Autonomous systems possess the features of inferring their own state, understanding their
surroundings, and performing autonomous navigation. With the applications of learning …

The field of autonomous mobile robots has undergone dramatic advancements over the past
decades. Despite achieving important milestones, several challenges are yet to be …

Visual SLAM (simultaneous localization and mapping) refers to the problem of using
images, as the only source of external information, in order to establish the position of a …

This paper describes the simultaneous localization and mapping (SLAM) problem and the
essential methods for solving the SLAM problem and summarizes key implementations and …

We present a real-time algorithm which can recover the 3D trajectory of a monocular
camera, moving rapidly through a previously unknown scene. Our system, which we dub …

This paper discusses the recursive Bayesian formulation of the simultaneous localization
and mapping (SLAM) problem in which probability distributions or estimates of absolute or …

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 …

Mobile robot vision-based navigation has been the source of countless research
contributions, from the domains of both vision and control. Vision is becoming more and …

To operate outdoors or on non-flat surfaces, mobile robots need appropriate data structures
that provide a compact representation of the environment and at the same time support …

In this paper we present a tutorial introduction to two important senses for biological and
robotic systems—inertial and visual perception. We discuss the fundamentals of these two …