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Unmanned Mobile Sensor Net - Ben Snively

Unmanned Mobile Sensor Net - Ben Snively. Unmanned Underwater Gliders Survey and extensions to work from: COOPERATIVE CONTROL OF COLLECTIVE MOTION FOR OCEAN SAMPLING WITH AUTONOMOUS VEHICLES; Derek A. Paley. Problem / Motivation. Manual Ocean Sampling labor, resource, and time intensive.

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Unmanned Mobile Sensor Net - Ben Snively

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  1. Unmanned Mobile Sensor Net- Ben Snively Unmanned Underwater Gliders Survey and extensions to work from: COOPERATIVE CONTROL OF COLLECTIVE MOTION FOR OCEAN SAMPLING WITH AUTONOMOUS VEHICLES; Derek A. Paley

  2. Problem / Motivation • Manual Ocean Sampling labor, resource, and time intensive. • Objectives/Sensing • Gradient Climbing • Feature Tracking • Boundary Monitoring • Perimeter Surveillance • Mapping • Autonomous Distributed Agents both reduce over costs, improve accuracy, and reduce latency for critical data.

  3. Marine Sensing Equipment • NOAA Manual Ocean Survey • Ships with complex survey equipment • Performs in both shallow and deep water collections. • AUV – Autonomous Underwater Vehicle • Shallow water survey using GPS and Satellite communication

  4. Sensor Network Details • Sink  Satellite Communication • Agents/Sensors  Mobile Gliders • Every Glider in Range of Sink / GPS • Satellite only communicate with satellite when at surface • Cannot control movement at surface (just floats) – has control only when submerged. • GCCS – Glider Coordinated Control System • GCCS steers groups/sets of gliders • Gliders controlled remotely • No Agenda/Beliefs/Planning GCCS

  5. Overview • “Apply a cooperative control methodology to control a fleet of autonomous underwater gliders. Underwater gliders soar through the water on a pair of fixed wings, collecting valuable oceanographic data for weeks at a time. We describe the Glider Coordinated Control System (GCCS), which steers multiple gliders to a set of coordinated trajectories. The GCCS automatically controlled up to six gliders continuously for over three weeks in a 800 km2 region in California’s Monterey Bay in August 2006. The GCCS enables oceanographers to specify and adapt glider sampling patterns with minimal human intervention.”(Paley)

  6. Mobile Sensors and Sink

  7. Domain Definition Domain: Outer Search Area

  8. Domain Example <domain> <rectangle> <x> <units>deg</units> <value>-122.3817</value> </x> <y> <units>deg</units> <value>36.9765</value> </y> <a> <units>met</units> <value>20000</value> </a> <b> <units>met</units> <value>10000</value> </b> <ori> <units>deg</units> <value>137</value> </ori> </rectangle> </domain> Center Point Longitude Center Point Longitude Width Height Angle

  9. Search Paths Tracks  Search Paths

  10. Tracks Example <tracks> <superellipse> <name>track1</name> <x> <units>deg</units> <value>-122.2713</value> </x> <y> <units>deg</units> <value>36.8950</value> </y> <a> <units>met</units> <value>10000</value> </a> <b> <units>met</units> <value>6667</value> </b> <ori> <units>deg</units> <value>47</value> </ori> <p> <value>3</value> </p> </superellipse> </tracks> Shape/Name Center Point Width Height

  11. Glider Groups Glider Tree: Entities, which paths to use, Comm model.

  12. Glider Groups Example <group> <group> <phase> <value>0</value> <units>pct</units> </phase> <glider> <mnf>w</mnf> <!-- Manufacturer --> <sn>7</sn> <!-- Serian Number --> <model>e</model> <track>track1</track> <direction>1</direction> <phase> <!-- Curve Phase --> <value>0</value> <units>pct</units> </phase> <control> sellipse control </control> </glider> <glider> . . . </glider> </group> </group>

  13. YAES Simulations • Simulations Performed • 4 Boundary Gliders rotating same direction • 4 Boundary and 6 Interior Sensors, All positioned in ideal/planned position. • 4 Boundary and 6 Interior Gliders, all starting from hub location • Actual software from research done in Matlab. • Software allows for both simulated and real tests

  14. Background Information on Simulation • XML Configurations drive simulation setup and context. • Much like the Real system, xml configuration files define gliders, tracks, and other system configuration. (The XML Schema was slightly modified in order to simplify configuration) • Main Simulation class allows for selection of which simulation to perform. • JAXB used to parse XML Input / Java 1.6 SDK/Runtime(JAXB = Java API for XML Binding)

  15. Simulation 1: Boundary Test Sink Communication at surface 4 Boundary Gliders

  16. Simulation 2 : Interior Gliders 6 Interior Gliders covering Area 3 Groups, 2 Gliders in each. (Gliders communicate w/ Sink at Surface)

  17. Simulation 3 : Boundary and Interior Gliders Sink Communication at surface 4 Boundary Gliders 6 Interior Gliders Flow adds error (off track) when Glider is at surface

  18. Extending Network • Current Limitations • Central control/Planning • Planning communication only done at surface (when gliders are floating and have no control – drift) • Limited Inter-glider communication. • Extending Sensor network principals to the system • Gliders become agents with beliefs, agendas, and planning • Sensor communication models and MDP principals (Specifically Partially Observable - MDP) • This is critical due to the fluxations and inconsistencies in the robot control.

  19. Glider Agents • Key Difference • Glider has Agenda, Goal, and isn’t pure input/sensing device. • Glider communicate with each other • Goal: • Cover area (and plan) that hasnot been covered by other agents. • Inform others plan/area covered. • Single Sink transmitter could be at surface, to bridge under-water to satellite gap.

  20. Planning / Decision Process • PO-MDP (Partially Observable Mark-ov Decision Process. • Outcome from Glider commands uncertain.Policy mapping between States / Actions  Perceived new State. • Routing issues isn’t applicable due to every glider having access to the sink (via satellite). • Routing issues could be introduced in a more complex system where messages between gliders and to sink are transmitted.

  21. Questions? • Questions / Comments? • Thank you.

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