Projects

🤖 Laser Guided Robot

EEE 402 — Control System Sessional · BUET · Group 03 · Level 4 Term 1

A closed-loop control system that autonomously follows a laser pointer using real-time computer vision, Bluetooth serial communication, and differential motor control.

📌 Objective

Build a practical closed-loop system in the form of a laser-following wheeled robot. The robot detects the position of a red laser pointer through a mounted smartphone camera, processes the video feed via computer vision on a PC, and steers itself to track the laser in real time — changing direction as the laser moves.

⚙️ System Pipeline

📱 Android Camera  →  🖥️ PC (Python + OpenCV)  →  📡 Bluetooth (HC-05)  →  🔧 Arduino UNO  →  🚗 DC Motors
   IP Webcam app        Centroid detection           Serial command            L298 driver        100 RPM × 2

Step-by-step

1. Video Capture — The Android app IP Webcam streams live video to a local IP (e.g. http://192.168.0.105:8080/video) over Wi-Fi.
2. Image Processing — Python reads the MJPEG stream, converts each frame to HSV, masks the red laser dot, and computes the centroid coordinates (cx, cy).
3. Command Generation — Based on the centroid position within the 800×480 frame, a single character command is generated.
4. Bluetooth Transmission — The character is sent from PC to the HC-05 module on the Arduino via serial Bluetooth (COM7, 9600 baud).
5. Motor Control — Arduino receives the character and drives the L298 motor controller to steer the robot accordingly.

🕹️ Motion Control Logic

Video resolution: 800 × 480 px

Searching Mode: If the laser disappears from view, the robot pauses, recalls the last known direction, rotates to search, and resumes tracking once the laser reappears.

🐍 Image Processing (Python + OpenCV)

import cv2, urllib2, numpy as np, time, serial

stream = urllib2.urlopen('http://192.168.0.105:8080/video')
bluetooth = serial.Serial("COM7", 9600)  # update COM port as needed

while True:
    # Decode MJPEG frame
    # ...frame extraction logic...

    # Convert BGR to HSV and isolate red laser dot
    hsv = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV)
    lower_red = np.array([160, 100, 100])
    upper_red = np.array([180, 255, 255])
    mask = cv2.inRange(hsv, lower_red, upper_red)

    # Find contours and compute centroid
    image, contours, hierarchy = cv2.findContours(
        mask, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE
    )
    if len(contours) > 0:
        M = cv2.moments(contours[pos])
        if M['m00'] != 0:
            cx = int(M['m10'] / M['m00'])
            cy = int(M['m01'] / M['m00'])

    # Send motion command via Bluetooth
    if abs(cy - 240) <= 20 and cx < 400:
        bluetooth.write(b'u')   # forward
    elif (cy - 240) > 20 and cx < 400:
        bluetooth.write(b'l')   # left
    elif (cy - 240) < -20 and cx < 400:
        bluetooth.write(b'r')   # right
    # ... additional conditions for 'e', 'f', 's'

⚠️ Update the IP address and COM port to match your local network and PC Bluetooth settings.

🔧 Arduino Motor Control (C++)

#include <SoftwareSerial.h>
SoftwareSerial BTserial(2, 3);

// Motor 1 pins
int ena = 5, outPin = 4, outPin2 = 6;
// Motor 2 pins
int enb = 9, outPin4 = 10, outPin3 = 11;

void loop() {
    if (BTserial.available()) {
        char bt = BTserial.read();

        if (bt == 'u') {                        // Forward
            analogWrite(ena, 120); analogWrite(enb, 120);
        } else if (bt == 's') {                 // Stop
            analogWrite(ena, 0);  analogWrite(enb, 0);
        } else if (bt == 'r') {                 // Right
            analogWrite(ena, 120); analogWrite(enb, 90);
        } else if (bt == 'l') {                 // Left
            analogWrite(ena, 90);  analogWrite(enb, 120);
        } else if (bt == 'e') {                 // Hard Left
            analogWrite(ena, 0);   analogWrite(enb, 120);
        } else if (bt == 'f') {                 // Hard Right
            analogWrite(ena, 120); analogWrite(enb, 0);
        }
    }
}

🔩 Hardware Components

⚠️ Limitations

1. Communication chain fragility — Any break in the Wi-Fi → PC → Bluetooth → Arduino chain halts the system completely.
2. Speed compromise — Image processing latency forced a reduced motor base speed to keep control loop timing in sync.
3. PC dependency — All processing runs on an external PC; the robot cannot operate standalone.

🚀 Future Improvements

• Password-protect the Wi-Fi stream to prevent unauthorized control
• Port image processing on-board (e.g. Raspberry Pi) for a fully standalone robot
• Improve laser detection robustness under varying lighting conditions
• Add PID control for smoother, more accurate tracking

Supervised by

• Md. Shafiqul Islam (Lecturer, EEE, BUET)
• Zabir Ahmed (Lecturer, EEE, BUET)

Demonstration

Report: Download PDF