6742

6284

كارشناسي ارشد

مهندسي مكانيك

اصفهان: دانشگاه صنعتي اصفهان، دانشكده مكانيك

1390

ده، 121ص: مصور، جدول، نمودار

ص.ع. به فارسي و انگليسي

مهران عمادي انداني، عباس فتاح

محمد پرنيان پور

17/3/91

محمد جعفر صديق، مصطفي غيور

1396/10/06

كتابنامه

مكانيك

مهندسي مكانيك

ID6284

به فارسي و انگليسي: قابل رويت در نسخه ديجيتالي

Movement Planning of Sit to Stand Transfer Based on Decomposing the Motion into its Corresponding Subtasks Mohsen Sadeghi m sadeghi@me iut ac ir Date of Submission 2012 01 29 Department of Mechanical Engineering Isfahan University of Technology Isfahan 84156 83111 Iran Degree M Sc Language Farsi Supervisors Mehran Emadi Andani Emadi@eng ui ac ir Abbas Fattah fattah@cc iut ac ir Abstract Recently computer modeling and simulation of human movements has attracted many researchers inthe field of neuroscience and biomedical engineering Understanding the strategies of Central NervousSystem CNS in planning and controlling the movements plays an increasing role in the improvement ofrehabilitation protocols sport techniques and the recognition of motor disorders In this case the presentstudy deals with the computational modeling of the CNS s performance in planning the Sit to Standtransfer as a challenging task The approach is based on the hypothesis that the CNS may decompose thecomplicated movements into several simpler sub tasks phases of motion According to this hypothesis andas a novel approach the constructive basic patterns of movement in each phase of motion are extractedfrom the recorded data and compared to the minimum jerk patterns It is shown that the CNS applies aminimum angle jerk policy when plans the motion of each phase Also by proposing a new optimizationbased model we suggest that unlike the previous approaches considering appropriate cost functionscorresponding to each phase of motion provides a better description of optimality in complicatedmovements In fact it seems that the CNS considers different strategies to plan different phases of motion On the other side the ability of CNS is generating a large repertoire of actions under various conditionsreveals that it does not need to go through optimization procedures to plan any single motion It should bementioned that optimization imposes heavy computational burdens to the CNS According to this fact anovel modular and hierarchical movement planner MHMP is developed to describe the function of CNSin planning the multi phase tasks under different environmental conditions The MHMP is made of fourfunctional parts including the kinematic estimator modules a time estimator module a gating module and amovement element based network These parts enable the model to plan the movements under unknownconditions by the use of past experiences The performance of MHMP is evaluated both with theoptimization based model and the empirical captured motions It is shown that the modular features of themodel as well as the concept of motion decomposition increase the ability of MHMP in planning the real time and optimal movements under different environmental conditions Sufficient accuracy of the model low computational requirements as well as the behavioral and neurophysiological supports make the modelto be considered as a suitable candidate to computationally interpret the function of CNS in planning thetasks Based on the concepts of movement decomposition definition of different objective functions foreach phase of the movement and the structure of the MHMP this work is ready to be used for humanoidrobots or any other robotic applications Keywords Movement planning Optimization based model Sit to Stand Motion decomposition Modular and hierarchical structure

مهران عمادي انداني، عباس فتاح

محمد پرنيان پور

محمد جعفر صديق، مصطفي غيور