Combining physics and deep learning to learn continuous-time dynamics models
Combining physics and deep learning to learn continuous-time dynamics models
Deep learning has been widely used within learning algorithms for robotics. One disadvantage of deep networks is that these networks are black-box representations. Therefore, the learned approximations ignore the existing knowledge of physics or robotics. Especially for learning dynamics models, these black-box models are not desirable as the underlying principles …