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The noise amplification index for optimal pose selection in robot calibration

Ali Nahvi, John M. Hollerbach

Year
2002
Citations
159

Abstract

This paper presents a new observability index to quantify the selection of best pose set in robot calibration. This noise amplification index is considerably more sensitive to calibration error than previously published observability indices. Support for the proposed index as provided analytically and geometrically, and also through comparison against previous indices by a simulation for a 3-link planar robot and by an experiment for a 3-DOF redundant parallel-drive robot.

Keywords

ObservabilityCalibrationRobotNoise (video)Computer scienceSelection (genetic algorithm)PlanarSet (abstract data type)Index (typography)Robot calibration

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