9 citations · 11 across the 7 of their papers we have counts for
11 papers
Low-Latency Mapless ESDF Queries for MAV Reactive Collision Avoidance
Leonard Freißmuth, Cedric Le Gentil, Helen Oleynikova +1
Reactive collision avoidance in unknown, cluttered environments must perceive obstacles and correct motion within milliseconds. Existing methods rely on maps for high-rate collisio…
Dr-LiSA: Direct Radar-Lidar Scan Alignment for SE(3) Localization
Alex Zhang, Daniil Lisus, Cedric Le Gentil +1
This paper introduces Dr-LiSA, a first-of-its-kind direct method for localizing 2D spinning radar intensity measurements in against 3D lidar maps. Radar-lidar localization…
DRT&R: Direct Radar Teach & Repeat
Alexander Krawciw, Daniil Lisus, Cedric Le Gentil +1
Radar-based navigation is appealing for its robustness to adverse conditions involving airborne particles, such as precipitation, dust, fog, and smoke, that can cause lidar-based s…
Scalix: Uncertainty-Aware Scale-Consistent Monocular SLAM
Sebastian Barbas Laina, Tianyi Zhang, Panagiotis Petropoulakis +5
Cameras are ubiquitous sensors in robotics due to their compact form factor and the perceptual richness captured through visual information. Monocular SLAM enables robots to unders…
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…
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…
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-…
BIEVR-LIO: Robust LiDAR-Inertial Odometry through Bump-Image-Enhanced Voxel Maps
Patrick Pfreundschuh, Turcan Tuna, Cedric Le Gentil +3
Reliable odometry is essential for mobile robots as they increasingly enter more challenging environments, which often contain little information to constrain point cloud registrat…
Breaking the Static Assumption: A Dynamic-Aware LIO Framework Via Spatio-Temporal Normal Analysis
Chen Zhiqiang, Le Gentil Cedric, Lin Fuling +5
This paper addresses the challenge of Lidar-Inertial Odometry (LIO) in dynamic environments, where conventional methods often fail due to their static-world assumptions. Traditiona…
Dynamic Object Detection in Range data using Spatiotemporal Normals
Raphael Falque, Cedric Le Gentil, Fouad Sukkar
On the journey to enable robots to interact with the real world where humans, animals, and unpredictable elements are acting as independent agents; it is crucial for robots to have…
IN2LAAMA: INertial Lidar Localisation Autocalibration And MApping
Cedric Le Gentil, Teresa Vidal-Calleja, Shoudong Huang
In this paper, we present INertial Lidar Localisation Autocalibration And MApping (IN2LAAMA): an offline probabilistic framework for localisation, mapping, and extrinsic calibratio…