Simulated Sound Sharpens Robot Skills

⊲ [arXiv] ⊳ The article presents “Multigen,” a framework that integrates generative models into physics-based simulators to enhance multimodal robot learning, particularly in tasks requiring audio feedback, such as pouring. It addresses challenges in simulating non-visual modalities by generating realistic audio to complement visual data, enabling effective training without real robot data. The multimodal training shows that including synthetic audio improves real-world performance compared to vision-only models, offering a practical path for sim-to-real learning using sound as a signal.
⊲ Image – DALL-E ⊳