ENGINEERING RESEARCH INSTITUTE OVERVIEW OF RESEARCH EXPERTISE

In Robotics, Diagnostics and Control

BY

Dr. Mohan J. Malkani, Associate Dean for Graduate Studies and Research

Director Engineering Rsearch Institute

(615) 963-5400, mmalkani@tnstate.edu

ENGINEERING RESEARCH INSTITUTE (ERI)Research Centers and Laboratories

ENGINEERING RESEARCH INSTITUTE (ERI)Research Centers and Laboratories

● Center for Battlefield Sensor Fusion – ARO (2004)

● Center for Environmental Engineering -- DOE (1996)

● Center for Neural Engineering -- ONR (1992)

● Digital Signal/ Image Processing Laboratory -- Air Force

(1991)

● Intelligent Control Systems Laboratory -- NASA (1993)

● Design Methodologies Laboratory -- NASA (1993)

● Intelligent Manufacturing Laboratory -- SME,ONR (1994)

● Intelligent Health Monitoring Laboratory -- PSU/MURI-

DURIP (1998)

● Computer and Information Systems Laboratory -- DOD/HP

(1996,99)

● Automatic Target Recognition (ATR) Test-bed --- AFRL

(2006-2008)

ERI Conducts Research in “Cutting-Edge Technology” Areas

ERI Conducts Research in “Cutting-Edge Technology” Areas

Some ERI sample strengths are:

Artificial Intelligence/NN/FL/GA Database Design&Data Mining Parallel&Distributed Computing Modeling, Simulation & Analysis Speaker Recognition Signal/ Image Processing Intelligent Control Systems Intelligent Health Monitoring Robotics and Automation

Intelligent Manufacturing Human-Machine Interfaces Sensors and Machine Vision CAD/CAM/CAE Tools Wireless Communication Automatic Target Recognition Cyber Security Environmental Remediation Probabilistic Design Methodologies

ERI MISSION

SMALL SCALE ROBOTICS

● MID-SOUTHE ENGINEERING, INC.TENNESSEE STATE UNIVERSITYSpherical Motor and Neural Controller for Micro Precision Robot Wrist

● ROBOTICS RESEARCH CORPORATIONJET PROPULSION LABORATORYNext Generation Controller for Redundant Robots

● AEROMOVER SYSTEMS CORPORATIONTHE UNIVERSITY OF MICHIGANDifferentiated Universal End Effector

● VISUAL INSPECTION TECHNOLOGIES, INC., SRI INTERNATIONAL Mobile Magnetic Robots for Inspection of Steel Structures

SMALL BUSINESS TECHNOLOGY TRANSFER (STTR) PROGRAMSMALL BUSINESS TECHNOLOGY TRANSFER (STTR) PROGRAM

NASA 1994 PHASE INASA 1994 PHASE I(PROPOSALS SELECTED FOR FUNDING OF STTR PHASE I CONTRACTS)

● TRANSITIONS RESEARCH CORPORATIONUNIVERSITY OF SOUTHERN CALIFORNIACombined Distance and Orientation Sensor(CODOS)

● AMHERST SYSTEMS, INC.STATE UNIVERSITY OF NEW YORK AT BUFFALOFoveal Sensor and Image Processor Prototype

● ENDOROBOTICS CORPORATIONUNIV OF CALIFORNIA BERKELEY Milli-Robots for Surgical Teleoperation

Center for Neural Engineering - Funded by ONR1992 - 2004

PredictiveMaintenance

HelicopterControlusing

NN, FL, GA

Embodiment of Intelligent

Behaviors on MobileRobots

BiologicallyMotivated NN

(PCNN) & MobileRobots

Robust IntegratedNeurocontroller

For ComplexDynamic Systems

Intelligent faultdiagnosis

tools

Health MonitoringOf NASP

Hypersonic Structures

Localization OfVentricular

ArrhythmogenicFoci

Chaos ControlIn

A FluidizedBed

IntelligentControl-

Wind PowerAnalysis

STTR InRobotics

NnClassification

For DigitalCommunication

Signal / NoiseSeparation

& BlindDeconvolution

1991-1995 1996-1999 1994-1996 1996-1999 1994 1997-1998 1994-1995

1993-1996

CBM of bearingand data

acquisition

Integrated predictivediagnosis for

helicoptergear box

Physics- basedmodeling of

bearing

Measure ofeffectiveness &

performance for AI based monitoring

systems

Simulationbased design using PDM, FEA & SM

1997-1998 1997-1998 1998-1999 1998-1999 1999-2000

1996-1998

2000-20031995-Present

1995-Present

1992-Present

NASA NASA NSA

NASA

VAAFRL DOE DOE

Lockheed Martin ONR ONR

NSF

Air To Air CampaignThunder ModelUsing Genetic

Algorithms

1998-1999

IntelligentAircraft

Controller

1995-1996

NASA Boeing Boeing

TowardsTelepresence Using Mobile

Robots

1998-2003 1998-2000

NSFCALTECH

Virtual TandemVehicles- Mobility

Controller ForMobile Robots

ARMY TACOM

Applied Research Lab - Penn. State University

NASA ARC

April 2005

Visual TeleroboticTask Planning Of

Cooperative RobotsUsing Soft Computing

2003-2005

NASA/JPL

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8-0.5

-0.4

-0.3

-0.2

-0.1

0

0.1

0.2

0.3

Time (seconds)

Filte

red

Sign

al

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8-0.6

-0.4

-0.2

0

0.2

0.4

0.6

Time (seconds)

Acc

eler

atio

n w

avef

orm

at

Left

Bea

ring

Ver

tical

(No

Load

)

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8-0.6

-0.4

-0.2

0

0.2

0.4

0.6

Time (seconds)

Acc

eler

atio

n w

avef

orm

at

Left

Bea

ring

Ver

tical

(No

Load

)

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8-0.2

-0.15

-0.1

-0.05

0.05

0.1

Time (seconds)

Filt

ered

Sig

nal

Fault Pattern Recognition

10 15 20

40

60

80

ENTECH PL-302 Multi-ChannelSpectrum Analyzer

10

20

30

40

50

60

0

10 15 20

40

60

80

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8-0.5

-0.4

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-0.1

0

0.1

0.2

0.3

Time (seconds)F

ilter

ed S

igna

l

Fault Pattern Classification)

Features Features ExtractionExtraction

DiagnosticData Fusion

CausalityReasoning

Rule-BasedFault Reasoning

Feature Vector Set Feature Vector Set Selection for Fault Selection for Fault

DiagnosisDiagnosis

Neural-NetworkNeural-NetworkSelection for FaultSelection for Fault

DiagnosisDiagnosis

0

20

25

Critical System Components

Data AcquisitionSignal Processing

Banks of Neural NetworksNovelty Faults

Diagnostics & Prognostics

CONDITION BASED MAINTENANCE

Tennessee State UniversityDepartment of Electrical and Computer Engineering

Intelligent Control Systems (ICS) Lab(Dr. Saleh Zein-Sabatto, mzein@tnstate.edu)

Intelligent Control Systems Research Work

“Control and Coordination of Multiple Unmanned Areal

Vehicles (UAVs)”Design & Modeling

Testing & SimulationHardware Prototyping

TSU RoboticsLab

Static/DynamicParameters

AlgorithmicSupportive

Tools

Behavior-basedCooperative

Tactical Strategies

Kinematic and Dynamic Module

Fuzzy-LogicMotion Controller

Module

Neural-NetworkTerrain Learning

Module

Genetic-AlgorithmTactical Formation

Module

Behavior-based Navigation

Module

World PerceptionModelingModule

Diagnostic andConflicts

Handling Module

Scheduling and Synchronization

Schemes

Signal/Image ProcessingSchemes

CommunicationProtocols

WirelessCommunication

Module

Sensory Info Acquisition &

Fusion

Man-MachineInterface

Distributed Distributed FMCell FMCell

SimulationSimulationEnvironmentEnvironment

IntegratedMobility

SupervisoryController

PhysicalPhysicalEnvironmentEnvironment

Penn State - DARPA - MURI Project

TSU RoboticsLab

Autonomous Surveillance Perspectives

ROBOTICCOMMUNICATION

Speech Recognition by Mobile Robots

Soldiers Recognize Commands and act

TSU will develop mapping that will be used by consortium partners

Three small mobile robots communicate and follow the commander

Sensors Technology Thrust Research-AFRL (2006-2008)

• Automatic Target Recognition- TSU (Lead)• Electro-Optics - University of Dayton (Lead)• Radio Frequency- Louisiana State Univ. (Lead)• ATR Consortium Member Universities:• Louisiana Tech University• Michigan State University• Prairie View A & M University• North Carolina A &T State University• Chaminade University of Hawaii

ATR Test-Bed (ATRTB)

Electric Helicopter and 7 Cameras Surveillance System

Student Research Participations

Faculty Participations

●C5

●C1

●C3

●C4

●C2

●C6

●C7

Camera Surveillance

System at TSU

UAV at TSU Campus

Energy Efficient Wireless Multimedia Sensor Networks

(Supported by AFRL-- ATR Project, 2007 - 2008)• Objective

Develop a test-bed for energy efficient multi-hop wireless multimedia sensor networks to explore design tradeoffs in cross-layer protocols, error control schemes, mesh image/video

transmission, etc.

• Wireless Multimedia Sensor Networks Test-bed

Access Point

Server Internet

ClientsClients

Tier 1

802.15.4/zigbee

Tier 2

Tier 3

Tier 4

802.11

motes with sensorsand low-resolution cameras

GatewayHeterogeneous Motes

Low-resolution camera

Robot with highresolution camera

Helicopter with high-resolution camera

Cross-Layer Design of Cognitive Networks with MIMO TechnologyObjectives MIMO Technology

ApproachCross-Layer Design MIMO-aware Hierarchical Network Architecture with link-jumping and head-rotation – enabling efficient routing – inexpensive self-reconfiguration MultiOptimal-MAC Protocol – a CSMA/CA based MAC with a multi-optimizer Efficient Routing Algorithms – short and robust: maximize network throughput and network lifetimeTesting and Evaluation – Test Modeling & Test-Bed – Performance Evaluation

Research Project for the Minority Leaders Sensors Program(Funded by AFRL, 2007 – 2008)

Without using extra energy and Without using extra energy and channel, a MIMO transceiver can channel, a MIMO transceiver can be used to be used to • Extend transmission range, or Extend transmission range, or reducing error rate at links by reducing error rate at links by using diversity gainusing diversity gain• Increase data rate at links by Increase data rate at links by using multiplexing gainusing multiplexing gain

Leverage MIMO technology in across-layer fashion involving network architecture, PHY, MAC, and routing protocols to multi-optimize networking performance and maximize network life in wireless sensor networks (WSNs)

T×1

T×2

T×M R×M

R×1

R×2

T×1

T×2

T×M R×M

R×1

R×2

MIMO sensor network

multiplexing gaindiversity gain

MIMO transceiver

`

Systematic sensor data & information fusion

Sensors networking in battlefield situations

Multiple target identification and tracking Battlefield source allocation and

management Networks modeling and simulation Network performance measurements Experimental testing & evaluation of

sensor network concepts.

CENTER OF EXCELLENCE FOR CENTER OF EXCELLENCE FOR BATTLEFIELD SENSOR FUSION (ARO)BATTLEFIELD SENSOR FUSION (ARO)

RESEARCH FOCUS AREAS

PARTNERSHIPS / CONTRACTSPARTNERSHIPS / CONTRACTSPARTNERSHIPS / CONTRACTSPARTNERSHIPS / CONTRACTS

TACOM

Bevilacqua Research Corporation

BRCBRC

2007-2008 ERI Funded Research projects

1. Center for Excellence in Battlefield Sensor Fusion, funded by Army Research Office (ARO) $2,331,255.(2004-2009)-Dr. Shirkhodaie (PI)

2. Multi-Mode UAV Sensor Technologies (Multi-MUST), funded by WPAFB, Air Force Research laboratory (AFRL)$137,000(2006-2007)-Dr. Shirkhodaie (PI)

3. Surface and Partially Buried UXO Identification, discrimination, and Localization Based on Cognitive Imagery Techniques, funded by Tyndall, AFRL $160,000 (2006-2007)-Dr. Shirkhodaie (PI)

4. Sensors Technology Thrust Research—(Automatic Target Recognition)-AFRL $780,000 (2006-2008)Dr. Mohan Malkani (PI)

5. Neural-Fuzzy Modeling in Model-Based Fault Detection, Isolation, Control Adaptation and Reconfiguration in Turbine Engines—funded by Propulsion Directorate (AFRL)---$ 288,520 (2007-2010)—Dr. Zein-Sabatto (PI)

6. Visual Telerobotic Task Planning of Cooperative Robots based on Soft Computing, funded by NASA/JPL $300,000 (2004-2007)-Dr. Shirkhodaie (PI)

7.Human Systems Integration (Seating Comfort)—Boeing--$750,000( 2007-2010)- Dr. Onyebueke (PI)

8..Cybersecurity-ORNL/BWXT Y-12 ---$538,149 Dr. Decatur B. Rogers (PI) (2207-2010)9. Intelligent Cognitive inspection System for Manufacturing Process Automated Reasoning and

Decision Making—funded by Rolls Royce--$90,000 (200-2007)-Dr. Shirkhodaie (PI)10. Failure Mode and Criticality Analysis of Maintenance Issue --funded by Aerospace Testing

Alliance $50,000—Dr. Devgan (PI)

Suite of Digital Signal Processing Tools Advanced Intelligence Tools: Neural Networks, Fuzzy Logic

and Genetic Algorithms Fault Detection and Health Monitoring Intelligent Control System: Aircraft, Helicopter Modeling, Simulation and Analysis Systems Engineering Mobile Robot Navigation Sensor Fusion Data Mining Computer Integrated Manufacturing Integrated Design Methodologies - FEM, SM and PDM Patents and Technology Transfer Information Technologies

STRONG POINTS OF OUR RESEARCH STRONG POINTS OF OUR RESEARCH CAPABILITIESCAPABILITIES