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Riccardo Giubilato

11 accepted papers

2026

Markerless Robot Detection and 6D Pose Estimation for Multi-Agent SLAM

Markus Rueggeberg, Maximilian Ulmer, Maximilian Durner, Wout Boerdijk, Marcus Gerhard Müller, Rudolph Triebel +1
ICRA 2026poster

The capability of multi-robot SLAM approaches to merge localization history and maps from different observers is often challenged by the difficulty in establishing data association. Loop closure detection between perceptual inputs of different robotic agents is easily compromised in the context of p…

Cited by 0Source ↗PDF ↗Scholar ↗
2026

Multi-Modal Loop Closure Detection with Foundation Models in Severely Unstructured Environments

Laura Alejandra Encinar Gonzalez, John Folkesson, Rudolph Triebel, Riccardo Giubilato
ICRA 2026poster

Robust loop closure detection is a critical component of Simultaneous Localization and Mapping (SLAM) algorithms in GNSS-denied environments, such as in the context of planetary exploration. In these settings, visual place recognition often fails due to aliasing and weak textures, while LiDAR-based …

Cited by 0Source ↗PDF ↗code ↗Scholar ↗
2024

Perception-aware Full Body Trajectory Planning for Autonomous Systems using Motion Primitives

Moritz Kuhne, Riccardo Giubilato, Martin J. Schuster, Maximo A. Roa
IROS 2024poster

Many robotic systems rely on visual sensing to accomplish simultaneously the tasks of state estimation, mapping, and path planning. One one hand, the usage of camera sensors represents a power-efficient and lightweight option for solving this problem. On the other hand, these tasks pose requirements…

Cited by 0Source ↗code ↗Scholar ↗
2024

Unifying Local and Global Multimodal Features for Place Recognition in Aliased and Low-Texture Environments

Alberto García-Hernández, Riccardo Giubilato, Klaus H. Strobl, Javier Civera, Rudolph Triebel
ICRA 2024poster

Perceptual aliasing and weak textures pose significant challenges to the task of place recognition, hindering the performance of Simultaneous Localization and Mapping (SLAM) systems. This paper presents a novel model, called UMF (standing for Unifying Local and Global Multimodal Features) that 1) le…

Cited by 3Source ↗code ↗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 16Source ↗Scholar ↗
2022

Challenges of SLAM in Extremely Unstructured Environments: The DLR Planetary Stereo, Solid-State LiDAR, Inertial Dataset

Riccardo Giubilato, Wolfgang Stürzl, Armin Wedler, Rudolph Triebel
RA-L 2022

We present the DLR Planetary Stereo, Solid-State LiDAR, Inertial (S3LI) dataset, recorded on Mt. Etna, Sicily, an environment analogous to the Moon and Mars, using a hand-held sensor suite with attributes suitable for implementation on a space-like mobile rover. The environment is characterized by c

Cited by 38Source ↗Scholar ↗
2021

Multi-Modal Loop Closing in Unstructured Planetary Environments with Visually Enriched Submaps

Riccardo Giubilato, Mallikarjuna Vayugundla, Wolfgang Stürzl, Martin J. Schuster, Armin Wedler, Rudolph Triebel
IROS 2021poster

Future planetary missions will rely on rovers that can autonomously explore and navigate in unstructured environments. An essential element is the ability to recognize places that were already visited or mapped. In this work, we leverage the ability of stereo cameras to provide both visual and depth…

Cited by 8Source ↗Scholar ↗
2020

Gaussian Process Gradient Maps for Loop-Closure Detection in Unstructured Planetary Environments

Cedric Le Gentil, Mallikarjuna Vayugundla, Riccardo Giubilato, Wolfgang Stürzl, Teresa Vidal-Calleja, Rudolph Triebel
IROS 2020poster

The ability to recognize previously mapped locations is an essential feature for autonomous systems. Unstructured planetary-like environments pose a major challenge to these systems due to the similarity of the terrain. As a result, the ambiguity of the visual appearance makes state-of-the-art visua…

Cited by 18Source ↗Scholar ↗
2020

Relocalization With Submaps: Multi-Session Mapping for Planetary Rovers Equipped With Stereo Cameras

Riccardo Giubilato, Mallikarjuna Vayugundla, Martin J. Schuster, Wolfgang Stürzl, Armin Wedler, Rudolph Triebel +1
RA-L 2020

To enable long term exploration of extreme environments such as planetary surfaces, heterogeneous robotic teams need the ability to localize themselves on previously built maps. While the Localization and Mapping problem for single sessions can be efficiently solved with many state of the art soluti

Cited by 21Source ↗Scholar ↗
2020

The ARCHES Space-Analogue Demonstration Mission: Towards Heterogeneous Teams of Autonomous Robots for Collaborative Scientific Sampling in Planetary Exploration

Martin J. Schuster, Marcus Gerhard Müller, Sebastian G. Brunner, Hannah Lehner, Peter Lehner, Ryo Sakagami +32
RA-L 2020

Teams of mobile robots will play a crucial role in future missions to explore the surfaces of extraterrestrial bodies. Setting up infrastructure and taking scientific samples are expensive tasks when operating in distant, challenging, and unknown environments. In contrast to current single-robot spa

Cited by 92Source ↗Scholar ↗
2018

Scale Correct Monocular Visual Odometry Using a LiDAR Altimeter

Riccardo Giubilato, Sebastiano Chiodini, Marco Pertile, Stefano Debei
IROS 2018poster

The inherent scale ambiguity in monocular vision is a well known issue that forces the integration of other sensory sources to obtain metric references. However, 2D or 3D LiDARs and RGB-D sensors, while guaranteeing metrological accuracy, impose a non negligible burden both in terms of computational…

Cited by 24Source ↗Scholar ↗