Ignacio Carlucho — accepted AI-conference papers

2026

InsSo3D: Inertial Navigation System and 3D Sonar SLAM for Turbid Environment Inspection

Simon Archieri, Ahmet Fatih Cinar, Shu Pan, Scharff Willners Jonatan, Michele Grimaldi, Ignacio Carlucho +1

ICRA 2026poster

This paper presents InsSo3D, an accurate and efficient method for large-scale 3D Simultaneous Localisation and Mapping (SLAM) using a 3D Sonar and an Inertial Navigation System (INS). Unlike traditional sonar, which produces 2D images containing range and azimuth information but lacks elevation info…

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2026

VISO: Robust Underwater Visual-Inertial-Sonar SLAM with Photometric Rendering for Dense 3D Reconstruction

Shu Pan, Simon Archieri, Ahmet Fatih Cinar, Jonatan Scharff Willners, Ignacio Carlucho, Yvan Petillot

ICRA 2026poster

Visual challenges in underwater environments significantly hinder the accuracy of vision-based localisation and the high-fidelity dense reconstruction. In this paper, we propose VISO, a robust underwater SLAM system that fuses a stereo camera, an inertial measurement unit (IMU), and a 3D sonar to ac…

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2025

3DSSDF: Underwater 3D Sonar Reconstruction Using Signed Distance Functions

Simon Archieri, Juliette Drupt, Ahmet Fatih Cinar, Michele Grimaldi, Ignacio Carlucho, Jonatan Scharff Willners +1

ICRA 2025

Underwater autonomous robotic operations require online localization and 3D mapping. Because of the absence of absolute positioning underwater, these tasks strongly rely on embedded sensors, including proprioceptive or navigation sensors - which can be fused for an odometry, - and exteroceptive sens

Cited by 2 Source ↗Scholar ↗

2025

Context-Aware Behavior Learning with Heuristic Motion Memory for Underwater Manipulation

Markus Buchholz, Ignacio Carlucho, Michele Grimaldi, Maria Koskinopoulou, Yvan R. Petillot

IROS 2025

Autonomous motion planning is critical for efficient and safe underwater manipulation in dynamic marine environments. Current motion planning methods often fail to effectively utilize prior motion experiences and adapt to real-time uncertainties inherent in underwater settings. In this paper, we int

Cited by 1 Source ↗Scholar ↗

2025

MarineGym: A High-Performance Reinforcement Learning Platform for Underwater Robotics

Shuguang Chu, Zebin Huang, Yutong Li, Mingwei Lin, Dejun Li, Ignacio Carlucho +2

IROS 2025

This study introduces MarineGym, a high-performance reinforcement learning platform tailored for underwater robotics. It aims to address the limitations of existing underwater simulation environments in terms of reinforcement learning compatibility, training efficiency, and standardized benchmarking

Cited by 9 Source ↗Scholar ↗

2025

Stonefish: Supporting Machine Learning Research in Marine Robotics

Michele Grimaldi, Patryk Cieslak, Eduardo Ochoa, Vibhav Bharti, Hayat Rajani, Ignacio Carlucho +3

ICRA 2025

Simulations are highly valuable in marine robotics, offering a cost-effective and controlled environment for testing in the challenging conditions of underwater and surface operations. Given the high costs and logistical difficulties of real-world trials, simulators capable of capturing the operatio

Cited by 19 Source ↗code ↗Scholar ↗

2024

FRAGG-Map: Frustum Accelerated GPU-Based Grid Map

Michele Grimaldi, Narcis Palomeras, Ignacio Carlucho, Yvan R. Petillot, Pere Ridao Rodriguez

IROS 2024poster

In robotics, occupancy grids serve as required repositories of information about the environment in numerous applications. One such critical application is Simultaneous Localization and Mapping (SLAM), where robots dynamically scan and explore their surroundings while in motion. In the context of ex…

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2022

Robotic Manipulators Performing Smart Sanding Operation: A Vibration Approach

Joshua Nguyen, Manuel Bailey, Ignacio Carlucho, Corina Barbalata

ICRA 2022poster

This paper presents the design of a novel expert system for robotic manipulators performing sanding tasks on work surfaces. The expert system adjusts the velocity of the robotic manipulator based on the observed surface quality. These observation are obtained by an analysis of the raw force data pro…

Cited by 7 Source ↗Scholar ↗