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Biomimetic Design
James Tacey, Aditi Shinde

Abstract—Robot locomotion is the name associated with
robotic movement. This is the area of research that focuses on
robots moving themselves from one location or space to another,
as well as how they handle various terrains and their effects. For
a robot to decide how, when and where to move autonomously is
the foremost aim in mimetic locomotion. Synchronization of
various parts and joints while moving around a place is one of the
complex part of robot design.
designers are now providing backup systems and tolerant
systems in place on robots. These systems will detect when the
robot is damaged or faulty, as well as which parts, and take
steps to bring redundant systems online, compensate for the
damage, or even repair itself.
Index Terms—Biomimetic, locomotion, degrees of freedom,
actuators, autonomous.
II. ARTIFICIAL INTELLIGENCE:REVIEW STAGE
I. INTRODUCTION
The ability to adapt to new situation rapidly is an extremely
beneficial tool. Much like a biological creature’s ability to
learn, research into artificial intelligence has been attempting
to give robots this same capability. Currently, as robots are
only able to respond to pre-programmed stimuli, they are very
limited in what they are capable of without a human controller.
The ability to learn and adapt to new experiences would give
robots the capability to respond to new situations and become
more efficient at tasks. By using positive and negative
feedback loops simple artificial intelligence can be achieved,
but there is still a very large potential in this area.
For years biological creatures have been adapting, traversing,
and existing in a wide variety of natural environments without
outside influence by humans. In comparison, robots in the past
have been limited in capability by the limitations imposed by
the technology available. More recently, robotic design has
shifted towards mimicry of animals and their capabilities. By
drawing insight from animal behavior and systems, more
recent generations of robots have been able to be more
efficient, adaptive, and to some extent, even capable of
learning.
Robotic Motion Mechanisms:
Biomimetic Locomotion From Biology:
As biomimetic locomotion is largely imitation and duplication
of structures found in nature, it is important to fully understand
what is being imitated and the biological mimicry behind it.
Neurological control, redundant systems, and the ability to
learn are all areas that robots can benefit from. Examined are a
few examples.
Neural Networks:
Through the study of how animals and people control their
various muscles, new systems can be developed that provide
more robust control systems. For example, by developing
neural networks in software, navigation systems can be made
that are similar to a biological thought process. Because of
this, robots can be developed that are more robust, and can
respond to a wider variety of input stimuli.
Biological Redundancy:
Another important feature of nature that is being applied to
robotics is the concept of redundancy and fault tolerance in
systems. Biological systems are often able to adapt and survive
damage, even when smaller biological systems fail. Similarly,
How to implement a robotic design is a very important
consideration. Exactly what methods and materials that will be
used can determine the success or failure of a robot. The
actuators and systems in place used to mimic actual biological
mechanisms should, much like a real biological creature, be
adapted to suit the environment and stress the robot will face.
Examined are a few locomotion mechanisms.
Shape Memory Effects:
One type of biomimetic material that closely resembles
muscles and is applied as an actuator in robotics is Nitinol.
This material is a nickel-titanium alloy that behaves will
contract and expand based on temperature applied, much as a
muscle would when stimulated using electricity. Called the
shape memory effect (SME), this interesting effect allows a
wide variety of approaches in robotic biomimetics.[3][1]
Pneumatic Actuators:
.
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Another muscle mimicry performed by robotics is done by
using pneumatic actuators. This will mimic muscles by
pressurizing rubber tubes with air which will cause them to
expand and contract similarly to biological muscles. While this
is an excellent lightweight alternative to some systems, the
pressures and frictions that the tubes undergo often leave these
types of muscles with a relatively short lifetime.[2][4][7]
Hydraulic Actuators:
Similar to the pneumatic actuators, hydraulic ones use fluid
instead of gas. These allow higher loads to be used and are
generally more durable. The drawback however, is that the
systems needed to use hydraulics, such as the pumps, are
generally large and cumbersome. This leads to a reduced use
in robotic motion.[2]
Electroactive Polymer:
These materials are polymers that change shape and behavior
when an electric current is passed through them. Due to the
extremely wide variety of these materials, they have an equally
wide application in robotics. The primary research focus in the
field of robotics at this time is their use as biomimetic muscles,
to be used to replace less adaptive systems.[1][2][5]
Chemical Muscles:
While not actually a muscle, the reciprocating chemical muscle
is a small self-contained noncombustible system that produces
large quantities of energy relative to its size, as well as
actuator motion. Many robot designers may be more familiar
with battery powered robots, chemical muscles provide an
interesting alternative that has a variety of applications.
Evolution:
One of the biggest problems faced with robotics is the
limitation of the materials and mechanisms, examined above.
Approaching robotics through the eyes of evolution, new
solutions to difficult problems can be procured. As a robot is
built of a few relatively simple components such as sensors
and actuators, co-evolution of the hardware and software can
FIG. 1 : Robotic Lobster
achieve impressive results. By simulating a robot using
software and genetic algorithms, solutions that are typically
difficult to obtain, such as a gait for a robot over a specific
terrain or environment, can be found. This allows the design of
a robot to go from having a human hand-design the robot
through repeated trial and error, which could still lead to an
inefficient design, to designing a robot by allowing it to
organically adapt to the environment through which it will
traverse.
Examples:
The following robotic examples employ one or several of the
above mentioned biomimetic approaches. Though some of the
evolutionary robotic projects might focus on simulations on
the computer, all the examples were selected according to the
requirement that they include a functioning hardware device
1. Robotic Lobster :
The goal was to create an underwater robot imitating the
Homarus Americanus. It focuses on remodeling the control
signals whose timing has improved over the years depending
upon a creatures response to animal muscles. Thus the need for
use of actuators which match their biological models arised.
SMA Nitinol turned out to be a best fit here considering its
stress-strain relationship, relaxation and contraction speeds.
Using it underwater with adequate insulation enhances its
relaxation speed. Three degrees of freedom are provided to
each leg of this eight legged robot. They are actuated by a pair
antagonistic Nitinol wire which allows the leg to rotate
bidirectionally. Elevation, swing and Side way motion are
other few properties of this robot. To keep a check on Nitinols
durability, the control signals are activated by PWM and have
sufficient relaxation time. The control architecture consists of
CPG network consisting of oscillating, command and
coordinating neurons. The control
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FIG. 2: Lamprey-based undulatory vehicle
system chooses different behaviors according to sensor-input
and supervised motivation of the robot
2. Lamprey-based undulatory vehicle
This too uses Nitnol as actuator and Lampreys swim in
rhythmic wave motion along the body axis. The efficient and
highly pliable swimming locomotion of the lamprey makes it a
choice for robotic emulation. It has a rigid hull which holds
the processor, a plastic notochord which is highly flexible and
a passive tail segment. Activation of the SMA wires allows
axial bending movements around 5 joints. A CPG control
architecture based on neural studies and outputs alternating
PWM pattern signal is used. Due to its artificial muscles this
robot produces strong autonomous forward swimming
3. SRI robots
FIG. 3: CWRU’s Robot V
5. Cricket microrobot
This type of robot designed after a cricket can sit in a 5cm
cube and can walk and jump. Braided pneumatic actuators
alon with spring bais are used as actuators for their joints. The
actuator system consists of 16 air muscles and 32 valves. It
employs a neural network control architecture. As a closedloop controller it includes the feedback from the angle sensors
to adjust the activation patterns.
SRI International’s six legged is loosely inspired by the
cockroach. Each leg having 2 degree of freedom controlled by
bow-tie actuators plus opposing spring forces. Its flapping
robot emulates the flying insects. Their body consists of 4 Si
bow-tie actuators which respond to their own resonance. SRI’s
inchworm robot is a 16mm rolled actuator made from
dielectric elastomer. Electrostatic clamps allows this robot to
move in inchworm style on both vertical and horizontal
surfaces.
4. Robot III + Robot V
The close observation of running cockroaches were used in
computer simulation and seven degrees of freedom were
transferred onto each leg. All this was used to develop a new
type of robot, robot III, a 75 cm long hexapod with aluminum
tube legs that were modeled closely after the cockroaches
morphology. The degree os freedoms vary for front, middle
and rear legs. The total 24 degrees of freedom of the robots
legs are actuated by double-acting pneumatic cylinders. Its
control aarchitecture acts at posture, swing and stance level. .
Due to pneumatic cylinders disability to deal load changes this
robot could not create a steady walking pattern.[7]. The Robot
IV replaced the pneumatic cylinder by pneumatic muscle. Its
drawback is it force-to weight ratio. It fails to carry its own
weight.[7]. As its predecessors robot V (also called Ajax) is
non-autonomous and relies on external power supply and
control. Its air muscle permits bidirection motion.
FIG. 4: CWRU’s Cricket microrobot
6. Sprawl
The ability of a cockroach to cross uneven terrain at a very afst
speed while climbing obstacles without losing its speed makes
it an ideal example for robot locomotion emulation in such
varied conditions. It employs the pneumatic pistons as main
actuators and servomotors for rotation of joints. Isprawl the
youngest member in the family was without any actuators to
allow autonomy. The use of polymers with different compliant
values allows components to reach elasticity characteristics
closer to their biological counterparts. This reduces the need
for complex control signals to mimic these properties in
software.
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FIG. 4:
This type of robot is excited by a pair of piezo-electric
actuators which are at same voltage but 90 degree out of
phase. This phase shifts brings in the two degrees of freedom
required on each leg in parallel aiding elliptical foot motion.
The drawback being such types of robot demand high voltage
actuation. The robot is able to turn by a radius of 5cm when
the excitation frequency is shifted [1]. Locomotion through
vibration at a specific resonance frequency is a different
approach for robotics.
FIG. 5: Standford’s iSprawl
9. Snake robots
7. Scorpion
As the name suggests this robot ahs eight legs having three
joints actuated by DC motors and allow protraction/retraction.
With the use of DC motors each leg of this robot can lift 8
times its own weight The control system is based on the CPG
model and is distributed to one global and several local
computing units. Use of oscillators yield rhythmic motion
patterns. This also employs reflex control mechanism which
alongwith CPG should be able to overcome uneven terrains.
Effective limless motion strategies can be observed from a
snake. S0 was constructed using 12 segments connected with
servometers. But its working turned out to be disappointing
due to fauty weight distribution and energy loss due to friction.
S3 is equipped with two servomotors and two degree of
freedoms. Robot S5 has 32 joints. The latest one is without the
wheels and employs sonar and heat sensors and a compass.
FIG. 8: Snake robot S7
FIG. 6: Fraunhofer Institute’s Scorpion
8. Mesoscale robot quadruped
10. RoboTuna
RoboTuna is modeled after Bluefin Tuna. Its first generation
was 1.25m long underwater robot having aluminium skeleton
and a hull ribs covered in lyrca skin The movement of the
backbone is through sic servo meters who energize it through
cable and pulley system.
FIG. 7: Mesoscale robot quadruped
FIG. 9: RoboTuna
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11. VCUUV
VCUUV stands for The Vorticity Control Unmanned
Undersea Vehicle. As opposed to the RoboTuna, VCUUV is
fully autonomous. It consists of an energy source, hydraulic
actuator and a control unit. . Stabilized by the caudal fin the
VCUUV propels and maneuvers steady in the horizontal plane.
Tests of the maneuverability of the vehicle show that its
performance matches those of real tunas [1][6].
FIG. 12: Neural oscillator control network for Rodney
14. OCT-1b
The octopod robot OCT-1b is designed after the body of a
lobster. Its eight metal legs are each actuated by two
servomotors that cause them to lift and swing. The robot was
used for different walking pattern evolutions that were carried
out in 1998.
FIG. 10: VCUUV
12. Entomopter
It tries to ape locomotion strategies of crawling, flying and
maneuvering while flying insects. It uses an ultrasonic range
finder for navigation which aids autonomous navigation.
FIG. 13: Oct-1b
15. SONY quadruped robot
13. Rodney
Four legged robots each having three degrees of freedom
created by Sony Corporation installs infrared sensors and a
camera for fast color detection. Preprogrammed procedures
help the robot to stand up and reposition itself and start from
its nitial position
.
Rodney is ahexapod whose each leg is actuated y two
servomtors to produce limb lift and swing. The control
architecture for the servomotors of the robot was designed as a
simple neural oscillator network withweighted connections.
The output of neural network is then downloaded into the
hexapod and its results verified by human researchers.
FIG. 14: Sony quadruped robot
16. Koharo - Crawling and Jumping Deformable Soft
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Robot
the point of error and creates a new best locomotion behavior
to compensate for the physical damage [10].
The Koharo project uses deformation as an alternative
approach for locomotion over rough terrain. By contracting the
additional coils elastic potential energy gets stored and if
released fast enough makes the robot jump a distance twice its
diameter [8].
FIG. 17: Self-modeling robot
19. Golem
FIG. 15: Koharo
The Genetically Organized Lifelike Electro Mechanics
Golem uses the simple electromechanical systems with
autonomous physical construction using rapid prototyping
technologies. Bars, actuators and artificial neurons are the
elementary building blocks for its design. It also employs
microcontrollers and neural networks
17. Random morphology robots
The RM-robots has 6 servo-motors linked together randomly
by thin metal joints. Its seen that as the control architecture
grasps the uneven morphology and generates locomotion
patterns. The analysis of the best control programs shows that
faster forward locomotion is usually reached by a more
complex and therefore longer program [9].
FIG. 18: Golem
20. Genobots
The building blocks for the Genobots are simple bars
connected through fixed or actuated joints that have a moving
angle of 60 degrees. Frequency and phase offset of the
actuators are parameters of the form finding process and
ensure the co-development of morphology and control
architecture.
FIG. 16: Random morphology robot
18. Self-modeling robot
This system studies its own morphology from scratch and
updates itself on unexpected damage to its structure. During
tests, the systems reads the observed and the predicted
behavior and restartrs a model finding process. After several
cycles of testing and remodeling the system is able to discover
FIG. 19: Genobots
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[6] Anderson, J. M. & Chhabra, N. K. (2002) ’Maneuvering and
stability performance of a robotic tuna’, Integrative and
Comparative Biology, vol. 42, pp. 118- 126.
21. Nonaped
Its an attempt at evolving dynamic walking patterns for a
physical robot. The robot has two stewart platforms and have
12 degrees of freedom. Each pneumatic actuator is mounted
between two platforms with ball-and-socket joints. Individual
actuation of the pneumatic piston allows the platforms pitch,
roll and yaw freedom.
[7] Kingsley, D. A., Quinn, R. D. & Ritzmann, R. E. (2003) ’A
cockroach inspired robot with artificial muscles’, Proceedings of
the International Symposium on Adaptive Motion of Animals and
Machines, Kyoto, Japan.
[8] Shiotsu, A., Yamanaka, M., Matsuyama, Y., Nakanishi, H., Hara,
Y., Tsuboi, T., Iwade, T., Sugiyama, Y. & Hirai, S. (2005)
’Crawling and jumping soft robot KOHARO’, Proceedings of
36th International Symposium on Robotics, Tokyo
[9] Dittrich, P., B¨urgel, A. & Banzhaf, W. (1998) ’Learning to move a
robot with random morphology’ in Evolutionary Robotics - First
European Workshop, ed. P. Husband & J-A. Meyer, Springer
Verlag, Heidelberg.
[10] Bongard, J., Zykov, V. & Lipson, H. (2006), ’Resilient machines
through continuous self-modeling-, Science, vol. 314, no. 5802,
pp. 1118 - 1121.
[11] Hornby, G. S., Lipson, H. & Pollack, J. B. (2001) ’Evolution of
generative design systems for modular physical robots’, IEEE
International Conference on Robotics and Automation,
Piscataway, NJ.
FIG. 20: CCSLs Nonaped
[12] Clark, J. E., Cham, J. G., Bailey, S. A., Froehlich, E. M., Nahata,
P. K., Full, R. J. & Cutkosky, M. R. (2001) ’Biomimetic design
and fabrication of a hexapedal running robot’, International
Conference on Robotics and Automation, Seoul, Korea.
III. CONCLUSION
While animals well-suited to their environments and perfectly
capable adapting to and learning new things, robots are largely
per-determined and incapable of these same capabilities. The
aims of biomimetics are to give robots the same capability and
adaptability, even survivability, of their animal counterparts.
The ability to repair itself, learn from mistakes, adapt to suit
the environment, and even think are all goals to biomimicry.
With the use of more creative materials and ideas, robots will
soon be just as capable as animals, if not even better in many
regards.
REFERENCES
[1] Ayers, J., Davis, J. L. & Rudolph, A. (2002) Neurotechnology for
biomimetic robots, MIT Press, Cambrdge
[2] Bar-Cohen, Y. & Breazeal, C. (2003) Biologically inspired
intelligent robots, SPIE PRESS, Bellingham,Washington
[3] Gilbertson, R. G. (1993, 2000) Muscle wires project book, Mondotronics, San Rafael
[4] Iovine, J. (2002) Robots, androids, and animatrons, McGraw-Hill,
USA.
[5] Ashley, S. (2003) ’Artificial muscles’, Scientific American, vol. 289,
no. 4 , pp 5259
.