Bradshaw - Sensory Information Systems - Spring Review 2013

1DISTRIBUTION A: Approved for public release; distribution is unlimited.26 February 2013
Integrity  Service  Excellence
Patrick Bradshaw
AFOSR/RTE
Air Force Research Laboratory
Sensory
Information
Systems Program
8 March 2013

2DISTRIBUTION A: Approved for public release; distribution is unlimited.
2013 AFOSR SPRING REVIEW
PORTFOLIO OVERVIEW
BRIEF DESCRIPTION OF PORTFOLIO:
•Auditory modeling for acoustic analysis
•Biological polarization optics & vision
•Sensori-motor control of bio- flight & navigation
SUB-AREAS IN PORTFOLIO:
Sensory Information Systems (3003/L)
Program Officer: Patrick Bradshaw

Program Trends and Strategy:
TOPIC AREA OVERVIEW
Polarization Vision & Optics:
Sensorimotor Control of Flight & Navigation:
Scientific Question: How do natural photoreceptors detect and how do
animal brains interpret polarization information? How is it used for nocturnal
navigation or recognition of obscured targets? Can these unique bio-optical
systems be emulated?
Scientific Question: How does neural control make natural, low-Reynolds
No. flight autonomous, efficient, and robust? Discover principles of
multisensory fusion, distributed sensors and actuators. Develop control laws
for emulation in MAVs.
Advanced Auditory Modeling:
Scientific Question: How does the auditory brain parse acoustic
landscapes, bind sensory inputs, adapt its filters, hear through noise and
distortion? Could autonomous listening devices emulate neurology to match or
exceed human auditory analysis, e.g., to detect and identify speech targets in
noise and reverberation?
40%
12%
47%
Strategy: Forge useful connections between math and biology
AFOSR
BioNavigation
Research
Initiative

TO: Navy: Bio-inspired method to classify acoustic sources, e.g., vehicles,
humans, marine animals etc., using cortical auditory model. Dr. Sam Pascarelle,
Advanced Acoustic Concepts, Inc.
TO: AFIT: Techniques in electrophysiology and neuroanatomy for
mechanical engineering projects to emulate flapping wing flight. Dr. Mark
Willis, Case Western U., Dr. Anthony Palazotto, AFIT
TO: DARPA: System for adaptive, autonomous control of robotic
movement, based upon hierarchical neural model of biological control.
Roger Quinn &. Roy Ritzmann, Case West. U.; G. Pratt, DARPA.
TO: Bloedel Hearing Institute: New, patented method to improve
auditory coding in cochlear implants. Developed by Dr. Les Atlas, U. Wash. Dr. Jay
Rebenstein will develop commercial applications.
TO: AFRL-- Eglin: Measurements and data on biological wide-field-of-view
optical systems to enable 6.2 and 6.3 efforts in vision-based guidance and
navigation. D. Stavenga, U. Groningen, N. Strausfeld, U. Arizona, M. Wehling, et al.
Recent Transitions

Subprogram:
Auditory Modeling for Acoustic Analysis
AIMS
Understand how neural signal
processing in the auditory
brain can advance the design
of acoustic techniques for
noise suppression, directional
hearing, and speech analysis
ACCOMPLISHMENTS
(Previously Reported}
• Mathematical and experimental analysis
of acoustic propagation via skull, middle
ear, and soft tissue
• Hybrid feed-forward, feed-back adaptive
noise cancellation
• Restoration of 3D spatial hearing via
headphones
CURRENT PROJECTS
Dynamic response of cochlear
hair cells. Bozovic, UCLA
Advanced methods for binaural
synthesis. Hartmann MSU
Neural Oscillations in Auditory
Cognition. Large, Circular Logic
Spectral, & contextual constraints
on 3D hearing. Iyer, Simpson, AFRL/RH
Analysis & control of Informational
Masking. Kidd, Boston U.
= REPORTED IN 2012 SPRING REV.

A Speech Analysis Breakthrough
Speech intelligibility improves markedly for
normal-hearing (NH) listeners and for hearing-
impaired (HI) listeners
FIRST TECHNIQUE TO APPLY COMPUTATIONAL AUDITORY
SCENE ANALYSIS TO IMPROVE MONAURAL INTELLIGIBILITY
Unpublished data. Status Report 1, STTR Phase II Project: "An Auditory Scene Analysis Approach to
Speech Segregation” Dr. DeLiang Wang, Ohio State University
Individual Speech Hearing Performance against Multitalker Babble

An Auditory Modeling Transition
for Acoustic Analysis
Key stages of hypothesized auditory processing,
from detection of an acoustic signal to
recognition of its source in ambient noise.
AFOSR Sensory System Program grants: FA9550-07-C-0095, 0017, FA9550-12-1-0388 to Dr.
Edward Large, Circular Logic, LLC.. SIBR: John Hall, Michael Spottswood 711HPW/RHCB
Unique dynamical system
model for auditory scene
analysis, based upon neural
gradient frequency networks
& Hebbian adaptation
AFOSR 6.1 Research
SBIR
Topic AF112-024
Listener Performance
Modeling in Urban
Environments

Polarization Biology Sub-Program
AIMS
HIGHLIGHTS
(Previously Reported)
NEW DEVELOPMENTS
A CURRENT FOCUS
Discover biological mechanisms
for sensing, control, and analysis
of polarized light….Derive new
optical information techniques.
• Mapped genetic landscape for
opsins in polarization vision.
• Discovered photoreceptor for
circular polarization detection.
• Discovered achromatic 1/4 wave
retarder membrane & deduced its
unique optical structure.
• Transitioned bio- polarization
principles for optical scene analysis.
Discover neural information-processing
principles that achieve successful
multiplexing & integration of spectral
and polarization signals. …Model and
emulate this in computational systems.
A multidisciplinary, coordinated grant.
BRISTOL, UK, QUEENSLAND, UMBC, & WUSTL
• Natural Dichroic Polarizer
• Polarization-Neutral Reflector
• High Resolution Pol Vision

A Natural Dichroic Polarizer
Used for Visual Signalling
Animal (Mantis Shrimp) uses
dichroic carotenoid molecule
(astaxanthin) in a movable
antennae to produce time-
varying polarization signals in
specific directions.
UMBC, U. Queensland, UC Berkeley: Chiou, et al., J. Exp. Biology 2012.
Broadband polarization
transmission depends on
antenna orientation
Polarization-active layer in
antennal scale,
Odontodactylus scyllarus
First-reported
biological dichroic
polarizer

Discovered: Mechanism of Biological
Non-Polarizing Reflectors
• T. M. Jordan, J. C. Partridge & N.W. Roberts. Univ. of Bristol.
• Nature Photonics 2012.
Unique optical reflectors:
Suppress polarization at all
angles
• Layers of guanine cytoplasm crystals
are broadband birefringent.
• No refractive index mismatch between
crystal layers and the external medium.
• Each crystal optical axis aligns with its
long axis or orthogonal to its plane.
• Optical design could be exploited in
synthetic devices.
Silvery fish avoid the Fresnel effect
(loss of reflectivity, gain of
polarization at Brewster’s angle):
They maintain polarization
camouflage in all directions

Discovered: High-Resolution
Polarization Vision
Mourning Cuttlefish, Sepia plangon
In most polarization-sensing animals, acuity
for polarization orientation (the “e-vector”
angle) ranges from about 10 to 20 degrees.
This cuttlefish, which lacks color vision,
shows (via a change in skin coloration) that it
can discriminate between targets and
backgrounds based on only a 1 degree
difference in e-vector angle … the highest
biological resolution yet known.
Research continues on how high-resolution
polarization sensory systems are employed In
covert signaling and camouflage.
S. E. Temple, et al., Current Biology (2012) supported by AFOSR Sensory Information Systems Program

Bombus terrestris
Megalopta genalis
(Nocturnal Bee)
Hawks & Falcons
Echolocating Bats
Dragonfly Hawk moth
Span of Natural Flier Research:
A Few Program Participants
Vertebrates Invertebrates

Sensori-motor Control of Natural
Flight and Navigation
= AFOSR BIO-NAVIGATION FUNDING INITIATIVE
P. Krishnaprasad ( U. MD):
Modeling formation flight control
T. Daniel ( U. Washington):
Wing mechanosensor functions.
H. Krapp ( Imp. College London):
Neural basis of visual steering
S. Humbert ( U. Maryland):
Modeling sensorimotor control
M. Frye ( UCLA):
Higher-order motion detection
S. Reppert ( U. Mass):
Clock-compensated navigation
R. Ritzmann (Case Western):
Adaptive locomotion control
J. Evers (AFRL/RW):
Natural 3D flight dynamics
G. Taylor (Oxford):
Raptor pursuit strategies in 3D
E. Warrant (Lund U.):
Nocturnal navigation
P. Shoemaker (Tanner Res.):
Visual detection of small targets
M. Willis (Case Western):
Visual / olfactory target tracking
R. Olberg ( Union College):
Dragonfly flight to target capture
S. Sterbing ( U. MD):
Wing sensors in bat flight control
M. Wehling ( AFRL/RW):
Neural analysis of optic flow.
S. Sane ( Tata Institute):
Insect multisensory integration

AFRL-DSTL Working Group
Biologically-Motivated Micro-Air-Vehicles
“STATE OF THE ART REVIEW”
Georgia Tech
15-18 June, 2010
Organizers: M. Wehling, AFRL. P. Biggins, Dstl
Presentations:
https://livelink.ebs.afrl.af.mil/livelink/llisapi.dll?func=ll&objId=24091294
&objAction=browse&viewType=1
30 Participants from UK, US, Industry, Academia, & Gov.
H. Krapp
J. Niven
G. Taylor
T. Daniel
S. Humbert
M. Willis
U.S.U.K.
International and 6.2
Coordination

Fundamental Question:
What underlying principles drive
biology’s design of actuation and
sensing architectures?
Motivating Observations
from Insect Research :
• Sensors are “noisy,” redundant, distributed
in non-orthogonal coordinates.
• Inputs fuse across modalities prior to
activating flight muscles.
• No conventional distinctions between
estimate/control or inner/outer loop
• Sensors differ radically in bandwidth &
temporal response, e.g., vision lags
mechanoreception.
Insect Lab, Eglin AFB
Dr. Jennifer Talley
Sensori-motor Control of Natural
Flight and Navigation

Wings are Sensory Receptors
- - - A New Research Effort
Hawkmoth, Manduca sexta
MECHANICAL
INPUT
Wing Campaniform Neurons Respond to Mechanical Forces
NEURON
RESPONSE
4-NEURON
COHERENCE
INPUT POWER
SPECTRUM
CORIOLIS
REGIONS
Hypothesis:
Wings not only drive flight, but also detect inertial moments.
- - - strain receptors modulate wing shape and position.
T. Daniel (biology) and K. Morgensen (Aeronautics) U. Washington.

Wings are Sensorimotor Surfaces
• Discovering their Role in Flight
Control
BATS
HAWKMOTHS
Measure joint muscle activity during flight.
What is controlled? Force or position?
Discover role of intrinsic (non-joint) muscles.
Record from strain receptors during wing motion.
Measure dynamics of response to mechanical inputs.
Map neural signal from wing to flight motor.
Find and study hair sensors on wings.
Measure response to air flow.
Map wing sensor circuits to cortex.

Mechanoreceptors in Flight Control
Sterbing-D’Angelo et al., PNAS 2011, Sterbing-D’Angelo & Moss (in press)
Tactile Hairs have directional bias:
Many favor reverse air flow.
Air flow reverses during low-speed flight
when vortices form and flow separates
Scientific Challenge:
Finding:
Hypothesis:
Tactile hairs indicate stall?
They enable the bat to stabilize
flight when airflow is disrupted?
Discover the role of wing receptors in
flight control.

Mechanoreceptors on Bat Wings
Cortical response to
single-unit stimulation
Flight Velocity
ProximitytoObstructions
Removing tactile hairs
alters flight steering
Tactile wing hair
200m length, 5m diameter base
ba
• Ringed by Merkel cells
• Responsive to air puffs
• Mapped to sensory cortex
• Needed for flight agility
Current Findings:
Sterbing-D’Angelo et al., PNAS 2011, Sterbing-D’Angelo & Moss (in press)

Biological Flight Coherence Inspires
New Control Laws
Key Insights:
In 2 dimensions, obstacle avoidance and
boundary tracking pose similar problems for
flight coordination, but 3-dimensional
coordinated flight requires a new approach.
Gyroscopic modeling enables biological
interpretations and tests.
Illustration of a gyroscopic
boundary- tracking law
following circular motion
on the surface of a sphere.
Scientific Challenge:
Develop control laws that model sensory
interactions and coordination in biological
flight.
Zhang, Justh, & Krishnaprasad, GaTech & U. MD. 2012

STTR AF12-BT03
Direction and Value (RW)
• Biologically-inspired topic provides science base to extend
current seeker state of the art from anthropomorphic narrow
field of view single color intensity imager to arthropomorphic
wide field of view multispectral intensity and polarization
imager
– Enhances situational awareness (120 deg fov vs 1 deg fov)
– Enhances target discrimination capability (multispectral
and polarization discrimination)
– Increases seeker functionality (from terminal guidance
sensor to sensor enabling guidance, navigation and
control and fuzing, applicable to ISR and BDA and
communication channel receiver)
• Supports vision-based sensor development in Nature-Inspired
Sciences Center of Excellence, and vision-based sensor
applications in BioUAS PA

Recent Highlights
AFOSR
Basic Research
Initiative:
Biological Sensing
of Magnetic Fields
Optimal Protocols for
Photic Re-Entrainment
Challenge:
Discover how geo-
magnetism can induce
neural signals for spatial
navigation.
Math solution minimizes
time to adjust circadian
phase (‘jet lag’)
D. Forger, U. Mich.
QuickTime™ and a
TIFF (LZW) decompressor
are needed to see this picture.
Nature-Inspired
sciences for sensing
& control of
autonomous flight
AFRL/RW
Center of Excellence:
A Program Partnership

Nature-Inspired CoE:
Direction and Value
• Technical focus in RW has been on the science
underlying optical sensors and associated
algorithms, for application to agile autonomous
airframes
• CoE provides opportunity to expand technical
focus to include additional sensory modes
(mechanosensors, chemosensors,
magnetosensors), and address efficient
approaches to combining information from these
sensors
• Opportunity for exchanging personnel and
students in each other’s laboratories

BIO-SENSING OF MAGNETIC FIELDS
A NEW BASIC RESEARCH INITIATIVE
AFOSR SENSORY INFORMATIN SYSTEMS PROGRAM
SCIENTIFIC CHALLENGE:
Discover the receptor mechanism(s)
for biological magnetic sensitivity,
especially at field strengths
comparable to the geomagnetic
background.
PM ADVISORY GROUP:
Patrick Bradshaw, Tatjana Curcic,
Hugh DeLong, John Gonglewski,
Willard Larkin (retired, v.e.c.)
*Primary co-PM

KNOWN:
What is known? … What is conjectured?
TWO CONJECTURES:
Magnetoreception is found in all
major vertebrate groups, plus
some molluscs, crustaceans, and
insects
Used for local position
finding (e.g. bats homing at
night)
Used for long-range migration
Magnetite Fe3O4 single-domain crystals associated with cell
membranes twist to align with an imposed field – this may
open/close ion channels.
Blue-light photoreceptive proteins – cryptochromes – are
somehow involved, possibly via quantum spin coherence among
radical pairs.

Why would this discovery matter?
It would explain the bio-sensory basis for long-
range navigation by orientation to the geomagnetic
field.
It could provide a missing scientific link to understand
neurocognitive effects of magnetic stimulation – these
phenomena currently are explored in AFRL 711HPW/RH.
It could reveal the first known quantum-level
biophysical mechanism in sensory biology -- we
conjecture that some natural biological systems acquire
extreme sensitivity via correlated spin dynamics of
certain electron transfer reactions.
It would deepen fundamental knowledge of
cryptochrome proteins in sensory function – these
proteins are implicated in a wide range of non-imaging
photosensitivity, e.g., adaptive camouflage. They may
be key to light-dependent magnetoreception.
1.
2.
3.
4.

Why enter this research area now?
• Weak experimental methods have hampered past efforts to find a
biophysical transduction mechanism for magnetic sensitivity. Better
techniques are now available, in behavioral, cellular, molecular, and
physics approaches.
A few key papers:
Kirschvink, et al., (J. Royal Society, 2010) Biophysics of magnetic
orientation: Strengthening the interface between theory and
experimental design.
Eder, et al. (PNAS, 2012) Magnetic characterization of isolated
candidate magnetoreceptor cells.
Solov’yov & Schulten (J. Phys. Chem. 2012) Reaction kinetics and
mechanism of magnetic field effects in cryptochrome.
Dorner, et al. (Quant. Phys. 2012) Toward quantum simulation of
biological information flow.
• A scientific community with growing interest and expertise has been
forming, especially with respect to “Quantum Effects in Biology,” (Dr.
Sterbing attended QEB meeting in June.) High quality proposals are
expected.

Where is the top research in this area?
Munich: Michael Winklhofer, at Ludwig-Maximillians Univ.
Duke U.: Sonke Johnson (a PI in Hugh DeLong’s program)
Oxford: P.J.Hore (DARPA-funded expert on quantum chemistry)
Baylor: David Dickman (expert on avian magnetic navigation)
U. Mass: Steven Reppert (a PI in Larkin’s program)
U. Oldenberg, GE: Henrik Mouritsen (Neurosensory Sciences)
Chapel Hill: Kenneth Lohmann (UNC biologist)

Conclusion
• Sensory information systems is a dynamic, cross cutting
discipline that is discovering what nature has perfected
• This program is feeding information to many of the TD’s
(RW, RY, RX) as well as the RTX’s (RTA, RTE)
• The BRI and COE are exciting opportunities that will
provide creative, new information for the science of flight

Backup Slides

Dissociated cell from trout olfactory epithelium
rotates with an imposed 33Hz magnetic field
Red arrows identify a micron-sized magnetic
cluster inside the cell. Such rotatable cells
were rare in this preparation, and had an
elongated shape (aspect ratio 1.6).
RECENT FINDING
CONJECTURE
Sources: Eder, et al., (PNAS 2012) and Lohmann (Nature 2010)

A RECENT FINDING:
“Magnetically sensitive light-induced
reactions in cryptochrome are consistent
with its proposed role as a
magnetoreceptor.”
Kinetics and quantum yields of photo-
induced radical pairs (flavin-tryptophan)
were studied for this plant cryptochrome
(in vitro). Rates of spin-coherent
processes were estimated. Magnetic field
effects were seen down to 1 mT.
Maeda, et al. (PNAS 2012)
Arabidopsis thaliana
Cryptochrome AtCry-1
CONJECTURE:
Magnetic sensitivity may be a
general feature of this protein family,
and could extrapolate to
vertebrate cryptochromes.

Can AFOSR take the lead in this area?
Current research funding is widely scattered: No
other focused Federal program exists.
DARPA’s program on quantum effects in biology (QEB)
has a much broader scope, but it has relevance to our
BRI. We have encouragement and continuing interest
from DARPA. (Matt Goodman and Guido Zuccarello)
Dr. Susanne Sterbing is deeply capable in the
physics, biophysics, and sensory neuroscience
needed for AFOSR’s PM leadership on this topic.

Visuomotor Convergence

Visual Sensory Equipment in
Flying Insects
1. Study the functional and physiological organization of two visual mechanisms (compound eye, ocelli)
in Locusts, Tabinids, and Asilids (Krapp)
2. Characterize observability properties of tangential cells and ocelli across species (Humbert)
3. Extract species-specific adaptations of visual control structures and determine general principles for
multisensory integration (Krapp, Humbert)
4. Implement bio-inspired visual feedback for stabilization and compare to traditional approaches
(Humbert)
How is visual sensor specification linked to flight performance?
Tabanidae (horseflies);
varying number of ocelli, 18-
25 VS cells, 6 HS cells
Asilidae (robber flies); no
ocelli, no VS cells, 5-18
HS cells
Calliphoridae (blowflies);
3 ocelli, 10/11 VS cells, 3
HS cells
Orthoptera (locusts); 3 ocelli,
likely to have no VS cells,
several HS cells, no halteres

Insect Sensorimotor Control
Power
Muscles
Steering
Muscles
Apply control- and information-theoretic tools to models of sensory systems and flight
dynamics to understand potential benefits to unmanned aerial systems (UAS)
What is novel/unique about insect sensorimotor systems?
• Measurements made in highly non-orthogonal axes
• Sensors configured to measure composite quantities
• Traditional separation between estimation/control and
inner/outer loops is absent
Fundamental Question: What underlying principles drive
biology’s design of actuation and sensing architectures?

Multidisciplinary Methods /
Approach
Novel combination of experimental and analytical methods from biology,
aerodynamics, flight dynamics and control/information theory
• Electrophysiology to study
functional and physiological
organization and generate
models of sensory systems
• High speed videography and
automated kinematics extraction
to determine control strategies
• Computational fluid dynamic
simulations (based on extracted
kinematics) to estimate flight
dynamics models
• Control- and information-theoretic
analysis of closed loop behavior
(observability/controllability)
+_
x(1 )
x(t)

Novel Contributions
• Formalization of operational principles for insect sensorimotor control systems
• Novel approach combining biological experimental techniques, high fidelity
simulations with solid grounding in control- and information theoretic analyses
• Are natural systems optimized for information extraction, maneuverability, robustness
or some combination of the above?
• Are sensory systems matched to the flight dynamics (Mode-Sensing Hypothesis)?
• What are the potential improvements in Air Force capabilities?
• Increased levels of agility, gust tolerance and autonomy for small scale UAS
• Comparisons of novel hardware implementations with traditional engineered solutions
(computational requirements, bandwidth, SWaP, closed loop performance)
Biological Principles Novel Hardware Implementations
(analog VLSI)
Increased Capabilities for Small UAS
(Agility, Robustness, Autonomy)

Visual flight control in dim light:
How moths see and maneuver in low light.
Objectives:
(1) Determine what part of the visual environment is
most important for flight stabilization and steering.
(2) Determine the spatial and temporal resolution of
motion-detecting neurons in the visual system.
(3) Determine the spatial and temporal resolution of
visual flight control mechanisms by challenging
freely behaving M. sexta moths to fly through
environments using identical stimuli and conditions.
Technical Approach:
(1) Record responses of freely flying moths to
visible patterns in areas of their visual
surround (i.e., above, below, to the side). Then
determine the combination of pattern density
and decreasing light level that causes flight
stabilization and maneuvering to degrade.
(2) Determine the spatial and temporal resolution
of the wide-field motion detecting neurons in
the visual system that supports adaptive flight
control in these moths.
(3) Coordinate these two approaches to show how
moths generate adaptive flight control at night.
DoD Benefit:
(1) Basic knowledge of important visual
principles that enable flight in dim light.
(2) Useful insights for the development of control
systems allowing autonomous micro air vehicles
to fly missions in dim light.
WIND
Parallel studies of the behavioral responses of freely flying moths
and the responses of neurons in the visual systems of the same
species, to the same visual stimuli, will reveal the performance
envelop of adaptive flight maneuvering in these specialized night
flying animals.

Flight Control Experiments
• Behavioral responses of freely flying moths
tracking odor plumes upwind will be recorded
as they encounter different visual patterns at
different light levels from daylight to starlight.
• Male moths track female pheromone plumes
upwind – supported by motion-sensitive
visual flight stabilization and steering control.
• The lowest pattern contrast (combination of
finest stripe density and moth flight speed)
that continues to allow stable flight control at
each light level reveals the maximum spatial
and temporal resolution of the flight control
system.
• Behavioral response will be compared to
physiological responses of neurons in the
moths visual system to the same stimulus
and light conditions.
Normal
control
Flight
disrupted
over low
contrast
pattern
WIND

Visual Motion Experiments
• Recordings of the physiological
responses of neurons in the visual
system sensitive to wide-field motion
will be made at different light levels
from daylight to starlight (using
neutral density filters).
• Neurons respond preferentially to
sinusoidal stripe gratings moving in
one direction – they are directionally
sensitive to motion.
• The fastest pattern motion and finest
stripe density that can distinguish at
each light level reveals the maximum
spatial and temporal resolution of the
visual system.
• Responses of these neurons will be
compared to responses of freely
flying moths in the same stimulus
and light conditions.

Haematopota pluvialis,
A horse fly
Stomatopod compound eye; six
midband rows contain spectral
and polarization sensing diversity

Insect Bird Bat
( ) with potential to be controlled during flight
Natural Fliers’ Wing Joints
Plagiopatagiales Muscles
Bat wing has Intrinsic,
non-joint muscles
Research Questions:
• Discover joint coordination timing
• Determine functional redundancy
• Do joint muscles control force or position?
• Discover what the intrinsic muscles do.
Wing Sensorimotor Activation
- - A New Program Initiative

Intrinsic Muscles Active
only
During Wing Upstroke:
Discovering Bat Wing Musculature
Dynamics during Flight
Large bat (1.2kg) in low speed flight
has precise control via wing skeletal
muscles and wing intramembranous
(intrinsic) muscles
• Electromyography during flight
• Thermal videography for metabolic load)
• Selective, reversible muscle paralysis
• 3D X-ray mapping of skeletal motion
ResearchTechniques:

SUMMARY:
Transformational Impacts & Opportunities
Advanced auditory modeling:
Hearing protection:
Optical processing:
Autonomous flight control:
• Adaptive airfoils based upon bio-sensory mechanisms
• Steering based upon neural autonomous systems
• Discover sensorimotor basis of formation flight
• Polarization vision and signaling adapted from biology
• Achromatic 1/4 wave optical retarders
• Emulating compound eye in new optical devices
• Mathematics for coherent modulation analysis
• Neural-Inspired analyses to parse acoustic scenes
• Massive improvements in high-noise attenuation.

Robber Fly
No Ocelli
Halteres
No VS cells
5-18 HS cells
New Lab for Insect Vision
Spectral & Polarization
Electroretinography
AFRL/RWG PI: Martin Wehling

Large bat (1.2kg) in low speed flight
maintains precise control via wing
skeletal muscles and wing
intramembranous muscles
Dynamics of Bat Wing Musculature
S. Swartz, T. Roberts, Brown Univ., 2011
Electromyography during flight
Thermal videography (to measure metabolic load)
Selective, reversible muscle paralysis
3D X-ray mapping of skeletal motion
Techniques:

Bradshaw - Sensory Information Systems - Spring Review 2013

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Bradshaw - Sensory Information Systems - Spring Review 2013