Abstract: The movement of points feet of the anthropomorphous robot in space occurs along some stable trajectory of a known form. A large number of modifications to the methods of control of biped robots indicate the fundamental complexity of the problem of stability of the program trajectory and, consequently, the stability of the control for the deviation for this trajectory. Existing gait generators use piecewise interpolation of program trajectories. This leads to jumps in the acceleration at the boundaries of sites. Another interpolation can be realized using differential equations with fractional derivatives. In work, the approach to synthesis of generators of program trajectories is considered. The resulting system of nonlinear differential equations describes a smooth trajectory of movement having rectilinear sites. The method is based on the theory of an asymptotic stability of invariant sets. The stability of such systems in the area of localization of oscillatory processes is investigated. The boundary of the area is a bounded closed surface. In the corresponding subspaces of the oscillatory circuits, the resulting stable limit cycles are curves having rectilinear sites. The solution of the problem is carried out by means of synthesis of a set of the continuous smooth controls with feedback. The necessary geometry of closed trajectories of movement is obtained due to the introduction of high-order nonlinearities in the control of stabilization systems. The offered method was used for the generation of trajectories of movement of point’s feet of the anthropomorphous robot. The synthesis of the robot's program movement was carried out by means of the inverse method.
Abstract: Underactuated biped robots control is one of the interesting topics in robotics. The main difficulties are its highly nonlinear dynamics, open-loop instability, and discrete event at the end of the gait. One of the methods to control underactuated systems is the partial feedback linearization, but it is not robust against uncertainties and disturbances that restrict its performance to control biped walking and running. In this paper, fuzzy partial feedback linearization is presented to overcome its drawback. Numerical simulations verify the effectiveness of the proposed method to generate stable and robust biped walking and running gaits.
Abstract: Recent fifteen years witnessed fast improvements in the field of humanoid robotics. The human-like robot structure is
more suitable to human environment with its supreme obstacle avoidance properties when compared with wheeled service robots.
However, the walking control for bipedal robots is a challenging task
due to their complex dynamics. Stable reference generation plays a very important role in control.
Linear Inverted Pendulum Model (LIPM) and the Zero Moment Point (ZMP) criterion are applied in a number of studies for stable
walking reference generation of biped walking robots. This paper follows this main approach too. We propose a natural and continuous ZMP reference trajectory for a stable and human-like walk. The ZMP reference trajectories move forward under the sole of the support foot when the robot body is supported by a single leg. Robot center of mass trajectory is obtained
from predefined ZMP reference trajectories by a Fourier series
approximation method. The Gibbs phenomenon problem common with Fourier approximations of discontinuous functions is avoided by employing continuous ZMP references. Also, these ZMP reference
trajectories possess pre-assigned single and double support phases,
which are very useful in experimental tuning work.
The ZMP based reference generation strategy is tested via threedimensional
full-dynamics simulations of a 12-degrees-of-freedom
biped robot model. Simulation results indicate that the proposed reference trajectory generation technique is successful.
Abstract: This paper summaries basic principles and concepts of
intelligent controls, implemented in humanoid robotics as well as
recent algorithms being devised for advanced control of humanoid
robots. Secondly, this paper presents a new approach neuro-fuzzy
system. We have included some simulating results from our
computational intelligence technique that will be applied to our
humanoid robot. Subsequently, we determine a relationship between
joint trajectories and located forces on robot-s foot through a
proposed neuro-fuzzy technique.
Abstract: This paper proposes a balance control scheme for a biped robot to trace an arbitrary path using image information. While moving, it estimates the zero moment point(ZMP) of the biped robot in the next step using a Kalman filter and renders an appropriate balanced pose of the robot. The ZMP can be calculated from the robot's pose, which is measured from the reference object image acquired by a CCD camera on the robot's head. For simplifying the kinematical model, the coordinates systems of individual joints of each leg are aligned and the robot motion is approximated as an inverted pendulum so that a simple linear dynamics, 3D-LIPM(3D-Linear Inverted Pendulum Mode) can be applied. The efficiency of the proposed algorithm has been proven by the experiments performed on unknown trajectory.
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: this paper presents a novel neural network controller
with composite adaptation low to improve the trajectory tracking
problems of biped robots comparing with classical controller. The
biped model has 5_link and 6 degrees of freedom and actuated by
Plated Pneumatic Artificial Muscle, which have a very high power to
weight ratio and it has large stoke compared to similar actuators. The
proposed controller employ a stable neural network in to approximate
unknown nonlinear functions in the robot dynamics, thereby
overcoming some limitation of conventional controllers such as PD
or adaptive controllers and guarantee good performance. This NN
controller significantly improve the accuracy requirements by
retraining the basic PD/PID loop, but adding an inner adaptive loop
that allows the controller to learn unknown parameters such as
friction coefficient, therefore improving tracking accuracy.
Simulation results plus graphical simulation in virtual reality show
that NN controller tracking performance is considerably better than
PD controller tracking performance.
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.