Simultaneous Localization and Mapping

86 papers with code • 0 benchmarks • 14 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

Visual-Inertial Monocular SLAM with Map Reuse

ZuoJiaxing/Learn-ORB-VIO-Stereo-Mono 19 Oct 2016

In recent years there have been excellent results in Visual-Inertial Odometry techniques, which aim to compute the incremental motion of the sensor with high accuracy and robustness.

Kimera: an Open-Source Library for Real-Time Metric-Semantic Localization and Mapping

MIT-SPARK/Kimera 6 Oct 2019

We provide an open-source C++ library for real-time metric-semantic visual-inertial Simultaneous Localization And Mapping (SLAM).

Sparse-to-Dense: Depth Prediction from Sparse Depth Samples and a Single Image

fangchangma/sparse-to-dense 21 Sep 2017

We consider the problem of dense depth prediction from a sparse set of depth measurements and a single RGB image.

ORB-SLAM2: an Open-Source SLAM System for Monocular, Stereo and RGB-D Cameras

raulmur/ORB_SLAM2 20 Oct 2016

We present ORB-SLAM2 a complete SLAM system for monocular, stereo and RGB-D cameras, including map reuse, loop closing and relocalization capabilities.

Online Spatial Concept and Lexical Acquisition with Simultaneous Localization and Mapping

EmergentSystemLabStudent/SpCoSLAM 15 Apr 2017

We have proposed a nonparametric Bayesian spatial concept acquisition model (SpCoA).

Incremental Visual-Inertial 3D Mesh Generation with Structural Regularities

MIT-SPARK/Kimera 4 Mar 2019

We propose instead to tightly couple mesh regularization and state estimation by detecting and enforcing structural regularities in a novel factor-graph formulation.

LiDARTag: A Real-Time Fiducial Tag System for Point Clouds

UMich-BipedLab/LiDARTag 23 Aug 2019

Because of the LiDAR sensors' nature, rapidly changing ambient lighting will not affect the detection of a LiDARTag; hence, the proposed fiducial marker can operate in a completely dark environment.

3D Dynamic Scene Graphs: Actionable Spatial Perception with Places, Objects, and Humans

MIT-SPARK/Kimera 15 Feb 2020

Our second contribution is to provide the first fully automatic Spatial PerceptIon eNgine(SPIN) to build a DSG from visual-inertial data.

DXSLAM: A Robust and Efficient Visual SLAM System with Deep Features

ivipsourcecode/dxslam 12 Aug 2020

For visual SLAM algorithms, though the theoretical framework has been well established for most aspects, feature extraction and association is still empirically designed in most cases, and can be vulnerable in complex environments.

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).