SOURCE-LINKED INTELLIGENCE
Embedding Physics Priors in Robot Learning: A Survey
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
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-09-15T16:53:06.000Z
First collected: 2026-09-23T21:42:15.362Z. This is not the publication date.