5 papers
Wasserstein Distributionally Robust Regret Optimization for Reinforcement Learning from Human Feedback
Yikai Wang, Shang Liu, Jose Blanchet
Reinforcement learning from human feedback (RLHF) is a central post-training tool for aligning large language models, but its training reward is only a learned proxy for true human…
HALO: Learning Human-Robot Collaboration via Heterogeneous-Agent Lyapunov Policy Optimization
Hao Zhang, Yaru Niu, Yikai Wang +2
To improve generalization and resilience in human-robot collaboration (HRC), robots must contend with diverse combinations of human behaviors and contexts, motivating multi-agent r…
APEX: Learning Adaptive High-Platform Traversal for Humanoid Robots
Yikai Wang, Tingxuan Leng, Changyi Lin +5
Humanoid locomotion has advanced rapidly with deep reinforcement learning (DRL), enabling robust feet-based traversal over uneven terrain. Yet platforms beyond leg length remain la…
LocoTouch: Learning Dynamic Quadrupedal Transport with Tactile Sensing
Changyi Lin, Yuxin Ray Song, Boda Huo +9
Quadrupedal robots have demonstrated remarkable agility and robustness in traversing complex terrains. However, they struggle with dynamic object interactions, where contact must b…
Human2LocoMan: Learning Versatile Quadrupedal Manipulation with Human Pretraining
Yaru Niu, Yunzhe Zhang, Mingyang Yu +11
Quadrupedal robots have demonstrated impressive locomotion capabilities in complex environments, but equipping them with autonomous versatile manipulation skills in a scalable way…