Camera anomalies like rain or dust can severelydegrade image quality and its related tasks, such as localizationand segmentation.
We therefore present SegMap: a map representation solution for localization and mapping based on the extraction of segments in 3D point clouds.
Changes in appearance is one of the main sources of failure in visual localization systems in outdoor environments.
In this paper we propose HF-Net, a hierarchical localization approach based on a monolithic CNN that simultaneously predicts local features and global descriptors for accurate 6-DoF localization.
Ranked #3 on Visual Place Recognition on Berlin Kudamm
Many robotics applications require precise pose estimates despite operating in large and changing environments.
We propose LandmarkBoost - an approach that, in contrast to the conventional 2D-3D matching methods, casts the search problem as a landmark classification task.
Yet, in highly dynamic environments, like crowded city streets, problems arise as major parts of the image can be covered by dynamic objects.
This paper discusses a large-scale and long-term mapping and localization scenario using the maplab open-source framework.
On the other hand, maplab provides the research community with a collection of multisession mapping tools that include map merging, visual-inertial batch optimization, and loop closure.
Then, we create a set of convex free-space clusters, which are the vertices of the topological map.