Shypd.aiThe largest open index of AI toolsrl_sar is an Open Source Product & Industrial Design tool that provides a framework for simulation verification and physical deployment of robot reinforcement learning algorithms. It supports quadruped, wheeled, and humanoid robots, facilitating the transition from simulation to real-world applications.
Trending
About
rl_sar is an open-source framework designed for the simulation verification and physical deployment of robot reinforcement learning algorithms. It supports a variety of robot types, including quadruped, wheeled, and humanoid robots, making it versatile for different robotic applications. The tool integrates with popular simulation environments like IsaacGym, IsaacSim, Gazebo, and Mujoco, and supports both ROS-Noetic and ROS2-Foxy/Humble for robust robotic operating system compatibility. It also offers support for libtorch and onnxruntime, enabling flexible model deployment. Users can compile and run the framework on Linux and macOS (Mujoco simulation only), with options for hardware deployment without simulation. The project emphasizes the 'simulation and real' aspect, providing a comprehensive solution for developing and testing robot behaviors in both virtual and physical settings.
Capabilities
Pricing & Plans
Open Source
Free
FAQs
Trending
