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[DPRG] Odometry and backlash

Subject: [DPRG] Odometry and backlash
From: David Anderson davida at smu.edu
Date: Mon Jan 5 15:30:48 CST 2015

Markus,

My SR04 robot, which has very good odometery, also has a laser pointer 
and can be wiggled back and forth within the backlash of the gear train, 
about +- 1 degree.  It's not a show stopper, and may not be the cause of 
the errors you are seeing.

I'm a little suspicious of the measurement method.  Seems like it 
assumes the robot is pivoting perfectly around the un-driven wheel, 
which may not be the case, and that's a bit hard to control for.

In my experience odometery can be made to work very well but it takes a 
lot of tuning of the robot.   For what it's worth, here's the method 
that works for me for a differentially steered robot:

1.    Be sure the encoders are working properly.

That is, not dropping any ticks, and working correctly forwards and 
backwards.  Care taken that the encoder hardware and software are 
working correctly and robustly will save lots of headaches later on.

     a.  Make a mark on the wheel(s) that lines up with something on the 
robot, set the encoder count to 0, and turn the wheel forward by hand 10 
turns.  Write down the number of encoder counts, then turn the wheel 
backward by hand 10 turns.  Be sure you get back close to 0.  Zero 
itself can be hard to get depending on the resolution of the encoders, 
but this is so you will know you are not dropping ticks forward or reverse.

     b.  Do the same with the other wheel, and verify that the numbers 
are about the same for both wheels.

     c.  Run the motors forward at full speed for a time and be sure 
that both encoders show about the same number of total counts.  They 
won't be identical because the motors are not really running at the same 
speed, open-loop.  But they should be close. Do the same in reverse.  
This helps determine if you are dropping any ticks at high speed.


2. Calibrate ticks-per-inch.  (or mm or whatever)

Set the encoders to 0 and run both motors forward at a medium speed, in 
more-or-less a straight line, for 10 feet, and stop. Write down the 
total number of counts for each encoder.  Then the robot's 
ticks-per-inch constant is:

#define TICKS_PER_INCH = ((left_encoder+right_encoder)/2)/120.

You can layout 10 feet with a tape measure on any convenient surface, 
kitchen floor, sidewalk, etc.    Alternately, lots of buildings have 
handy 1 foot square tile floors and a hallway makes a nice piece of 
built-in graph paper for encoder calibration.


3.  Manually measure the robot's wheel base.

For a differential two wheel drive robot, lay a ruler across the bottom 
of the robot from wheel to wheel, and record the distance from the 
center of one wheel to the center of the other.   This is the starting 
point for calibration of accurate turning and angles.

#define WHEEL_BASE = hand measurement.


4.  Run a series of left and right hand squares.

This is really the only way to separate out the various sources of 
errors.  It doesn't have to be 10 feet square, just use whatever room 
you have available.  The larger the square, the more apparent the 
errors.  But a smaller square works fine.  Also on carpet, if that's all 
you have available.

The procedure is to drive around a square and stop, and mark the 
distance in X and Y from the stopping point to the starting point.   Do 
it several times in one direction, say clock-wise, and average together 
the errors.   A little like sighting in a rifle scope.  Then do the same 
thing in the opposite direction, counter-clockwise in this case, and 
average together those errors.

The left and right hand squares will reveal two sources of errors.   
Borenstein's UMBmark paper goes into the math in detail.  But more 
basically the errors will be symmetrical and asymmetrical.    If the 
clockwise and counter-clockwise position errors are symmetrical, it 
means the robot is turning either too far or not far enough in the 
corners.  That's a wheel base error.

The larger the wheel base value, the fewer degrees the robot will turn 
for the same number of encoder ticks, and vice-versa.  So if the robot 
arrives short of the goal in both directions, it is not turning enough, 
and the wheel base value needs to be reduced.  If it overshoots the 
origin in both directions, it is turning too much, and the wheelbase 
value needs to be increased.

On the other hand, if the errors are not symmetrical around the origin 
(they won't be) then the robot has two wheels that are not exactly the 
same size.  This is common.   The correction is to add a small value to 
the TICKS_PER_INCH for one wheel, and subtract it from the other wheel.

#define LEFT_TICKS_PER_INCH = TICKS_PER_INCH + WHEEL_SIZE_ERROR
#define RIGHT_TICKS_PER)INCH = TICKS_PER_INCH - WHEEL_SIZE_ERROR

This corrects the odometery for the error in wheel size without 
effecting the previously measure ticks per inch.

5.  Now adjust the WHEEL_SIZE_ERROR.

Rerun the clockwise and counter-clockwise squares, adjusting the 
WHEEL_SIZE_ERROR until the position errors become symmetrical. You'll 
probably have to do this a few times.  This will cancel out the wheel 
size errors.

6.  Finally adjust the WHEEL_BASE value.

Increase or reduce the WHEEL_BASE constant until the position errors, 
now symmetrical, cluster around 0, for both clockwise and 
counter-clockwise runs.   This is the fine tuning of the WHEEL_BASE, 
which is in turn the accuracy of the robot's angles. Once all the errors 
are clustered symmetrically around the origin at 0,0, then that's about 
as good as it's going to get.

Just as a reference, the odometery code that uses these constants looks 
like this:

void odometery()
{

     /* calculate elapsed encoder counts and distance since last cycle */

     left_inches = (float)left_velocity / LEFT_TICKS_PER_INCH;
     right_inches = (float)right_velocity / RIGHT_TICKS_PER_INCH;
     inches = (left_inches + right_inches) / 2.0;

     /* calculate angle of rotation since last cycle */

     theta += (left_inches - right_inches) / WHEEL_BASE;

     /* And wrap theta at two pi */

     theta -= (float)((int)(theta/TWOPI))*TWOPI;

     /* calculate robot's current position in X and Y */

     X_pos += inches *  sin(theta);
     Y_pos += inches *  cos(theta);
}

This code runs at 25 Hz and maintains three global values: X, Y, and 
theta, which are the robot's current pose and location.  Those values 
are read by the navigation code that drives the robot to a target way 
point location.

Whoa, little windier than I intended, interesting how "simple" things 
are sometimes more complex than is apparent.

Anyway, hope this is helpful,
dpa



On 01/05/2015 12:12 PM, Markus Lampert wrote:
> Hey Rud, Steve,
> eventually I will want to incorporate visual processing. For now though I want to keep things as simple as possible and see how far they go.
>
> Hi David,
>
> those are good questions.
>
> First off, I am currently not using UMBMark, mainly because I don't have access to a level and smooth 10' square - the virtues of living in an old house and our office building is all carpet.
>
> What I did was I mounted a laser pointer on my robot and mark the spot on the wall where it hits. I then turn on a single wheel to the lowest PWM signal that still makes the robot move reliably. I count the encoder ticks until I should have completed a full circle and measure where the laser pointer ends up in relation to where it started off. The intent was to do that in both directions and thereby get the accurate ratios of right wheel radius to wheel base and left wheel radius to wheel base. Which I then can use to calculate theta (or phi)....
>
> What happens though is that with the same settings I get differences of almost 3 degrees. The observed relation is that I should get about 4.7 encoder ticks per degree (if only one wheel is turning). In other words, with exactly the same number of encoder ticks the resulting turn is between 360 and 362.8 degrees.
>
> I have repeated the tests with different turning angles. The number of turns doesn't seem to make a difference. If I turn 10 times around I end up with the same variance as I do for a single turn. So the steady state seems to be working OK and the error is solely introduced by starting and stopping.
>
> By placing the robot on the floor, again turning on the laser pointer I can 'wiggle' the robot by ~1 degree before the gearbox engages and I get the first encoder tick (2cm laser pointer travel when the wall is 150cm away). Note that this is 1 degree in total, not 1 degree in each direction.
>
> After sending my email yesterday I spent the rest of the day rebuilt my robot to get the battery pack (currently by far the heaviest piece of the robot) closer to the wheels. Will redo my tests tonight and see if it makes a difference. I also thought of repeating the tests without battery in order to eliminate slippage and inertia as much as possible (although that might help me understand what is going on it will not help the robot).
>
> Any help appreciated, thanks,
> Markus
>
>
> On Mon, 5 Jan 2015 00:11:24 -0600
> David Anderson<davida at smu.edu>  wrote:
>
>> Hi Markus,
>>
>> It would be good to know exactly where the problem lies.   How have
>> you determined the rather large variance in calibration runs?  Was
>> this done using the UMBMark?   Large left-hand and right-hand squares?
>>
>> Is the large variance observed in  the stopping point of a series of
>> similar, say, left-hand runs?   Or is it between the left-hand and
>> right-hand runs?  Those are different problems.
>>
>> ~1 degree slop in the gear train is probably manageable, depending on
>> how you are doing the navigation.   If it is a single calculation at
>> the start of a run or line segment, then ~1 degree theta error at the
>> start will throw the robot way off in X,Y at the end.   If instead
>> the odometry navigation is a continuously running calculation as the
>> robot travels, then ~1 degree of error becomes less and less
>> significant as the robot approaches its target, and basically
>> insignificant when the robot is at the target.
>>
>>
>> Don't give up on your drive-train yet. :)
>>
>> dpa
>>
>>
>>
>>
>>
>> On 01/04/2015 02:21 PM, Markus Lampert wrote:
>>> Hi,
>>>
>>> I am adding odometry to one of my robots and found a rather large
>>> variance in my calibration runs. As it turns out my gear motor has
>>> some backlash resulting in ~1 degree of heading "wiggle room". The
>>> quad encoder sits on the motor shaft, not on the wheel itself which
>>> means they don't pick up on the backlash at all.
>>>
>>> I could not find any methods for backlash compensation other than
>>> for CNC machines, which doesn't seem to translate to mobile robots.
>>>
>>> Is there a method to compensate for it or am I in the business of
>>> finding a 'better' drive train for my robot?
>>>
>>> Thanks in advance,
>>> Markus
>>>
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