Line following with camera in Drone Programming - Mini Project: Build & Apply

Line following with camera

📖 Scenario: You are programming a small drone to follow a black line on the ground using its camera. The drone's camera captures images, and you will process these images to detect the line and control the drone's movement to stay on the line.

🎯 Goal: Build a simple program that processes camera image data to detect a black line and outputs the drone's movement commands to follow the line.

📋 What You'll Learn

Create a list representing a camera image row with pixel brightness values

Set a threshold value to detect dark pixels representing the line

Use a loop to find the position of the line in the image row

Print the drone's movement command based on the line position

💡 Why This Matters

🌍 Real World

Drones use cameras to follow lines or paths on the ground for tasks like delivery or inspection.

💼 Career

Understanding how to process camera data and control drones is useful for robotics and autonomous vehicle jobs.

1

Create camera image data

Create a list called camera_row with these exact pixel brightness values: [255, 255, 0, 0, 0, 255, 255]. These values represent a row of pixels from the drone's camera, where 0 means black and 255 means white.

Drone Programming

# Create the camera_row list with pixel brightness values
# Your code here

Hint

Think of the camera row as a list of numbers showing how bright each pixel is. Black pixels have value 0.

2

Set threshold for line detection

Create a variable called threshold and set it to 50. This threshold will help detect dark pixels representing the line.

Drone Programming

camera_row = [255, 255, 0, 0, 0, 255, 255]
# Set the threshold value to detect dark pixels
# Your code here

Hint

The threshold is a number to decide if a pixel is dark enough to be part of the line.

3

Find line position in camera row

Use a for loop with variable index to go through camera_row. Find the first pixel where the brightness is less than threshold. Save this index in a variable called line_position. If no pixel is dark, set line_position to -1.

Drone Programming

camera_row = [255, 255, 0, 0, 0, 255, 255]
threshold = 50
# Use a for loop to find the first dark pixel and save its index as line_position
# Your code here

Hint

Loop over each pixel index and check if the pixel is dark. Stop when you find the first dark pixel.

4

Print drone movement command

Write a print statement to display the drone's movement command based on line_position. If line_position is -1, print "No line detected: Hover". If line_position is less than 3, print "Turn left". If line_position is greater than 3, print "Turn right". Otherwise, print "Go straight".

Drone Programming

camera_row = [255, 255, 0, 0, 0, 255, 255]
threshold = 50
line_position = -1
for index in range(len(camera_row)):
    if camera_row[index] < threshold:
        line_position = index
        break
# Print the drone movement command based on line_position
# Your code here

Hint

Use if-elif-else to decide the command based on where the line is detected.

Practice

1.

What is the main purpose of using a camera in a drone for line following?

easy

A. To detect the position of the line on the ground

B. To measure the drone's altitude

C. To record videos for entertainment

D. To communicate with other drones

Solution

1. Step 1: Understand the role of the camera

   The camera is used to see the environment below the drone, especially the line it needs to follow.

2. Step 2: Identify the main task for line following

   The drone must detect where the line is to adjust its path and stay on it.

3. Final Answer:

   To detect the position of the line on the ground -> Option A

4. Quick Check:

   Camera detects line position = B [OK]

Hint: Camera's job is to see the line, not altitude or communication [OK]

Common Mistakes:

• Confusing camera use with altitude measurement
• Thinking camera is for video recording only
• Assuming camera is for drone communication

2.

Which of the following is the correct way to start capturing images from the drone's camera in Python?

camera = DroneCamera()
# What next?

easy

A. camera.begin()

B. camera.start_capture()

C. start.camera()

D. camera.capture_start()

Solution

1. Step 1: Check common method names for starting capture

   Usually, methods to start camera capture are named with 'start' and 'capture' in order.

2. Step 2: Match method names with options

   camera.start_capture() uses 'start_capture()', which is a common and clear method name.

3. Final Answer:

   camera.start_capture() -> Option B

4. Quick Check:

   Start capture method = start_capture() [OK]

Hint: Look for method names with 'start' and 'capture' in order [OK]

Common Mistakes:

• Mixing method name order like capture_start()
• Using invalid syntax like start.camera()
• Guessing method names without checking conventions

3.

What will be the output of this code snippet that processes a camera frame to find the line position?

frame = camera.get_frame()
line_pos = detect_line_position(frame)
if line_pos < 0.4:
    print("Turn Left")
elif line_pos > 0.6:
    print("Turn Right")
else:
    print("Go Straight")

Assuming detect_line_position(frame) returns 0.3.

medium

A. Turn Left

B. Turn Right

C. Go Straight

D. No output

Solution

1. Step 1: Understand the value of line_pos

   The function returns 0.3, which is less than 0.4.

2. Step 2: Check the conditions in the if-elif-else

   Since 0.3 < 0.4, the first condition is true, so it prints "Turn Left".

3. Final Answer:

   Turn Left -> Option A

4. Quick Check:

   line_pos = 0.3 < 0.4 means Turn Left [OK]

Hint: Compare line_pos with 0.4 and 0.6 to decide direction [OK]

Common Mistakes:

• Confusing less than and greater than signs
• Ignoring the order of if-elif-else
• Assuming else runs when first condition is true

4.

Identify the error in this code snippet for line following and select the fix:

frame = camera.get_frame()
line_pos = detect_line_position(frame)
if line_pos < 0.5
    drone.turn_left()
else:
    drone.turn_right()

medium

A. Replace 'else:' with 'elif line_pos > 0.5:'

B. Change 'turn_left()' to 'turn_left'

C. Add a colon ':' after the if condition

D. Remove the else block entirely

Solution

1. Step 1: Check syntax of if statement

   The if statement is missing a colon ':' at the end, which is required in Python.

2. Step 2: Verify other parts

   turn_left() is a method call and correct, else: is valid syntax, so no changes needed there.

3. Final Answer:

   Add a colon ':' after the if condition -> Option C

4. Quick Check:

   Missing ':' after if condition causes syntax error [OK]

Hint: Always put ':' after if conditions in Python [OK]

Common Mistakes:

• Forgetting colon after if statement
• Confusing method call syntax with attribute
• Changing else to elif unnecessarily

5.

You want the drone to follow a black line on a white floor using the camera. The camera returns a grayscale image where the line pixels are darker (values near 0) and the floor is lighter (values near 255). Which approach best helps the drone decide how to move?

1. Calculate the average pixel value of the whole image.
2. Find the horizontal position of the darkest pixels (line).
3. Use the position to adjust drone's left or right movement.
4. Repeat continuously while flying.

hard

A. Use only the brightest pixels to follow the line

B. Use the average pixel value only to decide movement

C. Ignore pixel values and move randomly

D. Find darkest pixels' horizontal position and adjust movement accordingly

Solution

1. Step 1: Understand the image data

   The line is darker pixels (near 0), so finding their horizontal position shows where the line is.

2. Step 2: Use position to control drone movement

   Adjusting left or right movement based on line position keeps the drone following the line accurately.

3. Final Answer:

   Find darkest pixels' horizontal position and adjust movement accordingly -> Option D

4. Quick Check:

   Line position guides movement, not average or brightest pixels [OK]

Hint: Track darkest pixels' position to steer drone [OK]

Common Mistakes:

• Using average pixel value which loses position info
• Ignoring pixel brightness and moving randomly
• Following brightest pixels instead of darkest