Presentation - SEDC Conference 2014

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Early Design Requirements
Development and Assessment for
System Autonomy
Systems Engineering Conference
Washington DC
Jerrel Stracener, SMU PhD
CAPT Daniel P. Burns USNR, SMU PhD Student
Rusty Husar, SPAWAR, SMU PhD Student
3-4 April 2014 Chantilly, VA
Early Design
Requirements (101)
My Strategy for winning
the Cold War:
We Win
They Lose….
Current Politico-Military Requirements
Do This
• Cut Defense Budgets
–
–
–
–
But Still Do This
• Maintain national objectives
– Increased situational awareness
Do more with less
– Meet National CYBER
Reduce Sustainment & Manpower
Challenges & Demands
Use more Systems Autonomy
– Protect commercial shipping
lanes and interests abroad
Move to the Cloud
Who is Moving to the Cloud?
• Intelligence Community
– IC Information Technology Enterprise
– IC Cloud Hosting Environment
• Department of Defense
– Joint Information Environment
– DoD Core Data Centers & DoD Cloud Hosting Environment
• Department of Navy
– OPNAV – Task Force Cloud
– N2/N6 Navy TENCAP R&D functional lead
– ONI – Maritime ISR Enterprise
– NCDOC – Naval Cyber Cloud
Navy is “All-In”
Working Across Interagency Partners to Execute the Movement to the Cloud
Cloud Enabled Common Operating Picture
100011100110011010101010101010011110010010101001010
MIW
FORCEnet
ASW
IBGWN
SUW
Navy Approach for Unmanned Systems
A Maritime and Littoral force that
integrates manned and Unmanned
Systems (US) to increase capability
across the full spectrum of Naval
missions while remaining fiscally
achievable.
- CNO statement during June 2009 UxS CEB
Mission Autonomy
“Recommendation 4: The Assistant Secretary of
the Navy for Research, Development, and
Acquisition (ASN(RD&A)) should mandate that
level of mission autonomy be included as a
required up-front design trade-off in all
unmanned vehicle system development
contracts.”
Committee on Autonomous Vehicles in Support of Naval Operations
Naval Studies Board
Division on Engineering and Physical Sciences
National Research Council of the National Science Academies
Autonomy vs. Automation
• Automation, autonomy, full autonomy –
these terms are not synonymous
• Autonomy is a critical, yet potentially controversial
attribute of unmanned systems
• From the US NAVY CNO
– what is frequently referred to as a “level of autonomy” is
a combination of human interaction and machine automation
– Not fully understanding autonomy has hindered development
of unmanned systems by the Navy
– The degree of machine automation is not as easily categorized
• range of increasingly complex, computer-generated and computerexecuted tasks
Defining Levels of Autonomy
“Review the strategy for future development of autonomy in unmanned systems, including "sense and
avoid" technology. Project the likely timeframe for development of full autonomy."
• Defining Levels of Autonomy (LOA) in a simple,
useable form has proven a difficult task
• No single scale has been found acceptable
• Autonomy – Automation: Often interchanged
• Intuitively, LOA could be characterized by position on a
linear axis with manual operation at one end and full
automation at the other
• Intermediate levels of one scale often seem unrelated to
those of another
• Therefore, we propose that our discussion of
autonomy be broken down into descriptions of human
interaction and system automation
Sheridan Levels of Autonomy
High
Low
10
The computer decides everything, acts autonomously,
ignores the human
9
Informs the human only if it, the computer, decides to
8
Informs the human only if asked, or
7
executes automatically, then necessarily informs the
human, and
6
allows the human a restricted time to veto before
automatic execution, or
5
executes that suggestion if the human approves, or
4
suggests one alternative
3
narrows the selection down to a few, or
2
The computer offers a complete set of decision/action
alternatives, or
1
The computer offers no assistance, human must take all
decisions and actions.
AGILE and Rapid IT Development
Initiatives
• Current AGILE and RAPID Information
Technology (IT) programs drive the
acceleration in the development of unmanned
and autonomous systems and stress
conventional development frameworks
System Autonomy
Human Interaction
Q2
“level of autonomy” is
a combination of human interaction
and machine automation
Q1
Machine Automation
Q3
Q4
“level of autonomy” is
a combination of human interaction
and machine automation
F[SA] = F[MA] + F[HI]
Human Interaction
Levels of System Autonomy (SA)
support or exceed Mission
Operation Needs
MCT
SA
Levels of System Autonomy (SA)
DOES NOT support Mission
Operation Needs
Machine Automation
Human Interaction
System Autonomy treated as a vector
• Scalar component - SA= √(MA^2+HI^2)
• SA represents system capability
• Angular component - Ψ= tan-1[MA/HI]
• Ψ represents technology base
ψ – technology angle
Tele-operation
MCT set to 1
SA
Machine Automation
Android
Use Story for Early Design
Requirements Development
and Assessment for System
Autonomy
Arctic Territorial Claims
Retreating Ice Cap Opens Territorial
Boundary Claims
Establishing Eminent Domain
Nationalizes Natural Resources
Complex System of Underwater Autonomous Systems
Illustrative Concept #1
SEABOX Candidate Large Displacement UUV
as transit and deployment platform deploys
quantity 8 SEADART ocean survey UUVs.
Under development.
•
•
•
Speed - 6 knot, endurance – 45 days,
side scan sonar swath 12 meters
Estimated transit 7 days
Estimated ocean survey – 21 days
SEADART Candidate surveillance,
reconnaissance and data gathering (ISR)
UUVs. Mature proven design in wide use
•
Speed - 5 knot, endurance – 5 days,
side scan sonar swath 4 meters
Complex System of Underwater Autonomous Systems
Illustrative Concept #1
SEAHORSE Candidate Large Displacement
UUV as transit and deployment platform
deploys quantity 48 SEASWARM ocean
survey UUVs. Mature proven design in wide
use
•
•
•
Speed - 10 knot, endurance – 40 days,
side scan sonar swath 8 meters
Estimated transit 4 days
Estimated ocean survey – 22 days
SEASWARM Candidate surveillance,
reconnaissance and data gathering (ISR)
UUVs. Under development
•
•
Speed - 3 knot, endurance – 3/4 days,
side scan sonar swath 4 meters
Develops an underwater collaborative
network to perform ocean survey
Mission Timeline
• Develop time line for each candidate
– Mission phases are very similar to ocean surveys done
be UUVs
• Outline SA assessments used in very early AoA,
CONOPS and design concept phases
Summary
• Autonomous systems are a complex integration of human
intelligence supervising machine automation to adapt to
unforeseen events encountered during operations
• Missions are becoming more complex and spiraling the need for
ever-increasing autonomous systems
• An algorithmic relationship between the two major system
components, human supervisor and unmanned machines, provides
a tradeoff study capability to define requirements and assess
complex architectures during early development phases
• DoD’s significant use of Complex Autonomous systems to provide
– Situational awareness data
– Battegroup coordination
– Mission execution
• Current economic environments creates greater dependencies on
complex adaptive systems to perform ISR and execute missions
?? QUESTIONS ??
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