safety features, and the plowing strategy, as well as a brief
future commercialization blueprint for their vehicle. In 2017,
the President of the local ARCS Foundation chapter, Barb
Goergen, gave a short presentation on the function and
support by their STEM-based scholarship organization for
the Autonomous Snowplow Competition.
On Friday of the competition week, the teams attend
the Final Qualifying Review. This process involves stringent
testing and verification of each vehicle to ensure that it
meets all of the competition requirements, including size,
control, and safety. During Saturday and Sunday of the
competition week, all qualified vehicles participate in the
actual snowplowing portions of the competition.
In each dynamic snowplowing event, the teams are
presented with additional challenges including obstacle
avoidance. Colorful poles are placed throughout the
snowfield that the robots must be programmed to avoid.
The most recent competition featured two fixed posts: one
inside the path representing a parking meter, and one
outside of the snow path representing a tree trunk. If any
part of a vehicle hits any of the obstacles, a deduction is
made to the vehicle’s final score.
A new obstacle that was introduced in the 2017
competition was a moving stop sign, which the teams had
to prepare for by stopping when the sign was introduced at
any time on the course. The moving stop sign was attached
to a pole and controlled from outside the field, and was
presented for a short amount of time at a random point in
the course. This meant that the robot could not plan for
the obstruction beforehand and had to be able to recognize
it wherever the sign appeared — a necessary function for a
robot in the real world that may be coming in contact with
unexpected obstacles such as people or cars.
When the stop sign appeared, the vehicles were
required to make a full stop — determined by no vehicle
wheels turning — in front of the sign and keep still until the
sign was removed, without touching the sign at any point.
If any part of the vehicle hit the stop sign, the team would
lose points accordingly.
A newer element of the Autonomous Snowplow
Competition (also introduced at the 2017 event) involved
more cooperation between the teams and interaction
between the robots. The new event — dubbed the
Collaborative Operational Challenge — was organized last
year by Snowplow committee member, Dr. Demoz Gebre-Egziabher from the University of Minnesota-Twin Cities. The
event places two separate autonomous vehicles in a
snowfield together, encouraging them to work with one
another to quickly and accurately clear the snow. The
vehicles must also avoid hitting one another, although some
spectators cheered for the robots to tackle each other in a
more “battle bots”-esque scenario. Four robots competed in
this challenge in 2017, and this event is expected to expand
in the 2018 competition.
Every year, students introduce new and innovative
technology allowing their robots to guide themselves
through the different challenges
presented by the snowfields. The
2017 competition included teams
using laser navigation sensors; many
of them utilized wheel encoders
and inertial measurement units; and
several used image-processing
systems for the local visual field or
ultra-wide band radio beacons.
One ingenious team simply
placed a magnetic track around the
field before they began the run,
which allowed them to sense the
boundaries of the snowfield so that
their robot could accurately clear
The team that used ultra-wide
band radios performed admirably,
experiencing 10 cm accuracies or
better. Only one team used a
differential GPS system, although
many used a stand-alone GPS in
their vehicle’s navigation programs.
Another important design
element that the teams must
consider is the method that their
vehicles will use to actually plow the
30 SERVO 01.2018
Dunwoody College of Technology’s Wendigo.