From Hardware and Data to Models: How Sharpa Systematically Advances Dexterous Manipulation

In a conversation with Synced, Sharpa's academic lead Zhang Kaifeng outlined three main threads for advancing dexterous manipulation: human-centered data collection, high-frequency tactile low-level control that decouples motion from interaction, and tactile-anchored cross-embodiment representation learning.