Pascal Pomarede — accepted AI-conference papers

2022

Combined Grid and Feature-based Mapping of Metal Structures with Ultrasonic Guided Waves

Othmane-Latif Ouabi, Ayoub Ridani, Pascal Pomarede, Neil Zeghidour, Nico F. Declercq, Matthieu Geist +1

ICRA 2022poster

The ultrasonic mapping of plate-based facilities is an essential step towards the robotic inspection of large metal structures such as storage tanks or ship hulls. This work proposes a novel framework that exploits ultrasonic echoes to recover grid-based and feature-based spatial representations joi…

Cited by 2 Source ↗Scholar ↗

2021

A FastSLAM Approach Integrating Beamforming Maps for Ultrasound-Based Robotic Inspection of Metal Structures

Othmane-Latif Ouabi, Pascal Pomarede, Matthieu Geist, Nico F. Declercq, Cédric Pradalier

RA-L 2021

We present a novel FastSLAM approach for a robotic system inspecting structures made of large metal plates. By taking advantage of the reflections of ultrasonic guided waves on the plate boundaries, it is possible to recover, with enough precision, both the plate shape and the robot trajectory. Cont

Cited by 12 Source ↗Scholar ↗

2020

On-plate localization and mapping for an inspection robot using ultrasonic guided waves: a proof of concept

Cédric Pradalier, Othmane-Latif Ouabi, Pascal Pomarede, Jan Steckel

IROS 2020poster

This paper presents a proof-of-concept for a localization and mapping system for magnetic crawlers performing inspection tasks on structures made of large metal plates. By relying on ultrasonic guided waves reflected from the plate edges, we show that it is possible to recover the plate geometry and…

Cited by 7 Source ↗Scholar ↗