Vision Guided Robot Key to First-Known Automated Lug Nut Fastening Application

lynxherringAI and Robotics

Oct 18, 2013 (3 years and 10 months ago)

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Vision Guided Robot
Key to First
-
Known
Automated Lug Nut Fastening Application


Running down and torqu
ing the lug nuts that hold the wheel to the hub is
seemingly one of the simpler aspects of building an automobile
,

but it has
proven
one of the most

diff
icult to automate.
This is a difficult manual job,
as well,
because of the size and weight of the nutrunner and the need to
tighten the

nuts on two wheels in
approximately

40 seconds. If the position
of the lug nuts
is
known, a robot c
an

easily position th
e
nut
runner to
deliver
the needed torque
.
The problem is that
typically
the vehicle is only roughly
positioned by
a
conveyor and the wheels themselves are free to rotate, tilt,
and turn.
Therefore

an ordinary blind robot would never be able to find the
nut
s.


Radix Controls
, Oldcastle, Ontario,

successfully automated this application
by using a vision system to determine the position of the wheel including
its
fore and aft and side
-
to
-
side position
s

and three rotational axes
. With this
information, the robo
t can easily move the nut runner into the exact position
and tighten the nuts.
Automating this application

made it possible for two
people to move from difficult and stressful jobs to more proactive
roles
. “As
far as we know, this is the first
time
this ap
plication has been successfully
automated with the use of machine vision,” said Shelley Fellows, Vice
-
President Oper
ations for Radix Controls Inc.


Challenge of automating difficult manual task


The automotive assembly plant involved in this application bu
ilds vehicles
24 hour
s a day with

just
-
in
-
time
production scheduling
. In a previous
assembly line
stati
on
,
two

operator
s

(
one

on each side of the vehicle
)

place
wheel
s

onto the
four

hubs
. The operator
s

then

place a nut on each wheel stud
and turn the nut a

few times. The
assembly line conveyor then moves the
vehicle
to the next station where the lug nuts are
manually
torqued down. I
n
the past, an operator on each side
of the vehicle
would locate the first tire,
guide the nutrunner into position, torque the
nuts down, move to the second
wheel, guide the nut runner into position, and torque the second group of
nuts. The operator
s

have only

43 seconds to complete this entire operation
.


“The nut runner is heavy, unwieldy
,

and generates a lot of counterforce,”
F
ellows said. “As a result
,

this is a very physically demanding job that is
prone to workplace injuries.
All of the major automobile manufacturers have
tried to automate this job but they have run into some very
significan
t

challenges.

These challenges aris
e from the fact

that the vehicle cannot be
repeatably positioned on the assembly line.



The conveyor moving the vehicle is not accurate enough to position the
vehicle

in

the line of travel axis

the x axis

nor in the axis perpendicular to
the line of trave
l

the y axis

accurately
enough
for a robot to position the
nutrunner on the nuts. But even
if the conveyor was more accurate
, the
wheel
has the potential
to rotate in three different axes.
It

can be turned
slightly to the left or right, tilted
, (
also known

as camber
)
and rotate
d

around
the axles.
All five of these axes of motion must be precisely
known

for

the
robot to position the nutrunner
with

the required

degr
ee of accuracy.
Adding
to the challenge is the fact that the plant produces vehicles with a wid
e range
of wheel types that are intermixed on the production line.


Developing machine vision application


“This application
is

impossible
to automate
unless

the robot
can

reliably

and
repeatably

locate the
nuts
,” Fellows said.

Radix Controls took on the
c
hallenge of developing a machine vision application that could determine
the posit
i
on of the
nuts

in fi
ve different axes within a few seconds as needed
to meet the cycle time requirements. The innovative application relies upon
two

Cognex In
-
Sight
®

5403 vi
sion system
s

to
locate each wheel. Radix
selected In
-
Sight

because it provides a complete
solution

in a modular
package that does not require any additional hardware or other equipment.
The
6
0

x
11
0
x

80

mm

package

of the vision system
eas
il
y fit
s

within t
he
tight confines of the manufacturing plant. The
In
-
Sight
5403 model was
selected because
it offers a resolution of 1600
x

1200 pixels and an
image
acquisition time of 15 frames per second
;
it is

ideally suited
to meet
the high
accuracy and short cycle ti
me requirements of this application.


The vision application relies on Cognex’s unique PatMax
®

pattern matching
technology to quickly locate the wheel in the image. PatMax can be
programmed to recognize any pattern simply by
highlighting

the pattern in
an
image taken by the camera. Radix
enginee
rs programmed PatMax to
recognize each of the wheels used in the plant.
The system has been set up
so it can be easily programmed by plant personnel to
recognize new wheel
types.
The
information backbone
that runs th
e assembly line communicates
with the vision system to
let it know

which type of wheel will be on the next
vehicle and the vision system

load
s

the appropriate program.



Figure 1: Vision
-
guided robots position nutrunners on wheels


Cognex
’s

circle finder
tool is

then used to precisely determine the location
of the center of the axle.
The company’s e
dge tools inspect the feature in the
center of the rim to determine the angle of rotation of the wheel.
When the
first image is taken, a

laser generates a cross
hair on each wheel
. Then the
first laser is turned off
,

a second laser generates another crosshair from a
different angle

and a second image is acquired
.
The e
dge tools are then used
to inspect the crosshairs in each image. The coordinates of the crosshair
s are
passed to a program written by Radix
for the camera

that
uses the
differences between the crosshairs to
calculate
the angles at which the wheel
is turned and tilted.




Figure 2: Center feature in wheel is used to determine angle of rotation


The
sy
stem

then passes this information to the controller of a Fanuc robot.
T
he robot
swivels its wrist to match the angles to which the wheel is tilted
and turned and rotates the nutrunner to match the wheel

s angle of rotation.
Next, it

guides the nutrunner sq
uare onto the lug nuts. The nutrunner is
cycle
d

and tightens the nuts to the proper torque in a few seconds. The robot
then moves to the other wheel on its side of the car and, again
,

guided by the
coordinates and angles provided by the machine vision syst
em, places the
nutrunner onto the lug nuts and tightens the nuts.
The application has been in
operation for 18
months
with greater than 99.6% uptime (including system
errors like missing tires, water on tires, etc.)
.



Figure 3: Close
-
up view of vision
-
gu
ided robot and nutrunner


Calibrating the robot to the vision system


The ability to quickly calibrate the robot to the vision system is important
because of the potential for the vision system to be bumped by equipment
moving in the area.
The operator act
uates the calibration co
mmand on the
vision system
which

determines the
centerline
position of the
wheel

relative
to its own coordinate system and sends the coordinates to the robot
controller. The operator then jogs the robot to
position the nutrunner on
the
wheel

and the system

determines the offset
s

between the robot’s and vision
system’s coordinate systems.
By e
ntering the offsets into the robot control
system
,
the
complete coordinate system

used by

all of

the vision system
s

and
the robot
s in the cell
a
re then synchronized
.
The workcell is fully calibrated
in less than a minute with the custom features on a specialized calibration
target, and completes the automatic dynamic calibration sequence in under 2
seconds per cycle.


Radix Controls provided the v
ision
-
guided robot application as part of a
complete solution including
:

programming
;
custom lighting design
;
integrated robotic communication and robo
t

programming
; and,
full controls
design including safety controls, coordinated installation
,

startup and

systems training for operators, maintenance and engineering.

The key
to
success
fully automating this application

is the coupling of machine vision
and robotics to accurately and repeat
ab
ly guide the robot to the proper
position
,”

Fellows said
.

Automatio
n provides a substantial cost savings
to
the
automobile manufacturer
and
also improves quality by ensuring that the
lugs are repeat
ab
ly tightened to the proper torque.



FOR IMMEDIATE RELEASE

CONTACT:

Annmarie Latta

Gray & Rice Public Relations

(617) 367
-
0
100 x168

alatta
@gr2000.com