A method of localisation and multi-layered 2D mapping using selective update for particle filter

Abstract

Localisation and mapping are fundamental capabilities for autonomous mobile robots, and there has been a large amount of recent work in these fields. However, much of the work does not consider dynamic environments that include humans and moving objects. Such objects can cause occlusions resulting in a fewer visible landmarks, which can decrease localisation performance. This paper describes a novel method of localisation and multi-layered 2D mapping in dynamic environments using selective updating of a particle filter. A number of horizontal, planar laser scans at varying heights are used to construct a number of corresponding 2D maps. At each mapping step, the position estimate from the map layer which minimizes uncertainty is selected and used to update all maps. Using the proposed method, it is possible to localize precisely in dynamic environments, despite the effects of occlusion. Experimental results in a large outdoor environment confirms the effectiveness of the method.