Arena-Rosnav/rosnav-rl
RosNav-RL is a modular DRL framework for ROS 2 with a pluggable architecture, allowing you to switch between RL backends like Stable-Baselines3 and DreamerV3 to accelerate research and deployment.
This project provides a research toolkit for developing and deploying robot navigation agents using reinforcement learning (RL) within the ROS 2 ecosystem. It takes robot sensor data and desired reward functions as input, and outputs trained agents that can issue movement commands (Twist messages) to navigate a robot. Robotics researchers and developers focused on autonomous navigation would find this particularly useful.
Use this if you are a robotics researcher or developer looking to quickly prototype, train, and deploy RL-based navigation policies for your ROS 2-enabled mobile robots, especially when experimenting with different RL algorithms or reward structures.
Not ideal if you are looking for a pre-trained, off-the-shelf navigation solution without needing to engage with reinforcement learning frameworks or customize policies.
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Python
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Last pushed
Mar 13, 2026
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