Sharif Digital Repository

Color quantization is a technique for processing and reduction colors in image. The purposes of color quantization are displaying images on limited hardware, reduction use of storage media and accelerating image sending time. In this paper a hybrid algorithm of GA and Particle Swarm Optimization algorithms with FCM algorithm is proposed. Finally, some of color quantization algorithms are reviewed and compared with proposed algorithm. The results demonstrate Superior performance of proposed algorithm in comparison with other color quantization algorithms  

To have a complete model of a thunniform Fish-Robot, models of both body and tail are required. The dynamic model of the body is developed according to the parameters of a thunniform Fish-Robot built in MIT University, while, as the main part of this paper, the dynamic model of the tail is developed using fuzzy logic. Using experimental data and table look-up scheme, a fuzzy black box is introduced that gives the value of thrust force generated for any value of the Fish-Robot's input parameters: frequency of tail oscillation, amplitude of tail oscillation and speed of the Fish-Robot. In the second part, a trajectory fuzzy controller is designed for the Fish-Robot. The output of trajectory... 

In this paper, a 4-DOF robotic arm for tool handling in laparoscopic surgery is introduced. The robot provides sufficient force to handle endoscopic tools used for large organ manipulation and is capable of measuring the tool-tissue forces. The RCM constraint is achieved using a spherical mechanism and roll and insertion motions are provided using time pulley and spindle-drive, respectively. The forward and inverse kinematics of the robot was solved and the dimensions of its links were determined, using particle swarm optimization method, so that the maximum kinematic and dynamic performance could be achieved  

To have a complete model of a thunniform Fish-Robot, models of both body and tail are required. The dynamic model of the body is developed according to the parameters of a thunniform Fish-Robot built in MIT University, while, as the main part of this paper, the dynamic model of the tail is developed using fuzzy logic. Using experimental data and table look-up scheme, a fuzzy black box is introduced that gives the value of thrust force generated for any value of the Fish-Robot's input parameters: frequency of tail oscillation, amplitude of tail oscillation and speed of the Fish-Robot. In the second part, a trajectory fuzzy controller is designed for the Fish-Robot. The output of trajectory... 

The currently available robotic systems rely on rigid heart stabilizers to perform totally endoscopic coronary artery bypass (TECAB) surgery on beating hearts. Although such stabilizers facilitate the anastomosis procedure by immobilizing the heart and holding the surgery site steady, they can cause damage to the heart tissue and rupture of the capillary vessels, due to applying relatively large pressures on the epicardium. In this paper, we propose an advanced robotic approach to perform TECAB on a beating heart with minimal invasiveness. The idea comes from the fact that the main pulsations of the heart occur as excursions in normal direction, i.e., perpendicular to the heart surface. We... 

A new non-symmetric 5R-SPM is introduced and a geometrical approach is developed to analyze its configurations and singularities. The proposed methodology determines the type of configuration of a 5R-SPM, i.e. regular, singular, or out-of-workspace and also the type of singularity, i.e. instantaneous or finite, only based on geometric parameters and without solving verbose kinematic equations. It also provides insights into the workspace and singularities of 5R-SPMs, in the preliminary stage of design. The mechanism was analyzed by both the new geometrical approach and conventional methods for comparison. The geometrical approach could intuitively detect all the singularities observed by the... 

Calibrating the inverse kinematics of complex robots is often a challenging task. Finding analytical solutions is not always possible and the convergence of numerical methods is not guaranteed. The model-free approaches, based on machine learning and artificial intelligence, are fast and easy to work, however, they need a huge amount of experimental training data to provide acceptable results. In this article, we proposed a hybrid method to benefit the advantage of both model-based and model-free approaches. The forward kinematics of the robot is calibrated using a model-based approach, and its inverse kinematics using a neural network. Hence, while there is no need to solve the nonlinear...