Reinforcement Learning Legged Robot
Spider-Bot is an innovative legged robot project that leverages reinforcement learning to achieve dynamic locomotion and navigation capabilities. The project focuses on developing a four-legged robot that can learn to walk, navigate obstacles, and adapt to different terrains through advanced machine learning algorithms.
The robot features a biologically-inspired design with four articulated legs, each equipped with multiple degrees of freedom. Using PyBullet physics engine for simulation and deep reinforcement learning techniques, the Spider-Bot learns complex locomotion patterns through trial and error, demonstrating remarkable adaptability and stability across various challenging environments.