1 citations · 1 across the 4 of their papers we have counts for
5 papers
Heterogeneous LiDAR Early Fusion and Learned Re-Ranking Strategy for Robust Long-Term Place Recognition in Unstructured Environments
Judith Vilella-Cantos, Juan José Cabrera, Mónica Ballesta +2
Robust localization in unstructured environments, such as agricultural fields, is a critical challenge for autonomous systems. LiDAR sensors provide detailed 3D information about t…
Low Cost, High Efficiency: LiDAR Place Recognition in Vineyards with Matryoshka Representation Learning
Judith Vilella-Cantos, Mauro Martini, Marcello Chiaberge +2
Localization in agricultural environments is challenging due to their unstructured nature and lack of distinctive landmarks. Although agricultural settings have been studied in the…
TEMPO-VINE: A Multi-Temporal Sensor Fusion Dataset for Localization and Mapping in Vineyards
Mauro Martini, Marco Ambrosio, Judith Vilella-Cantos +2
In recent years, precision agriculture has been introducing groundbreaking innovations in the field, with a strong focus on automation. However, research studies in robotics and au…
Advanced techniques and applications of LiDAR Place Recognition in Agricultural Environments: A Comprehensive Survey
Judith Vilella-Cantos, Mónica Ballesta, David Valiente +2
An optimal solution to the localization problem is essential for developing autonomous robotic systems. Apart from autonomous vehicles, precision agriculture is one of the elds tha…
MinkUNeXt-SI: Improving point cloud-based place recognition including spherical coordinates and LiDAR intensity
Judith Vilella-Cantos, Juan José Cabrera, Luis Payá +2
In autonomous navigation systems, the solution of the place recognition problem is crucial for their safe functioning. But this is not a trivial solution, since it must be accurate…