10 papers
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…
Agile Flight Emerges from Multi-Agent Competitive Racing
Vineet Pasumarti, Lorenzo Bianchi, Antonio Loquercio
Through multi-agent competition and the sparse high-level objective of winning a race, we find that both agile flight (e.g., high-speed motion pushing the platform to its physical…