67 citations · 194 across the 25 of their papers we have counts for
8 papers · 1 filter
Toward Robust LiDAR Semantic Segmentation for Real-World Deployment: Evaluation under Coarse Labels, Adverse Conditions, and Domain Shifts
Samir Abou Haidar, Alexandre Chariot, Mehdi Darouich +2
LiDAR-based semantic segmentation is a core perception module for autonomous vehicles and mobile robots. Despite the strong performance of recent state-of-the-art methods on standa…
Leg Exoskeleton Odometry using a Limited FOV Depth Sensor
Fabio Elnecave Xavier, Matis Viozelange, Guillaume Burger +3
For leg exoskeletons to operate effectively in real-world environments, they must be able to perceive and understand the terrain around them. However, unlike other legged robots, e…
Are We Ready for Real-Time LiDAR Semantic Segmentation in Autonomous Driving?
Samir Abou Haidar, Alexandre Chariot, Mehdi Darouich +2
Within a perception framework for autonomous mobile and robotic systems, semantic analysis of 3D point clouds typically generated by LiDARs is key to numerous applications, such as…
Multi-IMU Proprioceptive State Estimator for Humanoid Robots
Fabio Elnecave Xavier, Guillaume Burger, Marine Pétriaux +2
Algorithms for state estimation of humanoid robots usually assume that the feet remain flat and in a constant position while in contact with the ground. However, this hypothesis is…
AdaSplats: Adaptive Splatting of Point Clouds for Accurate 3D Modeling and Real-time High-Fidelity LiDAR Simulation
Jean Pierre Richa, Jean-Emmanuel Deschaud, François Goulette +1
LiDAR sensors provide rich 3D information about their surrounding{s} and are becoming increasingly important for autonomous vehicles tasks such as {localization}, semantic segmenta…
CT-ICP: Real-time Elastic LiDAR Odometry with Loop Closure
Pierre Dellenbach, Jean-Emmanuel Deschaud, Bastien Jacquet +1
Multi-beam LiDAR sensors are increasingly used in robotics, particularly with autonomous cars for localization and perception tasks, both relying on the ability to build a precise…
What's in My LiDAR Odometry Toolbox?
Pierre Dellenbach, Jean-Emmanuel Deschaud, Bastien Jacquet +1
With the democratization of 3D LiDAR sensors, precise LiDAR odometries and SLAM are in high demand. New methods regularly appear, proposing solutions ranging from small variations…
IMLS-SLAM: scan-to-model matching based on 3D data
Jean-Emmanuel Deschaud
The Simultaneous Localization And Mapping (SLAM) problem has been well studied in the robotics community, especially using mono, stereo cameras or depth sensors. 3D depth sensors,…