The capability of a mobile robot to efficiently and safely perform complex missions is limited
by its knowledge of the environment, namely the situation. Advanced reasoning, decision …

3D spatial perception is the problem of building and maintaining an actionable and
persistent representation of the environment in real-time using sensor data and prior …

Maps have played an indispensable role in enabling safe and automated driving. Although
there have been many advances on different fronts ranging from SLAM to semantics …

Versatile and adaptive semantic understanding would enable autonomous systems to
comprehend and interact with their surroundings. Existing fixed-class models limit the …

3D scene graphs have recently emerged as an expressive high-level map representation
that describes a 3D environment as a layered graph where nodes represent spatial …

Situational Graphs (S-Graphs) merge geometric models of the environment generated by
Simultaneous Localization and Map** (SLAM) approaches with 3D scene graphs into a …

Map** is one of the key components of mobile robot navigation. Representing a map as a
topological structure is suitable for fast path planning and does not require high positioning …

Factor graphs, initially developed as probabilistic graphical models, have been widely
employed for solving large-scale inference problems in robotics, particularly in tasks such as …

Fiducial markers can encode rich information about the environment and aid Visual SLAM
(VSLAM) approaches in reconstructing maps with practical semantic information. Current …

3D scene graphs offer a more efficient representation of the environment by hierarchically
organizing diverse semantic entities and the topological relationships among them. Fiducial …