James D. Paduano Eric Feron Presented to the ACGSC, Salt Lake City March 2, 2005

Transition of UAV Technologies

from MIT Aeronautics &

Astronauticsto

Nascent Technology Corporation

James D. Paduano Eric Feron

Presented to the ACGSC, Salt Lake City

March 2, 2005

Aeronautics &AstronauticsNASCENT

TECHNOLOGY

04/22/23 Copyright Nascent Technology Corporation © 2005

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MOTIVATION – MIT UAV TECH OPPORTUNITIES

• MIT HAS CONTRIBUTED TO SEVERAL PROGRAMS ON UAV COORDINATION AND CONTROL– Software Enabled Control (DARPA)– Autonomous Integrated Network of Systems (AINS – ONR)– Mixed-Initiative Control of Autonomous Teams (MICA – DARPA)– Precision Autonomous Landing Adaptive Control Experiment (PALACE –

US Army, NASA Ames)

– Faculty participating: John Deyst (Draper collaborations) Eric Feron (LIDS)Jon How (formerly Stanford) Jim Paduano (through NTC)

• FLIGHT DEMONSTRATIONS USING MIT AUTONOMOUS MINIATURE HELICOPTER– Aggressive Maneuvering– MILP-Based Flight Control– Multi-Vehicle Coordination and Associated Optimization Methods

• MANY SBIR/STTR OPPORTUNITIES TO COMMERCIALIZE

Aeronautics &Astronautics


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NASCENT TECHNOLOGY CORPORATION

• NTC began commercializing MIT Technologies in 2001– Autonomous Highly Maneuverable Miniature Helicopter– Tools for Multi-vehicle Coordination– Flight Test Services

• Small, but Growing Base of SBIR, STTR and Aerospace Customers– SBIR: SOCOM, NSWC, MDA, DARPA– STTR: ONR (AINS Program)– Other:

• Lockheed Martin Systems Integration – Owego • TechnoSciences, Incorporated• Oregon Graduate Institute• MIT (flight test support)

• Three full-time, Three part-time employees



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AHMMH-1MIT Designed, NTC Built Flight System

• Seven copies built to date (MIT, LMSI, AFRL)

• API created to enable interface with various ground stations (TCP/IP/CORBA, AMUST-D, MIT Multi-vehicle, NTC)

• Upgraded for long range, endurance, and higher lift– Collaborative requirements

definition with ETGI, other potential customers

Know-how to re-create aggressive helicopters has migrated from MIT students to NTC employees



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Route Monitor triggers automated route replanning when a UAV route is jeopardized by threats.

Fuel Guardian monitors each UAV fuel usage and warns the operator of potentially dangerous low fuel situations.

Flight Management • Supports up to 16 UAVs – Sensor

workload limited• Control of UAVs Flight Mode

(Route, Loiter, Direct-To-Home)• Automated Onboard Route

Planning • Speed and Altitude Adjustments

Sensor Management• Controls for Sensor Pointing (Auto, Location, and Fixed Forward)• Sensor Coverage History• Video Display Window

Lockheed Martin Systems Integration - Owego

LMSI Proposed MMH/VTUAV/SonoUAV Team Demo


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Router/Switch

InteroperableTCDL Mux/Demux

ARC210 Radios

FLIR Processor

• Embedded Computer• Reduced Workload Command and Control• Integrated Digital Map

RFARFAARC210 Radios

smUAV Video

smUAV RadiosmUAVComms

Sensor Console

VTUAV Surrogate – Nascent TechnologyAHMMH-1

TUAV Surrogate - Nascent Technology/Cornell and ACR

Demonstrates migration of MMH manned/unmanned airborne system architecture with VTUAV/TUAV Surrogates

802.11

Dotted elements are currently under integration on base MMH program

Huey Avionics Testbed MMH Surrogate


LMSI 3-Vehicle Demonstration 17 August 2004ACR ‘Silver Fox’ and NTC AHMMH-1 as TUAV/VTUAV Surrogates


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Other Activities

• Flight demonstration of visibility-minimization guidance algorithms (for MIT)

– Vehicle performed an on-line computed path plan based on virtual urban map, reducing visibility to defined point

• ONR-STTR Two-vehicle demonstration of deceptive area search

– Flight test complete 20 November 2004 • Tactical Tomahawk Weapon Control System (TTWCS)

operator interface– Imbedded algorithms to optimally place missiles– Help Navy to take advantage of TTWCS loiter capabilities

• Optically-Enabled Flight– Laser range-finder integrated into avionics– DARPA program initiated Jan ’05 for optic-flow integration– Acquiring an automotive radar for testing and possible integration

• Negotiating Marketing Agreement with ETGI– Enforcement Technology Group Inc.– Markets to Police, Special Ops, ‘Three-Letter Organizations’



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Deceptive Area SearchScaled-down search area



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Deceptive Area Search



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Multi-vehicle Planning InterfaceDeveloped for Tactical Tomahawk…

…applicable to multi-vehicle coordination under human supervisory control


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Multi-vehicle Planning InterfaceDeveloped for Tactical Tomahawk, applicable to multi-vehicle coordination under human supervisory control



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Multi-vehicle Planning InterfaceDeveloped for Tactical Tomahawk, applicable to multi-vehicle coordination under human supervisory control



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What missions would benefit from MIT/NTC vehicles & algorithms?

Aeronautics &Astronautics• Aggressive Autonomous Helicopter: Any mission requiring…

… persistent observation (as opposed to fly-by) at close range

… flight at low altitude in obstacle-rich environments

… urban canyon sensor emplacement missions

… organic support of troops advancing through urban environments

• Algorithms:

– Fast, cooperative navigation to a target point in threat-laden environment

– Optimal coverage of multiple surveillance/target points (placement of assets)

– Deceptive reconnaissance of a planned route where ambush is possible

• Low Cost Flight Test: For testing sensors, multi-vehicle algorithms, etc.


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Scenario:•Nonlinear urban battlefield: Combat or Stability and Support Operation (SASO)•Intelligence Preparation of the Battlefield (IPB) completed to identify known or templated enemy locations•Imagery available prior to operations to identify urban grid of major/minor roads•GOAL: provide persistent recon of NAIs and key intersections to prevent enemy

from ambushing ground element

Assumptions:•Multiple UAVs organic at battalion and brigade •Analysts available in unit headquarters (TOC/TAC) to assess UAV imagery real-

time•Sufficient communications channels and bandwidth to enable UAVs to

communicate between each other and relay data to headquarters (TOC/TAC)•UAV sensors capable of identifying enemy ambushes

Recon Mission Priorities1. Timely, persistent recon of NAIs and potential

ambush sites to answer Commander’s PIR2. Provide situation awareness of enemy activities in

key locations 2. Remain stealthy

EXAMPLE: SENSOR EMPLACEMENT SCENARIO Ref: Army Field Manual 100-5, Staff Organizations and Operations


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Operations Officer (S3) develops ground route

OBJ

TAA

~8 miles

Intelligence Preparation of the Battlefield (IPB)Step 1: Define the Battlefield Environment

• Identify major road networkStep 2: Describe the Battlefield’s Effects

• Weather analysis• Identify friendly, neutral, and insurgent supported areas

Step 3: Evaluate the Threat• Develop threat model and doctrinal template

Step 4: Determine Threat Courses of Action (COAs)• †Develop Named Areas of Interest (NAIs) – zones necessary to observe to determine the enemy

COA; observing NAIs is the key to determining whether the enemy can and will ambush a convoy• Develop event template and event matrix – anticipated threat actions triggered by activity in NAIs


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Intelligence Officer (S2) develops NAIs†

OBJ

TAA

Intelligence Preparation of the Battlefield (IPB)Step 1: Define the Battlefield Environment

• Identify major road networkStep 2: Describe the Battlefield’s Effects

• Weather analysis• Identify friendly, neutral, and insurgent supported areas

Step 3: Evaluate the Threat• Develop threat model and doctrinal template

Step 4: Determine Threat Courses of Action (COAs)• †Develop Named Areas of Interest (NAIs) – zones necessary to observe to determine the enemy

COA; observing NAIs is the key to determining whether the enemy can and will ambush a convoy• Develop event template and event matrix – anticipated threat actions triggered by activity in NAIs


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Operations Officer (S3) develops alternate routes

OBJ

TAA


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Operations Officer (S3) and Intelligence Officer (S2) develop and publish Recon and Surveillance (R/S) Order tasking two UAVs (White and Red) and 50 sensor emplacements to recon NAIs and convoy route

Note: Ground convoy can depart at any time following the launch of the UAVs/sensors depending on the mission, threat and unit Tactics, Techniques and Procedures (TTPs)

OBJ

TAA


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Red and White UAVs begin ‘deceptive’ reconnaissance of planned and alternate routes

Sensors are placed in NAIs, either launched from TAA or from UAVs

OBJ

TAA


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Red and White UAVs begin ‘deceptive’ reconnaissanceof planned and alternate routes

Sensors are placed in NAIs, either launched from TAA or from UAVs

OBJ

TAA

White UAV remains within comm range of sensors

Red UAV forges ahead, relays comms from forward sensors through white UAV


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Spiral 2 Laboratory Configuration

AUAV Aircraft Model

Visualization

Low Level AutopilotGround Control

Station

Team Management ControlStation

AutopilotGPSIMU

CommLink

TUAV1 VTUAV Surrogate Autopilot and Closed Loop SImulator

TUAV2 Silver Fox Autopilot and Closed Loop Simulator

Net-Centric Testbed

Forward PlatformRelay PlatformShip Platform

Rugged Console

Real TUAVs

Simulated UAVs

JoystickTakeoff/Landing

Minimal TUAV where needed Control Station

UAV Laboratory supports integration with the MMH avionics system labs


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James D. Paduano Eric Feron Presented to the ACGSC, Salt Lake City March 2, 2005

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