SENSOR FUSION LABORATORY

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SENSOR FUSION LABORATORY
Thad Roppel, Associate Professor AU Electrical
and Computer Engineering Dept. troppel_at_eng.auburn.
edu

• EXAMPLES
• Infrared / Millimeter wave radar for vehicle
  detection and identification
• Chemical sensor arrays artificial nose
• Biomimetics imitating animal sensorimotor
  behaviors
• Biomedical using electrical and optical probes
  to study cardiac arrhythmias

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SENSOR FUSION LABORATORY
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Personnel and Publications

• PERSONNEL
• Ting-To Lo (PhD) Molecular Switching in
  Biosensors
• Rama Narendran (PhD) Biomimetic Simulations of
  Organized Machine Behavior
• Jun Pan (PhD) Wireless Protocol for Electrical
  and Optical Cardiac Microprobes
• Aroldo Couto (MS) Flight Stabilization Using
  Adaptive Artificial Neural Networks
• Brian Wingfield (MS) Silicon Processing for
  Lateral Emission Fiber-Optic Sensors

• REPRESENTATIVE RECENT PUBLICATIONS
• D. M. Wilson, T. Roppel, and R. Kalim,
  "Aggregation of Sensory Input for Robust
  Performance in Chemical Sensing Microsystems,"
  Sensors and Actuators B, 64(13), 107-117, June
  2000.
• T. Roppel and D. M. Wilson, "Biologically-Inspired
  Pattern Recognition for Odor Detection," Pattern
  Recognition Letters, 21(3), 213219, March 2000.
• D. M. Wilson, K. Dunman, T. Roppel, and R. Kalim,
  "Rank Extraction in Tin-Oxide Sensor Arrays,"
  Sensors and Actuators B, 62(3), 199-210, April
  2000.
• T. Roppel, R. Kalim, and D. Wilson, "Sensory
  Plane Analog-VLSI for Interfacing Sensor Arrays
  to Neural Networks, " Virtual Intelligence and
  Dynamic Neural Networks VI-DYNN '98, Stockholm,
  Sweden, June 22-26, 1998.

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IR / MMW DATA FUSION
Support AFOSR 1992-93
Project Goal Improved identification of military
vehicles from aerial scenes.
T-62 Tank
M-113 Armored Personnel Carrier (APC)
LANCE Missile Launcher
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IR / MMW Fusion, contd
OVERALL RESULT 14 improvement with sensor
fusion
PERFORMANCE ASSESSMENT
A T L
A - -
T - -
L - -

• Multiple permutations
• Confusion matrix
• Average result

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Chemical Sensor Arrays
Support DARPA 1997-99
PROJECT GOAL Improved identification and
detection of chemical plumes in non-laboratory
conditions.
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Canine Training at IBDS
Auburn is world-renowned for training of
detection dogs at the Institute for Biological
Detection Systems.
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Chemical Sensor Arrays, contd
Sensor Array Dynamic Response
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Chemical Sensor Arrays, contd
Preprocessing
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Chemical Sensor Arrays, contd
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Chemical Sensor Arrays, contd
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Chemical Sensor Arrays, contd
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Chemical Sensor Arrays - Summary

• A recurrent neural network was trained to
  recognize 9 odors presented in an arbitrary time
  sequence.
• Response time is reduced by an order of magnitude
  by threshold preprocessing.
• Well-suited for use as a front-end for a
  hierarchical suite of NNs in a portable,
  near-real time odor classification device.

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BIOMIMETICS
Support Under discussion with AF Advanced
Guidance Division, Munitions Directorate at Eglin
AFB
PROJECT GOAL Learn sensor fusion from animals.
Apply this to flying a drone to target using
onboard video.
Flies land accurately
Bats catch evading insects in flight
Bees find flowers
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BIOMIMETICS, contd
What do they know that we dont?
One possibility is that they use variations of
optic flow.
Represent sensory image field by motion vector
field.
Image Sequence
Optic Flow Field
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BIOMIMETICS, contd
EXAMPLES A fly can land simply by maintaining
constant optic flow. A dog can track by
maintaining constant sensory flow across
olfactory epithelium and following the gradient
(using sniffing as a form of chopper amplifier.
Questions to be answered Can we guide a missile
to target, orchestrate complex defense systems,
identify faces in a crowd, or track contaminated
food with similar approaches?
END OF PRESENTATION