Optimization and Analysis of Underactuated Linkage Robotic Finger

In this study it is required to maximize the transmission performance, which is leading to increase the transmitted torque from the actuated joints to the underactuated joints through transmission mechanism. Accordingly grasping forces in finger phalanges will increase. Studying the four bar mechanism parameters of a specific configuration within defined limits led to the linkage transmission defect parameter, which play a major role in deciding the linkage performance, used as optimization objective function to be minimized. This study presents an optimization procedure carried out using matlab fminunc function, formulated by using Freudenstein's equations to be applied on a (Cassino-Underactuated-Multifinger-Hand) design , using  one finger and a thumb .A mathematical model of grasping forces of the finger were introduced taking into account the solid links in the( Ca.U.M.Ha)  robotic finger . Keywords: Linkage , underactuated, optimizatio

The Mechanism Analysis of Underactuated Robotic Finger for Optimum Grasping Using Gradient Descent Method

This study was devoted in investigating the optimum geometric parameters for underactuated linkage three phalanges robotic finger. New kinematic and kinetic equations of grasping were derived in this research taking into account the angle for the ternary solid links of the four-bar linkages. To obtain the target of optimization, a gradient descent method was used which consists of three stages to find the optimal geometric parameters with high accuracy. Five criteria were selected to find the optimal solution by using multi objectives function algorithm, these are percentage of the grasping stability, the grasp forces, squeezing force, Mimic function for grasping task, and transmission angle for grasping operation. Gradient descent method starts by detecting the optimal geometric parameters for each criterion and choosing the best geometric parameters from the five criteria functions. At the optimum solution, the underactuated robotic finger prototype was built from hard Polylactic acid (PLA) plastic using rapid prototyping and was tested performance by grasping objects. Finally, the results have been shown that the robotic finger adapts to the wanted configurations

Position Control of Linkage Underactuated Robotic Hand

In this study a proposed PID control system for (Ca.U.M.Ha) robotic hand with a finger and a thumb introduced, to control grasping cylindrical objects made from different materials soft and hard within a range of (48-150) mm in diameter . A samples of PID response figures for object that need just a finger, and object that needs a finger with a thumb introduced in additional to the figures of actuators voltage needed for both cases through grasping. Keywords: Linkage , underactuated, position  PID contro

Estimation the Natural Frequencies of a Cracked Shaft Based on Finite Element Modeling and Artificial Neural Network

The early detection of faults in rotating systems considers an integral approach that has received considerable attention from the industrial sector, as it contributes to preventing catastrophic failures in machines. In this research, the natural frequencies of a shaft, when it is healthy and when cracks with different depths are introduced, have been calculated. The deviation of the computed natural frequencies from the healthy ones is counted as a sign of the presence of an abnormality in the system. For this intention, the finite element analysis (FEA) method based on ANSYS software has been utilized to obtain the first five natural frequencies of the shaft when there is a crack of different severity at different positions. The results of the FEA are used for designing an artificial neural network (ANN) model that can be easily used to predict the first five natural frequencies of the shaft based on just the crack’s position and depth. Finally, the predicted natural frequencies by the deigned ANN have been compared to their peers that were computed using the FEA method. The absolute error percentage has then been calculated and used to get an indication of how close the result of both techniques is. The recorded highest error percentage was 0.67%, which is quite small and referring to that the designed ANN can accurately predict the natural frequencies of rotating systems