| Line
tracking sensors and algorithms
By
Ibrahim Kamal
Last update:
15/4/08
 Overview
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Line tracking is a very important notion in the world of
robotics as it give to the robot a precise, error-less and
easy to implement navigation scheme.
As you may have seen, many robotics competitions
promote this concept, by adding lines on the playground
for the robot to follow, or sometimes, the sole purpose
of the competition is to race with other robots following
a line along a track.
In this tutorial, I am going to rely on the experience achieved
by building the line sensors of the robots that participated
to the robocon 2007 competition. |
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1.
Number of cells in a sensor
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A line
sensor is one that will gather information about the position
of a line traced on the ground underneath the robot, to help
it to navigate through an eventual grid of lines and intersections.
For the software to function correctly, the sensor's
electronic circuits have to provide a maximum number of information
about that line.
As
you can see in figure 1, a line sensor is composed of
a number cells and each cell is composed of a sender
and a receiver. The particularity of this sender/receiver
pair, is that it sends light that shall be reflected
by the line to be detected but not by the eventually
opaque background surrounding this line. Any sender/receiver
pair that is able to make a difference between a line
and the rest of ground (of a different color) can be
used in a line sensor.
Usually, to make it easier on the designer of the sensor,
there is an important contrast between the line and
the ground (for example: white line on a dark blue ground),
But in case there isn't enough contrast, there is a
method to easily build a line sensor adapted to that
specific situation, relying on old physics rules
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Figure 1 |
that
states that a colored surface will absorb the light of different
colors, and reflect the light of the same color. For example,
If you want to build a line sensor to detect white lines drawn
on a light blue floor, you can send red light, as the blue will
absorb all of it, and the white line will reflect all of it.
Actually this was the case in the playground of Robocon 2007
competition, there wasn't enough contrast between the white
lines and the blue ground, so we had to use RED LEDs as senders
instead of our preferred IR LEDs
So the first aspect that affects the precision and the quality
of a line sensor, is the number of cells. Some roboticists use
only 2 cells to know whether the line is at the left or at the
right of the robot, but as you shall see later in the software
part, this very poor source of information wont allow the controller
to gradually guide the robot back on the track, instead you
will notice that the robot will keep brutally turning right
and left, but will never be able to smoothly follow the line.
On the other hand, an 8 cells line sensor will give a spectrum
of relatively rich information to the controller, indicating
whether the robot is very close to the line, close, far, or
very far away. This variety of information will allow the controller
to take actions that are proportional to the distance between
the robot and the line, resulting in a smooth line tracking
system.
2-
Distance between the cells
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The second aspect the be considered when building a line sensor,
is the cell spacing (or the
distance
between a cell and the other). To understand the effect
of cells spacing, consider the differential drive robot
shown in figure 2, with an 8 cells line sensor, whose
cells are numbered from 1 to 8 (from the left to the
right). Three different situations are shown, In the
first one, the cells 4 and 5 detect the line, indicating
that the robot is perfectly centered on the line. In
the first situation, the spacing between the cells is
not very critical, but if the robot accidentally makes
a 10° turn away from the line (second situation),
you will notice that only the cell number 6 detect the
line, which is the only indication that the controller
will have about that 10° error. This means that,
most probably, an error smaller than 10° wont even
be noticed.
But in the third situation, the cells are closely collated
together, and you can notice that with the same 10°
deviation from the line, the sensor's cells 6 and 7
detected the line, leaving some other possible states
in between the perfectly centered position and the 10°
deviation. In other words, the closer are the cells
from each others, the more will be the resolution of
the sensor.
The same effect can be observed by changing the distance
between the sensor and the center of steering. In general,
It is important to always try to keep the sensor as
far as possible from the center of steering, which is
the back of the robot in a differential
steering one, because this will also
help to amplify the deviation detected by the sensor,
resulting in
a better response |
Figure 2 |
from the controller.
3.
Building the sensor
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There are many electronic components that can be used to build
the sender/receiver cells of a line sensor. Two of them are
discussed in this article, showing the advantages and disadvantages
of each one, and showing how to implement each one of them in
an electronic circuit.
IR
LEDs |
LDRs
and LEDs |
This
method relies on our famous IR
proximity sensor with some modification. It has
the advantage of being cheap and easy to implement,
but unfortunately need an important contrast between
the line and the ground. Refer to the this tutorial
for more information. |
When
you need to adapt to low contrast situations, as discussed
before, this is the most common alternative. You chose
the most suitable color of LED for sending the light,
then, the LDR will pick up the reflected light, but
it's slower to respond than IR LEDs. |
Figure 3.A: One cell
implementation
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Figure 3.B:One
cell implementation
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D1:
Emitter LED
D2: Receiver LED |
R6: Sensitivity
adjustment |
D1: Emitter
LED
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R1: Sensitivity adjustment
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After a lot of experiments,
I personally recommend the LDR based line sensor because it
can be easily adapted to many different environments by adjusting
the sensitivity using the potentiometer R1 or by changing the
color of the LED D1.
Here is the electronic circuit of the LDR based line sensor
we used in our robots in the Robocon 2007 competition. As you
can see it is composed of eight cells, each one resembling the
cell in figure 3.B. There are many reasons to choose to build
a sensor with exactly eight cells, no more, no less: Eight can
provide enough precision, it connects directly to one port of
the microcontroller, and is represented by one single Byte
of data, making it easier to implement in the programming and
in the memory of an 8 bit microcontroller.
Figure 3.C
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The wire connections W3 to W10 are the outputs of the 8 cells
of the sensor.
The value of R1 to R9 cannot be lower than 50 ohm, actually
this value is very low and that's why the sensor sinks a lot
of current. You may try to use larger values first, like 220
ohm, then if the intensity of the light is not en ought, reduce
it gradually.
You will also notice that there are 9 sender LEDs (not 8), that's
because the the LEDs and the LDRs are positioned in such a way
that each LDR has one led on its right and another on its left
(as you can see in figure 3.D). The purpose of this technique
is to make sure all LDRs share the same reflected light intensity,
and this way, only one potentiometer can be used to calibrate
all of them.
Figure 3.D
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4.
Proportional Control Algorithms
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Now that your sensor is working and is providing
a correct reading of the line underneath it, you still need
to develop some algorithms to use the data collected from the
line sensor. The quality of those algorithms is as important
- if not more important - than the quality of the sensor it
self. Its those software procedures that will give to the robot
the ability to smoothly and correctly track lines in a grid
of lines and intersections, perform 90° turns and many others
moves that can be implemented in such a lines grid.
Proportional Control, which is usually used in line following
algorithms, means that the intensity of the rotation of the
robot towards the line is proportional to the distance between
that robot and the line. In other words, if the center of the
robot is positioned exactly on the line, the rotation of the
robot will be equal to zero, but if the robot gets deviated
from the center of the line, the intensity of the rotation will
gradually increase, until it reaches maximum intensity if the
line is completely out of reach. This proportional Algorithm
will prevent the robot from oscillating to the right and to
the left of the line while trying to follow it.
What I mean by the intensity of rotation, is the speed at which
the wheels will turn (in a differential steering robot) or the
angle of the front wheel (in a car-like steering robot).
This may be true in theory, but in practice, due to the non-linearity
of the behavior of DC motors, and many others sources of error
that cannot be clearly defined, the robot would still oscillate
while trying to track the line, and would sometimes fail, because
the error would eventually increase instead of decreasing. That's
why the proportional control scheme have to be tailored for
each robot, depending on it's moment of inertia, on the type
of motor, on it's weight and on many other factors. After lot
of testing, the graph in figure 4.A shows a control scheme that
proved to work correctly on most differential steering robots.
Figure
4.A represents a relation between the speed that should
be applied on the right and left wheels of a differential
steering robot and the position of the line relative
to the center of the robot. As you can see, for an 8
cell line sensor, the line is considered to be at the
center of the robot when it reads 4.5, while it is considered
to be totally at the left when the first cell of the
sensor is detecting the line.
The only thing you may have to to do, is to define the
value of Smax suitable to your robot. The easiest way
to do this is by trial and error. You will probably
notice that High values of Smax will result in very
fast response, but with a lot of oscillations. |
Figure 4.A |
An important question is how to obtain analog
readings from such a digital output line sensor? The answer
is we actually don't obtain real analog signals, we just calculate
an average of the position of the line, when more than one cells
detect the line. For example, when cells number 4 and 5 detect
the line, the average of 4 and 5 is 4.5, and we will consider
this value as the reading of the line to be used in the graph
of the figure 4.A. Depending on the thickness of the line being
tracked, you can optain a multitude of readings between a integer
and the other.
In order to precisely control the speed of the motors in a differential
drive robot, you need to adapt what is called closed loop speed
control of DC motors, which is explained in detail in this tutorial.
For a 8051 microcontroller programmed in C, here is an example
source code of a function named follow_line()
which when called, reads the value of the sensor which is connected
to port 0, calculates the average then deduces the required
speed of the right and left wheels to smoothly adjust the robot
to the line.
follow_line(){
max_speed = 8;
half_speed = 4;
line_to_speed_factor = (max_speed) / 4.5;
//The line sensor is connected to P0
if (P0 != 0 ){ //Keep the old line reading in case the line is lost
old_line = P0;
}
new_line = P0;
l1 = P0_0; //Store the values of each cell of the 8 cells of the
l2 = P0_1; //line sensor in the variables l1 to l8.
l3 = P0_2;
l4 = P0_3;
l5 = P0_4;
l6 = P0_5;
l7 = P0_6;
l8 = P0_7;
fwd(); //Call a function that orders the robot to move forward
if (P0 == 0){ //In case the line is out of reach, rely on the last valid
if (old_line > 45){ //reading to decide whether to pivot right or
pivot_left(); //left to reach the line again.
req_right_pulses = max_speed;
req_left_pulses = max_speed;
}else{
pivot_right();
req_right_pulses = max_speed;
req_left_pulses = max_speed;
}
}else{
if(old_line != new_line){
//Calculate the average reading of the line.
line = (l1) + (l2*2) +(l3*3)+(l4*4)+(l5*5)+(l6*6)+(l7*7)+(l8*8);
line = line / (l1+l2+l3+l4+l5+l6+l7+l8);
//Calculate the required right and left speed
//according to the graph.
req_right_pulses_ = floor((line*line_to_speed_factor)+0.5);
req_left_pulses_ = floor(((9-line)*line_to_speed_factor)+0.5);
if (req_left_pulses_ > max_speed){
req_left_pulses = max_speed;
}else{
req_left_pulses = req_left_pulses_;
}
if (req_right_pulses_ > max_speed){
req_right_pulses = max_speed;
}else{
req_right_pulses = req_right_pulses_;
}
}
}
} |
Note that this code is not stand-alone, it is
a part of more complicated program that contains the the closed
loop speed control and many other functions allowing the robot
to navigate according to a specific path. for example, the values
'req_left_pulses' and 'req_right_pulses' have to be fed to the
closed loop speed controller.
You will also notice that the speed is calculated in two steps,
the first result is stored in 'req_right_pulses_' then the final
result is stored in 'req_right_pulses'. This is because the
graph in figure 4.A is composed of two independent linear relations,
the first is for the readings from 1 to 4.5, and the other relation
is for the rest of the readings, 4.5 to 8, (and the same applies
to the 'req_left_pulses' variable). This is just an example,
there are many ways to implement such a graph into a microcontroller
program, it's up to you to see the most suitable method according
to the architecture and organization of your program.
5-
Navigation through lines and intersections
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Now that you know
how to make your robot follow a line, you can use that same
sensor to
allow
it navigate through a grid of horizontal and vertical
lines as the one in figure 5.A, using the same 8 cells
sensor.
The main clue to an errorless navigation in such a maze,
is to be able to precisely detect intersections. To
do that, first you have to analyze the nature of those
lines, the angle of intersections, and the different
readings of the line sensor when crossing intersections.
Actually, you have to adapt your code to each and every
playground you expect you robot to navigate on.
After a lot of testing we developed this simple technique
to detect intersections,
whatever the way the robot crosses it.
|
Figure 5.A |
As
you can see in figure 5.B, three different situations
are shown, in each one of them, the robot crosses an
intersection, coming from a different angle. The cells
of the line sensor that detect the line are designated
by bright red spots, while cells that don't detect it
are designated by dark red spots.
What we tried to do is to find what is common between
those 3 different possibilities, and the following rule
was developed to detect intersections:
'If one of the end cells (1 or 8) detects the line while
one or more of the last 4 cells at the other end also
detect the line, then the sensor is crossing over an
intersection'
In other words, for an intersection to be validated,
the reading of the sensor must be as follow:
Cell number 1 detect the line AND one or more of the
cells 5 to 8 detect the line
OR
Cell number 8 detect the line AND one or more of
the cells 1 to 4 detect the line
Then you have to develop the code that will analyze
the readings of the sensor, count intersection, and
guide your robot through |
Figure 5.B |
the desired path, which can be done with a multitudes
of methods. The choice of the method to guide a robot, and precisely
localize it in a map can be very difficult task, even if you
are using line following algorithms. Some methods will even
involve a combination of dead reckoning and line following to
achieve more accurate results. Generally, it's your job to design
the navigation
scheme which is most suited to the environment of the
robot. It's important to note that robot navigation
is subject to many research and is still in an intensive
development phase in the robotics labs around the world.
I hope this article covered the main aspects required
to construct a simple robot navigation system based
on line following algorithms and helped to introduce
some of the scientific principle behind the operation
of such a system. |
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Preview of the last 15
messages discussing this page. Messages are sorted from the newest to
the oldest. |
Posted
by:
mohamed.amin
on:
05 May 2010 |
Re: Line tracking sensors and algorithms |
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Quoting ikalogic:
| Quoting mohamed.amin: i tried the white line on black surface ... |
And........... ???   |
:D sorry i was working on the project when i was writing and i got carried away :D the same result it reflected but i noticed that the surfaces except for white and red (because i am using red LED ) reflects but it has to be closer ..so i think your assumption was right from the beginning ...
thanx for your time 
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Posted
by:
mohamed.amin
on:
04 May 2010 |
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Re: Line tracking sensors and algorithms |
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Quoting ikalogic:
Quoting mohamed.amin:
Quoting mohamed.amin: hello...
it's a brilliant idea however i tried different surfaces with different colors but the light reflected in all cases
thx for ur time |
do u have any suggestions my project deadline is really close |
Oh, i didn't see that it was a question..!
So, did you try a white line on black surface? did you try to increase the series resistors of the LEDs (to decrease intensity) ? |
i tried the white line on black surface ...but i will try decreasing the illumination of the lead
thanks for ur time
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Posted
by:
ikalogic
on:
03 May 2010 |
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Re: Line tracking sensors and algorithms |
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Quoting mohamed.amin:
Quoting mohamed.amin: hello...
it's a brilliant idea however i tried different surfaces with different colors but the light reflected in all cases
thx for ur time |
do u have any suggestions my project deadline is really close |
Oh, i didn't see that it was a question..!
So, did you try a white line on black surface? did you try to increase the series resistors of the LEDs (to decrease intensity) ?
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Posted
by:
mohamed.amin
on:
03 May 2010 |
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Re: Line tracking sensors and algorithms |
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Quoting mohamed.amin: hello...
it's a brilliant idea however i tried different surfaces with different colors but the light reflected in all cases
thx for ur time |
do u have any suggestions my project deadline is really close
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Posted
by:
vigneshss6046
on:
28 Mar 2010 |
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Line tracking sensors and algorithms |
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I am a beginner and i would like to know the exact pcb and source program for the line follower and i am using AT89s52.I would like to know the details what other ic's i have to use and in which IC i have to load the source program(if it is in AT89s52 is it reprogammable)
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Posted
by:
bhargavsvashi
on:
24 Feb 2010 |
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Line tracking sensors and algorithms |
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okay buddy bt plz make it soon... i have herd 4m ur site nly dat ir sensors r faster as compared to leds... n my requirement of the project is fast line sensing... the contrast between the lines n background is much high so ir can b taken under consideration...
upload it soon buddy...
can i get a tentative date of when u uploading the stuff??
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Posted
by:
ikalogic
on:
23 Feb 2010 |
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Re: Line tracking sensors and algorithms |
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Quoting bhargavsvashi: thanks dude...
n can i get .pcb file for sensor array using infrared led?? |
I don't have it right now.. and as far as i remember the result wasn't that good (i am not saying that IR is not good for that purpose, but my implementation was not that good) It's in my todo list to add a line follower sensor kit on the site, one that is much more precise with auto-contrast adjustment.
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