Sensing planning to optimize work object location measurements in intelligent robotics

Abstract

This paper presents a method for planning the sensing features when the geometrical representation of the target object is known. The presented method is a synthesis -form and can be used in several measurement applications in robotics. Sensing planning is an important issue when the measurement data is sparse, includes a lot of noise or there are tight time-requirements. The criteria for selecting the measurement locations and orientations is a posteriori error covariance matrix of the parameters to be estimated. The presented approach is verified by simulation tests in the case of work object location.