Target Tracking

Overview

Target tracking is an important application of drone intelligence. In this project, you will learn how to track a colored target in real time using the OpenCV library.

What You’ll Learn

• Using the OpenCV library
• Color space conversion
• Target detection algorithms
• Real-time tracking control

Materials Needed

Item	Quantity	Notes
ESP32-S3 Drone	1	-
OV2640 Camera Module	1	-
Red Ball	1	10 cm diameter

Step 1: Install the OpenCV Library

Unzip esp32_opencv.zip and copy the library files into the project’s components folder.

Step 2: Open the Project

Unzip color_tracking.zip and open it with VS Code.

Step 3: Implement the Color Tracking Function

Open color_tracking.c and implement color tracking:

void color_tracking(uint8_t* frame, int width, int height, int* target_x, int* target_y) {
    // 1. Convert the RGB image to HSV color space
    cvt_color_rgb2hsv(frame, width, height);

    // 2. Apply color threshold filtering (red)
    uint8_t mask[width * height];
    hsv_threshold(frame, width, height, mask, 0, 10, 100, 255, 100, 255);

    // 3. Find contours and compute the target center
    find_contours(mask, width, height);
    if (has_contours()) {
        *target_x = get_largest_contour_center_x();
        *target_y = get_largest_contour_center_y();
    } else {
        *target_x = -1;
        *target_y = -1;
    }
}

Step 4: Add Tracking Logic

Open flight_control.c and add the following to the main loop:

int target_x, target_y;
color_tracking(frame, width, height, &target_x, &target_y);

if (target_x != -1) {
    // Target on the left → drone turns left
    if (target_x < width / 2 - 20) {
        motorsSetRatio(MOTOR_M1, current_ratio * 0.8);
        motorsSetRatio(MOTOR_M2, current_ratio * 1.2);
        motorsSetRatio(MOTOR_M3, current_ratio * 0.8);
        motorsSetRatio(MOTOR_M4, current_ratio * 1.2);
    }
    // Target on the right → drone turns right
    else if (target_x > width / 2 + 20) {
        motorsSetRatio(MOTOR_M1, current_ratio * 1.2);
        motorsSetRatio(MOTOR_M2, current_ratio * 0.8);
        motorsSetRatio(MOTOR_M3, current_ratio * 1.2);
        motorsSetRatio(MOTOR_M4, current_ratio * 0.8);
    }
    // Target in the center → drone moves forward
    else {
        motorsSetRatio(MOTOR_M1, current_ratio * 1.1);
        motorsSetRatio(MOTOR_M2, current_ratio * 1.1);
        motorsSetRatio(MOTOR_M3, current_ratio * 1.1);
        motorsSetRatio(MOTOR_M4, current_ratio * 1.1);
    }
}

Step 5: Testing

1. Move a red ball around and check whether the drone can follow it steadily
2. Challenge: lead the drone all the way around a table with the red ball

Troubleshooting

Inaccurate recognition

• Adjust the color threshold
• Improve the lighting conditions

Unstable tracking

• Tune the control parameters
• Add a prediction algorithm

Achievement

Congratulations! You have implemented a target tracking system — an important application of drone intelligence!

Next Steps

In the next project, you will learn how to deploy an AI model on the ESP32-S3.