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Fin Actuated Autonomous Underwater Vehicles
Inspired by nature, our intent is to generate novel bio-inspired systems that can out-perform existing engineered systems in speed, agility and efficiency. We focus on bioinspired actuators (based on fish-fin type structures) to control fluid dynamic artifacts (both in and away from the boundary layer) that will ultimately affect speed, agility, and stealth of air and underwater autonomous vehicles. Many underwater vehicles use propellers: propellers provide high thrust, high drag, and low maneuverability. Vehicles using a fish-tail type system are more maneuverable, have the potential to turn in much shorter and more constrained spaces, to have lower drag, to be quieter, and to be more efficient. Modeling of the fluid/actuator system must yield results both (a) amenable to control-theoretic studies and algorithm design, and (b) accurately representing reality. A simple prototype of such a system with rigid foils (shown here) has been simplistically modeled by assuming only primary fluid effects (e.g., quasistatic lift and drag, and added mass) and ignoring all secondary effects (e.g., wall and surface effects). While this approach may seem prohibitively simplistic, the resulting model is in fact capable of representing the qualitative physical performance in simple steady regimes. Our current work focuses on refining the model and extending it to more aggressive operation such as for flexible foils. MULTIVEHICLE MOVIE GALLERY Videos of the multifish tests done recently with wireless communication are below. All experiments utilize wireless underwater communication. |
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Coordination and Cooperation in Multivehicle Systems
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Schooling in Nature and Engineering
The work in this proposal focuses on a novel development of systems-level biomimetic control-theoretic models and motion control algorithms for embedded, emergent coordinated behavior of multiple organisms. We are addressing the limits of how information transmission in coordinated groups can be effected through local sensing when the dynamics of the individual elements are not homogeneous but are allowed to be nonuniform and are intentionally modified to act as control parameters. The methods used in this work fundamentally integrate techniques and tools from biology and engineering, and the resulting work will have high impact in a broad range of applications. The particular issues addressed in this project are emergent behaviors in schools of fish and coordinated control of autonomous underwater vehicles propelled in the carangiform style of locomotion. We concentrate our efforts on three aspects of information transfer in coordinated control of multi-component systems of interest to both biological and engineering disciplines: traffic rules and emergent behaviors in increasingly heterogeneous groups, the architecture of sensory input, and emergent behaviors from induced heterogeneity. To obtain data for traffic rules used by fish operating under heterogeneous sensing and traffic rules, schooling experiments are being performed using giant danio with different internal states to impose varying sensing rules. Fish trajectories are tracked with cameras, and the data is then extracted for use in derived control theoretic algorithms to be applied to engineered systems. These algorithms will be implemented on a testbed of free swimming remote-controlled robots. Experiments on the robot testbed will be used to validate and refine models and motivate further testing criteria for the schools of fish. |
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Hierarchical Integrated Communication and
Control
The approach taken for controller design is a superposition of spacing control and heading control. The heading control is derived from Kuramoto models of oscillators. When state data is transferred via dynamic communication, a natural discretization occurs. From the control perspective, a study of the resulting discretized dynamics can relate the discretization parameter Δ, delay in data transmission, and stabilizing values of the oscillator coupling gain K. Further, truncated data holds during update intervals can be shown to be more effective than typical zero order hold approaches. From the communication perspective, the discretization parameter Δ can be used to relate optimal network topologies to the broadcast of B bits of data. These optimization results indicate that single hop networks can outperform multi-hop schemes when the amount of data relative to the discretization interval is above a threshold. The performance of our proposed communication and control algorithms will be evaluated not only in simulation, but also in an existing 3D autonomous vehicle testbed at the University of Washington. The facility consists of three autonomous underwater vehicles linked by wireless communication and an instrumented water tank facility. The wireless communication is currently implemented via radio frequency and a vision-based tracking system. In implementation this communication method can be constrained to emulate characteristics of a variety of environments and hardware. |
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Coordination, Steering and Deconfliction for Unmanned Air Vehicles
The relative positions of the vehicles in the group will be specified using an application of spatial density functions. Density functions, which are a type of potential function, can be used to place vehicles in configurations such as linear or planar shapes with given boundary. Further, with density functions the intervehicle spacing can be modulated and time-varying to allow more vehicles in some areas and fewer in others, such as would be desired for greater sensor coverage in some areas. To accommodate realistic aircraft dynamics with angular rate and speed bounds, we are currently applying a version of averaging theory to the dynamics of the aircraft. Specifically, by applying state and time dependent amplitude-modulated sinusoidal control to nonholonomic vehicle models with fixed forward velocity, a class of controllable (but not STLC) systems emerges. |
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Modeling and Control in Mixed Human/Robotic Teams This project is a five-year multi-university research effort aimed at understanding
key aspects of cooperative distributed decision making, coordination, and distributed
control of groups of humans and autonomous machines. A team is composed of psychologists,
engineers, and applied mathematicians in a cross-disciplinary
collaboration to develop models of human relationships in organizational, command, and
social structures and in human-machine interactions in tactical operations. The goal of the
research is to develop new methods to capture, model, represent, and ultimately understand Previous work in this area at the University of Washington has addressed
the dependence and coupling of coordinated control system performance with dynamic network topology. This work has further considered the co-dependence of control objectives and
performance and wireless network capabilities and performance. Specifically we are interested in characterizing limitations on coordinated system capabilities based on networking
capabilities of the system (e.g. line-of-sight requirements, distance-based delay in transmission reception, channel noise effects on packet loss, available bandwidth, quantization
scales) and similarly the restrictions on networking capabilities dictated by the tasks being
performed by the vehicles (e.g. inability to position vehicles to guarantee full connectivity
during broadcast, etc.) The work in this MURI project will focus on the further effects
and constraints imposed by the incorporation of direct human interaction during mission
operation. Particular cases to be studied include perception of delay on error in human
response as a constraint on allowable network delay and therefore on spacing between vehicles in line-of-sight operations, perception of delay as a constraint on bandwidth and data
quantization, and time scale separation and coupling for guaranteed communication and One of the testbeds to be utilized as part of this project is the DSTARS system, a tool for experimenting with and validating guidance, navigation
and control (GNC) algorithms developed for autonomous vehicles. Different simulated and
actual systems can be integrated into the testbed. The integration only requires a software
module to interact with DataHub. The simulation systems which have been used with the
test bed include Insitu HIL FlightSim, CloudCap Piccolo Simulator, MLB BAT Simulator,
Boeing OEP, and Aerofly Pro. DSTARS is currently used by Insitu, UW and Cornell to
integrate and validate cooperative tracking algorithms for UAVs under an AFOSR STTR
Phase II contract. The capability of DSTARS enables testing multi-vehicle algorithms either
with all vehicles represented in simulation or with some actual vehicles operating in the field,
e.g. UAVs, USVs or UUVs. Various mission scenarios can be implemented to task operator
control actions as well as reactions to crisis situations. DSTARS will be utilized in this
project to test algorithms for human-in-the-loop control. Modification of the system to |
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Integrated Control, Networking and Digital Communication The focus of this project is design and analysis of integrated communication networks in service
of coordinated control of multi-vehicle systems. To achieve globally desirable
formation behavior, the controller of each vehicle must respond to the motion and state of others. Each
vehicle is equipped with wireless radio to disseminate vehicle state information. The fundamental
challenge in designing networked control systems is that the tasks of communication and control,
in general, cannot be considered decoupled from each other without loss of optimality. In fact, the
optimal solution can be formulated as a decentralized stochastic problem with information constraints
and imperfect observations and whose solution is known not to be modular. Clearly, some
degree of modularity, even if it introduces sub-optimality, can help find solutions that give insight
into the problem. Because the questions that arise lie at the intersection between communications
and controls research, the components of the project bring together expertise in decentralized control, networking, and signal processing. The
intellectual merit of the project consists of three interdependent theoretical components led respectively
by the co-PIs: (1) nonlinear coordinated control over dynamic graphs, (2) cross-layer optimization of wireless networks, and (3) physical layer solutions to decentralized communication and control.
An overarching experimental component will be used to compare and test how the communication
solutions provided by (2) and (3) perform under identical primitives from (1). This system will first use the existing 3D indoor autonomous underwater vehicle testbed at the University of Washington and later the in progress open water acoustic Seaglider system. |
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Last updated on: Thursday, December 11, 2008 16:04. Send questions or comments to morgansen@aa.washington.edu. |
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The objective of the work in this project is to
design integrated control and communication algorithms that guarantee that a set
of vehicles with differing data capabilities will conform to a specified
spatial distribution. Unlike most coordinated control settings, we are not
only interested in the question of formation control, but also the question
of reliably providing the communication necessary to achieve the
coordination. Each vehicle is equipped with physical devices that provide
local information from sensing and global information from communication.
Sensing devices are assumed to be lower cost in terms of power, computation,
and range of operation, while communication devices are comparatively higher
cost but with more information density and reconfigurability.
While each vehicle is equipped with a communication device, not all vehicles
will be allowed to use these devices due to resource limitations,
environmental constraints such as bandwidth, and/or failure of the device.
Such scenarios are typical of multiple autonomous aircraft in urban settings
or multiple autonomous underwater vehicles in shipyards.
The focus of the work in
this project is to develop coordinated control algorithms for formations of UAVs (Unmanned Air Vehicles) that allow the formation to
track single or multiple targets while preventing collisions. Successful tracking of a single target will
be characterized by the centroid of the group
tracking the position of the target, and tracking of multiple targets will be
characterized by both the centroid of the group
tracking the centroid of the set of targets and the
footprint of the group covering the set of targets. The relative locations of the vehicles
within the group is prespecified using potential
functions, and leader-follower techniques are used to guarantee each vehicle
maintains its specified relative location. Further, to ensure safe operation of the group, deconfliction techniques are being developed to prevent collisions.