Replace that tennis ball with a talking Raspberry Pi!

The challenge is not to hit the ladder while parking

Our garage has a ladder sticking out near where we park our car.  We want to park close to the ladder leaving enough room to walk in front of the car and also allow room behind the car for the garage door to close. A typical solution to this need, and one we’ve used in the past, is to have a tennis ball on a string positioned such that the car window nudges the ball and shakes the string — so you know when to stop.  A great analog solution!  I, however, desired a digital solution that incorporates a Raspberry Pi.

This parking-assist solution doesn’t “speak” to me!

OK, a digital solution should either have a sensor that is tripped by the car or, even better, something that could dynamically measure and show the distance from the car to the ladder.  This would require some way to provide feedback to the driver.   Hmmmm, feedback could be visual or maybe via sound.  Yes,  that’s it!  I could have an R-Pi measure the distance and “talk” to the car driver.  Another project is born 😎


So, what is needed to pull this project off?  A real time distance-measuring device that interfaces to a Raspberry Pi, software to convert values (measurements) to text, software to “read” the text (text-to-speech), and hardware for audio output.

Maxbotix USB ultrasonic sensor

Distance sensors come in several different flavors with different interfaces.  There are laser-based, IR-based and untrasonic range sensors.  Different types have different ranges and accuracy.  I wanted one that  could measure from about 1 foot to about 6-10 feet (30 cm to about 2-3 meters).  I also wanted a fairly wide “cone” to detect different size and shape fronts and rears on different vehicles.  Most sensor interfaces are either I2C or serial.  The Inter-integrated Circuit (I2C) Protocol only requires two signal wires to exchange information but requires connection to R-Pi headers and more complex software.  I did not want a soldering project and I liked the idea of a USB interface coupled with popular software support libraries.  Numeric values of distance could be sent as ASCII text via the serial interface and read and manipulated on the R-Pi without the need for low-level timing loops, etc.  After some research, I settled on the Maxbotix HRUSB-MaxSonar-EZ high resolution USB ultrasonic sensor, model MB1413.  I purchased one from Adafruit for about $50


The software

I decided to program my application in Python as all the pieces I needed could be accessed via various python libraries or by calling-out to the operating system for helper applications.  I decided on the pySerial 3.x module for serial communications.  I also installed the “minicom” Linux terminal application,  which enabled me to talk to the range sensor for setup and testing.  The sensor communicates via the USB port in a stream of ASCII text numbers.  Python provides the ability to maipulate strings and convert numbers into various units of measure (inches, feet, cetimeters, meters, etc.).  I wanted values and commands (“vehicle detected … 3 feet … 2 feet … 1 foot  … stop!”) to be spoken.  To do this, I needed a text-to-speech (TTS) utility.  There is a nice comparison of different TTS engines that run on the Raspberry Pi on eLinux.  After some research and experimentation I went with “pico2wave”.  I found this to produce the most natural speech — and it supports multiple languages.  As pico2wave outputs a “WAV” file, I needed another app to convert the WAV file into audible output.  I used “aplay”, a Linux command-line soundfile player.


My first step was to ensure the ultrasonic module could communicate with the R-P.  I connected the sensor to a USB port of the R-Pi with a USB 2.0 A-Male to Micro B cable.  After doing the usual “apt-get” update and upgrade, I installed the minicom terminal package:

sudo apt-get install minicom

Need to determine which USB port is being used.  Look for “tty” entries with “USB” suffix.

ls /dev/ttyUSB*

This command returned — for my R-Pi:


OK, time to run miniterm with appropriate settings and see what data the sensor is returning:

minicom -b 57600 -o -D /dev/ttyUSB0

enters terminal mode and shows something like:

Welcome to minicom 2.7

Compiled on Apr 22 2017, 09:14:19.
Port /dev/ttyUSB0, 15:28:59

Press CTRL-A Z for help on special keys

and a line constantly updating:


The “R” indicates a range reading and the number is the distance from the sensor in milimeters.  As you move things closer or further from the sensor, you’ll see the distance number change 🙂  You can exit terminal mode with CTRL-A followed by “x”.

Now we have the raw data that we want to manipulate.  I want to convert to imperial units (inches, feet, yards) for us Americans and I want the R-Pi to talk.  I am using Python 2.7 which is installed as “python” on the R-Pi.  Do not confuse with Python 3.5 (“python3” on R-Pi).

Make sure you have the python serial library installed:

sudo apt-get install python-serial

Install the Test-To-Speech (TTS) engine/app:

sudo apt-get install libttspico-utils

If you have your R-Pi setup for audio output, you can test things by using “pico3wave” and “aplay”.  I’ll leave it as a user exercise to ensure “aplay” is outputting to the correct device and that TV or amp/speakers are connected correctly.  The use of “aplay”, from the ALSA framework, over “omxplayer” allows for more output devices such as USB powered speakers, DACs or other USB audio devices.

pico2wave -w sorrydave.wav "I'm sorry Dave. I'm afraid I can not do that"
aplay sorrydave.wav

you should see output from aplay – something like:

Playing WAVE 'sorrydave.wav' : Signed 16 bit Little Endian, Rate 16000 Hz, Mono


rm sorrydave.wav

I’m going to call various Linux apps via Python.  I want the output from “pico2wave” (TTS) to be input to “aplay”.  In the Linux shell, I would normally pipe output (stdout) of one app to input (stdin) of another.  Unfortunately, “pico2wave” does not behave well 🙁  There is a workaround  under Linux.  You can make (link) a file be stdout and use this file as input.  For our purpose, we’ll do this via this command:

sudo ln -s /dev/stdout /var/local/pico2wave.wav


Python Code

I integrated the various pieces (sensor readings, text-to-speech and audio output) via a Python program.  I used the serial input library, did some measurement conversions and used system call for TTS output.

The code:

# -*- coding: utf-8 -*-
import serial
import time
import os

# Function to read chars from serial input until you get a <CR> or null
# before getting a line, clear the buffer/cache.  We do not want "lagging" data

def readlineCR(port):
    rv = ''
    while True:
        ch =
        rv += ch
        if ch == '\r' or ch == '':
            return rv

# Function to get sensor reading as text, validate & return numeric value in mm

def getDist():
    mmdist = 0
    while True:
        response = readlineCR(port)
        if len(response) == 6 and response[0] == 'R':
            mmdist = int(response[1:5])
            return mmdist

# setup serial port parameters per MaxBotix specs

port = serial.Serial(

# Open serial port for read/write

print port.isOpen()
print 'Port opened...'

# initialize variables
# saymtric = say metric measurement (in mm) else imperial (in inches)
# last = last measurement read - used to determine movement
# inches = used if conversion to imperial units desired
# delta = value in mm to determine motion between readings
# inrange = if closer then this, speak! (1800mm = 6' == 72")
# mmmm[ ] = used to determine median of multiple readings -- filter out noise

saymetric = True
last = 0
inches = 0
delta = 10
inrange = 1800
mmmm = [0, 0, 0]

# Loop forever for constant measuring.  Will speak if closer than 6 ft (180 cm)

while True:

# validate & convert text to numeric value in mm
# filter noise by using median of 3 readings

    mmmm[0] = getDist()
    mmmm[1] = getDist()
    mmmm[2] = getDist()
    mmm = mmmm[1]

# only talk if there is movement.  check delta

    if abs(last - mmm) > delta:
        inches = int(mmm * 10 / 254)
        print mmm

# check distance and use selected units of measure (metric vs. imperial)

        if (mmm < inrange):
            if (saymetric):
                os.system('pico2wave -w /var/local/pico2wave.wav ' + '"' + str(mmm) + '"'  + ' | aplay -q')
                os.system('pico2wave -w /var/local/pico2wave.wav ' + '"' + str(inches) + '"' + ' | aplay -q')

# save mm value to use in delta motion check

        last = mmm


Prototype using an R-Pi 3 and the SmartiPi Touch LCD with lego-type attachements 🙂

There are a couple of areas to note in the code.  MaxBotix suggests using the median of multiple readings to reduce “noise” and spurious measurements.  I also don’t want the R-Pi always talking!  I check to ensure an object (my car) is within 1800mm (6 ft.) and that there has been some movement since the last reading (use of “delta” variable).

I believe that there are many use cases for being able to measure distance, detect motion and have the R-Pi speak.  Please LMK if you build this “parking-assist” system or if you develop other uses for the concepts presented here.


— Andy




4 thoughts on “Replace that tennis ball with a talking Raspberry Pi!”

  1. Pingback: Parking assistance from a Raspberry Pi replaces a tennis ball – Raspberry Pi Pod

  2. Hi! Nice tutorial! I created this a while ago, but never did anything with it. This weekend, I borrowed some BlinkyTape lights from a friend and incorporated them into this project, instead of using the voice to tell you how far away. I set a simple if/else statement to set the correct color based on the distance. Only other thing I changed was reduced the delta to a smaller value, so that it would react quicker.

    Here’s a link to my code in github:
    And here’s a link to the working demo:

    I’m sure there’s more tweaking to do, but this seems to be working for now. One thing is the lights are always on. Might be worth adding a timer to turn the lights off if some amount of time has passed with no movement.

    Thanks for the tutorial!

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