Search Results for author: Julien Moras

Found 8 papers, 1 papers with code

Online Localisation and Colored Mesh Reconstruction Architecture for 3D Visual Feedback in Robotic Exploration Missions

no code implementations21 Jul 2022 Quentin Serdel, Christophe Grand, Julien Marzat, Julien Moras

This paper introduces an Online Localisation and Colored Mesh Reconstruction (OLCMR) ROS perception architecture for ground exploration robots aiming to perform robust Simultaneous Localisation And Mapping (SLAM) in challenging unknown environments and provide an associated colored 3D mesh representation in real time.

Surface Reconstruction

OV$^{2}$SLAM : A Fully Online and Versatile Visual SLAM for Real-Time Applications

1 code implementation8 Feb 2021 Maxime Ferrera, Alexandre Eudes, Julien Moras, Martial Sanfourche, Guy Le Besnerais

Many applications of Visual SLAM, such as augmented reality, virtual reality, robotics or autonomous driving, require versatile, robust and precise solutions, most often with real-time capability.

Autonomous Driving Monocular Visual Odometry +2

Learning-based vs Model-free Adaptive Control of a MAV under Wind Gust

no code implementations29 Jan 2021 Thomas Chaffre, Julien Moras, Adrien Chan-Hon-Tong, Julien Marzat, Karl Sammut, Gilles Le Chenadec, Benoit Clement

We compare it, in realistic simulations, to a model-free controller that uses the same deep reinforcement learning framework for the control of a micro aerial vehicle under wind gust.

reinforcement-learning

Technical Report: Co-learning of geometry and semantics for online 3D mapping

no code implementations4 Nov 2019 Marcela Carvalho, Maxime Ferrera, Alexandre Boulch, Julien Moras, Bertrand Le Saux, Pauline Trouvé-Peloux

This paper is a technical report about our submission for the ECCV 2018 3DRMS Workshop Challenge on Semantic 3D Reconstruction \cite{Tylecek2018rms}.

3D Reconstruction Autonomous Navigation +1

AQUALOC: An Underwater Dataset for Visual-Inertial-Pressure Localization

no code implementations31 Oct 2019 Maxime Ferrera, Vincent Creuze, Julien Moras, Pauline Trouvé-Peloux

The data acquisition is performed using Remotely Operated Vehicles equipped with a monocular monochromatic camera, a low-cost inertial measurement unit, a pressure sensor and a computing unit, all embedded in a single enclosure.

Simultaneous Localization and Mapping

The Aqualoc Dataset: Towards Real-Time Underwater Localization from a Visual-Inertial-Pressure Acquisition System

no code implementations19 Sep 2018 Maxime Ferrera, Julien Moras, Pauline Trouvé-Peloux, Vincent Creuze, Denis Dégez

This paper presents a new underwater dataset acquired from a visual-inertial-pressure acquisition system and meant to be used to benchmark visual odometry, visual SLAM and multi-sensors SLAM solutions.

Visual Odometry

Real-time Monocular Visual Odometry for Turbid and Dynamic Underwater Environments

no code implementations15 Jun 2018 Maxime Ferrera, Julien Moras, Pauline Trouvé-Peloux, Vincent Creuze

In the context of robotic underwater operations, the visual degradations induced by the medium properties make difficult the exclusive use of cameras for localization purpose.

Monocular Visual Odometry Optical Flow Estimation

Cannot find the paper you are looking for? You can Submit a new open access paper.