Adversarial Skill Learning for Robust Manipulation
Pingcheng Jian,Chao Yang,Di Guo,Huaping Liu,Fuchun Sun,Pingcheng Jian,Chao Yang,Di Guo,Huaping Liu,Fuchun Sun
Deep reinforcement learning has made significant progress in robotic manipulation tasks and it works well in the ideal disturbance-free environment. However, in a real-world environment, both internal and external disturbances are inevitable, thus the performance of the trained policy will dramatically drop. To improve the robustness of the policy, we introduce the adversarial training mechanism t...