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Fernando Caballero

11 accepted papers

2026

4D Radar-Inertial Odometry Based on Gaussian Modeling and Multi-Hypothesis Scan Matching

RA-L 2026

4D millimeter-wave (mmWave) radars are sensors that provide robustness against adverse weather conditions (rain, snow, fog, etc.), and as such they are increasingly used for odometry and SLAM (Simultaneous Location and Mapping). However, the noisy and sparse nature of the returned scan data proves t

Cited by 3SourcecodeScholar
2026

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

RA-L 2026

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 representation (in the vicinity of the points) enables working with raw 3D LiDAR data online, avoiding the need of LiDAR feature s

Cited by 3SourcecodeScholar
2026

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

ICRA 2026poster

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 representation (in the vicinity of the points) enables working with raw 3D LiDAR data online, avoiding the need of LiDAR feature s…

2026

DB-TSDF: Directional Bitmask-Based Truncated Signed Distance Fields for Efficient Volumetric Mapping

ICRA 2026poster

This paper presents a high-efficiency, CPU-only volumetric mapping framework based on a Truncated Signed Distance Field (TSDF). The system incrementally fuses raw LiDAR point-cloud data into a voxel grid using a directional bitmask-based integration scheme, producing dense and consistent TSDF repres…

2026

Radio-Based Multi-Robot Odometry and Relative Localization

ICRA 2026poster

Radio-based methods such as Ultra-Wideband (UWB) and RAdio Detection And Ranging (radar), which have traditionally seen limited adoption in robotics, are experiencing a boost in popularity thanks to their robustness to harsh environmental conditions and cluttered environments. This work proposes a m…

2024

Adaptive Social Force Window Planner with Reinforcement Learning

IROS 2024poster

Human-aware navigation is a complex task for mobile robots, requiring an autonomous navigation system capable of achieving efficient path planning together with socially compliant behaviors. Social planners usually add costs or constraints to the objective function, leading to intricate tuning proce…

Cited by 3SourceScholar
2023

HuNavSim: A ROS 2 Human Navigation Simulator for Benchmarking Human-Aware Robot Navigation

RA-L 2023

This work presents the Human Navigation Simulator ( <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">HuNavSim</i> ), a novel open-source tool for the simulation of different human-agent navigation behaviors in scenarios with mobile robots. The tool, t

Cited by 39SourcecodeScholar
2023

Path and Trajectory Planning of a Tethered UAV-UGV Marsupial Robotic System

RA-L 2023

This letter addresses the problem of trajectory planning in a marsupial robotic system consisting of an unmanned aerial vehicle (UAV) linked to an unmanned ground vehicle (UGV) through a non-taut tether with controllable length. To the best of our knowledge, this is the first method that addresses t

Cited by 27SourcecodeScholar
2021

DLL: Direct LIDAR Localization. A map-based localization approach for aerial robots

IROS 2021poster

This paper presents DLL, a fast direct map-based localization technique using 3D LIDAR for its application to aerial robots. DLL implements a point cloud to map registration based on non-linear optimization of the distance of the points and the map, thus not requiring features, neither point corresp…

Cited by 35SourcecodeScholar
2018

Learning Human-Aware Path Planning with Fully Convolutional Networks

ICRA 2018poster

This work presents an approach to learn path planning for robot social navigation by demonstration. We make use of Fully Convolutional Neural Networks (FCNs) to learn from expert's path demonstrations a map that marks a feasible path to the goal as a classification problem. The use of FCNs allows us…

Cited by 74SourceScholar
2018

MGRAPH: A Multigraph Homography Method to Generate Incremental Mosaics in Real-Time From UAV Swarms

RA-L 2018

During the last years, UAVs have proved to be an essential tool in the mapping industry. Furthermore, the next generation of UAVs is envisioned to work cooperatively, following the swarming/teaming concept. This letter presents MGRAPH, a novel approach to generate an incremental mosaic in real time

Cited by 20SourceScholar