Slam
Showing 29 of 29 projects
A comprehensive collection of Python sample codes and a textbook for robotics algorithms, covering localization, mapping, SLAM, path planning, and control.
A Python code collection and textbook for robotics algorithms, featuring implementations for localization, mapping, SLAM, path planning, and control.
An accurate open-source library for visual, visual-inertial, and multi-map SLAM supporting monocular, stereo, and RGB-D cameras.
A real-time, tightly-coupled lidar-inertial odometry package for robust robot localization and mapping.
A computationally efficient and robust LiDAR-inertial odometry (LIO) package using a tightly-coupled iterated Kalman filter.
A Python package for evaluating and comparing odometry and SLAM algorithm trajectories with support for multiple formats and metrics.
A production-grade navigation framework for autonomous mobile robots built on ROS 2.
A curated list of open-source tools for professional robotic development in C++ and Python, covering ROS, autonomous driving, and aerospace.
An open-source C++ framework for optimizing graph-based nonlinear error functions, widely used in robotics and computer vision.
A versatile visual SLAM framework for monocular, stereo, and RGB-D cameras with map storage and reuse capabilities.
A curated list of robotics libraries, simulators, and software for developers and researchers.
A curated list of robotics libraries, simulators, and software for developers and researchers.
An open research-oriented C++ framework for multi-session and multi-robot visual-inertial mapping and localization.
A lightweight, ground-optimized lidar odometry and mapping system for ROS-compatible unmanned ground vehicles.
A real-time monocular SLAM system that creates large-scale semi-dense maps using a fully direct approach without feature extraction.
A direct sparse odometry library for real-time monocular visual SLAM, estimating camera motion from image sequences.
A ROS-based 2D SLAM library for lifelong mapping, localization, and multi-robot SLAM with pose-graph optimization.
A clean, simplified implementation of the LOAM algorithm for real-time LiDAR odometry and mapping using Eigen and Ceres Solver.
An efficient probabilistic 3D mapping framework based on octrees for robotics and computer vision applications.
A ROS package for real-time 6DOF SLAM using 3D LIDAR, featuring graph-based optimization with multiple sensor constraints.
A fast semi-direct monocular visual odometry pipeline for robotics and computer vision applications.
A robust LiDAR odometry pipeline that works out-of-the-box without parameter tuning for accurate robot localization.
A comprehensive C++ toolkit for mobile robotics and computer vision research, providing libraries for SLAM, Bayesian filtering, and 3D geometry.
A C++ library for real-time metric-semantic SLAM, building semantically annotated 3D meshes from camera and IMU data.
ROS packages for the TurtleBot3, a popular open-source robotics platform for education and research.
A curated collection of datasets for Simultaneous Localization and Mapping (SLAM) research, categorized by topic, platform, and environment.
A modular C++ library implementing the Iterative Closest Point (ICP) algorithm for aligning 2D and 3D point clouds in robotics and computer vision.
A realtime LiDAR odometry and mapping (LOAM) method for state estimation and mapping using 3D lidar sensors like Velodyne VLP16.
A real-time monocular SLAM system for computing camera trajectories and sparse 3D scene reconstruction.
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