We present an extension to our feature based mapping technique that allows for the use of
planar surfaces such as walls, tables, counters, or other planar surfaces as landmarks in our …

Simultaneous Localization and Mapping (SLAM) is not a problem with a one-size-fits-all
solution. The literature includes a variety of SLAM approaches targeted at different …

Complex and structured landmarks like objects have many advantages over low-level image
features for semantic mapping. Low level features such as image corners suffer from …

Introducing a priori knowledge about the latent structure of the environment in simultaneous
localization and mapping (SLAM), can improve the quality and consistency results of its …

In indoor environments, there exists a few distinctive indoor spaces' features (ISFs).
However, up to our knowledge, there is no algorithm that fully utilizes ISF for accurate 3-D …

Place categorization and object recognition are competencies needed by robots to perform
a variety of service tasks in the home, such as fetch-and-carry, retrieval, cleaning, meal …

We consider how prior information can be exploited to improve the quality of SLAM. Prior
information, such as aerial imagery, can be readily obtained for many environments …

A robot system operating in an unknown environment must be able to track its position to
perform its mission. Vehicles with a consistent view of the sky, eg, aerial or water surface …

In mobile robotics, feature based maps are very popular for the representation of the
environment. Some of the main advantages of these maps are final compactness and …

In this paper we present a general method for exploiting prior information to constrain the
location of land marks in GraphSLAM. Prior information can be obtained for many …