PolyUMI: Accessible Visual-Tactile-Audio Data Collection for Object Inference
Overview
This paper presents PolyUMI, an open-source platform for scalable visual-tactile-audio demonstration collection and robot deployment. It features a lightweight, wireless handheld gripper that records synchronized sensory data. The paper also introduces VisTA, a token-level multimodal policy that integrates information across sensors and time to predict contact-aware robot actions. Experiments show that tactile and audio signals provide valuable task-relevant information beyond vision, and VisTA is competitive with or outperforms existing multimodal policies.
From arXiv Robotics — research abstracts
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- arXiv Robotics — research abstractsSignalPolyUMI: Accessible Visual-Tactile-Audio Data Collection for Object Inference and Manipulation
This paper presents PolyUMI, an open-source platform for scalable visual-tactile-audio demonstration collection and robot deployment. It features a lightweight, wireless handheld gripper that records synchronized sensory data. The paper also introduces VisTA, a token-level multimodal policy that integrates information across sensors and time to predict contact-aware robot actions. Experiments show that tactile and audio signals provide valuable task-relevant information beyond vision, and VisTA is competitive with or outperforms existing multimodal policies.
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