GOATS: Goal Sampling Adaptation for Scooping with Curriculum Reinforcement Learning
Yaru Niu,Shiyu Jin,Zeqing Zhang,Jiacheng Zhu,Ding Zhao,Liangjun Zhang,Yaru Niu,Shiyu Jin,Zeqing Zhang,Jiacheng Zhu,Ding Zhao,Liangjun Zhang
In this work, we first formulate the problem of robotic water scooping using goal-conditioned reinforcement learning. This task is particularly challenging due to the complex dynamics of fluid and the need to achieve multi-modal goals. The policy is required to successfully reach both position goals and water amount goals, which leads to a large convoluted goal state space. To overcome these chall...