514 citations · 2.1k across the 35 of their papers we have counts for
6 papers · 1 filter
Learning Robot Policies from Sparse Success Signals via STL-Guided Stein Variational Policy Gradient
Hongrui Zheng, Cristian Ioan Vasile, Antonio Loquercio +1
Learning robot policies for tasks with sparse success signals is challenging when completion depends on coordinated actions, precise contact outcomes, or satisfying several conditi…
AI Coaching for Accelerating Human Skill Development with Reinforcement Learning
Wei Wang, Enlin Gu, Antonio Loquercio +2
AI copilots can substantially boost human performance through shared control, but excessive assistance can induce over-reliance and skill atrophy. This paper studies how an embodie…
RAVEN: Long-Horizon Reasoning & Navigation with a Visuo-Spatio-Temporal Memory
Yixun Hu, Zhicheng Zheng, Lihan Zha +5
Long-term robot deployment requires a compact and scalable memory that preserves fine-grained visual semantics, grounds observations in space and time, and enables efficient storag…
Reinforcement Learning for Flow-Matching Policies with Density Transport
Boshu Lei, Kostas Daniilidis, Antonio Loquercio
We present an online reinforcement learning (RL) algorithm for fine-tuning flow-matching policies in continuous-control problems. Our key insight is to view RL-based policy improve…
RoSHI: A Versatile Robot-oriented Suit for Human Data In-the-Wild
Wenjing Margaret Mao, Jefferson Ng, Luyang Hu +2
Scaling up robot learning will likely require human data containing rich and long-horizon interactions in the wild. Existing approaches for collecting such data trade off portabili…
Efficient and Reliable Teleoperation through Real-to-Sim-to-Real Shared Autonomy
Shuo Sha, Yixuan Wang, Binghao Huang +2
Fine-grained, contact-rich teleoperation remains slow, error-prone, and unreliable in real-world manipulation tasks, even for experienced operators. Shared autonomy offers a promis…