Legged Gym is an exciting framework for training legged robots using deep reinforcement learning (RL). Inspired by the paper Learning to Walk in Minutes Using Massively Parallel Deep Reinforcement Learning, Legged Gym provides a simpler and less complicated alternative to NVIDIA Isaac Lab. Although the maintainers have mentioned that updates might be limited due to NVIDIA Isaac Lab's initialization, I believe Legged Gym remains an excellent starting point for those looking to dive into RL for legged robots.

Why Legged Gym?

• Simplicity: Unlike Isaac Lab, Legged Gym is easier to set up and understand, making it ideal for newcomers.
• Performance: It leverages Isaac Gym's GPU-based simulation, enabling thousands of parallel environments for rapid training.
• Research-Backed: The framework is inspired by cutting-edge research in massively parallel deep reinforcement learning.
• Focus on Legged Robots: Pre-configured environments for robots like ANYmal and A1 simplify experiments in legged locomotion.