Zobrazeno 1 - 10
of 96
pro vyhledávání: '"Bavle, Hriday"'
Autor:
Millan-Romera, Jose Andres, Bavle, Hriday, Shaheer, Muhammad, Voos, Holger, Sanchez-Lopez, Jose Luis
Understanding the relationships between geometric structures and semantic concepts is crucial for building accurate models of complex environments. In indoors, certain spatial constraints, such as the relative positioning of planes, remain consistent
Externí odkaz:
http://arxiv.org/abs/2409.11972
RGB-D cameras supply rich and dense visual and spatial information for various robotics tasks such as scene understanding, map reconstruction, and localization. Integrating depth and visual information can aid robots in localization and element mappi
Externí odkaz:
http://arxiv.org/abs/2409.06625
Autor:
Shaheer, Muhammad, Millan-Romera, Jose Andres, Bavle, Hriday, Giberna, Marco, Sanchez-Lopez, Jose Luis, Civera, Javier, Voos, Holger
Having prior knowledge of an environment boosts the localization and mapping accuracy of robots. Several approaches in the literature have utilized architectural plans in this regard. However, almost all of them overlook the deviations between actual
Externí odkaz:
http://arxiv.org/abs/2408.01737
5G New Radio Time of Arrival (ToA) data has the potential to revolutionize indoor localization for micro aerial vehicles (MAVs). However, its performance under varying network setups, especially when combined with IMU data for real-time localization,
Externí odkaz:
http://arxiv.org/abs/2404.00691
Aerial robots play a vital role in various applications where the situational awareness of the robots concerning the environment is a fundamental demand. As one such use case, drones in GPS-denied environments require equipping with different sensors
Externí odkaz:
http://arxiv.org/abs/2402.07537
Autor:
Fernandez-Cortizas, Miguel, Bavle, Hriday, Perez-Saura, David, Sanchez-Lopez, Jose Luis, Campoy, Pascual, Voos, Holger
Publikováno v:
IEEE Robotics and Automation Letters ( Volume: 9, Issue: 6, June 2024)
Collaborative Simultaneous Localization and Mapping (CSLAM) is critical to enable multiple robots to operate in complex environments. Most CSLAM techniques rely on raw sensor measurement or low-level features such as keyframe descriptors, which can l
Externí odkaz:
http://arxiv.org/abs/2401.05152
Autor:
Millan-Romera, Jose Andres, Bavle, Hriday, Shaheer, Muhammad, Oswald, Martin R., Voos, Holger, Sanchez-Lopez, Jose Luis
Recent works on SLAM extend their pose graphs with higher-level semantic concepts like Rooms exploiting relationships between them, to provide, not only a richer representation of the situation/environment but also to improve the accuracy of its esti
Externí odkaz:
http://arxiv.org/abs/2310.00401
Vision-based Situational Graphs Exploiting Fiducial Markers for the Integration of Semantic Entities
Autor:
Tourani, Ali, Bavle, Hriday, Sanchez-Lopez, Jose Luis, Avsar, Deniz Isinsu, Salinas, Rafael Munoz, Voos, Holger
Situational Graphs (S-Graphs) merge geometric models of the environment generated by Simultaneous Localization and Mapping (SLAM) approaches with 3D scene graphs into a multi-layered jointly optimizable factor graph. As an advantage, S-Graphs not onl
Externí odkaz:
http://arxiv.org/abs/2309.10461
3D scene graphs hierarchically represent the environment appropriately organizing different environmental entities in various layers. Our previous work on situational graphs extends the concept of 3D scene graph to SLAM by tightly coupling the robot
Externí odkaz:
http://arxiv.org/abs/2308.11242
Path planning is a basic capability of autonomous mobile robots. Former approaches in path planning exploit only the given geometric information from the environment without leveraging the inherent semantics within the environment. The recently prese
Externí odkaz:
http://arxiv.org/abs/2307.01613