DETERMINATION OF OPTIMAL MEASUREMENT CONFIGURATIONS FOR ROBOT CALIBRATION BASED ON OBSERVABILITY MEASURE

The selection of measurement configurations in robot calibration is investigated. The goal is to select a set of robot measurement configurations that will yield maximum observability of the error parameters in a defined position error model so that the effect of noise in parameter estimation can be minimized. The noise considered in this paper includes both measurement and modeling errors. An observability measure is used as a criterion for selecting measurement configurations for calibration. Experimental studies are performed to demonstrate the importance of observability to parameter estimation and to verify its implications in robot calibration. Based on the defined observability measure, the optimal measurement configurations for robot calibration are determined for general open-loop planar mechanism and PUMA type robots.