US States Activities with UAVs

UAS Activities in States

[001]~ Alabama (AL) [002]~ Alaska (AK) [003]~ Arizona (AZ)

[004]~ Arkansas (AR) [005]~ California (CA) [006]~ Colorado (CO)

[007]~ Connecticut (CT) [008]~ DC (DC) [009]~ Delaware (DE)

[010]~ Florida (FL) [011]~ Georgia (GA) [012]~ Hawaii (HI)

[013]~ Idaho (ID) [014]~ Illinois (IL) [015]~ Indiana (IN)

[016]~ Iowa (IA) [017]~ Kansas (KS) [018]~ Kentucky (KY)

[019]~ Louisiana (LA) [020]~ Maine (ME) [021]~ Maryland (MD)

[022]~ Massachusetts (MA) [023]~ Michigan (MI) [024]~ Minnesota (MN)

[025]~ Mississippi (MS) [026]~ Missouri (MO) [027]~ Montana (MT)

[028]~ Nebraska (NE) [029]~ Nevada (NV) [030]~ New Hampshire (NH)

[031]~ New Jersey (NJ) [032]~ New Mexico (NM) [033]~ North Carolina (NC)

[034]~ North Dakota (ND) [035]~ New York (NY) [036]~ Ohio (OH)

[037]~ Oklahoma (OK) [038]~ Oregon (OR) [039]~ Pennsylvania (PA)

[040]~ Rhode Island (RI) [041]~ South Carolina (SC) [042]~ South Dakota (SD)

[043]~ Tennessee (TN) [044]~ Texas (TX) [045]~ Utah (UT)

[046]~ Vermount (VT) [047]~ Virginia (VA) [048]~ Washington (WA)

[049]~ WestVirginia (WV) [050]~ Wisconsin (WI) [051]~ Wyoming (WY)

«UAVs in different countries «Content

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Alabama (AL)

The University of South Alabama

catch: ~[content] ~[Alaska] !

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Alaska (AK)

Mariner UAV Deploys to Alaska

catch: ~[content] ~[Arizona]!

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Arizona (AZ)

Predator UAV crashes in Arizona
UAV 2006

catch: ~[content] ~[Arkansas]!

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Arkansas (AR)

Plan Sharing: Showcasing Coordinated UAV Formation Flight

catch: ~[content] ~[California]

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California (CA)

NASA's Dryden Flight Center

Sandia
ξ Remote Sensing

Cubic
ξ realistic live combat training systems for military forces as well as virtual training systems, force modernization, education and engineering & technical support

L-3 Communication Titan
ξ Command, Control, Communications, Computer, Intelligence, Surveillance and Reconnaissance (C4ISR)

GA
ξ conceived in 1955 at San Diego, California for the purpose of harnessing the power of nuclear technologies for the benefit of mankind

MITRE

Northrop Grumman
ξ Northrop Grumman Corporation is a global defense company headquartered in Los Angeles, California
ξ provides products, services and solutions in systems integration, defense electronics, information technology, advanced aircraft, shipbuilding and space technology
ξ nation's sole designer, builder and refueler of nuclear-powered aircraft carriers and one of only two companies capable of designing and building nuclear-powered submarines

Northrop Grumman Unmanned
ξ Navy Fire Scout Vertical Takeoff and Landing Tactical Unmanned Air Vehicle System (VTUAV) system
ξ Fire Scout Class IV UAV for Army, FCS
ξ Global Hawk
ξ Hunter
ξ KillerBee
ξ UCAS (X-47A and X-47B) Unmanned Combat Air System

Photon
ξ provides physics-based modeling, simulation & analysis software, tools and services for national security and DoD customers, a wholly owned subsidiary of Raytheon

SAIC
ξ a systems, solutions and technical services company

ROS
ξ design and manufacturing of reliable, high-tech equipment and systems for the nuclear, offshore industry

21CSI
ξ intelligent agents process and analyze large amounts of data quickly, providing real-time, actionable knowledge to decision makers in high-stress environments

Titan Systems Corporation
ξ contributes to C4ISR systems that support agencies and organizations of DoD and evolving Department of Homeland Security

Autonomous Underwater Vehicle Project
ξ underwater AUV project by San Diego State University

Teledyne
ξ provider of sophisticated electronic components, instruments & communications products
ξ including defense electronics, data acquisition & communications equipment for airlines and business aircraft
ξ monitoring and control instruments for industrial and environmental applications and components
ξ subsystems for wireless and satellite communications

National Center for Geographic Information & Analysis (NCGIA)
ξ Los Angeles-Long Beach ports handle a huge volume of container traffic, roughly 10-15% of the nation’s overseas trade
ξ a ship carrying suspicious cargo could be “sniffed” while still at a distance from the port

SRI's Artificial Intelligence Center
ξ Bioinformatics Research Group at SRI International
DARPA Centibots
ξ aimed at developing new technology to support the coordinated deployment of as many as 100 robots for missions such as urban surveillance

NASA JPL Robotics, Los Angeles, Pasadena
ξ Urbie - Urban robot

UCLA, Los Angeles
ξ Internet in the Sky project, funded by The Office of Naval Research
ξ Center for Embedded Networked Sensing
ξ 1) ENS software and platform systems that exploit actuation and multi-tier sensor assets to properly guide sampling for a wide range of applications
ξ 2) ENS software and platforms that enable high spatiotemporal resolution monitoring
ξ 3) Localization and actuated sensing methods that exceed the performance of prior fixed sensor systems
ξ 4) fault detection and calibration methods that exploit actuation for diverse sensor systems and applications

University of California, Irvine
ξ An Architecture-Based Approach to Self -Adaptive
ξ A group key management in MANETS overseen by UAVs
ξ National Fuel Cell Research Center

UCSD San Diego
ξ Scripps Institute
ξ Air-Sea Interaction Research
ξ The Center for Wireless Communications (CWC) of the University of California at San Diego

Stanford University
ξ Energy Efficient Link Assesment in Wireless Sensor Networks
ξ Stanford University/Research sponsored by the Office of Naval Research
ξ Biomimesis: to mimic life, to imitate biological systems
ξ collaboration among robotics and physiology researchers at Stanford, U.C. Berkeley, Harvard and Johns Hopkins Universities
ξ search with UAV, several research papers available

Berkeley
ξ Tracking vehicles with a UAV-delivered sensor network

Naval Postgraduate School, Monterey

UCSC, Santa Cruz
ξ Embedded Systems & UAV Lab

Center for Robotics and Embedded Systems (CRES), University of Southern California

CALTECH /Robotics

catch: ~[content] of US States Activities!

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Colorado (CO)

Ad Hoc UAV Ground Network (AUGNet)
ξ AUGNet is a communication concept that combines unmanned aerial vehicles (UAVs) with ad hoc wireless (aka mesh) networking
ξ A Full-Scale Ad Hoc Networked UAV Test Bed

catch: ~[content] of US States Activities!

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Connecticut (CT)

catch: ~[content] of US States Activities!

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DC (DC)

catch: ~[content] of US States Activities!

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Delaware (DE)

catch: ~[content] of US States Activities!

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Florida (FL)

General Dynamics Ordnance and Tactical Systems
ξ As certified by the Office of the United States Secretary of Defense,
ξ General Dynamics OTS is the world's only manufacturer of MK80 Series Bomb Bodies
ξ that conforms to the U.S. Dept. of Defense's approved technical data packages.
ξ In this capacity, General Dynamics OTS is the U.S. Government's restricted source of supplyfor all MK80 Series General Purpose Bomb Bodies,
ξ both tactical and inert training rounds.MK82, 500 lbs. Tactical, (U.S. Air Force & Navy)
ξ BDU-50, 500 lbs. Inert, (U.S. Air Force)
ξ BDU-45, 500 lbs. Inert, with spotting charge, (U.S. Navy)
ξ MK83, 1,000 lbs. Tactical & Inert, (U.S. Air Force & Navy)
ξ MK84-4 2,000 lbs. Tactical, (U.S. Air Force)
ξ MK84-6, 2,000 lbs. Tactical, (U.S. Navy)
ξ BDU-56, 2,000 lbs. Inert, (U.S. Air Force and Navy)

The University of Florida : research and technologies, enabling unprecedented capabilities for Micro Air Vehicles (MAVs) and small Unmanned Air Vehicles (UAVs)

catch: ~[content] of US States Activities!

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Georgia (GA)

The University of Georgia

Georgia Tech Research Institute (GTRI)
ξ use the search engine

catch: ~[content] of US States Activities!

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Hawaii (HI)

catch: ~[content] of US States Activities!

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Idaho (ID)

catch: ~[content] of US States Activities!

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Illinois (IL)

The University of Illinois
ξ Multi - Vehicle Testbed for Network and Control Applications

catch: ~[content] of US States Activities!

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Indiana (IN)

University of Notre Dame
The University of Indiana

catch: ~[content] of US States Activities!

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Iowa (IA)

OIWA State University of Science and Technology
ξ Air Force Office of Scientific Research funding
ξ Virtual Reality Applications technology developed that allows a single operator to monitor & control multiple UAVs

catch: ~[content] of US States Activities!

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Kansas (KS)

»KalScott Engineering
ξ Turnkey, end-to-end payload flight test services
ξ Surrogate UAV and UAV payload risk reduction

catch: ~[content] of US States Activities!

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Kentucky (KY)

The University of Kentucky

catch: ~[content] of US States Activities!

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Louisiana (LA)

catch: ~[content] of US States Activities!

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Maine (ME)

catch: ~[content] of US States Activities!

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Maryland (MD)

Institute for Systems Research

catch: ~[content] of US States Activities!

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Massachusetts (MA)

Optical Alchemy
ξ a developer and manufacturer of ultra-lightweight, high performance stabilized sensor systems for unmanned vehicles

MIT, Boston
ξ UAVs as Tactical Wingmen
ξ MIT LegLab

Harvard

Clark University
ξ a systems engineering approach for successful UAV mission design and execution

catch: ~[content] of US States Activities!

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Michigan (MI)

The University of Michigan

catch: ~[content] of US States Activities!

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Minnesota (MN)

The University of Minnesota - Center for Distributed Robotics
ξ Ranger - sponsored in part by NSF, U.S. Army, DARPA, Microsoft, INEEL, and U.S. Air Force

catch: ~[content] of US States Activities!

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Mississippi (MS)

Aurora Flight Science

catch: ~[content] of US States Activities!

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Missouri (MO)

catch: ~[content] of US States Activities!

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Montana (MT)

catch: ~[content] of US States Activities!

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Nebraska (NE)

Avionics Databus Solutions
ξ modules for ARINC

catch: ~[content] of US States Activities!

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Nevada (NV)

Nellis Air Force Base

Mission
ξ to work with the warfighters and identify problems that can be solved using innovative UAV/Remotely Piloted Aircraft (RPA) solutions
ξ is based at Creech Air Force Base, Nev., and is assigned to Air Combat Command's USAF Warfare Center
ξ UAVB team works with industry, academia and National/Service labs to find solutions to warfighter problems
ξ demonstrate those solutions, make an objective decision on their military utility and then work to transition the initiative to the warfighter
ξ we pursue high return initiatives with the goal of conducting each initiative with minimal investment and
ξ maximum impact to warfighter's UAV/RPA organizations, doctrine, training and future requirements and acquisitions

Intelligence, Surveillance, and Reconnaissance (ISR) Division
ξ analyzes existing and emerging technologies for integration into Joint UAV systems
ξ with effects-based emphasis on ISR operations, to include radar, video, laser designation and other ISR systems
ξ manages evolutionary and revolutionary initiatives demonstrating enhanced UAV ISR capabilities
ξ each initiative is focused on moving successfully demonstrated technology from the battlelab to the warfighter
ξ serves as an Advisory group to ACC and Air Staff on UAV ISR issues

Combat Applications Division
ξ analyzes existing and emerging technologies for integration into Joint UAV systems
ξ with effects-based emphasis on kill chain operations, to include weaponization, sensor delivery, and electronic warfare (EW) systems
ξ manages evolutionary and revolutionary initiatives to demonstrate enhanced UAV attack and targeting capabilities
ξ a detailed roadmap to move successful initiatives from the battlelab to acquisition or operational status
ξ these initiatives are then transitioned to UAVs in a combat environment in support of the warfighter
ξ serves as an Advisory group to ACC and Air Staff on UAV weapon-related issues

Integration Division
ξ analyzes existing and emerging technologies for integration into Joint UAV systems with emphasis on service and joint applicability
ξ manages evolutionary and revolutionary initiatives to demonstrate enhanced UAV capabilities
ξ a detailed roadmap to move successful initiatives from the battlelab to acquisition or operational status
ξ these initiatives are then transitioned to UAVs in support of compelling warfighter needs
ξ serves as an Advisory group to ACC and Air Staff on joint or service UAV-related issues

To submit an idea or proposal to the Unmanned Aerial Vehicle Battlelab, send the proposal to UAVB.IDEAS@nellis.af.mil

UAV Target Upgrades
ξ Installation of new urban operation complex targets and unmanned aerial vehicle targets for the Nevada Test and Training Range
ξ Target upgrades on Leach Lake Tactical Range at the National Training Center, Fort Irwin, Calif.
ξ Expeditionary Readiness Training course expansion at the Nevada Test and Training Range

Urban operations complex and UAV targets
ξ a weapons of mass destruction storage area,
ξ simulated buildings, anti-aircraft artillery and surface-to-air missile sites, bunkers, caves and vehicles
ξ located about 35 miles southeast of Tonopah, Nev
ξ be on withdrawn land and are not accessible by the public

UAV targets
ξ would be built in a narrow canyon
ξ would consist of tents, huts and buildings, anti-aircraft weapons site
ξ military and civilian target vehicles and a weapons storage building

USAF Air Warfare Battlelab (AEFB)
ξ formally known as the Air Expeditionary Force Battlelab (AEFB)
ξ is one of seven Air Force battlelabs established by the chief of staff of the Air Force
ξ in July 1997, the AEF Battlelab stood up as one of six Air Force battlelabs, designed to identify innovation ideas and measure how well those ideas subject matter experts
ξ in 2002, a seventh battlelab, the Air Mobility Battlelab (AMB), was activated to specifically focus on the Air Mobility mission contribute to the mission of the Air Force
ξ each battlelab has a specific focus area staffed by dedicated military and civilian subject matter experts
ξ in 2002, a seventh battlelab, the Air Mobility Battlelab (AMB), was activated to specifically focus on the Air Mobility mission
ξ located at Mountain Home AFB, Idaho, the mission of the AEF Battlelab was to identify and rapidly prove the worth of innovative ideas for the employment of Air Expeditionary Forces for Global Engagement throughout the entire spectrum of warfare
ξ these ideas focused on six phases of AEF operations: readiness, employment, redeployment, deployment, sustainment and reconstitution
ξ in February of 2003, the AEF Battlelab was realigned under the USAF Warfare Center, Nellis AFB, NV,
ξ to better match its operational and testing functions giving the AEF Battlelab a direct window into the AWFC and its subordinate units
ξ realignment coupled with the standup of the Air Mobility Battlelab drove the need to reorganize the AEF Battlelab
ξ as of 1 Oct, 2004, the AEF Battlelab became the Air Warfare Battlelab, commanded by Col Ernest L. Parrott
ξ focusing on enhancing the deployabilty, sustainability, survivability and lethality of
ξ contingency Air Expeditionary Forces for Global Engagement

Mission
ξ The mission of the AWB is to improve expeditionary combat capability through innovation
ξ To complete this mission, the AWB focuses on ideas that are able to:
ξ Reduce deployment response time
ξ Reduce deployment support structure
ξ Increase combat capability and effectiveness

ξ After demonstration of an initiative, the AWB makes a recommendation to senior Air Force leaders and the Air Force acquisition community.
ξ The recommendations help determine whether or not the Air Force should procure the items, move forward on an idea, or wait for future technology improvements.
ξ The AWB can accept ideas from any source.
ξ We accept ideas from an airman or sergeant on the flight line, from civilians and from members of other military services.
ξ Contractors interested in gaining an entry point into the Air Force modernization process can present ideas thorough our Broad Agency Announcement in Commerce Business Daily.
ξ Once an idea passes our screening and initial research, we validate and outbrief the concept in about eighteen months
ξ The advantages for both the military and industry are tremendous.
ξ For industry, we provide analysis of the idea based on the expertise of subject area specialists and
ξ identify potential customers while guaranteeing that all ideas selected for evaluation
ξ will be visible to senior Air Force leaders and the acquisition community.
ξ Any proprietary information provided to the AWB will be safeguarded.
ξ From the military standpoint, ideas worked by the AWB directly impact the Air Force and joint operations,
ξ improve efficiency and effectiveness for the warfighter, and introduce new technologies, tactics, procedures,
ξ architecture and/or doctrine into the Air Force.
ξ Ideas submitted to the AWB should address improvements within any of the six phases of Air Expeditionary Force operations:
1) readiness
2) deployment
3) employment
4) sustainment
5) redeployment and/or
6) reconstitution

ξ Should an idea fit better in one of the other six Air Force battlelabs, we will forward it to the appropriate location.

Mission of the Battlelab Integration Division
ξ The Battlelab Integration Division (AF/XIIV - Pentagon) was established to
ξ Rapidly identify and prove the worth of innovative ideas which improve the ability of the Air Force
ξ to execute its core competencies and Joint Warfighting
ξ The seven battlelabs include:
1) the Air Warfare Battlelab at Mountain Home AFB, Idaho
2) the Force Protection Battlelab at Lackland AFB, Texas
3) the Unmanned Aerial Vehicle Battlelab at Indian Springs, Nevada
4) the Command and Control Battlelab at Hurlburt Field, Florida
5) the Information Warfare Battlelab at Lackland AFB, Texas
6) the Space Battlelab at Schriever AFB, Colorado
7) the Air Mobility Battlelab at Fort Dix, New Jersey
Each battlelab contains a small and focused group of subject matter experts thinking, planning and leading innovation efforts.

Personnel and Resources of AWB
ξ 30 military and civilian personnel, augmented with temporary duty experts or contractor support
ξ a limited budget, for day-to-day operations and demonstration execution, is provided in yearly operations and maintenance dollars

Organization
ξ AWB is aligned under Air Combat Command's USAF Warfare Center at Nellis AFB, Nev.
ξ it conducts the USAF's most advanced weapons and tactics training, including Red Flag and the USAF Weapons School
ξ it also conducts operational testing and tactics development and evaluation for combat weapons systems,
ξ as well as supports combat search and rescue and unmanned aerial vehicle reconnaissance operations worldwide

Point of Contact
ξ 99th Air Base Wing Public Affairs, 4430 Grissom Ave., Ste 107, Nellis AFB, Nev., 89191; DSN 682-2750, commercial (702) 652-2750,
ξ 99abw.pa@nellis.af.mil.

Creech Air Force Base
ξ Creech AFB is located about 45 miles northwest of Nellis AFB
ξ August 1951 the base became an auxiliary field
ξ July 1952 it transferred from Air Training Command to the Air Research and Development Command, reporting to the Air Force Special Weapons Center in Albuquerque, N.M.
ξ 1961 the base transferred to the Tactical Air Command
ξ it officially became Indian Springs Air Force Auxiliary Field during the 1980s
ξ following the inactivation of Tactical Air Command In 1992, the base became a component of Air Combat Command
ξ On June 20, 2005, Indian Springs Air Force Auxiliary Field officially changed its name to Creech Air Force Base in honor of Gen. Wilbur L. “Bill” Creech.
ξ it is home to the MQ-1 Predator unmanned aerial vehicle which flies daily in Afghanistan and Iraq
ξ it is also home to the Unmanned Aerial Vehicle Battlelab whose mission is to work with the warfighter and identify problems that can be solved using innovative UAV solutions

Joint UAV Center of Excellence (CEO)
ξ COE is designed to improve interoperability and use, and examines the use of sensors and intelligence collection assets to meet joint operational requirements of U.S. forces in any combat environment
ξ COE is an operationally focused organization concentrating on UAV systems technology, joint concepts, training, tactics, and procedural solutions to the warfighters’ needs
ξ The Joint COE stood up at Creech AFB in 1995.
ξ The Army will initially lead the Joint UAV COE with the Air Force as deputy
ξ These positions will rotate among the four military services
ξ Once established, the center has representatives from all four military services and other DOD and non-DOD agencies.

Sierra Nevada Corporation

catch: ~[content] of US States Activities!

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New Hampshire (NH)

catch: ~[content] of US States Activities!

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New Jersey (NJ)

catch: ~[content] of US States Activities!

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New Mexico (NM)

The University of New Mexico
Sandia
Los Alamos

catch: ~[content] of US States Activities!

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New York (NY)

Columbia University

The University of Fordham

The University of Rochester

catch: ~[content] of US States Activities!

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North Carolina (NC)

catch: ~[content] of US States Activities!

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North Dakota (ND)

catch: ~[content] of US States Activities!

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Ohio (OH)

Case Western Reserve University

CAISR
ξ CAISR integrates technologies such as Fuzzy Logic, Expert Systems and Neural Networks to create flexible systems

WPAB

catch: ~[content] of US States Activities!

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Oklahoma (OK)

catch: ~[content] of US States Activities!

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Oregon (OR)

Cloud Cap Technology
ξ provides software and hardware solutions for the Unmanned Aerial Vehicle (UAV) market

catch: ~[content] of US States Activities!

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Pennsylvania (PA)

Carnegie Mellon

Drexel University

Biorobotics Lab, Carnegie Mellon University

The University of Lehigh - Micro Air Vehicle Project

catch: ~[content] of US States Activities!

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Rhode Island (RI)

catch: ~[content] of US States Activities!

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South Carolina (SC)

catch: ~[content] of US States Activities!

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South Dakota (SD)

catch: ~[content] of US States Activities!

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Tennessee (TN)

Teledyne Advanced Manufacturing Divisions

Oak Ridge National Laboratory

The University of Vanderbilt
1. The system should learn broad categories of objects by learning from experience
ξ general classes of objects that may naturally be encountered in an environment
ξ such as trees, sidewalks, grass, brick walls, doors, windows, etc i.e. not specific, unique, object identification
2. The system should be able to explain how it is making its decision, as well as be able to justify (i.e. explain) any particular decision
3. The system should be able to detect that new or novel elements are in a visual scene
ξ this detection of novelty should trigger new learning
ξ the system will ask to be taught about the new objects, thus achieving self-directed learning
4. When appropriate, after making the general class identification, the system may employ other object recognition algorithms to identify a specific object
ξ such as but not limited to David Lowe’s SIFT algorithm and neural networks
ξ this general to specific identification is believed to relate to some biological approaches
5. Eventually, the system should be able to work in an unsupervised learning mode
ξ Objects it identifies with very high confidence it will label and add to its training database
ξ Objects it identifies with lesser confidence it records for later confirmation or correction by the human “teacher”
ξ Novel objects are recorded for subsequence teaching by the human “teacher”
ξ As the data set increases, memory consolidation will be used
Characteristic 1 is ongoing with constant changes in feature vectors and the addition of learned objects

catch: ~[content] of US States Activities!

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Texas (TX)

NASA Johnson Space Center

The University of Texas, Austin / Robotics
University of Texas Robotics Project

catch: ~[content] of US States Activities!

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Utah (UT)

catch: ~[content] of US States Activities!

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Vermount (VT)

catch: ~[content] of US States Activities!

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Virginia (VA)

US Navy Begins Development of VTUAV

Aurora

Battlespace
ξ offers UAV pilots, sensor operators, maintenance personnel and mission planners
ξ program management, system engineering, in-house digital services, contracting via GSA and NAVSEA Seaport-e

catch: ~[content] of US States Activities!

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Washington (WA)

Boeing

University of Washington

catch: ~[content] of US States Activities!

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West Virginia (WV)

Aurora

catch: ~[content] of US States Activities!

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Wisconsin (WI)

catch: ~[content] of US States Activities!

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Wyoming (WY)

catch: ~[content] of US States Activities!

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Small & Smart Inc reserves rights to change this document without any notice
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[001]~ Alabama (AL)	[002]~ Alaska (AK)	[003]~ Arizona (AZ)
[004]~ Arkansas (AR)	[005]~ California (CA)	[006]~ Colorado (CO)
[007]~ Connecticut (CT)	[008]~ DC (DC)	[009]~ Delaware (DE)
[010]~ Florida (FL)	[011]~ Georgia (GA)	[012]~ Hawaii (HI)
[013]~ Idaho (ID)	[014]~ Illinois (IL)	[015]~ Indiana (IN)
[016]~ Iowa (IA)	[017]~ Kansas (KS)	[018]~ Kentucky (KY)
[019]~ Louisiana (LA)	[020]~ Maine (ME)	[021]~ Maryland (MD)
[022]~ Massachusetts (MA)	[023]~ Michigan (MI)	[024]~ Minnesota (MN)
[025]~ Mississippi (MS)	[026]~ Missouri (MO)	[027]~ Montana (MT)
[028]~ Nebraska (NE)	[029]~ Nevada (NV)	[030]~ New Hampshire (NH)
[031]~ New Jersey (NJ)	[032]~ New Mexico (NM)	[033]~ North Carolina (NC)
[034]~ North Dakota (ND)	[035]~ New York (NY)	[036]~ Ohio (OH)
[037]~ Oklahoma (OK)	[038]~ Oregon (OR)	[039]~ Pennsylvania (PA)
[040]~ Rhode Island (RI)	[041]~ South Carolina (SC)	[042]~ South Dakota (SD)
[043]~ Tennessee (TN)	[044]~ Texas (TX)	[045]~ Utah (UT)
[046]~ Vermount (VT)	[047]~ Virginia (VA)	[048]~ Washington (WA)
[049]~ WestVirginia (WV)	[050]~ Wisconsin (WI)	[051]~ Wyoming (WY)