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dc.contributor.advisorWai K. Cheng and Andreas Hofmann.en_US
dc.contributor.authorAngelosanto, Gina (Gina C.)en_US
dc.contributor.otherMassachusetts Institute of Technology. Dept. of Mechanical Engineering.en_US
dc.date.accessioned2009-06-30T16:18:26Z
dc.date.available2009-06-30T16:18:26Z
dc.date.copyright2008en_US
dc.date.issued2008en_US
dc.identifier.urihttp://hdl.handle.net/1721.1/45791
dc.descriptionThesis (S.B.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 2008.en_US
dc.descriptionIncludes bibliographical references (leaves 41-42).en_US
dc.description.abstractThis study explores the use of Kalman filtering of measurements from an inertial measurement unit (IMU) to provide information on the orientation of a robot for balance control. A test bed was created to characterize the random noise and errors inherent to orientation sensing in the MicroStrain 3DM-GX1 IMU for static cases as well as after experiencing an impact force. Balance simulations were performed to control the center of mass location of a robot modeled as an inverted pendulum. The controlled center of mass trajectories with state estimates generated from Kalman filtering were compared, where possible, to the CM trajectory based on unfiltered sensor measurements of the states. For the simple case of inverted pendulum control, it was determined that noise and error in the IMU are sufficiently small that Kalman filtering is not necessary when all states can be measured, but results in significant improvements in the RMS error of the actual and desired center of mass positions.en_US
dc.description.statementofresponsibilityby Gina Angelosanto.en_US
dc.format.extent46 leavesen_US
dc.language.isoengen_US
dc.publisherMassachusetts Institute of Technologyen_US
dc.rightsM.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission.en_US
dc.rights.urihttp://dspace.mit.edu/handle/1721.1/7582en_US
dc.subjectMechanical Engineering.en_US
dc.titleKalman filtering of IMU sensor for robot balance controlen_US
dc.title.alternativeKalman filtering of inertial measurement unit sensor for robot balance controlen_US
dc.typeThesisen_US
dc.description.degreeS.B.en_US
dc.contributor.departmentMassachusetts Institute of Technology. Dept. of Mechanical Engineering.en_US
dc.identifier.oclc318906502en_US


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