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
ENGINEERINGRESEARCH
RESEARCHINSTITUTE
INSTITUTE(ERI)
(ERI)
Research
ResearchCenters
Centersand
andLaboratories
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 MISSION
ERI
ERI Conducts
Conducts Research
Research in “Cutting-Edge
Technology”
Technology” Areas
Some ERI sample strengths are:
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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
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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
SMALL BUSINESS TECHNOLOGY TRANSFER (STTR) PROGRAM
NASA 1994 PHASE I
(PROPOSALS SELECTED FOR FUNDING OF STTR PHASE I CONTRACTS)
SMALL SCALE ROBOTICS
● MID-SOUTHE ENGINEERING, INC.
TENNESSEE STATE UNIVERSITY
Spherical Motor and Neural Controller for
Micro Precision Robot Wrist
● ROBOTICS RESEARCH CORPORATION
JET PROPULSION LABORATORY
Next Generation Controller for Redundant
Robots
● TRANSITIONS RESEARCH CORPORATION
UNIVERSITY OF SOUTHERN
CALIFORNIA
Combined Distance and Orientation Sensor
(CODOS)
● AMHERST SYSTEMS, INC.
STATE UNIVERSITY OF NEW YORK
AT BUFFALO
Foveal Sensor and Image Processor Prototype
● AEROMOVER SYSTEMS CORPORATION
● ENDOROBOTICS CORPORATION
THE UNIVERSITY OF MICHIGAN
UNIV OF CALIFORNIA BERKELEY
Differentiated Universal End Effector
Milli-Robots for Surgical Teleoperation
● VISUAL INSPECTION TECHNOLOGIES,
INC., SRI INTERNATIONAL
Mobile Magnetic Robots for Inspection of
Steel Structures
Center for Neural Engineering - Funded by ONR
1992 - 2004
AFRL
Health Monitoring
Of NASP
Hypersonic
Structures
1991-1995
VA
DOE
Localization Of
Ventricular
Arrhythmogenic
Foci
Chaos Control
In
A Fluidized
Bed
1996-1999
Lockheed
Martin
Predictive
Maintenance
1995-Present
1994-1996
CALTECH
Intelligent fault
diagnosis
tools
1996-1998
1996-1999
1998-2003
Virtual Tandem
Vehicles- Mobility
Controller For
Mobile Robots
Signal / Noise
Separation
& Blind
Deconvolution
1994
1997-1998
1994-1995
NASA/JPL
Visual Telerobotic
Task Planning Of
Cooperative Robots
Using Soft Computing
1998-2000
2003-2005
Applied Research Lab - Penn. State University
CBM of bearing
and data
acquisition
Integrated predictive
diagnosis for
helicopter
gear box
1997-1998
1997-1998
Physics- based
modeling of
bearing
1998-1999
NASA
Robust Integrated
Neurocontroller
For Complex
Dynamic Systems
1992-Present
NSF ARMY TACOM
Towards
Telepresence
Using Mobile
Robots
STTR In
Robotics
Nn
Classification
For Digital
Communication
Biologically
Motivated NN
(PCNN) & Mobile
Robots
2000-2003
NSA
NASA
ONR
Embodiment of
Intelligent
Behaviors on Mobile
Robots
Helicopter
Control
using
NN, FL, GA
NASA
Intelligent
ControlWind Power
Analysis
NASA ARC
ONR
1995-Present
NSF
DOE
1993-1996
NASA
Boeing
Intelligent
Aircraft
Controller
1995-1996
Boeing
Air To Air Campaign
Thunder Model
Using Genetic
Algorithms
1998-1999
Measure of
effectiveness &
performance for AI
based monitoring
systems
Simulation
based design using
PDM, FEA & SM
1998-1999
1999-2000
April 2005
CONDITION BASED MAINTENANCE
Signal Processing
Data Acquisition
40
40
0.2
0
0.05
0.1
-0.2
0
0.1
0.2
0.3
0.4
0.5
Time (seconds)
10
0
15
20
15
25
0.6
0.7
20
0.8
-0.2
-0.3
-0.1
-0.4
-0.15
-0.5
0
-0.2
-0.6
0
0
-0.1
-0.05
-0.1
-0.4
20
10
0.1
Filtered Signal
0.1
0.3
0.2
Filtered Signal
60
60
0.2
0.4
Filtered Signal
80
80
Acceleration waveform at Left Bearing Vertical(No Load)
0.3
0.6
-0.3
-0.4
-0.2
0
-0.5
0
0.1
0.1
0.2
0.1
0.2
0.3
0.4
0.5
Time (seconds)
0.6
0.7
0.3 0.4 0.5 0.6
Time (seconds)
0.2
0.7
0.8
0.3 0.4 0.5 0.6
Time (seconds)
0.7
0.8
0.8
Critical System Components
60
Features
Extraction
Feature Vector Set
Selection for Fault
Diagnosis
50
40
30
20
Neural-Network
Selection for Fault
Diagnosis
10
0
Novelty Faults
Banks of Neural Networks
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Fault Pattern Recognition
Fault Pattern Classification)
Diagnostics & Prognostics
Rule-Based
Fault Reasoning
Diagnostic
Data Fusion
Causality
Reasoning
Tennessee State University
Department 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)”
Testing & Simulation
Design & Modeling
Hardware Prototyping
Penn State - DARPA - MURI Project
Autonomous Surveillance Perspectives
Speech Recognition by Mobile Robots
TSU will develop mapping that will be used by consortium partners
Soldiers Recognize
Commands and act
TSU
TSURobotics
Robotics
Lab
Lab
Kinematic and
Dynamic Module
Communication
Protocols
Scheduling and
Synchronization
Schemes
Man-Machine
Interface
Static/Dynamic
Parameters
Neural-Network
Terrain Learning
Module
Physical
Environment
Wireless
Communication
Module
Signal/Image
Processing
Schemes
Sensory Info
Acquisition &
Fusion
Integrated
Mobility
Supervisory
Controller
Distributed
FMCell
Simulation
Environment
Fuzzy-Logic
Motion Controller
Module
Behavior-based
Cooperative
Tactical Strategies
Algorithmic
Supportive
Tools
Three small mobile robots communicate
and follow the commander
Genetic-Algorithm
Tactical Formation
Module
Behavior-based
Navigation
Module
World Perception
Modeling
Module
Diagnostic and
Conflicts
Handling Module
ROBOTIC
COMMUNICATION
Sensors Technology Thrust
Research-AFRL (2006-2008)
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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
UAV at TSU Campus
Camera
Surveillance
System at TSU
●C1
●C5
●C4
●C2
●C7
●C3 Participations
Faculty
●C6
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 crosslayer protocols, error control
schemes, mesh image/video
transmission, etc.
Heterogeneous Motes
• Wireless Multimedia Sensor Networks
Test-bed
Clients
Clients
Server
Access Point
Internet
Tier 3
802.11
Gateway
Tier 2
Low-resolution camera
Tier 1
Robot with high
resolution camera
Helicopter with
high-resolution
camera
Tier 4
802.15.4/zigbee
motes with sensors
and low-resolution cameras
Research Project for the Minority Leaders Sensors Program
(Funded by AFRL, 2007 – 2008)
Cross-Layer Design of Cognitive Networks with MIMO Technology
Objectives
Leverage MIMO technology in a
cross-layer fashion involving
network architecture, PHY, MAC,
and routing protocols to multioptimize networking performance
and maximize network life in
wireless sensor networks (WSNs)
Approach
Cross-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 lifetime
Testing and Evaluation
– Test Modeling & Test-Bed
– Performance Evaluation
MIMO Technology
Without using extra energy and
channel, a MIMO transceiver can
be used to
• Extend transmission range, or
reducing error rate at links by
using diversity gain
• Increase data rate at links by
using multiplexing gain
MIMO transceiver
T×1
R×1
T×2
R×2
T×M
R×M
MIMO sensor network
diversity gain
multiplexing gain
CENTER OF EXCELLENCE FOR
BATTLEFIELD SENSOR FUSION (ARO)
RESEARCH FOCUS AREAS
 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.
`
PARTNERSHIPS / CONTRACTS
TACOM
BRC
Bevilacqua Research Corporation
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 (20062007)-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)
STRONG POINTS OF OUR RESEARCH
CAPABILITIES
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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