Page 17 - EngineerIt February 2021

AUTOMATION AND CONTROL

Transportation storage is being utilised. Currently, the only way to capture this
The panacea of autonomous driving is the addition of a low information using traditional methods is by using multiple
cost LIDAR system to complement the suite of instruments sensors, which itself has resolution limits while adding
that currently measure the surroundings of a vehicle. LIDAR significant cost to manufacturing. Being able to capture a whole
signals allow the autonomous system to gauge the detailed crop’s growth in granular detail over time provides important
surface features (thereby object-identifying) that radar cannot data and can inform on cultivation practices, both in real time
and cut through weather obstructions much better than a and for future crops. LIDAR can also help optimise the
traditional vision system. movement of automated machinery in harvesting crops.

Automation
Knowing the physical structure in precise detail adds
tremendous value to robotics, which can more accurately and
appropriately handle objects of various sizes and geometries.
This can be extrapolated to any manufacturing or warehouse
context that involves repetitive handling or sorting. Having this
additional information can also allow for the relaxation of
otherwise unnecessarily tight tolerances in manufacturing,
saving costs in production and quality control.

Figure 7: A car detecting features of proximal objects at night,
allowing for the safe operation of the vehicle.

Safety
Outfitting what were traditionally simple “Is there something
in front of me?” sensors with LIDAR systems can give the
benefit of knowing how and when to respond in safety
situations. A robotic arm that handles heavy objects will be
able to respond more keenly when a person-like object
enters its path as opposed to an object that it was designed
to handle.

Agriculture
Simple sensors have been used for years to detect things like
Figure 9: Damage and defects can be detected before bottling
the level of grain in a silo, the state of crops, fuel level, and so where it often is not practical to set up a large vision system
on. What these methods often do not capture is the deeper (which is more often used after the bottles are filled and
packaged). This is especially helpful when the bottles are
context, like how the shape of the mound that the grain makes
visually difficult to distinguish from one another.
when poured into the silo and where it is measured (highest,
lowest, mean, or arbitrary point) can affect how efficiently the The previously discussed applications are ones that are
currently being or have already been developed. As is always
the case in human endeavours, it is impossible to know what
other creative and useful ways people will come up with to use
technology such as LIDAR. If you have a product or system that
may be able to leverage the benefits of LIDAR, Analog Devices
has the expertise to help you along the journey from conception
through to creation, to make that idea reality. n

For additional information contact Conrad Coetzee,
Altron Arrow 083 746 2616

About the author
Tony Pirc has a BSc. in electrical engineering, as well as minors in
computer engineering, physics and mathematics from California
State University, Chico. He has a background in industrial automation
in a manufacturing environment. He supports precision amplifiers at
Figure 8: The plowing of a field with subsequent real-time Analog Devices and is an all-round, fun-loving guy. He can be
terrain mapping—insensitive to lighting conditions due to the reached at tony.pirc@analog.com
nature of LIDAR.

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