Bearing-only mapping by sequential triangulation and multi-dimensional scaling

In this paper, we introduce an alternative solution to the bearing-only mapping problem in which a mobile robot builds a map of features (landmarks) using only relative bearing measurements to them and odometry information. Our approach named BOM-STMDS (bearing-only mapping by sequential triangulation and multi-dimensional scaling) first tries to estimate relative distances among the features, then finds two-dimensional coordinates of all features by using multi-dimensional scaling (MDS) and its enhancements. BOM- STMDS is different from the conventional BOSLAM methods based on Bayesian filtering in that robot self-localization is not mandatory. Another remarkable property is that BOM-STMDS is able to utilize prior information about relative distances among features efficiently. In the experiment, the performance of BOM-STMDS is shown to be competitive with a conventional EKF-based BOSLAM method.