Topological simultaneous localization and mapping (SLAM): toward exact localization without explicit localization

TLDR

The environment’s topology is represented by a generalized Voronoi graph that also encodes some metric information. The study proposes a SLAM method that uses the GVG’s graph structure to localize a robot on a partially built map. The method generates a GVG via low‑level control laws, uses it as an arbitrator in a hybrid control system, and applies graph matching to localize the robot. Experiments confirm the effectiveness of the proposed localization approach.

Abstract

This paper presents a new method for simultaneous localization and mapping that exploits the topology of the robot's free space to localize the robot on a partially constructed map. The topology of the environment is encoded in a topological map; the particular topological map used in this paper is the generalized Voronoi graph (GVG), which also encodes some metric information about the robot's environment, as well. In this paper, we present the low-level control laws that generate the GVG edges and nodes, thereby allowing for exploration of an unknown space. With these prescribed control laws, the GVG can be viewed as an arbitrator for a hybrid control system that determines when to invoke a particular low-level controller from a set of controllers all working toward the high-level capability of mobile robot exploration. The main contribution, however, is using the graph structure of the GVG, via a graph matching process, to localize the robot. Experimental results verify the described work.