no code implementations • 30 Sep 2023 • Jose Andres Millan-Romera, Hriday Bavle, Muhammad Shaheer, Martin R. Oswald, Holger Voos, Jose Luis Sanchez-Lopez
Concretely, our previous work, Situational Graphs (S-Graphs+), a pioneer in jointly leveraging semantic relationships in the factor optimization process, relies on semantic entities such as Planes and Rooms, whose relationship is mathematically defined.
no code implementations • 22 Aug 2023 • Hriday Bavle, Jose Luis Sanchez-Lopez, Javier Civera, Holger Voos
A global optimization of the compressed graph is performed every time a loop closure is detected.
no code implementations • 3 Mar 2023 • Muhammad Shaheer, Jose Andres Millan-Romera, Hriday Bavle, Jose Luis Sanchez-Lopez, Javier Civera, Holger Voos
Firstly, we develop a method for converting the plan of a building into what we denote as an architectural graph (A-Graph).
1 code implementation • 22 Dec 2022 • Hriday Bavle, Jose Luis Sanchez-Lopez, Muhammad Shaheer, Javier Civera, Holger Voos
In this paper, we present an evolved version of Situational Graphs, which jointly models in a single optimizable factor graph (1) a pose graph, as a set of robot keyframes comprising associated measurements and robot poses, and (2) a 3D scene graph, as a high-level representation of the environment that encodes its different geometric elements with semantic attributes and the relational information between them.
no code implementations • 16 Nov 2022 • Hriday Bavle, Jose Luis Sanchez-Lopez, Muhammad Shaheer, Javier Civera, Holger Voos
Mobile robots extract information from its environment to understand their current situation to enable intelligent decision making and autonomous task execution.
no code implementations • 19 Oct 2022 • Ali Tourani, Hriday Bavle, Jose Luis Sanchez-Lopez, Holger Voos
In this regard, Visual Simultaneous Localization and Mapping (VSLAM) methods refer to the SLAM approaches that employ cameras for pose estimation and map generation.
no code implementations • 14 Mar 2022 • Claudio Cimarelli, Hriday Bavle, Jose Luis Sanchez-Lopez, Holger Voos
To this end, we match 2D keypoints between consecutive frames using pre-trained deep networks, Superpoint and Superglue, while training a network for depth and pose estimation using an unsupervised training protocol.
no code implementations • 24 Feb 2022 • Hriday Bavle, Jose Luis Sanchez-Lopez, Muhammad Shaheer, Javier Civera, Holger Voos
Mobile robots should be aware of their situation, comprising the deep understanding of their surrounding environment along with the estimation of its own state, to successfully make intelligent decisions and execute tasks autonomously in real environments.
no code implementations • 1 Oct 2021 • Hriday Bavle, Jose Luis Sanchez-Lopez, Claudio Cimarelli, Ali Tourani, Holger Voos
The capability of a mobile robot to efficiently and safely perform complex missions is limited by its knowledge of the environment, namely the situation.