most citedTrain Once, Get a Family: State-Adaptive Balances for Offline-to-Online Reinforcement Learning

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cs.RO2026

Grasp-Then-Plan with Failure Attribution: A Closed Two-Stage Framework for Precise and Generalizable Robotic Manipulation

Jiahao Xu, Peiyuan Wang, Hanzhuo Zhang +7

In robotic manipulation, the tight coupling between grasping and motion planning often obscures the true source of failure, leading to inefficient trial-and-error. To enable effici…

cs.RO2026

Swimming Under Constraints: A Safe Reinforcement Learning Framework for Quadrupedal Bio-Inspired Propulsion

Xinyu Cui, Fei Han, Hang Xu +9

Bio-inspired aquatic propulsion offers high thrust and maneuverability but is prone to destabilizing forces such as lift fluctuations, which are further amplified by six-degree-of-…