Abstract Simultaneous Localization and Mapping (SLAM) is a process to use multiple
sensors to position an unmanned mobile vehicle without previous knowledge of the …

Simultaneous Localization and Mapping, commonly known as SLAM, has been an active
research area in the field of Robotics over the past three decades. For solving the SLAM …

In this paper, we present incremental smoothing and mapping (iSAM), which is a novel
approach to the simultaneous localization and mapping problem that is based on fast …

Many successful indoor mapping techniques employ frame-to-frame matching of laser scans
to produce detailed local maps as well as the closing of large loops. In this paper, we …

We present a system for monocular simultaneous localization and mapping (mono-SLAM)
relying solely on video input. Our algorithm makes it possible to precisely estimate the …

This paper addresses the problem of exploring and mapping an unknown environment
using a robot equipped with a stereo vision sensor. The main contribution of our work is a …

In this paper, we analyze and extend the recently proposed closed-form online pose-chain
simultaneous localization and mapping (SLAM) algorithm. Pose-chains are a specific type of …

With recent advances in real-time implementations of filters for solving the simultaneous
localization and mapping (SLAM) problem in the range-sensing domain, attention has …

Most vision-based SLAM systems utilize corner-like features, and may be unstable in non-
textured environments where only a few corner features can be extracted. To cope with this …

This paper explores the possibilities of using monocular simultaneous localization and
mapping (SLAM) algorithms in systems with more than one camera. The idea is to combine …