Jonatan Scharff Willners — accepted AI-conference papers

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 ↗

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

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 ↗