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In this paper we introduced a new method for motion control in humanoid robots. The problem of movement learning specially dance and repetitive actions of human beings to humanoid robots is a major challenge in the field of robotics. Imitation learning, which is a subset of supervised learning, is a main form to teach complex tasks to the humanoid robot, and the accordingly is based on that an artificial system can imitate a lot of information through learning from human trainer. The main technique is using Central Pattern Generators structures which is able to produce required motion trajectories based on imitation learning. Systematic design of this these neural networks is main problem which is solved in this paper. The proposed model is a basic paradigm for imitation learning in the humanoid robots which do not required direct design of controller and programming. The proposed model has many benefits including smooth walking patterns and modulation during imitation. Simulation results of this learning system in the robot simulator (WEBOTS) that has been linked with MATLAB software and its implementation on a NAO robot demonstrate that the robot has learned desired motion with high accuracy. This model can be extended and used in the Nao soccer player both for the standard platform and the 3D soccer simulation leagues of Robocup SPL competitions to train different types of motions.

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In this paper, the effects of the addition of an active toe joint on a 2D humanoid robot with heel-off and toe-off motions are studied. To this end, the trajectories of joints and links are designed firstly. After gait planning, the dynamic model of the humanoid robot in different phases of motion is derived using Kane and Lagrange methods. Then, the veracity of the derived dynamic model is demonstrated by two different methods. The under-study model, is in accordance with the features of SURENA III, which is a humanoid robot designed and fabricated at the Center of Advanced Systems and Technologies (CAST) located in University of Tehran. Afterward, the optimization procedure is done by selection of two different goal functions; one of them minimizes the energy consumption and the other maximizes the stability of the robot. At last, the obtained results are presented. According to the results, there is an optimum value for heel-off and toe-off angles in each velocity which minimizes the consumption of energy. The results also show that, the heel-off angle does not have any significant effects on the stability of the robot while increasing the toe-off angle improves the stability of motion. Finally, the effects of mass and length of the toe joint is inspected. These inspections suggest that heavier toe joints cause an increase in both energy consumption and stability of the robot while increasing the length of the toe joint does not have any effects on both goal functions.

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In this paper, to improve the accuracy of the one-mass and three-mass inverted pendulum models, which have been used for generating real-time walking patterns for biped robots, we propose a novel model based on the three-mass inverted pendulum. The proposed model employs an approximation of moment of inertia of the swing leg to improve the accuracy of the three-mass inverted pendulum in estimating dynamic behavior of the robot. In order to show significance of the proposed model, trajectories for the Center of Mass (CoM) are obtained using the three models, based on a desired ZMP trajectory. The task space trajectories, then, are mapped into the joint space, using inverse kinematics. Having the joint space variables, the actual ZMPs for the three obtained walking patterns are computed and compared. This comparison well shows merit of the proposed model in estimating dynamic behavior of the robot, especially for walking with relatively high speeds. The kinematic and dynamic properties of the models in this paper are based on the humanoid robot SURENA III, which has been designed and fabricated in the Center of Advanced System and Technologies (CAST), university of Tehran.

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Due to necessity of increasing performance in new generations of the humanoid robots, in this paper, a novel power transmission mechanism to actuate the ankle joint of a humanoid robot is presented in order to increase the motion speed of SURENAIII humanoid robot. Also, the energy consumption of the proposed and the previous mechanisms are studied. In the proposed mechanism, the actuators of the ankle joint are located in the shank link. Then, a combined timing belt-pulley and a harmonic drive module are exploited for power transmission for the pitch joint. Also, the roll joint drive has employed a roller screw. In order to validate the design procedure, the simulation results of the robot are compared with the experimental data. The results reveal that the dynamic model is fairly matched to the real behavior of the robot. Also, the revolutionary genetic algorithm is employed to optimize the effective path planning parameters with respect to the minimum knee joint torque. This optimization procedure which is employed in robot walking on flat terrains consist of straight motion, ensures the robot's stability. As a result, the optimal path planning parameters for proposed mechanism are obtained in such a way that has decreased the actuating torques of lower-body of SURENAIII. Also, the proposed mechanism can achieve using lighter motors and getting the robot faster by means of mass reduction of foot.

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In this paper a controller has been presented based on the predictive control to drive and control the bipedal Nao robot. One of the challenges in the practical applying of these types of controllers is their high computational loading and the time-consuming control operations in each time step, in which it is suggested to use Laguerre Functions to reduce the computational loading of the predictive controller. In this study, at first using the conventional methods for the identification, and via the real data obtained from the Nao robot in Mechatronics research center of Qazvin Azad University, a proper model is proposed for walking the Nao robot which is considered as a two-dimensional motion in the plane. Then a controller will be designed to control the robot motion using the model based predictive controller. The purpose of this control approach in the first place is to stabilize the walking of the robot and then to guide and keep it on the desired trajectory, so that this trajectory tracking can be performed well as much as possible. Moreover, in order to evaluate the efficiency of the proposed controller, this controller has been compared with a proportional-integral-derivative controller and will be studied. The simulation results show the effectiveness of the proposed controller performance in the robot trajectory tracking, which finally comparing the obtained results from both of the control approaches, indicates the efficiency and different capabilities of the proposed method in this study.

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In this paper a push recovery controller for balancing humanoid robot under severe pushes for situation that contact surface is small is presented. Human response to progressively increasing disturbances can be categorized into three strategies: ankle strategy, hip strategy and stepping strategy. The reaction of human to external disturbances in the situations that contact surface is small or stepping is not possible is generating upper body angular momentum. In this way in this paper, a single model predictive controller scheme is employed to controlling the capture point by modulating zero moment point and centroidal moment pivot. The proposed algorithm is capable of recovering balance of humanoid robot under severe pushes without stepping in situation that contact surface is shrunked to a strip. The goal of the proposed controller is to control the capture point, employing the centroidal moment pivot when the capture point is out of the support polygon, and/or the zero moment point when the capture point is inside the support polygon. The merit of proposed algorithm is shown successfully in different simulation scenarios using characteristic of SURENA III humanoid robot.

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This paper investigated the imitation of human motions by a NAO humanoid robot which can be regarded as a human-robot interaction research. In this research, first, human motion is captured by a Kinect 3-dimentional camera through a Robot Operating System (ROS) package. Captured motion is then mapped into the robot’s dimension due to the differences between human and humanoid robot dimensions. After performing the mapping procedure, the solution of both forward and inverse kinematic problem of the robot are solved. To this end, a “Distal” form of forward kinematics solution of the NAO humanoid robot is computed and based on the latter form an analytical inverse kinematics solution for the whole-body imitation purpose is used. The foregoing issue, as one of the contributions of this paper, can be regarded as one of the main reason for obtaining a smooth imitation. In order to keep the robot’s stability during the imitation, an ankle strategy based on a Linear Inverted Pendulum Model (LIPM) and the Ground projection of the Center of Mass (GCoM) criteria is introduced. Moreover, the latter LIPM is controlled by a Proportional-Integral-Derivative (PID) controller for two cases, namely, double and single support phases. Considering the limitation on the motion capture device, from experimental and simulation results obtained by implementing the proposed method on a NAO-H25 Version4 it can be inferred that the robot exhibits an accurate, smooth and fast whole-body motion imitation.

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This article examines Zoha Kazemi’s novel, Humanoid, from the perspective of memory studies and pursues two goals: to delve into the effects of advanced technologies, in the dystopian society of the novel, on characters’ memories and the change in their human identity; and to examine the relation between the act of narrating in the novel and memory and its functions, and its relation with the formation of the political act and social reform. This research is necessary as Humanoid came into being in an era of rapid technological change whereby the impact of these developments on mind, memory, individual and collective identity, and culture is inevitable. Thus, the investigation of these concerns in the crucible of literature is a timely response. This study adopts theories from the field of memory studies and provides a close reading of parts of the novel whenever required. In this way, focal issues such as declarative memory and procedural memory, the connection of memory with technology and the formation of identity, and the connection of memory with politics and narrative in the novel will be expounded. The results show that modern technologies in the field of biology in the dystopian society of Humanoid are tools to control and shape the human identity, and put it on its path of evolution towards the post-human state. On the other hand, narrative can be considered as a tool to preserve human identity whereby it leads to political action, and moves the society towards awareness, resistance and change.