collaborators

7 papers

cs.RO2026

3DRO: Lidar-level SE(3) Direct Radar Odometry Using a 2D Imaging Radar and a Gyroscope

Cedric Le Gentil, Daniil Lisus, Timothy D. Barfoot

Recently, the robotics community has regained interest in radar-based perception and state estimation. A 2D imaging radar provides dense 360deg information about the environment. D…

cs.RO2026

Dr-BA: Separable Optimization for Direct Radar Bundle Adjustment & Localization

Daniil Lisus, Cedric Le Gentil, Timothy D. Barfoot

This paper introduces Dr-BA, a first-of-its-kind radar bundle adjustment (BA) framework that operates directly on 2D spinning radar intensity images. Unlike camera or lidar sensors…

cs.RO2026

Dr-PoGO: Direct Radar Pose-Graph Optimization

Cedric Le Gentil, Weican Li, Leonardo Brizi +1

This paper introduces Dr-PoGO, a method for Simultaneous Localization And Mapping (SLAM) using a 2D spinning radar. Unlike cameras or lidars that require line-of-sight, millimetre-…

cs.RO2026

FoMo: A Multi-Season Dataset for Robot Navigation in Forêt Montmorency

Matěj Boxan, Gabriel Jeanson, Alexander Krawciw +5

The Forêt Montmorency (FoMo) dataset is a comprehensive multi-season data collection, recorded over the span of one year in a boreal forest. Featuring a unique combination of on-…

cs.RO2026

Boreas Road Trip: A Multi-Sensor Autonomous Driving Dataset on Challenging Roads

Daniil Lisus, Katya M. Papais, Cedric Le Gentil +4

The Boreas Road Trip (Boreas-RT) dataset extends the multi-season Boreas dataset to new and diverse locations that pose challenges for modern autonomous driving algorithms. Boreas-…

cs.RO2025

2Fast-2Lamaa: Large-Scale Lidar-Inertial Localization and Mapping with Continuous Distance Fields

Cedric Le Gentil, Raphael Falque, Daniil Lisus +1

This paper introduces 2Fast-2Lamaa, a lidar-inertial state estimation framework for odometry, mapping, and localization. Its first key component is the optimization-based undistort…