UNMANNED SYSTEMS RESEARCH Aeronautics & Astronautics

University of Washington

Dr. Juris Vagners

Professor Emeritus

February 26, 2010

AUVSI Cascade Chapter Meeting

Seattle, Washington

PRESENTATION OUTLINE

• Faculty Research Labs

• A brief history

• Faculty laboratory activity summaries and selected research projects

Controls & Systems Faculty Research Labs

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Kristi A. MorgansenAssociate Professorhttp://www.aa.washington.edu/research/ndcl

Mehran MesbahiAssociate Professorhttp://dssl.aa.washington.edu/

Juris VagnersProfessor Emeritushttp://www.aa.washington.edu/research/afsl

WIND TUNNEL TESTING, UWAL

Aerosonde, the first UAV across the Atlantic

The launch: St John’s, Newfoundland

North Atlantic Crossing: The route and weather

Transatlantic route of Aerosonde Laima 20-21 August 1998plotted on the Meteosat infrared image

taken at 23:30 UTC 20 August3270 km in 26 hr 45 min on 4 kg fuel

position at 23:30 UTC

LandedSouth Uist Island,

Hebrides12:44 UTC 21 Aug

LaunchedBell Island,

Newfoundland09:59 UTC 20 Aug

arrows show winds logged enroute; 2 1 /2 barbs in this example indicate 25 kt.

LAIMA in the Museum of Flight

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Modeling Estimation

Control

Heterogeneous coordinated control with limited communication

Bioinspired system modeling for coordinated control

Integrated communication and control

Modeling and control of shape-actuated immersed mechanical systems

Nonlinear Dynamics and Control Labhttp://vger.aa.washington.edu

Kristi A. Morgansen

Cognitive dynamics models for human-in-the-loop systems

Coordinated control with communication

for UUVs

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Modeling and control of fin-actuated underwater vehicles

Tail locomotion and pectoral fin maneuverability

NSF CAREERUW RRFNSF BE (with J. Parrish and D. Grunbaum, UW)

Goals

•Agile maneuverability•Analytical control theoretic models of immersed shape-actuated devices•Underwater localization•Nonlinear control•Coordinated control

Challenges

•Small size•Coriolis effects•Unmodeled or approximated fluid dynamics elements•Communication and sensing limitations

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UW Fin-Actuated UUV - Control

•Results extendable to many fluid-body models•Rigorous mathematics with simple implementation•Experimental stabilization robustºIncorporate vortex dynamics and unsteady effects into modelºOptimal motion generationºExtension to flexible actuators

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Coordinated Control with Limited Communication

Goals

•Control in the presence of communication and sensing constraints•Control over networks•Deconfliction•Schooling/swarming group behavior

Challenges

•Managing time delays in local control•Definition of attention•Allocation of resources•Construction of stabilizing controllers•Modeling

NSF CAREERAFOSR (with Prof. Tara Javidi, UCSD)AFOSR (with The Insitu Group, Inc.)The Boeing Company

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Hierarchical Integrated Communication and Control

NSF CAREERAFOSR (with Prof. Tara Javidi, UCSD)AFOSR (with The Insitu Group, Inc.)

Goals

•Coordinated tracking of objects or boundaries•Non-separated design of communication and control algorithms•Data quantization•Cooperative task management•Control over networks

Challenges

•Managing time delays in local control•Allocation of resources•Construction of stabilizing controllers•Modeling for both communication and control

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Bioinspired Coordinated Control

•Models of social aggregations

•Effects of heterogeneity (levels of hunger, familiarity)

•Relation to engineered systems

•Application to fishery management, population modeling

NSF BE (with J. Parrish and D. Grunbaum, UW)

Murdock Trust

Goals

Challenges

•Tracking of objects•Data fusion•Model representation

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Cognitive Dynamics for Human-in-the-Loop

Challenges

•Model representation•Heterogeneity•Information flow•Levels of autonomy

Goals

•Coordinated control for heterogeneous multivehicle system with human interaction•Cognitive models and social psychology•Dynamics and control

AFOSR MURI (with J. Baillieul (BU), F. Bullo (UCSB), D. Castanon (BU), J. Cohen (Princeton), P. Holmes (Princeton), N. Leonard (Princeton), D. Prentice (Prentice), J. Vagners (UW))

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Identification and Influence in Networks

Coordination over randomly evolved networks

Decentralized computation and estimation

Autonomous networks with foreign inputs

Informed design for controllability and security of networks

Distributed Space Systems Labhttp://dssl.aa.washington.edu

Mehran Mesbahi

Adaptable swarms

Network identification

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Spacecraft Formation Flying

Distributed Space Systems Labhttp://dssl.aa.washington.edu

Mehran Mesbahi

Spacecraft Attitude Control

Formation Initialization of Microsatellites

Space Interferometry Mission Reorientation in multiple attitude constraints

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Decentralized UAV De-confliction

Distributed Space Systems Labhttp://dssl.aa.washington.edu

Mehran Mesbahi

Planar Collective UAV Coordination UAV path planning &

Collision Avoidance

Limited communication

Can perform under turn-rate constraints and limit sensing capability

Can guarantee collision free and reach destination

Formation flying

Leader-Followers on Unicycle model UAV

Using navigation function

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Dynamic Mission Management

General UAV GN&C Work

Path Planning and Collision Avoidance

General USV Work

Autonomous Flight Systems Laboratoryhttp://www.aa.washington.edu/research/afsl

Juris Vagners

To conduct research that

advances technologies relevant to unmanned systems.

Human in the Loop Architectures

Coordinated Searching Using Autonomous Agents

Washington Technology CenterWashington Space Grant ConsortiumAir Force Office of Scientific ResearchBoeing/InsituNorthwind Marine

Goals

•Increase autonomy of group of agents involved in a search mission.•Guarantee detection of target in search domain.•Develop control laws so agents act in coordinated fashion.

Challenges

•Heterogeneous team with different capabilities and constraints.•Environment may be complex and/or dynamic.•Algorithm scalability and inter-vehicle communication.

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•Target locations probabilistically modeled using occupancy based maps.•Search strategy based on non-linear optimization and Voronoi partitioning.

Coordinated Searching Using Autonomous Agents

Environment

Occupancy based map Single agent patrolling a New York harbor

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•Validate algorithms in simulation, in Boeing Vehicle Swarm Technology (VSTL) lab, and in flight test.

Coordinated Searching Using Autonomous Agents

Flight test in single engine aircraft over Puget Sound

Flight test using quadrotor UAVs in

Boeing VSTL

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Human-in-the-Loop Control Architectures

Goals

•Develop a system for rapid verification and validation of strategic, autonomous algorithms.•Investigate interactions between human and automated algorithms.

Challenges

•Logistics and high overhead for simple tests.•Rules and regulations.•Non-deterministic human behavior.

Washington Technology CenterAFOSR

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Dynamic Mission Management and Path Planning

Goals

•Perform dynamic task assignment for large number of autonomous agents.•Provide feasible paths which allow agents to accomplish tasks.•Replan according to rapidly changing environment and/or conditions.

•Heterogeneous agents means varying capabilities and constraints.•Actions which benefit individual agents may not benefit team.•Environmental constraints.

Challenges

DARPAAFOSRNorthwind MarineWash. Technology Center

Dynamic Mission Management and Path Planning

• Distributed control of multiple, heterogeneous vehicles

• Provides a solution at any time, based on evolutionary computation techniques

• Continuous task/path replanning based on market strategies

• Operates in uncertain dynamic environments (weather, pop-ups, damage, new objectives)

• Complex performance trade-offs

• Collision avoidance

• Vehicle capabilities can be explicit

• Handles loss of vehicles

• Timing constraints can be explicit

• Seamless integration of operator inputs

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Dynamic Mission Management and Path Planning

Evolution-Based Cooperative Planning Systems (ECoPS)

Elliot Bay mission Agents adapt plan to accommodate changing environment

Risk Assessment Tool for UAS Operations

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Goals•User-friendly tool for modeling the risk of UAS team operations•Direct users where to find needed info•Wed-based & downloadable versions•Promote risk-based approach to UAS regulation & policy Challenges

•Wide variety of UAS operations•Diverse areas overflown (disparate population profiles)•Accurately model air traffic create tool to predict traffic in specific area•Limited data for validation

“Acceptable system safety studies must include a hazard analysis, risk assessment, and other appropriate documentation,” -FAA

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The next demonstration

http://www.aerovelco.com/

THANK YOU!

QUESTIONS?