Abstract
Autonomous map construction is one of the most fundamental and significant issues for intelligent mobile robots. While a variety of construction methods have been proposed, most of them are dependent on the quantitative sensor information and accurate physical models for estimating the positions and directions of the external objects and robot itself. This paper proposes a new map construction method based on rough information of “how often two objects are observed simultaneously” . This method is founded on the combination of a simple and general heuristics-“closely located objects are likely to be seen simultaneously more often than distant objects” and a well-known technique in the multivariate data analysis-Multi-Dimensional Scaling (MDS) . A significant feature of this method is that it requires little quantitative models nor precise sensor information, unlike conventional map construction methods. Simulation and experiment results suggest that this method is sufficiently practical for grasping a topological configuration of identifiable landmarks quickly.
