posted on 2021-10-01, 10:37authored byJames Riordan, Manduhu Manduhu, Julie Black, Alexander Dow, Gerard Dooly, Santiago Matalonga
The solution to mitigating risks associated with
beyond Visual Line of Sight (BVLOS) operations of Unmanned
Aerial System (UAS) generally focuses on the use of advanced
Unmanned Traffic Management (UTM) systems. However, this
solution does not take into account other uncooperative objects
in the airspace. A more robust approach is to have UTM
integrations coupled with onboard machine vision which is tied
to automated collision avoidance systems. Future BVLOS
regulations in urban situations may require robust embedded
software that is capable of detecting air collision hazards in real time at near and far ranges as uncooperative small aircraft and
other unpredictable small objects with fast-changing and
unscheduled trajectories pose significant hazards to UAS. This
work presents the concept and initial prototyping of a Digital
Twin to evaluate the capability of UAS mounted LiDAR to
detect small-object air collision risks. A Digital Twin of the Port
of Hamburg is augmented with typical port and harbour aerial
hazards such as birds, drones, helicopters, and low flying
aircraft. The use case scenarios are created in Maya and Unity,
with Optix ray tracing of typical LiDAR imaging configurations
used to replicate the cause and effect relationship between
different LiDAR specifications and their response to small flying
objects. Our results demonstrate the inhomogeneous point
clouds generated at different spatial-temporal parts of the
LiDAR scanning cycle and field of view. These results confirm
the challenges of detecting small uncooperative objects by
LiDAR.
Funding
Observation of limbal stem cell niche using in vivo confocal microscope