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  • 1. ENGINEERING RESEARCH INSTITUTE OVERVIEW OF RESEARCH EXPERTISE In Robotics, Diagnostics and Control College of Engineering, Technology and Computer Science BY Dr. Mohan J. Malkani, Associate Dean for Graduate Studies and Research Director Engineering Rsearch Institute (615) 963-5400, [email_address] College of Engineering, Technology and Computer Science
  • 2. Undergraduate Programs Organizational Chart Dr. Melvin N. Johnson President Dr. Robert Hampton Provost/ Executive Vice President Dr. Lonnie Sharpe Interim Dean Dr. Mohan J. Malkani Associate Dean and Director of ERI Architectural and Facilities Engineering Master of Engineering ME Graduate Studies Civil and Environmental Engineering Computer Science Electrical and Computer Engineering Mechanical and Manufacturing Engineering Aviation and Industrial Technology Master of Science MS Doctor of Philosophy Ph.D Environmental Engineering Biomedical Engineering Manufacturing Engineering Mechanical Engineering Electrical Engineering Computer Communication and Network Control System and Signal Processing Robotics and Computer Integrated Manufacturing Computer and Information Systems Engineering CISE Computer and Information Systems Engineering CISE TENNESSEE STATE UNIVERSITY
  • 3. 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 )
  • 4.
    • 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
    ERI Conducts Research in “Cutting-Edge Technology” Areas
    • 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
  • 5.
    • 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
    • AEROMOVER SYSTEMS CORPORATION
    • THE UNIVERSITY OF MICHIGAN
    • Differentiated Universal End Effector
    • VISUAL INSPECTION TECHNOLOGIES, INC., SRI INTERNATIONAL
    • Mobile Magnetic Robots for Inspection of Steel Structures
    SMALL BUSINESS TECHNOLOGY TRANSFER (STTR) PROGRAM NASA 1994 PHASE I (PROPOSALS SELECTED FOR FUNDING OF STTR PHASE I CONTRACTS)
    • 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
    • ENDOROBOTICS CORPORATION
    • UNIV OF CALIFORNIA BERKELEY
    • Milli-Robots for Surgical Teleoperation
  • 6. Center for Neural Engineering - Funded by ONR 1992 - 2004 Predictive Maintenance Helicopter Control using NN, FL, GA Embodiment of Intelligent Behaviors on Mobile Robots Biologically Motivated NN (PCNN) & Mobile Robots Robust Integrated Neurocontroller For Complex Dynamic Systems Intelligent fault diagnosis tools Health Monitoring Of NASP Hypersonic Structures Localization Of Ventricular Arrhythmogenic Foci Chaos Control In A Fluidized Bed Intelligent Control- Wind Power Analysis STTR In Robotics Nn Classification For Digital Communication Signal / Noise Separation & Blind Deconvolution 1991-1995 1996-1999 1994-1996 1996-1999 1994 1997-1998 1994-1995 1993-1996 CBM of bearing and data acquisition Integrated predictive diagnosis for helicopter gear box Physics- based modeling of bearing Measure of effectiveness & performance for AI based monitoring systems Simulation based design using PDM, FEA & SM 1997-1998 1997-1998 1998-1999 1998-1999 1999-2000 1996-1998 2000-2003 1995-Present 1995-Present 1992-Present NASA NASA NSA NASA VA AFRL DOE DOE Lockheed Martin ONR ONR NSF Air To Air Campaign Thunder Model Using Genetic Algorithms 1998-1999 Intelligent Aircraft Controller 1995-1996 NASA Boeing Boeing Towards Telepresence Using Mobile Robots 1998-2003 1998-2000 NSF CALTECH Virtual Tandem Vehicles- Mobility Controller For Mobile Robots ARMY TACOM Applied Research Lab - Penn. State University NASA ARC April 2005 Visual Telerobotic Task Planning Of Cooperative Robots Using Soft Computing 2003-2005 NASA/JPL
  • 7. Fault Pattern Recognition 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 -0.3 -0.2 -0.1 0 0.1 0.2 0.3 Time (seconds) Filtered Signal Fault Pattern Classification) Features Extraction Diagnostic Data Fusion Causality Reasoning Rule-Based Fault Reasoning Probability of Fault Symptoms Feature Vector Set Selection for Fault Diagnosis Neural-Network Selection for Fault Diagnosis 0 20 25 Critical System Components Data Acquisition Signal Processing Banks of Neural Networks Novelty Faults Diagnostics & Prognostics CONDITION BASED MAINTENANCE 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) Filtered Signal 10 15 20 40 60 80
  • 8. 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)” Design & Modeling Testing & Simulation Hardware Prototyping
  • 9. TSU Robotics Lab Static/Dynamic Parameters Algorithmic Supportive Tools Behavior-based Cooperative Tactical Strategies Kinematic and Dynamic Module Fuzzy-Logic Motion Controller Module Neural-Network Terrain Learning Module Genetic-Algorithm Tactical Formation Module Behavior-based Navigation Module World Perception Modeling Module Diagnostic and Conflicts Handling Module Scheduling and Synchronization Schemes Signal/Image Processing Schemes Communication Protocols Wireless Communication Module Sensory Info Acquisition & Fusion Man-Machine Interface Distributed Distributed FMCell FMCell Simulation Simulation Environment Environment Integrated Mobility Supervisory Controller Physical Physical Environment Environment Penn State - DARPA - MURI Project TSU Robotics Lab Autonomous Surveillance Perspectives ROBOTIC COMMUNICATION 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
  • 10. 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
  • 11. ATR Test-Bed (ATRTB) Electric Helicopter and 7 Cameras Surveillance System Student Research Participations Faculty Participations Camera Surveillance System at TSU UAV at TSU Campus ● C 5 ● C 1 ● C 3 ● C 4 ● C 2 ● C 6 ● C 7
  • 12. 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 Clients Clients Tier 1 802.15.4/zigbee Tier 2 Tier 3 Tier 4 802.11 motes with sensors and low-resolution cameras Gateway Heterogeneous Motes Low-resolution camera Robot with high resolution camera Helicopter with high-resolution camera
  • 13. Research Project for the Minority Leaders Sensors Program (Funded by AFRL, 2007 – 2008 )
    • 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
    Leverage MIMO technology in a cross-layer fashion involving network architecture, PHY, MAC, and routing protocols to multi-optimize networking performance and maximize network life in wireless sensor networks (WSNs) MIMO sensor network MIMO transceiver Cross-Layer Design of Cognitive Networks with MIMO Technology Objectives MIMO Technology 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 multiplexing gain diversity gain
  • 14. `
    • 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 BATTLEFIELD SENSOR FUSION (ARO) RESEARCH FOCUS AREAS
  • 15. PARTNERSHIPS / CONTRACTS TACOM Bevilacqua Research Corporation BRC
  • 16. 2007-2008 ERI Funded Research projects
    • 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)
  • 17.
    • 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 CAPABILITIES