Optimization of Robotic Arm Manipulator Using Multi-Objective Genetic Algorithms

碩士 === 國立高雄第一科技大學 === 機械與自動化工程所 === 97 === The efficiency of robotic arm manipulators is greatly reduced due to the extra moves made by axle joints, and will eventually leads to underproduction. Also, the flexibility and manipulability are inevitably decreased during processing because of the emerge...

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Bibliographic Details
Main Authors: Bo-Kai Chiu, 邱柏凱
Other Authors: Tung-Kuan Liu
Format: Others
Language:zh-TW
Published: 2009
Online Access:http://ndltd.ncl.edu.tw/handle/15794105979361731534
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Summary:碩士 === 國立高雄第一科技大學 === 機械與自動化工程所 === 97 === The efficiency of robotic arm manipulators is greatly reduced due to the extra moves made by axle joints, and will eventually leads to underproduction. Also, the flexibility and manipulability are inevitably decreased during processing because of the emergence of singularity point. Therefore, in order to increase the processing efficiency and avoid the singularity point phenomenon, exploring the best inverse kinematics solutions of axle joints is the primary goal of this research. Measurements of singularity points based on the performance of manipulators, smoothness of axle joints and multiple objective genetic algorithms are applied to achieve the goal. Two different industrial robotic arm manipulators are targeted in this research. The ultimate robotic arm manipulators positioning and performance are researched on condition that the least variation quantity has to be achieved. To do so, formulations suggested by Denavit Hertenberg are keys to explore space coordinate system of manipulator base and manipulator tip. Finally, simulations will be conducted by utilizing CATIA throughout the whole experiment to ensure that the outcome of the experiment will not be jeopardized by miscalculations.