29 citations
- Centre de Robotique9 papers
- École Nationale Supérieure des Mines de ParisFR2 papers
- Huawei Technologies (France)FR2 papers
- Université Paris Sciences et LettresFR2 papers
- Aix-Marseille UniversitéFR1 paper
- Institut Supérieur de l'Aéronautique et de l'Espace (ISAE-SUPAERO)FR1 paper
- Laboratoire d’Informatique et SystèmesFR1 paper
- Local Initiatives Support CorporationUS1 paper
- ParisTechFR1 paper
- Safran Electronics (Canada)CA1 paper
- Safran (France)FR1 paper
- Schlumberger (British Virgin Islands)VG1 paper
9 papers
Invariant Smoothing for Localization: Including the IMU Biases
Paul Chauchat, Silvère Bonnabel, Axel Barrau
In this article we investigate smoothing (i.e., optimisation-based) estimation techniques for robot localization using an IMU aided by other localization sensors. We more particula…
ImPosing: Implicit Pose Encoding for Efficient Visual Localization
Arthur Moreau, Thomas Gilles, Nathan Piasco +3
We propose a novel learning-based formulation for visual localization of vehicles that can operate in real-time in city-scale environments. Visual localization algorithms determine…
GRI: General Reinforced Imitation and its Application to Vision-Based Autonomous Driving
Raphael Chekroun, Marin Toromanoff, Sascha Hornauer +1
Deep reinforcement learning (DRL) has been demonstrated to be effective for several complex decision-making applications such as autonomous driving and robotics. However, DRL is no…
LENS: Localization enhanced by NeRF synthesis
Arthur Moreau, Nathan Piasco, Dzmitry Tsishkou +2
Neural Radiance Fields (NeRF) have recently demonstrated photo-realistic results for the task of novel view synthesis. In this paper, we propose to apply novel view synthesis to th…
TrouSPI-Net: Spatio-temporal attention on parallel atrous convolutions and U-GRUs for skeletal pedestrian crossing prediction
Joseph Gesnouin, Steve Pechberti, Bogdan Stanciulescu +1
Understanding the behaviors and intentions of pedestrians is still one of the main challenges for vehicle autonomy, as accurate predictions of their intentions can guarantee their…
3D Point Cloud Registration with Multi-Scale Architecture and Unsupervised Transfer Learning
Sofiane Horache, Jean-Emmanuel Deschaud, François Goulette
We propose a method for generalizing deep learning for 3D point cloud registration on new, totally different datasets. It is based on two components, MS-SVConv and UDGE. Using Mult…