LATIDIA · Robótica

Incorporación de los conocimientos previos de física en el aprendizaje de robots: una encuesta

arXiv: 2609.22319v1Tipo de anuncio: nuevo Resumen: El rápido progreso de la inteligencia artificial está remodelando la robótica y acelerando la adopción de enfoques basados en el aprendizaje. Mientras que los métodos puramente basados en datos han logrado

La noticia

arXiv:2609.22319v1 Announce Type: new Abstract: The rapid progress of artificial intelligence is reshaping robotics and accelerating the adoption of learning-based approaches. While purely data-driven methods have achieved remarkable success in computer vision and natural language processing, robotics remains constrained by limited data, complex real-world interactions, and the need for reliable operation. These challenges have motivated the exploration of physics-embedded robot learning, which embeds physics priors into learning algorithms. By encoding the underlying physical laws and constraints, physics priors can complement limited data with robotics-specific inductive biases, potentially improving generalization, interpretability, and sample efficiency. However, the literature on physics-embedded robot learning remains fragmented across terminology, methodologies, and application domains, making it