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of 1 358
pro vyhledávání: '"LÓPEZ, JOSÉ LUIS"'
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
The integration of Unmanned Aerial Vehicles (UAVs) into Search and Rescue (SAR) missions presents a promising avenue for enhancing operational efficiency and effectiveness. However, the success of these missions is not solely dependent on the technic
Externí odkaz:
http://arxiv.org/abs/2402.18487
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