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Sensors: how robots perceive

Each sensor below is a live simulation of a real component you'll use in this course. Drag, click, and watch the readings change.

📡 HC-SR04 Ultrasonic Distance Sensor

Emits a 40 kHz pulse, measures echo time. distance = (echo_time × 343 m/s) / 2. Drag the obstacle to change distance.

Reading

Distance— cm

Echo time— µs

Status—

Wiring (your Pi car)

VCC  → 5V
GND  → GND
TRIG → GPIO 23
ECHO → GPIO 24 (via voltage divider)

Python snippet

import RPi.GPIO as GPIO, time
GPIO.output(TRIG, True)
time.sleep(0.00001)
GPIO.output(TRIG, False)
while GPIO.input(ECHO)==0: t0=time.time()
while GPIO.input(ECHO)==1: t1=time.time()
dist_cm = (t1-t0) * 17150

🔴 IR Line-Follower Array

3 downward-facing IR sensors detect black vs. white. Drag the line to see how the array reports its position.

Sensor outputs

Left—

Center—

Right—

Decision—

Decision rule

if center: go straight
elif left:  turn left
elif right: turn right
else:       stop / search

A real line-follower extends this with a PID on the error between the line center and the sensor midpoint.

🔄 Rotary Encoder

A slotted disc + photo-interrupter counts ticks as the wheel turns. Click "Spin" or use the speed slider.

Controls

Wheel speed 60

Reading

Ticks (total)0

Revolutions0.00

RPM (estimate)0

Distance @ r=3cm0.0 cm

Sensor fusion preview — Real robots combine multiple sensors because each one is noisy or limited. Your Pi car will use the ultrasonic to detect obstacles, but it could add IR to follow a line and encoders to know how far it has traveled. A Kalman filter combines all three into one clean estimate of the robot's state.