Booth Id:
ROBO027
Category:
Robotics and Intelligent Machines
Year:
2018
Finalist Names:
Boyea, Samantha (School: Greenwich Junior-Senior High School)
Abstract:
Small scale farms are responsible for producing 70% of food worldwide. Of this
food produced a large amount is stored in structures called silos. Silos are
agricultural containment vessels often cylindrical in shape that are mainly used for
the storage of grain and silage. Inspections are performed in order to ensure the
integrity, stability, and safety of the structure. However, these inspections require
human risk due low oxygen conditions and the presence of dangerous gases such
as nitrogen dioxide within the silo. In order to remedy this a drone or UAV could
be employed to enter and autonomously inspect the silo when it is unsafe for a
farmer to do so. After determining the UAVs ability to both locate and detect
damage within the silo while the inspector is a significant distance away, the next
goal proposed is to improve the accessibility through use of a semi-autonomous
function. The first step in constructing a UAS capable of accomplishing this
objective would be to, using computer software, pre-program flight paths based on
inputs of diameter and height of the silo to be inspected. In order to accomplish
this objective a quadcopter was designed and constructed that utilizes both a
Navio 2 flight controller and Raspberry Pi. The combination of these devices
allows for instructions regarding flight paths to be sent between the ground station
and UAV.
Awards Won:
Second Award of $2,000
China Association for Science and Technology (CAST): Award of $1,200