Title: SENSOR FUSION LABORATORY
1SENSOR FUSION LABORATORY
Thad Roppel, Associate Professor AU Electrical
and Computer Engineering Department troppel_at_eng.au
burn.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
2SENSOR FUSION LABORATORY
3Personnel 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.
4IR / 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
5IR / MMW Fusion, contd
OVERALL RESULT 14 improvement with sensor
fusion
PERFORMANCE ASSESSMENT
A T L
A - -
T - -
L - -
- Multiple permutations
- Confusion matrix
- Average result
6Chemical Sensor Arrays
Support DARPA 1997-99
PROJECT GOAL Improved identification and
detection of chemical plumes in non-laboratory
conditions.
7Canine Training at IBDS
Auburn is world-renowned for training of
detection dogs at the Institute for Biological
Detection Systems.
8Chemical Sensor Arrays, contd
Sensor Array Dynamic Response
9Chemical Sensor Arrays, contd
Preprocessing
10Chemical Sensor Arrays, contd
11Chemical Sensor Arrays, contd
12Chemical Sensor Arrays, contd
13Chemical 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.
14BIOMIMETICS
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
15BIOMIMETICS, 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
16BIOMIMETICS, 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 navigate an
aircraft, guide a missile to target, orchestrate
complex defense systems, identify faces in a
crowd, or track contaminated food with similar
approaches?
17OPTIC FLOW FOR NAVIGATION
18OPTIC FLOW THEORY
OPTIC FLOW EQUATIONS http//cw.scouting.org.za/ian
/research/tut2/
19OPTIC FLOW EXAMPLES
Contraction
Expansion
Translation
The distinctive patterns of optic flow are
analogous to the motion blurs depicted above
Source http//vision.psy.mq.edu.au/derek/OpticFl
ow.htm
20SENSOR FUSION