We review the use of factor graphs for the modeling and solving of large-scale inference
problems in robotics. Factor graphs are a family of probabilistic graphical models, other …

When multiple robots are involved in the process of simultaneous localization and mapping
(SLAM), a global map should be constructed by merging the local maps built by individual …

This paper presents the formalization of the closest point plane representation and an
analysis of its incorporation in 3D indoor simultaneous localization and mapping (SLAM) …

The amount of captured 3D data is continuously increasing, with the democratization of
consumer depth cameras, the development of modern multi‐view stereo capture setups and …

Simultaneous localization and mapping with infinite planes is attractive because of the
reduced complexity with respect to both sparse point-based and dense volumetric methods …

We present a simultaneous localization and mapping (SLAM) algorithm for a hand-held 3D
sensor that uses both points and planes as primitives. We show that it is possible to register …

Real-time plane extraction in 3D point clouds is crucial to many robotics applications. We
present a novel algorithm for reliably detecting multiple planes in real time in organized …

Indoor environments have abundant presence of high-level semantic information which can
provide a better understanding of the environment for robots to improve the uncertainty in …

In this work, we develop a novel keyframe-based dense planar SLAM (KDP-SLAM) system,
based on CPU only, to reconstruct large indoor environments in real-time using a hand-held …

Segmentation is an important step in many perception tasks, such as object detection and
recognition. We present an approach to organized point cloud segmentation and its …