Tech Briefs Magazine - August 2023 - 18

Machine Vision
sticker indicating that it has passed inspection,
can be performed by simple,
2D camera-based systems at a lower
price point.
The global machine vision market
grew by 10.7 percent between 2021 and
2022 to reach a value of $12 billion, according
to MarketsandMarkets, and is
projected to reach $17.2 billion by 2027.
Major factors driving the adoption of
machine vision in cobot systems include:
the increasing affordability of machine
vision
hardware; usability
enhancements;
and the incorporation of artificial
intelligence. These improvements compound
to improve performance, make
new cobot applications possible, and reduce
the TCO (total cost of ownership)
on machine vision projects.
So, what are the main considerations
to keep in mind when choosing a machine
vision system for a cobot-based
application?
1. Determine the Need for Machine Vision
First things first, are you sure that your
application requires machine vision?
Could the application be performed
using traditional sensors or fixturing?
Some cobots, for example, have builtin
user-friendly palletizing wizards that
can easily pick up parts placed in a grid
pattern on a peg board, which would
not require vision at all. Similarly, simple
sorting and detection applications that
don't require high precision, could be
performed using traditional sensors.
Nevertheless, a significant number of
tasks require some sort of machine vision
system. These include applications
involving object recognition, variable
object locations, quality inspection tasks,
and safety.
2. Location, Inspection, or Safety?
Before you purchase a cobot arm
with built-in vision, make sure that it is
the right vision solution for your application.
Cobots that provide seamless
integration with a wide range of vision
solutions from entry-level to advanced
are a real plus here; broad compatibility
provides more flexibility and helps to
futureproof the initial cobot investment.
Most vision-based applications fall into
one of three subdomains: location (including
path planning), inspection, and
safety. For part location applications, it's
important that the vision system is capable
of accurate object recognition and
pose estimation.
In quality inspection roles, the system
should be able to detect minute defects.
Universal Robots certifies numerous vision cameras to integrate seamlessly with UR cobots through
the UR+ platform. At DCL Logistics, a 3PL fulfillment center in California, the company has deployed
a UR10e cobot equipped with a Datalogic vision camera. Once a product is picked, the SKU
is verified by the camera that sends a " pass " or " fail " command to the cobot. If the product picked
is incorrect, the UR10e places the product in a reject bin. (Image: Universal Robots)
This requires high-resolution cameras
and advanced image processing software.
For safety applications, such as detecting
when a human has approached and/
or entered the cobot's workspace, a machine
vision system will require real-time
processing capabilities, robust object detection,
and tracking functionality.
3. Consider Your Lighting
Lighting
strongly influences image
quality and, as a result, makes a major
impact on the performance of vision systems.
Some vision systems need consistent,
high-contrast lighting conditions.
Many machine vision systems come with
their own illumination components to
address this aspect.
New England-based Humatics has developed a radio frequency-based system for high speed, advanced
cobot-powered applications that require microlocation and fast data transfer. Here, a pair
of UR10e and UR16e cobots from Universal Robots perform assembly tasks on an engine that's in
motion - no machine vision required. (Image: Humatics)
18
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Meanwhile, other machine vision solutions
can cope with variable lighting conditions.
Changes in ambient light levels
over the course of a day might throw
some vision systems, but not others. Even
a change in the type of light bulb used in
a factory, like switching from fluorescent
to LED bulb use, can cause some vision
systems to fail.
4. Select a 2D or 3D Camera
Often, 2D robotic vision works well
across a wide range of simple applicaTech
Briefs, August 2023

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Tech Briefs Magazine - August 2023

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