Experimental study of observability of parameter errors in robot calibration

Abstract

The selection of measurement configurations for robot calibration is investigated. The goal is to select a set of robot measurement configurations which will yield maximum observability of the model parameter errors so that the effects of noise in parameter estimation can be minimized. The noise considered includes both measurement and modeling errors. An observability measure is used as a criterion for selecting measurement configurations in 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 observability measure defined, the optimal measurement configurations for kinematic model calibration are determined for PUMA-type robots.<>