TestFlightX
@TestFlightX · Post #34682 · 11/21/2024, 02:47 PM
#D#ROS https://testflight.apple.com/join/cFKaKfro
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Source channel @githubtrending · Post #15340 · Dec 17
#python#gym#gym_environment#reinforcement_learning#reinforcement_learning_agent#reinforcement_learning_environments#rl_environment#rl_training NeMo Gym helps you build and run reinforcement‑learning training environments for large language models, letting you develop, test, and collect verified rollouts separately from the training loop and integrate with your preferred RL framework and model endpoints (OpenAI, vLLM, etc.). It includes ready resource servers, datasets, and patterns for multi‑step, multi‑turn, and tool‑using scenarios, runs on a typical dev machine (no GPU required), and is early-stage with evolving APIs and docs. Benefit: you can generate high‑quality, verifiable training data faster and plug it into existing training pipelines to improve model behavior. https://github.com/NVIDIA-NeMo/Gym
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@githubtrending · Post #15616 · 04/15/2026, 12:00 PM
#cplusplus#hap#mid_360#ros#ros2 Livox ROS Driver 2 connects your Livox LiDARs like HAP and Mid360 to ROS (Noetic) or ROS2 (Foxy/Humble/Jazzy) on matching Ubuntu versions. Clone the repo in a workspace/src folder, build Livox-SDK2, then run ./build.sh with your ROS version, and launch with roslaunch or ros2 launch files from launch_ROS1/ROS2 folders—edit JSON configs for IP, ports, frequency (up to 100Hz), and formats. This lets you quickly test and visualize point clouds in RViz for robotics development, saving time on setup and debugging. https://github.com/Livox-SDK/livox_ros_driver2
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@githubtrending · Post #14795 · 06/05/2025, 02:30 PM
#cplusplus#arducopter#ardupilot#arduplane#ardurover#ardusub#autopilot#auv#copter#drone#dronekit#mavlink#plane#robotics#ros#rov#rover#sub#uas#uav#ugv ArduPilot is a powerful and open-source autopilot system that can control many types of vehicles, including drones, planes, helicopters, and even submarines. It offers features like autonomous flight modes, programmable missions, and support for various sensors and communication systems. This system is highly reliable and customizable, making it beneficial for users who need advanced control over their vehicles. It also has a strong community and extensive documentation, which helps users learn and improve their projects. https://github.com/ArduPilot/ardupilot