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EVALUATION OF SOLID STATE ACCELEROMETER SENSOR FOR EFFECTIVE POSITION ESTIMATION

dc.contributor.authorLele, Meenal Anand
dc.contributor.copyright-releaseNot Applicableen_US
dc.contributor.degreeMaster of Applied Scienceen_US
dc.contributor.departmentDepartment of Electrical & Computer Engineeringen_US
dc.contributor.ethics-approvalNot Applicableen_US
dc.contributor.external-examinerDr. William J. Phillipsen_US
dc.contributor.graduate-coordinatorDr. Micheal Cadaen_US
dc.contributor.manuscriptsNot Applicableen_US
dc.contributor.thesis-readerDr. Jose Gonzalez Cuetoen_US
dc.contributor.thesis-supervisorDr. Jason Guen_US
dc.date.accessioned2010-12-08T14:48:55Z
dc.date.available2010-12-08T14:48:55Z
dc.date.defence2010-11-22
dc.date.issued2010-12-08
dc.description.abstractInertial sensors such as Gyroscope and Accelerometer show systematic as well as random errors in the measurement. Furthermore, double integration method shows accumulation of error in position estimation due to inherent accelerometer bias drift. The primary objective of this research was to evaluate ADXL 335 acceleration sensor for better position estimation using acceleration bias drift error model. In addition, measurement data was recorded with four point rotation test for investigation of error characteristics. The fitted model was validated by using nonlinear regression analysis. The secondary objective was to examine the effect of bias drift and scale factor errors by introducing error model in Kalman Filter smoothing algorithm. The study showed that the accelerometer may be used for short distance mobile robot position estimation. This research would also help to establish a generalized test procedure for evaluation of accelerometer in terms of sensitivity, accuracy and data reliability.en_US
dc.identifier.urihttp://hdl.handle.net/10222/13128
dc.language.isoen_USen_US
dc.subjectMOBILE ROBOTICS, KALMAN FILTER, POSITION ESTIMATIONen_US
dc.titleEVALUATION OF SOLID STATE ACCELEROMETER SENSOR FOR EFFECTIVE POSITION ESTIMATIONen_US

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