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Document Type : Latin Dissertation
Language of Document : English
Record Number : 152517
Doc. No : ET24309
Main Entry : Christopher Stewart Langley
Title Proper : FEATURE-BASED POSE-ESTIMATION FOR ROBOTIC FIXTURELESS ASSEMBLYPOMPES PAR TRANSITIONS MULTIPLES
Note : This document is digital این مدرک بصورت الکترونیکی می باشد
Abstract : The research presented herein is a step toward the realization of a prototype flexiblefixtureless assembly workcell. One requirement of a fixtureless workcell is the ability tolocate and grasp parts that have been presented in arbitrary poses. The Feature CMACneural network has been shown to solve the 3-DOF pose-estimation problem based onvisual information for simple target parts. Through the use of more advanced feature-extraction algorithms and improved methods of manipulation, the Feature CMAC'scapability has been extended for use with an unmodified industrial target part. The RMSpositional error was found to be below 1.0 mrn, and below 1 .ZO in orientation. Inaddition, the necessary tasks for application of the Feature CMAC pose-estimationsystem to a fixtureless assembly workcell have been identified..
Subject : Electericl tess
: برق
electronic file name : TL48515.pdf
Title and statement of responsibility and : FEATURE-BASED POSE-ESTIMATION FOR ROBOTIC FIXTURELESS ASSEMBLYPOMPES PAR TRANSITIONS MULTIPLES [Thesis]
 
 
 
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