Xplomo Hacking for Defense 2017

Standoff IED Detection Using UAVs
Week 1: Original Focus
Hardware - A small, portable drone:
● that uses different sensors...

103
Interviews
19
Government
Affiliated
12
Image
Processing
Experts
54 Armed
Forces
Personnel18
Industry
Affiliated
PLOMO

Yicheng An Weihan Zhang Robert André
Borochok
Marko Jakovljevic
M.S. Computer
Vision & Machine
Learning
M.S. Business M.S....

The Journey
PLOMO
Hardware Software

Our Opening Hypotheses
It’s all about the
Hardware
Multi-Functional Tool to
Replace Human
Detects All Types of IEDs
PLOMO

Who’s our Beneficiary? … Everyone!
PLOMO

Rock Bottom
PLOMO

PLOMO
Our problem scope is
far too wide.

We Need to Truly Understand the Problem
PLOMO

“Infantrymen are the most
vulnerable to IED
attacks...they are trained to
detect IEDs, but rely mainly
on visual cues.”
- ...

Focusing on Our Primary Beneficiary
PRIMARY:
DISMOUNTED
INFANTRY
Most vulnerable to
attack
Relies on visual cues
(potholes...

Week 3: Mission Model Canvas
Value Proposition
Replace infantrymens’
capabilities to detect IEDs
A drone system
System to ...

Let’s build a counter-
IED drone for ground
infantry...
PLOMO

...Or not.
“We already use surveillance
drones…why would we need
another one?”
- Operational Commander
PLOMO

Let’s Modify Existing Hardware!
Build a Drone Add Sensors to Existing
Drones
PIVOT
PLOMO

Pivot to Sensor Improvements
PLOMO
Hypothesis:
Sensors added to
drones like Raven will
increase situational
awareness and ...

Pivot to Sensor Improvements
PLOMO
Hypothesis:
Sensors added to
drones like Raven will
increase situational
awareness and ...

Pivot to Sensor Improvements
PLOMO
Hypothesis:
Sensors added to
drones like Raven will
increase situational
awareness and ...

Hardware is Clearly not the Issue
PLOMO

“My analysts spend hours
staring at a screen to pick up
anomalies. We still miss
things from time to time.”
- Intelligence...

Getting out of the building
PLOMO
Camp Pendleton (San Diego)

Because of the near
infinite number of
ways an IED can be
hidden, we limit our
initial product to
pothole detection.
PLOMO

Week 5: Mission Model Canvas
23
Value Proposition
Augment replace
warfighters’ capabilities
to detect IEDs via
software
Dr...

Software is What’s Really Needed!
Drone Hardware “Analyst in the hand”
PIVOT
PLOMO

We Have Found Xplomo’s Calling
PLOMO

Our MVP and Beneficiary
Needs Match.
So Let’s Start Identifying
Partners.
PLOMO

So Who Do We Need to Work With?
PLOMO

So Who Do We Need to Work With?
PLOMO
XPLOMO

Week 6: Mission Model Canvas
Key Partners
JIDO J8/J6
Image Processing
Experts
Mission Achievement
- Algorithm that success...

In the rush to develop a
working product,
you’ve got to
Fail Fast, Move Quick
PLOMO

Feature Detection Works…. ...Until It Doesn’t
PLOMO
...
Xplomo’s Experimental Results

PLOMO
Academic Articles and 1 Paper Later...

Feature Detection
Anomaly Detection
Machine Learning
PLOMO
“Analyst in the
hand”
Successful Detection
of Well-Defined
Poth...

Week 8: Mission Model Canvas
Key Activities
Implement image
processing methods:
● Anomaly detection -
CFAR
● Machine learn...

Final Minimum Viable Product
“Analyst-in-the-hand” Operator
Any Aerial Platform
PLOMO

Internal Readiness Level
PLOMO
Current product is an initial
iteration of an algorithm that we
will continue to improve.
I...

Moving Forward
Buried IEDs
VBIED
Week 1 Week 10
H4D
Military
GIS Output
Dual
use
Agriculture
Forestry
Road maintenance
Bui...

Thank You
JIDO
Wayne A. Stanbery
W. Richards Thissell
James McGuyer
Industry Mentor
Kevin Ray
Robert Medve
Special Contrib...

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