AirSim AirSim Announcement: This repository will be archived next year In 2017, Microsoft Research created AirSim as a simulation platform for AI research and experimentation. Five years later, this research project has achieved its goals and made significant progress—becoming a common way to share research code and test new ideas for aerial AI development and […]
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VINS-Fusion Sources: https://github.com/HKUST-Aerial-Robotics/VINS-Fusion https://github.com/JanekDev/VINS-Fusion-ROS2-humble-arm ROS2 Humble version of VINS-Fusion, suitable for Notice You can now run VINS-Fusion on ROS2 Humble using ros2 launch or ros2 run. The code is mostly based on this repository by zinuok . Prerequisites Construction Play EuRoC dataset To download the sample EuRoC dataset package, run get_example_data.sh the script. Then use the script to convert the
RTAB-MAP Source: https://github.com/introlab/rtabmap RTAB-Map library and standalone application. For more information (e.g., papers, major updates), visit the RTAB-Map homepage. For installation instructions and examples, visit the RTAB-Map wiki. To use RTAB-Map under ROS, visit the rtabmap page on the ROS wiki. Acknowledgements This project is supported by the IntRoLab (Intelligent/Interactive/Integrated/Interdisciplinary Robotics Laboratory) in Sherbrooke, Quebec, Canada . ROS ros-$ROS_DISTRO-rtabmap
ORB-SLAM3 Source: https://github.com/UZ-SLAMLab/ORB_SLAM3 V1.0, December **Authors:** Carlos Campos, Richard Elvira, Juan J. Gómez Rodríguez, José MM Montiel, Juan D. Tardos. The changelog describes the features of each version. ORB-SLAM3 is the first real-time SLAM library capable of performing visual, visual-inertial, and multi-map SLAM using monocular, stereo, and RGB-D cameras, supporting both pinhole and fisheye lens models. Across all sensor configurations, ORB-SLAM3 achieves robustness comparable
FAST-LIO Source: https://github.com/hku-mars/FAST_LIO/tree/ROS2 ROS2 Fork repo Maintainer: Ericsiii Related Work and Extended SLAM： Control and Plan： FAST-LIO FAST-LIO (Fast LiDAR-Inertial Odometry) is a computationally efficient and robust lidar-inertial odometry software package. It fuses lidar feature points with IMU data using a tightly coupled iterative extended Kalman filter, enabling robust navigation in fast-moving, noisy, or cluttered environments, even without
Cartographer Source: https://google-cartographer.readthedocs.io/en/latest/# Cartographer is a system that provides 2D and 3D real-time simultaneous localization and mapping (SLAM) across multiple platforms and sensor configurations. Technical Cartographer is a standalone C++ library. To get started quickly, use our ROS integration. ROS integration is provided by the Cartographer ROS codebase. You can find complete documentation on how to use Cartographer to integrate
Navigation2 Source: https://docs.nav2.org/index.html Overview Nav2 is the professionally supported spiritual successor to the ROS navigation stack. The project aims to find a safe way to enable mobile robots to complete complex tasks in a wide variety of environments and robot kinematics. It not only enables movement from point A to point B, but also handles intermediate
FastPlanner Source: https://github.com/HKUST-Aerial-Robotics/Fast-Planner Fast-Planner is designed to help quadrotors achieve rapid flight in complex, unknown environments. It includes a rich set of carefully designed planning algorithms and provides a foundational code framework and algorithms that support several popular open-source drone projects, including ego-planner, FUEL, and RACER. information: Authors: Zhou Boyu and Shen Shaojie from the Aerial Robotics Group of the Hong Kong University of Science
Ego Planner Source: https://github.com/ZJU-FAST-Lab/ego-planner-swarm/tree/ros2_version 1. Required 2.Prerequisites Maybe some of my publish and subscribe settings are not written correctly. Using the default FastDDS of ROS2 will cause the program to run very slowly. I haven’t found the reason yet, so please change DDS to cyclonedds as follows 2.1 Installing 2.2 Modify the default 2.3 Check if
Collision Avoidance Collision avoidance can be used to automatically slow down and stop the drone before it collides with an obstacle. This feature can be enabled when a multirotor is using acceleration-based positioning mode (or when a vertical takeoff and landing aircraft is in multirotor mode). It can be enabled for multi-rotor aircraft in position mode and can