Guaranteed Mobile Robot Tracking Using Interval Analysis

Abstract

: The problem considered here is state estimation in the presence of bounded process and measurement noise. A new nonlinear state estimator, based on interval analysis and the notion of set inversion, is applied to robot localization and tracking. This estimator evaluates a set guaranteed to contain all values of the state that are consistent with the available observations, given the noise bounds and some possibly very large set containing the initial value of the state. Three situations are considered to illustrate the properties of the estimator. Keywords: Bounded-error estimation, Interval analysis, Robot localization, Robot tracking, State estimation. 1 Introduction Much of recent research in robotics has been devoted to increasing autonomy, e.g., by adding sensors, mobility and decision capability. To be autonomous, robots must be able to estimate their present state from available prior information and measurements. The problem to be considered here is the autonomous localizati...