Deep Reinforcement Learning for High Precision Assembly Tasks
文獻目錄 本篇論文的目的是控制機械臂在組件裝配精度高於機器人控制精度的情況下實現軸孔的裝配。本文使用雙層LSTM網絡結構來作爲狀態-行爲價值函數Q的近似，輸入爲機械臂的力-力矩傳感器反饋信號以及機械臂末端的近似位置，輸出爲機械臂末端三個軸上施加的力與兩個方向上姿態的旋轉角度。從演示視頻來看效果還是很不錯的。 該論文實驗中有一個前置條件：假設軸已經被抓且與孔板相接觸。那麼這篇論文其實就是分兩步走：一
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相關文章
- 1. PR17.10.2:Reproducibility of Benchmarked Deep Reinforcement Learning Tasks for Continuous Control
- 2. Deep Reinforcement Learning for Dialogue Generation
- 3. Deep Reinforcement Learning for Join Order Enumeration
- 4. Deep Reinforcement Learning for List-wise Recommendations
- 5. Deep Reinforcement Learning
- 6. Reinforcement learning and Deep learning
- 7. Building a ROS simulation platform for Deep Reinforcement Learning research ...
- 8. Relational Deep Reinforcement Learning
- 9. (轉) Deep Reinforcement Learning: Pong from Pixels
- 10. Playing Atari with Deep Reinforcement Learning