Abstract
To enable safe and efficient Unmanned Aircraft
Systems (UAS) operations at low altitudes, it is necessary to
conduct airspace management and operations for UAS traffic.
This study focuses on deterministic clustering-based drone
routing, with specific emphasis on the trade-off between
horizontal and vertical travel costs. The routing problem is
simplified to a 2D problem that we solve at several altitude
candidates. Altitude candidates were generated based on clustered
static obstacles in low urban airspace. Fast-Marching algorithm is
performed to generate the shortest path at each altitude candidate.
The optimal altitude is determined by weighing the vertical cost
for ascent and descent over the horizontal cruising cost at certain
altitude. Experiments are conducted to choose proper number of
clusters and weight given to building height in the clustering
procedure, and different shortest path algorithms are compared.
Larger scale of Unmanned Aerial Vehicles (UAV) missions are
simulated, based on which we analyze the relationship between
optimal travel altitude and shortest cruise path, and estimate the
UAV cost function.
Systems (UAS) operations at low altitudes, it is necessary to
conduct airspace management and operations for UAS traffic.
This study focuses on deterministic clustering-based drone
routing, with specific emphasis on the trade-off between
horizontal and vertical travel costs. The routing problem is
simplified to a 2D problem that we solve at several altitude
candidates. Altitude candidates were generated based on clustered
static obstacles in low urban airspace. Fast-Marching algorithm is
performed to generate the shortest path at each altitude candidate.
The optimal altitude is determined by weighing the vertical cost
for ascent and descent over the horizontal cruising cost at certain
altitude. Experiments are conducted to choose proper number of
clusters and weight given to building height in the clustering
procedure, and different shortest path algorithms are compared.
Larger scale of Unmanned Aerial Vehicles (UAV) missions are
simulated, based on which we analyze the relationship between
optimal travel altitude and shortest cruise path, and estimate the
UAV cost function.
| Original language | English |
|---|---|
| Publication status | Published - 2020 |
| Event | International Conference on Research in Air Transportation - virtual Duration: 15 Sept 2020 → … |
Conference
| Conference | International Conference on Research in Air Transportation |
|---|---|
| Period | 15/09/20 → … |
Keywords
- UAV path planning
- UAV cost function
- Fast Marching
- A star