UniBYD: A Unified Framework for Learning Robotic Manipulation Across Embodiments Beyond Imitation of Human Demonstrations
UniBYD introduces a unified reinforcement learning framework that learns manipulation policies for various robotic hands by moving from imitation to online exploration. It uses a Unified Morphological Representation to handle different hand shapes consistently, paired with dynamic PPO and reward annealing to transition smoothly from following human demonstrations to discovering optimal physical behaviors.