ABSTRACT The goal of this research project is to investigate the neuronal control of flying prey interception in dragonflies b

Adam R Zinman

Ashok Ramasubramanian

David A Hodgson

Max L Balter

Robert Olberg

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DESIGN, CONSTRUCTION, AND TESTING OF A FLYING PREY SIMULATOR
Adam R. Zinman
Department of Mechanical Engineering
Union College
Schenectady, New York 12308
Max L. Balter†∗
Robert Olberg‡
Ashok Ramasubramanian†
David A.       Hodgson
†Department of Mechanical Engineering
‡Department of Biology
Union College
Schenectady, New York, 12308
ABSTRACT
The goal of this research project is to investigate the neu-
ronal control of flying prey interception in dragonflies by design-
ing, constructing, and testing an apparatus to simulate the com-
plex motions of a flying insect. Our three-dimensional motion
device is capable of mimicking a flying insect by moving a small
bead accurately up to speeds of 1 m
s
in any direction. Dragonflies
are efficient aerial predators that can intercept and capture small
insects in flight. Our stimulus device will be used to determine
the way in which dragonfly neurons encode information about
object movement in three dimensions. Sinusoidal position track-
ing experiments using multiple input frequencies were conducted
using the apparatus. The results indicate that the machine oper-
ates with good repeatability with little variability between trials.
Preliminary dragonfly testing with the apparatus showed favor-
able results, indicating proof of concept.
INTRODUCTION
Dragonflies are highly efficient aerial predators that have the
remarkable capability of capturing small insects in flight. This
complex process generally occurs in less than 300 ms with inter-
ception flights having success rates as high as 97 % [1]. Visual
information concerning the prey’s position, orientation, and ve-
locity are converted into navigation directions, mapping the drag-
onfly’s flight path to intersect with the prey’s flight path. Our
research is aimed at understanding the neuronal control in this
∗Max Balter and Adam Zinman contributed equally to this paper.
rapid and highly accurate visually-guided behavior.
This distinctive prey-capture behavior requires both rapid
visual processing and information transmission, resulting in the
evolution of large neurons. The specific neurons that control this
process consist of target-selective descending neurons (TSDNs).
TSDNs provide the dragonfly’s flight control system with steer-
ing instructions to direct the flying dragonfly toward its prey.
Fortunately, these large neurons are accessible for electrophys-
iological studies.
Motivation
To date, studies of the dragonfly visual neurons have been
mostly restricted to two dimensions, the X direction (left–right)
and the Y direction (up–down), recording responses to images
displayed on a flat projection screen [2]. However, the flying in-
sect prey pursued by dragonflies move in three dimensions and
little is known about how the visual neurons encode the third
dimension (front–back). It is hypothesized that Z dimension
(front–back) movement is vital to understanding the exact roles
of these neurons in prey interception. To address this question,
we built an apparatus to aid in the investigation of these visual
neurons. This device will simulate an insect flying in three di-
mensions, with all movements computer controlled via Simulink
and Real Time Windows Target, both of which are components
of MATLAB 7.10 (The MathWorks, Inc, Natick, MA).
Eight bilateral pairs of TSDNs are implicated in steering the
1Corresponding Author, hodgsond@union.edu
                                             †1
ASME 2012 5th Annual Dynamic Systems and Control Conference joint with the
JSME 2012 11th Motion and Vibration Conference
DSCC2012-MOVIC2012
DSCC2012-MOVIC2012-8559
October 17-19, 2012, Fort Lauderdale, Florida, USA
1 Copyright © 2012 by ASME
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interception flight. These neurons descend from the brain of the
dragonfly to the wing motor regions of the thorax, transmitting
visual information about prey movement [3] [4] [5]. Their activ-
ity drives steering adjustments in wing angle. Our device will be
used to determine the way in which the TSDNs encode informa-
tion about object movement in three dimensions. This apparatus
has the potential to reveal which target-selective neurons encode
three-dimensional movement and how their activity is modulated
by movement in the third (front–back) dimension. This informa-
tion is crucial for understanding how the dragonfly intercepts its
flying prey.
In order to better understand real-world responses, looming
objects need to be introduced that are moving at various veloc-
ities and directions, while the dragonfly is held stationary. The
looming artificial prey objects are composed of glass beads of
varying sizes (1 mm - 1 cm) sturdily mounted on a fine nylon
monofilament. The monofilament is not visible to the foraging
dragonflies as evidenced in previous studies in which they occa-
sionally collided with the monofilament in flight [6].
In a preliminary study, testing was conducted by controlling
the bead by hand. The problem with moving the bead manually
is that it makes it more difficult to track the kinematic properties
(position, velocity, and acceleration) of the bead at any given
time. It also prevents the researcher from easily correlating the
bead movement with the neuronal activity.
Neurobiological studies with the apparatus will help us un-
derstand the coding of three dimensional visual information by
individual neurons. We expect to gain further comprehension of
the visual selectivity and responsiveness of the TSDNs to three-
dimensional object position and velocity.
METHODS
The project involved designing, constructing, and testing a
machine to simulate the complex motions that insects exhibit
in the natural environment. The design requirements included
a maximum speed of 1 m
s
in all dimensions and a motor rise time
less than 10 ms in all directions. The size requirement was an
interior volume of 46 cm3 in which the bead can move.
The project goals were outlined as follows: (1) devise and
construct the structural framework of the apparatus, (2) achieve
open loop control by implementing motors and encoders, (3) ob-
tain closed loop control through Simulink and Real Time Win-
dows Target, and (4) run neurobiological experiments with live
dragonflies.
Basic Design Framework and Motor Selection
Based on the design requirements, the apparatus was cre-
ated using t-slot extruded aluminum, timing belts and pulleys,
ball bearings, metal axles, and DC brushed motors. The appara-
tus (shown in Fig. 1 during an experimental test run with a live
dragonfly) works by moving a small glass bead simultaneuosly
in three directions. The bead is mounted on a thin microfilament
Table 1. SUMMARY OF MOTOR SPECIFICATIONS
Motor X Y Z
Rated Voltage (V ) 24 24 24
Peak Current (A) 1.99 23.8 40.4
No Load Speed ( rad
s
) 822 388 336
Stall Torque (N −m) 0.052 1.4 2.9
Power Output (W ) 43 136 244
Gear Ratio 5 3 3
(not visible in Fig. 1) and moved in the lateral (left–right) direc-
tion by the X motor. The ends of the microfilament are connected
to spindles attached to the two vertical posts (Fig. 1). Each of
these spindles is moved in the vertical direction (up–down) by the
Y motors. Two separate motors, marked Y1 and Y2 in Fig. 1,
are used to move the bead in the Y direction because the space in
front of the dragonfly should be completely unobstructed. This
prevented us from using just one motor and some sort of rigid
coupling between the two vertical posts. Instead, we used two
motors and employed control to ensure that their motions were
synchronized. The Z motor moved the entire assembly (12.5 kg)
in the Z (front–back) direction. It was mounted as low as possi-
ble to prevent visual obstruction.
Since the load (bead + microfilament) in the X direction
(left–right) is quite small, the X motor is the smallest among
all the motors used. The Y motors need to move the X motor
and the spindle-microfilament assembly in the Y direction (up–
down); hence they are bigger than the X motor. One of the Y
motors, Y1, also carries a bigger load becuase it carries the X
motor and the spindle assembly while the Y2 motor carries just
the spindle assembly. As mentioned previously, their vertical po-
sitions are synchronized using control. The Z motor needs to
move the entire assembly, including the two vertical posts, in the
Z direction (front–back); hence it is the largest motor used.
Power and gear ratio calculations were performed to select
appropriate DC brushed motors and timing pulleys respectively.
The motors also include encoders to allow for closed loop feed-
back control. Motor specifications in the three directions are
summarized in Table 1. Note that the Y1 and Y2 motors are
the same.
Motor drivers (Dimension Engineering SynRen 10, 25, and
2x25 A) were used in packetized serial mode to allow Real Time
Windows Target to send signals to the motors. 500 counts per
revolution (CPR) optical encoders were used to measure the bead
position in each movement direction. Based on the gear ratios
and timing pulleys for each dimension, the precisions in the X,
Y, and Z directions were 1357, 586, and 599 counts
cm
respectively.
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Figure 1. EXPERIMENTAL APPARATUS: D=DRAGONFLY, X=X MO-
TOR, Y1=Y1 MOTOR, Y2=Y2 MOTOR, AND Z=Z MOTOR. THE THREE
MOVEMENT DIRECTIONS ARE ALSO INDICATED. X DENOTES LEFT
TO RIGHT DIRECTION, Y UP AND DOWN DIRECTION, AND Z FRONT
TO BACK DIRECTION.
Friction Cancellation
The precision of the motion control apparatus was slightly
compromised due to friction. Our system involves repeated ve-
locity reversals in all three dimensions, making it necessary to
reduce the unwanted friction. Although our motors have the po-
tential to generate linear speeds up to 1 m
s
, the machine is typ-
ically used only at low velocities. Low velocity, bidirectional
position tracking systems are particular vulnerable to friction er-
rors [7].
In the controller algorithm for each motor, biases were ex-
perimentally determined to eliminate Coulomb friction at low ve-
locities. For example, in the X dimension, when a signal between
-8 to +8 was sent to the motor, the bead failed to move. In order
to eliminate the Coulomb friction that prevented the motor from
rotating, a bias of 8 was added to the signal. Fig. 2 plots the sig-
nal versus steady state velocity for the X motor without friction
cancellation to demonstrate how the bias was derived.
Closed Loop System
The closed loop feedback control system was modeled in
Simulink using Real Time Windows Target. The general form of
the model is shown in Fig. 3. A simple proportional controller
was used in all directions. The proportional gains were 0.1, 0.1,
0.1 and 0.2 for the X, Y1, Y2, and Z directions respectively.
Dragonfly Test Setup
Experimental tests were performed with a live dragonfly to
validate the purpose of the apparatus. A dragonfly (Anax junius)
was mounted with wax to a rigid bar. A small incision in the tho-
rax exposed the ventral nerve cord between the prothoracic and
Figure 2. X MOTOR SIGNAL VS STEADY STATE VELOCITY BEFORE
FRICTION CANCELLATION. NOTE: DEAD ZONE DENOTES FRIC-
TION.
Figure 3. THE GENERALIZED CLOSED LOOP CONTROL SYSTEM.
mesothoracic ganglia. A small hook electrode, fashioned from
bare 100 µm silver wire, was positioned under one of the paired
connectives of the nerve cord. The recording site was insulated
by the injection of petroleum jelly, and a ground electrode was
inserted through a leg socket near the recording site. The drag-
onfly, with implanted electrodes was mounted ventral side up, so
that movements of the 3 mm bead were centered on the acute
region of the dorsal compound eye.
The dragonfly was held stationary while the TSDN signals
were recorded. It was crucial for the dragonfly to be completely
isolated from the vibrations caused by the mechanical compo-
nents of the device to eliminate the responses of vibration sen-
sitive neurons. For this reason, the experimental animal and
recording hardware was mechanically isolated from the stimu-
lus apparatus with an anti-vibration air table. However, dragon-
flies are not known to have any hearing organs or to show any
responses to sounds, so the subtle mechanical noise of the appa-
ratus did not affect the electrophysiological recordings.
The signal from the recording electrode was amplified (A-M
systems Model 1700, bandpass 0.3-5 kHz) and passed to a data
acquisition system (AD Instruments Powerlab running LabChart
6 software). Synchronization pulses were sent from MATLAB to
the data acquisition system to synchronize the start of the electro-
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0 0.5 1 1.5 2 2.5 3 3.5 4 4.5
−15
−10
−5
0
5
10
15
desired signal
actual signal with friction cancellation
actual signal without friction cancellation
Figure 4. X MOTOR FREQUENCY TESTING AT 1.5 HZ.
physiological recordings with the start of the programmed bead
trajectory. This allowed us to match specific neuron spikes with
the kinematic properties of the bead at any given time. A sample
is shown in Fig. 6C.
RESULTS
Sinusoidal Tracking
Closed loop sine wave frequency response testing was per-
formed separately for each motor in the system to determine the
root mean square (RMS) errors with and without friction cancel-
lation. Testing was conducted at low (1.5 Hz), medium (3 Hz),
and high (6 Hz) frequencies.
Five trials were conducted for each motor for both with and
without friction cancellation cases (note: friction cancellation
has not been performed yet for the Z motor). For each trial,
one cycle with an amplitude of approximately 8.5 cm was an-
alyzed to determine the RMS error. Fig. 4 illustrates the fre-
quency response at 1.5 Hz for the X motor with and without fric-
tion cancellation. The results of the five trials for each motor
were averaged and the standard deviations were calculated. Fig.
5 summarizes the results of the experiments at each frequency.
The repeatability of results with sinusoidal tracking was excel-
lent. This led to extremely small standard deviations. For this
reason, the error bars, even though present, are not visible in Fig.
5 for most of the cases.
Dragonfly Testing
Figure 6 shows the correlation between the dragonfly neuron
spikes and the X Y, and Z positions when the bead followed a
collision-like path. The bead trajectory formed the shape of a
pyramid, with the pyramid’s apex positioned at the head of the
dragonfly (Fig. 4A).
(1.5Hz)
(3Hz)
(6Hz)
Figure 5. FREQUENCY TEST RESULTS FOR TRACKING IN X, Y1, Y2,
AND Z DIRECTIONS. FC DENOTES FRICTION CANCELLATION.
DISCUSSION
Although this is an interdisciplinary project involving ele-
ments of both control theory and biology, this paper focuses more
on the former. The device is fully functional and when more
experiments are performed, the data will be published in appro-
priate venues. Also, details such as transfer function analysis in
z and s domains, open and closed loop pole locations, stability
analysis, and step responses are currently being worked out and
will be made available in a forthcoming journal publication. Al-
though a formal stability proof is not yet available, we can report
that the apparatus did not exhibit any unstable behavior in any of
the experiments discussed in this paper and indeed has a remark-
able level of repeatability. The maximum standard deviation was
just 0.019 cm for an 8.5 cm amplitude position command.
In all cases of sinusoidal tracking, as with any servo control
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C
a
m
p
li
tu
d
e
(m
v
)
time (s)
B
time (s)
A
x
di
sp
la
ce
m
en
t (
cm
)
y
d
is
p
la
ce
m
e
n
t
(c
m
)
zdisplacement (cm)
Figure 6. A: SAMPLE 3D BEAD TRAJECTORY, B: DISPLACEMENT
VS TIME IN ALL DIRECTIONS, AND C: DRAGONFLY NEURON RE-
SPONSE.
system, performance decreased with increasing frequency (Fig.
5). Also, for all cases reported, friction cancellation decreased
the RMS error, as expected. The error bars in Fig. 5 are quite
small, demonstrating good repeatability.
The stimulus apparatus will help further our understanding
of the information transmitted by the TSDNs in the dragonfly.
These neurons are implicated in guiding the interception of flying
insects by the foraging dragonfly [8]. They are known to trans-
mit information about prey location and angular velocity (direc-
tion and speed), but very little is known at present about the way
in which information concerning the third dimension, prey dis-
tance, is integrated into their responses or even about how such
information is obtained.
Unraveling the neural basis of visually guided prey intercep-
tion by dragonflies could reveal how a small group of neurons
can drive a fast, complex, and highly reliable behavior such as
the interception of flying insects. The results of this study could
potentially lead to the development of effective guidance mech-
anisms for military or civilian use.
ACKNOWLEDGMENTS
We thank the Air Force Office of Scientific Research
(AFOSR grant # FA9550-10-1-0472 to RO) for equipment and
summer fellowship support. This research was also funded by
Student Research Grants from Union College.
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[3] Tanouye, M., and Wyman, R., 1980. “Motor outputs of giant
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[4] Blondeau, J., 1981. “Electrically evoked course control in
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[5] Pearson, K., and Robertson, R., 1981. “Interneurons coac-
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[6] Olberg, R., Seaman, R., Coats, M., and Henry, A., 2007.
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[7] Ramasubramanian, A., and Ray, L., 2007. “Comparison of
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DESIGN, CONSTRUCTION, AND TESTING OF A FLYING PREY SIMULATOR

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DESIGN, CONSTRUCTION, AND TESTING OF A FLYING PREY SIMULATOR

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