600 citations · 712 across the 15 of their papers we have counts for
15 papers
Robot Synesthesia: In-Hand Manipulation with Visuotactile Sensing
Ying Yuan, Haichuan Che, Yuzhe Qin +6
Executing contact-rich manipulation tasks necessitates the fusion of tactile and visual feedback. However, the distinct nature of these modalities poses significant challenges. In…
Pre-Trained Image Encoder for Generalizable Visual Reinforcement Learning
Zhecheng Yuan, Zhengrong Xue, Bo Yuan +4
Learning generalizable policies that can adapt to unseen environments remains challenging in visual Reinforcement Learning (RL). Existing approaches try to acquire a robust represe…
Phasic Self-Imitative Reduction for Sparse-Reward Goal-Conditioned Reinforcement Learning
Yunfei Li, Tian Gao, Jiaqi Yang +2
It has been a recent trend to leverage the power of supervised learning (SL) towards more effective reinforcement learning (RL) methods. We propose a novel phasic approach by alter…
Continuously Discovering Novel Strategies via Reward-Switching Policy Optimization
Zihan Zhou, Wei Fu, Bingliang Zhang +1
We present Reward-Switching Policy Optimization (RSPO), a paradigm to discover diverse strategies in complex RL environments by iteratively finding novel policies that are both loc…
Variational Automatic Curriculum Learning for Sparse-Reward Cooperative Multi-Agent Problems
Jiayu Chen, Yuanxin Zhang, Yuanfan Xu +5
We introduce a curriculum learning algorithm, Variational Automatic Curriculum Learning (VACL), for solving challenging goal-conditioned cooperative multi-agent reinforcement learn…
Learning Efficient Multi-Agent Cooperative Visual Exploration
Chao Yu, Xinyi Yang, Jiaxuan Gao +3
We tackle the problem of cooperative visual exploration where multiple agents need to jointly explore unseen regions as fast as possible based on visual signals. Classical planning…