Achieving precise manipulation with multi-fingered robotic hands

Determine effective approaches for achieving precise manipulation—defined as fingertip-scale, finely controlled motions and contacts that yield accurate object poses and delicate interactions—using multi-fingered robotic hands.

Background

The paper distinguishes power manipulation—where multi-fingered hands excel due to increased contact stability—from precise manipulation, which requires fingertip-scale control and accurate object poses. In practice, parallel grippers are more commonly used for precision tasks, underscoring a gap in capabilities for multi-fingered hands.

Within this context, the authors explicitly note that achieving precise manipulation with multi-fingered hands remains an open problem for the community, motivating their co-design approach that optimizes both control strategies and fingertip geometry to address this challenge.

References

How to achieve precise manipulation, especially with multi-fingered hands, is still an open problem for the community.

From Power to Precision: Learning Fine-grained Dexterity for Multi-fingered Robotic Hands  (2511.13710 - Ye et al., 17 Nov 2025) in Section 2: Related Work, Power to Precise Manipulation

It is an open question how to extend such rapid online learning techniques to handle grasping or finger gaiting motions.

Rapid Learning of Dexterous In-Hand Pen Writing through Real-Time Jacobian Estimation  (2609.11775 - Stewart et al., 10 Sep 2026) in Section 8, Discussion, subsection “Limitations.”