科研之友
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摘要
We propose a multi-hypothesis solution to the simplified problem of simultaneous localization and mapping (SLAM) that arises when only two measurement frames are available. The proposed solution is obtained through direct evaluation of the posterior density as given by finite set statistics. We show that hypothesis probabilities can be evaluated within reasonable accuracy by means of a closed-form expression. Consistency properties are discussed extensively. We overcome inconsistency problems of the extended Kalman filter by means of natural gradient optimization, and we demonstrate through implementations on simulated and real data that the proposed approach has better consistency properties than alternative approaches when applied to the two-frame SLAM problem.
- 出版日期2015-1
