1 citations · 1 across the 7 of their papers we have counts for
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Keep the Future, Drop the Rollout: RIFT for World Action Models
Chushan Zhang, Jinguang Tong, Xuesong Li +2
World action models (WAMs) condition robot actions on predicted futures, but iterative video rollout increases deployment latency. We ask whether action generation requires the evo…
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…
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…
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…
EMOS: Embodiment-aware Heterogeneous Multi-robot Operating System with LLM Agents
Junting Chen, Checheng Yu, Xunzhe Zhou +7
Heterogeneous multi-robot systems (HMRS) have emerged as a powerful approach for tackling complex tasks that single robots cannot manage alone. Current large-language-model-based m…