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

TL;DR

This paper introduces F-TAC Hand, a biomimetic robotic hand with high-resolution tactile sensing covering most of its surface, enabling adaptive, human-like grasping in dynamic environments through a generative control algorithm.

Contribution

The paper presents a novel robotic hand with extensive high-resolution tactile sensing and a generative algorithm for human-like configurations, advancing tactile-enabled manipulation.

Findings

Outperforms non-tactile systems in complex tasks (p<0.0001)

Demonstrates robust grasping in real-world trials

Highlights the importance of tactile feedback in robotic intelligence

Abstract

Developing robotic hands that adapt to real-world dynamics remains a fundamental challenge in robotics and machine intelligence. Despite significant 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 (0.1mm 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 new perspectives on the relationship between physical sensing capabilities and intelligent behavior.