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hanifeh--shahrzad
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A Study on Relationships between Career Anchors and Career Orientations
, M.Sc. Thesis Sharif University of Technology ; Alavi, Babak (Supervisor)
Abstract
Career Orientations or career choices, can be affected by internal and external factors. External factors are the environmental conditions that the reward and the attractiveness of selecting a career choice are dependent to them. Internal factors include the needs of oneself from his/her job, his/her beliefs and his/her skills and competencies about the job. In this research the internal antecedents of managerial and technical orientations between programmers have been identified. On the other hand the perception of people about the compensation system as an external factor which can affect the mentioned relationships, have been analyzed. It seems that this is the first research which career...
Design and Implementation of an Activation Mechanism for Wristed Laparoscopic Instruments at Sina Robotic Surgery System
, M.Sc. Thesis Sharif University of Technology ; Farahmand, Farzam (Supervisor)
Abstract
Sina surgical system is a telesurgery robotic system which is capable of using the conventional laparoscopic tools. In order to provide the wrist degree of freedom and increase the surgical maneuverability, a mechanism is introduced here which enables Sina to use and activate the wristed laparoscopic instrument Laparo-Angle. At first, the kinematics and dynamics characteristics of Laparo-Angle were identified experimentally. This tool contains 4 degrees of freedom, pitch, yaw, grasp and distal Roll. Activation of pitch and Yaw degrees of freedom requires a mechanism which at least has two rotational degrees of freedom to move the tool handle in a cone shape workspace with an apex angle of 36...
Investigation of a hybrid kinematic calibration method for the 'sina' surgical robot
, Article IEEE Robotics and Automation Letters ; Volume 5, Issue 4 , 2020 , Pages 5276-5282 ; Samandi, P ; Hanifeh, S ; Kheradmand, P ; Mirbagheri, A. R ; Farahmand, F ; Sarkar, S ; Sharif University of Technology
Institute of Electrical and Electronics Engineers Inc
2020
Abstract
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...