2 papers
cs.RO2026
Failure-Aware RL: Reliable Offline-to-Online Reinforcement Learning with Self-Recovery for Real-World Manipulation
Huanyu Li, Kun Lei, Sheng Zang +5
Post-training algorithms based on deep reinforcement learning can push the limits of robotic models for specific objectives, such as generalizability, accuracy, and robustness. How…
cs.RO2025
RL-100: Performant Robotic Manipulation with Real-World Reinforcement Learning
Kun Lei, Huanyu Li, Dongjie Yu +6
Real-world robotic manipulation in homes and factories demands reliability, efficiency, and robustness that approach or surpass those of skilled human operators. We present RL-100,…