1. SIERRA PROJECT
Aerospace Engineering University of Cincinnati
Presenter Liberty Shockley Class of 2019 Mentors Manish Kumar, Ph.D Kelly Cohen, Ph.D
Bryan Brown, Graduate Student
Development of Navigation and Path Planning Algorithms for UAVs for SAR Ops
S TAR S E ARCH
What does it do?
 Moves to the center of the area
 Draws a small star (Radius = 1500)
 Enlarges by 140%
 Rotates by pi/6 radians (30 degrees)
 Draws new star
 Repeats until found or Time Max
Note: after 60 minutes, it returns to
the smallest sized star (Radius = 1500)
and begins enlarging process again2,5
 Concentrates in the middle
 Effectively searches entire area
 Fast and efficient
IMPORTANCE
Who is going to use this?
Firefighters!
 Low-cost
 Automatic, but fast
 Safe
It will save lives and make their jobs easier by completing
missions more efficiently2,7
Why do different paths matter?
A grid path is great for searching an area if all you want to do is
see what’s there, and have a long time to do it. We want to find
something in an area, fast. I explored stars,
because it broadly checks around an area
while focusing on its center, which is the
center of the search area, and the best
guess for where the target will be.
GRID S E ARCH
Given no information, a grid, going back and forth across an area
like a lawnmower is the best way to search an area. However, it
takes 392 minutes search our 10 x 10 area.That’s six and a half
hours! Practical UAVs can’t fly that long, and a person could run a
marathon in that kind of time.
Below are two runs of the Grid Simulation, showing how the
code runs and how it finds the target (Note: Time constraint was
removed for the left figure, to show full capability)
EDU>> Simulation_GRID
The error taken was 90 meters
Time of Flight is 392 minutes
RANDOM S E ARCH
This simulation was run just for fun, to see if a UAV that makes its
own uneducated decisions can still accomplish the mission
Can move North, South, East, or West randomly each iteration
EDU>> Simulation_RANDOM
The error taken was 90 meters
Time of flight is 300 minutes
This run suggests that the UAV
needs some navigational guidance
to optimally search a path. However,
it does get very lucky when the
target position estimate has little error.
CONCLUS IONS
 A grid is good if the UAV had infinite battery life, and we
could search every spot with care
 A random search relies too much on chance and did not show
desirable results
 The star algorithm is the optimal search path of those
chosen, because it focuses in the middle while still
conducting a broad search, with good time results
 The diamond, while similar to the star algorithm, is good, but
not as thorough and does not show any increased accuracy
when the time constraint is removed
FUTURE RE S E ARCH
 Further time analysis
 Algorithm for scope size dependent on the altitude of the
UAV
 Different shift angles5
 Hybrid pattern searches – star and diamond work together
 Fine searches
 Working with FAA Regulations and nearby airports3
R E F E R E N C E S
[ ] All plots created by Liberty Shockley in MATLAB
[1] Image pulled from Google Images
[2] dePalo, Le K; 2005, Maxwell paper,Vol #35
[3] http://knowbeforeyoufly.org/ accessed 20 May 15
RE S ULTS
DIAMOND S E ARCH
The diamond algorithm is almost identical to the star algorithm.
It follows the same process, but of course, it draws a diamond
instead of a star.
As shown in the figures above, there is no focus on the center of
the shape, only the borders. This causes larger gaps between the
area searched, and, in turn, its success rate.
OBJE CTIVE
Discover the UAV optimal flight path to find a missing person
Flight PathsTested: GRID, RANDOM, STAR, DIAMOND
Determined by creating simulations of a general search and
rescue mission for a slow-moving target in an unpopulated area
using one UAV scope.
ME THODOLOGY
DEFINITIONS
Search area 10 km by 10 km area (plot)
Scope How much the camera can see in an instant
Target What the UAV wants to find
TOF Time of Flight of the mission
Cost Function minimizeTOF to find the target
Time Max 150 minutes (life of the UAV)
TARGET
Always begins
between (3000, 3000)
and (7000, 7000)4
UAV SCOPE
The scope moves through the
search paths using a system
of waypoints (blue squares)
generated in MATLAB scripts
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Grid Path Simulation with Ten Second Iterations
EDU>> Simulation_GRID
Found Target!
The error taken was 90 meters
Time of Flight is 141 minutes
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Grid Path Simulation with Ten Second Iterations
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Grid Path Simulation with Ten Second Iterations
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Grid Path Simulation with 10 Second Iterations
Success Rate for 1000 simulations
GRID RANDOM STAR DIAMOND
Time < 1000
minutes 87.8% 17.1% 100.0% 54.8%
Time < 150 minutes 14.7% 9.7% 76.0% 55.4%
Avg Time (minutes) 136 100 60 50
Min Time (minutes) 106 1 5 5
Max Time (minutes) 150 150 150 114
1
EDU>> Simulation_5PTSTAR
Found Target!
The error taken was 90 meters
Time of Flight is 17 minutes
EDU>> Simulation_5PTSTAR
The error taken was 90 meters
Time of Flight is 387 minutes
EDU>> Simulation_5PTSTAR
Found Target!
The error taken was 90 meters
Time of Flight is 77 minutes
[4] Canadian Journal of Administrative Sciences, Sept 2007
[5] European Journal of Operational Research, May 2005
[6] EE BrighamYoung University
[7] Sean R. Semper, September 2011
EDU>> Simulation_DIAMOND
Found Target!
The error taken was 90 meters
Time of Flight is 84 minutesEDU>> Simulation_DIAMOND
The error taken was 90 meters
Time of Flight is 16 minutes
EDU>> Simulation_DIAMOND
The error taken was 90 meters
Time of Flight is 1000 minutes