پديد آورنده :
صابريان، محمد
عنوان :
طراحي بهينه مسير ربات با درجه آزادي اضافي با استفاده از روش هاي محاسباتي نرم
مقطع تحصيلي :
كارشناسي ارشد
گرايش تحصيلي :
طراحي كاربردي
محل تحصيل :
اصفهان: دانشگاه صنعتي اصفهان، دانشكده مكانيك
صفحه شمار :
[سيزده]، 97ص.: مصور، جدول، نمودار
يادداشت :
ص.ع. به فارسي و انگليسي
استاد راهنما :
مهدي كشميري
استاد مشاور :
سعيد بهبهاني
توصيفگر ها :
ربات هاي افزونه , بهينه سازي , الگوريتم هاي هوشمند , موقعيت و سرعت مانع , همزمان ﴿بلادرنگ﴾
تاريخ نمايه سازي :
27/10/90
استاد داور :
محمد دانش، مصطفي غيور
تاريخ ورود اطلاعات :
1396/10/12
چكيده فارسي :
به فارسي و انگليسي: قابل رويت در نسخه ديجيتالي
چكيده انگليسي :
Optimal Path Planning for Redundant Robot Using Soft Computing Methods Mohammad Saberian m saberian@me iut ac ir August 1th 2011 Department of Mechanical Engineering Isfahan University of Technology Isfahan 84156 83111 IranDegree M Sc Language FarsiSupervisor M Keshmiri Assoc Prof mehdik@cc iut ac ir AbstractThe path planning problem has been studied extensively over the past decades The goal of path planning is tofind the robot motion trajectory versus time The path planning is an important subject in robotic systems andmanipulators to successfully use to their abilities for performing difficult tasks in different fields The pathplanning problem is a well studied problem of robot intelligence to which different approaches were applied for example neural networks NN potential fields genetic algorithms GA particle swarm optimization PSO Generally speaking these methods are classified into two categories according to the characteristics of theenvironment namely the off line global path planning and the on line local path planning based on detectingunknown environments In known static environments the path can be planned offline For unknown taskspaces and environments with unpredictable changes which require online path planning speed and accuracy ofcomputational algorithms are very important Due to the redundancy in redundant robots the path planning isregarded as an optimization problem This optimization can be resolved dynamically or parametrically Becauseof very slow and difficult solution process in dynamic optimization this problem should be solvedparametrically in which the optimal path is generated by finding the best combination of known functions Inthis thesis the optimal paths for redundant manipulators are found by intelligent algorithms that optimize thekinematic and dynamic index through the given path of end effector in the task space This algorithm has beenapplied on a plannar 3 link robot and a cooperative robot To validate the present work the results of proposedalgorithms have been compared with the result of the high precision search method For different states andconstraints the optimal path is generated by soft computing techniques including genetic algorithm artificialbee colony optimization and particle swarm optimization By comparing the results it is found that the particleswarm optimization is faster and more accurate than the others Therefore it is used to generate data for trainingneural networks in online path planning Neural networks is employed for online path planning in dynamicenvironments for known and unknown path of end effector in the task space The unknown path is calculatedthrough the optimization problem with assuming the specified initial and target points of the end effector In thismethod the path planning is performed in both static and dynamic environment Two methods are proposed where the optimal path is generated by detecting the position of obstacle in the first method and by detecting theposition and measuring the velocity of obstacle in the second method and for correcting the errors the algorithmis presented Keywords path planning redundant manipulator optimization soft computing techniques dynamic environment obstacle online
استاد راهنما :
مهدي كشميري
استاد مشاور :
سعيد بهبهاني
استاد داور :
محمد دانش، مصطفي غيور
