The Industry 4.0 paradigm is being increasingly adopted in the production, distribution and commercialization chains worldwide. The integration of the cutting-edge techniques behind it entails a deep and complex revolution ...

Probabilistic Graphical Models (PGMs) in general, and Undirected Graphical Models (UGMs) in particular, become suitable frameworks to capture and conveniently model the uncertainty inherent in a variety of problems. When ...

In domestic robotics, passing through narrow areas becomes critical for safe and effective robot navigation. Due to factors like sensor noise or miscalibration, even if the free space is sufficient for the robot to pass ...

A world model representing the elements in a robot’s environment needs to maintain a correspondence between the objects being observed and their internal representations, which is known as the anchoring problem. Anchoring ...

We present a new fast Ground Decoupled 3D Lidar Odometry (GND-LO) method. The particularity of GND-LO is that it takes advantage of the distinct spatial layout found in urban settings to efficiently recover the lidar movement ...

This paper presents the Robot-at-Home dataset (Robot@Home), a collection of raw and processed sensory data from domestic settings aimed at serving as a benchmark for semantic mapping algorithms through the categorization ...

Scene object recognition is an essential requirement for intelligent mobile robots. In addition to geometric or appearance features, modern recogni- tion systems strive to incorporate contextual information, normally ...

Semantic maps augment traditional representations of robot workspaces, typically based on their geometry and/or topology, with meta-information about the properties, relations and functionalities of their composing elements. ...