56 / 84
We are on the threshold of the next
industrial revolution where machine
vision will be the major game-
changer, as intelligent vision can
now even incorporate deep-learning
algorithms. These enable cooperative
work environments between humans
and machines or machine vision that
is part of critical-control feedback
loops. And these algorithms are most
efficiently executed on heterogeneous
system architectures.
Machine vision moving to
“sense-plan-act’”
In early applications, machine vision
was used with frame grabbers and
Digital Signal Processors (DSP).
Today, with the development of
reasonably priced high performance
sensors - one of three major enablers
for the new robotics revolution - we
can see examples of applications in
which recognition is not simply just
(Brushless DC motors) are enabler
number three. The combination of
all these three enablers, i.e., their
enhanced technologies, makes vision
systems and robotics so revolutionary
today.
New intelligent vision
systems
So let’s take a closer look at the vision
part of this industrial revolution.
Human eyes are connected via nerves
to the ‘visual cortex’ in our brain. Out
of our five senses, the visual cortex
accounts for the largest section of the
brain. Machine vision systems, such
as the IVS-70 (see figure 2) based
on parallel computing offered by
heterogeneous SoCs, are the enablers
of Artificial Visual Cortex for machine
vision systems. Their eyes are lenses
and optical sensors. Their optic nerves
to the Artificial Visual Cortex are
high speed connections between the
Mission-critical machine vision in an insecure IoT world
Intelligent machine vision cameras are driven by heterogeneous computing architectures
Dr. Lars Asplund and Dr. Fredrik Bruhn, Unibap AB
a means of identifying well-known
schematics in a ‘sense-compare-
decide’ manner. Today, robotics
– starting with simple stationary
systems right up to autonomous
vehicles - are transforming towards
more sophisticated ‘sense-plan-act’
behavior. In this respect, a vision
system is the most powerful eye
of a robot which informs it of its
position and its environment. And the
computing power of Heterogeneous
System Architecture-based embedded
processors like the AMD G-series SoC
provides the brain that understands
and interprets the environment. The
second enabler is the processor which
delivers the required high performance
with moderate power consumption.
The final part of a smart robot is
the act component. Acting robots
require high power density in the
batteries and high efficiency motors.
So state-of-the-art batteries and BLDC
56 l New-Tech Magazine Europe