Biped robots have gained much attention for decades. A variety of researches has been conducted to make them able to assist or even substitute for humans in performing special tasks. In addition, studying biped robots is important in order to understand the human locomotion and to develop and improve control strategies for prosthetic and orthotic limbs. Some challenges encountered in the design of biped robots are: (1) biped robots have unstable structures due to the passive joint located at the unilateral foot-ground contact. (2) They have different configuration when switching from walking phase to another. During the singlesupport phase, the robot is under-actuated, while turning into an over-actuated system during the double-support phase. (3) Biped robots have many degrees of freedom (DOFs). (4) Biped robots interact with different unknown environments. Therefore, this work attempts to investigate and resolve different issues encountered in dynamics, walking pattern generators and control of biped robots; the details as follows: • Dynamics Two walking patterns have been modeled using two well-known formulations: Lagrangian and the modified recursive Newton-Euler (N-E) formulations. The first walking pattern moves with 6 DOFs during the single support phase (SSP) changing its configuration with 7 DOFs during the double support phase (DSP) (the stance foot will move directly during the DSP). Whereas the other walking pattern has 6 DOFs during all walking phases (the SSP and the two sub-phases of the DSP); the stance foot will be fixed during the first sub-phase of the DSP. These two walking pattern are different in configuration and number of phases during the DSP. To resolve the problem of over-actuation, a linear transition function is proposed to ensure smooth transition for the biped from the SSP to the DSP and vice versa. If we assume ideal dynamic response, this strategy can resolve the discontinuity in input control torque and ground reaction forces. • Walking pattern generators Two methods have been used to generate walking patterns of biped mechanism which are (1) optimal control theory and (2) center of gravity (COG)-based model. Computational optimal control has been performed to investigate the effects of some imposed constraints on biped locomotion, such as enforcing swing foot to move level to the ground, hip motion with constant height etc. finite difference approach has been used to transcribe infinite dimensional optimal control problem into finite dimensional suboptimal control problem. Then parameter optimization has been used to get suboptimal trajectory of the biped with the imposing different constraints. In general, any artificially imposed constraint to biped locomotion can lead to increase in value of input control torques. On the other hand, suboptimal trajectory of biped robot during complete gait cycle had been accomplished with different cases such that continuous dynamic response occurs. Enforcing the biped locomotion to move with linear transition of zero-moment point (ZMP) during the DSP can lead to more energy consumption. Using the simple COG-based model, a comparative study has been conducted to generate continuous motion for COG of the biped; all these methods depend on linear pendulum model. It has been shown all these methods are equivalent. On the other hand, the effect of foot configuration has been investigated. Foot rotation can improve biped configuration at heel strike by controlling foot angle. In addition, foot motion with impact can give some freedom and uniform biped configuration compared with motion without impact. To compensate for the deviation of ZMP trajectory due to approximate model of the COG, a novel strategy has been proposed to satisfy kinematic and dynamic constraints, as well as singularity condition. A stable motion has been obtained for the target walking patterns. • Low-level control Two control schemes have been proposed based on dynamics formulations which are conventional adaptive control based on local approximation technique and Lagrangian formulation, and virtual decomposition control (VDC) based on local approximation technique and recursive N-E formulation. In the first approach (conventional control), a new representation of dynamic matrices has been coined which is computationally efficient than other representation (sparse-base representation, Kronecker product etc.). Controller structures for the SSP and the DSP have been designed in details. Since adaptive control assumes no prior knowledge of estimated weighting matrices; therefore, zero input control torques could be result in at the beginning of each phase. Consequently, discontinuous dynamic response could result. The VDC is an efficient tool for complex robotic system such as biped robot. Therefore each subsystem (link, joint) has been controlled using adaptive approximation–based VDC. A novel optimization technique has been used to deal with continuous dynamic response; however, using zero initial weighting matrices for estimation dynamic matrices and vectors could result in zero input control at beginning of each walking phases.
In this research the results of applying Artificial Neural Networks with modified activation function to perform the online and offline identification of four Degrees of Freedom (4-DOF) Selective Compliance Assembly Robot Arm (SCARA) manipulator robot will be described. The proposed model of identification strategy consists of a feed-forward neural network with a modified activation function that operates in parallel with the SCARA robot model. Feed-Forward Neural Networks (FFNN) which have been trained online and offline have been used, without requiring any previous knowledge about the system to be identified. The activation function that is used in the hidden layer in FFNN is a modified version of the wavelet function. This approach ha
... Show MoreIn this research the results of applying Artificial Neural Networks with modified activation function to
perform the online and offline identification of four Degrees of Freedom (4-DOF) Selective Compliance
Assembly Robot Arm (SCARA) manipulator robot will be described. The proposed model of
identification strategy consists of a feed-forward neural network with a modified activation function that
operates in parallel with the SCARA robot model. Feed-Forward Neural Networks (FFNN) which have
been trained online and offline have been used, without requiring any previous knowledge about the
system to be identified. The activation function that is used in the hidden layer in FFNN is a modified
version of the wavelet func
The applications of mobile robots in rescue scenarios, surviving to search, and exploration for outdoor navigation have received increasing attention due to their promising prospects. In this paper, a simulation of a differential wheeled mobile robot was presented, implementing a Global Positioning System (GPS) data points to specified starting points, final destination, and total error.
In this work, a simple kinematic controller for polar coordinate trajectory tracking is developed. The tracking between two points, pose to pose, was specified by using the GPS data points. After that, the geodesy (GEO) formulation was used to convert the geodesy coordinate to Euclidean or polar coordinate. The Haversine equation
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Background: Unlike normal EEG patterns, the epileptiform abnormal pattern is characterized by different mor phologies such as the high-frequency oscillations (HFOs) of ripples on spikes, spikes and waves, continuous and sporadic spikes, and ploy2 spikes. Several studies have reported that HFOs can be novel biomarkers in human epilepsy study. S) Method: To regenerate and investigate these patterns, we have proposed three large scale brain network models (BNM by linking the neural mass model (NMM) of Stefanescu-Jirsa 2D (S-J 2D) with our own structural con nectivity derived from the realistic biological data, so called, large-scale connectivity connectome. These models include multiple network connectivity of brain regions at different
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Background: Lateral cephalometric radiography is commonly used as a standard tool in orthodontic assessment and treatment planning. This study aimed to determine the tongue and surrounding space area in a sample of Iraqi adults with class I dental and skeletal pattern. Materials and methods: The study included thirty healthy subjects (15 males and 15 females) with an age ranged between 23-34 years and class I dental and skeletal pattern with no history of any sleep related disorders. The assessed cephalometric measurement included length and height of the tongue and position of hyoid bone from cervical line. Descriptive statistics were obtained for the data. Genders difference was evaluated by independent sample t-test. Results: There wer
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In this paper, a cognitive system based on a nonlinear neural controller and intelligent algorithm that will guide an autonomous mobile robot during continuous path-tracking and navigate over solid obstacles with avoidance was proposed. The goal of the proposed structure is to plan and track the reference path equation for the autonomous mobile robot in the mining environment to avoid the obstacles and reach to the target position by using intelligent optimization algorithms. Particle Swarm Optimization (PSO) and Artificial Bee Colony (ABC) Algorithms are used to finding the solutions of the mobile robot navigation problems in the mine by searching the optimal paths and finding the reference path equation of the optimal
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Magneto-rheological (MR) valve is one of the devices generally used to control the speed of Hydraulic actuator of MR fluid. The performance of valve depends on the magnetic circuit design. Present study deals with a new design of MR valve. A mathematical model for the MR valve is developed and the simulation is carried out to evaluate the newly developed MR valve. The design of the magnetic circuit is accomplished by magnetic finite element software such as Finite Element Method Magnetic (FEMMR). The model dimensions of MR valve, material properties are taken into account. The results of analysis are presented in terms of magnetic strength H and magnetic flux density B. The simulation results based on the proposed model indicate that the ef
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