# In-Hand Cube Reconfiguration: Simplified

arXiv: https://arxiv.org/abs/2308.12178 · HTML: https://mlsanity.com/paper/2308.12178/

## Key facts

- Cited by 4 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 23 Aug 2023.

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

- [Lessons from Learning to Spin "Pens"](https://mlsanity.com/paper/2407.18902/) (2024)
- [Learning Dexterous Manipulation Skills from Imperfect Simulations](https://mlsanity.com/paper/2512.02011/) (2025)
- [Language Conditioned Multi-Finger Dexterous Manipulation Enabled by Physical Compliance and Switching of Controllers](https://mlsanity.com/paper/2410.14022/) (2024)
- [From Simple to Complex Skills: The Case of In-Hand Object Reorientation](https://mlsanity.com/paper/2501.05439/) (2025)

## Abstract (arXiv)

We present a simple approach to in-hand cube reconfiguration. By simplifying planning, control, and perception as much as possible, while maintaining robust and general performance, we gain insights into the inherent complexity of in-hand cube reconfiguration. We also demonstrate the effectiveness of combining GOFAI-based planning with the exploitation of environmental constraints and inherently compliant end-effectors in the context of dexterous manipulation. The proposed system outperforms a substantially more complex system for cube reconfiguration based on deep learning and accurate physical simulation, contributing arguments to the discussion about what the most promising approach to general manipulation might be. Project website: https://rbo.gitlab-pages.tu-berlin.de/robotics/simpleIHM/