Laura Oliva-Maza — accepted AI-conference papers

2024

CoFlex TOP: A Teleoperation System for Flexible Ureteroscopy

Christopher Schlenk, Anja Hellings-Kuß, Katharina Hagmann, Nikola Budjakoski, Laura Oliva-Maza, Julian Klodmann +4

RA-L 2024

In flexible ureteroscopy (fURS) for kidney stones, the renal collecting system is inspected and stones are removed with a flexible ureteroscope (FU). One alternative to the fragmentation of stones and their removal with the help of graspers or extraction baskets is the dusting of stones with laser l

Cited by 1 Source ↗Scholar ↗

2023

SID-SLAM: Semi-Direct Information-Driven RGB-D SLAM

Alejandro Fontán, Riccardo Giubilato, Laura Oliva-Maza, Javier Civera, Rudolph Triebel

RA-L 2023

This work presents SID-SLAM, a complete SLAM framework for RGB-D cameras. Our main contribution is a semi-direct approach that, for the first time, combines tightly and indistinctly photometric and feature-based image measurements. Additionally, SID-SLAM uses information metrics to reduce the state

Cited by 16 Source ↗Scholar ↗

2022

Model for Multi-View Residual Covariances Based on Perspective Deformation

Alejandro Fontán, Laura Oliva-Maza, Javier Civera, Rudolph Triebel

RA-L 2022

In this work, we derive a model for the covariance of the visual residuals in multi-view SfM, odometry and SLAM setups. The core of our approach is the formulation of the residual covariances as a combination of geometric and photometric noise sources. And our key novel contribution is the derivatio

Cited by 9 Source ↗Scholar ↗