Motion Skill

Motion skill research focuses on enabling robots and virtual characters to learn and execute diverse movements, addressing challenges in control, adaptability, and generalization. Current efforts leverage techniques like reinforcement learning, imitation learning, and generative models (including transformers and variational autoencoders), often incorporating pre-trained vision models and synergistic action representations to improve efficiency and robustness. This work is crucial for advancing robotics, animation, and our understanding of motor control, with applications ranging from autonomous driving to physically realistic character animation and the development of more agile and adaptable robots.