<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Ros2 on Noureddine RAMDI</title><link>https://ramdi.fr/tags/ros2/</link><description>Recent content in Ros2 on Noureddine RAMDI</description><generator>Hugo</generator><language>en</language><lastBuildDate>Sat, 23 May 2026 20:41:27 +0000</lastBuildDate><atom:link href="https://ramdi.fr/tags/ros2/index.xml" rel="self" type="application/rss+xml"/><item><title>Exploring autonomy_stack_go2: A ROS2 and Unity-based autonomous vehicle simulation stack</title><link>https://ramdi.fr/github-stars/exploring-autonomy-stack-go2-a-ros2-and-unity-based-autonomous-vehicle-simulation-stack/</link><pubDate>Sat, 23 May 2026 20:41:14 +0000</pubDate><guid>https://ramdi.fr/github-stars/exploring-autonomy-stack-go2-a-ros2-and-unity-based-autonomous-vehicle-simulation-stack/</guid><description>autonomy_stack_go2 is a C++ ROS2 stack integrated with Unity for autonomous vehicle simulation. Supports ROS2 Foxy and Humble with waypoint navigation in RVIZ.</description></item><item><title>FusionCore: A robust ROS 2 Unscented Kalman Filter for sensor fusion with adaptive GPS outlier rejection</title><link>https://ramdi.fr/github-stars/fusioncore-a-robust-ros-2-unscented-kalman-filter-for-sensor-fusion-with-adaptive-gps-outlier-rejection/</link><pubDate>Sat, 23 May 2026 20:41:14 +0000</pubDate><guid>https://ramdi.fr/github-stars/fusioncore-a-robust-ros-2-unscented-kalman-filter-for-sensor-fusion-with-adaptive-gps-outlier-rejection/</guid><description>FusionCore is a ROS 2 SDK implementing an Unscented Kalman Filter that fuses IMU, wheel encoders, and GPS at 100 Hz with adaptive noise covariance and robust GPS outlier rejection.</description></item><item><title>Learning autonomous mobile robots with ROS 2: a hands-on course companion</title><link>https://ramdi.fr/github-stars/learning-autonomous-mobile-robots-with-ros-2-a-hands-on-course-companion/</link><pubDate>Sat, 23 May 2026 20:41:14 +0000</pubDate><guid>https://ramdi.fr/github-stars/learning-autonomous-mobile-robots-with-ros-2-a-hands-on-course-companion/</guid><description>This repo complements a ROS 2 course with hands-on C++/Python exercises, Gazebo simulation, and real robot control focusing on localization, mapping, and obstacle avoidance.</description></item><item><title>Deploying RL-trained motion tracking policies on legged robots with motion_tracking_controller</title><link>https://ramdi.fr/github-stars/deploying-rl-trained-motion-tracking-policies-on-legged-robots-with-motion-tracking-controller/</link><pubDate>Mon, 04 May 2026 10:23:02 +0000</pubDate><guid>https://ramdi.fr/github-stars/deploying-rl-trained-motion-tracking-policies-on-legged-robots-with-motion-tracking-controller/</guid><description>motion_tracking_controller is a C++ ROS 2 package deploying RL-trained motion tracking policies on legged robots with ONNX inference and embedded robot control metadata.</description></item><item><title>Inside the ZED SDK: GPU-accelerated spatial perception for stereo cameras</title><link>https://ramdi.fr/github-stars/inside-the-zed-sdk-gpu-accelerated-spatial-perception-for-stereo-cameras/</link><pubDate>Mon, 04 May 2026 10:23:02 +0000</pubDate><guid>https://ramdi.fr/github-stars/inside-the-zed-sdk-gpu-accelerated-spatial-perception-for-stereo-cameras/</guid><description>Explore the ZED SDK, a C++ library for real-time stereo vision, SLAM, and spatial mapping with GPU acceleration and zero-copy CUDA interoperability for edge robotics.</description></item><item><title>Super-LIO: A structured mapping LiDAR-Inertial Odometry system for faster real-time navigation</title><link>https://ramdi.fr/github-stars/super-lio-a-structured-mapping-lidar-inertial-odometry-system-for-faster-real-time-navigation/</link><pubDate>Mon, 04 May 2026 10:23:01 +0000</pubDate><guid>https://ramdi.fr/github-stars/super-lio-a-structured-mapping-lidar-inertial-odometry-system-for-faster-real-time-navigation/</guid><description>Super-LIO improves LiDAR-Inertial Odometry with a compact mapping strategy that speeds up correspondence search by 1.2-4x. It supports ROS1/2 and targets Livox Mid-360 sensors.</description></item></channel></rss>