This paper describes the details of a Quadrotor miniature unmanned aerial system capable of autonomously exploring cluttered indoor areas without relying on any external navigational aids such as GPS. A streamlined ...

This paper describes the design and flight test of a completely self-contained autonomous indoor Miniature Unmanned Aerial System (M-UAS). Guidance, navigation, and control algorithms are presented, enabling the M-UAS ...

In this paper, we present an information-based approach to select a reduced number of landmarks and poses for a robot to localize itself and simultaneously build an accurate map. We develop an information theoretic ...

Pose graph optimization is the non-convex optimization problem underlying pose-based Simultaneous Localization and Mapping (SLAM). If robot orientations were known, pose graph optimization would be a linear least-squares ...

Factor graphs are a general estimation framework that has been widely used in computer vision and robotics. In several classes of problems a natural partition arises among variables involved in the estimation. ...

The goal of simultaneous localization and mapping (SLAM) is to compute the posterior distribution over landmark poses. Typically, this is made possible through the static world assumption - the landmarks remain in the same ...

This paper will explore the relationship between sensory accuracy and Simultaneous Localization and Mapping (SLAM) performance. As inexpensive robots are developed with commodity components, the relationship between ...

In this paper we propose an efficient preconditioned conjugate gradients (PCG) approach to solving large-scale SLAM problems. While direct methods, popular in the literature, exhibit quadratic convergence and can be ...

We propose a novel method to solve online SLAM problems with many loop-closures on the basis of two state- of-the-art SLAM methods, iSAM and SPCG. We first use iSAM to solve a sparse sub-problem to ...

Recent work on simultaneous trajectory estimation and mapping (STEAM) for mobile robots has found success by representing the trajectory as a Gaussian process. Gaussian processes can represent a ...