad)
  • CAD software for 3D modeling (Fusion 360, SolidWorks)
  • Embedded development environments (Arduino IDE, PlatformIO)
  • Simulation tools (MATLAB, Gazebo, V-REP)
  • Version control (Git, GitHub)

15. Prototyping and Iteration

  • 3D printing for custom parts
  • Prototyping with breadboards, wires, and test equipment
  • Iterative design approach (testing, modifying, retesting)