Section outline

  • Project – Self-Parking Robot

    In this hands-on section, we will design and implement an autonomous self-parking robot using a microcontroller, ultrasonic sensors, and motor control logic. The goal is to simulate a real-world scenario where the robot detects a parking space, aligns itself, and maneuvers into position safely and accurately.

    • Understanding Autonomous Parking Logic

      • Environment Scanning: The robot uses side-mounted ultrasonic sensors to measure distances to nearby objects and determine if a space is wide enough for parking.
      • Alignment Check: Once a space is detected, the robot repositions itself to align with the center of the parking spot.
      • Reverse and Adjust: The robot reverses in a curve while checking boundaries, correcting its angle during the process to park within the designated space.

      Hardware Requirements

      • Arduino Uno or similar microcontroller
      • 2 or 3 ultrasonic sensors (front, side, and optional rear)
      • Motor driver module (e.g., L298N)
      • DC motors and wheels
      • Chassis frame
      • Battery pack or USB power

      Software and Control Logic

      The control algorithm involves constant monitoring of distances from sensors and deciding when to slow down, stop, and start reverse-parking. Here is a simplified logic breakdown:

      1. Drive forward and scan for empty space using the right-side sensor.
      2. If a suitable gap (e.g., 25 cm or more) is detected, stop.
      3. Move forward a bit and start reversing with a left turn.
      4. Use back and front sensors to track how deep the robot has gone in.
      5. Once inside, make a small forward-right move to straighten.

      Arduino Pseudocode

      // Pseudocode for self-parking behavior
while (drivingForward) {
    if (rightDistance > 25cm) {
        stopMotors();
        forwardSlightly();
        reverseWithCurve();
        checkBackSensor();
        if (aligned) {
            stopMotors();
            beepSuccess();
        }
    }
}

      Challenges and Considerations

      • Sensor blind spots: Use angled mounts or additional sensors if needed.
      • Precision control: Use PWM motor control for better speed adjustment.
      • Test in varying light: Avoid IR sensors for parking, as light may interfere. Stick to ultrasonic for reliable distance measurement.

      Outcome

      This project combines key topics learned so far: sensor integration, decision logic, motion control, and real-time response. It gives students a real taste of how autonomous systems are built, tested, and fine-tuned for real-world applications.