方向简介
探索传统控制与强化学习结合的边界,用数据与模型融合的方式使机器人策略更加鲁棒稳定
Paper List
- Jingtian Ji, Buqing Nie, Yue Gao,"DAGA: Dynamics Aware Reinforcement Learning with Graph-Based Rapid Adaptation", IEEE Robotics and Automation Letters (IEEE RA-L), 2023. (Corresponding Author)
- Yue Gao, Bo Su, Lei Jiang, Feng Gao, "Multi-legged Robots: Progress and Challenges", National Science Review, 2022.
- Hongjie Cai, Yue Gao, Manhua Liu, Graph Transformer Geometric Learning of Brain Networks Using Multimodal MR Images for Brain Age Estimation", IEEE Transactions on Medical Imaging, 2022. (Corresponding Author)
- Feng Gao, Shuo Li, Yue Gao, Chenkun Qi, Qiyan Tian, Guangzhong Yang, "Robots at the Beijing 2022 Winter Olympics", Science Robotics, 2022.
- Yangqing Fu, Ming Sun, Yue Gao, "Tightly Coupled Distributed Kalman Filter under Non-Gaussian Noises", Signal Processing, 2022.
- Yue Zhao, Yue Gao, Qiao Sun, "A real-time low-computation cost human-following framework in outdoor environment for legged robots", Robotics and Autonomous Systems (RAS), 2021.
- Ming Sun, Yue Gao, "GATER: Learning Grasp-Action-Target Embeddings and Relations for Task-Specific Grasping", IEEE Robotics and Automation Letters (RAL), 2021.
- Buqing Nie, Yue Gao, Yidong Mei, "Capability Iteration Network for Robot Path Planning", International Journal of Robotics and Automation (IJRA), 2021.
- Ming Sun, Yue Gao, Wei Liu, Shaoyuan Li, "Data-efficient Model-based Reinforcement Learning for Robot Control", International Journal of Robotics and Automation (IJRA), 2020.
- Yue Gao, Shimon Edelman, "Hedonic and Eudaimonic Well-being Based Reward for Intrinsic Motivated Reinforcement Learning Agents," Adaptive Behavior, 2016.
- Yue Gao, Shimon Edelman, "Between Pleasure and Contentment: Evolutionary Dynamics of Some Possible Parameters of Happiness," PLoS ONE, 2016.
- Yue Gao, Nitzany E, and Shimon. Edelman, "Online learning of causal structure in a dynamic game situation," Cognitive Science, 2012.
- Michael Coen, Yue Gao, "Learning from Games: Inductive Bias and Bayesian Inference," Cognitive Science, 2009.