[SLAM survey] IROS2019 SLAM 관련 논문 정리

IROS2019 SLAM 관련 논문 정리

SuMa++Efficient LiDAR-based Semantic SLAM

SuMa (Efficient Surfel-Based SLAM using 3D Laser Range Data in Urban Environments) - RSS2018

RangeNet++: Fast and Accurate LiDAR Semantic Segmentation

Robot Localization in Floor Plans Using a Room Layout Edge Extraction Network

Free-Space Features: Global Localization in 2D Laser SLAM Using Distance Function Maps

FLAME: Feature-Likelihood Based Mapping and Localization for Autonomous Vehicles

ORBSLAM-Atlas: a robust and accurate multi-map system

Exploiting Sparse Semantic HD Maps for Self-Driving Vehicle Localization

Lane Marking Learning based on Crowdsourced Data

Fusing Lidar Data and Aerial Imagery with Perspective Correction for Precise Localization in Urban Canyons

Automatic Spatial Template Generation for Realistic 3D Modeling of Large-Scale Indoor Spaces

A Robust Laser-Inertial Odometry and Mapping Method for Large-Scale Highway Environments

Visual-Inertial Localization with Prior LiDAR Map Constraints

Degeneracy-Aware Factors with Applications to Underwater SLAM

Visual-Inertial Odometry with Point and Line Features

LIC-Fusion: LiDAR-Inertial-Camera Odometry

Stereo Visual Inertial LiDAR Simultaneous Localization and Mapping