most citedD-LIO: 6DoF Direct LiDAR-Inertial Odometry based on Simultaneous Truncated Distance Field Mapping

3 citations · 5 across the 5 of their papers we have counts for

collaborators

5 papers

cs.RO2026

4D Radar Gaussian Modeling and Scan Matching with RCS

Fernando Amodeo, Luis Merino, Fernando Caballero

4D millimeter-wave (mmWave) radars are increasingly used in robotics, as they offer robustness against adverse environmental conditions. Besides the usual XYZ position, they provid…

cs.RO2026

G-EDF-Loc: 3D Continuous Gaussian Distance Field for Robust Gradient-Based 6DoF Localization

José E. Maese, Lucía Coto-Elena, Luis Merino +1

This paper presents a robust 6-DoF localization framework based on a direct, CPU-based scan-to-map registration pipeline. The system leverages G-EDF, a novel continuous and memory-…

cs.RO2025

C-3TO: Continuous 3D Trajectory Optimization on Neural Euclidean Signed Distance Fields

Guillermo Gil, Jose Antonio Cobano, Luis Merino +1

This paper introduces a novel framework for continuous 3D trajectory optimization in cluttered environments, leveraging online neural Euclidean Signed Distance Fields (ESDFs). Unli…

eess.SY2025★ 2 cited

Exploiting Euclidean Distance Field Properties for Fast and Safe 3D planning with a modified Lazy Theta*

Jose A. Cobano, L. Merino, F. Caballero

This paper presents the FS-Planner, a fast graph-search planner based on a modified Lazy Theta* algorithm that exploits the analytical properties of Euclidean Distance Fields (EDFs…

cs.RO2025★ 3 cited

D-LIO: 6DoF Direct LiDAR-Inertial Odometry based on Simultaneous Truncated Distance Field Mapping

Lucia Coto-Elena, J. E. Maese, L. Merino +1

This paper presents a new approach for 6DoF Direct LiDAR-Inertial Odometry (D-LIO) based on the simultaneous mapping of truncated distance fields on CPU. Such continuous representa…