Probabilistic structure matching for visual SLAM with a multi-camera rig |
| |
Affiliation: | 1. Industrial Technical Laboratory, Yonsei University, Republic of Korea;2. School of Civil and Environmental Engineering, Yonsei University, Republic of Korea |
| |
Abstract: | We propose to use a multi-camera rig for simultaneous localization and mapping (SLAM), providing flexibility in sensor placement on mobile robot platforms while exploiting the stronger localization constraints provided by omni-directional sensors. In this context, we present a novel probabilistic approach to data association, that takes into account that features can also move between cameras under robot motion. Our approach circumvents the combinatorial data association problem by using an incremental expectation maximization algorithm. In the expectation step we determine a distribution over correspondences by sampling. In the maximization step, we find optimal parameters of a density over the robot motion and environment structure. By summarizing the sampling results in so-called virtual measurements, the resulting optimization simplifies to the equivalent optimization problem for known correspondences. We present results for simulated data, as well as for data obtained by a mobile robot equipped with a multi-camera rig. |
| |
Keywords: | |
本文献已被 ScienceDirect 等数据库收录! |
|