Search Results for "slam"
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Showing 48 open source projects for "slam"
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Isaac ROS Visual SLAM
Visual SLAM/odometry package based on NVIDIA-accelerated cuVSLAM
Discover a faster, easier way to build advanced AI robotics applications with the NVIDIA Isaac™ ROS collection of accelerated computing packages and AI models, bringing NVIDIA acceleration to ROS developers everywhere. Isaac ROS Visual SLAM provides a high-performance, best-in-class ROS 2 package for VSLAM (visual simultaneous localization and mapping). This package uses one or more stereo cameras and optionally an IMU to estimate odometry as an input to navigation. It is GPU-accelerated... -
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rtabmap
RTAB-Map library and standalone application
RTAB-Map (Real-Time Appearance-Based Mapping) is a RGB-D, Stereo and Lidar Graph-Based SLAM approach based on an incremental appearance-based loop closure detector. The loop closure detector uses a bag-of-words approach to determine how likely a new image comes from a previous location or a new location. When a loop closure hypothesis is accepted, a new constraint is added to the map’s graph, then a graph optimizer minimizes the errors in the map. A memory management approach is used to limit... -
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lidarslam_ros2
ROS 2 package of 3D lidar slam using ndt/gicp registration
ROS 2 package of 3D lidar slam using ndt/gicp registration and pose-optimization. ros2 slam package of the frontend using OpenMP-boosted gicp/ndt scan matching and the backend using graph-based slam. -
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Caesar.jl
Robust robotic localization and mapping
A multimodal/non-Gaussian robotic toolkit for localization and mapping -- reducing the barrier of entry for sensor/data fusion tasks, including Simultaneous Localization and Mapping (SLAM). Code changes are currently tracked via Github's integrated Milestone/Issues/PR system. -
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The Hypersim Dataset
Photorealistic Synthetic Dataset for Holistic Indoor Scene
Hypersim is a large-scale, photorealistic synthetic dataset and tooling suite for indoor scene understanding research. It provides richly annotated renderings—RGB, depth, surface normals, instance and semantic segmentations, and material/lighting metadata—produced from high-fidelity virtual environments. The dataset spans diverse furniture layouts, room types, and camera trajectories, enabling robust training for geometry, segmentation, and SLAM-adjacent tasks. Rendering pipelines and utilities... -
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CoordinateTransformations.jl
A fresh approach to coordinate transformations
... it easy to perform optimization and therefore ideal for computer vision applications such as SLAM (simultaneous localization and mapping). -
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Theseus
A library for differentiable nonlinear optimization
Theseus is a library for differentiable nonlinear optimization that lets you embed solvers like Gauss-Newton or Levenberg–Marquardt inside PyTorch models. Problems are expressed as factor graphs with variables on manifolds (e.g., SE(3), SO(3)), so classical robotics and vision tasks—bundle adjustment, pose graph optimization, hand–eye calibration—can be written succinctly and solved efficiently. Because solves are differentiable, you can backpropagate through optimization to learn cost... -
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Tomb
the Crypto Undertaker
Tomb is a minimalistic command-line tool for creating and managing encrypted “tombs,” which are files that act as mountable, private storage vaults. Under the hood it uses Linux dm-crypt with LUKS for strong, disk-level encryption, and separates the key material from the vault itself to improve security workflows. Keys can be protected with passphrases and even hidden via steganography inside innocuous files, giving you options for concealment and off-device storage. The interface is... -
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CoTracker
CoTracker is a model for tracking any point (pixel) on a video
.... Its transformer-style architecture aggregates information both along time and across points, allowing it to recover tracks even after brief disappearances. The repository ships with inference scripts, pretrained weights, and simple interfaces to seed points, run tracking, and export trajectories for downstream tasks. Typical uses include correspondence building, motion analysis, dynamic SLAM priors, video editing masks, and evaluation of geometric consistency in real scenes. -
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GraphView
Bundle Adjustment Graph Visualisation
A simple OpenGL ES viewer of Bundle Adjustment (BA) graphs. This is a tool, useful with SLAM ++. -
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The 3D Toolkit provides algorithms and methods to process 3D point clouds. In includes automatic precise registration (6D simultaneous localization and mapping, 6D SLAM) and other tools, e.g., a fast 3D viewer, plane extraction software, etc.
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BTS-SIO-SLAM-CYBER-INTERVENTION
Cybersecurity intervention for BTS SIO SLAM
You will find all the files to prepare a security intervention in a BTS SIO (SLAM - development part). This training aims to highlight the role of the developer in cybersecurity. Different software vulnerabilities are presented as well as the good practices that allow limiting them. To this goal, some aspects of a secure system design are addressed. Informations and documentation are here: https://sourceforge.net/p/bts-sio-slam-cyberintervention/wiki/Home/. -
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ucoslam
Visual SLAM. https://www.uco.es/investiga/grupos/ava/portfolio/ucoslam
https://www.uco.es/investiga/grupos/ava/portfolio/ucoslam/ UcoSLAM is a library for Simultaneous Localization and Mapping using keypoints that able to operate with monocular cameras, stereo cameras, rgbd cameras. Additionally, our library is fully integrated with the ArUco library for detecting squared fiducial markers. They can be placed in the environment to improve tracking. See doc at https://drive.google.com/file/d/1bFIEPKadVKKbr_SkIUxGkipIe0t1AxpN/view?usp=share_link -
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LaMa
LaMa - A Localization and Mapping library
LaMa is a C++11 software library for robotic localization and mapping developed at the Intelligent Robotics and Systems (IRIS) Laboratory at the University of Aveiro - Portugal. It includes a framework for 3D volumetric grids (for mapping), a localization algorithm based on scan matching, and two SLAM solutions (an Online SLAM and a Particle Filter SLAM). The main feature is efficiency. Low computational effort and low memory usage whenever possible. The minimum viable computer to run our... -
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Slam Mirror Bot
Aria/qBittorrent Telegram Mirror/Leech Bot
Slam Mirror Bot is a multipurpose Telegram Bot written in Python for mirroring files on the Internet to our beloved Google Drive. Based on python-aria-mirror-bot. -
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Introduction-to-Autonomous-Robots
Introduction to Autonomous Robots
An open textbook focusing on computational principles of autonomous robots. The source-code is released under Creative Commons 4.0 (CC-BY-NC-ND), whereas the print version is copyrighted by MIT Press. You are therefore permitted to use images and content from the book for non-commercial purposes (including teaching) with proper attribution, but you cannot post compiled versions of the book online. In order to compile a PDF of this book yourself, you either need a working implementation of... -
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libRSF
A robust sensor fusion library for online localization
The libRSF is an open source C++ library that provides several components that are required to estimate the state of a (robotic) system based on probabilistic methods. By applying the factor graph concept, well known from Graph SLAM, libRSF provides a robust solution for many sensor fusion problems. The general idea of factor graphs is to describe the state estimation problem as a graph of nodes (the state variables) that are connected by factors (measurements). The resulting graph optimization... -
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Cartographer
Cartographer is a system that provides real-time localization
Cartographer is a system that provides real-time simultaneous localization and mapping (SLAM) in 2D and 3D across multiple platforms and sensor configurations. -
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SLAMBook-en
The English version of 14 lectures on visual SLAM
This project is the English version of “14 Lectures on Visual SLAM: From Theory to Practice,” a text and teaching resource about visual simultaneous localization and mapping (SLAM). It provides the full LaTeX source (formerly Markdown) for all 14 chapters, letting readers compile and study the material systematically. Within the repository you’ll find organized subfolders (e.g. chapters, latex, resources) containing the lecture contents, references, figures, and supporting assets for each part... -
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gradslam
gradslam is an open source differentiable dense SLAM library
gradslam is an open-source framework providing differentiable building blocks for simultaneous localization and mapping (SLAM) systems. We enable the usage of dense SLAM subsystems from the comfort of PyTorch. The question of “representation” is central in the context of dense simultaneous localization and mapping (SLAM). Newer learning-based approaches have the potential to leverage data or task performance to directly inform the choice of representation. However, learning representations... -
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Kimera-VIO
Visual Inertial Odometry with SLAM capabilities and 3D Mesh generation
Visual Inertial Odometry with SLAM capabilities and 3D Mesh generation. Kimera-VIO is a Visual Inertial Odometry pipeline for accurate State Estimation from Stereo + IMU data. It can optionally use Mono + IMU data instead of stereo cameras. -
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SLAM++
high-performance nonlinear least squares solver for graph problems
SLAM++ is a minimalist implementation of incremental nonlinear least squares, containing lighting fast implementation of linear algebra on sparse block matrices. It is aimed for use in 3D reconstruction or robotics. -
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MATLAB Robotics
MATLAB sample codes for mobile robot navigation
MATLABRobotics is a collection of robotics-related algorithms and simulation tools implemented in MATLAB. The repository brings together a wide range of robotics functionality, including path planning, control, localization, and mapping. It provides practical algorithmic implementations such as A*, RRT, Kalman filters, particle filters, and SLAM, making it a valuable resource for students, researchers, and developers learning or prototyping robotics applications. The code is written... -
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