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/

翻译：我们提出了一种简单的手部魔方重配置方法。通过尽可能简化规划、控制与感知环节，同时保持鲁棒且通用的性能，我们得以深入理解手部魔方重配置问题的内在复杂性。本研究还展示了将基于GOFAI的规划与环境约束利用、固有柔顺末端执行器相结合在灵巧操作中的有效性。所提出的系统在魔方重配置任务上超越了基于深度学习与精确物理仿真的显著更复杂的系统，为关于通用操作最有前景路径的讨论提供了论据。项目网站：https://rbo.gitlab-pages.tu-berlin.de/robotics/simpleIHM/