Yvan R. Petillot — 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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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…

Cited by 0 Source ↗Scholar ↗

2023

Adaptive Heading for Perception-Aware Trajectory Following

Jonatan Scharff Willners, Sean Katagiri, Shida Xu, Tomasz Luczynski, Joshua Roe, Yvan R. Petillot

ICRA 2023

This paper presents an adaptive heading approach for perception awareness during trajectory following. By adapting the heading of a robot to improve the feature tracking in the current mapped environment, the accuracy in localisation can be improved. This can have a significant advantage for autonom

Cited by 4 Source ↗Scholar ↗

2023

Observability-Aware Active Extrinsic Calibration of Multiple Sensors

Shida Xu, Jonatan Scharff Willners, Ziyang Hong, Kaicheng Zhang, Yvan R. Petillot, Sen Wang

ICRA 2023poster

The extrinsic parameters play a crucial role in multi-sensor fusion, such as visual-inertial Simultaneous Localization and Mapping(SLAM), as they enable the accurate alignment and integration of measurements from different sensors. However, extrinsic calibration is challenging in scenarios, such as…

Cited by 8 Source ↗Scholar ↗

2021

Robust Underwater Visual SLAM Fusing Acoustic Sensing

Elizabeth Vargas, Raluca Scona, Jonatan Scharff Willners, Tomasz Luczynski, Yu Cao, Sen Wang +1

ICRA 2021poster

In this paper, we propose an approach for robust visual Simultaneous Localisation and Mapping (SLAM) in underwater environments leveraging acoustic, inertial and altimeter/depth sensors. Underwater visual SLAM is challenging due to factors including poor visibility caused by suspended particles in w…

Cited by 61 Source ↗Scholar ↗

2021

Underwater Visual Acoustic SLAM with Extrinsic Calibration

Shida Xu, Tomasz Luczynski, Jonatan Scharff Willners, Ziyang Hong, Kaicheng Zhang, Yvan R. Petillot +1

IROS 2021poster

Underwater scenarios are challenging for visual Simultaneous Localization and Mapping (SLAM) due to limited visibility and intermittently losing structures in image views. In this paper, we propose a visual acoustic bundle adjustment system which fuses a camera and a Doppler Velocity Log (DVL) in a…

Cited by 32 Source ↗Scholar ↗

2019

Learning Generalizable Coupling Terms for Obstacle Avoidance via Low-Dimensional Geometric Descriptors

Èric Pairet, Paola Ardón, Michael N. Mistry, Yvan R. Petillot

RA-L 2019

Unforeseen events are frequent in the real-world environments where robots are expected to assist, raising the need for fast replanning of the on-going policy to guarantee operational safety. Inspired by human behavioral studies of obstacle avoidance and route selection, this letter presents a hiera

Cited by 33 Source ↗Scholar ↗

2019

Sampling-Based Path Planning for Cooperative Autonomous Maritime Vehicles to Reduce Uncertainty in Range-Only Localization

Jonatan Scharff Willners, Lachlan Toohey, Yvan R. Petillot

RA-L 2019

The following letter presents an adaptive path planning algorithm for cooperative localization in the maritime environment. It considers the scenario where an Autonomous Surface Vehicle (ASV) acts as a Communication and Navigation Aid (CNA) to support Autonomous Underwater Vehicles (AUVs) with range

Cited by 30 Source ↗Scholar ↗

2018

StaticFusion: Background Reconstruction for Dense RGB-D SLAM in Dynamic Environments

Raluca Scona, Mariano Jaimez, Yvan R. Petillot, Maurice Fallon, Daniel Cremers

ICRA 2018poster

Dynamic environments are challenging for visual SLAM as moving objects can impair camera pose tracking and cause corruptions to be integrated into the map. In this paper, we propose a method for robust dense RGB-D SLAM in dynamic environments which detects moving objects and simultaneously reconstru…

Cited by 248 Source ↗Scholar ↗

2017

Direct visual SLAM fusing proprioception for a humanoid robot

Raluca Scona, Simona Nobili, Yvan R. Petillot, Maurice Fallon

IROS 2017poster

In this paper we investigate the application of semi-dense visual Simultaneous Localisation and Mapping (SLAM) to the humanoid robotics domain. Challenges of visual SLAM applied to humanoids include the type of dynamic motion executed by the robot, a lack of features in man-made environments and the…

Cited by 41 Source ↗Scholar ↗