Maximum-Likelihood Estimation of a Sensor Configuration in a Polygonal Environment

摘要

In order to enhance the accuracy of mobile robot navigation, we propose a new method of pattern matching to estimate the robot configuration. It matches the observed data acquired by an environmental sensor to a given map of the robot environment. In this paper, we assume that the environment is expressed by a set of line segments in a two-dimensional space. We also assume that the environ- mental sensor consists of a set of range sensors oriented radially from a point, and that each range sensor has a normal error distribution. Our algorithm minimizes the expectation of the error of matching. The thee-dimensional configuration space is divided into perceptual equivalence classes, then the minima in each class are sought in the x-y plane and in the θ direction. Experimental results are shown.