Shypd.aiThe largest open index of AI toolsSERL is an AI Frameworks & Infra tool that provides a software suite for sample-efficient robotic reinforcement learning. It offers libraries, environment wrappers, and examples to train RL policies for robotic manipulation tasks.
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SERL (Software Suite for Sample-Efficient Robotic Reinforcement Learning) is a comprehensive toolkit designed to facilitate the training of RL policies for robotic manipulation. It includes a set of libraries, environment wrappers, and practical examples, enabling users to develop and deploy reinforcement learning solutions for robots. The suite is structured with an asynchronous actor and learner node architecture, allowing for parallel training and inference, with data exchange via agentlace. While providing tools for simulation with Franka robots, it also supports deployment on real Franka arms. SERL is currently being deprecated in favor of HIL-SERL, and users are encouraged to explore the new project for future developments.
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