Bipedal Robotic System Utilizing Dynamic Balance and Adaptive Walking Gaits
1829 E. Donald St.
South Bend, IN 46613
1311 S. Logan St.
Mishawaka, IN 46544
Proposed Project Dates:
November 2012 to February 2013
To create a biped walking robot system that relies on dynamic
balance, motion sensors, and tactile sensors for real
in order to traverse unfamiliar
Numerous forms of motion can be
seen throughout nature. Humans
have a unique
upright bipedal walk.
In order to create robots that more efficiently interact with humans, the
robot must move with a huma
nlike bipedal walking gait.
The goal of this project is to create a
bipedal robot that utilizes dynamic balance and models after human walking. This will be
approached by analyzing human walking gaits at different speeds and inclines and by developing
relationship between these variables. Next a bipedal robot, modeled after human legs and torso
in dimensions and weight distributions, will be created for testing and analyzing the effectiveness
of the walking gait.
Finally, stability data will be incorporated into the gait using an
accelerometer and live data analysis for automatic corrections. The robot will be able to traverse
at multiple speeds and inclines
. Research into robotics, in particularly the study of
walking motion, has impacts in many different regions of science. First, biped research can help
in the understanding of how humans learn to
walk. Artificial legs have an impact on prosthetics
both military and civilian applications. Fin
ally, robotics is an area that is developing
quickly and spreading into everyone’s lives.
Mobility is vital for any creature’s survival. All throughout nature numerous forms of
movement are seen by animals and creatures of all sizes
swimming to flying to
many others, nature has solved the problems of
efficient locomotion in creatures.
Therefore when implementing movements into robotics, modeling natural locomotion of animals
is beneficial in order to crea
te effective mobility in the device.
Likewise, if the robot is intended
to interact primarily with humans in any human environment, the most effective solution is a
like robot utilizing a biped walking system.
“Less than half the Earth's landmass i
accessible to wheeled and tracked vehicles, yet people and animals can go alm
ost anywhere on
et al. 1).
Although accommodations can be made for wheeled robots in a human
environment, the most probabl
solution would be to design the robot
to move in a human
Much research has gone into differences in walking patterns and effective walking gaits.
In walking robotic systems, two major techniques can be
vement: dynamic balance or static balance.
These two are based on different principles for
design and function of the robot.
Static balance incorporates moving through several states of
static equilibrium ens
uring that the robot is always at a state of equilibrium
with dynamic bala
nce, the projected center of mass is allowed outside of the area inscribed by
the feet, and the walker may be falling
during parts of the gait cycle” (Kun et al. 1). This falling
motion is what is translated into the motion because the leg at some point b
reaks this fall allows
the robot to continue onward. This forms of control requires greater sophistication in the
mechanical device as well as in the programs running the robot.
A successful dynamically
balance robot has greater benefits that those of a s
tatically balanced robot.
Many difficulties arise when implementing bipedal motion into a robot. Several reasons
exist for this difficulty. “
The control goals (translating without falling) are not easily
decomposed in terms of the actions of individual a
The system is unstable, or only
marginally stable (depending on foot design).
Time delays in the control loop amplify stability
The system nonlinear dynamics and kinematics are difficult to model accurately, and
simplified models are
generally not adequate.
Other significant properties are difficult to model
accurately (gear stiction, gear play, foot flex, etc.).
Since the robot has no direct connection to an
inertial frame of reference, the controller must rely on often noisy sensors
force sensors and
accelerometers, for example) to represent the relationship between the rob
ot and the external
environment” (Kun et al. 1). Each one of these problems compounds the reasons why so few
successful bipedal robots are built and why eve
n fewer are put into practical applications.
Many different approaches have been
difficulties in dynamically
balanced bipedal robots. In the development of a walking gait, approaches such as learning
algorithms in the robots have
shown results of success based upon human learning methods for
bipedal control. Several investigations have used computer models to approximate a biped robot
that physically exists in order to develop a walking gait through computer trials before ever
plementing it into the robot. Some research has
utilized neural networks in conjunction with
adaptive control to provide a walking pattern. Finally, all of these studies aim to produce the
like and efficient gait and method for finding that pa
ttern that will be implemented
into the biped robots.
To create a biped walking robot system that relies on
dynamic balance, motion sensors, and tactile sensors for real
world data in order to traverse
The process of engineering a biped robot must be separated into portions of work that
serve as benchmarks towards a successful outcome. Each phase must be accomplished before
advancing to the next goal. F
benchmark goals are in place in order
research towards the final goal of a bipedal robot that adapts its gait to provide balance and
stabilization over various inclines in the terrain. These intermediate goals are as follows:
analyze human walking gaits at various inc
lines in order to create scalable relationships between
the functions of the gaits of different inclines,
create a biped robot in proportion to a human in
size and mass in order to implement and test the walking gaits,
write a program for the
r to send to
that performs a basic walking gait, 4) update the
walking gait to change the speed of the legs based on input from the computer, and 5) finally
update the program and hardware to implement sagittal balance into the robot’s
allowing it to traverse at different inclines.
To analyze the walking gait, the angles of the joints in the legs must be measured
continuously to gather data of the motion of that joint over a single period in that gait. Physical
collection can be performed by placing an angle sensor at each joint to collect data
throughout the time of one period. This angle sensor is a variable resistor, or a potentiometer
can be used to vary a
voltage based on its
angle. This vol
tage would be re
d by a
microcontroller and sent to a desktop computer via serial where it can
then be analyzed
and fit to
a polynomial function
Each joint would be measured and interpreted separately
for one period
of the gait
. This process is then repe
ated for different speeds and angles of incline of the walking
After fitting a polynomial function to the points, t
hese functions can then be analyzed to
find a scalable relationship between different angles as well as between different speeds.
The next step of the process is to build
the first pair of bipedal legs. The basic version
needs several components in order to operate which are as follow: a power supply, leg actuation
at the hips and knees, a microcontroller, and a computer to operate t
supply will be a
battery with voltage regulators for the microcontrollers and
integrated circuits. The leg actuation at the hips and knees will require a large
amount of torque.
For these joints, a car windshield wiper motor will be used along with a potentiometer for
position feedback. These large motors will be powered using a circuit based around a
motor driver. Control will be provided to these u
sing a Propeller microcontroller
all of the motors to be controlled simultaneously
. A second Propeller microcontroller will be
interface with the computer as well as the accelerometer. The structure of the legs will
be built using
aluminum pieces because of its little weight and strength. The form of the robot
will roughly follow the shape of a human legs and torso focusing on accurately distributing the
weight across proper dimensions.
The next steps involve creating
a program on the on the computer to receive
serial data on the position of the accelerometer and to send updated motor signals based on the
accelerometer readings and the corresponding scaling factors present. Connected to the
is a seri
al to USB interface that allows the microcontroller to speak to the
program in the Raspberry Pi computer.
Using this interaction, the computer will read the
accelerometer data and analyze it based on previous trials. Depending on its variation
tandard stabilities at the given time
, it will send updated motor commands
to correct for the
various instabilities in the robot because of the terrain it is encountering. With all of these goals
reached, a biped robot system with capabilities of traversi
ng various terrains will have
successfully been created.
influences a broad range of categories.
First of all, it
affects he scientific understanding of human walking gaits. This includes how they function
which can lead to an understanding of
how people learn to walk. This research also affects
prosthetic devices. Developing walking gaits and robo
ts that can accurately perform a human
walk can lead to new designs of prosthetics that can incorporate automated leg motion allowing
prosthetics to be used as treatments for a larger variety of treatments. This can also affect the
military giving them ne
w forms of transportation for carrying heavy loads across uneven terrains.
Finally, this has an everyday application where walking robots will one day be implemented into
everyone’s daily lives.
Educationally, this project is giving me the opportunity
to research an area that I have
been interested in my whole life.
Over the past summer, I built and programmed a robotic arm
plotter that utilized inverse kinematics to draw images sent to it by a computer. This experience
made me want to pursue this fie
ld of robotics even more. After completing the bipedal robotic
I will have learned many new useful techniques that I can use in the future for my
career. This will be especially helpful for me because I plan to pursue a degree in engineerin
college next year. With this project complete, I plan to enter it into the Indiana Junior Science
and Humanities Symposium, the Northern Indiana Regional Science and Engineering Fair, and
any competitions after these.
12VDC Wiper Motor
Connection Socket Vertical 40 position DIP
IC EEPROM 256KBIT 400KHZ 8DIP
Connection IC Socket Vertical 8
Rotary Potentiometer 10K OHM
L298 IC Driver Full Dual 15 Multiwatt
Breakaway Connection Header 40
Connection Receptors 2MM VERT
Memsic 2125 Accelerometer
Prop Plug (Serial to USB connection)
5.000 MHZ Crystal
3A Schottky Diode
Blank Single Sided Printed Circuit Board
Jameco Value Pro Prototyping Kit
Black and Decker 300 Amp portable jump
16 Conductor ribbon
pi / prog
Other Equipment and Supplies
All of the expendable items requested are necessary for the construction of the bipedal
robotic legs. Many of the items have been specifically chosen because of their economic
efficiency such as the 12VDC Motor Wipers and
the Parallax Propeller microcontroller. The
microcontroller’s support circuitry was budgeted unassembled so the costs would remain low.
Kun, Andrew L., and W. Thomas Miller, III. "Adaptive Dynamic Balance of a Biped Robot
Using Neural Netwo
Robotics Laboratory, ECE Dept., University of New
Raibert, Marc, Kevin Blankespoor, Gabriel Nelson, and Rob Playter. "BigDog, the Rough
Terrain Quadruped Robot."
The International Federation of Automatic Control