Following Line based on Centroid Detection

This is a simple solution for line following tasks.

GitHub_Link

1. Solution Introduction

Key implementation points:

Objective: Enable autonomous line following for the robot
Core concept: Detect and create a "ball" in the line for the robot to follow - this is the Centroid Detection
Technical implementation: Color-based recognition using OpenCV for image processing
Special features: Includes obstacle avoidance and other special condition handling

2. Solution Framework and Process

3. Centroid Detection Principle

3.1 Binary Processing

Image contains only yellow and black colors
Convert image to binary matrix: black represents "0", yellow represents "1"
Binary processing facilitates subsequent mathematical calculations

3.2 Image Moment Calculation

In the yellow area, calculate the following:

Zero-order moment (M00): Represents the total area
First-order moments (M10, M01): Weighted sums along x and y axes

Calculation formulas:

M_{00} = \sum\sum I(x,y)

M_{10} = \sum\sum x \cdot I(x,y)

M_{01} = \sum\sum y \cdot I(x,y)

3.3 Centroid Coordinate Calculation

Using the calculated moments, we can obtain the centroid coordinates (cx, cy) of the yellow area:

cx = \frac{M_{10}}{M_{00}}

cy = \frac{M_{01}}{M_{00}}

4. Motion Control Implementation

4.1 Error Calculation

To ensure accurate line following, calculate the error between the centroid and image center:

error = cx - \frac{width}{2}

Where:

cx: detected centroid x-coordinate
width: image width
error: deviation from center

4.2 P Controller

Based on practical testing, using only a P controller achieves good control results:

angular_speed = -K_p \cdot error

Notes:

Simple P control is used instead of full PID control
Testing showed P control alone works better in this scenario
Robot response sensitivity can be adjusted through Kp value

5. Multi-State Decision Implementation

5.1 State Definitions

The system defines three basic states:

State1 (line): Yellow line detection state
State2 (obstacle): Obstacle detection state
State3 (explore): Exploration state

5.2 State Transition Logic

if detect_line():
    # Line detected, follow centroid using P control
    follow_centroid()
elif not (detect_line() or detect_obstacle() or is_exploring):
    # No line detected and not exploring, rotate to search
    rotate_search()
    if search_timeout():
        set_explore_mode(True)
elif not (detect_line() or detect_obstacle()) and is_exploring:
    # Exploration mode, move forward to find target
    move_forward()
else:
    # Obstacle encountered, use left-hand rule for avoidance
    left_wall_follower()

6. System Limitations and Future Work

6.1 Current Limitations

Color Recognition Limitations:
- Only supports specific color line detection
- Challenges with multi-colored lines or actual roads
Obstacle Avoidance Constraints:
- May lose original line during avoidance
- Lacks line memory and relocation capabilities