Bearing-only mapping by sequential triangulation and multi-dimensional scaling
Takehisa Yairi, Hirofumi Kanazaki
- 发表年份
- 2008
- 引用次数
- 2
摘要
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. BOMSTMDS 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.
关键词
相关论文
Statistical Learning Theory
Yuhai Wu, Vladimir Vapnik
1999
Artificial intelligence: a modern approach
1995
Applied Nonlinear Control
Jean-Jacques Slotine, Weiping Li
1991
A new optimizer using particle swarm theory
R.C. Eberhart, James Kennedy
2002