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Transcript of Systems Engineering Conference Washington DC Jerrel Stracener, SMU PhD CAPT Daniel P. Burns USNR,...
Systems Engineering Conference Washington DC
Jerrel Stracener, SMU PhDCAPT Daniel P. Burns USNR, SMU PhD Student
Rusty Husar, SPAWAR, SMU PhD Student
3-4 April 2014 Chantilly, VA
Early Design Requirements Development and Assessment for
System Autonomy
Early Design Requirements (101)
My Strategy for winning the Cold War:
We Win
They Lose….
Current Politico-Military Requirements
Do This
• Cut Defense Budgets
– Do more with less– Reduce Sustainment & Manpower– Use more Systems Autonomy – Move to the Cloud
But Still Do This
• Maintain national objectives– Increased situational awareness– Meet National CYBER
Challenges & Demands– Protect commercial shipping
lanes and interests abroad
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
ASW
MIW
SUW
IBGWN
Cloud Enabled Common Operating Picture
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FORCEnet
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 OperationsNaval Studies Board
Division on Engineering and Physical SciencesNational 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 computer-executed tasks
Defining Levels of 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
“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."
Sheridan Levels of AutonomyHigh
10 The computer decides everything, acts autonomously, ignores the human
9 Informs the human only if it, the computer, decides to8 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, or4 suggests one alternative3 narrows the selection down to a few, or
2 The computer offers a complete set of decision/action alternatives, or
Low1 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
Human Interaction
Machine Automation
Q1Q2
Q4Q3
“level of autonomy” is a combination of human interaction
and machine automation
System Autonomy
Human Interaction
Machine Automation
Levels of System Autonomy (SA) support or exceed Mission
Operation Needs
Levels of System Autonomy (SA) DOES NOT support Mission
Operation Needs
MCT
SA
F[SA] = F[MA] + F[HI]
“level of autonomy” is a combination of human interaction
and machine automation
Human Interaction
Machine Automation
Tele-operation
Android
MCT set to 1
ψ – technology angle
SA
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
Use Story for Early Design Requirements Development and Assessment for System
Autonomy
Arctic Territorial ClaimsRetreating 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.
SEADART Candidate surveillance, reconnaissance and data gathering (ISR) UUVs. Mature proven design in wide use
• Speed - 6 knot, endurance – 45 days, side scan sonar swath 12 meters
• Estimated transit 7 days• Estimated ocean survey – 21 days
• 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
SEASWARM Candidate surveillance, reconnaissance and data gathering (ISR) UUVs. Under development
• Speed - 10 knot, endurance – 40 days, side scan sonar swath 8 meters
• Estimated transit 4 days• Estimated ocean survey – 22 days
• 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 ??