Embedding high-resolution touch across robotic hands enables adaptive human-like grasping

  • Zihang Zhao
  • , Wanlin Li
  • , Yuyang Li
  • , Tengyu Liu
  • , Boren Li
  • , Meng Wang
  • , Kai Du
  • , Hangxin Liu
  • , Yixin Zhu
  • , Qining Wang
  • , Kaspar Althoefer
  • , Song Chun Zhu

Research output: Contribution to journalArticlepeer-review

11 Scopus citations

Abstract

Developing robotic hands that adapt to real-world dynamics remains a fundamental challenge in robotics and machine intelligence. Despite notable advances in replicating human-hand kinematics and control algorithms, robotic systems still struggle to match human capabilities in dynamic environments, primarily due to inadequate tactile feedback. To bridge this gap, we present F-TAC Hand, a biomimetic hand featuring high-resolution tactile sensing (0.1-mm spatial resolution) across 70% of its surface area. Through optimized hand design, we overcome traditional challenges in integrating high-resolution tactile sensors while preserving the full range of motion. The hand, powered by our generative algorithm that synthesizes human-like hand configurations, demonstrates robust grasping capabilities in dynamic real-world conditions. Extensive evaluation across 600 real-world trials demonstrates that this tactile-embodied system significantly outperforms non-tactile-informed alternatives in complex manipulation tasks (P < 0.0001). These results provide empirical evidence for the critical role of rich tactile embodiment in developing advanced robotic intelligence, offering promising perspectives on the relationship between physical sensing capabilities and intelligent behaviour.

Original languageEnglish
Pages (from-to)889-900
Number of pages12
JournalNature Machine Intelligence
Volume7
Issue number6
DOIs
StatePublished - Jun 2025
Externally publishedYes

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