تقرير
Learning to Transfer In-Hand Manipulations Using a Greedy Shape Curriculum
| العنوان: | Learning to Transfer In-Hand Manipulations Using a Greedy Shape Curriculum |
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| المؤلفون: | Zhang, Yunbo, Clegg, Alexander, Ha, Sehoon, Turk, Greg, Ye, Yuting |
| سنة النشر: | 2023 |
| المجموعة: | Computer Science |
| مصطلحات موضوعية: | Computer Science - Computer Vision and Pattern Recognition, Computer Science - Graphics, Computer Science - Robotics |
| الوصف: | In-hand object manipulation is challenging to simulate due to complex contact dynamics, non-repetitive finger gaits, and the need to indirectly control unactuated objects. Further adapting a successful manipulation skill to new objects with different shapes and physical properties is a similarly challenging problem. In this work, we show that natural and robust in-hand manipulation of simple objects in a dynamic simulation can be learned from a high quality motion capture example via deep reinforcement learning with careful designs of the imitation learning problem. We apply our approach on both single-handed and two-handed dexterous manipulations of diverse object shapes and motions. We then demonstrate further adaptation of the example motion to a more complex shape through curriculum learning on intermediate shapes morphed between the source and target object. While a naive curriculum of progressive morphs often falls short, we propose a simple greedy curriculum search algorithm that can successfully apply to a range of objects such as a teapot, bunny, bottle, train, and elephant. Comment: Published as a conference paper at EuroGraphics 2023 |
| نوع الوثيقة: | Working Paper |
| URL الوصول: | http://arxiv.org/abs/2303.12726 |
| رقم الأكسشن: | edsarx.2303.12726 |
| قاعدة البيانات: | arXiv |
| الوصف غير متاح. |