Mapping and localization from planar markers

Abstract

Squared planar markers are a popular tool for fast, accurate and robust camera localization, but its use is frequently limited to a single marker, or at most, to a small set of them for which their relative pose is known beforehand. Mapping and localization from a large set of planar markers is yet a scarcely treated problem in favour of keypoint-based approaches. However, while keypoint detectors are not robust to rapid motion, large changes in viewpoint, or significant changes in appearance, fiducial markers can be robustly detected under a wider range of conditions. This paper proposes a novel method to simultaneously solve the problems of mapping and localization from a set of squared planar markers. First, a quiver of pairwise relative marker poses is created, from which an initial pose graph is obtained. The pose graph may contain small pairwise pose errors, that when propagated, leads to large errors. Thus, we distribute the rotational and translational error along the basis cycles of the graph so as to obtain a corrected pose graph. Finally, we perform a global pose optimization by minimizing the reprojection errors of the planar markers in all observed frames. The experiments conducted show that our method performs better than Structure from Motion and visual SLAM techniques.

UcoSLAM: Simultaneous localization and mapping by fusion of keypoints and squared planar markers

“…Third, our method allows robust tracking in repetitive environments such as office-like buildings. Four, our method does not require the markers to operate, unlike our previous works [34,6], but it is able to properly use them (if available) in order to improve tracking.…”

SLAP: Simultaneous Localization and Planning Under Uncertainty via Dynamic Replanning in Belief Space

“…3) Sensing Model: For sensing purposes, we use the onboard laptop webcam. We perform a vision-based landmark detection based on ArUco (a minimal library for Augmented Reality applications) [72]. Each landmark is a black and white pattern printed on a letter-size paper.…”

Optimizing the Maximal Perturbation in Point Sets while Preserving the Order Type

“…Fiducial tags, or fiducial markers, are used in computer vision (CV) applications for robot localization [1,2], mapping and localization of large environments [3][4][5], or for pose estimation in medical endoscopy [6]. Markers are also used for metric purposes, e.g., for calibration [7] and monitoring changes in distances and orientations in historic structures [8].…”