Search Results for author: Arnaud de La Fortelle

Found 8 papers, 0 papers with code

LENS: Localization enhanced by NeRF synthesis

no code implementations13 Oct 2021 Arthur Moreau, Nathan Piasco, Dzmitry Tsishkou, Bogdan Stanciulescu, Arnaud de La Fortelle

Neural Radiance Fields (NeRF) have recently demonstrated photo-realistic results for the task of novel view synthesis.

Data Augmentation Domain Adaptation +1

CoordiNet: uncertainty-aware pose regressor for reliable vehicle localization

no code implementations19 Mar 2021 Arthur Moreau, Nathan Piasco, Dzmitry Tsishkou, Bogdan Stanciulescu, Arnaud de La Fortelle

In this setup, structure-based methods require a large database, and we show that our proposal is a reliable alternative, achieving 29cm median error in a 1. 9km loop in a busy urban area

Autonomous Vehicles Camera Localization +1

Deep Sensor Fusion for Real-Time Odometry Estimation

no code implementations31 Jul 2019 Michelle Valente, Cyril Joly, Arnaud de La Fortelle

Cameras and 2D laser scanners, in combination, are able to provide low-cost, light-weight and accurate solutions, which make their fusion well-suited for many robot navigation tasks.

Robot Navigation Sensor Fusion +1

Classifying logistic vehicles in cities using Deep learning

no code implementations4 Jun 2019 Salma Benslimane, Simon Tamayo, Arnaud de La Fortelle

Major cities can use traffic counting as a tool to monitor the presence of delivery vehicles in order to implement intelligent city planning measures.

An LSTM Network for Real-Time Odometry Estimation

no code implementations22 Feb 2019 Michelle Valente, Cyril Joly, Arnaud de La Fortelle

The use of 2D laser scanners is attractive for the autonomous driving industry because of its accuracy, light-weight and low-cost.

Robotics

An LSTM Network for Highway Trajectory Prediction

no code implementations24 Jan 2018 Florent Altché, Arnaud de La Fortelle

In order to drive safely and efficiently on public roads, autonomous vehicles will have to understand the intentions of surrounding vehicles, and adapt their own behavior accordingly.

Autonomous Vehicles Trajectory Prediction

Finite-Time Stabilization of Longitudinal Control for Autonomous Vehicles via a Model-Free Approach

no code implementations5 Apr 2017 Philip Polack, Brigitte d'Andréa-Novel, Michel Fliess, Arnaud de La Fortelle, Lghani Menhour

This communication presents a longitudinal model-free control approach for computing the wheel torque command to be applied on a vehicle.

Autonomous Vehicles

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