Simultaneous Localization and Mapping

131 papers with code • 0 benchmarks • 18 datasets

Simultaneous localization and mapping (SLAM) is the task of constructing or updating a map of an unknown environment while simultaneously keeping track of an agent's location within it.

( Image credit: ORB-SLAM2 )

Libraries

Use these libraries to find Simultaneous Localization and Mapping models and implementations

Most implemented papers

Semantic Histogram Based Graph Matching for Real-Time Multi-Robot Global Localization in Large Scale Environment

gxytcrc/Semantic-Graph-based--global-Localization 19 Oct 2020

The core problem of visual multi-robot simultaneous localization and mapping (MR-SLAM) is how to efficiently and accurately perform multi-robot global localization (MR-GL).

Optimal Target Shape for LiDAR Pose Estimation

UMich-BipedLab/global_pose_estimation_for_optimal_shape 2 Sep 2021

However, symmetric shapes lead to pose ambiguity when using sparse sensor data such as LiDAR point clouds and suffer from the quantization uncertainty of the LiDAR.

LF-VISLAM: A SLAM Framework for Large Field-of-View Cameras with Negative Imaging Plane on Mobile Agents

flysoaryun/lf-vislam 12 Sep 2022

As loop closure on wide-FoV panoramic data further comes with a large number of outliers, traditional outlier rejection methods are not directly applicable.

ORB-SLAM: a Versatile and Accurate Monocular SLAM System

raulmur/ORB_SLAM 3 Feb 2015

This paper presents ORB-SLAM, a feature-based monocular SLAM system that operates in real time, in small and large, indoor and outdoor environments.

MultiCol-SLAM - A Modular Real-Time Multi-Camera SLAM System

urbste/MultiCol-SLAM 24 Oct 2016

The basis for most vision based applications like robotics, self-driving cars and potentially augmented and virtual reality is a robust, continuous estimation of the position and orientation of a camera system w. r. t the observed environment (scene).

Monocular LSD-SLAM Integration within AR System

MaXvanHeLL/ARift 8 Feb 2017

In this paper, we cover the process of integrating Large-Scale Direct Simultaneous Localization and Mapping (LSD-SLAM) algorithm into our existing AR stereo engine, developed for our modified "Augmented Reality Oculus Rift".

SLAM with Objects using a Nonparametric Pose Graph

BeipengMu/objectSLAM 19 Apr 2017

The \textit{data association} and \textit{simultaneous localization and mapping} (SLAM) problems are, individually, well-studied in the literature.

Unsupervised Learning of Depth and Ego-Motion from Monocular Video Using 3D Geometric Constraints

tensorflow/models CVPR 2018

We present a novel approach for unsupervised learning of depth and ego-motion from monocular video.

Semi-Dense 3D Reconstruction with a Stereo Event Camera

HKUST-Aerial-Robotics/ESVO ECCV 2018

Event cameras are bio-inspired sensors that offer several advantages, such as low latency, high-speed and high dynamic range, to tackle challenging scenarios in computer vision.

CNN-SVO: Improving the Mapping in Semi-Direct Visual Odometry Using Single-Image Depth Prediction

yan99033/CNN-SVO 1 Oct 2018

Reliable feature correspondence between frames is a critical step in visual odometry (VO) and visual simultaneous localization and mapping (V-SLAM) algorithms.