Localization of a Moving Sensor by Particle Filters

Abstract

Recently, interests in localization and map building with laser range sensor have been increasing in robotics community. One of the reasons for this is that the algorithms with laser range sensor are with lower computational cost and are more robust than using vision sensors. Another reason is the robustness against environment changes (e.g. lighting condition, etc.). We are developing a walking aid system for physically-handicapped persons. As the first step in this project, we consider the localization of a moving cart with laser range sensor and building environment map. We estimate the moving cart position and orientation by maximizing the number of matched point pairs between current scan data and reference scan data. Our matching algorithm is based on point-to-point matching algorithms. In this paper, we show some preliminary results using raw data and discuss the availability of our matching algorithm for the future applications. We also show the way to apply particle filters for this problem and examine this localization algorithm.