A generic bias-correction method with application to scan-based localization

Abstract

In previous work a method was proposed to determine the bias in localization algorithms using range or bearing data. In this paper the method is extended to be more generic; in particular, different types of measurement data are permitted, and there may be more measurements than there are variables to estimate. The method combines the Taylor series and Jacobian matrices to determine the bias, and leads to an easily calculated analytical bias expression, despite the general unavailability of analytic expressions for the solution of most localization problems. The method is used to estimate the bias in scan-based localization. Monte Carlo simulation results verify the performance of the proposed method in this context.