Semantic information has been agreed to be a key complement for more accurate SLAM or
navigation and higher-level behavior planning. In dynamic scene, it also has the potential to …

An autonomous robot performing tasks in a human environment needs to recognize
semantic information about places. Semantic mapping is a task in which suitable semantic …

We propose to use a multi-camera rig for simultaneous localization and mapping (SLAM),
providing flexibility in sensor placement on mobile robot platforms while exploiting the …

Object-based maps are relevant for scene under-standing since they integrate geometric
and semantic information of the environment, allowing autonomous robots to robustly …

Humanoid robots still have a low-level perception of their surroundings, which is a
formidable obstacle to performing complex tasks. To improve their perceptual capabilities …

Semantic mapping is one of the most active and promising research areas within
autonomous mobile robotics. Informally, a semantic map associates a high-level human …

In order to diminish the influence of pose choice during appearance-based mapping, a more
natural representation of location models is established using covisibility graphs. As the …

This paper proposes a method to integrate the rich semantic data-set provided by Building
Information Modeling (BIM) with robotics world models, taking as use case indoor semantic …

High-accurate and real-time localization is the fundamental and challenging task for
autonomous driving in a dynamic traffic environment. This paper presents a coordinated …

This article develops a Bayesian continuous 3D semantic occupancy map from noisy point
clouds by generalizing the Bayesian kernel inference model for building occupancy maps, a …