DISCOVERY ARTICLES
AGBOT:
SENIOR DESIGN ROBOTICS
TEAM TAKES TOP PRIZE WITH
AUTONOMOUS HARVESTER
The Virginia Tech agBOT team
clinched first place in the third annual
2018 agBOT Challenge at Gerrish Farms
in Rockville, Indiana, earning a top prize
of $30,000.
The national event, hosted by Gerrish
Farms and airBridge LLC, was broken
into two separate challenges – weed and
feed and harvesting – with university and
industry teams competing head-to-head
for $100,000 in prizes.
Virginia Tech’s team won the
watermelon harvesting challenge by
creating an autonomous system that
could locate, identify, sort, and harvest
ripe watermelons in a field. Teams
were scored in mechanics, software,
innovativeness of their solution, and
execution of their solution.
Two separate teams were formed to
tackle the competition challenges. A
mechanical engineering senior design
team was tasked to design and build
a harvester, while a second special
studies team was responsible for the
autonomous vehicle that towed the
harvester. The latter was composed of
volunteer mechanical, electrical, and
computer engineering undergraduates
and computer science students.
As team lead for both teams, Hongxu
“Howard” Guo, a double major in
mechanical and electrical engineering,
coordinated the work of 14 people.
With the tow vehicle, Guo and
his special studies group used
computer vision and machine learning
technologies that allowed the vehicle
to locate watermelons. When no melon
was in sight, the vehicle used way-point
navigation to find its way through the
fields. When a watermelon was spotted,
the machine’s cameras guided it toward
the fruit. Once there, the harvester
determined whether or not the melon
was ripe.
The process humans have used for
centuries to determine if a watermelon
is ripe is to slap it and listen for a deep,
hollow sound. This sound has a particular
frequency range, which the team made
into a mathematical model to develop
their automated system.
“We placed a microphone under
the unit and angled it to the bottom
of the melon where it captures the
reverberations from the slapper,” said
Guo. “If the audio analysis indicates a
sound ratio above a particular threshold,
what we call the sub-band short-time
energy ratio, then the watermelon is
ripe and harvested. If not, it is left on
the ground.”
As the vehicle rolls past melons, they
are channeled into a funnel where the
slapper hits the melons and the sound
is analyzed; melons that meet the
frequency for ripeness are scooped up
into the machine’s storage unit. A linear
actuator relays how much current is used
to lift the scoop and this provides a size
and weight estimate for the melon.
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