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Automated Assembly Using Feature Localization

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dc.creator Gordon, Steven Jeffrey
dc.date 2004-10-20T20:02:58Z
dc.date 2004-10-20T20:02:58Z
dc.date 1986-12-01
dc.date.accessioned 2013-10-09T02:47:22Z
dc.date.available 2013-10-09T02:47:22Z
dc.date.issued 2013-10-09
dc.identifier AITR-932
dc.identifier http://hdl.handle.net/1721.1/6860
dc.identifier.uri http://koha.mediu.edu.my:8181/xmlui/handle/1721
dc.description Automated assembly of mechanical devices is studies by researching methods of operating assembly equipment in a variable manner; that is, systems which may be configured to perform many different assembly operations are studied. The general parts assembly operation involves the removal of alignment errors within some tolerance and without damaging the parts. Two methods for eliminating alignment errors are discussed: a priori suppression and measurement and removal. Both methods are studied with the more novel measurement and removal technique being studied in greater detail. During the study of this technique, a fast and accurate six degree-of-freedom position sensor based on a light-stripe vision technique was developed. Specifications for the sensor were derived from an assembly-system error analysis. Studies on extracting accurate information from the sensor by optimally reducing redundant information, filtering quantization noise, and careful calibration procedures were performed. Prototype assembly systems for both error elimination techniques were implemented and used to assemble several products. The assembly system based on the a priori suppression technique uses a number of mechanical assembly tools and software systems which extend the capabilities of industrial robots. The need for the tools was determined through an assembly task analysis of several consumer and automotive products. The assembly system based on the measurement and removal technique used the six degree-of-freedom position sensor to measure part misalignments. Robot commands for aligning the parts were automatically calculated based on the sensor data and executed.
dc.format 279 p.
dc.format 35053969 bytes
dc.format 28370075 bytes
dc.format application/postscript
dc.format application/pdf
dc.language en_US
dc.relation AITR-932
dc.title Automated Assembly Using Feature Localization


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