# A Wearable Robotic Hand for Hand-over-Hand Imitation Learning

arXiv: https://arxiv.org/abs/2309.14860 · HTML: https://mlsanity.com/paper/2309.14860/

## Key facts

- Cited by 4 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 26 Sep 2023.

## Built on by (most cited first, 4 of 4)

- [Mamba Policy: Towards Efficient 3D Diffusion Policy with Hybrid Selective State Models](https://mlsanity.com/paper/2409.07163/) (2024)
- [CIVIL: Causal and Intuitive Visual Imitation Learning](https://mlsanity.com/paper/2504.17959/) (2025)
- [Hand-in-the-Loop: Improving VLA Policies for Dexterous Manipulation via Seamless Hand-Arm Intervention](https://mlsanity.com/paper/2605.15157/) (2026)
- [Grasp Like Humans: Learning Generalizable Multi-Fingered Grasping from Human Proprioceptive Sensorimotor Integration](https://mlsanity.com/paper/2509.08354/) (2025)

## Abstract (arXiv)

Dexterous manipulation through imitation learning has gained significant attention in robotics research. The collection of high-quality expert data holds paramount importance when using imitation learning. The existing approaches for acquiring expert data commonly involve utilizing a data glove to capture hand motion information. However, this method suffers from limitations as the collected information cannot be directly mapped to the robotic hand due to discrepancies in their degrees of freedom or structures. Furthermore,it fails to accurately capture force feedback information between the hand and objects during the demonstration process. To overcome these challenges, this paper presents a novel solution in the form of a wearable dexterous hand, namely Hand-over-hand Imitation learning wearable RObotic Hand (HIRO Hand),which integrates expert data collection and enables the implementation of dexterous operations. This HIRO Hand empowers the operator to utilize their own tactile feedback to determine appropriate force, position, and actions, resulting in more accurate imitation of the expert's actions. We develop both non-learning and visual behavior cloning based controllers allowing HIRO Hand successfully achieves grasping and in-hand manipulation ability.