Lesson 6 · Two-Sensor Line Following

Module 2 · Line Tracking

Lesson 6 · Two-Sensor Line Following

50–60 minControl loopsFollowing the center

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Last lesson the robot followed one edge with a single sensor. Now you'll use both sensors together — and the code actually gets simpler. The robot straddles the line and follows its center, giving smoother, more reliable tracking.

Learning Objectives

By the end of this lesson you will be able to:

• Explain why two sensors track better than one
• Compute error with two sensors: error = left − right
• Predict the sign of the error from the robot's position
• Build a two-sensor proportional control loop
• Explain the negative sign in arcade(base_effort, -correction)

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Printable knowledge checks — the 3 questions from this lesson on one page, with room to write. Teachers: answer key.

The difference is the error

With two sensors straddling the line, you don't need a setpoint anymore. Just subtract one reading from the other:

error = left − right

When both sensors read the same, the difference is zero and the robot drives straight. When one drifts onto the line, the difference tells you exactly how much and which way:

Position	left	right	error = L − R	Meaning
Centered	0.5	0.5	0.0	drive straight
Drifted left	0.8	0.2	+0.6	steer left to correct
Drifted right	0.2	0.8	−0.6	steer right to correct
Both on white	0.1	0.1	0.0	straight (lost line)
Both on black	0.9	0.9	0.0	straight (an intersection!)

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Diagram — two sensors straddling a line, centered vs. drifted left vs. drifted right

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Two sensors straddle the line. The difference between them says which way the robot has drifted.

Knowledge Check

The left sensor reads 0.8 and the right reads 0.2. What is the error, and which way has the robot drifted?

The control loop (and that negative sign)

The loop is the same rhythm as Lesson 5 — read, compute, steer — just with the new error and a negated correction:

from XRPLib.differential_drive import DifferentialDrive
from XRPLib.reflectance import Reflectance
from XRPLib.board import Board
import time

drivetrain = DifferentialDrive.get_default_differential_drive()
reflectance = Reflectance.get_default_reflectance()
board = Board.get_default_board()

Kp = 0.5            # tune this
base_effort = 0.3

board.wait_for_button()

while True:
    left_sensor = reflectance.get_left()
    right_sensor = reflectance.get_right()

    error = left_sensor - right_sensor
    correction = error * Kp
    drivetrain.arcade(base_effort, -correction)   # note the minus sign

    time.sleep(0.01)

Why the minus? A positive error means the robot drifted left, so it must steer left — and in arcade() a negative turn steers left. Negating the correction lines the math up with reality.

Knowledge Check

Why is the correction negated in arcade(base_effort, -correction) here, when Lesson 5 didn't negate it?

Teach the sign with the explorer program first

Before the control loop, run a read-and-print program and have students manually slide the robot across the line, watching error = left − right go positive, negative, and zero in real time. That physical intuition makes the negative sign click. Spend real time on why the sign flipped from Lesson 5 (the meaning of a positive error changed) — it's the subtle point of the lesson. Expect to re-tune Kp, since the error range differs from the one-sensor version.

Activity · Follow the circle, then compare

1. Run the two-sensor follower with the line running between the sensors, and watch it track the circle.
2. Run your Lesson 5 (one-sensor) version right after. Which is smoother? Which handles the curves and higher speeds better?
3. Challenge: turn base_effort up to 0.4–0.5 on both and watch what happens to each. Which one degrades first, and what does that tell you about how much information one sensor gives the robot?

Knowledge Check

Both sensors suddenly read high (0.9 and 0.9), so error ≈ 0 and the robot drives straight. What has it most likely reached?

Differentiation & the cliffhanger

More support: hand out a reference card — "left high = drifted left; right high = drifted right" — and lean on the explorer program. More challenge: a speed boost on long straights (when error stays near zero), or track at max speed and re-tune. End by flagging the last table row: both-sensors-high gives error ≈ 0, so the robot ignores an intersection. That ambiguity is the hook for Lesson 7.

Real-world connections

Comparing two sensors to find a position is a workhorse technique:

Audio

Stereo & hearing

You locate a sound from the tiny difference between your two ears — same differential idea.

Navigation

Differential GPS

Comparing two receivers cancels error and pins a position down to centimeters.

Robotics

Sensor arrays

Advanced line followers use 5–8 sensors, but the principle is the one you just learned.

Wrap-up

• What's the two-sensor error formula, and why no setpoint? (left − right; equal readings already mean zero.)
• Positive error means the robot drifted which way? (Left.)
• Why the negative sign on the correction? (A positive error needs a left steer, which is a negative turn in arcade().)

Assessment & next lesson

Formative: compute left − right, predict drift direction and steer, and explain the negated correction. Exit ticket: "Both sensors read 0.9 — what's the error, and what might it physically mean?" (≈0; an intersection). Preview: next lesson we detect that intersection with left > threshold and right > threshold.

Resources

• XRPLib Documentation
• XRP Robot User Guide