Abstract: We proposed the use of a Toda-Rayleigh ring as a
central pattern generator (CPG) for controlling hexapodal robots. We
show that the ring composed of six Toda-Rayleigh units coupled to
the limb actuators reproduces the most common hexapodal gaits. We
provide an electrical circuit implementation of the CPG and test our
theoretical results obtaining fixed gaits. Then we propose a method
of incorporation of the actuator (motor) dynamics in the CPG. With
this approach we close the loop CPG – environment – CPG, thus
obtaining a decentralized model for the leg control that does not
require higher level intervention to the CPG during locomotion in
a nonhomogeneous environments. The gaits generated by the novel
CPG are not fixed, but adapt to the current robot bahvior.
Abstract: The aim of this paper is to present the kinematic
analysis and mechanism design of an assistive robotic leg for
hemiplegic and hemiparetic patients. In this work, the priority is to
design and develop the lightweight, effective and single driver
mechanism on the basis of experimental hip and knee angles- data for
walking speed of 1 km/h. A mechanism of cam-follower with three
links is suggested for this purpose. The kinematic analysis is carried
out and analysed using commercialized MATLAB software based on
the prototype-s links sizes and kinematic relationships. In order to
verify the kinematic analysis of the prototype, kinematic analysis data
are compared with the experimental data. A good agreement between
them proves that the anthropomorphic design of the lower extremity
exoskeleton follows the human walking gait.
Abstract: The purpose of this study is to find natural gait of
biped robot such as human being by analyzing the COG (Center Of
Gravity) trajectory of human being's gait. It is discovered that human
beings gait naturally maintain the stability and use the minimum
energy. This paper intends to find the natural gait pattern of biped
robot using the minimum energy as well as maintaining the stability by
analyzing the human's gait pattern that is measured from gait image on
the sagittal plane and COG trajectory on the frontal plane. It is not
possible to apply the torques of human's articulation to those of biped
robot's because they have different degrees of freedom. Nonetheless,
human and 5-link biped robots are similar in kinematics. For this, we
generate gait pattern of the 5-link biped robot by using the GA
algorithm of adaptation gait pattern which utilize the human's ZMP
(Zero Moment Point) and torque of all articulation that are measured
from human's gait pattern. The algorithm proposed creates biped
robot's fluent gait pattern as that of human being's and to minimize
energy consumption because the gait pattern of the 5-link biped robot
model is modeled after consideration about the torque of human's each
articulation on the sagittal plane and ZMP trajectory on the frontal
plane. This paper demonstrate that the algorithm proposed is superior
by evaluating 2 kinds of the 5-link biped robot applied to each gait
patterns generated both in the general way using inverse kinematics
and in the special way in which by considering visuality and
efficiency.
Abstract: Children with hemiplgic cerebral palsy often walk
with diminished reciprocal arm swing so the purpose of this study
was to describe kinematic characteristics in children with hemiplegic
cerebral palsy (CP) during the gait suphases, and find if there is a
correlation between upper(shoulder and elbow) and lower(hip, knee,
and ankle) limb joints either in involved or uninvolved.48 children
with hemiplegic cerebral palsy (18boys, 30girls) with an average age
of (5.1±0.87) years were selected randomly to evaluate joint angles
during gait by 3D motion analysis system with 6 pro reflex cameras
in a sagittal plane for both sides of the body. The results showed
increased shoulder and elbow flexion, increased hip angular
displacement, decreased knee and ankle arcs during gait cycle, also
there is correlation between shoulder and elbow to hip, knee, and
ankle joints during various subphases of gait.
Abstract: This paper proposes a method of adaptively generating a gait pattern of biped robot. The gait synthesis is based on human's gait pattern analysis. The proposed method can easily be applied to generate the natural and stable gait pattern of any biped robot. To analyze the human's gait pattern, sequential images of the human's gait on the sagittal plane are acquired from which the gait control values are extracted. The gait pattern of biped robot on the sagittal plane is adaptively generated by a genetic algorithm using the human's gait control values. However, gait trajectories of the biped robot on the sagittal plane are not enough to construct the complete gait pattern because the biped robot moves on 3-dimension space. Therefore, the gait pattern on the frontal plane, generated from Zero Moment Point (ZMP), is added to the gait one acquired on the sagittal plane. Consequently, the natural and stable walking pattern for the biped robot is obtained.
Abstract: The atmospheric pressure plasma torch with a direct
current arc discharge stabilized by water vapor vortex was
experimentally investigated. Overheated up to 450K water vapor was
used as plasma forming gas. Plasma torch design is one of the most
important factors leading to a stable operation of the device. The
electrical and thermal characteristics of the plasma torch were
determined during the experimental investigations. The design and
the basic characteristics of the water vapor plasma torch are presented
in the paper.
Plasma torches with the electric arc stabilized by water vapor
vortex provide special performance characteristics in some plasma
processing applications such as thermal plasma neutralization and
destruction of organic wastes enabling to extract high caloric value
synthesis gas as by-product of the process. Syngas could be used as a
surrogate fuel partly replacing the dependence on the fossil fuels or
used as a feedstock for hydrogen, methanol production.
Abstract: Biometrics methods include recognition techniques
such as fingerprint, iris, hand geometry, voice, face, ears and gait. The gait recognition approach has some advantages, for example it
does not need the prior concern of the observed subject and it can
record many biometric features in order to make deeper analysis, but
most of the research proposals use high computational cost. This
paper shows a gait recognition system with feature subtraction on a
bundle rectangle drawn over the observed person. Statistical results
within a database of 500 videos are shown.
Abstract: This paper presents a real time force sensing
instrument that is designed for human gait analysis purposes. It is
capable of recording and monitoring ground reaction forces exerted
by human foot during various activities such as walking, running and
jumping in real time. In overall, force sensing mat mainly consists of
three elements: the force sensing mat, signal conditioning circuit and
data acquisition device. Force sensing mat is the mat that contains an
array of force sensing elements. To control and process the incoming
signal from the force sensing mat, Force-Logger and Force-Reloader
are developed using National Instrument Labview. This paper
describes the architecture of the force sensing mat, signal
conditioning circuit and the real time streaming of the incoming data
from the force sensing mat. Additionally, a preliminary experiment
dataset is presented in this paper.
Abstract: Human identification at a distance has recently gained
growing interest from computer vision researchers. Gait recognition
aims essentially to address this problem by identifying people based
on the way they walk [1]. Gait recognition has 3 steps. The first step
is preprocessing, the second step is feature extraction and the third
one is classification. This paper focuses on the classification step that
is essential to increase the CCR (Correct Classification Rate).
Multilayer Perceptron (MLP) is used in this work. Neural Networks
imitate the human brain to perform intelligent tasks [3].They can
represent complicated relationships between input and output and
acquire knowledge about these relationships directly from the data
[2]. In this paper we apply MLP NN for 11 views in our database and
compare the CCR values for these views. Experiments are performed
with the NLPR databases, and the effectiveness of the proposed
method for gait recognition is demonstrated.
Abstract: For stable bipedal gait generation on the level floor,
efficient restoring of mechanical energy lost by heel collision at
the ground is necessary. Parametric excitation principle is one of
the solutions. We dealt with the robot-s total center of mass as
an inverted pendulum to consider the total dynamics of the robot.
Parametrically excited walking requires the use of continuous target
trajectory that is close to discontinuous optimal trajectory. In this
paper, we proposed the new target trajectory based on a position
in the walking direction. We surveyed relations between walking
performance and the parameters that form the target trajectory via
numerical simulations. As a result, it was found that our target
trajectory has the similar characteristics of a parametrically excited
inverted pendulum.
Abstract: This paper presents a real time force sensing instrument that is designed for human gait analysis purposes. This instrument mainly consists of three main elements: the force sensing mat, signal conditioning and switching circuit and data acquisition
device. In order to control and to process the incoming signals from the force sensing mat, Force-Logger and Force-Reloader program are
developed using Labview 8.0. This paper describes the architecture of the force sensing mat, signal conditioning and switching circuit and the real time streaming of the incoming data from the force
sensing mat.
Abstract: In this paper we present a technique to speed up
ICA based on the idea of reducing the dimensionality of the data
set preserving the quality of the results. In particular we refer to
FastICA algorithm which uses the Kurtosis as statistical property
to be maximized. By performing a particular Johnson-Lindenstrauss
like projection of the data set, we find the minimum dimensionality
reduction rate ¤ü, defined as the ratio between the size k of the reduced
space and the original one d, which guarantees a narrow confidence
interval of such estimator with high confidence level. The derived
dimensionality reduction rate depends on a system control parameter
β easily computed a priori on the basis of the observations only.
Extensive simulations have been done on different sets of real world
signals. They show that actually the dimensionality reduction is very
high, it preserves the quality of the decomposition and impressively
speeds up FastICA. On the other hand, a set of signals, on which the
estimated reduction rate is greater than 1, exhibits bad decomposition
results if reduced, thus validating the reliability of the parameter β.
We are confident that our method will lead to a better approach to
real time applications.
Abstract: Current image-based individual human recognition
methods, such as fingerprints, face, or iris biometric modalities
generally require a cooperative subject, views from certain aspects,
and physical contact or close proximity. These methods cannot
reliably recognize non-cooperating individuals at a distance in the
real world under changing environmental conditions. Gait, which
concerns recognizing individuals by the way they walk, is a relatively
new biometric without these disadvantages. The inherent gait
characteristic of an individual makes it irreplaceable and useful in
visual surveillance.
In this paper, an efficient gait recognition system for human
identification by extracting two features namely width vector of
the binary silhouette and the MPEG-7-based region-based shape
descriptors is proposed. In the proposed method, foreground objects
i.e., human and other moving objects are extracted by estimating
background information by a Gaussian Mixture Model (GMM) and
subsequently, median filtering operation is performed for removing
noises in the background subtracted image. A moving target classification
algorithm is used to separate human being (i.e., pedestrian)
from other foreground objects (viz., vehicles). Shape and boundary
information is used in the moving target classification algorithm.
Subsequently, width vector of the outer contour of binary silhouette
and the MPEG-7 Angular Radial Transform coefficients are taken as
the feature vector. Next, the Principal Component Analysis (PCA)
is applied to the selected feature vector to reduce its dimensionality.
These extracted feature vectors are used to train an Hidden Markov
Model (HMM) for identification of some individuals. The proposed
system is evaluated using some gait sequences and the experimental
results show the efficacy of the proposed algorithm.